From d67515a998d9333d9a343240a609331e36f27c8d Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Wed, 9 Oct 2024 18:39:58 +0300 Subject: [PATCH 001/125] create shunt_characteristic_temp & trafo/trafo3w characteristic objects for voltage_ratio & angle_deg --- pandapower/build_branch.py | 6 +- pandapower/control/util/auxiliary.py | 10 +++- .../shunts/nonLinearShuntCompensatorCim16.py | 48 ++++++++++++++- .../transformers/powerTransformersCim16.py | 59 ++++++++++++------- .../transformers/tapController.py | 9 +-- .../control/test_tap_dependent_impedance.py | 1 + 6 files changed, 101 insertions(+), 32 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index f48cb2371..9f7b49c00 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -526,7 +526,7 @@ def _calc_y_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net_sn_mva): b_pu = b_mva / vnl_squared * baseZ * parallel / np.square(vn_trafo_lv / vn_lv_kv) return g_pu, b_pu - +# todo: add characteristics for tap percent and degree changes here def _calc_tap_from_dataframe(net, trafo_df): """ Adjust the nominal voltage vnh and vnl to the active tab position "tap_pos". @@ -604,6 +604,7 @@ def _replace_nan(array, value=0): return array +# todo create similar or expand/rename function to include voltage_ratio and angle_deg def _get_vk_values(trafo_df, characteristic, trafotype="2W"): if trafotype == "2W": vk_variables = ("vk_percent", "vkr_percent") @@ -665,6 +666,7 @@ def _get_vk_values(trafo_df, characteristic, trafotype="2W"): def _calc_tap_dependent_value(tap_pos, value, tap_dependent_impedance, characteristic, characteristic_idx): +# todo expand to include voltage_ratio & angle_deg or probably better to write own function # we skip the trafos with NaN characteristics even if tap_dependent_impedance is True (we already checked for missing characteristics) relevant_idx = tap_dependent_impedance & ~np.isnan(characteristic_idx) vk_characteristic = np.zeros_like(tap_dependent_impedance, dtype="object") @@ -681,7 +683,7 @@ def custom_func(f, t, c): def _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, sn_mva, sequence=1, characteristic=None, update_vk_values=True): """ - Calculates (Vectorized) the resitance and reactance according to the + Calculates (Vectorized) the resistance and reactance according to the transformer values """ parallel = get_trafo_values(trafo_df, "parallel") diff --git a/pandapower/control/util/auxiliary.py b/pandapower/control/util/auxiliary.py index 570c45012..d7a0eec91 100644 --- a/pandapower/control/util/auxiliary.py +++ b/pandapower/control/util/auxiliary.py @@ -214,9 +214,12 @@ def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_point # create characteristics for the specified variable and set their indices in the trafo table col = f"{variable}_characteristic" # check if the variable is a valid attribute of the trafo table - supported_columns = {"trafo": ["vk_percent_characteristic", "vkr_percent_characteristic"], - "trafo3w": [f"vk{r}_{side}_percent_characteristic" for side in ["hv", "mv", "lv"] for r in - ["", "r"]]} + supported_columns = {"trafo": ["voltage_ratio_characteristic", "angle_deg_characteristic", + "vk_percent_characteristic", "vkr_percent_characteristic"], + "trafo3w": ["voltage_ratio_characteristic", "angle_deg_characteristic", + "vkr_hv_percent_characteristic", "vkr_mv_percent_characteristic", + "vkr_lv_percent_characteristic", "vk_hv_percent_characteristic", + "vk_mv_percent_characteristic", "vk_lv_percent_characteristic"]} if col not in supported_columns[trafotable]: raise UserWarning("Variable %s is not supported for table %s" % (variable, trafotable)) @@ -230,6 +233,7 @@ def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_point if (len(x_points) != len(y_points)): raise UserWarning("The lengths of the points do not match!") + # todo change name of the flag to reflect expanded columns if 'tap_dependent_impedance' not in net[trafotable]: net[trafotable]['tap_dependent_impedance'] = Series(index=net[trafotable].index, dtype=np.bool_, data=False) diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py index e938dc08a..d113822df 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py @@ -23,6 +23,7 @@ def convert_nonlinear_shunt_compensator_cim16(self): self.logger.info("Start converting NonlinearShuntCompensator.") if self.cimConverter.cim['eq']['NonlinearShuntCompensator'].index.size > 0: eqssh_shunts = self._prepare_nonlinear_shunt_compensator_cim16() + self._create_shunt_characteristics(eqssh_shunts) self.cimConverter.copy_to_pp('shunt', eqssh_shunts) else: eqssh_shunts = pd.DataFrame(None) @@ -61,9 +62,50 @@ def _prepare_nonlinear_shunt_compensator_cim16(self) -> pd.DataFrame: eqssh_shunts = eqssh_shunts[eqssh_shunts_cols] if 'inService' in eqssh_shunts.columns: eqssh_shunts['connected'] = eqssh_shunts['connected'] & eqssh_shunts['inService'] + # added to use the logic of p/q values multiplied by the number of steps + # this is only correct for the current step values + # todo add characteristics for p & q per step per shunt - similar to trafos tap dependent impedance + eqssh_shunts['p'] = eqssh_shunts['p'] / eqssh_shunts['sections'] + eqssh_shunts['q'] = eqssh_shunts['q'] / eqssh_shunts['sections'] eqssh_shunts = eqssh_shunts.rename(columns={ 'rdfId': sc['o_id'], 'rdfId_Terminal': sc['t'], 'connected': 'in_service', 'index_bus': 'bus', - 'nomU': 'vn_kv', 'p': 'p_mw', 'q': 'q_mvar'}) - eqssh_shunts['step'] = 1 - eqssh_shunts['max_step'] = 1 + 'nomU': 'vn_kv', 'p': 'p_mw', 'q': 'q_mvar', 'sections': 'step', 'maximumSections': 'max_step'}) + # commented out - this way information on current and max step is not lost + # eqssh_shunts['step'] = 1 + # eqssh_shunts['max_step'] = 1 return eqssh_shunts + + def _create_shunt_characteristics(self, eqssh_shunts): + if 'id_characteristic' not in eqssh_shunts.columns: + eqssh_shunts['id_characteristic'] = np.NaN + if 'shunt_characteristic_temp' not in self.cimConverter.net.keys(): + self.cimConverter.net['shunt_characteristic_temp'] = pd.DataFrame( + columns=['id_characteristic', 'step', 'q_mvar', 'p_mw']) + char_temp = eqssh_shunts.drop(columns=['p_mw', 'q_mvar', 'step']) + char_temp['p'] = float('NaN') + char_temp['q'] = float('NaN') + # get the NonlinearShuntCompensatorPoints + nscp = self.cimConverter.cim['eq']['NonlinearShuntCompensatorPoint'][ + ['NonlinearShuntCompensator', 'sectionNumber', 'b', 'g']].rename( + columns={'NonlinearShuntCompensator': 'origin_id'}) + char_temp = pd.merge(char_temp, nscp, how='left', on='origin_id') + # calculate p & q from b & g for all sections + y = char_temp['g'] + char_temp['b'] * 1j + s = char_temp['vn_kv'] ** 2 * np.conj(y) + char_temp['p_temp'] = s.values.real + char_temp['q_temp'] = s.values.imag + # calculate cumulative sums for all sections + char_temp = char_temp.sort_values(by=['origin_id', 'sectionNumber']) + char_temp['p'] = char_temp.groupby('origin_id')['p_temp'].cumsum() + char_temp['q'] = char_temp.groupby('origin_id')['q_temp'].cumsum() + char_temp = char_temp.rename(columns={'p': 'p_mw', 'q': 'q_mvar', 'sectionNumber': 'step'}) + char_temp['step'] = char_temp['step'].astype(int) + # assign id_characteristic + char_temp['id_characteristic'] = pd.factorize(char_temp['origin_id'])[0] + + # set the id_characteristic at the corresponding shunt + id_char_dict = char_temp.drop_duplicates('origin_id').set_index('origin_id')['id_characteristic'].to_dict() + eqssh_shunts['id_characteristic'] = eqssh_shunts['origin_id'].map(id_char_dict) + + self.cimConverter.net['shunt_characteristic_temp'] = \ + char_temp[['id_characteristic', 'step', 'q_mvar', 'p_mw']] diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index 205d6f218..da0806a21 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -59,24 +59,25 @@ def _create_trafo_characteristics(self, trafo_type, trafo_df_origin): trafo_df_origin['id_characteristic'] = np.nan if 'characteristic_temp' not in self.cimConverter.net.keys(): self.cimConverter.net['characteristic_temp'] = pd.DataFrame( - columns=['id_characteristic', 'step', 'vk_percent', + columns=['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent', 'vkr_hv_percent', 'vkr_mv_percent', 'vkr_lv_percent', 'vk_hv_percent', 'vk_mv_percent', 'vk_lv_percent']) # get the TablePoints ptct = self.cimConverter.cim['eq']['PhaseTapChangerTabular'][['TransformerEnd', 'PhaseTapChangerTable']] ptct = pd.merge(ptct, self.cimConverter.cim['eq']['PhaseTapChangerTablePoint'][ - ['PhaseTapChangerTable', 'step', 'r', 'x']], how='left', on='PhaseTapChangerTable') - # append the ratio tab changers + ['PhaseTapChangerTable', 'step', 'r', 'x', 'ratio', 'angle']], how='left', on='PhaseTapChangerTable') + # append the ratio tap changers ptct_ratio = self.cimConverter.cim['eq']['RatioTapChanger'][['TransformerEnd', 'RatioTapChangerTable']] ptct_ratio = pd.merge(ptct_ratio, self.cimConverter.cim['eq']['RatioTapChangerTablePoint'][ - ['RatioTapChangerTable', 'step', 'r', 'x']], how='left', on='RatioTapChangerTable') + ['RatioTapChangerTable', 'step', 'r', 'x', 'ratio']], how='left', on='RatioTapChangerTable') ptct = pd.concat([ptct, ptct_ratio], ignore_index=True, sort=False) - ptct = ptct.rename(columns={'step': 'tabular_step', 'r': 'r_dev', 'x': 'x_dev', 'TransformerEnd': sc['pte_id']}) + ptct.rename(columns={'step': 'tabular_step', 'r': 'r_dev', 'x': 'x_dev', 'TransformerEnd': sc['pte_id'], + 'ratio': 'ratio_dev', 'angle': 'angle_dev'}, inplace=True) ptct = ptct.drop(columns=['PhaseTapChangerTable']) if trafo_type == 'trafo': trafo_df = trafo_df_origin.sort_values(['PowerTransformer', 'endNumber']).reset_index() - # precessing the transformer data + # processing the transformer data # a list of transformer parameters which are used for each transformer winding copy_list = ['ratedU', 'r', 'x', sc['pte_id'], 'neutralStep', 'lowStep', 'highStep', 'step'] for one_item in copy_list: @@ -95,7 +96,8 @@ def _create_trafo_characteristics(self, trafo_type, trafo_df_origin): # merge the trafos with the tap changers trafo_df = pd.merge(trafo_df, ptct, how='left', on=sc['pte_id']) trafo_df = pd.merge(trafo_df, ptct.rename(columns={'tabular_step': 'tabular_step_lv', 'r_dev': 'r_dev_lv', - 'x_dev': 'x_dev_lv', + 'x_dev': 'x_dev_lv', 'ratio_dev': 'ratio_dev_lv', + 'angle_dev': 'angle_dev_lv', sc['pte_id']: sc['pte_id'] + '_lv'}), how='left', on=sc['pte_id'] + '_lv') fillna_list = ['tabular_step'] @@ -118,6 +120,12 @@ def _create_trafo_characteristics(self, trafo_type, trafo_df_origin): trafo_df['r_lv'] = trafo_df['r_lv'] * (1 + trafo_df['r_dev_lv'] / 100) trafo_df['x'] = trafo_df['x'] + trafo_df['x'] * trafo_df['x_dev'] / 100 trafo_df['x_lv'] = trafo_df['x_lv'] * (1 + trafo_df['x_dev_lv'] / 100) + fillna_list = ['ratio_dev', 'angle_dev'] + for one_item in fillna_list: + trafo_df[one_item] = trafo_df[one_item].fillna(trafo_df[one_item + '_lv']) + trafo_df['ratio_dev'] = trafo_df['ratio_dev'].fillna(1.00000) + trafo_df['angle_dev'] = trafo_df['angle_dev'].fillna(0) + trafo_df.rename(columns={'ratio_dev': 'voltage_ratio', 'angle_dev': 'angle_deg'}, inplace=True) # calculate vkr_percent and vk_percent trafo_df['vkr_percent'] = \ @@ -129,7 +137,8 @@ def _create_trafo_characteristics(self, trafo_type, trafo_df_origin): (abs(trafo_df.r_lv) ** 2 + abs(trafo_df.x_lv) ** 2) ** 0.5 * \ (trafo_df.ratedS * 1e3) / (10. * trafo_df.ratedU_lv ** 2) trafo_df['tabular_step'] = trafo_df['tabular_step'].astype(int) - append_dict = dict({'id_characteristic': [], 'step': [], 'vk_percent': [], 'vkr_percent': []}) + append_dict = dict({'id_characteristic': [], 'step': [], 'voltage_ratio': [], 'angle_deg': [], + 'vk_percent': [], 'vkr_percent': []}) else: trafo_df = trafo_df_origin.copy() trafo_df = trafo_df.sort_values(['PowerTransformer', 'endNumber']).reset_index() @@ -156,19 +165,18 @@ def _create_trafo_characteristics(self, trafo_type, trafo_df_origin): trafo_df = pd.concat([pd.merge(trafo_df, ptct, how='left', on=sc['pte_id']), pd.merge(trafo_df, ptct.rename(columns={'tabular_step': 'tabular_step_mv', 'r_dev': 'r_dev_mv', - 'x_dev': 'x_dev_mv', + 'x_dev': 'x_dev_mv', 'ratio_dev': 'ratio_dev_mv', + 'angle_dev': 'angle_dev_mv', sc['pte_id']: sc['pte_id'] + '_mv'}), how='left', on=sc['pte_id'] + '_mv'), pd.merge(trafo_df, ptct.rename(columns={'tabular_step': 'tabular_step_lv', 'r_dev': 'r_dev_lv', - 'x_dev': 'x_dev_lv', + 'x_dev': 'x_dev_lv', 'ratio_dev': 'ratio_dev_lv', + 'angle_dev': 'angle_dev_lv', sc['pte_id']: sc['pte_id'] + '_lv'}), how='left', on=sc['pte_id'] + '_lv') ], ignore_index=True, sort=False) - # remove elements with mor than one tap changer per trafo - trafo_df = trafo_df.loc[(~trafo_df.duplicated(subset=['PowerTransformer', 'tabular_step'], keep=False)) | ( - ~trafo_df.RatioTapChangerTable.isna())] - # remove elements with mor than one tap changer per trafo + # remove elements with more than one tap changer per trafo trafo_df = trafo_df.loc[(~trafo_df.duplicated(subset=['PowerTransformer', 'tabular_step'], keep=False)) | ( ~trafo_df.RatioTapChangerTable.isna())] fillna_list = ['tabular_step'] @@ -180,6 +188,14 @@ def _create_trafo_characteristics(self, trafo_type, trafo_df_origin): fillna_list = ['r_dev', 'r_dev_mv', 'r_dev_lv', 'x_dev', 'x_dev_mv', 'x_dev_lv'] for one_item in fillna_list: trafo_df[one_item] = trafo_df[one_item].fillna(0) + fillna_list = ['ratio_dev', 'angle_dev'] + for one_item in fillna_list: + trafo_df[one_item] = trafo_df[one_item].fillna(trafo_df[one_item + '_mv']) + trafo_df[one_item] = trafo_df[one_item].fillna(trafo_df[one_item + '_lv']) + trafo_df['ratio_dev'] = trafo_df['ratio_dev'].fillna(1.00000) + trafo_df['angle_dev'] = trafo_df['angle_dev'].fillna(0) + trafo_df.rename(columns={'ratio_dev': 'voltage_ratio', 'angle_dev': 'angle_deg'}, inplace=True) + # calculate vkr_percent and vk_percent trafo_df['r'] = trafo_df['r'] * (1 + trafo_df['r_dev'] / 100) trafo_df['r_mv'] = trafo_df['r_mv'] * (1 + trafo_df['r_dev_mv'] / 100) @@ -218,14 +234,15 @@ def _create_trafo_characteristics(self, trafo_type, trafo_df_origin): trafo_df.ratedU_lv / trafo_df.ratedU) ** 2) ** 2) ** 0.5 * \ trafo_df.min_s_lvhv * 100 / trafo_df.ratedU_lv ** 2 trafo_df['tabular_step'] = trafo_df['tabular_step'].astype(int) - append_dict = dict({'id_characteristic': [], 'step': [], 'vkr_hv_percent': [], 'vkr_mv_percent': [], - 'vkr_lv_percent': [], 'vk_hv_percent': [], 'vk_mv_percent': [], 'vk_lv_percent': []}) + append_dict = dict({'id_characteristic': [], 'step': [], 'voltage_ratio': [], 'angle_deg': [], + 'vkr_hv_percent': [], 'vkr_mv_percent': [], 'vkr_lv_percent': [], 'vk_hv_percent': [], + 'vk_mv_percent': [], 'vk_lv_percent': []}) def append_row(res_dict, id_c, row, cols): res_dict['id_characteristic'].append(id_c) res_dict['step'].append(row.tabular_step) - for variable in ['vkr_percent', 'vk_percent', 'vk_hv_percent', 'vkr_hv_percent', 'vk_mv_percent', - 'vkr_mv_percent', 'vk_lv_percent', 'vkr_lv_percent']: + for variable in ['voltage_ratio', 'angle_deg', 'vkr_percent', 'vk_percent', 'vk_hv_percent', + 'vkr_hv_percent', 'vk_mv_percent', 'vkr_mv_percent', 'vk_lv_percent', 'vkr_lv_percent']: if variable in cols: res_dict[variable].append(getattr(row, variable)) @@ -257,7 +274,8 @@ def append_row(res_dict, id_c, row, cols): self.cimConverter.net['characteristic_temp'] = pd.concat( [self.cimConverter.net['characteristic_temp'], pd.DataFrame(append_dict)], ignore_index=True, sort=False) - self.cimConverter.net['characteristic_temp']['step'] = self.cimConverter.net['characteristic_temp']['step'].astype(int) + self.cimConverter.net['characteristic_temp']['step'] = \ + self.cimConverter.net['characteristic_temp']['step'].astype(int) def _prepare_power_transformers_cim16(self) -> pd.DataFrame: if 'sc' in self.cimConverter.cim.keys(): @@ -329,6 +347,7 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: one_df = one_df.set_index('step') neutral_step = one_df['neutralStep'].iloc[0] ptct = ptct.drop(drop_index) + # todo change to populate tap_step_percent & tap_step_degree based on neutral tap_pos? # ptct.loc[keep_index, 'angle'] = # one_df.loc[current_step, 'angle'] / max(1, abs(current_step - neutral_step)) ptct.loc[keep_index, 'angle'] = one_df.loc[current_step, 'angle'] # todo fix if pp supports them @@ -491,7 +510,7 @@ def _prepare_trafos_cim16(self, power_trafo2w: pd.DataFrame) -> pd.DataFrame: power_trafo2w['shift_degree'] = power_trafo2w['phaseAngleClock'].astype(float).fillna( power_trafo2w['phaseAngleClock_lv'].astype(float)) * 30 power_trafo2w['parallel'] = 1 - power_trafo2w['tap_phase_shifter'] = False + power_trafo2w['tap_phase_shifter'] = False # todo remove hardcoded False flag to enable angle regulation power_trafo2w['in_service'] = power_trafo2w.connected & power_trafo2w.connected_lv power_trafo2w['connectionKind'] = power_trafo2w['connectionKind'].fillna('') power_trafo2w['connectionKind_lv'] = power_trafo2w['connectionKind_lv'].fillna('') diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py index a940d5d44..6b92c0619 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py @@ -28,7 +28,8 @@ def create_tap_controller_for_power_transformers(self): self.logger.info("Creating the tap dependent impedance characteristic objects for 2w-trafos.") # create the characteristic objects for transformers characteristic_df_temp = \ - self.cimConverter.net['characteristic_temp'][['id_characteristic', 'step', 'vk_percent', 'vkr_percent']] + self.cimConverter.net['characteristic_temp'][ + ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent']] for trafo_id, trafo_row in self.cimConverter.net.trafo.dropna(subset=['id_characteristic']).iterrows(): characteristic_df = characteristic_df_temp.loc[ characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic']] @@ -44,7 +45,7 @@ def create_tap_controller_for_power_transformers(self): # create the characteristic objects for transformers characteristic_df_temp = \ self.cimConverter.net['characteristic_temp'][ - ['id_characteristic', 'step', 'vkr_hv_percent', 'vkr_mv_percent', + ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vkr_hv_percent', 'vkr_mv_percent', 'vkr_lv_percent', 'vk_hv_percent', 'vk_mv_percent', 'vk_lv_percent']] for trafo_id, trafo_row in self.cimConverter.net.trafo3w.dropna(subset=['id_characteristic']).iterrows(): characteristic_df = characteristic_df_temp.loc[ @@ -56,8 +57,8 @@ def create_tap_controller_for_power_transformers(self): def _create_characteristic_object(self, net, trafo_type: str, trafo_id: List, characteristic_df: pd.DataFrame): self.logger.info("Adding characteristic object for trafo_type: %s and trafo_id: %s" % (trafo_type, trafo_id)) - for variable in ['vkr_percent', 'vk_percent', 'vk_hv_percent', 'vkr_hv_percent', 'vk_mv_percent', - 'vkr_mv_percent', 'vk_lv_percent', 'vkr_lv_percent']: + for variable in ['voltage_ratio', 'angle_deg', 'vkr_percent', 'vk_percent', 'vk_hv_percent', 'vkr_hv_percent', + 'vk_mv_percent', 'vkr_mv_percent', 'vk_lv_percent', 'vkr_lv_percent']: if variable in characteristic_df.columns: pandapower.control.create_trafo_characteristics(net, trafo_type, trafo_id, variable, [characteristic_df['step'].to_list()], diff --git a/pandapower/test/control/test_tap_dependent_impedance.py b/pandapower/test/control/test_tap_dependent_impedance.py index a6af15ce2..1833dd26c 100644 --- a/pandapower/test/control/test_tap_dependent_impedance.py +++ b/pandapower/test/control/test_tap_dependent_impedance.py @@ -12,6 +12,7 @@ trafo_characteristics_diagnostic +# todo add tests for voltage_ratio and angle_dev? def test_tap_dependent_impedance_control(): net = pp.create_empty_network() b1 = pp.create_bus(net, 110) From de0b2b322c8dee030e933e52b56463e169cc647b Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Wed, 30 Oct 2024 14:59:20 +0200 Subject: [PATCH 002/125] create shunt spline characteristics --- pandapower/control/util/auxiliary.py | 39 ++++++++++++++++++- pandapower/control/util/characteristic.py | 10 ++--- .../shunts/nonLinearShuntCompensatorCim16.py | 22 +++++++++-- .../transformers/tapController.py | 10 ++--- pandapower/converter/cim/cim_tools.py | 2 +- 5 files changed, 68 insertions(+), 15 deletions(-) diff --git a/pandapower/control/util/auxiliary.py b/pandapower/control/util/auxiliary.py index d7a0eec91..beaf819cb 100644 --- a/pandapower/control/util/auxiliary.py +++ b/pandapower/control/util/auxiliary.py @@ -233,7 +233,6 @@ def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_point if (len(x_points) != len(y_points)): raise UserWarning("The lengths of the points do not match!") - # todo change name of the flag to reflect expanded columns if 'tap_dependent_impedance' not in net[trafotable]: net[trafotable]['tap_dependent_impedance'] = Series(index=net[trafotable].index, dtype=np.bool_, data=False) @@ -252,3 +251,41 @@ def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_point # create the characteristic and set its index in the trafotable s = SplineCharacteristic(net, x_p, y_p) net[trafotable].at[tid, col] = s.index + +# todo merge create_trafo_characteristics and create_shunt_characteristics? +def create_shunt_characteristics(net, shunt_index, variable, x_points, y_points): + # create characteristics for the specified variable and set their indices in the shunt table + col = f"{variable}_characteristic" + # check if the variable is a valid attribute of the shunt table + supported_columns = ["q_mvar_characteristic", "p_mw_characteristic"] + if col not in supported_columns: + raise UserWarning("Variable %s is not supported for table shunt" % variable) + + # check inputs, check if 1 shunt or multiple, verify shape of x_points and y_points and shunt_index + if hasattr(shunt_index, '__iter__'): + single_mode = False + if not (len(shunt_index) == len(x_points) == len(y_points)): + raise UserWarning("The lengths of the shunt index and points do not match!") + else: + single_mode = True + if len(x_points) != len(y_points): + raise UserWarning("The lengths of the points do not match!") + + if 'step_dependent_power' not in net["shunt"]: + net["shunt"]["step_dependent_power"] = Series(index=net["shunt"].index, dtype=np.bool_, data=False) + + if col not in net["shunt"]: + net["shunt"][col] = Series(index=net["shunt"].index, dtype="Int64") + + # set the flag for the shunt table + net["shunt"].loc[shunt_index, "step_dependent_power"] = True + + if single_mode: + zip_params = zip([shunt_index], [x_points], [y_points]) + else: + zip_params = zip(shunt_index, x_points, y_points) + + for tid, x_p, y_p in zip_params: + # create the characteristic and set its index in the shunt table + s = SplineCharacteristic(net, x_p, y_p, table="shunt_characteristic") + net["shunt"].at[tid, col] = s.index diff --git a/pandapower/control/util/characteristic.py b/pandapower/control/util/characteristic.py index 9ca60afef..9e9deb376 100644 --- a/pandapower/control/util/characteristic.py +++ b/pandapower/control/util/characteristic.py @@ -74,11 +74,11 @@ class Characteristic(JSONSerializableClass): >>> c.satisfies(x=2.5, measured=3.1, epsilon=0.1) False """ - def __init__(self, net, x_values, y_values, **kwargs): + def __init__(self, net, x_values, y_values, table="characteristic", **kwargs): super().__init__() self.x_vals = x_values self.y_vals = y_values - self.index = super().add_to_net(net, "characteristic") + self.index = super().add_to_net(net, table) # @property # def x_vals(self): @@ -162,8 +162,8 @@ class SplineCharacteristic(Characteristic): """ json_excludes = ["self", "__class__", "_interpolator"] - def __init__(self, net, x_values, y_values, interpolator_kind="interp1d", **kwargs): - super().__init__(net, x_values=x_values, y_values=y_values) + def __init__(self, net, x_values, y_values, interpolator_kind="interp1d", table="characteristic", **kwargs): + super().__init__(net, x_values=x_values, y_values=y_values, table=table) self.kwargs = kwargs self.interpolator_kind = interpolator_kind @@ -172,7 +172,7 @@ def interpolator(self): """ We need to store the interpolator in a property because we need to serialize the characteristic. Instead of storing the serialized interpolator, we store the - x_values and y_values (the attribute _interpolator is ecluded from serialization by + x_values and y_values (the attribute _interpolator is excluded from serialization by adding it to json_excludes). For it to work, we need to recreate the interpolator on demand. As soon as the characteristic is called, if the interpolator is there, we can use it. If not, we recreate it. diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py index d113822df..84ebcba61 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py @@ -4,6 +4,7 @@ import pandas as pd import numpy as np +from pandapower.control.util import auxiliary from pandapower.converter.cim import cim_tools from pandapower.converter.cim.cim2pp import build_pp_net from pandapower.converter.cim.other_classes import Report, LogLevel, ReportCode @@ -25,6 +26,7 @@ def convert_nonlinear_shunt_compensator_cim16(self): eqssh_shunts = self._prepare_nonlinear_shunt_compensator_cim16() self._create_shunt_characteristics(eqssh_shunts) self.cimConverter.copy_to_pp('shunt', eqssh_shunts) + self._create_shunt_characteristic_object(net=self.cimConverter.net) else: eqssh_shunts = pd.DataFrame(None) self.logger.info("Created %s shunts in %ss." % (eqssh_shunts.index.size, time.time() - time_start)) @@ -64,7 +66,6 @@ def _prepare_nonlinear_shunt_compensator_cim16(self) -> pd.DataFrame: eqssh_shunts['connected'] = eqssh_shunts['connected'] & eqssh_shunts['inService'] # added to use the logic of p/q values multiplied by the number of steps # this is only correct for the current step values - # todo add characteristics for p & q per step per shunt - similar to trafos tap dependent impedance eqssh_shunts['p'] = eqssh_shunts['p'] / eqssh_shunts['sections'] eqssh_shunts['q'] = eqssh_shunts['q'] / eqssh_shunts['sections'] eqssh_shunts = eqssh_shunts.rename(columns={ @@ -77,7 +78,7 @@ def _prepare_nonlinear_shunt_compensator_cim16(self) -> pd.DataFrame: def _create_shunt_characteristics(self, eqssh_shunts): if 'id_characteristic' not in eqssh_shunts.columns: - eqssh_shunts['id_characteristic'] = np.NaN + eqssh_shunts['id_characteristic'] = np.nan if 'shunt_characteristic_temp' not in self.cimConverter.net.keys(): self.cimConverter.net['shunt_characteristic_temp'] = pd.DataFrame( columns=['id_characteristic', 'step', 'q_mvar', 'p_mw']) @@ -105,7 +106,22 @@ def _create_shunt_characteristics(self, eqssh_shunts): # set the id_characteristic at the corresponding shunt id_char_dict = char_temp.drop_duplicates('origin_id').set_index('origin_id')['id_characteristic'].to_dict() - eqssh_shunts['id_characteristic'] = eqssh_shunts['origin_id'].map(id_char_dict) + eqssh_shunts['id_characteristic'] = eqssh_shunts['origin_id'].map(id_char_dict).astype(int) + # populate shunt_characteristic_temp table self.cimConverter.net['shunt_characteristic_temp'] = \ char_temp[['id_characteristic', 'step', 'q_mvar', 'p_mw']] + + def _create_shunt_characteristic_object(self, net): + if self.cimConverter.net['shunt_characteristic_temp'].index.size > 0: + self.logger.info("Creating the step dependent power characteristic objects for shunts.") + characteristic_df_temp = self.cimConverter.net['shunt_characteristic_temp'] + for shunt_id, shunt_row in self.cimConverter.net.shunt.dropna(subset=['id_characteristic']).iterrows(): + shunt_characteristic_df = characteristic_df_temp.loc[ + characteristic_df_temp['id_characteristic'] == shunt_row['id_characteristic']] + for variable in ['q_mvar', 'p_mw']: + if variable in shunt_characteristic_df.columns: + auxiliary.create_shunt_characteristics( + net, [shunt_id], variable, [shunt_characteristic_df['step'].to_list()], + [shunt_characteristic_df[variable].to_list()] + ) diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py index 6b92c0619..c66f22511 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py @@ -33,8 +33,8 @@ def create_tap_controller_for_power_transformers(self): for trafo_id, trafo_row in self.cimConverter.net.trafo.dropna(subset=['id_characteristic']).iterrows(): characteristic_df = characteristic_df_temp.loc[ characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic']] - self._create_characteristic_object(net=self.cimConverter.net, trafo_type='trafo', trafo_id=[trafo_id], - characteristic_df=characteristic_df) + self._create_trafo_characteristic_object(net=self.cimConverter.net, trafo_type='trafo', + trafo_id=[trafo_id], characteristic_df=characteristic_df) self.logger.info(f"Finished creating tap dependent impedance characteristic objects for 2w-trafos in " f"{time.time() - time_start}.") if self.cimConverter.power_trafo3w.index.size > 0: @@ -50,12 +50,12 @@ def create_tap_controller_for_power_transformers(self): for trafo_id, trafo_row in self.cimConverter.net.trafo3w.dropna(subset=['id_characteristic']).iterrows(): characteristic_df = characteristic_df_temp.loc[ characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic']] - self._create_characteristic_object(net=self.cimConverter.net, trafo_type='trafo3w', trafo_id=[trafo_id], - characteristic_df=characteristic_df) + self._create_trafo_characteristic_object(net=self.cimConverter.net, trafo_type='trafo3w', + trafo_id=[trafo_id], characteristic_df=characteristic_df) self.logger.info(f"Finished creating tap dependent impedance characteristic objects for 3w-trafos in " f"{time.time() - time_start}.") - def _create_characteristic_object(self, net, trafo_type: str, trafo_id: List, characteristic_df: pd.DataFrame): + def _create_trafo_characteristic_object(self, net, trafo_type: str, trafo_id: List, characteristic_df: pd.DataFrame): self.logger.info("Adding characteristic object for trafo_type: %s and trafo_id: %s" % (trafo_type, trafo_id)) for variable in ['voltage_ratio', 'angle_deg', 'vkr_percent', 'vk_percent', 'vk_hv_percent', 'vkr_hv_percent', 'vk_mv_percent', 'vkr_mv_percent', 'vk_lv_percent', 'vkr_lv_percent']: diff --git a/pandapower/converter/cim/cim_tools.py b/pandapower/converter/cim/cim_tools.py index 9668b2387..3ab342086 100644 --- a/pandapower/converter/cim/cim_tools.py +++ b/pandapower/converter/cim/cim_tools.py @@ -72,7 +72,7 @@ def extend_pp_net_cim(net: pandapowerNet, override: bool = True) -> pandapowerNe fill_dict['storage'] = dict() fill_dict['storage'][np_str_type] = [sc['t'], 'description'] fill_dict['shunt'] = dict() - fill_dict['shunt'][np_str_type] = [sc['t'], 'description'] + fill_dict['shunt'][np_str_type] = [sc['t'], 'description', 'id_characteristic'] fill_dict['ward'] = dict() fill_dict['ward'][np_str_type] = [sc['t'], 'description'] fill_dict['xward'] = dict() From 8e780cc0c64942f15474c681fb041c8f4a1fc0d0 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 14 Nov 2024 13:01:19 +0200 Subject: [PATCH 003/125] parameter re-naming --- pandapower/control/util/auxiliary.py | 16 ++++++------ .../shunts/nonLinearShuntCompensatorCim16.py | 25 +++++++++--------- .../transformers/powerTransformersCim16.py | 26 +++++++++---------- .../transformers/tapController.py | 22 +++++++++------- pandapower/converter/cim/cim_tools.py | 6 ++--- 5 files changed, 49 insertions(+), 46 deletions(-) diff --git a/pandapower/control/util/auxiliary.py b/pandapower/control/util/auxiliary.py index beaf819cb..4647f275e 100644 --- a/pandapower/control/util/auxiliary.py +++ b/pandapower/control/util/auxiliary.py @@ -233,14 +233,14 @@ def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_point if (len(x_points) != len(y_points)): raise UserWarning("The lengths of the points do not match!") - if 'tap_dependent_impedance' not in net[trafotable]: - net[trafotable]['tap_dependent_impedance'] = Series(index=net[trafotable].index, dtype=np.bool_, data=False) + if 'tap_characteristic_table' not in net[trafotable]: + net[trafotable]['tap_characteristic_table'] = Series(index=net[trafotable].index, dtype=np.bool_, data=False) if col not in net[trafotable]: net[trafotable][col] = Series(index=net[trafotable].index, dtype="Int64") # set the flag for the trafo table - net[trafotable].loc[trafo_index, 'tap_dependent_impedance'] = True + net[trafotable].loc[trafo_index, 'tap_characteristic_table'] = True if single_mode: zip_params = zip([trafo_index], [x_points], [y_points]) @@ -249,7 +249,7 @@ def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_point for tid, x_p, y_p in zip_params: # create the characteristic and set its index in the trafotable - s = SplineCharacteristic(net, x_p, y_p) + s = SplineCharacteristic(net, x_p, y_p, table="trafo_characteristic_spline") net[trafotable].at[tid, col] = s.index # todo merge create_trafo_characteristics and create_shunt_characteristics? @@ -271,14 +271,14 @@ def create_shunt_characteristics(net, shunt_index, variable, x_points, y_points) if len(x_points) != len(y_points): raise UserWarning("The lengths of the points do not match!") - if 'step_dependent_power' not in net["shunt"]: - net["shunt"]["step_dependent_power"] = Series(index=net["shunt"].index, dtype=np.bool_, data=False) + if 'step_characteristic_table' not in net["shunt"]: + net["shunt"]["step_characteristic_table"] = Series(index=net["shunt"].index, dtype=np.bool_, data=False) if col not in net["shunt"]: net["shunt"][col] = Series(index=net["shunt"].index, dtype="Int64") # set the flag for the shunt table - net["shunt"].loc[shunt_index, "step_dependent_power"] = True + net["shunt"].loc[shunt_index, "step_characteristic_table"] = True if single_mode: zip_params = zip([shunt_index], [x_points], [y_points]) @@ -287,5 +287,5 @@ def create_shunt_characteristics(net, shunt_index, variable, x_points, y_points) for tid, x_p, y_p in zip_params: # create the characteristic and set its index in the shunt table - s = SplineCharacteristic(net, x_p, y_p, table="shunt_characteristic") + s = SplineCharacteristic(net, x_p, y_p, table="shunt_characteristic_spline") net["shunt"].at[tid, col] = s.index diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py index 84ebcba61..3779d58de 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py @@ -24,7 +24,7 @@ def convert_nonlinear_shunt_compensator_cim16(self): self.logger.info("Start converting NonlinearShuntCompensator.") if self.cimConverter.cim['eq']['NonlinearShuntCompensator'].index.size > 0: eqssh_shunts = self._prepare_nonlinear_shunt_compensator_cim16() - self._create_shunt_characteristics(eqssh_shunts) + self._create_shunt_characteristic_table(eqssh_shunts) self.cimConverter.copy_to_pp('shunt', eqssh_shunts) self._create_shunt_characteristic_object(net=self.cimConverter.net) else: @@ -76,11 +76,11 @@ def _prepare_nonlinear_shunt_compensator_cim16(self) -> pd.DataFrame: # eqssh_shunts['max_step'] = 1 return eqssh_shunts - def _create_shunt_characteristics(self, eqssh_shunts): - if 'id_characteristic' not in eqssh_shunts.columns: - eqssh_shunts['id_characteristic'] = np.nan - if 'shunt_characteristic_temp' not in self.cimConverter.net.keys(): - self.cimConverter.net['shunt_characteristic_temp'] = pd.DataFrame( + def _create_shunt_characteristic_table(self, eqssh_shunts): + if 'id_characteristic_table' not in eqssh_shunts.columns: + eqssh_shunts['id_characteristic_table'] = np.nan + if 'shunt_characteristic_table' not in self.cimConverter.net.keys(): + self.cimConverter.net['shunt_characteristic_table'] = pd.DataFrame( columns=['id_characteristic', 'step', 'q_mvar', 'p_mw']) char_temp = eqssh_shunts.drop(columns=['p_mw', 'q_mvar', 'step']) char_temp['p'] = float('NaN') @@ -106,19 +106,20 @@ def _create_shunt_characteristics(self, eqssh_shunts): # set the id_characteristic at the corresponding shunt id_char_dict = char_temp.drop_duplicates('origin_id').set_index('origin_id')['id_characteristic'].to_dict() - eqssh_shunts['id_characteristic'] = eqssh_shunts['origin_id'].map(id_char_dict).astype(int) + eqssh_shunts['id_characteristic_table'] = eqssh_shunts['origin_id'].map(id_char_dict).astype(int) # populate shunt_characteristic_temp table - self.cimConverter.net['shunt_characteristic_temp'] = \ + self.cimConverter.net['shunt_characteristic_table'] = \ char_temp[['id_characteristic', 'step', 'q_mvar', 'p_mw']] def _create_shunt_characteristic_object(self, net): - if self.cimConverter.net['shunt_characteristic_temp'].index.size > 0: + if self.cimConverter.net['shunt_characteristic_table'].index.size > 0: self.logger.info("Creating the step dependent power characteristic objects for shunts.") - characteristic_df_temp = self.cimConverter.net['shunt_characteristic_temp'] - for shunt_id, shunt_row in self.cimConverter.net.shunt.dropna(subset=['id_characteristic']).iterrows(): + characteristic_df_temp = self.cimConverter.net['shunt_characteristic_table'] + for shunt_id, shunt_row in self.cimConverter.net.shunt.dropna( + subset=['id_characteristic_table']).iterrows(): shunt_characteristic_df = characteristic_df_temp.loc[ - characteristic_df_temp['id_characteristic'] == shunt_row['id_characteristic']] + characteristic_df_temp['id_characteristic'] == shunt_row['id_characteristic_table']] for variable in ['q_mvar', 'p_mw']: if variable in shunt_characteristic_df.columns: auxiliary.create_shunt_characteristics( diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index da0806a21..caa2e3946 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -35,14 +35,14 @@ def convert_power_transformers_cim16(self): if power_trafo2w.index.size > 0: # process the two winding transformers - self._create_trafo_characteristics('trafo', power_trafo2w) + self._create_trafo_characteristic_table('trafo', power_trafo2w) power_trafo2w = self._prepare_trafos_cim16(power_trafo2w) self.cimConverter.copy_to_pp('trafo', power_trafo2w) self.cimConverter.power_trafo2w = power_trafo2w if power_trafo3w.index.size > 0: # process the three winding transformers - self._create_trafo_characteristics('trafo3w', power_trafo3w) + self._create_trafo_characteristic_table('trafo3w', power_trafo3w) power_trafo3w = self._prepare_trafo3w_cim16(power_trafo3w) self.cimConverter.copy_to_pp('trafo3w', power_trafo3w) self.cimConverter.power_trafo3w = power_trafo3w @@ -54,11 +54,11 @@ def convert_power_transformers_cim16(self): message="Created %s 2w trafos and %s 3w trafos from PowerTransformers in %ss." % (power_trafo2w.index.size, power_trafo3w.index.size, time.time() - time_start))) - def _create_trafo_characteristics(self, trafo_type, trafo_df_origin): - if 'id_characteristic' not in trafo_df_origin.columns: - trafo_df_origin['id_characteristic'] = np.nan - if 'characteristic_temp' not in self.cimConverter.net.keys(): - self.cimConverter.net['characteristic_temp'] = pd.DataFrame( + def _create_trafo_characteristic_table(self, trafo_type, trafo_df_origin): + if 'id_characteristic_table' not in trafo_df_origin.columns: + trafo_df_origin['id_characteristic_table'] = np.nan + if 'trafo_characteristic_table' not in self.cimConverter.net.keys(): + self.cimConverter.net['trafo_characteristic_table'] = pd.DataFrame( columns=['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent', 'vkr_hv_percent', 'vkr_mv_percent', 'vkr_lv_percent', 'vk_hv_percent', 'vk_mv_percent', @@ -246,7 +246,7 @@ def append_row(res_dict, id_c, row, cols): if variable in cols: res_dict[variable].append(getattr(row, variable)) - id_characteristic = self.cimConverter.net['characteristic_temp']['id_characteristic'].max() + 1 + id_characteristic = self.cimConverter.net['trafo_characteristic_table']['id_characteristic'].max() + 1 if math.isnan(id_characteristic): id_characteristic = 0 for one_id, one_df in trafo_df.groupby(sc['pte_id']): @@ -256,7 +256,7 @@ def append_row(res_dict, id_c, row, cols): # set the ID at the corresponding transformer trafo_df_origin.loc[trafo_df_origin['PowerTransformer'] == trafo_df_origin.loc[ trafo_df_origin[sc['pte_id']] == one_id, 'PowerTransformer'].values[ - 0], 'id_characteristic'] = id_characteristic + 0], 'id_characteristic_table'] = id_characteristic # iterate over the rows and get the desired data for one_row in one_df.itertuples(): # to add only selected characteristic data instead of all available data, disable the next line and @@ -271,11 +271,11 @@ def append_row(res_dict, id_c, row, cols): # elif one_row.tabular_step == one_row.step and one_row.step != one_row.highStep \ # and one_row.step != one_row.lowStep and one_row.step != one_row.neutralStep: # append_row(append_dict, id_characteristic, one_row, one_df.columns) - self.cimConverter.net['characteristic_temp'] = pd.concat( - [self.cimConverter.net['characteristic_temp'], pd.DataFrame(append_dict)], + self.cimConverter.net['trafo_characteristic_table'] = pd.concat( + [self.cimConverter.net['trafo_characteristic_table'], pd.DataFrame(append_dict)], ignore_index=True, sort=False) - self.cimConverter.net['characteristic_temp']['step'] = \ - self.cimConverter.net['characteristic_temp']['step'].astype(int) + self.cimConverter.net['trafo_characteristic_table']['step'] = \ + self.cimConverter.net['trafo_characteristic_table']['step'].astype(int) def _prepare_power_transformers_cim16(self) -> pd.DataFrame: if 'sc' in self.cimConverter.cim.keys(): diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py index c66f22511..339fd3da9 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py @@ -25,34 +25,36 @@ def create_tap_controller_for_power_transformers(self): # create transformer tap controller self._create_tap_controller(self.cimConverter.power_trafo2w, 'trafo') time_start = time.time() - self.logger.info("Creating the tap dependent impedance characteristic objects for 2w-trafos.") + self.logger.info("Creating the tap dependent characteristic objects for 2w-trafos.") # create the characteristic objects for transformers characteristic_df_temp = \ - self.cimConverter.net['characteristic_temp'][ + self.cimConverter.net['trafo_characteristic_table'][ ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent']] - for trafo_id, trafo_row in self.cimConverter.net.trafo.dropna(subset=['id_characteristic']).iterrows(): + for trafo_id, trafo_row in self.cimConverter.net.trafo.dropna( + subset=['id_characteristic_table']).iterrows(): characteristic_df = characteristic_df_temp.loc[ - characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic']] + characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic_table']] self._create_trafo_characteristic_object(net=self.cimConverter.net, trafo_type='trafo', trafo_id=[trafo_id], characteristic_df=characteristic_df) - self.logger.info(f"Finished creating tap dependent impedance characteristic objects for 2w-trafos in " + self.logger.info(f"Finished creating tap dependent characteristic objects for 2w-trafos in " f"{time.time() - time_start}.") if self.cimConverter.power_trafo3w.index.size > 0: # create transformer tap controller self._create_tap_controller(self.cimConverter.power_trafo3w, 'trafo3w') time_start = time.time() - self.logger.info("Creating the tap dependent impedance characteristic objects for 3w-trafos.") + self.logger.info("Creating the tap dependent characteristic objects for 3w-trafos.") # create the characteristic objects for transformers characteristic_df_temp = \ - self.cimConverter.net['characteristic_temp'][ + self.cimConverter.net['trafo_characteristic_table'][ ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vkr_hv_percent', 'vkr_mv_percent', 'vkr_lv_percent', 'vk_hv_percent', 'vk_mv_percent', 'vk_lv_percent']] - for trafo_id, trafo_row in self.cimConverter.net.trafo3w.dropna(subset=['id_characteristic']).iterrows(): + for trafo_id, trafo_row in self.cimConverter.net.trafo3w.dropna( + subset=['id_characteristic_table']).iterrows(): characteristic_df = characteristic_df_temp.loc[ - characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic']] + characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic_table']] self._create_trafo_characteristic_object(net=self.cimConverter.net, trafo_type='trafo3w', trafo_id=[trafo_id], characteristic_df=characteristic_df) - self.logger.info(f"Finished creating tap dependent impedance characteristic objects for 3w-trafos in " + self.logger.info(f"Finished creating tap dependent characteristic objects for 3w-trafos in " f"{time.time() - time_start}.") def _create_trafo_characteristic_object(self, net, trafo_type: str, trafo_id: List, characteristic_df: pd.DataFrame): diff --git a/pandapower/converter/cim/cim_tools.py b/pandapower/converter/cim/cim_tools.py index 3ab342086..24c9cd827 100644 --- a/pandapower/converter/cim/cim_tools.py +++ b/pandapower/converter/cim/cim_tools.py @@ -72,7 +72,7 @@ def extend_pp_net_cim(net: pandapowerNet, override: bool = True) -> pandapowerNe fill_dict['storage'] = dict() fill_dict['storage'][np_str_type] = [sc['t'], 'description'] fill_dict['shunt'] = dict() - fill_dict['shunt'][np_str_type] = [sc['t'], 'description', 'id_characteristic'] + fill_dict['shunt'][np_str_type] = [sc['t'], 'description', 'id_characteristic_table'] fill_dict['ward'] = dict() fill_dict['ward'][np_str_type] = [sc['t'], 'description'] fill_dict['xward'] = dict() @@ -95,14 +95,14 @@ def extend_pp_net_cim(net: pandapowerNet, override: bool = True) -> pandapowerNe fill_dict['trafo'] = dict() fill_dict['trafo'][np_str_type] = [sc['t_hv'], sc['t_lv'], sc['pte_id_hv'], sc['pte_id_lv'], sc['tc'], sc['tc_id'], - 'description', 'vector_group', 'id_characteristic'] + 'description', 'vector_group', 'id_characteristic_table'] fill_dict['trafo'][np_float_type] = ['vk0_percent', 'vkr0_percent', 'xn_ohm'] fill_dict['trafo'][np_bool_type] = ['power_station_unit', 'oltc'] fill_dict['trafo3w'] = dict() fill_dict['trafo3w'][np_str_type] = [sc['t_hv'], sc['t_mv'], sc['t_lv'], sc['pte_id_hv'], sc['pte_id_mv'], sc['pte_id_lv'], sc['tc'], sc['tc_id'], 'description', 'vector_group', - 'id_characteristic'] + 'id_characteristic_table'] fill_dict['trafo3w'][np_float_type] = ['vk0_hv_percent', 'vk0_mv_percent', 'vk0_lv_percent', 'vkr0_hv_percent', 'vkr0_mv_percent', 'vkr0_lv_percent'] fill_dict['trafo3w'][np_bool_type] = ['power_station_unit'] From ada4320a7985649532ada42393a6ad59fdbefaaa Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 15 Nov 2024 12:25:25 +0200 Subject: [PATCH 004/125] move 'tap_characteristic_table' and 'shunt_characteristic_table' flags into the converter; move trafo & shunt spline characteristic creation out of the converter (old code commented) --- pandapower/control/util/auxiliary.py | 84 +++++++++++++++++-- .../shunts/linearShuntCompensatorCim16.py | 3 + .../shunts/nonLinearShuntCompensatorCim16.py | 39 +++++---- .../shunts/staticVarCompensatorCim16.py | 4 + .../transformers/powerTransformersCim16.py | 9 ++ .../transformers/tapController.py | 78 +++++++++-------- pandapower/converter/cim/cim_tools.py | 7 +- 7 files changed, 159 insertions(+), 65 deletions(-) diff --git a/pandapower/control/util/auxiliary.py b/pandapower/control/util/auxiliary.py index 4647f275e..c430b6eb4 100644 --- a/pandapower/control/util/auxiliary.py +++ b/pandapower/control/util/auxiliary.py @@ -3,6 +3,7 @@ # Copyright (c) 2016-2024 by University of Kassel and Fraunhofer Institute for Energy Economics # and Energy System Technology (IEE), Kassel. All rights reserved. import sys +import time import numpy as np from pandas import Index, Series @@ -210,6 +211,49 @@ def plot_characteristic(characteristic, start, stop, num=20, xlabel=None, ylabel plt.ylabel(ylabel) +def create_trafo_characteristic_object(net): + if (net['trafo_characteristic_table'].index.size > 0 and + net['trafo_characteristic_table']['vk_percent'].notna().any()): + time_start = time.time() + logger.info("Creating tap dependent characteristic objects for 2w-trafos.") + characteristic_df_temp = net['trafo_characteristic_table'][ + ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent']] + for trafo_id, trafo_row in net.trafo.dropna(subset=['id_characteristic_table']).iterrows(): + characteristic_df = characteristic_df_temp.loc[ + characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic_table']] + logger.info("Adding characteristic object for 2w-trafo with trafo_id: %s" % trafo_id) + for variable in ['voltage_ratio', 'angle_deg', 'vkr_percent', 'vk_percent']: + if variable in characteristic_df.columns: + create_trafo_characteristics(net, "trafo", [trafo_id], variable, + [characteristic_df['step'].to_list()], + [characteristic_df[variable].to_list()]) + logger.info(f"Finished creating tap dependent characteristic objects for 2w-trafos in " + f"{time.time() - time_start}.") + else: + logger.info("trafo_characteristic_table has no values for 2w-trafos - no characteristic objects created.") + if (net['trafo_characteristic_table'].index.size > 0 and + net['trafo_characteristic_table']['vkr_hv_percent'].notna().any()): + time_start = time.time() + logger.info("Creating tap dependent characteristic objects for 3w-trafos.") + characteristic_df_temp = net['trafo_characteristic_table'][ + ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vkr_hv_percent', 'vkr_mv_percent', + 'vkr_lv_percent', 'vk_hv_percent', 'vk_mv_percent', 'vk_lv_percent']] + for trafo_id, trafo_row in net.trafo3w.dropna(subset=['id_characteristic_table']).iterrows(): + characteristic_df = characteristic_df_temp.loc[ + characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic_table']] + logger.info("Adding characteristic object for 2w-trafo with trafo_id: %s" % trafo_id) + for variable in ['voltage_ratio', 'angle_deg', 'vk_hv_percent', 'vkr_hv_percent', 'vk_mv_percent', + 'vkr_mv_percent', 'vk_lv_percent', 'vkr_lv_percent']: + if variable in characteristic_df.columns: + create_trafo_characteristics(net, "trafo3w", [trafo_id], variable, + [characteristic_df['step'].to_list()], + [characteristic_df[variable].to_list()]) + logger.info(f"Finished creating tap dependent characteristic objects for 3w-trafos in " + f"{time.time() - time_start}.") + else: + logger.info("trafo_characteristic_table has no values for 3w-trafos - no characteristic objects created.") + + def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_points, y_points): # create characteristics for the specified variable and set their indices in the trafo table col = f"{variable}_characteristic" @@ -233,14 +277,14 @@ def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_point if (len(x_points) != len(y_points)): raise UserWarning("The lengths of the points do not match!") - if 'tap_characteristic_table' not in net[trafotable]: - net[trafotable]['tap_characteristic_table'] = Series(index=net[trafotable].index, dtype=np.bool_, data=False) - if col not in net[trafotable]: net[trafotable][col] = Series(index=net[trafotable].index, dtype="Int64") - # set the flag for the trafo table - net[trafotable].loc[trafo_index, 'tap_characteristic_table'] = True + # moved into converter + # if 'tap_characteristic_table' not in net[trafotable]: + # net[trafotable]['tap_characteristic_table'] = Series(index=net[trafotable].index, dtype=np.bool_, data=False) + # # set the flag for the trafo table + # net[trafotable].loc[trafo_index, 'tap_characteristic_table'] = True if single_mode: zip_params = zip([trafo_index], [x_points], [y_points]) @@ -252,6 +296,28 @@ def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_point s = SplineCharacteristic(net, x_p, y_p, table="trafo_characteristic_spline") net[trafotable].at[tid, col] = s.index + +def create_shunt_characteristic_object(net): + if net['shunt_characteristic_table'].index.size > 0: + time_start = time.time() + logger.info("Creating step dependent power characteristic objects for shunts.") + characteristic_df_temp = net['shunt_characteristic_table'] + for shunt_id, shunt_row in net.shunt.dropna(subset=['id_characteristic_table']).iterrows(): + shunt_characteristic_df = characteristic_df_temp.loc[ + characteristic_df_temp['id_characteristic'] == shunt_row['id_characteristic_table']] + logger.info("Adding characteristic object for shunt with shunt_id: %s" % shunt_id) + for variable in ['q_mvar', 'p_mw']: + if variable in shunt_characteristic_df.columns: + create_shunt_characteristics( + net, [shunt_id], variable, [shunt_characteristic_df['step'].to_list()], + [shunt_characteristic_df[variable].to_list()] + ) + logger.info(f"Finished creating step dependent power characteristic objects for shunts in" + f"{time.time() - time_start}.") + else: + logger.info("shunt_characteristic_table is empty - no characteristic objects created.") + + # todo merge create_trafo_characteristics and create_shunt_characteristics? def create_shunt_characteristics(net, shunt_index, variable, x_points, y_points): # create characteristics for the specified variable and set their indices in the shunt table @@ -271,14 +337,14 @@ def create_shunt_characteristics(net, shunt_index, variable, x_points, y_points) if len(x_points) != len(y_points): raise UserWarning("The lengths of the points do not match!") - if 'step_characteristic_table' not in net["shunt"]: - net["shunt"]["step_characteristic_table"] = Series(index=net["shunt"].index, dtype=np.bool_, data=False) - if col not in net["shunt"]: net["shunt"][col] = Series(index=net["shunt"].index, dtype="Int64") + # moved into converter + # if 'step_characteristic_table' not in net["shunt"]: + # net["shunt"]["step_characteristic_table"] = Series(index=net["shunt"].index, dtype=np.bool_, data=False) # set the flag for the shunt table - net["shunt"].loc[shunt_index, "step_characteristic_table"] = True + # net["shunt"].loc[shunt_index, "step_characteristic_table"] = True if single_mode: zip_params = zip([shunt_index], [x_points], [y_points]) diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/linearShuntCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/linearShuntCompensatorCim16.py index 39406ecbc..55bf4af4d 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/linearShuntCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/linearShuntCompensatorCim16.py @@ -41,4 +41,7 @@ def _prepare_linear_shunt_compensator_cim16(self) -> pd.DataFrame: s = eqssh_shunts['vn_kv'] ** 2 * np.conj(y) eqssh_shunts['p_mw'] = s.values.real eqssh_shunts['q_mvar'] = s.values.imag + # create step_characteristic_table flag + if 'step_characteristic_table' not in eqssh_shunts.columns: + eqssh_shunts["step_characteristic_table"] = pd.Series(index=eqssh_shunts.index, dtype=np.bool_, data=False) return eqssh_shunts diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py index 3779d58de..0ddae0661 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py @@ -4,7 +4,7 @@ import pandas as pd import numpy as np -from pandapower.control.util import auxiliary +# from pandapower.control.util import auxiliary from pandapower.converter.cim import cim_tools from pandapower.converter.cim.cim2pp import build_pp_net from pandapower.converter.cim.other_classes import Report, LogLevel, ReportCode @@ -26,7 +26,7 @@ def convert_nonlinear_shunt_compensator_cim16(self): eqssh_shunts = self._prepare_nonlinear_shunt_compensator_cim16() self._create_shunt_characteristic_table(eqssh_shunts) self.cimConverter.copy_to_pp('shunt', eqssh_shunts) - self._create_shunt_characteristic_object(net=self.cimConverter.net) + # self._create_shunt_characteristic_object(net=self.cimConverter.net) # moved out of converter else: eqssh_shunts = pd.DataFrame(None) self.logger.info("Created %s shunts in %ss." % (eqssh_shunts.index.size, time.time() - time_start)) @@ -108,21 +108,28 @@ def _create_shunt_characteristic_table(self, eqssh_shunts): id_char_dict = char_temp.drop_duplicates('origin_id').set_index('origin_id')['id_characteristic'].to_dict() eqssh_shunts['id_characteristic_table'] = eqssh_shunts['origin_id'].map(id_char_dict).astype(int) + # create step_characteristic_table flag + if 'step_characteristic_table' not in eqssh_shunts.columns: + eqssh_shunts["step_characteristic_table"] = pd.Series(index=eqssh_shunts.index, dtype=np.bool_, data=False) + # set step_characteristic_table as True for all non-linear shunt compensators + eqssh_shunts.loc[eqssh_shunts['id_characteristic_table'].notna(), 'step_characteristic_table'] = True + # populate shunt_characteristic_temp table self.cimConverter.net['shunt_characteristic_table'] = \ char_temp[['id_characteristic', 'step', 'q_mvar', 'p_mw']] - def _create_shunt_characteristic_object(self, net): - if self.cimConverter.net['shunt_characteristic_table'].index.size > 0: - self.logger.info("Creating the step dependent power characteristic objects for shunts.") - characteristic_df_temp = self.cimConverter.net['shunt_characteristic_table'] - for shunt_id, shunt_row in self.cimConverter.net.shunt.dropna( - subset=['id_characteristic_table']).iterrows(): - shunt_characteristic_df = characteristic_df_temp.loc[ - characteristic_df_temp['id_characteristic'] == shunt_row['id_characteristic_table']] - for variable in ['q_mvar', 'p_mw']: - if variable in shunt_characteristic_df.columns: - auxiliary.create_shunt_characteristics( - net, [shunt_id], variable, [shunt_characteristic_df['step'].to_list()], - [shunt_characteristic_df[variable].to_list()] - ) + # moved out of converter + # def _create_shunt_characteristic_object(self, net): + # if self.cimConverter.net['shunt_characteristic_table'].index.size > 0: + # self.logger.info("Creating the step dependent power characteristic objects for shunts.") + # characteristic_df_temp = self.cimConverter.net['shunt_characteristic_table'] + # for shunt_id, shunt_row in self.cimConverter.net.shunt.dropna( + # subset=['id_characteristic_table']).iterrows(): + # shunt_characteristic_df = characteristic_df_temp.loc[ + # characteristic_df_temp['id_characteristic'] == shunt_row['id_characteristic_table']] + # for variable in ['q_mvar', 'p_mw']: + # if variable in shunt_characteristic_df.columns: + # auxiliary.create_shunt_characteristics( + # net, [shunt_id], variable, [shunt_characteristic_df['step'].to_list()], + # [shunt_characteristic_df[variable].to_list()] + # ) diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py index 0db967655..ced1de626 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py @@ -2,6 +2,7 @@ import time import pandas as pd +import numpy as np from pandapower.converter.cim import cim_tools from pandapower.converter.cim.cim2pp import build_pp_net @@ -42,4 +43,7 @@ def _prepare_static_var_compensator_cim16(self) -> pd.DataFrame: 'voltageSetPoint': 'vn_kv', 'index_bus': 'bus', 'connected': 'in_service'}) eq_stat_coms['step'] = 1 eq_stat_coms['max_step'] = 1 + # create step_characteristic_table flag + if 'step_characteristic_table' not in eq_stat_coms.columns: + eq_stat_coms["step_characteristic_table"] = pd.Series(index=eq_stat_coms.index, dtype=np.bool_, data=False) return eq_stat_coms diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index caa2e3946..2e2aa7d98 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -271,6 +271,15 @@ def append_row(res_dict, id_c, row, cols): # elif one_row.tabular_step == one_row.step and one_row.step != one_row.highStep \ # and one_row.step != one_row.lowStep and one_row.step != one_row.neutralStep: # append_row(append_dict, id_characteristic, one_row, one_df.columns) + + # create tap_characteristic_table flag + if 'tap_characteristic_table' not in trafo_df_origin.columns: + trafo_df_origin['tap_characteristic_table'] = pd.Series( + index=trafo_df_origin.index, dtype=np.bool_, data=False + ) + # set tap_characteristic_table as True for all non-linear shunt compensators + trafo_df_origin.loc[trafo_df_origin['id_characteristic_table'].notna(), 'tap_characteristic_table'] = True + self.cimConverter.net['trafo_characteristic_table'] = pd.concat( [self.cimConverter.net['trafo_characteristic_table'], pd.DataFrame(append_dict)], ignore_index=True, sort=False) diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py index 339fd3da9..bb0c423ad 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py @@ -24,47 +24,51 @@ def create_tap_controller_for_power_transformers(self): if self.cimConverter.power_trafo2w.index.size > 0: # create transformer tap controller self._create_tap_controller(self.cimConverter.power_trafo2w, 'trafo') - time_start = time.time() - self.logger.info("Creating the tap dependent characteristic objects for 2w-trafos.") - # create the characteristic objects for transformers - characteristic_df_temp = \ - self.cimConverter.net['trafo_characteristic_table'][ - ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent']] - for trafo_id, trafo_row in self.cimConverter.net.trafo.dropna( - subset=['id_characteristic_table']).iterrows(): - characteristic_df = characteristic_df_temp.loc[ - characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic_table']] - self._create_trafo_characteristic_object(net=self.cimConverter.net, trafo_type='trafo', - trafo_id=[trafo_id], characteristic_df=characteristic_df) - self.logger.info(f"Finished creating tap dependent characteristic objects for 2w-trafos in " - f"{time.time() - time_start}.") + # moved out of converter + # time_start = time.time() + # self.logger.info("Creating the tap dependent characteristic objects for 2w-trafos.") + # # create the characteristic objects for transformers + # characteristic_df_temp = \ + # self.cimConverter.net['trafo_characteristic_table'][ + # ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent']] + # for trafo_id, trafo_row in self.cimConverter.net.trafo.dropna( + # subset=['id_characteristic_table']).iterrows(): + # characteristic_df = characteristic_df_temp.loc[ + # characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic_table']] + # self._create_trafo_characteristic_object(net=self.cimConverter.net, trafo_type='trafo', + # trafo_id=[trafo_id], characteristic_df=characteristic_df) + # self.logger.info(f"Finished creating tap dependent characteristic objects for 2w-trafos in " + # f"{time.time() - time_start}.") if self.cimConverter.power_trafo3w.index.size > 0: # create transformer tap controller self._create_tap_controller(self.cimConverter.power_trafo3w, 'trafo3w') - time_start = time.time() - self.logger.info("Creating the tap dependent characteristic objects for 3w-trafos.") - # create the characteristic objects for transformers - characteristic_df_temp = \ - self.cimConverter.net['trafo_characteristic_table'][ - ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vkr_hv_percent', 'vkr_mv_percent', - 'vkr_lv_percent', 'vk_hv_percent', 'vk_mv_percent', 'vk_lv_percent']] - for trafo_id, trafo_row in self.cimConverter.net.trafo3w.dropna( - subset=['id_characteristic_table']).iterrows(): - characteristic_df = characteristic_df_temp.loc[ - characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic_table']] - self._create_trafo_characteristic_object(net=self.cimConverter.net, trafo_type='trafo3w', - trafo_id=[trafo_id], characteristic_df=characteristic_df) - self.logger.info(f"Finished creating tap dependent characteristic objects for 3w-trafos in " - f"{time.time() - time_start}.") + # moved out of converter + # time_start = time.time() + # self.logger.info("Creating the tap dependent characteristic objects for 3w-trafos.") + # # create the characteristic objects for transformers + # characteristic_df_temp = \ + # self.cimConverter.net['trafo_characteristic_table'][ + # ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vkr_hv_percent', 'vkr_mv_percent', + # 'vkr_lv_percent', 'vk_hv_percent', 'vk_mv_percent', 'vk_lv_percent']] + # for trafo_id, trafo_row in self.cimConverter.net.trafo3w.dropna( + # subset=['id_characteristic_table']).iterrows(): + # characteristic_df = characteristic_df_temp.loc[ + # characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic_table']] + # self._create_trafo_characteristic_object(net=self.cimConverter.net, trafo_type='trafo3w', + # trafo_id=[trafo_id], characteristic_df=characteristic_df) + # self.logger.info(f"Finished creating tap dependent characteristic objects for 3w-trafos in " + # f"{time.time() - time_start}.") - def _create_trafo_characteristic_object(self, net, trafo_type: str, trafo_id: List, characteristic_df: pd.DataFrame): - self.logger.info("Adding characteristic object for trafo_type: %s and trafo_id: %s" % (trafo_type, trafo_id)) - for variable in ['voltage_ratio', 'angle_deg', 'vkr_percent', 'vk_percent', 'vk_hv_percent', 'vkr_hv_percent', - 'vk_mv_percent', 'vkr_mv_percent', 'vk_lv_percent', 'vkr_lv_percent']: - if variable in characteristic_df.columns: - pandapower.control.create_trafo_characteristics(net, trafo_type, trafo_id, variable, - [characteristic_df['step'].to_list()], - [characteristic_df[variable].to_list()]) + # moved out of converter + # def _create_trafo_characteristic_object(self, net, trafo_type: str, trafo_id: List, + # characteristic_df: pd.DataFrame): + # self.logger.info("Adding characteristic object for trafo_type: %s and trafo_id: %s" % (trafo_type, trafo_id)) + # for variable in ['voltage_ratio', 'angle_deg', 'vkr_percent', 'vk_percent', 'vk_hv_percent', 'vkr_hv_percent', + # 'vk_mv_percent', 'vkr_mv_percent', 'vk_lv_percent', 'vkr_lv_percent']: + # if variable in characteristic_df.columns: + # pandapower.control.create_trafo_characteristics(net, trafo_type, trafo_id, variable, + # [characteristic_df['step'].to_list()], + # [characteristic_df[variable].to_list()]) def _create_tap_controller(self, input_df: pd.DataFrame, trafo_type: str): if not self.cimConverter.kwargs.get('create_tap_controller', True): diff --git a/pandapower/converter/cim/cim_tools.py b/pandapower/converter/cim/cim_tools.py index 24c9cd827..334dd200d 100644 --- a/pandapower/converter/cim/cim_tools.py +++ b/pandapower/converter/cim/cim_tools.py @@ -72,7 +72,7 @@ def extend_pp_net_cim(net: pandapowerNet, override: bool = True) -> pandapowerNe fill_dict['storage'] = dict() fill_dict['storage'][np_str_type] = [sc['t'], 'description'] fill_dict['shunt'] = dict() - fill_dict['shunt'][np_str_type] = [sc['t'], 'description', 'id_characteristic_table'] + fill_dict['shunt'][np_str_type] = [sc['t'], 'description', 'id_characteristic_table', 'step_characteristic_table'] fill_dict['ward'] = dict() fill_dict['ward'][np_str_type] = [sc['t'], 'description'] fill_dict['xward'] = dict() @@ -95,14 +95,15 @@ def extend_pp_net_cim(net: pandapowerNet, override: bool = True) -> pandapowerNe fill_dict['trafo'] = dict() fill_dict['trafo'][np_str_type] = [sc['t_hv'], sc['t_lv'], sc['pte_id_hv'], sc['pte_id_lv'], sc['tc'], sc['tc_id'], - 'description', 'vector_group', 'id_characteristic_table'] + 'description', 'vector_group', 'id_characteristic_table', + 'tap_characteristic_table'] fill_dict['trafo'][np_float_type] = ['vk0_percent', 'vkr0_percent', 'xn_ohm'] fill_dict['trafo'][np_bool_type] = ['power_station_unit', 'oltc'] fill_dict['trafo3w'] = dict() fill_dict['trafo3w'][np_str_type] = [sc['t_hv'], sc['t_mv'], sc['t_lv'], sc['pte_id_hv'], sc['pte_id_mv'], sc['pte_id_lv'], sc['tc'], sc['tc_id'], 'description', 'vector_group', - 'id_characteristic_table'] + 'id_characteristic_table', 'tap_characteristic_table'] fill_dict['trafo3w'][np_float_type] = ['vk0_hv_percent', 'vk0_mv_percent', 'vk0_lv_percent', 'vkr0_hv_percent', 'vkr0_mv_percent', 'vkr0_lv_percent'] fill_dict['trafo3w'][np_bool_type] = ['power_station_unit'] From 824f13d50baff2ad5456242ef4282921077700ef Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Mon, 18 Nov 2024 16:36:09 +0100 Subject: [PATCH 005/125] Changes in pst logic --- pandapower/build_branch.py | 69 ++++++++++++------- .../control/controller/station_control.py | 2 +- 2 files changed, 46 insertions(+), 25 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 9f7b49c00..9fabde8dd 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -571,30 +571,49 @@ def _calc_tap_from_dataframe(net, trafo_df): sin = lambda x: np.sin(np.deg2rad(x)) arctan = lambda x: np.rad2deg(np.arctan(x)) - for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: - phase_shifters = tap_phase_shifter & (tap_side == side) - tap_complex = np.isfinite(tap_step_percent) & np.isfinite(tap_pos) & (tap_side == side) & \ - ~phase_shifters - if tap_complex.any(): - tap_steps = tap_step_percent[tap_complex] * tap_diff[tap_complex] / 100 - tap_angles = _replace_nan(tap_step_degree[tap_complex]) - u1 = vn[tap_complex] - du = u1 * _replace_nan(tap_steps) - vn[tap_complex] = np.sqrt((u1 + du * cos(tap_angles)) ** 2 + (du * sin(tap_angles)) ** 2) - trafo_shift[tap_complex] += (arctan(direction * du * sin(tap_angles) / - (u1 + du * cos(tap_angles)))) - if phase_shifters.any(): - degree_is_set = _replace_nan(tap_step_degree[phase_shifters]) != 0 - percent_is_set = _replace_nan(tap_step_percent[phase_shifters]) != 0 - if (degree_is_set & percent_is_set).any(): - raise UserWarning( - "Both tap_step_degree and tap_step_percent set for ideal phase shifter") - trafo_shift[phase_shifters] += np.where( - (degree_is_set), - (direction * tap_diff[phase_shifters] * tap_step_degree[phase_shifters]), - (direction * 2 * np.rad2deg(np.arcsin(tap_diff[phase_shifters] * \ - tap_step_percent[phase_shifters] / 100 / 2))) - ) + if 'tap_characteristic_table' in trafo_df: + ideal_phase_shifter = get_trafo_values(trafo_df, f"phase_shifter_type") + print("do something") + for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: + # ideal_phase_shifter = 1 + if ideal_phase_shifter.any(): + degree_is_set = _replace_nan(tap_step_degree[phase_shifters]) != 0 + percent_is_set = _replace_nan(tap_step_percent[phase_shifters]) != 0 + if (degree_is_set & percent_is_set).any(): + raise UserWarning( + "Both tap_step_degree and tap_step_percent set for ideal phase shifter") + trafo_shift[phase_shifters] += np.where( + (degree_is_set), + (direction * tap_diff[phase_shifters] * tap_step_degree[phase_shifters]), + (direction * 2 * np.rad2deg(np.arcsin(tap_diff[phase_shifters] * \ + tap_step_percent[phase_shifters] / 100 / 2))) + ) + + else: + for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: + phase_shifters = tap_phase_shifter & (tap_side == side) + tap_complex = np.isfinite(tap_step_percent) & np.isfinite(tap_pos) & (tap_side == side) & \ + ~phase_shifters + if tap_complex.any(): + tap_steps = tap_step_percent[tap_complex] * tap_diff[tap_complex] / 100 + tap_angles = _replace_nan(tap_step_degree[tap_complex]) + u1 = vn[tap_complex] + du = u1 * _replace_nan(tap_steps) + vn[tap_complex] = np.sqrt((u1 + du * cos(tap_angles)) ** 2 + (du * sin(tap_angles)) ** 2) + trafo_shift[tap_complex] += (arctan(direction * du * sin(tap_angles) / + (u1 + du * cos(tap_angles)))) + if phase_shifters.any(): + degree_is_set = _replace_nan(tap_step_degree[phase_shifters]) != 0 + percent_is_set = _replace_nan(tap_step_percent[phase_shifters]) != 0 + if (degree_is_set & percent_is_set).any(): + raise UserWarning( + "Both tap_step_degree and tap_step_percent set for ideal phase shifter") + trafo_shift[phase_shifters] += np.where( + (degree_is_set), + (direction * tap_diff[phase_shifters] * tap_step_degree[phase_shifters]), + (direction * 2 * np.rad2deg(np.arcsin(tap_diff[phase_shifters] * \ + tap_step_percent[phase_shifters] / 100 / 2))) + ) return vnh, vnl, trafo_shift @@ -1202,6 +1221,8 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): trafo2["shift_degree"] = {"hv": np.zeros(nr_trafos), "mv": t3.shift_mv_degree.values, "lv": t3.shift_lv_degree.values} trafo2["tap_phase_shifter"] = {side: np.zeros(nr_trafos).astype(bool) for side in sides} + trafo2["tap_characteristic_table"] = {side: t3.tap_characteristic_table for side in sides} + trafo2["id_characteristic_table"] = {side: t3.id_characteristic_table for side in sides} trafo2["parallel"] = {side: np.ones(nr_trafos) for side in sides} trafo2["df"] = {side: np.ones(nr_trafos) for side in sides} # even though this is not relevant (at least now), the values cannot be empty: diff --git a/pandapower/control/controller/station_control.py b/pandapower/control/controller/station_control.py index b3592c934..852908483 100644 --- a/pandapower/control/controller/station_control.py +++ b/pandapower/control/controller/station_control.py @@ -11,7 +11,7 @@ class BinarySearchControl(Controller): reactive power control or voltage control. in case of voltage control, the input parameter voltage_ctrl must be set to true. Input and output elements and indexes can be lists. Input elements can be transformers, switches, lines or busses (only in case of voltage control). in case of voltage control, a bus_index must be present, - where the voltage will be controlled.Output elements are sgens, where active and reactive power can be set. The + where the voltage will be controlled. Output elements are sgens, where active and reactive power can be set. The output value distribution describes the distribution of reactive power provision between multiple output_elements and must sum up to 1. From af2bcc50956dcf45a164119383765a79197817c7 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Wed, 20 Nov 2024 14:52:55 +0200 Subject: [PATCH 006/125] introduce id_characteristic_spline flag for trafos & shunts; align index with id_characteristic_table; remove individual spline characteristic indices from trafo and shunt tables; create one row per trafo/shunt in trafo_characteristic_spline & shunt_characteristic_spline tables with all spline characteristic objects --- pandapower/control/util/auxiliary.py | 222 ++++++++++-------- .../transformers/powerTransformersCim16.py | 2 +- 2 files changed, 130 insertions(+), 94 deletions(-) diff --git a/pandapower/control/util/auxiliary.py b/pandapower/control/util/auxiliary.py index c430b6eb4..1ef457976 100644 --- a/pandapower/control/util/auxiliary.py +++ b/pandapower/control/util/auxiliary.py @@ -6,7 +6,8 @@ import time import numpy as np -from pandas import Index, Series +import pandas as pd +from pandas import Index from pandapower.auxiliary import soft_dependency_error, ensure_iterability from .characteristic import SplineCharacteristic @@ -103,7 +104,7 @@ def get_controller_index(net, ctrl_type=None, parameters=None, idx=[]): INPUT: **net** (pandapowerNet) - The pandapower network - OPTINAL: + OPTIONAL: **controller_type** (controller object or string name of controller object) **parameters** (None, dict) - Dict of parameter names, which are in the controller object or @@ -212,6 +213,11 @@ def plot_characteristic(characteristic, start, stop, num=20, xlabel=None, ylabel def create_trafo_characteristic_object(net): + # check if trafo_characteristic_spline table already exists + if "trafo_characteristic_spline" in net: + raise UserWarning("A trafo_characteristic_spline table already exists - " + "no trafo characteristic objects created.") + # 2-winding transformers if (net['trafo_characteristic_table'].index.size > 0 and net['trafo_characteristic_table']['vk_percent'].notna().any()): time_start = time.time() @@ -221,137 +227,167 @@ def create_trafo_characteristic_object(net): for trafo_id, trafo_row in net.trafo.dropna(subset=['id_characteristic_table']).iterrows(): characteristic_df = characteristic_df_temp.loc[ characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic_table']] - logger.info("Adding characteristic object for 2w-trafo with trafo_id: %s" % trafo_id) - for variable in ['voltage_ratio', 'angle_deg', 'vkr_percent', 'vk_percent']: - if variable in characteristic_df.columns: - create_trafo_characteristics(net, "trafo", [trafo_id], variable, - [characteristic_df['step'].to_list()], - [characteristic_df[variable].to_list()]) + variables = ['voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent'] + variables_filtered = [var for var in variables if var in characteristic_df.columns] + x_points = [characteristic_df['step'].to_list()] + y_points = {col: [characteristic_df[col].tolist()] for col in variables_filtered} + logger.info("Adding characteristic objects for 2w-trafo with trafo_id %s and variables " + "%s" % (trafo_id, variables_filtered)) + create_trafo_characteristics(net, "trafo", [trafo_id], variables_filtered, + x_points, y_points) logger.info(f"Finished creating tap dependent characteristic objects for 2w-trafos in " f"{time.time() - time_start}.") else: logger.info("trafo_characteristic_table has no values for 2w-trafos - no characteristic objects created.") + # 3-winding transformers if (net['trafo_characteristic_table'].index.size > 0 and net['trafo_characteristic_table']['vkr_hv_percent'].notna().any()): time_start = time.time() logger.info("Creating tap dependent characteristic objects for 3w-trafos.") characteristic_df_temp = net['trafo_characteristic_table'][ - ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vkr_hv_percent', 'vkr_mv_percent', - 'vkr_lv_percent', 'vk_hv_percent', 'vk_mv_percent', 'vk_lv_percent']] + ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_hv_percent', 'vkr_hv_percent', + 'vk_mv_percent', 'vkr_mv_percent', 'vk_lv_percent', 'vkr_lv_percent']] for trafo_id, trafo_row in net.trafo3w.dropna(subset=['id_characteristic_table']).iterrows(): characteristic_df = characteristic_df_temp.loc[ characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic_table']] - logger.info("Adding characteristic object for 2w-trafo with trafo_id: %s" % trafo_id) - for variable in ['voltage_ratio', 'angle_deg', 'vk_hv_percent', 'vkr_hv_percent', 'vk_mv_percent', - 'vkr_mv_percent', 'vk_lv_percent', 'vkr_lv_percent']: - if variable in characteristic_df.columns: - create_trafo_characteristics(net, "trafo3w", [trafo_id], variable, - [characteristic_df['step'].to_list()], - [characteristic_df[variable].to_list()]) + variables = ['voltage_ratio', 'angle_deg', 'vk_hv_percent', 'vkr_hv_percent', 'vk_mv_percent', + 'vkr_mv_percent', 'vk_lv_percent', 'vkr_lv_percent'] + variables_filtered = [var for var in variables if var in characteristic_df.columns] + x_points = [characteristic_df['step'].to_list()] + y_points = {col: [characteristic_df[col].tolist()] for col in variables_filtered} + logger.info("Adding characteristic objects for 3w-trafo with trafo_id %s and variables " + "%s" % (trafo_id, variables_filtered)) + create_trafo_characteristics(net, "trafo3w", [trafo_id], variables_filtered, + x_points, y_points) logger.info(f"Finished creating tap dependent characteristic objects for 3w-trafos in " f"{time.time() - time_start}.") else: logger.info("trafo_characteristic_table has no values for 3w-trafos - no characteristic objects created.") + # pivot spline characteristic objects to have one row per trafo/trafo3w + net["trafo_characteristic_spline"] = net["trafo_characteristic_spline_temp"].applymap( + lambda x: net["trafo_characteristic_spline"].loc[x, 'object'] if pd.notna(x) else pd.NA).sort_index() + # create id_characteristic column + net["trafo_characteristic_spline"]["id_characteristic"] = net["trafo_characteristic_spline"].index + net["trafo_characteristic_spline"].insert( + 0, 'id_characteristic', net["trafo_characteristic_spline"].pop('id_characteristic')) + del net["trafo_characteristic_spline_temp"] + def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_points, y_points): - # create characteristics for the specified variable and set their indices in the trafo table - col = f"{variable}_characteristic" - # check if the variable is a valid attribute of the trafo table supported_columns = {"trafo": ["voltage_ratio_characteristic", "angle_deg_characteristic", "vk_percent_characteristic", "vkr_percent_characteristic"], "trafo3w": ["voltage_ratio_characteristic", "angle_deg_characteristic", - "vkr_hv_percent_characteristic", "vkr_mv_percent_characteristic", - "vkr_lv_percent_characteristic", "vk_hv_percent_characteristic", - "vk_mv_percent_characteristic", "vk_lv_percent_characteristic"]} - if col not in supported_columns[trafotable]: - raise UserWarning("Variable %s is not supported for table %s" % (variable, trafotable)) - - # check inputs, check if 1 trafo or multiple, verify shape of x_points and y_points and trafo_index - if hasattr(trafo_index, '__iter__'): - single_mode = False - if not (len(trafo_index) == len(x_points) == len(y_points)): - raise UserWarning("The lengths of the trafo index and points do not match!") - else: - single_mode = True - if (len(x_points) != len(y_points)): - raise UserWarning("The lengths of the points do not match!") - - if col not in net[trafotable]: - net[trafotable][col] = Series(index=net[trafotable].index, dtype="Int64") - - # moved into converter - # if 'tap_characteristic_table' not in net[trafotable]: - # net[trafotable]['tap_characteristic_table'] = Series(index=net[trafotable].index, dtype=np.bool_, data=False) - # # set the flag for the trafo table - # net[trafotable].loc[trafo_index, 'tap_characteristic_table'] = True + "vk_hv_percent_characteristic", "vkr_hv_percent_characteristic", + "vk_mv_percent_characteristic", "vkr_mv_percent_characteristic", + "vk_lv_percent_characteristic", "vkr_lv_percent_characteristic"]} + + # create id_characteristic_spline column - same indices as id_characteristic_table + if "id_characteristic_spline" not in net[trafotable]: + net[trafotable]["id_characteristic_spline"] = net[trafotable]["id_characteristic_table"].copy() + if "trafo_characteristic_spline_temp" not in net: + col_list = list(dict.fromkeys(supported_columns["trafo"] + supported_columns["trafo3w"])) + net["trafo_characteristic_spline_temp"] = pd.DataFrame(columns=col_list, dtype="Int64") + + for var in variable: + # create characteristics for the specified variable and set their indices in the trafo table + col = f"{var}_characteristic" + # check if the variable is a valid attribute of the trafo table + if col not in supported_columns[trafotable]: + raise UserWarning("Variable %s is not supported for table %s" % (var, trafotable)) + + # check inputs, check if 1 trafo or multiple, verify shape of x_points and y_points and trafo_index + if hasattr(trafo_index, '__iter__'): + single_mode = False + if not (len(trafo_index) == len(x_points) == len(y_points[var])): + raise UserWarning("The lengths of the trafo index and points do not match!") + else: + single_mode = True + if len(x_points) != len(y_points[var]): + raise UserWarning("The lengths of the points do not match!") - if single_mode: - zip_params = zip([trafo_index], [x_points], [y_points]) - else: - zip_params = zip(trafo_index, x_points, y_points) + if single_mode: + zip_params = zip([trafo_index], [x_points], [y_points[var]]) + else: + zip_params = zip(trafo_index, x_points, y_points[var]) - for tid, x_p, y_p in zip_params: - # create the characteristic and set its index in the trafotable - s = SplineCharacteristic(net, x_p, y_p, table="trafo_characteristic_spline") - net[trafotable].at[tid, col] = s.index + for tid, x_p, y_p in zip_params: + # create the characteristic and set its index in the trafotable + s = SplineCharacteristic(net, x_p, y_p, table="trafo_characteristic_spline") + idx = net[trafotable].at[tid, "id_characteristic_spline"] + # save the index of the new spline characteristic object in the temp table + net["trafo_characteristic_spline_temp"].at[idx, col] = s.index def create_shunt_characteristic_object(net): + # check if shunt_characteristic_spline table already exists + if "shunt_characteristic_spline" in net: + raise UserWarning("A shunt_characteristic_spline table already exists - " + "no shunt characteristic objects created.") if net['shunt_characteristic_table'].index.size > 0: time_start = time.time() logger.info("Creating step dependent power characteristic objects for shunts.") characteristic_df_temp = net['shunt_characteristic_table'] for shunt_id, shunt_row in net.shunt.dropna(subset=['id_characteristic_table']).iterrows(): - shunt_characteristic_df = characteristic_df_temp.loc[ + characteristic_df = characteristic_df_temp.loc[ characteristic_df_temp['id_characteristic'] == shunt_row['id_characteristic_table']] - logger.info("Adding characteristic object for shunt with shunt_id: %s" % shunt_id) - for variable in ['q_mvar', 'p_mw']: - if variable in shunt_characteristic_df.columns: - create_shunt_characteristics( - net, [shunt_id], variable, [shunt_characteristic_df['step'].to_list()], - [shunt_characteristic_df[variable].to_list()] - ) + variables = ['q_mvar', 'p_mw'] + variables_filtered = [var for var in variables if var in characteristic_df.columns] + x_points = [characteristic_df['step'].to_list()] + y_points = {col: [characteristic_df[col].tolist()] for col in variables_filtered} + logger.info("Adding characteristic objects for shunt with shunt_id %s and variables " + "%s" % (shunt_id, variables_filtered)) + create_shunt_characteristics(net, [shunt_id], variables_filtered, + x_points, y_points) logger.info(f"Finished creating step dependent power characteristic objects for shunts in" f"{time.time() - time_start}.") else: logger.info("shunt_characteristic_table is empty - no characteristic objects created.") + # pivot spline characteristic objects to have one row per shunt + net["shunt_characteristic_spline"] = net["shunt_characteristic_spline_temp"].applymap( + lambda x: net["shunt_characteristic_spline"].loc[x, 'object'] if pd.notna(x) else pd.NA).sort_index() + # create id_characteristic column + net["shunt_characteristic_spline"]["id_characteristic"] = net["shunt_characteristic_spline"].index + net["shunt_characteristic_spline"].insert( + 0, 'id_characteristic', net["shunt_characteristic_spline"].pop('id_characteristic')) + del net["shunt_characteristic_spline_temp"] + -# todo merge create_trafo_characteristics and create_shunt_characteristics? def create_shunt_characteristics(net, shunt_index, variable, x_points, y_points): - # create characteristics for the specified variable and set their indices in the shunt table - col = f"{variable}_characteristic" - # check if the variable is a valid attribute of the shunt table supported_columns = ["q_mvar_characteristic", "p_mw_characteristic"] - if col not in supported_columns: - raise UserWarning("Variable %s is not supported for table shunt" % variable) - - # check inputs, check if 1 shunt or multiple, verify shape of x_points and y_points and shunt_index - if hasattr(shunt_index, '__iter__'): - single_mode = False - if not (len(shunt_index) == len(x_points) == len(y_points)): - raise UserWarning("The lengths of the shunt index and points do not match!") - else: - single_mode = True - if len(x_points) != len(y_points): - raise UserWarning("The lengths of the points do not match!") - - if col not in net["shunt"]: - net["shunt"][col] = Series(index=net["shunt"].index, dtype="Int64") - # moved into converter - # if 'step_characteristic_table' not in net["shunt"]: - # net["shunt"]["step_characteristic_table"] = Series(index=net["shunt"].index, dtype=np.bool_, data=False) - # set the flag for the shunt table - # net["shunt"].loc[shunt_index, "step_characteristic_table"] = True - - if single_mode: - zip_params = zip([shunt_index], [x_points], [y_points]) - else: - zip_params = zip(shunt_index, x_points, y_points) + # create id_characteristic_spline column - same indices as id_characteristic_table + if "id_characteristic_spline" not in net["shunt"]: + net["shunt"]["id_characteristic_spline"] = net["shunt"]["id_characteristic_table"].copy() + if "shunt_characteristic_spline_temp" not in net: + net["shunt_characteristic_spline_temp"] = pd.DataFrame(columns=supported_columns, dtype="Int64") + + for var in variable: + # create characteristics for the specified variable and set their indices in the shunt table + col = f"{var}_characteristic" + # check if the variable is a valid attribute of the shunt table + if col not in supported_columns: + raise UserWarning("Variable %s is not supported for table shunt" % var) + + # check inputs, check if 1 shunt or multiple, verify shape of x_points and y_points and shunt_index + if hasattr(shunt_index, '__iter__'): + single_mode = False + if not (len(shunt_index) == len(x_points) == len(y_points[var])): + raise UserWarning("The lengths of the shunt index and points do not match!") + else: + single_mode = True + if len(x_points) != len(y_points[var]): + raise UserWarning("The lengths of the points do not match!") - for tid, x_p, y_p in zip_params: - # create the characteristic and set its index in the shunt table - s = SplineCharacteristic(net, x_p, y_p, table="shunt_characteristic_spline") - net["shunt"].at[tid, col] = s.index + if single_mode: + zip_params = zip([shunt_index], [x_points], [y_points[var]]) + else: + zip_params = zip(shunt_index, x_points, y_points[var]) + + for tid, x_p, y_p in zip_params: + # create the characteristic and set its index in the shunt table + s = SplineCharacteristic(net, x_p, y_p, table="shunt_characteristic_spline") + idx = net["shunt"].at[tid, "id_characteristic_spline"] + # save the index of the new spline characteristic object in the temp table + net["shunt_characteristic_spline_temp"].at[idx, col] = s.index diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index 2e2aa7d98..66d3565f6 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -56,7 +56,7 @@ def convert_power_transformers_cim16(self): def _create_trafo_characteristic_table(self, trafo_type, trafo_df_origin): if 'id_characteristic_table' not in trafo_df_origin.columns: - trafo_df_origin['id_characteristic_table'] = np.nan + trafo_df_origin['id_characteristic_table'] = pd.Series(pd.NA, dtype="Int64") if 'trafo_characteristic_table' not in self.cimConverter.net.keys(): self.cimConverter.net['trafo_characteristic_table'] = pd.DataFrame( columns=['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent', From b30a97290750affbac393729d194f24991d04a7b Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 21 Nov 2024 12:15:13 +0200 Subject: [PATCH 007/125] rename tap_characteristic_table to tap_dependency_table & step_characteristic_table to step_dependency_table --- .../shunts/linearShuntCompensatorCim16.py | 6 +++--- .../shunts/nonLinearShuntCompensatorCim16.py | 10 +++++----- .../shunts/staticVarCompensatorCim16.py | 6 +++--- .../transformers/powerTransformersCim16.py | 10 +++++----- pandapower/converter/cim/cim_tools.py | 6 +++--- 5 files changed, 19 insertions(+), 19 deletions(-) diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/linearShuntCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/linearShuntCompensatorCim16.py index 55bf4af4d..191214424 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/linearShuntCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/linearShuntCompensatorCim16.py @@ -41,7 +41,7 @@ def _prepare_linear_shunt_compensator_cim16(self) -> pd.DataFrame: s = eqssh_shunts['vn_kv'] ** 2 * np.conj(y) eqssh_shunts['p_mw'] = s.values.real eqssh_shunts['q_mvar'] = s.values.imag - # create step_characteristic_table flag - if 'step_characteristic_table' not in eqssh_shunts.columns: - eqssh_shunts["step_characteristic_table"] = pd.Series(index=eqssh_shunts.index, dtype=np.bool_, data=False) + # create step_dependency_table flag + if 'step_dependency_table' not in eqssh_shunts.columns: + eqssh_shunts["step_dependency_table"] = pd.Series(index=eqssh_shunts.index, dtype=np.bool_, data=False) return eqssh_shunts diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py index 0ddae0661..deb0bcd07 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py @@ -108,11 +108,11 @@ def _create_shunt_characteristic_table(self, eqssh_shunts): id_char_dict = char_temp.drop_duplicates('origin_id').set_index('origin_id')['id_characteristic'].to_dict() eqssh_shunts['id_characteristic_table'] = eqssh_shunts['origin_id'].map(id_char_dict).astype(int) - # create step_characteristic_table flag - if 'step_characteristic_table' not in eqssh_shunts.columns: - eqssh_shunts["step_characteristic_table"] = pd.Series(index=eqssh_shunts.index, dtype=np.bool_, data=False) - # set step_characteristic_table as True for all non-linear shunt compensators - eqssh_shunts.loc[eqssh_shunts['id_characteristic_table'].notna(), 'step_characteristic_table'] = True + # create step_dependency_table flag + if 'step_dependency_table' not in eqssh_shunts.columns: + eqssh_shunts["step_dependency_table"] = pd.Series(index=eqssh_shunts.index, dtype=np.bool_, data=False) + # set step_dependency_table as True for all non-linear shunt compensators + eqssh_shunts.loc[eqssh_shunts['id_characteristic_table'].notna(), 'step_dependency_table'] = True # populate shunt_characteristic_temp table self.cimConverter.net['shunt_characteristic_table'] = \ diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py index ced1de626..101e831ad 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py @@ -43,7 +43,7 @@ def _prepare_static_var_compensator_cim16(self) -> pd.DataFrame: 'voltageSetPoint': 'vn_kv', 'index_bus': 'bus', 'connected': 'in_service'}) eq_stat_coms['step'] = 1 eq_stat_coms['max_step'] = 1 - # create step_characteristic_table flag - if 'step_characteristic_table' not in eq_stat_coms.columns: - eq_stat_coms["step_characteristic_table"] = pd.Series(index=eq_stat_coms.index, dtype=np.bool_, data=False) + # create step_dependency_table flag + if 'step_dependency_table' not in eq_stat_coms.columns: + eq_stat_coms["step_dependency_table"] = pd.Series(index=eq_stat_coms.index, dtype=np.bool_, data=False) return eq_stat_coms diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index 66d3565f6..1a19399b2 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -272,13 +272,13 @@ def append_row(res_dict, id_c, row, cols): # and one_row.step != one_row.lowStep and one_row.step != one_row.neutralStep: # append_row(append_dict, id_characteristic, one_row, one_df.columns) - # create tap_characteristic_table flag - if 'tap_characteristic_table' not in trafo_df_origin.columns: - trafo_df_origin['tap_characteristic_table'] = pd.Series( + # create tap_dependency_table flag + if 'tap_dependency_table' not in trafo_df_origin.columns: + trafo_df_origin['tap_dependency_table'] = pd.Series( index=trafo_df_origin.index, dtype=np.bool_, data=False ) - # set tap_characteristic_table as True for all non-linear shunt compensators - trafo_df_origin.loc[trafo_df_origin['id_characteristic_table'].notna(), 'tap_characteristic_table'] = True + # set tap_dependency_table as True for respective trafos + trafo_df_origin.loc[trafo_df_origin['id_characteristic_table'].notna(), 'tap_dependency_table'] = True self.cimConverter.net['trafo_characteristic_table'] = pd.concat( [self.cimConverter.net['trafo_characteristic_table'], pd.DataFrame(append_dict)], diff --git a/pandapower/converter/cim/cim_tools.py b/pandapower/converter/cim/cim_tools.py index 334dd200d..d567ba7cf 100644 --- a/pandapower/converter/cim/cim_tools.py +++ b/pandapower/converter/cim/cim_tools.py @@ -72,7 +72,7 @@ def extend_pp_net_cim(net: pandapowerNet, override: bool = True) -> pandapowerNe fill_dict['storage'] = dict() fill_dict['storage'][np_str_type] = [sc['t'], 'description'] fill_dict['shunt'] = dict() - fill_dict['shunt'][np_str_type] = [sc['t'], 'description', 'id_characteristic_table', 'step_characteristic_table'] + fill_dict['shunt'][np_str_type] = [sc['t'], 'description', 'id_characteristic_table', 'step_dependency_table'] fill_dict['ward'] = dict() fill_dict['ward'][np_str_type] = [sc['t'], 'description'] fill_dict['xward'] = dict() @@ -96,14 +96,14 @@ def extend_pp_net_cim(net: pandapowerNet, override: bool = True) -> pandapowerNe fill_dict['trafo'] = dict() fill_dict['trafo'][np_str_type] = [sc['t_hv'], sc['t_lv'], sc['pte_id_hv'], sc['pte_id_lv'], sc['tc'], sc['tc_id'], 'description', 'vector_group', 'id_characteristic_table', - 'tap_characteristic_table'] + 'tap_dependency_table', 'phase_shifter_type'] fill_dict['trafo'][np_float_type] = ['vk0_percent', 'vkr0_percent', 'xn_ohm'] fill_dict['trafo'][np_bool_type] = ['power_station_unit', 'oltc'] fill_dict['trafo3w'] = dict() fill_dict['trafo3w'][np_str_type] = [sc['t_hv'], sc['t_mv'], sc['t_lv'], sc['pte_id_hv'], sc['pte_id_mv'], sc['pte_id_lv'], sc['tc'], sc['tc_id'], 'description', 'vector_group', - 'id_characteristic_table', 'tap_characteristic_table'] + 'id_characteristic_table', 'tap_dependency_table', 'phase_shifter_type'] fill_dict['trafo3w'][np_float_type] = ['vk0_hv_percent', 'vk0_mv_percent', 'vk0_lv_percent', 'vkr0_hv_percent', 'vkr0_mv_percent', 'vkr0_lv_percent'] fill_dict['trafo3w'][np_bool_type] = ['power_station_unit'] From c069bfabce03e3babffb9c0e1131e55a6353b59a Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 21 Nov 2024 12:48:38 +0200 Subject: [PATCH 008/125] introduce tap_phase_shifter_type flag; populate tap_step_percent & tap_step_degree with the values corresponding to the neutral tap position for PhaseTapChangerTabular trafos --- .../transformers/powerTransformersCim16.py | 42 +++++++------------ pandapower/converter/cim/cim_tools.py | 4 +- 2 files changed, 16 insertions(+), 30 deletions(-) diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index 1a19399b2..636cbc188 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -309,12 +309,14 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: self.cimConverter.cim['ssh']['RatioTapChanger'][['rdfId', 'step']], how='left', on='rdfId') eqssh_tap_changers[sc['tc']] = 'RatioTapChanger' + eqssh_tap_changers['tap_phase_shifter_type'] = 0 # Ratio/Asymmetrical phase shifter eqssh_tap_changers[sc['tc_id']] = eqssh_tap_changers['rdfId'].copy() eqssh_tap_changers_linear = pd.merge(self.cimConverter.cim['eq']['PhaseTapChangerLinear'], self.cimConverter.cim['ssh']['PhaseTapChangerLinear'], how='left', on='rdfId') eqssh_tap_changers_linear['stepVoltageIncrement'] = .001 eqssh_tap_changers_linear[sc['tc']] = 'PhaseTapChangerLinear' + eqssh_tap_changers_linear['tap_phase_shifter_type'] = 2 # Ideal phase shifter eqssh_tap_changers_linear[sc['tc_id']] = eqssh_tap_changers_linear['rdfId'].copy() eqssh_tap_changers = pd.concat([eqssh_tap_changers, eqssh_tap_changers_linear], ignore_index=True, sort=False) eqssh_tap_changers_async = pd.merge(self.cimConverter.cim['eq']['PhaseTapChangerAsymmetrical'], @@ -323,6 +325,7 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: eqssh_tap_changers_async['stepVoltageIncrement'] = eqssh_tap_changers_async['voltageStepIncrement'][:] eqssh_tap_changers_async = eqssh_tap_changers_async.drop(columns=['voltageStepIncrement']) eqssh_tap_changers_async[sc['tc']] = 'PhaseTapChangerAsymmetrical' + eqssh_tap_changers_async['tap_phase_shifter_type'] = 0 # Ratio/Asymmetrical phase shifter eqssh_tap_changers_async[sc['tc_id']] = eqssh_tap_changers_async['rdfId'].copy() eqssh_tap_changers = pd.concat([eqssh_tap_changers, eqssh_tap_changers_async], ignore_index=True, sort=False) eqssh_ratio_tap_changers_sync = pd.merge(self.cimConverter.cim['eq']['PhaseTapChangerSymmetrical'], @@ -331,6 +334,7 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: eqssh_ratio_tap_changers_sync['stepVoltageIncrement'] = eqssh_ratio_tap_changers_sync['voltageStepIncrement'] eqssh_ratio_tap_changers_sync = eqssh_ratio_tap_changers_sync.drop(columns=['voltageStepIncrement']) eqssh_ratio_tap_changers_sync[sc['tc']] = 'PhaseTapChangerSymmetrical' + eqssh_ratio_tap_changers_sync['tap_phase_shifter_type'] = 1 # Symmetrical phase shifter eqssh_ratio_tap_changers_sync[sc['tc_id']] = eqssh_ratio_tap_changers_sync['rdfId'].copy() eqssh_tap_changers = \ pd.concat([eqssh_tap_changers, eqssh_ratio_tap_changers_sync], ignore_index=True, sort=False) @@ -356,16 +360,14 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: one_df = one_df.set_index('step') neutral_step = one_df['neutralStep'].iloc[0] ptct = ptct.drop(drop_index) - # todo change to populate tap_step_percent & tap_step_degree based on neutral tap_pos? - # ptct.loc[keep_index, 'angle'] = - # one_df.loc[current_step, 'angle'] / max(1, abs(current_step - neutral_step)) - ptct.loc[keep_index, 'angle'] = one_df.loc[current_step, 'angle'] # todo fix if pp supports them - ptct.loc[keep_index, 'ratio'] = \ - (one_df.loc[current_step, 'ratio'] - 1) * 100 / max(1, abs(current_step - neutral_step)) + # keep the angle and ratio based on neutral tap position + ptct.loc[keep_index, 'angle'] = one_df.loc[neutral_step, 'angle'] + ptct.loc[keep_index, 'ratio'] = one_df.loc[neutral_step, 'ratio'] ptct = ptct.drop(columns=['rdfId', 'PhaseTapChangerTable', 'step']) ptct = ptct.rename(columns={'current_step': 'step'}) - # ptct['stepPhaseShiftIncrement'] = ptct['angle'][:] # todo fix if pp supports them + ptct['stepPhaseShiftIncrement'] = ptct['angle'][:] ptct['stepVoltageIncrement'] = ptct['ratio'][:] + ptct['tap_phase_shifter_type'] = 0 # Ratio/Asymmetrical phase shifter eqssh_tap_changers = pd.concat([eqssh_tap_changers, ptct], ignore_index=True, sort=False) del eqssh_tap_changers_linear, eqssh_tap_changers_async, eqssh_ratio_tap_changers_sync @@ -436,6 +438,8 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: how='left', left_on='Terminal', right_on='rdfId_Terminal') # add the TapChangers power_transformers = pd.merge(power_transformers, eqssh_tap_changers, how='left', on=sc['pte_id']) + power_transformers['tap_phase_shifter_type'] = power_transformers['tap_phase_shifter_type'].apply( + lambda x: int(x) if not pd.isna(x) else x).astype('Int64') return power_transformers def _prepare_trafos_cim16(self, power_trafo2w: pd.DataFrame) -> pd.DataFrame: @@ -501,16 +505,7 @@ def _prepare_trafos_cim16(self, power_trafo2w: pd.DataFrame) -> pd.DataFrame: power_trafo2w['vk0_percent'] = power_trafo2w['x0_sign'] * power_trafo2w['vk0_percent'] power_trafo2w['std_type'] = None power_trafo2w['df'] = 1. - # todo remove if pp supports phase shifter - if power_trafo2w.loc[power_trafo2w['angle'].notna()].index.size > 0: - self.logger.warning("Modifying angle from 2W transformers. This kind of angle regulation is currently not " - "supported by pandapower! Affected transformers: \n%s" % - power_trafo2w.loc[power_trafo2w['angle'].notna()]) - self.cimConverter.report_container.add_log(Report( - level=LogLevel.WARNING, code=ReportCode.WARNING_CONVERTING, - message="Modifying angle from 2W transformers. This kind of angle regulation is currently not " - "supported by pandapower! Affected transformers: \n%s" % - power_trafo2w.loc[power_trafo2w['angle'].notna()])) + # todo check shift_degree code power_trafo2w['phaseAngleClock_temp'] = power_trafo2w['phaseAngleClock'].copy() power_trafo2w['phaseAngleClock'] = power_trafo2w['angle'] / 30 power_trafo2w['phaseAngleClock'] = power_trafo2w['phaseAngleClock'].fillna(power_trafo2w['angle_lv'] * -1 / 30) @@ -519,7 +514,7 @@ def _prepare_trafos_cim16(self, power_trafo2w: pd.DataFrame) -> pd.DataFrame: power_trafo2w['shift_degree'] = power_trafo2w['phaseAngleClock'].astype(float).fillna( power_trafo2w['phaseAngleClock_lv'].astype(float)) * 30 power_trafo2w['parallel'] = 1 - power_trafo2w['tap_phase_shifter'] = False # todo remove hardcoded False flag to enable angle regulation + # power_trafo2w['tap_phase_shifter'] = False # removed power_trafo2w['in_service'] = power_trafo2w.connected & power_trafo2w.connected_lv power_trafo2w['connectionKind'] = power_trafo2w['connectionKind'].fillna('') power_trafo2w['connectionKind_lv'] = power_trafo2w['connectionKind_lv'].fillna('') @@ -636,16 +631,7 @@ def _prepare_trafo3w_cim16(self, power_trafo3w: pd.DataFrame) -> pd.DataFrame: power_trafo3w.ratedU_lv / power_trafo3w.ratedU) ** 2) ** 2) ** 0.5 * \ power_trafo3w.min_s_lvhv * 100 / power_trafo3w.ratedU_lv ** 2 power_trafo3w['std_type'] = None - # todo remove if pp supports phase shifter - if power_trafo3w.loc[power_trafo3w['angle_mv'].notna()].index.size > 0: - self.logger.warning("Modifying angle from 3W transformers. This kind of angle regulation is currently not " - "supported by pandapower! Affected transformers: \n%s" % - power_trafo3w.loc[power_trafo3w['angle_mv'].notna()]) - self.cimConverter.report_container.add_log(Report( - level=LogLevel.WARNING, code=ReportCode.WARNING_CONVERTING, - message="Modifying angle from 3W transformers. This kind of angle regulation is currently not " - "supported by pandapower! Affected transformers: \n%s" % - power_trafo3w.loc[power_trafo3w['angle_mv'].notna()])) + # todo check shift_degree code power_trafo3w['phaseAngleClock_temp'] = power_trafo3w['phaseAngleClock_mv'].copy() power_trafo3w['phaseAngleClock_mv'] = power_trafo3w['angle_mv'] * -1 / 30 power_trafo3w['phaseAngleClock_mv'] = power_trafo3w['phaseAngleClock_mv'].fillna( diff --git a/pandapower/converter/cim/cim_tools.py b/pandapower/converter/cim/cim_tools.py index d567ba7cf..a909ddf60 100644 --- a/pandapower/converter/cim/cim_tools.py +++ b/pandapower/converter/cim/cim_tools.py @@ -96,14 +96,14 @@ def extend_pp_net_cim(net: pandapowerNet, override: bool = True) -> pandapowerNe fill_dict['trafo'] = dict() fill_dict['trafo'][np_str_type] = [sc['t_hv'], sc['t_lv'], sc['pte_id_hv'], sc['pte_id_lv'], sc['tc'], sc['tc_id'], 'description', 'vector_group', 'id_characteristic_table', - 'tap_dependency_table', 'phase_shifter_type'] + 'tap_dependency_table', 'tap_phase_shifter_type'] fill_dict['trafo'][np_float_type] = ['vk0_percent', 'vkr0_percent', 'xn_ohm'] fill_dict['trafo'][np_bool_type] = ['power_station_unit', 'oltc'] fill_dict['trafo3w'] = dict() fill_dict['trafo3w'][np_str_type] = [sc['t_hv'], sc['t_mv'], sc['t_lv'], sc['pte_id_hv'], sc['pte_id_mv'], sc['pte_id_lv'], sc['tc'], sc['tc_id'], 'description', 'vector_group', - 'id_characteristic_table', 'tap_dependency_table', 'phase_shifter_type'] + 'id_characteristic_table', 'tap_dependency_table', 'tap_phase_shifter_type'] fill_dict['trafo3w'][np_float_type] = ['vk0_hv_percent', 'vk0_mv_percent', 'vk0_lv_percent', 'vkr0_hv_percent', 'vkr0_mv_percent', 'vkr0_lv_percent'] fill_dict['trafo3w'][np_bool_type] = ['power_station_unit'] From fbbdec1c69a7f01288b76c019c86e1c5476eeba8 Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Fri, 22 Nov 2024 09:03:05 +0100 Subject: [PATCH 009/125] Renamed tap_dependency_table and tap_phase_shifter_type --- pandapower/build_branch.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 9fabde8dd..9c7385cde 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -571,8 +571,8 @@ def _calc_tap_from_dataframe(net, trafo_df): sin = lambda x: np.sin(np.deg2rad(x)) arctan = lambda x: np.rad2deg(np.arctan(x)) - if 'tap_characteristic_table' in trafo_df: - ideal_phase_shifter = get_trafo_values(trafo_df, f"phase_shifter_type") + if 'tap_dependency_table' in trafo_df: + phase_shifter_type = get_trafo_values(trafo_df, f"tap{t}_phase_shifter_type") print("do something") for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: # ideal_phase_shifter = 1 From 8dc4ae733cc9b2e3114c82f3c02668f82905cb9f Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Fri, 22 Nov 2024 09:21:25 +0100 Subject: [PATCH 010/125] Changes in Controller documentation --- doc/control/controller.rst | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/doc/control/controller.rst b/doc/control/controller.rst index c8fe8826d..80e25be7e 100644 --- a/doc/control/controller.rst +++ b/doc/control/controller.rst @@ -107,11 +107,10 @@ SplineCharacteristic .. autoclass:: pandapower.control.util.characteristic.SplineCharacteristic :members: -The following controllers are used for the representation of station controllers as used in PowerFactory - Station Controller ================== +The following controllers are used for the representation of station controllers as used in PowerFactory ********************** Binary Search Control From ad1c6a07535160e46facf43b41c749f778ad6d06 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 22 Nov 2024 17:40:44 +0200 Subject: [PATCH 011/125] fix shift_degree for trafo/3w --- .../transformers/powerTransformersCim16.py | 15 +++------------ 1 file changed, 3 insertions(+), 12 deletions(-) diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index 636cbc188..9d79d9825 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -505,11 +505,7 @@ def _prepare_trafos_cim16(self, power_trafo2w: pd.DataFrame) -> pd.DataFrame: power_trafo2w['vk0_percent'] = power_trafo2w['x0_sign'] * power_trafo2w['vk0_percent'] power_trafo2w['std_type'] = None power_trafo2w['df'] = 1. - # todo check shift_degree code - power_trafo2w['phaseAngleClock_temp'] = power_trafo2w['phaseAngleClock'].copy() - power_trafo2w['phaseAngleClock'] = power_trafo2w['angle'] / 30 - power_trafo2w['phaseAngleClock'] = power_trafo2w['phaseAngleClock'].fillna(power_trafo2w['angle_lv'] * -1 / 30) - power_trafo2w['phaseAngleClock'] = power_trafo2w['phaseAngleClock'].fillna(power_trafo2w['phaseAngleClock_temp']) + power_trafo2w.loc[power_trafo2w['phaseAngleClock'] == 0, 'phaseAngleClock'] = np.nan power_trafo2w['phaseAngleClock_lv'] = power_trafo2w['phaseAngleClock_lv'].fillna(0) power_trafo2w['shift_degree'] = power_trafo2w['phaseAngleClock'].astype(float).fillna( power_trafo2w['phaseAngleClock_lv'].astype(float)) * 30 @@ -631,15 +627,10 @@ def _prepare_trafo3w_cim16(self, power_trafo3w: pd.DataFrame) -> pd.DataFrame: power_trafo3w.ratedU_lv / power_trafo3w.ratedU) ** 2) ** 2) ** 0.5 * \ power_trafo3w.min_s_lvhv * 100 / power_trafo3w.ratedU_lv ** 2 power_trafo3w['std_type'] = None - # todo check shift_degree code - power_trafo3w['phaseAngleClock_temp'] = power_trafo3w['phaseAngleClock_mv'].copy() - power_trafo3w['phaseAngleClock_mv'] = power_trafo3w['angle_mv'] * -1 / 30 - power_trafo3w['phaseAngleClock_mv'] = power_trafo3w['phaseAngleClock_mv'].fillna( - power_trafo3w['phaseAngleClock_temp']) power_trafo3w['phaseAngleClock_mv'] = power_trafo3w['phaseAngleClock_mv'].fillna(0) power_trafo3w['phaseAngleClock_lv'] = power_trafo3w['phaseAngleClock_lv'].fillna(0) - power_trafo3w['shift_mv_degree'] = power_trafo3w['phaseAngleClock_mv'] * 30 - power_trafo3w['shift_lv_degree'] = power_trafo3w['phaseAngleClock_mv'] * 30 + power_trafo3w['shift_mv_degree'] = power_trafo3w['phaseAngleClock_mv'].astype(float) * 30 + power_trafo3w['shift_lv_degree'] = power_trafo3w['phaseAngleClock_mv'].astype(float) * 30 power_trafo3w['tap_at_star_point'] = False power_trafo3w['in_service'] = power_trafo3w.connected & power_trafo3w.connected_mv & power_trafo3w.connected_lv power_trafo3w['connectionKind'] = power_trafo3w['connectionKind'].fillna('') From 7cade729e093c085fb2f117e1b9a1f0a4fa425f8 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 22 Nov 2024 18:30:32 +0200 Subject: [PATCH 012/125] address Mario's comments; update create.py lib for trafo/trafo3w parameter changes --- pandapower/control/util/auxiliary.py | 10 +- .../shunts/linearShuntCompensatorCim16.py | 2 +- .../shunts/nonLinearShuntCompensatorCim16.py | 34 +- .../shunts/staticVarCompensatorCim16.py | 2 +- .../transformers/powerTransformersCim16.py | 19 +- pandapower/converter/cim/cim_tools.py | 8 +- pandapower/converter/cim/pp_tools.py | 4 +- pandapower/create.py | 426 +++++++----------- pandapower/std_types.py | 36 +- .../control/test_tap_dependent_impedance.py | 2 +- 10 files changed, 199 insertions(+), 344 deletions(-) diff --git a/pandapower/control/util/auxiliary.py b/pandapower/control/util/auxiliary.py index 1ef457976..d85ef1605 100644 --- a/pandapower/control/util/auxiliary.py +++ b/pandapower/control/util/auxiliary.py @@ -213,10 +213,9 @@ def plot_characteristic(characteristic, start, stop, num=20, xlabel=None, ylabel def create_trafo_characteristic_object(net): - # check if trafo_characteristic_spline table already exists + # check if trafo_characteristic_spline table already exists & if so, delete & re-create if "trafo_characteristic_spline" in net: - raise UserWarning("A trafo_characteristic_spline table already exists - " - "no trafo characteristic objects created.") + del net["trafo_characteristic_spline"] # 2-winding transformers if (net['trafo_characteristic_table'].index.size > 0 and net['trafo_characteristic_table']['vk_percent'].notna().any()): @@ -320,10 +319,9 @@ def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_point def create_shunt_characteristic_object(net): - # check if shunt_characteristic_spline table already exists + # check if shunt_characteristic_spline table already exists & if so, delete & re-create if "shunt_characteristic_spline" in net: - raise UserWarning("A shunt_characteristic_spline table already exists - " - "no shunt characteristic objects created.") + del net["shunt_characteristic_spline"] if net['shunt_characteristic_table'].index.size > 0: time_start = time.time() logger.info("Creating step dependent power characteristic objects for shunts.") diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/linearShuntCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/linearShuntCompensatorCim16.py index 191214424..9905cb3e9 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/linearShuntCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/linearShuntCompensatorCim16.py @@ -43,5 +43,5 @@ def _prepare_linear_shunt_compensator_cim16(self) -> pd.DataFrame: eqssh_shunts['q_mvar'] = s.values.imag # create step_dependency_table flag if 'step_dependency_table' not in eqssh_shunts.columns: - eqssh_shunts["step_dependency_table"] = pd.Series(index=eqssh_shunts.index, dtype=np.bool_, data=False) + eqssh_shunts["step_dependency_table"] = False return eqssh_shunts diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py index deb0bcd07..2bb03cb5f 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py @@ -88,48 +88,32 @@ def _create_shunt_characteristic_table(self, eqssh_shunts): # get the NonlinearShuntCompensatorPoints nscp = self.cimConverter.cim['eq']['NonlinearShuntCompensatorPoint'][ ['NonlinearShuntCompensator', 'sectionNumber', 'b', 'g']].rename( - columns={'NonlinearShuntCompensator': 'origin_id'}) - char_temp = pd.merge(char_temp, nscp, how='left', on='origin_id') + columns={'NonlinearShuntCompensator': sc['o_id']}) + char_temp = pd.merge(char_temp, nscp, how='left', on=sc['o_id']) # calculate p & q from b & g for all sections y = char_temp['g'] + char_temp['b'] * 1j s = char_temp['vn_kv'] ** 2 * np.conj(y) char_temp['p_temp'] = s.values.real char_temp['q_temp'] = s.values.imag # calculate cumulative sums for all sections - char_temp = char_temp.sort_values(by=['origin_id', 'sectionNumber']) - char_temp['p'] = char_temp.groupby('origin_id')['p_temp'].cumsum() - char_temp['q'] = char_temp.groupby('origin_id')['q_temp'].cumsum() + char_temp = char_temp.sort_values(by=[sc['o_id'], 'sectionNumber']) + char_temp['p'] = char_temp.groupby(sc['o_id'])['p_temp'].cumsum() + char_temp['q'] = char_temp.groupby(sc['o_id'])['q_temp'].cumsum() char_temp = char_temp.rename(columns={'p': 'p_mw', 'q': 'q_mvar', 'sectionNumber': 'step'}) char_temp['step'] = char_temp['step'].astype(int) # assign id_characteristic - char_temp['id_characteristic'] = pd.factorize(char_temp['origin_id'])[0] + char_temp['id_characteristic'] = pd.factorize(char_temp[sc['o_id']])[0] # set the id_characteristic at the corresponding shunt - id_char_dict = char_temp.drop_duplicates('origin_id').set_index('origin_id')['id_characteristic'].to_dict() - eqssh_shunts['id_characteristic_table'] = eqssh_shunts['origin_id'].map(id_char_dict).astype(int) + id_char_dict = char_temp.drop_duplicates(sc['o_id']).set_index(sc['o_id'])['id_characteristic'].to_dict() + eqssh_shunts['id_characteristic_table'] = eqssh_shunts[sc['o_id']].map(id_char_dict).astype('Int64') # create step_dependency_table flag if 'step_dependency_table' not in eqssh_shunts.columns: - eqssh_shunts["step_dependency_table"] = pd.Series(index=eqssh_shunts.index, dtype=np.bool_, data=False) + eqssh_shunts["step_dependency_table"] = False # set step_dependency_table as True for all non-linear shunt compensators eqssh_shunts.loc[eqssh_shunts['id_characteristic_table'].notna(), 'step_dependency_table'] = True # populate shunt_characteristic_temp table self.cimConverter.net['shunt_characteristic_table'] = \ char_temp[['id_characteristic', 'step', 'q_mvar', 'p_mw']] - - # moved out of converter - # def _create_shunt_characteristic_object(self, net): - # if self.cimConverter.net['shunt_characteristic_table'].index.size > 0: - # self.logger.info("Creating the step dependent power characteristic objects for shunts.") - # characteristic_df_temp = self.cimConverter.net['shunt_characteristic_table'] - # for shunt_id, shunt_row in self.cimConverter.net.shunt.dropna( - # subset=['id_characteristic_table']).iterrows(): - # shunt_characteristic_df = characteristic_df_temp.loc[ - # characteristic_df_temp['id_characteristic'] == shunt_row['id_characteristic_table']] - # for variable in ['q_mvar', 'p_mw']: - # if variable in shunt_characteristic_df.columns: - # auxiliary.create_shunt_characteristics( - # net, [shunt_id], variable, [shunt_characteristic_df['step'].to_list()], - # [shunt_characteristic_df[variable].to_list()] - # ) diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py index 101e831ad..0bc0fa665 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py @@ -45,5 +45,5 @@ def _prepare_static_var_compensator_cim16(self) -> pd.DataFrame: eq_stat_coms['max_step'] = 1 # create step_dependency_table flag if 'step_dependency_table' not in eq_stat_coms.columns: - eq_stat_coms["step_dependency_table"] = pd.Series(index=eq_stat_coms.index, dtype=np.bool_, data=False) + eq_stat_coms["step_dependency_table"] = False return eq_stat_coms diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index 9d79d9825..70c8fc6db 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -72,8 +72,8 @@ def _create_trafo_characteristic_table(self, trafo_type, trafo_df_origin): ptct_ratio = pd.merge(ptct_ratio, self.cimConverter.cim['eq']['RatioTapChangerTablePoint'][ ['RatioTapChangerTable', 'step', 'r', 'x', 'ratio']], how='left', on='RatioTapChangerTable') ptct = pd.concat([ptct, ptct_ratio], ignore_index=True, sort=False) - ptct.rename(columns={'step': 'tabular_step', 'r': 'r_dev', 'x': 'x_dev', 'TransformerEnd': sc['pte_id'], - 'ratio': 'ratio_dev', 'angle': 'angle_dev'}, inplace=True) + ptct = ptct.rename(columns={'step': 'tabular_step', 'r': 'r_dev', 'x': 'x_dev', 'TransformerEnd': sc['pte_id'], + 'ratio': 'ratio_dev', 'angle': 'angle_dev'}) ptct = ptct.drop(columns=['PhaseTapChangerTable']) if trafo_type == 'trafo': trafo_df = trafo_df_origin.sort_values(['PowerTransformer', 'endNumber']).reset_index() @@ -123,9 +123,9 @@ def _create_trafo_characteristic_table(self, trafo_type, trafo_df_origin): fillna_list = ['ratio_dev', 'angle_dev'] for one_item in fillna_list: trafo_df[one_item] = trafo_df[one_item].fillna(trafo_df[one_item + '_lv']) - trafo_df['ratio_dev'] = trafo_df['ratio_dev'].fillna(1.00000) + trafo_df['ratio_dev'] = trafo_df['ratio_dev'].fillna(1.) trafo_df['angle_dev'] = trafo_df['angle_dev'].fillna(0) - trafo_df.rename(columns={'ratio_dev': 'voltage_ratio', 'angle_dev': 'angle_deg'}, inplace=True) + trafo_df = trafo_df.rename(columns={'ratio_dev': 'voltage_ratio', 'angle_dev': 'angle_deg'}) # calculate vkr_percent and vk_percent trafo_df['vkr_percent'] = \ @@ -192,9 +192,9 @@ def _create_trafo_characteristic_table(self, trafo_type, trafo_df_origin): for one_item in fillna_list: trafo_df[one_item] = trafo_df[one_item].fillna(trafo_df[one_item + '_mv']) trafo_df[one_item] = trafo_df[one_item].fillna(trafo_df[one_item + '_lv']) - trafo_df['ratio_dev'] = trafo_df['ratio_dev'].fillna(1.00000) + trafo_df['ratio_dev'] = trafo_df['ratio_dev'].fillna(1.) trafo_df['angle_dev'] = trafo_df['angle_dev'].fillna(0) - trafo_df.rename(columns={'ratio_dev': 'voltage_ratio', 'angle_dev': 'angle_deg'}, inplace=True) + trafo_df = trafo_df.rename(columns={'ratio_dev': 'voltage_ratio', 'angle_dev': 'angle_deg'}) # calculate vkr_percent and vk_percent trafo_df['r'] = trafo_df['r'] * (1 + trafo_df['r_dev'] / 100) @@ -274,9 +274,7 @@ def append_row(res_dict, id_c, row, cols): # create tap_dependency_table flag if 'tap_dependency_table' not in trafo_df_origin.columns: - trafo_df_origin['tap_dependency_table'] = pd.Series( - index=trafo_df_origin.index, dtype=np.bool_, data=False - ) + trafo_df_origin['tap_dependency_table'] = False # set tap_dependency_table as True for respective trafos trafo_df_origin.loc[trafo_df_origin['id_characteristic_table'].notna(), 'tap_dependency_table'] = True @@ -438,8 +436,7 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: how='left', left_on='Terminal', right_on='rdfId_Terminal') # add the TapChangers power_transformers = pd.merge(power_transformers, eqssh_tap_changers, how='left', on=sc['pte_id']) - power_transformers['tap_phase_shifter_type'] = power_transformers['tap_phase_shifter_type'].apply( - lambda x: int(x) if not pd.isna(x) else x).astype('Int64') + power_transformers['tap_phase_shifter_type'] = power_transformers['tap_phase_shifter_type'].astype('Int64') return power_transformers def _prepare_trafos_cim16(self, power_trafo2w: pd.DataFrame) -> pd.DataFrame: diff --git a/pandapower/converter/cim/cim_tools.py b/pandapower/converter/cim/cim_tools.py index a909ddf60..567af5575 100644 --- a/pandapower/converter/cim/cim_tools.py +++ b/pandapower/converter/cim/cim_tools.py @@ -72,7 +72,7 @@ def extend_pp_net_cim(net: pandapowerNet, override: bool = True) -> pandapowerNe fill_dict['storage'] = dict() fill_dict['storage'][np_str_type] = [sc['t'], 'description'] fill_dict['shunt'] = dict() - fill_dict['shunt'][np_str_type] = [sc['t'], 'description', 'id_characteristic_table', 'step_dependency_table'] + fill_dict['shunt'][np_str_type] = [sc['t'], 'description'] fill_dict['ward'] = dict() fill_dict['ward'][np_str_type] = [sc['t'], 'description'] fill_dict['xward'] = dict() @@ -95,15 +95,13 @@ def extend_pp_net_cim(net: pandapowerNet, override: bool = True) -> pandapowerNe fill_dict['trafo'] = dict() fill_dict['trafo'][np_str_type] = [sc['t_hv'], sc['t_lv'], sc['pte_id_hv'], sc['pte_id_lv'], sc['tc'], sc['tc_id'], - 'description', 'vector_group', 'id_characteristic_table', - 'tap_dependency_table', 'tap_phase_shifter_type'] + 'description', 'vector_group'] fill_dict['trafo'][np_float_type] = ['vk0_percent', 'vkr0_percent', 'xn_ohm'] fill_dict['trafo'][np_bool_type] = ['power_station_unit', 'oltc'] fill_dict['trafo3w'] = dict() fill_dict['trafo3w'][np_str_type] = [sc['t_hv'], sc['t_mv'], sc['t_lv'], sc['pte_id_hv'], sc['pte_id_mv'], - sc['pte_id_lv'], sc['tc'], sc['tc_id'], 'description', 'vector_group', - 'id_characteristic_table', 'tap_dependency_table', 'tap_phase_shifter_type'] + sc['pte_id_lv'], sc['tc'], sc['tc_id'], 'description', 'vector_group'] fill_dict['trafo3w'][np_float_type] = ['vk0_hv_percent', 'vk0_mv_percent', 'vk0_lv_percent', 'vkr0_hv_percent', 'vkr0_mv_percent', 'vkr0_lv_percent'] fill_dict['trafo3w'][np_bool_type] = ['power_station_unit'] diff --git a/pandapower/converter/cim/pp_tools.py b/pandapower/converter/cim/pp_tools.py index 53de04d88..f02975b59 100644 --- a/pandapower/converter/cim/pp_tools.py +++ b/pandapower/converter/cim/pp_tools.py @@ -33,8 +33,8 @@ def set_pp_col_types(net: Union[pandapower.auxiliary.pandapowerNet, Dict], ignor time_start = time.time() pp_elements = ['bus', 'dcline', 'ext_grid', 'gen', 'impedance', 'line', 'load', 'motor', 'sgen', 'shunt', 'storage', 'switch', 'trafo', 'trafo3w', 'ward', 'xward'] - to_int = ['bus', 'element', 'to_bus', 'from_bus', 'hv_bus', 'mv_bus', 'lv_bus'] - to_bool = ['in_service', 'closed', 'tap_phase_shifter'] + to_int = ['bus', 'element', 'to_bus', 'from_bus', 'hv_bus', 'mv_bus', 'lv_bus', 'tap_phase_shifter_type'] + to_bool = ['in_service', 'closed'] logger.info("Setting the columns data types for buses to int and in_service to bool for the following elements: " "%s" % pp_elements) int_type = int diff --git a/pandapower/create.py b/pandapower/create.py index 7e98c7954..8cf5f165a 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -8,7 +8,7 @@ from typing import Tuple, List, Union, Iterable import pandas as pd -from numpy import nan, isnan, arange, dtype, isin, any as np_any, array, bool_, \ +from numpy import nan, zeros, isnan, arange, dtype, isin, any as np_any, array, bool_, \ all as np_all, float64, intersect1d, unique as uni from pandas import isnull from pandas.api.types import is_object_dtype @@ -158,6 +158,8 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("vn_kv", "f8"), ("step", "u4"), ("max_step", "u4"), + ('id_characteristic_table', 'i4'), + ('step_dependency_table', 'bool'), ("in_service", "bool")], "svc": [("name", dtype(object)), ("bus", "u4"), @@ -178,19 +180,19 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("set_vm_pu", "f8"), ("controllable", "bool"), ("in_service", "bool")], - "vsc": [("name", dtype(object)), - ("bus", "u4"), - ("bus_dc", "u4"), - ("r_ohm", "f8"), - ("x_ohm", "f8"), - ("r_dc_ohm", "f8"), - ("pl_dc_mw", "f8"), - ("control_mode_ac", dtype(object)), - ("control_value_ac", "f8"), - ("control_mode_dc", dtype(object)), - ("control_value_dc", "f8"), - ("controllable", "bool"), - ("in_service", "bool")], + "vsc": [("name", dtype(object)), + ("bus", "u4"), + ("bus_dc", "u4"), + ("r_ohm", "f8"), + ("x_ohm", "f8"), + ("r_dc_ohm", "f8"), + ("pl_dc_mw", "f8"), + ("control_mode_ac", dtype(object)), + ("control_value_ac", "f8"), + ("control_mode_dc", dtype(object)), + ("control_value_dc", "f8"), + ("controllable", "bool"), + ("in_service", "bool")], "ext_grid": [("name", dtype(object)), ("bus", "u4"), ("vm_pu", "f8"), @@ -218,7 +220,7 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("to_bus_dc", "u4"), ("length_km", "f8"), ("r_ohm_per_km", "f8"), - ("g_us_per_km", "f8"), # TODO: check if DC lines also have any shunt components + ("g_us_per_km", "f8"), # TODO: check if DC lines also have any shunt components ("max_i_ka", "f8"), ("df", "f8"), ("parallel", "u4"), @@ -244,7 +246,9 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("tap_step_percent", "f8"), ("tap_step_degree", "f8"), ("tap_pos", "i4"), - ("tap_phase_shifter", 'bool'), + ("tap_phase_shifter_type", 'i4'), + ('id_characteristic_table', 'i4'), + ('tap_dependency_table', 'bool'), ("parallel", "u4"), ("df", "f8"), ("in_service", 'bool')], @@ -277,6 +281,9 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("tap_step_degree", "f8"), ("tap_pos", "i4"), ("tap_at_star_point", 'bool'), + ("tap_phase_shifter_type", 'i4'), + ('id_characteristic_table', 'i4'), + ('tap_dependency_table', 'bool'), ("in_service", 'bool')], "impedance": [("name", dtype(object)), ("from_bus", "u4"), @@ -352,9 +359,6 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("cq1_eur_per_mvar", dtype("f8")), ("cq2_eur_per_mvar2", dtype("f8")) ], - 'characteristic': [ - ('object', dtype(object)) - ], 'controller': [ ('object', dtype(object)), ('in_service', "bool"), @@ -443,15 +447,15 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("va_internal_degree", "f8"), ("vm_pu", "f8"), ("va_degree", "f8")], - "_empty_res_vsc": [("p_mw", "f8"), - ("q_mvar", "f8"), - ("p_dc_mw", "f8"), - ("vm_internal_pu", "f8"), - ("va_internal_degree", "f8"), - ("vm_pu", "f8"), - ("va_degree", "f8"), - ("vm_internal_dc_pu", "f8"), - ("vm_dc_pu", "f8")], + "_empty_res_vsc": [("p_mw", "f8"), + ("q_mvar", "f8"), + ("p_dc_mw", "f8"), + ("vm_internal_pu", "f8"), + ("va_internal_degree", "f8"), + ("vm_pu", "f8"), + ("va_degree", "f8"), + ("vm_internal_dc_pu", "f8"), + ("vm_dc_pu", "f8")], "_empty_res_switch": [("i_ka", "f8"), ("loading_percent", "f8"), ("p_from_mw", "f8"), @@ -727,7 +731,7 @@ def create_bus(net, vn_kv, name=None, index=None, geodata=None, type="b", zone=N def create_bus_dc(net, vn_kv, name=None, index=None, geodata=None, type="b", zone=None, - in_service=True, max_vm_pu=nan, min_vm_pu=nan, coords=None, **kwargs): + in_service=True, max_vm_pu=nan, min_vm_pu=nan, coords=None, **kwargs): """ Adds one dc bus in table net["bus_dc"]. @@ -876,7 +880,7 @@ def _geodata_to_geo_series(data: Union[Iterable[Tuple[float, float]], Tuple[int, def create_buses_dc(net, nr_buses_dc, vn_kv, index=None, name=None, type="b", geodata=None, - zone=None, in_service=True, max_vm_pu=nan, min_vm_pu=nan, coords=None, **kwargs): + zone=None, in_service=True, max_vm_pu=nan, min_vm_pu=nan, coords=None, **kwargs): """ Adds several dc buses in table net["bus_dc"] at once. @@ -2483,6 +2487,7 @@ def create_line_dc(net, from_bus_dc, to_bus_dc, length_km, std_type, name=None, return index + def create_lines(net, from_buses, to_buses, length_km, std_type, name=None, index=None, geodata=None, df=1., parallel=1, in_service=True, max_loading_percent=nan, **kwargs): @@ -2614,8 +2619,8 @@ def create_lines(net, from_buses, to_buses, length_km, std_type, name=None, inde def create_lines_dc(net, from_buses_dc, to_buses_dc, length_km, std_type, name=None, index=None, - geodata=None, df=1., parallel=1, in_service=True, max_loading_percent=nan, - **kwargs): + geodata=None, df=1., parallel=1, in_service=True, max_loading_percent=nan, + **kwargs): """ Convenience function for creating many dc lines at once. Parameters 'from_buses_dc' and 'to_buses_dc' must be arrays of equal length. Other parameters may be either arrays of the same length or single or values. In any case the dc line parameters are defined through a single standard @@ -2694,7 +2699,8 @@ def create_lines_dc(net, from_buses_dc, to_buses_dc, length_km, std_type, name=N std_type="Not specified yet") """ - _check_multiple_branch_elements(net, from_buses_dc, to_buses_dc, "Lines_dc", node_name='bus_dc', plural='(all dc buses)') + _check_multiple_branch_elements(net, from_buses_dc, to_buses_dc, "Lines_dc", node_name='bus_dc', + plural='(all dc buses)') index = _get_multiple_index_with_check(net, "line_dc", index, len(from_buses_dc)) @@ -2712,7 +2718,7 @@ def create_lines_dc(net, from_buses_dc, to_buses_dc, length_km, std_type, name=N entries["type"] = lineparam["type"] else: lineparam = list(map(load_std_type, [net] * len(std_type), std_type, - ['line_dc'] * len(std_type))) + ['line_dc'] * len(std_type))) entries["r_ohm_per_km"] = list(map(itemgetter("r_ohm_per_km"), lineparam)) entries["max_i_ka"] = list(map(itemgetter("max_i_ka"), lineparam)) entries["g_us_per_km"] = [line_param_dict.get("g_us_per_km", 0) for line_param_dict in lineparam] @@ -2737,6 +2743,7 @@ def create_lines_dc(net, from_buses_dc, to_buses_dc, length_km, std_type, name=N return index + def create_line_from_parameters(net, from_bus, to_bus, length_km, r_ohm_per_km, x_ohm_per_km, c_nf_per_km, max_i_ka, name=None, index=None, type=None, geodata=None, in_service=True, df=1., parallel=1, g_us_per_km=0., @@ -3151,8 +3158,9 @@ def create_lines_from_parameters(net, from_buses, to_buses, length_km, r_ohm_per def create_lines_dc_from_parameters(net, from_buses_dc, to_buses_dc, length_km, r_ohm_per_km, - max_i_ka, name=None, index=None, type=None,geodata=None, - in_service=True, df=1., parallel=1, g_us_per_km=0., max_loading_percent=nan, alpha=nan, + max_i_ka, name=None, index=None, type=None, geodata=None, + in_service=True, df=1., parallel=1, g_us_per_km=0., max_loading_percent=nan, + alpha=nan, temperature_degree_celsius=nan, **kwargs): """ Convenience function for creating many dc lines at once. Parameters 'from_buses_dc' and 'to_buses_dc' @@ -3232,11 +3240,12 @@ def create_lines_dc_from_parameters(net, from_buses_dc, to_buses_dc, length_km, **index** (list of int) - The unique ID of the created dc lines EXAMPLE: - create_lines_dc_from_parameters(net, name= ["line_dc1","line_dc2"], from_buses_dc = [0,1], to_buses_dc = [2,3], lenght_km=0.1, - r_ohm_per_km = .01, max_i_ka = 0.4) + create_lines_dc_from_parameters(net, name= ["line_dc1","line_dc2"], from_buses_dc = [0,1], to_buses_dc = [2,3], + length_km=0.1, r_ohm_per_km = .01, max_i_ka = 0.4) """ - _check_multiple_branch_elements(net, from_buses_dc, to_buses_dc, "Lines_dc",node_name='bus_dc', plural= '(all dc buses)') + _check_multiple_branch_elements(net, from_buses_dc, to_buses_dc, "Lines_dc", node_name='bus_dc', + plural='(all dc buses)') index = _get_multiple_index_with_check(net, "line", index, len(from_buses_dc)) @@ -3272,9 +3281,8 @@ def create_lines_dc_from_parameters(net, from_buses_dc, to_buses_dc, length_km, def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in_service=True, index=None, max_loading_percent=nan, parallel=1, df=1., - tap_dependent_impedance=nan, vk_percent_characteristic=None, - vkr_percent_characteristic=None, pt_percent=nan, oltc=nan, xn_ohm=nan, - tap2_pos=nan, **kwargs): + tap_dependency_table=nan, id_characteristic_table = nan, + pt_percent=nan, oltc=nan, xn_ohm=nan, tap2_pos=nan, **kwargs): """ Creates a two-winding transformer in table net["trafo"]. The trafo parameters are defined through the standard type library. @@ -3322,21 +3330,14 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in **df** (float) - derating factor: maximal current of transformer in relation to nominal \ current of transformer (from 0 to 1) - **tap_dependent_impedance** (boolean) - True if transformer impedance must be adjusted dependent \ - on the tap position of the trabnsformer. Requires the additional columns \ - "vk_percent_characteristic" and "vkr_percent_characteristic" that reference the index of the \ - characteristic from the table net.characteristic. A convenience function \ - pandapower.control.create_trafo_characteristics can be used to create the SplineCharacteristic \ - objects, add the relevant columns and set up the references to the characteristics. \ - The function pandapower.control.trafo_characteristics_diagnostic can be used for sanity checks. - - **vk_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. + **tap_dependency_table** (boolean) - True if transformer characteristics (voltage ratio, angle, impedance) \ + must be adjusted dependent on the tap position of the transformer. Requires the additional column \ + "id_characteristic_table" - **vkr_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. + **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ + net.trafo_characteristic_table - **xn_ohm** (float) - impedance of the grounding reactor (Z_N) for shor tcircuit calculation + **xn_ohm** (float) - impedance of the grounding reactor (Z_N) for short circuit calculation **tap2_pos** (int, float, nan) - current tap position of the second tap changer of the transformer. \ Defaults to the medium position (tap2_neutral) @@ -3374,12 +3375,10 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in "parallel": parallel, "df": df, "shift_degree": ti["shift_degree"] if "shift_degree" in ti else 0, - "tap_phase_shifter": ti["tap_phase_shifter"] if "tap_phase_shifter" in ti - and pd.notnull( - ti["tap_phase_shifter"]) else False + "tap_phase_shifter_type": ti["tap_phase_shifter_type"] if "tap_phase_shifter_type" in ti else nan } - if "tap2_phase_shifter" in ti and pd.notnull(ti["tap2_phase_shifter"]): - updates["tap2_phase_shifter"] = ti["tap2_phase_shifter"] + if "tap2_phase_shifter_type" in ti: + updates["tap2_phase_shifter_type"] = ti["tap2_phase_shifter_type"] for zero_param in ['vk0_percent', 'vkr0_percent', 'mag0_percent', 'mag0_rx', 'si0_hv_partial']: if zero_param in ti: updates[zero_param] = ti[zero_param] @@ -3400,21 +3399,14 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in _set_entries(net, "trafo", index, **v, **kwargs) _set_value_if_not_nan(net, index, max_loading_percent, "max_loading_percent", "trafo") - _set_value_if_not_nan(net, index, tap_dependent_impedance, "tap_dependent_impedance", + _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo", dtype=bool_, default_val=False) - _set_value_if_not_nan(net, index, vk_percent_characteristic, - "vk_percent_characteristic", "trafo", "Int64") - _set_value_if_not_nan(net, index, vkr_percent_characteristic, - "vkr_percent_characteristic", "trafo", "Int64") + _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", + "trafo", dtype="Int64") _set_value_if_not_nan(net, index, pt_percent, "pt_percent", "trafo") _set_value_if_not_nan(net, index, oltc, "oltc", "trafo", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, xn_ohm, "xn_ohm", "trafo") - # tap_phase_shifter default False - net.trafo.tap_phase_shifter = net.trafo.tap_phase_shifter.fillna(False) - if "tap2_phase_shifter" in net.trafo.columns: - net.trafo.tap2_phase_shifter = net.trafo.tap2_phase_shifter.fillna(False).astype(bool_) - return index @@ -3423,19 +3415,16 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn shift_degree=0, tap_side=None, tap_neutral=nan, tap_max=nan, tap_min=nan, tap_step_percent=nan, tap_step_degree=nan, - tap_pos=nan, tap_phase_shifter=False, in_service=True, - name=None, vector_group=None, index=None, + tap_pos=nan, tap_phase_shifter_type=nan, id_characteristic_table=nan, + in_service=True, name=None, vector_group=None, index=None, max_loading_percent=nan, parallel=1, df=1., vk0_percent=nan, vkr0_percent=nan, mag0_percent=nan, mag0_rx=nan, si0_hv_partial=nan, - pt_percent=nan, oltc=nan, tap_dependent_impedance=nan, - vk_percent_characteristic=None, - vkr_percent_characteristic=None, xn_ohm=nan, - tap2_side=None, tap2_neutral=nan, tap2_max=nan, + pt_percent=nan, oltc=nan, tap_dependency_table=nan, + xn_ohm=nan, tap2_side=None, tap2_neutral=nan, tap2_max=nan, tap2_min=nan, tap2_step_percent=nan, tap2_step_degree=nan, - tap2_pos=nan, tap2_phase_shifter=nan, - **kwargs): + tap2_pos=nan, tap2_phase_shifter_type=nan, **kwargs): """ Creates a two-winding transformer in table net["trafo"]. The trafo parameters are defined through the standard type library. @@ -3474,7 +3463,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **mag0_percent** - zero sequence magnetizing impedance/ vk0 - **mag0_rx** - zero sequence magnitizing R/X ratio + **mag0_rx** - zero sequence magnetizing R/X ratio **si0_hv_partial** - Distribution of zero sequence leakage impedances for HV side @@ -3505,7 +3494,8 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **tap_step_degree** (float) - tap step size for voltage angle in degree* - **tap_phase_shifter** (bool) - whether the transformer is an ideal phase shifter* + **tap_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + 1: Symmetrical, 2: Ideal)* **index** (int, None) - Force a specified ID if it is available. If None, the index one \ higher than the highest already existing index is selected. @@ -3515,25 +3505,18 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **df** (float) - derating factor: maximal current of transformer in relation to nominal \ current of transformer (from 0 to 1) - **tap_dependent_impedance** (boolean) - True if transformer impedance must be adjusted dependent \ - on the tap position of the trabnsformer. Requires the additional columns \ - "vk_percent_characteristic" and "vkr_percent_characteristic" that reference the index of the \ - characteristic from the table net.characteristic. A convenience function \ - pandapower.control.create_trafo_characteristics can be used to create the SplineCharacteristic \ - objects, add the relevant columns and set up the references to the characteristics. \ - The function pandapower.control.trafo_characteristics_diagnostic can be used for sanity checks. + **tap_dependency_table** (boolean) - True if transformer characteristics (voltage ratio, angle, impedance) \ + must be adjusted dependent on the tap position of the transformer. Requires the additional column \ + "id_characteristic_table" - **vk_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vkr_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. + **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ + net.trafo_characteristic_table **pt_percent** (float, nan) - (short circuit only) **oltc** (bool, False) - (short circuit only) - **xn_ohm** (float) - impedance of the grounding reactor (Z_N) for shor tcircuit calculation + **xn_ohm** (float) - impedance of the grounding reactor (Z_N) for short circuit calculation **tap2_side** (string) - position of the second tap changer ("hv", "lv") @@ -3551,7 +3534,8 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **tap2_step_degree** (float) - second tap step size for voltage angle in degree* - **tap2_phase_shifter** (bool) - whether the transformer is an ideal phase shifter* + **tap2_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + 1: Symmetrical, 2: Ideal)* **leakage_resistance_ratio_hv** (bool) - ratio of transformer short-circuit resistance on HV side (default 0.5) @@ -3587,8 +3571,8 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn "pfe_kw": pfe_kw, "i0_percent": i0_percent, "tap_neutral": tap_neutral, "tap_max": tap_max, "tap_min": tap_min, "shift_degree": shift_degree, "tap_side": tap_side, "tap_step_percent": tap_step_percent, - "tap_step_degree": tap_step_degree, - "tap_phase_shifter": tap_phase_shifter, "parallel": parallel, "df": df} + "tap_step_degree": tap_step_degree, "tap_phase_shifter_type": tap_phase_shifter_type, + "parallel": parallel, "df": df} if ("tap_neutral" in v) and (tap_pos is nan): v["tap_pos"] = v["tap_neutral"] @@ -3600,22 +3584,22 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn v.update(kwargs) _set_entries(net, "trafo", index, **v) - _set_value_if_not_nan(net, index, tap_dependent_impedance, - "tap_dependent_impedance", "trafo", dtype=bool_, default_val=False) - _set_value_if_not_nan(net, index, vk_percent_characteristic, - "vk_percent_characteristic", "trafo", "Int64") - _set_value_if_not_nan(net, index, vkr_percent_characteristic, - "vkr_percent_characteristic", "trafo", "Int64") + _set_value_if_not_nan(net, index, tap_dependency_table, + "tap_dependency_table", "trafo", dtype=bool_, default_val=False) + _set_value_if_not_nan(net, index, id_characteristic_table, + "id_characteristic_table", "trafo", dtype="Int64") _set_value_if_not_nan(net, index, tap2_side, "tap2_side", "trafo", dtype=str) _set_value_if_not_nan(net, index, tap2_neutral, "tap2_neutral", "trafo", dtype=np.float64) _set_value_if_not_nan(net, index, tap2_min, "tap2_min", "trafo", dtype=np.float64) _set_value_if_not_nan(net, index, tap2_max, "tap2_max", "trafo", dtype=np.float64) - _set_value_if_not_nan(net, index, tap2_step_percent, "tap2_step_percent", "trafo", dtype=np.float64) + _set_value_if_not_nan(net, index, tap2_step_percent, "tap2_step_percent", + "trafo", dtype=np.float64) _set_value_if_not_nan(net, index, tap2_step_degree, "tap2_step_degree", "trafo", dtype=np.float64) _set_value_if_not_nan(net, index, tap2_pos if pd.notnull(tap2_pos) else tap2_neutral, "tap2_pos", "trafo", dtype=np.float64) - _set_value_if_not_nan(net, index, tap2_phase_shifter, "tap2_phase_shifter", "trafo", dtype=bool_) + _set_value_if_not_nan(net, index, tap2_phase_shifter_type, "tap2_phase_shifter_type", + "trafo", dtype="Int64") if not (isnan(vk0_percent) and isnan(vkr0_percent) and isnan(mag0_percent) and isnan(mag0_rx) and isnan(si0_hv_partial) and vector_group is None): @@ -3637,16 +3621,14 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k vkr_percent, vk_percent, pfe_kw, i0_percent, shift_degree=0, tap_side=None, tap_neutral=nan, tap_max=nan, tap_min=nan, tap_step_percent=nan, tap_step_degree=nan, tap_pos=nan, - tap_phase_shifter=False, in_service=True, name=None, - vector_group=None, index=None, max_loading_percent=nan, + tap_phase_shifter_type=nan, id_characteristic_table=nan, in_service=True, + name=None, vector_group=None, index=None, max_loading_percent=nan, parallel=1, df=1., vk0_percent=nan, vkr0_percent=nan, mag0_percent=nan, mag0_rx=nan, si0_hv_partial=nan, - pt_percent=nan, oltc=nan, tap_dependent_impedance=nan, - vk_percent_characteristic=None, - vkr_percent_characteristic=None, xn_ohm=nan, - tap2_side=None, tap2_neutral=nan, tap2_max=nan, + pt_percent=nan, oltc=nan, tap_dependency_table=nan, + xn_ohm=nan, tap2_side=None, tap2_neutral=nan, tap2_max=nan, tap2_min=nan, tap2_step_percent=nan, tap2_step_degree=nan, - tap2_pos=nan, tap2_phase_shifter=nan, + tap2_pos=nan, tap2_phase_shifter_type=nan, **kwargs): """ Creates several two-winding transformers in table net["trafo"]. @@ -3686,7 +3668,7 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k **mag0_percent** - (list of float) zero sequence magnetizing impedance/ vk0 - **mag0_rx** - (list of float) zero sequence magnitizing R/X ratio + **mag0_rx** - (list of float) zero sequence magnetizing R/X ratio **si0_hv_partial** - (list of float) Distribution of zero sequence leakage impedances for \ HV side @@ -3718,7 +3700,8 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k **tap_step_degree** (float) - tap step size for voltage angle in degree* - **tap_phase_shifter** (bool) - whether the transformer is an ideal phase shifter* + **tap_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + 1: Symmetrical, 2: Ideal)* **index** (int, None) - Force a specified ID if it is available. If None, the index one \ higher than the highest already existing index is selected. @@ -3728,25 +3711,18 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k **df** (float) - derating factor: maximal current of transformer in relation to nominal \ current of transformer (from 0 to 1) - **tap_dependent_impedance** (boolean) - True if transformer impedance must be adjusted dependent \ - on the tap position of the trabnsformer. Requires the additional columns \ - "vk_percent_characteristic" and "vkr_percent_characteristic" that reference the index of the \ - characteristic from the table net.characteristic. A convenience function \ - pandapower.control.create_trafo_characteristics can be used to create the SplineCharacteristic \ - objects, add the relevant columns and set up the references to the characteristics. \ - The function pandapower.control.trafo_characteristics_diagnostic can be used for sanity checks. - - **vk_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. + **tap_dependency_table** (boolean) - True if transformer characteristics (voltage ratio, angle, impedance) \ + must be adjusted dependent on the tap position of the transformer. Requires the additional column \ + "id_characteristic_table" - **vkr_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. + **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ + net.trafo_characteristic_table **pt_percent** (float, nan) - (short circuit only) **oltc** (bool, False) - (short circuit only) - **xn_ohm** (float) - impedance of the grounding reactor (Z_N) for shor tcircuit calculation + **xn_ohm** (float) - impedance of the grounding reactor (Z_N) for short circuit calculation **tap2_side** (string) - position of the second tap changer ("hv", "lv") @@ -3764,7 +3740,8 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k **tap2_step_degree** (float) - second tap step size for voltage angle in degree* - **tap2_phase_shifter** (bool) - whether the transformer is an ideal phase shifter* + **tap2_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + 1: Symmetrical, 2: Ideal)* ** only considered in loadflow if calculate_voltage_angles = True @@ -3789,14 +3766,12 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k "tap_neutral": tp_neutral, "tap_max": tap_max, "tap_min": tap_min, "shift_degree": shift_degree, "tap_pos": tp_pos, "tap_side": tap_side, "tap_step_percent": tap_step_percent, "tap_step_degree": tap_step_degree, - "tap_phase_shifter": tap_phase_shifter, "parallel": parallel, "df": df} + "tap_phase_shifter_type": tap_phase_shifter_type, "parallel": parallel, "df": df} - _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap_dependent_impedance", - tap_dependent_impedance, dtype=bool_, default_val=False) - _add_to_entries_if_not_nan(net, "trafo", entries, index, "vk_percent_characteristic", - vk_percent_characteristic, "Int64") - _add_to_entries_if_not_nan(net, "trafo", entries, index, "vkr_percent_characteristic", - vkr_percent_characteristic, "Int64") + _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap_dependency_table", + tap_dependency_table, dtype=bool_, default_val=False) + _add_to_entries_if_not_nan(net, "trafo", entries, index, "id_characteristic_table", + id_characteristic_table, dtype="Int64") _add_to_entries_if_not_nan(net, "trafo", entries, index, "vk0_percent", vk0_percent) _add_to_entries_if_not_nan(net, "trafo", entries, index, "vkr0_percent", vkr0_percent) @@ -3816,9 +3791,10 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_step_percent", tap2_step_percent) _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_step_degree", tap2_step_degree) _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_pos", tap2_pos) - _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_phase_shifter", tap2_phase_shifter, dtype=bool_) + _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_phase_shifter_type", + tap2_phase_shifter_type, dtype="Int64") - defaults_to_fill = [("tap_dependent_impedance", False)] + defaults_to_fill = [("tap_dependency_table", False)] _set_multiple_entries(net, "trafo", index, defaults_to_fill=defaults_to_fill, **entries, **kwargs) @@ -3827,11 +3803,7 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_pos=nan, in_service=True, index=None, max_loading_percent=nan, - tap_at_star_point=False, tap_dependent_impedance=nan, - vk_hv_percent_characteristic=None, vkr_hv_percent_characteristic=None, - vk_mv_percent_characteristic=None, vkr_mv_percent_characteristic=None, - vk_lv_percent_characteristic=None, vkr_lv_percent_characteristic=None, - **kwargs): + tap_at_star_point=False, tap_dependency_table=nan, id_characteristic_table=nan, **kwargs): """ Creates a three-winding transformer in table net["trafo3w"]. The trafo parameters are defined through the standard type library. @@ -3867,31 +3839,12 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p **tap_at_star_point (bool)** - whether tap changer is modelled at star point or at the bus - **tap_dependent_impedance** (boolean) - True if transformer impedance must be adjusted dependent \ - on the tap position of the trabnsformer. Requires the additional columns \ - "vk_percent_characteristic" and "vkr_percent_characteristic" that reference the index of the \ - characteristic from the table net.characteristic. A convenience function \ - pandapower.control.create_trafo_characteristics can be used to create the SplineCharacteristic \ - objects, add the relevant columns and set up the references to the characteristics. \ - The function pandapower.control.trafo_characteristics_diagnostic can be used for sanity checks. - - **vk_hv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vkr_hv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vk_mv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vkr_mv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vk_lv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. + **tap_dependency_table** (boolean) - True if transformer characteristics (voltage ratio, angle, impedance) \ + must be adjusted dependent on the tap position of the transformer. Requires the additional column \ + "id_characteristic_table" - **vkr_lv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. + **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ + net.trafo_characteristic_table OUTPUT: **index** (int) - The unique ID of the created transformer @@ -3950,20 +3903,10 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p net["trafo3w"].columns, axis=1) _set_value_if_not_nan(net, index, max_loading_percent, "max_loading_percent", "trafo3w") - _set_value_if_not_nan(net, index, tap_dependent_impedance, - "tap_dependent_impedance", "trafo3w", dtype=bool_, default_val=False) - _set_value_if_not_nan(net, index, vk_hv_percent_characteristic, - "vk_hv_percent_characteristic", "trafo3w", "Int64") - _set_value_if_not_nan(net, index, vkr_hv_percent_characteristic, - "vkr_hv_percent_characteristic", "trafo3w", "Int64") - _set_value_if_not_nan(net, index, vk_mv_percent_characteristic, - "vk_mv_percent_characteristic", "trafo3w", "Int64") - _set_value_if_not_nan(net, index, vkr_mv_percent_characteristic, - "vkr_mv_percent_characteristic", "trafo3w", "Int64") - _set_value_if_not_nan(net, index, vk_lv_percent_characteristic, - "vk_lv_percent_characteristic", "trafo3w", "Int64") - _set_value_if_not_nan(net, index, vkr_lv_percent_characteristic, - "vkr_lv_percent_characteristic", "trafo3w", "Int64") + _set_value_if_not_nan(net, index, tap_dependency_table, + "tap_dependency_table", "trafo3w", dtype=bool_, default_val=False) + _set_value_if_not_nan(net, index, id_characteristic_table, + "id_characteristic_table", "trafo3w", dtype="Int64") return index @@ -3980,10 +3923,7 @@ def create_transformer3w_from_parameters( max_loading_percent=nan, tap_at_star_point=False, vk0_hv_percent=nan, vk0_mv_percent=nan, vk0_lv_percent=nan, vkr0_hv_percent=nan, vkr0_mv_percent=nan, vkr0_lv_percent=nan, - vector_group=None, tap_dependent_impedance=nan, - vk_hv_percent_characteristic=None, vkr_hv_percent_characteristic=None, - vk_mv_percent_characteristic=None, vkr_mv_percent_characteristic=None, - vk_lv_percent_characteristic=None, vkr_lv_percent_characteristic=None, **kwargs): + vector_group=None, tap_dependency_table=nan, id_characteristic_table=nan, **kwargs): """ Adds a three-winding transformer in table net["trafo3w"]. The model currently only supports one tap-changer per 3W Transformer. @@ -4057,31 +3997,12 @@ def create_transformer3w_from_parameters( **max_loading_percent (float)** - maximum current loading (only needed for OPF) - **tap_dependent_impedance** (boolean) - True if transformer impedance must be adjusted dependent \ - on the tap position of the trabnsformer. Requires the additional columns \ - "vk_percent_characteristic" and "vkr_percent_characteristic" that reference the index of the \ - characteristic from the table net.characteristic. A convenience function \ - pandapower.control.create_trafo_characteristics can be used to create the SplineCharacteristic \ - objects, add the relevant columns and set up the references to the characteristics. \ - The function pandapower.control.trafo_characteristics_diagnostic can be used for sanity checks. + **tap_dependency_table** (boolean) - True if transformer characteristics (voltage ratio, angle, impedance) \ + must be adjusted dependent on the tap position of the transformer. Requires the additional column \ + "id_characteristic_table" - **vk_hv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vkr_hv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vk_mv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vkr_mv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vk_lv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vkr_lv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. + **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ + net.trafo_characteristic_table **vk0_hv_percent** (float) - zero sequence short circuit voltage from high to medium voltage @@ -4137,20 +4058,10 @@ def create_transformer3w_from_parameters( _set_entries(net, "trafo3w", index, **dict(zip(columns, values)), **kwargs) _set_value_if_not_nan(net, index, max_loading_percent, "max_loading_percent", "trafo3w") - _set_value_if_not_nan(net, index, tap_dependent_impedance, - "tap_dependent_impedance", "trafo3w", dtype=bool_, default_val=False) - _set_value_if_not_nan(net, index, vk_hv_percent_characteristic, - "vk_hv_percent_characteristic", "trafo3w", "Int64") - _set_value_if_not_nan(net, index, vkr_hv_percent_characteristic, - "vkr_hv_percent_characteristic", "trafo3w", "Int64") - _set_value_if_not_nan(net, index, vk_mv_percent_characteristic, - "vk_mv_percent_characteristic", "trafo3w", "Int64") - _set_value_if_not_nan(net, index, vkr_mv_percent_characteristic, - "vkr_mv_percent_characteristic", "trafo3w", "Int64") - _set_value_if_not_nan(net, index, vk_lv_percent_characteristic, - "vk_lv_percent_characteristic", "trafo3w", "Int64") - _set_value_if_not_nan(net, index, vkr_lv_percent_characteristic, - "vkr_lv_percent_characteristic", "trafo3w", "Int64") + _set_value_if_not_nan(net, index, tap_dependency_table, + "tap_dependency_table", "trafo3w", dtype=bool_, default_val=False) + _set_value_if_not_nan(net, index, id_characteristic_table, + "id_characteristic_table", "trafo3w", dtype="Int64") return index @@ -4167,10 +4078,7 @@ def create_transformers3w_from_parameters( tap_at_star_point=False, vk0_hv_percent=nan, vk0_mv_percent=nan, vk0_lv_percent=nan, vkr0_hv_percent=nan, vkr0_mv_percent=nan, vkr0_lv_percent=nan, - vector_group=None, tap_dependent_impedance=nan, - vk_hv_percent_characteristic=None, vkr_hv_percent_characteristic=None, - vk_mv_percent_characteristic=None, vkr_mv_percent_characteristic=None, - vk_lv_percent_characteristic=None, vkr_lv_percent_characteristic=None, **kwargs): + vector_group=None, tap_dependency_table=nan, id_characteristic_table=nan, **kwargs): """ Adds a three-winding transformer in table net["trafo3w"]. @@ -4249,31 +4157,12 @@ def create_transformers3w_from_parameters( **max_loading_percent (float)** - maximum current loading (only needed for OPF) - **tap_dependent_impedance** (boolean) - True if transformer impedance must be adjusted dependent \ - on the tap position of the trabnsformer. Requires the additional columns \ - "vk_percent_characteristic" and "vkr_percent_characteristic" that reference the index of the \ - characteristic from the table net.characteristic. A convenience function \ - pandapower.control.create_trafo_characteristics can be used to create the SplineCharacteristic \ - objects, add the relevant columns and set up the references to the characteristics. \ - The function pandapower.control.trafo_characteristics_diagnostic can be used for sanity checks. - - **vk_hv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. + **tap_dependency_table** (boolean) - True if transformer characteristics (voltage ratio, angle, impedance) \ + must be adjusted dependent on the tap position of the transformer. Requires the additional column \ + "id_characteristic_table" - **vkr_hv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vk_mv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vkr_mv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vk_lv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. - - **vkr_lv_percent_characteristic** (int) - index of the characteristic from net.characteristic for \ - the adjustment of the parameter "vk_percent" for the calculation of tap dependent impedance. + **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ + net.trafo_characteristic_table **vk0_hv_percent** (float) - zero sequence short circuit voltage from high to medium voltage @@ -4334,21 +4223,11 @@ def create_transformers3w_from_parameters( _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "max_loading_percent", max_loading_percent) - _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "tap_dependent_impedance", - tap_dependent_impedance, dtype=bool_, default_val=False) - _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "vk_hv_percent_characteristic", - vk_hv_percent_characteristic, "Int64") - _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "vkr_hv_percent_characteristic", - vkr_hv_percent_characteristic, "Int64") - _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "vk_mv_percent_characteristic", - vk_mv_percent_characteristic, "Int64") - _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "vkr_mv_percent_characteristic", - vkr_mv_percent_characteristic, "Int64") - _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "vk_lv_percent_characteristic", - vk_lv_percent_characteristic, "Int64") - _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "vkr_lv_percent_characteristic", - vkr_lv_percent_characteristic, "Int64") - defaults_to_fill = [("tap_dependent_impedance", False)] + _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "tap_dependency_table", + tap_dependency_table, dtype=bool_, default_val=False) + _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "id_characteristic_table", + id_characteristic_table, dtype="Int64") + defaults_to_fill = [("tap_dependency_table", False)] _set_multiple_entries(net, "trafo3w", index, defaults_to_fill=defaults_to_fill, **entries, **kwargs) @@ -4929,8 +4808,7 @@ def create_impedance(net, from_bus, to_bus, rft_pu, xft_pu, sn_mva, rtf_pu=None, UserWarning If required impedance parameters are missing. """ - - + index = _get_index_with_check(net, "impedance", index) _check_branch_element(net, "Impedance", index, from_bus, to_bus) @@ -4982,11 +4860,12 @@ def create_impedance(net, from_bus, to_bus, rft_pu, xft_pu, sn_mva, rtf_pu=None, return index + def create_impedances(net, from_buses, to_buses, rft_pu, xft_pu, sn_mva, rtf_pu=None, xtf_pu=None, - name=None, in_service=True, index=None, - rft0_pu=None, xft0_pu=None, rtf0_pu=None, xtf0_pu=None, - gf_pu=0, bf_pu=0, gt_pu=None, bt_pu=None, - gf0_pu=None, bf0_pu=None, gt0_pu=None, bt0_pu=None, **kwargs): + name=None, in_service=True, index=None, + rft0_pu=None, xft0_pu=None, rtf0_pu=None, xtf0_pu=None, + gf_pu=0, bf_pu=0, gt_pu=None, bt_pu=None, + gf0_pu=None, bf0_pu=None, gt0_pu=None, bt0_pu=None, **kwargs): """ Creates an impedance element in per unit (pu). @@ -5111,7 +4990,7 @@ def create_impedances(net, from_buses, to_buses, rft_pu, xft_pu, sn_mva, rtf_pu= entries = dict(zip(columns, values)) _set_multiple_entries(net, "impedance", index, **entries, **kwargs) - + if rft0_pu is not None: _set_value_if_not_nan(net, index, rft0_pu, "rft0_pu", "impedance") _set_value_if_not_nan(net, index, xft0_pu, "xft0_pu", "impedance") @@ -5127,7 +5006,6 @@ def create_impedances(net, from_buses, to_buses, rft_pu, xft_pu, sn_mva, rtf_pu= return index - def create_tcsc(net, from_bus, to_bus, x_l_ohm, x_cvar_ohm, set_p_to_mw, thyristor_firing_angle_degree, name=None, controllable=True, in_service=True, index=None, @@ -6014,7 +5892,6 @@ def _add_to_entries_if_not_nan(net, element_type, entries, index, column, values try_astype(entries, column, dtype) - def _add_multiple_branch_geodata(net, geodata, index, table="line"): dtypes = net[table].dtypes if hasattr(geodata, '__iter__') and all([isinstance(g, tuple) and len(g) == 2 for g in geodata]): @@ -6026,7 +5903,8 @@ def _add_multiple_branch_geodata(net, geodata, index, table="line"): geo = [[[x, y] for x, y in g] for g in geodata] series = pd.Series([f'{{"coordinates": {g}, "type": "LineString"}}' for g in geo], index=index) else: - raise ValueError("geodata must be an Iterable of Iterable of coordinate tuples or an Iterable of coordinate tuples") + raise ValueError( + "geodata must be an Iterable of Iterable of coordinate tuples or an Iterable of coordinate tuples") net[table].loc[:, "geo"] = series diff --git a/pandapower/std_types.py b/pandapower/std_types.py index 612504653..4554ca009 100644 --- a/pandapower/std_types.py +++ b/pandapower/std_types.py @@ -51,7 +51,7 @@ def create_std_type(net, data, name, element="line", overwrite=True, check_requi "endtemp_degree": 70.0, "r0_ohm_per_km": 0.7766, "x0_ohm_per_km": 0.2990796, "c0_nf_per_km": 496.2}, name="unsymmetric_line_type",element = "line") - >>> #Three phase transformer creation + >>> # Three phase transformer creation >>> pp.create_std_type(net, {"sn_mva": 1.6, "vn_hv_kv": 10, "vn_lv_kv": 0.4, @@ -67,7 +67,7 @@ def create_std_type(net, data, name, element="line", overwrite=True, check_requi "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": False, + "tap_phase_shifter_type": 0, "vk0_percent": 6, "vkr0_percent": 0.78125, "mag0_percent": 100, @@ -984,7 +984,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": False}, + "tap_phase_shifter_type": 0}, "100 MVA 220/110 kV": {"i0_percent": 0.06, "pfe_kw": 55, @@ -1001,7 +1001,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": False}, + "tap_phase_shifter_type": 0}, # compare to IFT Ingenieurbüro data and Schlabbach book "63 MVA 110/20 kV": @@ -1020,7 +1020,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": False}, + "tap_phase_shifter_type": 0}, "40 MVA 110/20 kV": {"i0_percent": 0.05, "pfe_kw": 18, @@ -1037,7 +1037,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": False}, + "tap_phase_shifter_type": 0}, "25 MVA 110/20 kV": {"i0_percent": 0.07, "pfe_kw": 14, @@ -1054,7 +1054,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": False}, + "tap_phase_shifter_type": 0}, "63 MVA 110/10 kV": {"sn_mva": 63, "vn_hv_kv": 110, @@ -1071,7 +1071,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": False}, + "tap_phase_shifter_type": 0}, "40 MVA 110/10 kV": {"sn_mva": 40, "vn_hv_kv": 110, @@ -1088,7 +1088,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": False}, + "tap_phase_shifter_type": 0}, "25 MVA 110/10 kV": {"sn_mva": 25, "vn_hv_kv": 110, @@ -1105,8 +1105,8 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": False}, - # Tafo20/0.4 + "tap_phase_shifter_type": 0}, + # Trafo 20/0.4 # 0.25 MVA 20/0.4 kV 0.45 Trafo Union "0.25 MVA 20/0.4 kV": {"sn_mva": 0.25, @@ -1124,7 +1124,7 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": False}, + "tap_phase_shifter_type": 0}, # 0.4 MVA 20/0.4 kV Trafo Union "0.4 MVA 20/0.4 kV": {"sn_mva": 0.4, "vn_hv_kv": 20, "vn_lv_kv": 0.4, @@ -1140,7 +1140,7 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": False}, + "tap_phase_shifter_type": 0}, # 0.63 MVA 20/0.4 kV Trafo Union "0.63 MVA 20/0.4 kV": {"sn_mva": 0.63, @@ -1158,8 +1158,8 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": False}, - # Tafo10/0.4: + "tap_phase_shifter_type": 0}, + # Trafo 10/0.4: # 0.25 MVA 10/0.4 kV 0.4 Trafo Union wnr "0.25 MVA 10/0.4 kV": {"sn_mva": 0.25, @@ -1177,7 +1177,7 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": False}, + "tap_phase_shifter_type": 0}, # 0.4 MVA 10/0.4 kV Trafo Union wnr "0.4 MVA 10/0.4 kV": {"sn_mva": 0.4, @@ -1195,7 +1195,7 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": False}, + "tap_phase_shifter_type": 0}, # 0.63 MVA 10/0.4 kV Trafo Union wnr "0.63 MVA 10/0.4 kV": {"sn_mva": 0.63, @@ -1213,7 +1213,7 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": False}, + "tap_phase_shifter_type": 0}, } return trafotypes diff --git a/pandapower/test/control/test_tap_dependent_impedance.py b/pandapower/test/control/test_tap_dependent_impedance.py index 1833dd26c..1529a8990 100644 --- a/pandapower/test/control/test_tap_dependent_impedance.py +++ b/pandapower/test/control/test_tap_dependent_impedance.py @@ -12,7 +12,7 @@ trafo_characteristics_diagnostic -# todo add tests for voltage_ratio and angle_dev? +# todo add tests for voltage_ratio and angle_dev def test_tap_dependent_impedance_control(): net = pp.create_empty_network() b1 = pp.create_bus(net, 110) From 56602854361fc70b73f7274214aa4fa24d0cc2b5 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 28 Nov 2024 11:31:02 +0200 Subject: [PATCH 013/125] update pp_tools.py; update create.py lib for trafo/trafo3w & shunt parameter changes --- pandapower/converter/cim/pp_tools.py | 2 +- pandapower/create.py | 423 ++++++++++++++------------- 2 files changed, 226 insertions(+), 199 deletions(-) diff --git a/pandapower/converter/cim/pp_tools.py b/pandapower/converter/cim/pp_tools.py index f02975b59..100d57db4 100644 --- a/pandapower/converter/cim/pp_tools.py +++ b/pandapower/converter/cim/pp_tools.py @@ -33,7 +33,7 @@ def set_pp_col_types(net: Union[pandapower.auxiliary.pandapowerNet, Dict], ignor time_start = time.time() pp_elements = ['bus', 'dcline', 'ext_grid', 'gen', 'impedance', 'line', 'load', 'motor', 'sgen', 'shunt', 'storage', 'switch', 'trafo', 'trafo3w', 'ward', 'xward'] - to_int = ['bus', 'element', 'to_bus', 'from_bus', 'hv_bus', 'mv_bus', 'lv_bus', 'tap_phase_shifter_type'] + to_int = ['bus', 'element', 'to_bus', 'from_bus', 'hv_bus', 'mv_bus', 'lv_bus'] to_bool = ['in_service', 'closed'] logger.info("Setting the columns data types for buses to int and in_service to bool for the following elements: " "%s" % pp_elements) diff --git a/pandapower/create.py b/pandapower/create.py index 8cf5f165a..77b5396a6 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -902,7 +902,7 @@ def create_buses_dc(net, nr_buses_dc, vn_kv, index=None, name=None, type="b", ge **geodata** ((x,y)-tuple or list of tuples with length == nr_buses_dc, default None) - coordinates used for plotting - **type** (string, default "b") - Type of the dc bus. "n" - auxilary node, + **type** (string, default "b") - Type of the dc bus. "n" - auxiliary node, "b" - busbar, "m" - muff **zone** (string, None) - grid region @@ -1051,7 +1051,7 @@ def create_loads(net, buses, p_mw, q_mvar=0, const_z_percent=0, const_i_percent= OPTIONAL: **p_mw** (list of floats) - The active power of the loads - - postive value -> load + - positive value -> load - negative value -> generation **q_mvar** (list of floats, default 0) - The reactive power of the loads @@ -1067,7 +1067,7 @@ def create_loads(net, buses, p_mw, q_mvar=0, const_z_percent=0, const_i_percent= **name** (list of strings, default None) - The name for this load **scaling** (list of floats, default 1.) - An OPTIONAL scaling factor to be set customly. - Multiplys with p_mw and q_mvar. + Multiplies with p_mw and q_mvar. **type** (string, None) - type variable to classify the load @@ -1155,7 +1155,7 @@ def create_asymmetric_load(net, bus, p_a_mw=0, p_b_mw=0, p_c_mw=0, q_a_mvar=0, q **name** (string, default: None) - The name for this load **scaling** (float, default: 1.) - An OPTIONAL scaling factor to be set customly - Multiplys with p_mw and q_mvar of all phases. + Multiplies with p_mw and q_mvar of all phases. **type** (string,default: wye) - type variable to classify three ph load: delta/wye @@ -1214,7 +1214,8 @@ def create_asymmetric_load(net, bus, p_a_mw=0, p_b_mw=0, p_c_mw=0, q_a_mvar=0, q # **index** (int) - The unique ID of the created load # # Load elements are modeled from a consumer point of view. Active power will therefore always be -# positive, reactive power will be positive for under-excited behavior (Q absorption, decreases voltage) and negative for over-excited behavior (Q injection, increases voltage) +# positive, reactive power will be positive for under-excited behavior (Q absorption, decreases voltage) and +# negative for over-excited behavior (Q injection, increases voltage) # """ # if bus not in net["bus"].index.values: # raise UserWarning("Cannot attach to bus %s, bus does not exist" % bus) @@ -1253,7 +1254,8 @@ def create_load_from_cosphi(net, bus, sn_mva, cos_phi, mode, **kwargs): **cos_phi** (float) - power factor cos_phi - **mode** (str) - "underexcited" (Q absorption, decreases voltage) or "overexcited" (Q injection, increases voltage) + **mode** (str) - "underexcited" (Q absorption, decreases voltage) or "overexcited" + (Q injection, increases voltage) OPTIONAL: same as in create_load, keyword arguments are passed to the create_load function @@ -1262,8 +1264,8 @@ def create_load_from_cosphi(net, bus, sn_mva, cos_phi, mode, **kwargs): **index** (int) - The unique ID of the created load Load elements are modeled from a consumer point of view. Active power will therefore always be - positive, reactive power will be positive for underexcited behavior (Q absorption, decreases voltage) and negative for - overexcited behavior (Q injection, increases voltage). + positive, reactive power will be positive for underexcited behavior (Q absorption, decreases voltage) and negative + for overexcited behavior (Q injection, increases voltage). """ from pandapower.toolbox import pq_from_cosphi p_mw, q_mvar = pq_from_cosphi(sn_mva, cos_phi, qmode=mode, pmode="load") @@ -1305,7 +1307,7 @@ def create_sgen(net, bus, p_mw, q_mvar=0, sn_mva=nan, name=None, index=None, higher than the highest already existing index is selected. **scaling** (float, 1.) - An OPTIONAL scaling factor to be set customly. - Multiplys with p_mw and q_mvar. + Multiplies with p_mw and q_mvar. **type** (string, None) - Three phase Connection type of the static generator: wye/delta @@ -1417,7 +1419,7 @@ def create_sgens(net, buses, p_mw, q_mvar=0, sn_mva=nan, name=None, index=None, **p_mw** (list of floats) - The active power of the sgens - - postive value -> generation + - positive value -> generation - negative value -> load **q_mvar** (list of floats, default 0) - The reactive power of the sgens @@ -1427,7 +1429,7 @@ def create_sgens(net, buses, p_mw, q_mvar=0, sn_mva=nan, name=None, index=None, **name** (list of strings, default None) - The name for this sgen **scaling** (list of floats, default 1.) - An OPTIONAL scaling factor to be set customly. - Multiplys with p_mw and q_mvar. + Multiplies with p_mw and q_mvar. **type** (string, None) - type variable to classify the sgen @@ -1567,7 +1569,7 @@ def create_asymmetric_sgen(net, bus, p_a_mw=0, p_b_mw=0, p_c_mw=0, q_a_mvar=0, q higher than the highest already existing index is selected. **scaling** (float, 1.) - An OPTIONAL scaling factor to be set customly. - Multiplys with p_mw and q_mvar of all phases. + Multiplies with p_mw and q_mvar of all phases. **type** (string, 'wye') - Three phase Connection type of the static generator: wye/delta @@ -1608,15 +1610,16 @@ def create_sgen_from_cosphi(net, bus, sn_mva, cos_phi, mode, **kwargs): **cos_phi** (float) - power factor cos_phi - **mode** (str) - "underexcited" (Q absorption, decreases voltage) or "overexcited" (Q injection, increases voltage) + **mode** (str) - "underexcited" (Q absorption, decreases voltage) or "overexcited" + (Q injection, increases voltage) OUTPUT: **index** (int) - The unique ID of the created sgen gen, sgen, and ext_grid are modelled in the generator point of view. Active power - will therefore be postive for generation, and reactive power will be negative for + will therefore be positive for generation, and reactive power will be negative for underexcited behavior (Q absorption, decreases voltage) and - positive for for overexcited behavior (Q injection, increases voltage). + positive for overexcited behavior (Q injection, increases voltage). """ from pandapower.toolbox import pq_from_cosphi p_mw, q_mvar = pq_from_cosphi(sn_mva, cos_phi, qmode=mode, pmode="gen") @@ -1634,11 +1637,11 @@ def create_storage(net, bus, p_mw, max_e_mwh, q_mvar=0, sn_mva=nan, soc_percent= of either a sgen or a load is (per definition of the elements) not correct. To overcome this issue, a storage element can be created. - As pandapower is not a time dependend simulation tool and there is no time domain parameter in + As pandapower is not a time dependent simulation tool and there is no time domain parameter in default power flow calculations, the state of charge (SOC) is not updated during any power flow calculation. The implementation of energy content related parameters in the storage element allows to create - customized, time dependend simulations by running several power flow calculations and updating + customized, time dependent simulations by running several power flow calculations and updating variables manually. INPUT: @@ -1668,7 +1671,7 @@ def create_storage(net, bus, p_mw, max_e_mwh, q_mvar=0, sn_mva=nan, soc_percent= higher than the highest already existing index is selected. **scaling** (float, 1.) - An OPTIONAL scaling factor to be set customly. - Multiplys with p_mw and q_mvar. + Multiplies with p_mw and q_mvar. **type** (string, None) - type variable to classify the storage @@ -1730,11 +1733,11 @@ def create_storages( of either a sgen or a load is (per definition of the elements) not correct. To overcome this issue, a storage element can be created. - As pandapower is not a time dependend simulation tool and there is no time domain parameter in + As pandapower is not a time dependent simulation tool and there is no time domain parameter in default power flow calculations, the state of charge (SOC) is not updated during any power flow calculation. The implementation of energy content related parameters in the storage element allows to create - customized, time dependend simulations by running several power flow calculations and updating + customized, time dependent simulations by running several power flow calculations and updating variables manually. INPUT: @@ -1764,7 +1767,7 @@ def create_storages( higher than the highest already existing index is selected. **scaling** (list of float, 1.) - An OPTIONAL scaling factor to be set customly. - Multiplys with p_mw and q_mvar. + Multiplies with p_mw and q_mvar. **type** (list of string, None) - type variable to classify the storage @@ -1849,14 +1852,12 @@ def create_gen(net, bus, p_mw, vm_pu=1., sn_mva=nan, name=None, index=None, max_ **controllable** (bool, NaN) - True: p_mw, q_mvar and vm_pu limits are enforced for this \ generator in OPF - False: p_mw and vm_pu setpoints are enforced and *limits are ignored*. + False: p_mw and vm_pu set points are enforced and *limits are ignored*. defaults to True if "controllable" column exists in DataFrame **slack_weight** (float, default 0.0) - Contribution factor for distributed slack power flow calculation (active power balancing) - powerflow - **vn_kv** (float, NaN) - Rated voltage of the generator for short-circuit calculation **xdss_pu** (float, NaN) - Subtransient generator reactance for short-circuit calculation @@ -1968,7 +1969,7 @@ def create_gens(net, buses, p_mw, vm_pu=1., sn_mva=nan, name=None, index=None, m **controllable** (bool, NaN) - True: p_mw, q_mvar and vm_pu limits are enforced for this \ generator in OPF - False: p_mw and vm_pu setpoints are enforced and \ + False: p_mw and vm_pu set points are enforced and \ *limits are ignored*. defaults to True if "controllable" column exists in DataFrame powerflow @@ -2141,20 +2142,20 @@ def create_ext_grid(net, bus, vm_pu=1.0, va_degree=0., name=None, in_service=Tru **va_degree** (float, default 0.) - voltage angle at the slack node in degrees* - **name** (string, default None) - name of of the external grid + **name** (string, default None) - name of the external grid **in_service** (boolean) - True for in_service or False for out of service - **s_sc_max_mva** (float, NaN) - maximal short circuit apparent power to calculate internal \ + **s_sc_max_mva** (float, NaN) - maximum short circuit apparent power to calculate internal \ impedance of ext_grid for short circuit calculations - **s_sc_min_mva** (float, NaN) - minimal short circuit apparent power to calculate internal \ + **s_sc_min_mva** (float, NaN) - minimum short circuit apparent power to calculate internal \ impedance of ext_grid for short circuit calculations - **rx_max** (float, NaN) - maximal R/X-ratio to calculate internal impedance of ext_grid \ + **rx_max** (float, NaN) - maximum R/X-ratio to calculate internal impedance of ext_grid \ for short circuit calculations - **rx_min** (float, NaN) - minimal R/X-ratio to calculate internal impedance of ext_grid \ + **rx_min** (float, NaN) - minimum R/X-ratio to calculate internal impedance of ext_grid \ for short circuit calculations **max_p_mw** (float, NaN) - Maximum active power injection. Only respected for OPF @@ -2165,21 +2166,22 @@ def create_ext_grid(net, bus, vm_pu=1.0, va_degree=0., name=None, in_service=Tru **min_q_mvar** (float, NaN) - Minimum reactive power injection. Only respected for OPF - **r0x0_max** (float, NaN) - maximal R/X-ratio to calculate Zero sequence + **r0x0_max** (float, NaN) - maximum R/X-ratio to calculate Zero sequence internal impedance of ext_grid - **x0x_max** (float, NaN) - maximal X0/X-ratio to calculate Zero sequence + **x0x_max** (float, NaN) - maximum X0/X-ratio to calculate Zero sequence internal impedance of ext_grid - **slack_weight** (float, default 1.0) - Contribution factor for distributed slack power flow calculation (active power balancing) + **slack_weight** (float, default 1.0) - Contribution factor for distributed slack power flow calculation + (active power balancing) - ** only considered in loadflow if calculate_voltage_angles = True + ** only considered in load flow if calculate_voltage_angles = True **controllable** (bool, NaN) - True: p_mw, q_mvar and vm_pu limits are enforced for the \ ext_grid in OPF. The voltage limits set in the \ ext_grid bus are enforced. - False: p_mw and vm_pu setpoints are enforced and *limits are\ - ignored*. The vm_pu setpoint is enforced and limits \ + False: p_mw and vm_pu set points are enforced and *limits are\ + ignored*. The vm_pu set point is enforced and limits \ of the bus table are ignored. defaults to False if "controllable" column exists in\ DataFrame @@ -2235,7 +2237,7 @@ def create_line(net, from_bus, to_bus, length_km, std_type, name=None, index=Non **length_km** (float) - The line length in km - **std_type** (string) - Name of a standard linetype : + **std_type** (string) - Name of a standard line type: - Pre-defined in standard_linetypes @@ -2257,14 +2259,14 @@ def create_line(net, from_bus, to_bus, length_km, std_type, name=None, index=Non **in_service** (boolean, True) - True for in_service or False for out of service - **df** (float, 1) - derating factor: maximal current of line in relation to nominal current\ + **df** (float, 1) - derating factor: maximum current of line in relation to nominal current\ of line (from 0 to 1) **parallel** (integer, 1) - number of parallel line systems **max_loading_percent (float)** - maximum current loading (only needed for OPF) - **alpha (float)** - temperature coefficient of resistance: R(T) = R(T_0) * (1 + alpha * (T - T_0))) + **alpha (float)** - temperature coefficient of resistance: R(T) = R(T_0) * (1 + alpha * (T - T_0)) **temperature_degree_celsius (float)** - line temperature for which line resistance is adjusted @@ -2371,7 +2373,7 @@ def create_line_dc(net, from_bus_dc, to_bus_dc, length_km, std_type, name=None, **length_km** (float) - The line length in km - **std_type** (string) - Name of a standard linetype : + **std_type** (string) - Name of a standard line type : - Pre-defined in standard_linetypes @@ -2393,14 +2395,14 @@ def create_line_dc(net, from_bus_dc, to_bus_dc, length_km, std_type, name=None, **in_service** (boolean, True) - True for in_service or False for out of service - **df** (float, 1) - derating factor: maximal current of line_dc in relation to nominal current\ + **df** (float, 1) - derating factor: maximum current of line_dc in relation to nominal current\ of line (from 0 to 1) **parallel** (integer, 1) - number of parallel line systems **max_loading_percent (float)** - maximum current loading (only needed for OPF) - **alpha (float)** - temperature coefficient of resistance: R(T) = R(T_0) * (1 + alpha * (T - T_0))) + **alpha (float)** - temperature coefficient of resistance: R(T) = R(T_0) * (1 + alpha * (T - T_0)) **temperature_degree_celsius (float)** - line temperature for which line resistance is adjusted @@ -2508,7 +2510,7 @@ def create_lines(net, from_buses, to_buses, length_km, std_type, name=None, inde **length_km** (list of float) - The line length in km - **std_type** (string) - The linetype of the lines. + **std_type** (string) - The line type of the lines. OPTIONAL: **name** (list of string, None) - A custom name for this line @@ -2524,14 +2526,14 @@ def create_lines(net, from_buses, to_buses, length_km, std_type, name=None, inde **in_service** (list of boolean, True) - True for in_service or False for out of service - **df** (list of float, 1) - derating factor: maximal current of line in relation to \ + **df** (list of float, 1) - derating factor: maximum current of line in relation to \ nominal current of line (from 0 to 1) **parallel** (list of integer, 1) - number of parallel line systems **max_loading_percent (list of float)** - maximum current loading (only needed for OPF) - **alpha (float)** - temperature coefficient of resistance: R(T) = R(T_0) * (1 + alpha * (T - T_0))) + **alpha (float)** - temperature coefficient of resistance: R(T) = R(T_0) * (1 + alpha * (T - T_0)) **temperature_degree_celsius (float)** - line temperature for which line resistance is adjusted @@ -2565,7 +2567,8 @@ def create_lines(net, from_buses, to_buses, length_km, std_type, name=None, inde **index** (list of int) - The unique ID of the created lines EXAMPLE: - create_lines(net, ["line1", "line2"], from_buses=[0,1], to_buses=[2,3], length_km=0.1, std_type="NAYY 4x50 SE") + create_lines(net, ["line1", "line2"], from_buses=[0,1], to_buses=[2,3], length_km=0.1, + std_type="NAYY 4x50 SE") """ _check_multiple_branch_elements(net, from_buses, to_buses, "Lines") @@ -2593,8 +2596,7 @@ def create_lines(net, from_buses, to_buses, length_km, std_type, name=None, inde entries["x_ohm_per_km"] = list(map(itemgetter("x_ohm_per_km"), lineparam)) entries["c_nf_per_km"] = list(map(itemgetter("c_nf_per_km"), lineparam)) entries["max_i_ka"] = list(map(itemgetter("max_i_ka"), lineparam)) - entries["g_us_per_km"] = [line_param_dict.get("g_us_per_km", 0) for line_param_dict in \ - lineparam] + entries["g_us_per_km"] = [line_param_dict.get("g_us_per_km", 0) for line_param_dict in lineparam] entries["type"] = [line_param_dict.get("type", None) for line_param_dict in lineparam] _add_to_entries_if_not_nan(net, "line", entries, index, "max_loading_percent", @@ -2654,14 +2656,14 @@ def create_lines_dc(net, from_buses_dc, to_buses_dc, length_km, std_type, name=N **in_service** (list of boolean, True) - True for in_service or False for out of service - **df** (list of float, 1) - derating factor: maximal current of line in relation to \ + **df** (list of float, 1) - derating factor: maximum current of line in relation to \ nominal current of line (from 0 to 1) **parallel** (list of integer, 1) - number of parallel line systems **max_loading_percent (list of float)** - maximum current loading (only needed for OPF) - **alpha (float)** - temperature coefficient of resistance: R(T) = R(T_0) * (1 + alpha * (T - T_0))) + **alpha (float)** - temperature coefficient of resistance: R(T) = R(T_0) * (1 + alpha * (T - T_0)) **temperature_degree_celsius (float)** - line temperature for which line resistance is adjusted @@ -2787,7 +2789,7 @@ def create_line_from_parameters(net, from_bus, to_bus, length_km, r_ohm_per_km, **type** (str, None) - type of line ("ol" for overhead line or "cs" for cable system) - **df** (float, 1) - derating factor: maximal current of line in relation to nominal current\ + **df** (float, 1) - derating factor: maximum current of line in relation to nominal current\ of line (from 0 to 1) **g_us_per_km** (float, 0) - dielectric conductance in micro Siemens per km @@ -2838,7 +2840,7 @@ def create_line_from_parameters(net, from_bus, to_bus, length_km, r_ohm_per_km, **index** (int) - The unique ID of the created line EXAMPLE: - create_line_from_parameters(net, "line1", from_bus = 0, to_bus = 1, lenght_km=0.1, + create_line_from_parameters(net, "line1", from_bus = 0, to_bus = 1, length_km=0.1, r_ohm_per_km = .01, x_ohm_per_km = 0.05, c_nf_per_km = 10, max_i_ka = 0.4) @@ -2923,7 +2925,7 @@ def create_line_dc_from_parameters(net, from_bus_dc, to_bus_dc, length_km, r_ohm **type** (str, None) - type of dc line ("ol" for overhead dc line or "cs" for cable system) - **df** (float, 1) - derating factor: maximal current of dc line in relation to nominal current\ + **df** (float, 1) - derating factor: maximum current of dc line in relation to nominal current\ of line (from 0 to 1) **g_us_per_km** (float, 0) - dielectric conductance in micro Siemens per km @@ -2974,7 +2976,7 @@ def create_line_dc_from_parameters(net, from_bus_dc, to_bus_dc, length_km, r_ohm **index** (int) - The unique ID of the created line EXAMPLE: - create_line_dc_from_parameters(net, "line_dc1", from_bus_dc = 0, to_bus_dc = 1, lenght_km=0.1, + create_line_dc_from_parameters(net, "line_dc1", from_bus_dc = 0, to_bus_dc = 1, length_km=0.1, r_ohm_per_km = .01, max_i_ka = 0.4) """ @@ -3062,7 +3064,7 @@ def create_lines_from_parameters(net, from_buses, to_buses, length_km, r_ohm_per **type** (list of string, None) - type of line ("ol" for overhead line or "cs" for cable system) - **df** (list of float, 1) - derating factor: maximal current of line in relation to nominal current\ + **df** (list of float, 1) - derating factor: maximum current of line in relation to nominal current\ of line (from 0 to 1) **g_us_per_km** (list of float, 0) - dielectric conductance in micro Siemens per km @@ -3191,7 +3193,7 @@ def create_lines_dc_from_parameters(net, from_buses_dc, to_buses_dc, length_km, **type** (list of str, None) - type of dc line ("ol" for overhead dc line or "cs" for cable system) - **df** (list of float, 1) - derating factor: maximal current of line in relation to nominal current\ + **df** (list of float, 1) - derating factor: maximum current of line in relation to nominal current\ of line (from 0 to 1) **g_us_per_km** (list of float, 0) - dielectric conductance in micro Siemens per km @@ -3280,8 +3282,8 @@ def create_lines_dc_from_parameters(net, from_buses_dc, to_buses_dc, length_km, def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in_service=True, - index=None, max_loading_percent=nan, parallel=1, df=1., - tap_dependency_table=nan, id_characteristic_table = nan, + index=None, max_loading_percent=nan, parallel=1, df=1., tap_phase_shifter_type=nan, + tap_dependency_table=False, id_characteristic_table=nan, pt_percent=nan, oltc=nan, xn_ohm=nan, tap2_pos=nan, **kwargs): """ Creates a two-winding transformer in table net["trafo"]. @@ -3327,15 +3329,22 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in **parallel** (integer) - number of parallel transformers - **df** (float) - derating factor: maximal current of transformer in relation to nominal \ + **df** (float) - derating factor: maximum current of transformer in relation to nominal \ current of transformer (from 0 to 1) - **tap_dependency_table** (boolean) - True if transformer characteristics (voltage ratio, angle, impedance) \ + **tap_dependency_table** (boolean, False) - True if transformer parameters (voltage ratio, angle, impedance) \ must be adjusted dependent on the tap position of the transformer. Requires the additional column \ - "id_characteristic_table" + "id_characteristic_table". The function pandapower.control.trafo_characteristic_table_diagnostic \ + can be used for sanity checks. \ + The function pandapower.control.create_trafo_characteristic_object can be used to create \ + SplineCharacteristic objects in the net.trafo_characteristic_spline table and add the additional column \ + "id_characteristic_spline" to set up the reference to the spline characteristics. **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ net.trafo_characteristic_table + + **tap_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + 1: Symmetrical, 2: Ideal)* **xn_ohm** (float) - impedance of the grounding reactor (Z_N) for short circuit calculation @@ -3399,8 +3408,6 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in _set_entries(net, "trafo", index, **v, **kwargs) _set_value_if_not_nan(net, index, max_loading_percent, "max_loading_percent", "trafo") - _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", - "trafo", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo", dtype="Int64") _set_value_if_not_nan(net, index, pt_percent, "pt_percent", "trafo") @@ -3421,7 +3428,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn df=1., vk0_percent=nan, vkr0_percent=nan, mag0_percent=nan, mag0_rx=nan, si0_hv_partial=nan, - pt_percent=nan, oltc=nan, tap_dependency_table=nan, + pt_percent=nan, oltc=nan, tap_dependency_table=False, xn_ohm=nan, tap2_side=None, tap2_neutral=nan, tap2_max=nan, tap2_min=nan, tap2_step_percent=nan, tap2_step_degree=nan, tap2_pos=nan, tap2_phase_shifter_type=nan, **kwargs): @@ -3486,9 +3493,9 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **tap_neutral** (int, nan) - tap position where the transformer ratio is equal to the \ ratio of the rated voltages - **tap_max** (int, nan) - maximal allowed tap position + **tap_max** (int, nan) - maximum allowed tap position - **tap_min** (int, nan): minimal allowed tap position + **tap_min** (int, nan): minimum allowed tap position **tap_step_percent** (float) - tap step size for voltage magnitude in percent @@ -3502,12 +3509,16 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **max_loading_percent (float)** - maximum current loading (only needed for OPF) - **df** (float) - derating factor: maximal current of transformer in relation to nominal \ + **df** (float) - derating factor: maximum current of transformer in relation to nominal \ current of transformer (from 0 to 1) - **tap_dependency_table** (boolean) - True if transformer characteristics (voltage ratio, angle, impedance) \ + **tap_dependency_table** (boolean, False) - True if transformer parameters (voltage ratio, angle, impedance) \ must be adjusted dependent on the tap position of the transformer. Requires the additional column \ - "id_characteristic_table" + "id_characteristic_table". The function pandapower.control.trafo_characteristic_table_diagnostic \ + can be used for sanity checks. \ + The function pandapower.control.create_trafo_characteristic_object can be used to create \ + SplineCharacteristic objects in the net.trafo_characteristic_spline table and add the additional column \ + "id_characteristic_spline" to set up the reference to the spline characteristics. **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ net.trafo_characteristic_table @@ -3526,9 +3537,9 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **tap2_neutral** (int, nan) - second tap position where the transformer ratio is equal to the \ ratio of the rated voltages - **tap2_max** (int, nan) - maximal allowed tap position of the second tap changer + **tap2_max** (int, nan) - maximum allowed tap position of the second tap changer - **tap2_min** (int, nan): minimal allowed tap position of the second tap changer + **tap2_min** (int, nan): minimum allowed tap position of the second tap changer **tap2_step_percent** (float) - second tap step size for voltage magnitude in percent @@ -3541,7 +3552,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **leakage_reactance_ratio_hv** (bool) - ratio of transformer short-circuit reactance on HV side (default 0.5) - ** only considered in loadflow if calculate_voltage_angles = True + ** only considered in load flow if calculate_voltage_angles = True OUTPUT: **index** (int) - The unique ID of the created transformer @@ -3578,14 +3589,12 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn v["tap_pos"] = v["tap_neutral"] else: v["tap_pos"] = tap_pos - if type(tap_pos) == float: + if type(tap_pos) is float: net.trafo.tap_pos = net.trafo.tap_pos.astype(float) v.update(kwargs) _set_entries(net, "trafo", index, **v) - _set_value_if_not_nan(net, index, tap_dependency_table, - "tap_dependency_table", "trafo", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo", dtype="Int64") @@ -3625,7 +3634,7 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k name=None, vector_group=None, index=None, max_loading_percent=nan, parallel=1, df=1., vk0_percent=nan, vkr0_percent=nan, mag0_percent=nan, mag0_rx=nan, si0_hv_partial=nan, - pt_percent=nan, oltc=nan, tap_dependency_table=nan, + pt_percent=nan, oltc=nan, tap_dependency_table=False, xn_ohm=nan, tap2_side=None, tap2_neutral=nan, tap2_max=nan, tap2_min=nan, tap2_step_percent=nan, tap2_step_degree=nan, tap2_pos=nan, tap2_phase_shifter_type=nan, @@ -3676,82 +3685,81 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k OPTIONAL: - **in_service** (boolean) - True for in_service or False for out of service + **in_service** (list of boolean) - True for in_service or False for out of service - **parallel** (integer) - number of parallel transformers + **parallel** (list of integer) - number of parallel transformers - **name** (string) - A custom name for this transformer + **name** (list of string) - A custom name for this transformer - **shift_degree** (float) - Angle shift over the transformer* + **shift_degree** (list of float) - Angle shift over the transformer* - **tap_side** (string) - position of tap changer ("hv", "lv") + **tap_side** (list of string) - position of tap changer ("hv", "lv") - **tap_pos** (int, nan) - current tap position of the transformer. Defaults to the medium \ - position (tap_neutral) + **tap_pos** (list of int, nan) - current tap position of the transformer. Defaults to the neutral \ + tap position (tap_neutral) - **tap_neutral** (int, nan) - tap position where the transformer ratio is equal to the ratio\ + **tap_neutral** (list of int, nan) - tap position where the transformer ratio is equal to the ratio \ of the rated voltages - **tap_max** (int, nan) - maximal allowed tap position + **tap_max** (list of int, nan) - maximum allowed tap position - **tap_min** (int, nan): minimal allowed tap position + **tap_min** (list of int, nan): minimum allowed tap position - **tap_step_percent** (float) - tap step size for voltage magnitude in percent + **tap_step_percent** (list of float) - tap step size for voltage magnitude in percent - **tap_step_degree** (float) - tap step size for voltage angle in degree* + **tap_step_degree** (list of float) - tap step size for voltage angle in degree* - **tap_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + **tap_phase_shifter_type** (list of int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal)* - **index** (int, None) - Force a specified ID if it is available. If None, the index one \ + **index** (list of int, None) - Force a specified ID if it is available. If None, the index one \ higher than the highest already existing index is selected. - **max_loading_percent (float)** - maximum current loading (only needed for OPF) + **max_loading_percent (list of float)** - maximum current loading (only needed for OPF) - **df** (float) - derating factor: maximal current of transformer in relation to nominal \ + **df** (list of float) - derating factor: maximum current of transformer in relation to nominal \ current of transformer (from 0 to 1) - **tap_dependency_table** (boolean) - True if transformer characteristics (voltage ratio, angle, impedance) \ - must be adjusted dependent on the tap position of the transformer. Requires the additional column \ - "id_characteristic_table" + **tap_dependency_table** (list of boolean, False) - True if transformer parameters (voltage ratio, angle, \ + impedance) must be adjusted dependent on the tap position of the transformer. Requires the additional \ + column "id_characteristic_table". The function pandapower.control.trafo_characteristic_table_diagnostic \ + can be used for sanity checks. \ + The function pandapower.control.create_trafo_characteristic_object can be used to create \ + SplineCharacteristic objects in the net.trafo_characteristic_spline table and add the additional column \ + "id_characteristic_spline" to set up the reference to the spline characteristics. - **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ - net.trafo_characteristic_table + **id_characteristic_table** (list of int, nan) - references the index of the characteristic from the lookup \ + table net.trafo_characteristic_table - **pt_percent** (float, nan) - (short circuit only) + **pt_percent** (list of float, nan) - (short circuit only) - **oltc** (bool, False) - (short circuit only) + **oltc** (list of bool, False) - (short circuit only) - **xn_ohm** (float) - impedance of the grounding reactor (Z_N) for short circuit calculation + **xn_ohm** (list of float) - impedance of the grounding reactor (Z_N) for short circuit calculation - **tap2_side** (string) - position of the second tap changer ("hv", "lv") + **tap2_side** (list of string) - position of the second tap changer ("hv", "lv") - **tap2_pos** (int, nan) - current tap position of the second tap changer of the transformer. \ + **tap2_pos** (list of int, nan) - current tap position of the second tap changer of the transformer. \ Defaults to the medium position (tap2_neutral) - **tap2_neutral** (int, nan) - second tap position where the transformer ratio is equal to the \ + **tap2_neutral** (list of int, nan) - second tap position where the transformer ratio is equal to the \ ratio of the rated voltages - **tap2_max** (int, nan) - maximal allowed tap position of the second tap changer + **tap2_max** (list of int, nan) - maximum allowed tap position of the second tap changer - **tap2_min** (int, nan): minimal allowed tap position of the second tap changer + **tap2_min** (list of int, nan): minimum allowed tap position of the second tap changer - **tap2_step_percent** (float) - second tap step size for voltage magnitude in percent + **tap2_step_percent** (list of float) - second tap step size for voltage magnitude in percent - **tap2_step_degree** (float) - second tap step size for voltage angle in degree* + **tap2_step_degree** (list of float) - second tap step size for voltage angle in degree* - **tap2_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + **tap2_phase_shifter_type** (list of int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal)* - ** only considered in loadflow if calculate_voltage_angles = True + ** only considered in load flow if calculate_voltage_angles = True OUTPUT: - **index** (int) - The unique ID of the created transformer - - EXAMPLE: - create_transformer_from_parameters(net, hv_bus=0, lv_bus=1, name="trafo1", sn_mva=40, \ - vn_hv_kv=110, vn_lv_kv=10, vk_percent=10, vkr_percent=0.3, pfe_kw=30, \ - i0_percent=0.1, shift_degree=30) + **index** (list of int) - The unique IDs of the created transformers """ _check_multiple_branch_elements(net, hv_buses, lv_buses, "Transformers") @@ -3766,13 +3774,11 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k "tap_neutral": tp_neutral, "tap_max": tap_max, "tap_min": tap_min, "shift_degree": shift_degree, "tap_pos": tp_pos, "tap_side": tap_side, "tap_step_percent": tap_step_percent, "tap_step_degree": tap_step_degree, - "tap_phase_shifter_type": tap_phase_shifter_type, "parallel": parallel, "df": df} + "tap_phase_shifter_type": tap_phase_shifter_type, "parallel": parallel, "df": df, + "tap_dependency_table": tap_dependency_table} - _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap_dependency_table", - tap_dependency_table, dtype=bool_, default_val=False) _add_to_entries_if_not_nan(net, "trafo", entries, index, "id_characteristic_table", id_characteristic_table, dtype="Int64") - _add_to_entries_if_not_nan(net, "trafo", entries, index, "vk0_percent", vk0_percent) _add_to_entries_if_not_nan(net, "trafo", entries, index, "vkr0_percent", vkr0_percent) _add_to_entries_if_not_nan(net, "trafo", entries, index, "mag0_percent", mag0_percent) @@ -3795,15 +3801,14 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k tap2_phase_shifter_type, dtype="Int64") defaults_to_fill = [("tap_dependency_table", False)] - _set_multiple_entries(net, "trafo", index, defaults_to_fill=defaults_to_fill, **entries, - **kwargs) + _set_multiple_entries(net, "trafo", index, defaults_to_fill=defaults_to_fill, **entries, **kwargs) return index def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_pos=nan, in_service=True, index=None, max_loading_percent=nan, - tap_at_star_point=False, tap_dependency_table=nan, id_characteristic_table=nan, **kwargs): + tap_at_star_point=False, tap_dependency_table=False, id_characteristic_table=nan): """ Creates a three-winding transformer in table net["trafo3w"]. The trafo parameters are defined through the standard type library. @@ -3839,9 +3844,13 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p **tap_at_star_point (bool)** - whether tap changer is modelled at star point or at the bus - **tap_dependency_table** (boolean) - True if transformer characteristics (voltage ratio, angle, impedance) \ + **tap_dependency_table** (boolean, False) - True if transformer parameters (voltage ratio, angle, impedance) \ must be adjusted dependent on the tap position of the transformer. Requires the additional column \ - "id_characteristic_table" + "id_characteristic_table". The function pandapower.control.trafo_characteristic_table_diagnostic \ + can be used for sanity checks. \ + The function pandapower.control.create_trafo_characteristic_object can be used to create \ + SplineCharacteristic objects in the net.trafo_characteristic_spline table and add the additional column \ + "id_characteristic_spline" to set up the reference to the spline characteristics. **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ net.trafo_characteristic_table @@ -3895,7 +3904,7 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p v["tap_pos"] = v["tap_neutral"] else: v["tap_pos"] = tap_pos - if type(tap_pos) == float: + if type(tap_pos) is float: net.trafo3w.tap_pos = net.trafo3w.tap_pos.astype(float) dd = pd.DataFrame(v, index=[index]) @@ -3903,8 +3912,6 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p net["trafo3w"].columns, axis=1) _set_value_if_not_nan(net, index, max_loading_percent, "max_loading_percent", "trafo3w") - _set_value_if_not_nan(net, index, tap_dependency_table, - "tap_dependency_table", "trafo3w", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo3w", dtype="Int64") @@ -3923,7 +3930,7 @@ def create_transformer3w_from_parameters( max_loading_percent=nan, tap_at_star_point=False, vk0_hv_percent=nan, vk0_mv_percent=nan, vk0_lv_percent=nan, vkr0_hv_percent=nan, vkr0_mv_percent=nan, vkr0_lv_percent=nan, - vector_group=None, tap_dependency_table=nan, id_characteristic_table=nan, **kwargs): + vector_group=None, tap_dependency_table=False, id_characteristic_table=nan, **kwargs): """ Adds a three-winding transformer in table net["trafo3w"]. The model currently only supports one tap-changer per 3W Transformer. @@ -3997,9 +4004,13 @@ def create_transformer3w_from_parameters( **max_loading_percent (float)** - maximum current loading (only needed for OPF) - **tap_dependency_table** (boolean) - True if transformer characteristics (voltage ratio, angle, impedance) \ + **tap_dependency_table** (boolean, False) - True if transformer parameters (voltage ratio, angle, impedance) \ must be adjusted dependent on the tap position of the transformer. Requires the additional column \ - "id_characteristic_table" + "id_characteristic_table". The function pandapower.control.trafo_characteristic_table_diagnostic \ + can be used for sanity checks. \ + The function pandapower.control.create_trafo_characteristic_object can be used to create \ + SplineCharacteristic objects in the net.trafo_characteristic_spline table and add the additional column \ + "id_characteristic_spline" to set up the reference to the spline characteristics. **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ net.trafo_characteristic_table @@ -4058,8 +4069,6 @@ def create_transformer3w_from_parameters( _set_entries(net, "trafo3w", index, **dict(zip(columns, values)), **kwargs) _set_value_if_not_nan(net, index, max_loading_percent, "max_loading_percent", "trafo3w") - _set_value_if_not_nan(net, index, tap_dependency_table, - "tap_dependency_table", "trafo3w", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo3w", dtype="Int64") @@ -4078,20 +4087,20 @@ def create_transformers3w_from_parameters( tap_at_star_point=False, vk0_hv_percent=nan, vk0_mv_percent=nan, vk0_lv_percent=nan, vkr0_hv_percent=nan, vkr0_mv_percent=nan, vkr0_lv_percent=nan, - vector_group=None, tap_dependency_table=nan, id_characteristic_table=nan, **kwargs): + vector_group=None, tap_dependency_table=False, id_characteristic_table=nan, **kwargs): """ Adds a three-winding transformer in table net["trafo3w"]. Input: **net** (pandapowerNet) - The net within this transformer should be created - **hv_bus** (list) - The bus on the high-voltage side on which the transformer will be \ + **hv_bus** (list of int) - The bus on the high-voltage side on which the transformer will be \ connected to - **mv_bus** (list) - The bus on the middle-voltage side on which the transformer will be \ + **mv_bus** (list of int) - The bus on the middle-voltage side on which the transformer will be \ connected to - **lv_bus** (list) - The bus on the low-voltage side on which the transformer will be \ + **lv_bus** (list of int) - The bus on the low-voltage side on which the transformer will be \ connected to **vn_hv_kv** (float or list) rated voltage on high voltage side @@ -4134,60 +4143,56 @@ def create_transformers3w_from_parameters( **tap_step_degree** (float or list) - Tap phase shift angle in degrees - **tap_side** (string, None) - "hv", "mv", "lv" + **tap_side** (list of string, None) - "hv", "mv", "lv" - **tap_neutral** (int, nan) - default tap position + **tap_neutral** (list of int, nan) - default tap position - **tap_min** (int, nan) - Minimum tap position + **tap_min** (list of int, nan) - Minimum tap position - **tap_max** (int, nan) - Maximum tap position + **tap_max** (list of int, nan) - Maximum tap position - **tap_pos** (int, nan) - current tap position of the transformer. Defaults to the \ + **tap_pos** (list of int, nan) - current tap position of the transformer. Defaults to the \ medium position (tap_neutral) - **tap_at_star_point** (boolean) - Whether tap changer is located at the star point of the \ + **tap_at_star_point** (list of boolean) - Whether tap changer is located at the star point of the \ 3W-transformer or at the bus - **name** (string, None) - Name of the 3-winding transformer + **name** (list of string, None) - Name of the 3-winding transformer - **in_service** (boolean, True) - True for in_service or False for out of service + **in_service** (list of boolean, True) - True for in_service or False for out of service - ** only considered in loadflow if calculate_voltage_angles = True + ** only considered in load flow if calculate_voltage_angles = True **The model currently only supports one tap-changer per 3W Transformer. - **max_loading_percent (float)** - maximum current loading (only needed for OPF) + **max_loading_percent (list of float)** - maximum current loading (only needed for OPF) - **tap_dependency_table** (boolean) - True if transformer characteristics (voltage ratio, angle, impedance) \ - must be adjusted dependent on the tap position of the transformer. Requires the additional column \ - "id_characteristic_table" + **tap_dependency_table** (list of boolean, False) - True if transformer parameters (voltage ratio, angle, \ + impedance) must be adjusted dependent on the tap position of the transformer. Requires the additional \ + column "id_characteristic_table". The function pandapower.control.trafo_characteristic_table_diagnostic \ + can be used for sanity checks. \ + The function pandapower.control.create_trafo_characteristic_object can be used to create \ + SplineCharacteristic objects in the net.trafo_characteristic_spline table and add the additional column \ + "id_characteristic_spline" to set up the reference to the spline characteristics. - **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ - net.trafo_characteristic_table + **id_characteristic_table** (list of int, nan) - references the index of the characteristic from the \ + lookup table net.trafo_characteristic_table - **vk0_hv_percent** (float) - zero sequence short circuit voltage from high to medium voltage + **vk0_hv_percent** (list of float) - zero sequence short circuit voltage from high to medium voltage - **vk0_mv_percent** (float) - zero sequence short circuit voltage from medium to low voltage + **vk0_mv_percent** (list of float) - zero sequence short circuit voltage from medium to low voltage - **vk0_lv_percent** (float) - zero sequence short circuit voltage from high to low voltage + **vk0_lv_percent** (list of float) - zero sequence short circuit voltage from high to low voltage - **vkr0_hv_percent** (float) - zero sequence real part of short circuit voltage from high to medium voltage + **vkr0_hv_percent** (list of float) - zero sequence real part of short circuit voltage from high to medium voltage - **vkr0_mv_percent** (float) - zero sequence real part of short circuit voltage from medium to low voltage + **vkr0_mv_percent** (list of float) - zero sequence real part of short circuit voltage from medium to low voltage - **vkr0_lv_percent** (float) - zero sequence real part of short circuit voltage from high to low voltage + **vkr0_lv_percent** (list of float) - zero sequence real part of short circuit voltage from high to low voltage - **vector_group** (list of String) - Vector group of the transformer3w + **vector_group** (list of string) - Vector group of the transformer3w OUTPUT: - **trafo_id** - List of trafo_ids of the created 3W transformers - - Example: - create_transformer3w_from_parameters(net, hv_bus=0, mv_bus=1, lv_bus=2, name="trafo1", - sn_hv_mva=40, sn_mv_mva=20, sn_lv_mva=20, vn_hv_kv=110, vn_mv_kv=20, vn_lv_kv=10, - vk_hv_percent=10,vk_mv_percent=11, vk_lv_percent=12, vkr_hv_percent=0.3, - vkr_mv_percent=0.31, vkr_lv_percent=0.32, pfe_kw=30, i0_percent=0.1, shift_mv_degree=30, - shift_lv_degree=30) - + **trafo_id** (list of int) - List of trafo_ids of the created 3W transformers """ index = _get_multiple_index_with_check(net, "trafo3w", index, len(hv_buses), name="Three winding transformers") @@ -4219,12 +4224,10 @@ def create_transformers3w_from_parameters( "vk0_hv_percent": vk0_hv_percent, "vk0_mv_percent": vk0_mv_percent, "vk0_lv_percent": vk0_lv_percent, "vkr0_hv_percent": vkr0_hv_percent, "vkr0_mv_percent": vkr0_mv_percent, "vkr0_lv_percent": vkr0_lv_percent, - "vector_group": vector_group} + "vector_group": vector_group, "tap_dependency_table": tap_dependency_table} _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "max_loading_percent", max_loading_percent) - _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "tap_dependency_table", - tap_dependency_table, dtype=bool_, default_val=False) _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "id_characteristic_table", id_characteristic_table, dtype="Int64") defaults_to_fill = [("tap_dependency_table", False)] @@ -4411,8 +4414,8 @@ def create_switches(net, buses, elements, et, closed=True, type=None, name=None, return index -def create_shunt(net, bus, q_mvar, p_mw=0., vn_kv=None, step=1, max_step=1, name=None, - in_service=True, index=None, **kwargs): +def create_shunt(net, bus, q_mvar, p_mw=0., vn_kv=None, step=1, max_step=1, name=None, step_dependency_table=False, + id_characteristic_table=nan, in_service=True, index=None, **kwargs): """ Creates a shunt element @@ -4421,9 +4424,9 @@ def create_shunt(net, bus, q_mvar, p_mw=0., vn_kv=None, step=1, max_step=1, name **bus** - bus number of bus to whom the shunt is connected to - **p_mw** - shunt active power in MW at v= 1.0 p.u. + **p_mw** - shunt active power in MW at v = 1.0 p.u. per step - **q_mvar** - shunt susceptance in MVAr at v= 1.0 p.u. + **q_mvar** - shunt reactive power in MVAr at v = 1.0 p.u. per step OPTIONAL: **vn_kv** (float, None) - rated voltage of the shunt. Defaults to rated voltage of @@ -4431,10 +4434,19 @@ def create_shunt(net, bus, q_mvar, p_mw=0., vn_kv=None, step=1, max_step=1, name **step** (int, 1) - step of shunt with which power values are multiplied - **max_step** (boolean, True) - True for in_service or False for out of service + **max_step** (int, 1) - maximum allowed step of shunt **name** (str, None) - element name + **step_dependency_table** (boolean, False) - True if shunt parameters (p_mw, q_mvar) must be adjusted \ + dependent on the step of the shunt. Requires the additional column "id_characteristic_table". \ + The function pandapower.control.create_shunt_characteristic_object can be used to create \ + SplineCharacteristic objects in the net.shunt_characteristic_spline table and add the additional column \ + "id_characteristic_spline" to set up the reference to the spline characteristics. + + **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ + net.shunt_characteristic_table + **in_service** (boolean, True) - True for in_service or False for out of service **index** (int, None) - Force a specified ID if it is available. If None, the index one @@ -4453,26 +4465,30 @@ def create_shunt(net, bus, q_mvar, p_mw=0., vn_kv=None, step=1, max_step=1, name if vn_kv is None: vn_kv = net.bus.vn_kv.at[bus] - entries = dict(zip(["bus", "name", "p_mw", "q_mvar", "vn_kv", "step", "max_step", "in_service"], - [bus, name, p_mw, q_mvar, vn_kv, step, max_step, in_service])) + entries = dict(zip(["bus", "name", "p_mw", "q_mvar", "vn_kv", "step", "max_step", "in_service", + "step_dependency_table"], + [bus, name, p_mw, q_mvar, vn_kv, step, max_step, in_service, step_dependency_table])) _set_entries(net, "shunt", index, **entries, **kwargs) + _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", + "shunt", dtype="Int64") + return index -def create_shunts(net, buses, q_mvar, p_mw=0., vn_kv=None, step=1, max_step=1, name=None, - in_service=True, index=None, **kwargs): +def create_shunts(net, buses, q_mvar, p_mw=0., vn_kv=None, step=1, max_step=1, name=None, step_dependency_table=False, + id_characteristic_table=nan, in_service=True, index=None, **kwargs): """ Creates a number of shunt elements INPUT: **net** (pandapowerNet) - The pandapower network in which the element is created - **buses** - bus numbers of buses to which the shunts should be connected to + **buses** (list of ints) - bus numbers of buses to which the shunts should be connected to - **p_mw** - shunts active power in MW at v= 1.0 p.u. + **p_mw** (list of floats, 0) - shunts' active power in MW at v = 1.0 p.u. - **q_mvar** - shunts susceptance in MVAr at v= 1.0 p.u. + **q_mvar** (list of floats) - shunts' reactive power in MVAr at v = 1.0 p.u. OPTIONAL: **vn_kv** (list of floats, None) - rated voltage of the shunts. Defaults to rated voltage of @@ -4480,20 +4496,29 @@ def create_shunts(net, buses, q_mvar, p_mw=0., vn_kv=None, step=1, max_step=1, n **step** (list of ints, 1) - step of shunts with which power values are multiplied - **max_step** (list of booleans, True) - True for in_service or False for out of service + **max_step** (list of ints, 1) - maximum allowed step of shunts **name** (list of strs, None) - element name + **step_dependency_table** (list of booleans, False) - True if shunt parameters (p_mw, q_mvar) must be \ + adjusted dependent on the step of the shunts. Requires the additional column "id_characteristic_table". \ + The function pandapower.control.create_shunt_characteristic_object can be used to create \ + SplineCharacteristic objects in the net.shunt_characteristic_spline table and add the additional column \ + "id_characteristic_spline" to set up the reference to the spline characteristics. + + **id_characteristic_table** (list of ints, nan) - references the index of the characteristic from the lookup \ + table net.shunt_characteristic_table + **in_service** (list of booleans, True) - True for in_service or False for out of service **index** (list of ints, None) - Force a specified ID if it is available. If None, the index one higher than the highest already existing index is selected. OUTPUT: - **index** (int) - The unique ID of the created shunt + **index** (list of ints) - The unique IDs of the created shunts EXAMPLE: - create_shunt(net, 0, 20) + create_shunts(net, [0, 1], [20, 25]) """ _check_multiple_node_elements(net, buses) @@ -4502,8 +4527,10 @@ def create_shunts(net, buses, q_mvar, p_mw=0., vn_kv=None, step=1, max_step=1, n if vn_kv is None: vn_kv = net.bus.vn_kv.loc[buses] - entries = dict(zip(["bus", "name", "p_mw", "q_mvar", "vn_kv", "step", "max_step", "in_service"], - [buses, name, p_mw, q_mvar, vn_kv, step, max_step, in_service])) + entries = dict(zip(["bus", "name", "p_mw", "q_mvar", "vn_kv", "step", "max_step", "in_service", + "step_dependency_table", "id_characteristic_table"], + [buses, name, p_mw, q_mvar, vn_kv, step, max_step, in_service, + step_dependency_table, id_characteristic_table])) _set_multiple_entries(net, "shunt", index, **entries, **kwargs) return index @@ -5019,10 +5046,10 @@ def create_tcsc(net, from_bus, to_bus, x_l_ohm, x_cvar_ohm, set_p_to_mw, have the same from_bus or the same to_bus. Note: in the Newton-Raphson power flow calculation, the initial voltage vector is adjusted slightly - if the initial voltage at the from bus is the same as at the to_bus to avoid + if the initial voltage at the from_bus is the same as at the to_bus to avoid some terms in J (for TCSC) becoming zero. - min_angle_degree, max_angle_degree are placehowlders (ignored in the Newton-Raphson power flow at the moment). + min_angle_degree, max_angle_degree are placeholders (ignored in the Newton-Raphson power flow at the moment). INPUT: **net** (pandapowerNet) - The pandapower network in which the element is created @@ -5176,7 +5203,7 @@ def create_wards(net, buses, ps_mw, qs_mvar, pz_mw, qz_mvar, name=None, in_servi index = _get_multiple_index_with_check(net, "storage", index, len(buses)) entries = {"name": name, "bus": buses, "ps_mw": ps_mw, "qs_mvar": qs_mvar, "pz_mw": pz_mw, - "qz_mvar": qz_mvar, "name": name, "in_service": in_service} + "qz_mvar": qz_mvar, "in_service": in_service} _set_multiple_entries(net, "ward", index, **entries, **kwargs) @@ -5247,9 +5274,9 @@ def create_dcline(net, from_bus, to_bus, p_mw, loss_percent, loss_mw, vm_from_pu **loss_mw** - (float) Total transmission loss in MW - **vm_from_pu** - (float) Voltage setpoint at from bus + **vm_from_pu** - (float) Voltage set point at from bus - **vm_to_pu** - (float) Voltage setpoint at to bus + **vm_to_pu** - (float) Voltage set point at to bus OPTIONAL: **index** (int, None) - Force a specified ID if it is available. If None, the index one \ @@ -5313,7 +5340,7 @@ def create_measurement(net, meas_type, element_type, value, std_dev, element, si **side** (int, string, default: None) - Only used for measured lines or transformers. Side \ defines at which end of the branch the measurement is gathered. For lines this may be \ - "from", "to" to denote the side with the from_bus or to_bus. It can also the be index \ + "from", "to" to denote the side with the from_bus or to_bus. It can also be the index \ of the from_bus or to_bus. For transformers, it can be "hv", "mv" or "lv" or the \ corresponding bus index, respectively @@ -5398,7 +5425,7 @@ def create_pwl_cost(net, element, et, points, power_type="p", index=None, check= **element** (int) - ID of the element in the respective element table **et** (string) - element type, one of "gen", "sgen", "ext_grid", "load", - "dcline", "storage"] + "dcline", "storage" **points** - (list) list of lists with [[p1, p2, c1], [p2, p3, c2], ...] where c(n) \ defines the costs between p(n) and p(n+1) @@ -5450,9 +5477,9 @@ def create_pwl_costs(net, elements, et, points, power_type="p", index=None, chec **elements** (iterable of integers) - IDs of the elements in the respective element table **et** (string or iterable) - element type, one of "gen", "sgen", "ext_grid", "load", - "dcline", "storage"] + "dcline", "storage" - **points** - (list of list of list) with [[p1, p2, c1], [p2, p3, c2], ...] for each element + **points** - (list of lists of lists) with [[p1, p2, c1], [p2, p3, c2], ...] for each element where c(n) defines the costs between p(n) and p(n+1) OPTIONAL: @@ -5503,7 +5530,7 @@ def create_poly_cost(net, element, et, cp1_eur_per_mw, cp0_eur=0, cq1_eur_per_mv cq0_eur=0, cp2_eur_per_mw2=0, cq2_eur_per_mvar2=0, index=None, check=True, **kwargs): """ - Creates an entry for polynimoal costs for an element. The currently supported elements are: + Creates an entry for polynomial costs for an element. The currently supported elements are: - Generator ("gen") - External Grid ("ext_grid") - Static Generator ("sgen") @@ -5899,7 +5926,7 @@ def _add_multiple_branch_geodata(net, geodata, index, table="line"): geo = [[x, y] for x, y in geodata] series = [f'{{"coordinates": {geo}, "type": "LineString"}}'] * len(index) elif hasattr(geodata, '__iter__') and all([isinstance(g, Iterable) for g in geodata]): - # geodata is Iterable of Iterable of coordinate tuples + # geodata is Iterable of coordinate tuples geo = [[[x, y] for x, y in g] for g in geodata] series = pd.Series([f'{{"coordinates": {g}, "type": "LineString"}}' for g in geo], index=index) else: From 3bf4b5211863da08e78c5ef276d21a8a9c771e5a Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 28 Nov 2024 13:48:08 +0200 Subject: [PATCH 014/125] update diagnostic.py lib --- pandapower/control/util/diagnostic.py | 77 ++++++++++----------------- 1 file changed, 28 insertions(+), 49 deletions(-) diff --git a/pandapower/control/util/diagnostic.py b/pandapower/control/util/diagnostic.py index e4d95f7d2..a092ccf07 100644 --- a/pandapower/control/util/diagnostic.py +++ b/pandapower/control/util/diagnostic.py @@ -3,8 +3,6 @@ # Copyright (c) 2016-2024 by University of Kassel and Fraunhofer Institute for Energy Economics # and Energy System Technology (IEE), Kassel. All rights reserved. from copy import deepcopy -import numpy as np -import pandas as pd from pandapower.control.util.auxiliary import get_controller_index from pandapower.control.controller.trafo_control import TrafoController @@ -64,54 +62,35 @@ def control_diagnostic(net, respect_in_service=True): trafo_ctrl.remove(val) -def trafo_characteristics_diagnostic(net): - logger.info("Checking transformer characteristics") - cols2w = ["vk_percent_characteristic", "vkr_percent_characteristic"] - cols3w = [f"vk{r}_{side}_percent_characteristic" for side in ["hv", "mv", "lv"] for r in ["", "r"]] +def trafo_characteristic_table_diagnostic(net): + logger.info("Checking transformer characteristic table") + if "trafo_characteristic_table" not in net: + logger.info("No transformer characteristic table found") + return False + cols2w = ["id_characteristic", "step", "voltage_ratio", "angle_deg", "vk_percent", "vkr_percent"] + cols3w = ["id_characteristic", "step", "voltage_ratio", "angle_deg", "vk_hv_percent", "vkr_hv_percent", + "vk_mv_percent", "vkr_mv_percent", "vk_lv_percent", "vkr_lv_percent"] for trafo_table, cols in zip(["trafo", "trafo3w"], [cols2w, cols3w]): if len(net[trafo_table]) == 0 or \ - 'tap_dependent_impedance' not in net[trafo_table] or \ - not net[trafo_table]['tap_dependent_impedance'].any(): - logger.info("No %s with tap-dependent impedance found." % trafo_table) + not all(col in net[trafo_table] for col in ['id_characteristic_table', 'tap_dependency_table']) or \ + not net[trafo_table]['id_characteristic_table'].notna().any() or \ + not net[trafo_table]['tap_dependency_table'].any(): + logger.warning("No %s with tap-dependent characteristics found." % trafo_table) continue - # check if there are any missing characteristics - tap_dependent_impedance = net[trafo_table]['tap_dependent_impedance'].fillna(False).values - logger.info( - f"{trafo_table}: found {sum(tap_dependent_impedance)} transformer(s) with tap-dependent" - " impedance") - if len(np.intersect1d(net[trafo_table].columns, cols)) == 0: - logger.warning("No columns defined for transformer tap characteristics in %s. " - "Power flow calculation will raise an error." % trafo_table) - elif net[trafo_table].loc[tap_dependent_impedance, np.intersect1d( - cols, net[trafo_table].columns)].isnull().all(axis=1).any(): + # check if both tap_dependency_table & id_characteristic_table columns are populated + mismatch = net[trafo_table][ + net[trafo_table]['tap_dependency_table'] ^ net[trafo_table]['id_characteristic_table'].notna()].shape[0] + if mismatch != 0: logger.warning( - f"Some transformers in {trafo_table} table have tap_dependent_impedance set to " - f"True, but no defined characteristics. Power flow calculation will raise an error.") - for col in cols: - if col not in net[trafo_table]: - logger.info("%s: %s is missing" % (trafo_table, col)) - continue - elif net[trafo_table].loc[tap_dependent_impedance, col].isnull().any(): - logger.info("%s: %s is missing for some transformers" % (trafo_table, col)) - elif len(set(net[trafo_table].loc[tap_dependent_impedance, col]) - \ - set(net.characteristic.index)) > 0: - logger.info("%s: %s contains invalid characteristics indices" % (trafo_table, col)) - else: - logger.debug(f"{trafo_table}: {col} has {len(net[trafo_table][col].dropna())} " - "characteristics") - - # chack if any characteristics have value at the neutral point that deviates from the transformer parameter - variable = col.replace("_characteristic", "") - for element_index in net[trafo_table].index[tap_dependent_impedance]: - tap_neutral = net[trafo_table].tap_neutral.fillna(0).at[element_index] - s_id = net[trafo_table][col].at[element_index] - if pd.isnull(s_id): - continue - s = net.characteristic.object.at[s_id] - s_val = s(tap_neutral) - var_val = net[trafo_table].at[element_index, variable] - if not np.isclose(s_val, var_val, rtol=0, atol=1e-6): - logger.warning( - f"The characteristic value of {s_val} at the neutral tap position " - f"{tap_neutral} does not match the value {var_val} of {variable} for the " - f"{trafo_table} with index {element_index} (deviation of {s_val-var_val})") + f"{trafo_table}: found {mismatch} transformer(s) with not both " + f"tap_dependency_table and id_characteristic_table parameters populated. " + f"Power flow calculation will raise an error.") + # check if all relevant columns are populated in the trafo_characteristic_table + temp = net[trafo_table].dropna(subset=["id_characteristic_table"])[ + ["tap_dependency_table", "id_characteristic_table"]] + merged_df = temp.merge(net["trafo_characteristic_table"], left_on="id_characteristic_table", + right_on="id_characteristic", how="inner") + unpopulated = merged_df.loc[~merged_df[cols].notna().all(axis=1)] + if not unpopulated.empty: + logger.warning(f"There are some transformers in the {trafo_table} table with not all characteristics " + f"populated in the trafo_characteristic_table.") From 9b4286e390a705716d8a5cc16650b2dee5a92207 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 28 Nov 2024 15:02:30 +0200 Subject: [PATCH 015/125] update __init__.py lib (rename import) --- pandapower/control/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pandapower/control/__init__.py b/pandapower/control/__init__.py index 04d9e5cdf..689918630 100644 --- a/pandapower/control/__init__.py +++ b/pandapower/control/__init__.py @@ -20,4 +20,4 @@ from pandapower.control.run_control import * from pandapower.control.util.characteristic import Characteristic, SplineCharacteristic from pandapower.control.util.auxiliary import get_controller_index, plot_characteristic, create_trafo_characteristics -from pandapower.control.util.diagnostic import control_diagnostic, trafo_characteristics_diagnostic +from pandapower.control.util.diagnostic import control_diagnostic, trafo_characteristic_table_diagnostic From 82ca8fc42fb92c7d645a5730a0818840755bedf1 Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Thu, 28 Nov 2024 14:32:37 +0100 Subject: [PATCH 016/125] WIP trafo --- pandapower/build_branch.py | 56 ++++++++++++++++++++++++++------------ 1 file changed, 39 insertions(+), 17 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 9c7385cde..9faad48b3 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -562,7 +562,6 @@ def _calc_tap_from_dataframe(net, trafo_df): tap_pos = get_trafo_values(trafo_df, f"tap{t}_pos") tap_neutral = get_trafo_values(trafo_df, f"tap{t}_neutral") tap_diff = tap_pos - tap_neutral - tap_phase_shifter = get_trafo_values(trafo_df, f"tap{t}_phase_shifter") tap_side = get_trafo_values(trafo_df, f"tap{t}_side") tap_step_percent = get_trafo_values(trafo_df, f"tap{t}_step_percent") tap_step_degree = get_trafo_values(trafo_df, f"tap{t}_step_degree") @@ -573,23 +572,46 @@ def _calc_tap_from_dataframe(net, trafo_df): if 'tap_dependency_table' in trafo_df: phase_shifter_type = get_trafo_values(trafo_df, f"tap{t}_phase_shifter_type") - print("do something") - for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: - # ideal_phase_shifter = 1 - if ideal_phase_shifter.any(): - degree_is_set = _replace_nan(tap_step_degree[phase_shifters]) != 0 - percent_is_set = _replace_nan(tap_step_percent[phase_shifters]) != 0 - if (degree_is_set & percent_is_set).any(): - raise UserWarning( - "Both tap_step_degree and tap_step_percent set for ideal phase shifter") - trafo_shift[phase_shifters] += np.where( - (degree_is_set), - (direction * tap_diff[phase_shifters] * tap_step_degree[phase_shifters]), - (direction * 2 * np.rad2deg(np.arcsin(tap_diff[phase_shifters] * \ - tap_step_percent[phase_shifters] / 100 / 2))) - ) - + tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") + id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") + phase_shifter_type = phase_shifter_type.fillna(-1) + tap_table = np.logical_and(tap_dependency, np.logical_not(phase_shifter_type == -1)) + tap_no_table = np.logical_and(tap_dependency == False, np.logical_not(phase_shifter_type == -1)) + if any(tap_table): + for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: + print("do something") + id = id_characteristic_table[tap_table] + vn[tap_table] = 1 + vn[tap_table] = net.trafo_characteristic_table.loc[net.trafo_characteristic_table.id_characteristic.isin(id) & net.trafo_characteristic_table.step.isin(tap_pos[tap_table])] #& net.trafo_characteristic_table.step.isin(tap_pos[tap_table]) + trafo_shift[tap_table] = 1 + if any(tap_no_table): + tap_ideal = np.logical_and(phase_shifter_type == 2, tap_no_table) + tap_complex = np.logical_and(np.logical_or(phase_shifter_type == 0, phase_shifter_type == 1), tap_no_table) + for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: + if any(tap_ideal): + degree_is_set = _replace_nan(tap_step_degree[tap_ideal]) != 0 + percent_is_set = _replace_nan(tap_step_percent[tap_ideal]) != 0 + if (degree_is_set & percent_is_set).any(): + raise UserWarning( + "Both tap_step_degree and tap_step_percent set for ideal phase shifter") + trafo_shift[tap_ideal] += np.where( + (degree_is_set), + (direction * tap_diff[phase_shifter_type == 2] * tap_step_degree[phase_shifter_type == 2]), + (direction * 2 * np.rad2deg(np.arcsin(tap_diff[phase_shifter_type == 2] * \ + tap_step_percent[phase_shifter_type == 2] / 100 / 2))) + ) + elif any(tap_complex): + + print("do something else:") + tap_steps = tap_step_percent[tap_complex] * tap_diff[tap_complex] / 100 + tap_angles = _replace_nan(tap_step_degree[tap_complex]) + u1 = vn[tap_complex] + du = u1 * _replace_nan(tap_steps) + vn[tap_complex] = np.sqrt((u1 + du * cos(tap_angles)) ** 2 + (du * sin(tap_angles)) ** 2) + trafo_shift[tap_complex] += (arctan(direction * du * sin(tap_angles) / + (u1 + du * cos(tap_angles)))) else: + tap_phase_shifter = get_trafo_values(trafo_df, f"tap{t}_phase_shifter") for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: phase_shifters = tap_phase_shifter & (tap_side == side) tap_complex = np.isfinite(tap_step_percent) & np.isfinite(tap_pos) & (tap_side == side) & \ From 3d6d9d310549294147d53968f0cd207f4c25dfb0 Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Fri, 29 Nov 2024 10:44:43 +0100 Subject: [PATCH 017/125] WIP trafo phase shifter reworking --- pandapower/build_branch.py | 47 ++++++++++++++++++++++---------------- 1 file changed, 27 insertions(+), 20 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 9faad48b3..99c88e857 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -574,16 +574,22 @@ def _calc_tap_from_dataframe(net, trafo_df): phase_shifter_type = get_trafo_values(trafo_df, f"tap{t}_phase_shifter_type") tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") - phase_shifter_type = phase_shifter_type.fillna(-1) + phase_shifter_type = phase_shifter_type.to_numpy() if not isinstance(trafo_df, dict) else phase_shifter_type + phase_shifter_type = np.nan_to_num(phase_shifter_type, nan=-1) tap_table = np.logical_and(tap_dependency, np.logical_not(phase_shifter_type == -1)) tap_no_table = np.logical_and(tap_dependency == False, np.logical_not(phase_shifter_type == -1)) if any(tap_table): for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: - print("do something") - id = id_characteristic_table[tap_table] - vn[tap_table] = 1 - vn[tap_table] = net.trafo_characteristic_table.loc[net.trafo_characteristic_table.id_characteristic.isin(id) & net.trafo_characteristic_table.step.isin(tap_pos[tap_table])] #& net.trafo_characteristic_table.step.isin(tap_pos[tap_table]) - trafo_shift[tap_table] = 1 + mask = tap_table & (side == tap_side) + filter = pd.DataFrame({ + 'id_characteristic': id_characteristic_table, + 'step': tap_pos, + 'mask': mask + }) + + filtered_df = net.trafo_characteristic_table.merge(filter[filter['mask']], on=['id_characteristic', 'step']) + vn[mask] = vn[mask] * filtered_df['voltage_ratio'] + trafo_shift[mask] = filtered_df['angle_deg'] if any(tap_no_table): tap_ideal = np.logical_and(phase_shifter_type == 2, tap_no_table) tap_complex = np.logical_and(np.logical_or(phase_shifter_type == 0, phase_shifter_type == 1), tap_no_table) @@ -601,8 +607,6 @@ def _calc_tap_from_dataframe(net, trafo_df): tap_step_percent[phase_shifter_type == 2] / 100 / 2))) ) elif any(tap_complex): - - print("do something else:") tap_steps = tap_step_percent[tap_complex] * tap_diff[tap_complex] / 100 tap_angles = _replace_nan(tap_step_degree[tap_complex]) u1 = vn[tap_complex] @@ -613,9 +617,9 @@ def _calc_tap_from_dataframe(net, trafo_df): else: tap_phase_shifter = get_trafo_values(trafo_df, f"tap{t}_phase_shifter") for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: - phase_shifters = tap_phase_shifter & (tap_side == side) + tap_ideal = tap_phase_shifter & (tap_side == side) tap_complex = np.isfinite(tap_step_percent) & np.isfinite(tap_pos) & (tap_side == side) & \ - ~phase_shifters + ~tap_ideal if tap_complex.any(): tap_steps = tap_step_percent[tap_complex] * tap_diff[tap_complex] / 100 tap_angles = _replace_nan(tap_step_degree[tap_complex]) @@ -624,17 +628,17 @@ def _calc_tap_from_dataframe(net, trafo_df): vn[tap_complex] = np.sqrt((u1 + du * cos(tap_angles)) ** 2 + (du * sin(tap_angles)) ** 2) trafo_shift[tap_complex] += (arctan(direction * du * sin(tap_angles) / (u1 + du * cos(tap_angles)))) - if phase_shifters.any(): - degree_is_set = _replace_nan(tap_step_degree[phase_shifters]) != 0 - percent_is_set = _replace_nan(tap_step_percent[phase_shifters]) != 0 + if tap_ideal.any(): + degree_is_set = _replace_nan(tap_step_degree[tap_ideal]) != 0 + percent_is_set = _replace_nan(tap_step_percent[tap_ideal]) != 0 if (degree_is_set & percent_is_set).any(): raise UserWarning( "Both tap_step_degree and tap_step_percent set for ideal phase shifter") - trafo_shift[phase_shifters] += np.where( + trafo_shift[tap_ideal] += np.where( (degree_is_set), - (direction * tap_diff[phase_shifters] * tap_step_degree[phase_shifters]), - (direction * 2 * np.rad2deg(np.arcsin(tap_diff[phase_shifters] * \ - tap_step_percent[phase_shifters] / 100 / 2))) + (direction * tap_diff[tap_ideal] * tap_step_degree[tap_ideal]), + (direction * 2 * np.rad2deg(np.arcsin(tap_diff[tap_ideal] * \ + tap_step_percent[tap_ideal] / 100 / 2))) ) return vnh, vnl, trafo_shift @@ -1242,9 +1246,12 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): trafo2["vn_lv_kv"] = {side: t3["vn_%s_kv" % side].values for side in sides} trafo2["shift_degree"] = {"hv": np.zeros(nr_trafos), "mv": t3.shift_mv_degree.values, "lv": t3.shift_lv_degree.values} - trafo2["tap_phase_shifter"] = {side: np.zeros(nr_trafos).astype(bool) for side in sides} - trafo2["tap_characteristic_table"] = {side: t3.tap_characteristic_table for side in sides} - trafo2["id_characteristic_table"] = {side: t3.id_characteristic_table for side in sides} + if 'tap_dependency_table' in t3: + trafo2["tap_phase_shifter_type"] = {side: t3.tap_phase_shifter_type for side in sides} + trafo2["tap_dependency_table"] = {side: t3.tap_dependency_table for side in sides} + trafo2["id_characteristic_table"] = {side: t3.id_characteristic_table for side in sides} + else: + trafo2["tap_phase_shifter"] = {side: np.zeros(nr_trafos).astype(bool) for side in sides} trafo2["parallel"] = {side: np.ones(nr_trafos) for side in sides} trafo2["df"] = {side: np.ones(nr_trafos) for side in sides} # even though this is not relevant (at least now), the values cannot be empty: From b90ac2b52119f03f5db50d390c7bac68f673837a Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 29 Nov 2024 22:37:04 +0200 Subject: [PATCH 018/125] update auxiliary.py function (fix bug); update testing libraries --- pandapower/control/__init__.py | 3 +- pandapower/control/util/auxiliary.py | 5 +- pandapower/test/api/test_auxiliary.py | 140 +++++++++++++-------- pandapower/test/converter/test_from_cim.py | 102 +++++++++------ 4 files changed, 157 insertions(+), 93 deletions(-) diff --git a/pandapower/control/__init__.py b/pandapower/control/__init__.py index 689918630..c2905f713 100644 --- a/pandapower/control/__init__.py +++ b/pandapower/control/__init__.py @@ -19,5 +19,6 @@ # --- Other --- from pandapower.control.run_control import * from pandapower.control.util.characteristic import Characteristic, SplineCharacteristic -from pandapower.control.util.auxiliary import get_controller_index, plot_characteristic, create_trafo_characteristics +from pandapower.control.util.auxiliary import (get_controller_index, plot_characteristic, create_trafo_characteristics, + create_trafo_characteristic_object) from pandapower.control.util.diagnostic import control_diagnostic, trafo_characteristic_table_diagnostic diff --git a/pandapower/control/util/auxiliary.py b/pandapower/control/util/auxiliary.py index d85ef1605..b1a99479d 100644 --- a/pandapower/control/util/auxiliary.py +++ b/pandapower/control/util/auxiliary.py @@ -281,9 +281,8 @@ def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_point "vk_mv_percent_characteristic", "vkr_mv_percent_characteristic", "vk_lv_percent_characteristic", "vkr_lv_percent_characteristic"]} - # create id_characteristic_spline column - same indices as id_characteristic_table - if "id_characteristic_spline" not in net[trafotable]: - net[trafotable]["id_characteristic_spline"] = net[trafotable]["id_characteristic_table"].copy() + # create or re-populate id_characteristic_spline column - same indices as id_characteristic_table + net[trafotable]["id_characteristic_spline"] = net[trafotable]["id_characteristic_table"].copy() if "trafo_characteristic_spline_temp" not in net: col_list = list(dict.fromkeys(supported_columns["trafo"] + supported_columns["trafo3w"])) net["trafo_characteristic_spline_temp"] = pd.DataFrame(columns=col_list, dtype="Int64") diff --git a/pandapower/test/api/test_auxiliary.py b/pandapower/test/api/test_auxiliary.py index be6c60a24..344fe040b 100644 --- a/pandapower/test/api/test_auxiliary.py +++ b/pandapower/test/api/test_auxiliary.py @@ -208,50 +208,82 @@ def test_memory_leak_dict(): def test_create_trafo_characteristics(): net = pp.networks.example_multivoltage() - - # test 2 modes, multiple index and single index, for 2w trafo - pp.control.create_trafo_characteristics(net, "trafo", [1], 'vk_percent', [[-2,-1,0,1,2]], [[2,3,4,5,6]]) - assert "characteristic" in net - assert "tap_dependent_impedance" in net.trafo.columns - assert net.trafo.tap_dependent_impedance.dtype == np.bool_ - assert net.trafo.tap_dependent_impedance.at[1] - assert not net.trafo.tap_dependent_impedance.at[0] - assert "vk_percent_characteristic" in net.trafo.columns - assert net.trafo.at[1, 'vk_percent_characteristic'] == 0 - assert pd.isnull(net.trafo.at[0, 'vk_percent_characteristic']) - assert net.trafo.vk_percent_characteristic.dtype == pd.Int64Dtype() - assert "vkr_percent_characteristic" not in net.trafo.columns - - pp.control.create_trafo_characteristics(net, "trafo", 1, 'vkr_percent', [-2,-1,0,1,2], [1.323,1.324,1.325,1.326,1.327]) - assert len(net.characteristic) == 2 - assert "vkr_percent_characteristic" in net.trafo.columns - assert net.trafo.at[1, 'vkr_percent_characteristic'] == 1 - assert pd.isnull(net.trafo.at[0, 'vkr_percent_characteristic']) - assert net.trafo.vkr_percent_characteristic.dtype == pd.Int64Dtype() - - assert isinstance(net.characteristic.object.at[0], pp.control.SplineCharacteristic) - assert isinstance(net.characteristic.object.at[1], pp.control.SplineCharacteristic) + net["trafo_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [1, 1, 1, 1, 1], + 'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [2, 3, 4, 5, 6], + 'vkr_percent': [1.323, 1.324, 1.325, 1.326, 1.327], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan, + 'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan}) + net.trafo['id_characteristic_table'].at[1] = 0 + net.trafo['tap_dependency_table'].at[0] = False + net.trafo['tap_dependency_table'].at[1] = True + # add spline characteristics for one transformer based on trafo_characteristic_table + pp.control.create_trafo_characteristic_object(net) + assert "trafo_characteristic_spline" in net + assert "id_characteristic_spline" in net.trafo.columns + assert len(net.trafo_characteristic_spline) == 1 + assert net.trafo.id_characteristic_spline.dtype == pd.Int64Dtype() + assert isinstance(net.trafo.id_characteristic_spline.at[1], np.int64) + assert pd.isna(net.trafo.id_characteristic_spline.at[0]) + assert all(col in net.trafo_characteristic_spline.columns for col in [ + 'voltage_ratio_characteristic', 'angle_deg_characteristic', + 'vk_percent_characteristic', 'vkr_percent_characteristic']) + assert isinstance(net.trafo_characteristic_spline.at[ + net.trafo.id_characteristic_spline.at[1], 'vk_percent_characteristic'], + pp.control.SplineCharacteristic) + assert net.trafo_characteristic_spline.at[ + net.trafo.id_characteristic_spline.at[1], 'vk_percent_characteristic'](-2) == 2 + assert pd.isna(net.trafo_characteristic_spline.at[ + net.trafo.id_characteristic_spline.at[1], 'vkr_hv_percent_characteristic']) + + # create spline characteristics again for two transformers based on the updated trafo_characteristic_table + new_rows = pd.DataFrame( + {'id_characteristic': [1, 1, 1, 1, 1], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [1, 1, 1, 1, 1], + 'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [2, 3, 4, 5, 6], + 'vkr_percent': [1.323, 1.324, 1.325, 1.326, 1.327]}) + net["trafo_characteristic_table"] = pd.concat([net["trafo_characteristic_table"], new_rows], ignore_index=True) + net.trafo['id_characteristic_table'].at[0] = 1 + net.trafo['tap_dependency_table'].at[0] = True + pp.control.create_trafo_characteristic_object(net) + assert len(net.trafo_characteristic_spline) == 2 + assert net.trafo.at[0, 'id_characteristic_spline'] == 1 + assert isinstance(net.trafo_characteristic_spline.at[ + net.trafo.id_characteristic_spline.at[0], 'vk_percent_characteristic'], + pp.control.SplineCharacteristic) + assert net.trafo_characteristic_spline.at[ + net.trafo.id_characteristic_spline.at[0], 'vk_percent_characteristic'](2) == 6 + assert isinstance(net.trafo_characteristic_spline.at[ + net.trafo.id_characteristic_spline.at[1], 'vk_percent_characteristic'], + pp.control.SplineCharacteristic) + assert net.trafo_characteristic_spline.at[ + net.trafo.id_characteristic_spline.at[1], 'vk_percent_characteristic'](-1) == 3 + assert pd.isna(net.trafo_characteristic_spline.at[ + net.trafo.id_characteristic_spline.at[0], 'vkr_hv_percent_characteristic']) + assert pd.isna(net.trafo_characteristic_spline.at[ + net.trafo.id_characteristic_spline.at[1], 'vkr_hv_percent_characteristic']) # test for 3w trafo - pp.control.create_trafo_characteristics(net, "trafo3w", 0, 'vk_hv_percent', [-8, -4, 0, 4, 8], [8.1, 9.1, 10.1, 11.1, 12.1]) - assert "tap_dependent_impedance" in net.trafo3w.columns - assert net.trafo3w.tap_dependent_impedance.dtype == np.bool_ - assert net.trafo3w.tap_dependent_impedance.at[0] - assert "vk_hv_percent_characteristic" in net.trafo3w.columns - assert net.trafo3w.at[0, 'vk_hv_percent_characteristic'] == 2 - assert net.trafo3w.vk_hv_percent_characteristic.dtype == pd.Int64Dtype() - assert "vkr_hv_percent_characteristic" not in net.trafo3w.columns - assert "vk_mv_percent_characteristic" not in net.trafo3w.columns - - pp.control.create_trafo_characteristics(net, "trafo3w", 0, 'vk_mv_percent', [-8, -4, 0, 4, 8], [8.1, 9.1, 10.1, 11.1, 12.1]) - assert net.trafo3w.tap_dependent_impedance.dtype == np.bool_ - assert net.trafo3w.tap_dependent_impedance.at[0] - assert "vk_mv_percent_characteristic" in net.trafo3w.columns - assert net.trafo3w.at[0, 'vk_mv_percent_characteristic'] == 3 - assert net.trafo3w.vk_hv_percent_characteristic.dtype == pd.Int64Dtype() - assert "vkr_mv_percent_characteristic" not in net.trafo3w.columns - assert "vk_lv_percent_characteristic" not in net.trafo3w.columns - assert "vkr_lv_percent_characteristic" not in net.trafo3w.columns + new_rows = pd.DataFrame( + {'id_characteristic': [2, 2, 2, 2, 2], 'step': [-8, -4, 0, 4, 8], 'voltage_ratio': [1, 1, 1, 1, 1], + 'angle_deg': [0, 0, 0, 0, 0], 'vk_hv_percent': [8.1, 9.1, 10.1, 11.1, 12.1], + 'vkr_hv_percent': [1.323, 1.324, 1.325, 1.326, 1.327], 'vk_mv_percent': [8.1, 9.1, 10.1, 11.1, 12.1], + 'vkr_mv_percent': [1.323, 1.324, 1.325, 1.326, 1.327], 'vk_lv_percent': [8.1, 9.1, 10.1, 11.1, 12.1], + 'vkr_lv_percent': [1.323, 1.324, 1.325, 1.326, 1.327]}) + net["trafo_characteristic_table"] = pd.concat([net["trafo_characteristic_table"], new_rows], ignore_index=True) + net.trafo3w['id_characteristic_table'].at[0] = 2 + net.trafo3w['tap_dependency_table'].at[0] = True + # create spline characteristics again including a 3-winding transformer + pp.control.create_trafo_characteristic_object(net) + assert len(net.trafo_characteristic_spline) == 3 + assert "id_characteristic_spline" in net.trafo3w.columns + assert isinstance(net.trafo3w.id_characteristic_spline.at[0], np.int64) + assert net.trafo_characteristic_spline.loc[net.trafo3w['id_characteristic_table'].at[0]].notna().sum() == 9 + assert isinstance(net.trafo_characteristic_spline.at[ + net.trafo3w.id_characteristic_spline.at[0], 'vkr_hv_percent_characteristic'], + pp.control.SplineCharacteristic) + assert net.trafo_characteristic_spline.at[ + net.trafo3w.id_characteristic_spline.at[0], 'vkr_hv_percent_characteristic'](-4) == 1.324 + assert pd.isna(net.trafo_characteristic_spline.at[ + net.trafo3w.id_characteristic_spline.at[0], 'vk_percent_characteristic']) # this should be enough testing for adding columns # now let's test if it raises errors @@ -283,34 +315,34 @@ def test_create_trafo_characteristics(): @pytest.mark.parametrize("file_io", (False, True), ids=("Without JSON I/O", "With JSON I/O")) def test_characteristic(file_io): net = pp.create_empty_network() - c1 = SplineCharacteristic(net, [0,1,2], [0, 1, 4], fill_value=(0, 4)) - c2 = SplineCharacteristic(net, [0,1,2], [0, 1, 4], interpolator_kind="Pchip", extrapolate=False) - c3 = SplineCharacteristic(net, [0,1,2], [0, 1, 4], interpolator_kind="hello") - c4 = LogSplineCharacteristic(net, [0,1,2], [0, 1, 4], interpolator_kind="Pchip", extrapolate=False) + c1 = SplineCharacteristic(net, [0, 1, 2], [0, 1, 4], fill_value=(0, 4)) + c2 = SplineCharacteristic(net, [0, 1, 2], [0, 1, 4], interpolator_kind="Pchip", extrapolate=False) + c3 = SplineCharacteristic(net, [0, 1, 2], [0, 1, 4], interpolator_kind="hello") + c4 = LogSplineCharacteristic( + net, [0, 1, 2], [0, 1, 4], interpolator_kind="Pchip", extrapolate=False) if file_io: net_copy = pp.from_json_string(pp.to_json(net)) c1, c2, c3, c4 = net_copy.characteristic.object.values assert np.allclose(c1([-1]), [0], rtol=0, atol=1e-6) - #assert c1(3) == 4 - #assert c1(1) == 1 - #assert c1(2) == 4 - #assert c1(1.5) == 2.25 - + # assert c1(3) == 4 + # assert c1(1) == 1 + # assert c1(2) == 4 + # assert c1(1.5) == 2.25 # test that unknown kind causes error: with pytest.raises(NotImplementedError): c3([0]) + def test_log_characteristic_property(): net = pp.create_empty_network() - c = LogSplineCharacteristic(net, [10, 1000, 10000], [1000, 0.1, 0.001], interpolator_kind="Pchip", extrapolate=False) + c = LogSplineCharacteristic(net, [10, 1000, 10000], [1000, 0.1, 0.001], + interpolator_kind="Pchip", extrapolate=False) c._x_vals c([2]) - - if __name__ == '__main__': pytest.main([__file__, "-xs"]) diff --git a/pandapower/test/converter/test_from_cim.py b/pandapower/test/converter/test_from_cim.py index 6930f1d15..2aac5bf18 100644 --- a/pandapower/test/converter/test_from_cim.py +++ b/pandapower/test/converter/test_from_cim.py @@ -1,4 +1,6 @@ import os + +import numpy as np import pytest import math import pandas as pd @@ -8,6 +10,8 @@ from pandapower.converter import from_cim as cim2pp +from pandapower.control.util.auxiliary import create_trafo_characteristic_object, create_shunt_characteristic_object + @pytest.fixture(scope="session") def fullgrid_v2(): @@ -18,6 +22,21 @@ def fullgrid_v2(): return cim2pp.from_cim(file_list=cgmes_files) + +@pytest.fixture(scope="session") +def fullgrid_v2_spline(): + folder_path = os.path.join(test_path, "test_files", "example_cim") + + cgmes_files = [os.path.join(folder_path, 'CGMES_v2.4.15_FullGridTestConfiguration_BB_BE_v1.zip'), + os.path.join(folder_path, 'CGMES_v2.4.15_FullGridTestConfiguration_BD_v1.zip')] + + net = cim2pp.from_cim(file_list=cgmes_files) + create_trafo_characteristic_object(net) + create_shunt_characteristic_object(net) + + return net + + @pytest.fixture(scope="session") def fullgrid_v3(): folder_path = os.path.join(test_path, "test_files", "example_cim") @@ -659,7 +678,7 @@ def test_fullgrid_trafo3w(fullgrid_v2): assert 'RatioTapChanger' == element_0['tapchanger_class'].item() assert '_fe25f43a-7341-446e-a71a-8ab7119ba806' == element_0['tapchanger_id'].item() assert 'YYY' == element_0['vector_group'].item() - assert isinstance(element_0['id_characteristic'].item(), float) + assert isinstance(element_0['id_characteristic_table'].item(), np.int64) assert math.isnan(element_0['vk0_hv_percent'].item()) assert math.isnan(element_0['vk0_mv_percent'].item()) assert math.isnan(element_0['vk0_lv_percent'].item()) @@ -667,13 +686,22 @@ def test_fullgrid_trafo3w(fullgrid_v2): assert math.isnan(element_0['vkr0_mv_percent'].item()) assert math.isnan(element_0['vkr0_lv_percent'].item()) assert not element_0['power_station_unit'].item() - assert element_0['tap_dependent_impedance'].item() - assert 14 == element_0['vk_hv_percent_characteristic'].item() - assert 16 == element_0['vk_mv_percent_characteristic'].item() - assert 18 == element_0['vk_lv_percent_characteristic'].item() - assert 15 == element_0['vkr_hv_percent_characteristic'].item() - assert 17 == element_0['vkr_mv_percent_characteristic'].item() - assert 19 == element_0['vkr_lv_percent_characteristic'].item() + assert element_0['tap_dependency_table'].item() + + +def test_fullgrid_trafo3w_spline(fullgrid_v2_spline): + assert "trafo_characteristic_spline" in fullgrid_v2_spline + element_0 = fullgrid_v2_spline.trafo3w[ + fullgrid_v2_spline.trafo3w['origin_id'] == '_84ed55f4-61f5-4d9d-8755-bba7b877a246'] + cols = ["voltage_ratio_characteristic", "angle_deg_characteristic", + "vk_hv_percent_characteristic", "vkr_hv_percent_characteristic", "vk_mv_percent_characteristic", + "vkr_mv_percent_characteristic", "vk_lv_percent_characteristic", "vkr_lv_percent_characteristic"] + spline_row = fullgrid_v2_spline["trafo_characteristic_spline"][ + fullgrid_v2_spline["trafo_characteristic_spline"]["id_characteristic"] == element_0[ + 'id_characteristic_spline'].item()] + assert 7 == element_0['id_characteristic_spline'].item() + assert not spline_row.empty + assert spline_row[cols].notna().all(axis=1).item() def test_fullgrid_trafo(fullgrid_v2): @@ -698,7 +726,7 @@ def test_fullgrid_trafo(fullgrid_v2): assert 1.250 == element_0['tap_step_percent'].item() assert math.isnan(element_0['tap_step_degree'].item()) assert -2.0 == element_0['tap_pos'].item() - assert not element_0['tap_phase_shifter'].item() + assert 0 == element_0['tap_phase_shifter_type'].item() assert 1.0 == element_0['parallel'].item() assert 1.0 == element_0['df'].item() assert element_0['in_service'].item() @@ -710,15 +738,13 @@ def test_fullgrid_trafo(fullgrid_v2): assert 'RatioTapChanger' == element_0['tapchanger_class'].item() assert '_f6b6428b-d201-4170-89f3-4f630c662b7c' == element_0['tapchanger_id'].item() assert 'YY' == element_0['vector_group'].item() - assert isinstance(element_0['id_characteristic'].item(), float) + assert isinstance(element_0['id_characteristic_table'].item(), np.int64) assert math.isnan(element_0['vk0_percent'].item()) assert math.isnan(element_0['vkr0_percent'].item()) assert math.isnan(element_0['xn_ohm'].item()) assert not element_0['power_station_unit'].item() assert not element_0['oltc'].item() - assert element_0['tap_dependent_impedance'].item() - assert 0 == element_0['vkr_percent_characteristic'].item() - assert 1 == element_0['vk_percent_characteristic'].item() + assert element_0['tap_dependency_table'].item() element_1 = fullgrid_v2.trafo[fullgrid_v2.trafo['origin_id'] == '_99f55ee9-2c75-3340-9539-b835ec8c5994'] assert 'BE-TR2_6' == element_1['name'].item() @@ -740,7 +766,7 @@ def test_fullgrid_trafo(fullgrid_v2): assert math.isnan(element_1['tap_step_percent'].item()) assert math.isnan(element_1['tap_step_degree'].item()) assert math.isnan(element_1['tap_pos'].item()) - assert not element_1['tap_phase_shifter'].item() + assert pd.isna(element_1['tap_phase_shifter_type'].item()) assert 1.0 == element_1['parallel'].item() assert 1.0 == element_1['df'].item() assert element_1['in_service'].item() @@ -752,23 +778,38 @@ def test_fullgrid_trafo(fullgrid_v2): assert math.isnan(element_1['tapchanger_class'].item()) assert math.isnan(element_1['tapchanger_id'].item()) assert 'YY' == element_1['vector_group'].item() - assert isinstance(element_1['id_characteristic'].item(), float) + assert isinstance(element_1['id_characteristic_table'].item(), np.int64) assert math.isnan(element_1['vk0_percent'].item()) assert math.isnan(element_1['vkr0_percent'].item()) assert math.isnan(element_1['xn_ohm'].item()) assert not element_1['power_station_unit'].item() assert not element_1['oltc'].item() - assert element_1['tap_dependent_impedance'].item() - assert 8 == element_1['vkr_percent_characteristic'].item() - assert 9 == element_1['vk_percent_characteristic'].item() + assert element_1['tap_dependency_table'].item() element_2 = fullgrid_v2.trafo[fullgrid_v2.trafo['origin_id'] == '_ff3a91ec-2286-a64c-a046-d62bc0163ffe'] assert 1.990 == element_2['tap_step_degree'].item() assert 'PhaseTapChangerLinear' == element_2['tapchanger_class'].item() - assert math.isnan(element_2['id_characteristic'].item()) - assert not element_2['tap_dependent_impedance'].item() - assert pd.isna(element_2['vkr_percent_characteristic'].item()) - assert pd.isna(element_2['vk_percent_characteristic'].item()) + assert 2 == element_2['tap_phase_shifter_type'].item() + assert pd.isna(element_2['id_characteristic_table'].item()) + assert not element_2['tap_dependency_table'].item() + + +def test_fullgrid_trafo_spline(fullgrid_v2_spline): + assert "trafo_characteristic_spline" in fullgrid_v2_spline + element_0 = fullgrid_v2_spline.trafo[ + fullgrid_v2_spline.trafo['origin_id'] == '_99f55ee9-2c75-3340-9539-b835ec8c5994'] + cols = ["voltage_ratio_characteristic", "angle_deg_characteristic", + "vk_percent_characteristic", "vkr_percent_characteristic"] + spline_row = fullgrid_v2_spline["trafo_characteristic_spline"][ + fullgrid_v2_spline["trafo_characteristic_spline"]["id_characteristic"] == element_0[ + 'id_characteristic_spline'].item()] + assert 0 == element_0['id_characteristic_spline'].item() + assert not spline_row.empty + assert spline_row[cols].notna().all(axis=1).item() + + element_1 = fullgrid_v2_spline.trafo[ + fullgrid_v2_spline.trafo['origin_id'] == '_ff3a91ec-2286-a64c-a046-d62bc0163ffe'] + assert pd.isna(element_1['id_characteristic_spline'].item()) def test_fullgrid_tcsc(fullgrid_v2): @@ -812,6 +853,8 @@ def test_fullgrid_shunt(fullgrid_v2): assert element_0['in_service'].item() assert 'LinearShuntCompensator' == element_0['origin_class'].item() assert '_d5e2e58e-ccf6-47d9-b3bb-3088eb7a9b6c' == element_0['terminal'].item() + assert not element_0['step_dependency_table'].item() + assert pd.isna(element_0['id_characteristic_table'].item()) def test_fullgrid_sgen(fullgrid_v2): @@ -1071,19 +1114,8 @@ def test_fullgrid_controller(fullgrid_v2): assert math.isnan(obj.object.vm_upper_pu) -def test_fullgrid_characteristic_temp(fullgrid_v2): - assert 8 == len(fullgrid_v2.characteristic_temp.index) - - -def test_fullgrid_characteristic(fullgrid_v2): - assert 20 == len(fullgrid_v2.characteristic.index) - for _, obj in fullgrid_v2.characteristic.iterrows(): - if obj.object.index == \ - fullgrid_v2.trafo[fullgrid_v2.trafo['origin_id'] == - '_99f55ee9-2c75-3340-9539-b835ec8c5994']['vkr_percent_characteristic'].item(): - assert [1] == obj.object.x_vals - assert [1.3405981856094185] == obj.object.y_vals - break +def test_fullgrid_trafo_characteristic_table(fullgrid_v2): + assert 8 == len(fullgrid_v2.trafo_characteristic_table.index) def test_fullgrid_bus_geodata(fullgrid_v2): From 56a573107ec379fca0ca0d3b178d16793cf47b95 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Sat, 30 Nov 2024 15:18:25 +0200 Subject: [PATCH 019/125] update create.py, diagnostic.py & test_tap_dependent_impedance.py libs (tests passed) --- pandapower/control/util/diagnostic.py | 29 +++-- pandapower/create.py | 6 +- .../control/test_tap_dependent_impedance.py | 107 +++++++----------- 3 files changed, 68 insertions(+), 74 deletions(-) diff --git a/pandapower/control/util/diagnostic.py b/pandapower/control/util/diagnostic.py index a092ccf07..3603bfe1c 100644 --- a/pandapower/control/util/diagnostic.py +++ b/pandapower/control/util/diagnostic.py @@ -73,15 +73,17 @@ def trafo_characteristic_table_diagnostic(net): for trafo_table, cols in zip(["trafo", "trafo3w"], [cols2w, cols3w]): if len(net[trafo_table]) == 0 or \ not all(col in net[trafo_table] for col in ['id_characteristic_table', 'tap_dependency_table']) or \ - not net[trafo_table]['id_characteristic_table'].notna().any() or \ - not net[trafo_table]['tap_dependency_table'].any(): - logger.warning("No %s with tap-dependent characteristics found." % trafo_table) + (not net[trafo_table]['id_characteristic_table'].notna().any() and + not net[trafo_table]['tap_dependency_table'].any()): + logger.info("No %s with tap-dependent characteristics found." % trafo_table) continue # check if both tap_dependency_table & id_characteristic_table columns are populated mismatch = net[trafo_table][ - net[trafo_table]['tap_dependency_table'] ^ net[trafo_table]['id_characteristic_table'].notna()].shape[0] + (net[trafo_table]['tap_dependency_table'] & net[trafo_table]['id_characteristic_table'].isna()) | + (~net[trafo_table]['tap_dependency_table'] & net[trafo_table]['id_characteristic_table'].notna()) + ].shape[0] if mismatch != 0: - logger.warning( + raise UserWarning( f"{trafo_table}: found {mismatch} transformer(s) with not both " f"tap_dependency_table and id_characteristic_table parameters populated. " f"Power flow calculation will raise an error.") @@ -92,5 +94,18 @@ def trafo_characteristic_table_diagnostic(net): right_on="id_characteristic", how="inner") unpopulated = merged_df.loc[~merged_df[cols].notna().all(axis=1)] if not unpopulated.empty: - logger.warning(f"There are some transformers in the {trafo_table} table with not all characteristics " - f"populated in the trafo_characteristic_table.") + raise UserWarning(f"There are some transformers in the {trafo_table} table with not all characteristics " + f"populated in the trafo_characteristic_table.") + # check tap_dependency_table & id_characteristic_table column types + if net[trafo_table]['tap_dependency_table'].dtype != 'bool': + raise UserWarning(f"The tap_dependency_table column in the {trafo_table} table is not of bool type.") + if net[trafo_table]['id_characteristic_table'].dtype != 'Int64': + raise UserWarning(f"The id_characteristic_table column in the {trafo_table} table is not of Int64 type.") + # check if all id_characteristic_table values are present in id_characteristic column + # of trafo_characteristic_table + if not net[trafo_table]['id_characteristic_table'].isin( + net["trafo_characteristic_table"]['id_characteristic']).all(): + raise UserWarning(f"Not all id_characteristic_table values in the {trafo_table} table are present" + f"in id_characteristic column of trafo_characteristic_table. " + f"Power flow calculation will raise an error.") + return True diff --git a/pandapower/create.py b/pandapower/create.py index 77b5396a6..58f3f940a 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -3283,7 +3283,7 @@ def create_lines_dc_from_parameters(net, from_buses_dc, to_buses_dc, length_km, def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in_service=True, index=None, max_loading_percent=nan, parallel=1, df=1., tap_phase_shifter_type=nan, - tap_dependency_table=False, id_characteristic_table=nan, + tap_dependency_table=nan, id_characteristic_table=nan, pt_percent=nan, oltc=nan, xn_ohm=nan, tap2_pos=nan, **kwargs): """ Creates a two-winding transformer in table net["trafo"]. @@ -3410,6 +3410,10 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in _set_value_if_not_nan(net, index, max_loading_percent, "max_loading_percent", "trafo") _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo", dtype="Int64") + _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo", + dtype=bool_, default_val=False) + _set_value_if_not_nan(net, index, tap_phase_shifter_type, "tap_phase_shifter_type", + "trafo", dtype="Int64") _set_value_if_not_nan(net, index, pt_percent, "pt_percent", "trafo") _set_value_if_not_nan(net, index, oltc, "oltc", "trafo", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, xn_ohm, "xn_ohm", "trafo") diff --git a/pandapower/test/control/test_tap_dependent_impedance.py b/pandapower/test/control/test_tap_dependent_impedance.py index 1529a8990..ccc0ad3f9 100644 --- a/pandapower/test/control/test_tap_dependent_impedance.py +++ b/pandapower/test/control/test_tap_dependent_impedance.py @@ -1,5 +1,5 @@ # -*- coding: utf-8 -*- - +import pandas as pd # Copyright (c) 2016-2024 by University of Kassel and Fraunhofer Institute for Energy Economics # and Energy System Technology (IEE), Kassel. All rights reserved. @@ -9,7 +9,7 @@ import pandapower as pp from pandapower.control import Characteristic, SplineCharacteristic, TapDependentImpedance, \ - trafo_characteristics_diagnostic + trafo_characteristic_table_diagnostic # todo add tests for voltage_ratio and angle_dev @@ -64,7 +64,7 @@ def test_tap_dependent_impedance_restore(): # check if the impedance has been restored assert net.trafo.vk_percent.at[0] == 12.3 assert net.trafo.vkr_percent.at[0] == 0.5 - # check if the losses are different than at the neutral position -> the tap-dependent impedance has been conbsidered + # check if the losses are different from the neutral position -> the tap-dependent impedance has been considered assert abs(net.res_trafo.pl_mw.at[0] - pl_mw_neutral) > 0.015 net.trafo.tap_pos = 20 @@ -72,7 +72,7 @@ def test_tap_dependent_impedance_restore(): # check if the impedance has been restored assert net.trafo.vk_percent.at[0] == 12.3 assert net.trafo.vkr_percent.at[0] == 0.5 - # check if the losses are different than at the neutral position -> the tap-dependent impedance has been conbsidered + # check if the losses are different from the neutral position -> the tap-dependent impedance has been considered assert abs(net.res_trafo.pl_mw.at[0] - pl_mw_neutral) > 0.002 @@ -111,79 +111,54 @@ def test_characteristic(): assert c4(2) == 4 -def test_characteristic_diagnostic(): +def test_trafo_characteristic_table_diagnostic(): net = pp.create_empty_network() vn_kv = 20 b1 = pp.create_bus(net, vn_kv=vn_kv) pp.create_ext_grid(net, b1, vm_pu=1.01) b2 = pp.create_bus(net, vn_kv=vn_kv) - l1 = pp.create_line_from_parameters(net, b1, b2, 12.2, r_ohm_per_km=0.08, x_ohm_per_km=0.12, - c_nf_per_km=300, max_i_ka=.2, df=.8) + pp.create_line_from_parameters(net, b1, b2, 12.2, r_ohm_per_km=0.08, x_ohm_per_km=0.12, + c_nf_per_km=300, max_i_ka=.2, df=.8) cb = pp.create_bus(net, vn_kv=0.4) pp.create_load(net, cb, 0.2, 0.05) pp.create_transformer(net, hv_bus=b2, lv_bus=cb, std_type="0.25 MVA 20/0.4 kV", tap_pos=2) - pp.control.create_trafo_characteristics(net, 'trafo', 0, 'vk_percent', - [-2, -1, 0, 1, 2], [5, 5.2, 6, 6.8, 7]) # single mode - pp.control.create_trafo_characteristics(net, 'trafo', [0], 'vkr_percent', - [[-2, -1, 0, 1, 2]], [[1.3, 1.4, 1.44, 1.5, 1.6]]) # multiple indices + # initially no trafo_characteristic_table is available + assert trafo_characteristic_table_diagnostic(net) is False + + # add trafo_characteristic_table + net["trafo_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [1, 1, 1, 1, 1], + 'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [5, 5.2, 6, 6.8, 7], + 'vkr_percent': [1.3, 1.4, 1.44, 1.5, 1.6], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan, + 'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan}) + # populate id_characteristic_table parameter + net.trafo['id_characteristic_table'].at[0] = 0 + net.trafo['tap_dependency_table'].at[0] = False + with pytest.raises(UserWarning): + trafo_characteristic_table_diagnostic(net) + # populate tap_dependency_table parameter + net.trafo['tap_dependency_table'].at[0] = True + assert trafo_characteristic_table_diagnostic(net) is True + + # add trafo_characteristic_table with missing parameter values + net["trafo_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [1, 1, 1, 1, 1], + 'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [5, 5.2, 6, 6.8, 7], + 'vkr_percent': np.nan, 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan, + 'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan}) + with pytest.raises(UserWarning): + trafo_characteristic_table_diagnostic(net) # let's make some invalid configurations - net.trafo.at[0, "vk_percent"] += 1e-6 - # missing any characteristic - pp.create_transformer(net, hv_bus=net.trafo.at[0, 'hv_bus'], - lv_bus=net.trafo.at[0, 'lv_bus'], std_type="0.25 MVA 20/0.4 kV", tap_pos=2, - tap_dependent_impedance=True) - b2 = net.trafo.at[0, "hv_bus"] - cb = pp.create_bus(net, vn_kv=0.4) - pp.create_load(net, cb, 0.2, 0.05) - pp.create_transformer(net, hv_bus=b2, lv_bus=cb, std_type="0.25 MVA 20/0.4 kV", tap_pos=2) - # missing columns for characteristics - - cbm = pp.create_bus(net, vn_kv=0.9) - pp.create_load(net, cbm, 0.1, 0.03) - pp.create_transformer3w_from_parameters(net, hv_bus=b2, mv_bus=cbm, lv_bus=cb, - vn_hv_kv=20., vn_mv_kv=0.9, vn_lv_kv=0.45, sn_hv_mva=0.6, - sn_mv_mva=0.5, sn_lv_mva=0.4, vk_hv_percent=1., - vk_mv_percent=1., vk_lv_percent=1., vkr_hv_percent=0.3, - vkr_mv_percent=0.3, vkr_lv_percent=0.3, pfe_kw=0.2, - i0_percent=0.3, tap_neutral=0., tap_pos=2, - tap_step_percent=1., tap_min=-2, tap_max=2) - - net.trafo3w['tap_dependent_impedance'] = True - - import io - s = io.StringIO() - h = logging.StreamHandler(stream=s) - logger = pp.control.util.diagnostic.logger - logger.addHandler(h) - - old_level = logger.level - logger.setLevel("INFO") - trafo_characteristics_diagnostic(net) - logger.setLevel(old_level) - - msg = s.getvalue() - - assert "trafo: found 2 transformer(s) with tap-dependent impedance" in msg - assert "Power flow calculation will raise an error" in msg - assert "vk_percent_characteristic is missing for some transformers" in msg - assert "vk_percent_characteristic is missing for some transformers" in msg - assert "vkr_percent_characteristic is missing for some transformers" in msg - assert "The characteristic value of 6.0 at the neutral tap position 0 does not match the value 6.000001" in msg - assert "trafo3w: found 1 transformer(s) with tap-dependent impedance" in msg - assert "No columns defined for transformer tap characteristics in trafo3w" in msg - assert "vk_hv_percent_characteristic is missing" in msg - assert "vkr_hv_percent_characteristic is missing" in msg - assert "vk_mv_percent_characteristic is missing" in msg - assert "vkr_mv_percent_characteristic is missing" in msg - assert "vk_lv_percent_characteristic is missing" in msg - assert "vkr_lv_percent_characteristic is missing" in msg - - pp.control.util.diagnostic.logger.removeHandler(h) - del h - del s + net.trafo.at[0, "tap_dependency_table"] = 0 + with pytest.raises(UserWarning): + trafo_characteristic_table_diagnostic(net) + net.trafo.at[0, "tap_dependency_table"] = True + net.trafo.at[0, "id_characteristic_table"] = int(2) + with pytest.raises(UserWarning): + trafo_characteristic_table_diagnostic(net) if __name__ == '__main__': - pytest.main([__file__, "-xs"]) \ No newline at end of file + pytest.main([__file__, "-xs"]) From 0b6459b6a82499542270c113f878627e68b4ca03 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Mon, 2 Dec 2024 21:51:56 +0200 Subject: [PATCH 020/125] rename tap related parameters; update/replace related tests --- pandapower/convert_format.py | 6 +- .../networks/IEEE_European_LV_Off_Peak_1.json | 34 +- .../IEEE_European_LV_Off_Peak_1440.json | 34 +- .../IEEE_European_LV_On_Peak_566.json | 34 +- pandapower/networks/lv_schutterwald.json | 44 +-- pandapower/networks/mv_oberrhein.json | 4 +- .../networks/mv_oberrhein_substations.json | 4 +- .../GBnetwork.json | 4 +- .../GBreducednetwork.json | 4 +- .../power_system_test_case_jsons/case118.json | 44 +-- .../case11_iwamoto.json | 44 +-- .../case1354pegase.json | 44 +-- .../power_system_test_case_jsons/case14.json | 44 +-- .../power_system_test_case_jsons/case145.json | 44 +-- .../case1888rte.json | 44 +-- .../case24_ieee_rts.json | 44 +-- .../case2848rte.json | 44 +-- .../case2869pegase.json | 44 +-- .../power_system_test_case_jsons/case30.json | 44 +-- .../power_system_test_case_jsons/case300.json | 44 +-- .../case3120sp.json | 44 +-- .../case33bw.json | 44 +-- .../power_system_test_case_jsons/case39.json | 44 +-- .../power_system_test_case_jsons/case4gs.json | 44 +-- .../power_system_test_case_jsons/case5.json | 44 +-- .../power_system_test_case_jsons/case57.json | 44 +-- .../case5_demo_gridcal.json | 4 +- .../case6470rte.json | 44 +-- .../case6495rte.json | 44 +-- .../case6515rte.json | 44 +-- .../power_system_test_case_jsons/case6ww.json | 44 +-- .../case89pegase.json | 44 +-- .../power_system_test_case_jsons/case9.json | 44 +-- .../case9241pegase.json | 44 +-- .../case_ieee30.json | 44 +-- .../case_illinois200.json | 44 +-- .../power_system_test_case_jsons/iceland.json | 4 +- pandapower/test/api/test_create.py | 20 +- .../test/control/testfiles/stactrl_test.json | 34 +- .../test/converter/case2_2_by_code.json | 30 +- .../converter/testfiles/test_line_3ph.json | 32 +- .../test_net_3ph_test_2020_10_19.json | 34 +- .../converter/testfiles/test_trafo_3ph.json | 34 +- .../converter/testfiles/trafo_tap_model.json | 54 +-- pandapower/test/estimation/3bus_wls.json | 4 +- .../test/estimation/test_wls_estimation.py | 4 +- .../test/loadflow/runpp_3ph Validation.json | 36 +- pandapower/test/loadflow/test_recycle.py | 7 +- pandapower/test/loadflow/test_results.py | 312 +++++++++--------- pandapower/test/loadflow/test_runpp.py | 34 +- pandapower/test/loadflow/test_runpp_3ph.py | 2 +- .../shortcircuit/sc_test_meshed_grid.json | 4 +- pandapower/test/shortcircuit/test_1ph.py | 2 +- .../test/test_files/IEC60909-4_example.json | 48 +-- .../controller_containing_NoneNan.json | 32 +- .../old_versions/example_2.0.0.json | 2 +- .../old_versions/example_2.0.1.json | 2 +- .../old_versions/example_2.1.0.json | 32 +- .../old_versions/example_2.10.0.json | 32 +- .../old_versions/example_2.10.1.json | 32 +- .../old_versions/example_2.11.0.json | 32 +- .../old_versions/example_2.11.1.json | 32 +- .../old_versions/example_2.12.0.json | 32 +- .../old_versions/example_2.12.1.json | 32 +- .../old_versions/example_2.13.0.1.json | 36 +- .../old_versions/example_2.13.0.json | 32 +- .../old_versions/example_2.14.0.json | 36 +- .../old_versions/example_2.2.0.json | 32 +- .../old_versions/example_2.3.0.json | 32 +- .../old_versions/example_2.3.1.json | 32 +- .../old_versions/example_2.4.0.json | 32 +- .../old_versions/example_2.5.0.json | 32 +- .../old_versions/example_2.6.0.json | 32 +- .../old_versions/example_2.7.0.json | 32 +- .../old_versions/example_2.8.0.json | 32 +- .../old_versions/example_2.9.0.json | 32 +- pandapower/test/test_files/test_ac_dc.json | 34 +- .../test/test_files/test_trafo3w_tap.json | 32 +- .../timeseries/test_timeseries_recycle.py | 4 +- .../test/toolbox/test_grid_modification.py | 43 +-- pandapower/toolbox/data_modification.py | 11 - pandapower/toolbox/grid_modification.py | 26 +- 82 files changed, 1403 insertions(+), 1410 deletions(-) diff --git a/pandapower/convert_format.py b/pandapower/convert_format.py index e30dfef70..cf0f4cd4f 100644 --- a/pandapower/convert_format.py +++ b/pandapower/convert_format.py @@ -363,10 +363,10 @@ def _add_missing_columns(net, elements_to_deserialize): net.gen["slack"] = False if _check_elements_to_deserialize('trafo', elements_to_deserialize) and \ - "tap_phase_shifter" not in net.trafo and "tp_phase_shifter" not in net.trafo: - net.trafo["tap_phase_shifter"] = False + "tap_phase_shifter_type" not in net.trafo: + net.trafo["tap_phase_shifter_type"] = pd.NA - # unsymmetric impedance + # asymmetric impedance if _check_elements_to_deserialize('impedance', elements_to_deserialize): if "r_pu" in net.impedance: net.impedance["rft_pu"] = net.impedance["rtf_pu"] = net.impedance["r_pu"] diff --git a/pandapower/networks/IEEE_European_LV_Off_Peak_1.json b/pandapower/networks/IEEE_European_LV_Off_Peak_1.json index e91c815a8..baf88455d 100644 --- a/pandapower/networks/IEEE_European_LV_Off_Peak_1.json +++ b/pandapower/networks/IEEE_European_LV_Off_Peak_1.json @@ -318,7 +318,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", "orient": "split", "dtype": { "name": "object", @@ -340,7 +340,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -1203,7 +1203,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1221,7 +1221,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1239,7 +1239,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1257,7 +1257,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "08 MVA 10/04 kV Dyn1 ASEA": { "sn_mva": 0.800000011920929, @@ -1277,7 +1277,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1298,7 +1298,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1316,7 +1316,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1334,7 +1334,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1352,7 +1352,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1370,7 +1370,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1388,7 +1388,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1406,7 +1406,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1424,7 +1424,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1442,7 +1442,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1460,7 +1460,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json b/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json index ccc96d974..832d0d859 100644 --- a/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json +++ b/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json @@ -318,7 +318,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", "orient": "split", "dtype": { "name": "object", @@ -340,7 +340,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -1203,7 +1203,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1221,7 +1221,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1239,7 +1239,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1257,7 +1257,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "08 MVA 10/04 kV Dyn1 ASEA": { "sn_mva": 0.800000011920929, @@ -1277,7 +1277,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1298,7 +1298,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1316,7 +1316,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1334,7 +1334,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1352,7 +1352,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1370,7 +1370,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1388,7 +1388,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1406,7 +1406,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1424,7 +1424,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1442,7 +1442,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1460,7 +1460,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/networks/IEEE_European_LV_On_Peak_566.json b/pandapower/networks/IEEE_European_LV_On_Peak_566.json index 870517ef1..af2a3fdc8 100644 --- a/pandapower/networks/IEEE_European_LV_On_Peak_566.json +++ b/pandapower/networks/IEEE_European_LV_On_Peak_566.json @@ -318,7 +318,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", "orient": "split", "dtype": { "name": "object", @@ -340,7 +340,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -1203,7 +1203,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1221,7 +1221,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1239,7 +1239,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1257,7 +1257,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "08 MVA 10/04 kV Dyn1 ASEA": { "sn_mva": 0.800000011920929, @@ -1277,7 +1277,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1298,7 +1298,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1316,7 +1316,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1334,7 +1334,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1352,7 +1352,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1370,7 +1370,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1388,7 +1388,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1406,7 +1406,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1424,7 +1424,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1442,7 +1442,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1460,7 +1460,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/networks/lv_schutterwald.json b/pandapower/networks/lv_schutterwald.json index b33bacfb1..1badb2cd5 100644 --- a/pandapower/networks/lv_schutterwald.json +++ b/pandapower/networks/lv_schutterwald.json @@ -290,7 +290,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1,3,4,5,6,7,10,11,12,13,14,15,16],\"data\":[[\"T_idx_47\",\"0.4 MVA 20\\/0.4 kV\",2983,3000,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_45\",\"0.25 MVA 20\\/0.4 kV\",2984,3001,0.25,20.0,0.4,6.0,1.44,0.8,0.32,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_35\",\"0.4 MVA 20\\/0.4 kV\",2986,3003,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_77\",\"0.4 MVA 20\\/0.4 kV\",2987,3004,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_78\",\"0.63 MVA 20\\/0.4 kV\",2988,3005,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_119\",\"0.63 MVA 20\\/0.4 kV\",2989,3006,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_118\",\"0.63 MVA 20\\/0.4 kV\",2990,3007,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_117\",\"0.4 MVA 20\\/0.4 kV\",2993,3010,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_80\",\"0.63 MVA 20\\/0.4 kV\",2994,3011,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_73\",\"0.63 MVA 20\\/0.4 kV\",2995,3012,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_43\",\"0.63 MVA 20\\/0.4 kV\",2996,3013,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_81\",\"0.63 MVA 20\\/0.4 kV\",2997,3014,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_71\",\"0.4 MVA 20\\/0.4 kV\",2998,3015,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_ZUSATZ\",\"0.63 MVA 20\\/0.4 kV\",2999,3016,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1,3,4,5,6,7,10,11,12,13,14,15,16],\"data\":[[\"T_idx_47\",\"0.4 MVA 20\\/0.4 kV\",2983,3000,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_45\",\"0.25 MVA 20\\/0.4 kV\",2984,3001,0.25,20.0,0.4,6.0,1.44,0.8,0.32,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_35\",\"0.4 MVA 20\\/0.4 kV\",2986,3003,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_77\",\"0.4 MVA 20\\/0.4 kV\",2987,3004,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_78\",\"0.63 MVA 20\\/0.4 kV\",2988,3005,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_119\",\"0.63 MVA 20\\/0.4 kV\",2989,3006,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_118\",\"0.63 MVA 20\\/0.4 kV\",2990,3007,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_117\",\"0.4 MVA 20\\/0.4 kV\",2993,3010,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_80\",\"0.63 MVA 20\\/0.4 kV\",2994,3011,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_73\",\"0.63 MVA 20\\/0.4 kV\",2995,3012,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_43\",\"0.63 MVA 20\\/0.4 kV\",2996,3013,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_81\",\"0.63 MVA 20\\/0.4 kV\",2997,3014,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_71\",\"0.4 MVA 20\\/0.4 kV\",2998,3015,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_ZUSATZ\",\"0.63 MVA 20\\/0.4 kV\",2999,3016,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -312,7 +312,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -926,7 +926,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 160.0 }, "100 MVA 220/110 kV": { @@ -944,7 +944,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 100.0 }, "63 MVA 110/20 kV": { @@ -962,7 +962,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 63.0 }, "40 MVA 110/20 kV": { @@ -980,7 +980,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 40.0 }, "25 MVA 110/20 kV": { @@ -998,7 +998,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 25.0 }, "63 MVA 110/10 kV": { @@ -1016,7 +1016,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 63.0 }, "40 MVA 110/10 kV": { @@ -1034,7 +1034,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 40.0 }, "25 MVA 110/10 kV": { @@ -1052,7 +1052,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 25.0 }, "63 MVA 110/20 kV v1.4.3 and older": { @@ -1070,7 +1070,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 63.0 }, "40 MVA 110/20 kV v1.4.3 and older": { @@ -1088,7 +1088,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 40.0 }, "25 MVA 110/20 kV v1.4.3 and older": { @@ -1106,7 +1106,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 25.0 }, "63 MVA 110/10 kV v1.4.3 and older": { @@ -1124,7 +1124,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 63.0 }, "40 MVA 110/10 kV v1.4.3 and older": { @@ -1142,7 +1142,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 40.0 }, "25 MVA 110/10 kV v1.4.3 and older": { @@ -1160,7 +1160,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 25.0 }, "0.25 MVA 20/0.4 kV": { @@ -1178,7 +1178,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 0.25 }, "0.4 MVA 20/0.4 kV": { @@ -1196,7 +1196,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 0.4 }, "0.63 MVA 20/0.4 kV": { @@ -1214,7 +1214,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 0.63 }, "0.25 MVA 10/0.4 kV": { @@ -1232,7 +1232,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 0.25 }, "0.4 MVA 10/0.4 kV": { @@ -1250,7 +1250,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 0.4 }, "0.63 MVA 10/0.4 kV": { @@ -1268,7 +1268,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "sn_mva": 0.63 } }, diff --git a/pandapower/networks/mv_oberrhein.json b/pandapower/networks/mv_oberrhein.json index 00053a005..1384c4dc0 100644 --- a/pandapower/networks/mv_oberrhein.json +++ b/pandapower/networks/mv_oberrhein.json @@ -292,7 +292,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[114,142],\"data\":[[\"HV\\/MV Transformer 0\",\"25 MVA 110\\/20 kV\",58,39,25.0,110.0,20.0,11.199999999999999,0.282,29.0,0.071,150.0,\"hv\",0,-9,9,1.5,null,-2,false,1,1.0,true],[\"HV\\/MV Transformer 1\",\"25 MVA 110\\/20 kV\",318,319,25.0,110.0,20.0,11.199999999999999,0.282,29.0,0.071,150.0,\"hv\",0,-9,9,1.5,null,-3,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[114,142],\"data\":[[\"HV\\/MV Transformer 0\",\"25 MVA 110\\/20 kV\",58,39,25.0,110.0,20.0,11.199999999999999,0.282,29.0,0.071,150.0,\"hv\",0,-9,9,1.5,null,-2,false,1,1.0,true],[\"HV\\/MV Transformer 1\",\"25 MVA 110\\/20 kV\",318,319,25.0,110.0,20.0,11.199999999999999,0.282,29.0,0.071,150.0,\"hv\",0,-9,9,1.5,null,-3,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -314,7 +314,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" diff --git a/pandapower/networks/mv_oberrhein_substations.json b/pandapower/networks/mv_oberrhein_substations.json index 0becaa3fd..00ceab33b 100644 --- a/pandapower/networks/mv_oberrhein_substations.json +++ b/pandapower/networks/mv_oberrhein_substations.json @@ -292,7 +292,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" diff --git a/pandapower/networks/power_system_test_case_jsons/GBnetwork.json b/pandapower/networks/power_system_test_case_jsons/GBnetwork.json index 9e25cb852..feced48bc 100644 --- a/pandapower/networks/power_system_test_case_jsons/GBnetwork.json +++ b/pandapower/networks/power_system_test_case_jsons/GBnetwork.json @@ -296,7 +296,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -318,7 +318,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" diff --git a/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json b/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json index e12a8873b..1f5f1baa0 100644 --- a/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json +++ b/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json @@ -301,7 +301,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1,10,11,12,2,3,4,5,6,7,8,9],\"data\":[[null,null,0,2,132.0,275.0,132.0,19.8215482745,0.924,0.0,-3.9393939394,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,0,2,132.0,275.0,132.0,19.8215482745,0.924,0.0,-3.9393939394,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,3,2,648.0,275.0,132.0,26.639027009300001,1.944,0.0,-0.0679012346,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,3,2,648.0,275.0,132.0,26.639027009300001,1.944,0.0,-0.6790123457,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,1,2,652.0,275.0,132.0,53.889295279899997,19.586079999999999,0.0,-0.1901840491,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,6,3,1090.0,400.0,275.0,14.893648478799999,2.2999,0.0,-1.0770642202,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,5,3,1500.0,400.0,275.0,34.555064751800003,1.95,0.0,-0.9973333333,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,5,3,1120.0,400.0,275.0,25.801115014699999,1.456,0.0,-1.5696428571,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,4,3,1000.0,400.0,275.0,24.020824298899999,1.0,0.0,-1.25,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,4,3,1000.0,400.0,275.0,24.020824298899999,1.0,0.0,-1.25,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,6,3,1090.0,400.0,275.0,14.8919691781,2.289,0.0,-1.4110091743,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,11,17,2400.0,400.0,400.0,21.672890347199999,1.776,0.0,-1.2129166667,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,11,12,3100.0,400.0,400.0,33.550250371600001,2.976,0.0,-1.2419354839,2.0,null,null,null,null,null,null,null,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1,10,11,12,2,3,4,5,6,7,8,9],\"data\":[[null,null,0,2,132.0,275.0,132.0,19.8215482745,0.924,0.0,-3.9393939394,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,0,2,132.0,275.0,132.0,19.8215482745,0.924,0.0,-3.9393939394,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,3,2,648.0,275.0,132.0,26.639027009300001,1.944,0.0,-0.0679012346,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,3,2,648.0,275.0,132.0,26.639027009300001,1.944,0.0,-0.6790123457,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,1,2,652.0,275.0,132.0,53.889295279899997,19.586079999999999,0.0,-0.1901840491,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,6,3,1090.0,400.0,275.0,14.893648478799999,2.2999,0.0,-1.0770642202,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,5,3,1500.0,400.0,275.0,34.555064751800003,1.95,0.0,-0.9973333333,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,5,3,1120.0,400.0,275.0,25.801115014699999,1.456,0.0,-1.5696428571,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,4,3,1000.0,400.0,275.0,24.020824298899999,1.0,0.0,-1.25,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,4,3,1000.0,400.0,275.0,24.020824298899999,1.0,0.0,-1.25,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,6,3,1090.0,400.0,275.0,14.8919691781,2.289,0.0,-1.4110091743,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,11,17,2400.0,400.0,400.0,21.672890347199999,1.776,0.0,-1.2129166667,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,11,12,3100.0,400.0,400.0,33.550250371600001,2.976,0.0,-1.2419354839,2.0,null,null,null,null,null,null,null,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -323,7 +323,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" diff --git a/pandapower/networks/power_system_test_case_jsons/case118.json b/pandapower/networks/power_system_test_case_jsons/case118.json index 28efc1bdc..c1e127e0b 100644 --- a/pandapower/networks/power_system_test_case_jsons/case118.json +++ b/pandapower/networks/power_system_test_case_jsons/case118.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,11,12,2,3,4,5,6,7,8,9],\"data\":[[null,null,7,4,9900.0,345.0,138.0,264.329999999999984,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,1.5,null,-1.0,false,1,1.0,true,100.0],[null,null,25,24,9900.0,345.0,138.0,378.180000000000007,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,80,79,9900.0,345.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,86,85,9900.0,161.0,138.0,2072.25986507098105,279.97199999999998,0.0,-0.04494949494949,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,115,67,9900.0,345.0,161.0,40.236040821631541,3.366,0.0,-0.16565656565657,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,29,16,9900.0,345.0,138.0,384.120000000000005,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,37,36,9900.0,345.0,138.0,371.25,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,62,58,9900.0,345.0,138.0,382.139999999999986,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,63,60,9900.0,345.0,138.0,265.319999999999993,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,1.5,null,-1.0,false,1,1.0,true,100.0],[null,null,64,65,9900.0,345.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,64,67,9900.0,345.0,161.0,158.988082081645359,13.662000000000001,0.0,-0.64444444444444,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,67,68,9900.0,161.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,80,67,9900.0,345.0,161.0,200.72906123678257,17.324999999999999,0.0,-0.81616161616162,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", + "_object": 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"orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -928,7 +928,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -946,7 +946,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -964,7 +964,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -982,7 +982,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1000,7 +1000,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1018,7 +1018,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1036,7 +1036,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1054,7 +1054,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1072,7 +1072,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1090,7 +1090,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1108,7 +1108,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1126,7 +1126,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1144,7 +1144,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1162,7 +1162,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1180,7 +1180,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1198,7 +1198,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1216,7 +1216,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1234,7 +1234,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1252,7 +1252,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1270,7 +1270,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json b/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json index ab15b1e10..4ba762bdb 100644 --- a/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json +++ b/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json @@ -287,7 +287,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -309,7 +309,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -918,7 +918,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -936,7 +936,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -954,7 +954,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -972,7 +972,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -990,7 +990,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "vn_hv_kv": 110, @@ -1008,7 +1008,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "vn_hv_kv": 110, @@ -1026,7 +1026,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "vn_hv_kv": 110, @@ -1044,7 +1044,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV v1.4.3 and older": { "i0_percent": 0.086, @@ -1062,7 +1062,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV v1.4.3 and older": { "i0_percent": 0.08, @@ -1080,7 +1080,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV v1.4.3 and older": { "i0_percent": 0.071, @@ -1098,7 +1098,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV v1.4.3 and older": { "vn_hv_kv": 110, @@ -1116,7 +1116,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV v1.4.3 and older": { "vn_hv_kv": 110, @@ -1134,7 +1134,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV v1.4.3 and older": { "vn_hv_kv": 110, @@ -1152,7 +1152,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "vn_hv_kv": 20, @@ -1170,7 +1170,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "vn_hv_kv": 20, @@ -1188,7 +1188,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "vn_hv_kv": 20, @@ -1206,7 +1206,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "vn_hv_kv": 10, @@ -1224,7 +1224,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "vn_hv_kv": 10, @@ -1242,7 +1242,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "vn_hv_kv": 10, @@ -1260,7 +1260,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/networks/power_system_test_case_jsons/case1354pegase.json b/pandapower/networks/power_system_test_case_jsons/case1354pegase.json index 840d7cf2f..4fb86767a 100644 --- a/pandapower/networks/power_system_test_case_jsons/case1354pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case1354pegase.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -929,7 +929,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -947,7 +947,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -965,7 +965,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -983,7 +983,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1001,7 +1001,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1019,7 +1019,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1037,7 +1037,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1055,7 +1055,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1073,7 +1073,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1091,7 +1091,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1109,7 +1109,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1127,7 +1127,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1145,7 +1145,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1163,7 +1163,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1181,7 +1181,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1199,7 +1199,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1217,7 +1217,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1235,7 +1235,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1253,7 +1253,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1271,7 +1271,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case14.json b/pandapower/networks/power_system_test_case_jsons/case14.json index f64d58cf2..c60707aa5 100644 --- a/pandapower/networks/power_system_test_case_jsons/case14.json +++ b/pandapower/networks/power_system_test_case_jsons/case14.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,3,6,9900.0,135.0,14.0,2070.288000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,3,8,9900.0,135.0,0.208,5506.181999999999789,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.1,null,-1.0,false,1,1.0,true,100.0],[null,null,4,5,9900.0,135.0,0.208,2494.998000000000047,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.8,null,-1.0,false,1,1.0,true,100.0],[null,null,6,7,9900.0,14.0,12.0,1743.884999999999991,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,6,8,9900.0,14.0,0.208,1089.098999999999933,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,3,6,9900.0,135.0,14.0,2070.288000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,3,8,9900.0,135.0,0.208,5506.181999999999789,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.1,null,-1.0,false,1,1.0,true,100.0],[null,null,4,5,9900.0,135.0,0.208,2494.998000000000047,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.8,null,-1.0,false,1,1.0,true,100.0],[null,null,6,7,9900.0,14.0,12.0,1743.884999999999991,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,6,8,9900.0,14.0,0.208,1089.098999999999933,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -928,7 +928,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -946,7 +946,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -964,7 +964,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -982,7 +982,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1000,7 +1000,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1018,7 +1018,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1036,7 +1036,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1054,7 +1054,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1072,7 +1072,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1090,7 +1090,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1108,7 +1108,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1126,7 +1126,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1144,7 +1144,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1162,7 +1162,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1180,7 +1180,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1198,7 +1198,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1216,7 +1216,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1234,7 +1234,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1252,7 +1252,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1270,7 +1270,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case145.json b/pandapower/networks/power_system_test_case_jsons/case145.json index 623f9a433..1104e61e2 100644 --- a/pandapower/networks/power_system_test_case_jsons/case145.json +++ b/pandapower/networks/power_system_test_case_jsons/case145.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -929,7 +929,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -947,7 +947,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -965,7 +965,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -983,7 +983,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1001,7 +1001,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1019,7 +1019,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1037,7 +1037,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1055,7 +1055,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1073,7 +1073,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1091,7 +1091,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1109,7 +1109,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1127,7 +1127,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1145,7 +1145,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1163,7 +1163,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1181,7 +1181,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1199,7 +1199,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1217,7 +1217,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1235,7 +1235,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1253,7 +1253,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1271,7 +1271,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case1888rte.json b/pandapower/networks/power_system_test_case_jsons/case1888rte.json index ae0d70712..7a7d0690a 100644 --- a/pandapower/networks/power_system_test_case_jsons/case1888rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case1888rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -933,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -951,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -969,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -987,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1005,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1023,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1041,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1059,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1077,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1095,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1113,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1131,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1149,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1167,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1185,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1203,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1221,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1239,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1257,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1275,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json b/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json index c169eacc0..b68ae2328 100644 --- a/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json +++ b/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,23,2,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,10,8,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,11,8,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,10,9,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,2.0,null,1,false,1,1.0,true,100.0],[null,null,11,9,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,2.0,null,1,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,23,2,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,10,8,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,11,8,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,10,9,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,2.0,null,1,false,1,1.0,true,100.0],[null,null,11,9,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,2.0,null,1,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -933,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -951,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -969,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -987,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1005,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1023,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1041,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1059,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1077,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1095,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1113,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1131,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1149,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1167,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1185,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1203,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1221,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1239,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1257,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1275,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case2848rte.json b/pandapower/networks/power_system_test_case_jsons/case2848rte.json index a7375b421..d8d3f499d 100644 --- a/pandapower/networks/power_system_test_case_jsons/case2848rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case2848rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -933,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -951,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -969,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -987,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1005,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1023,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1041,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1059,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1077,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1095,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1113,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1131,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1149,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1167,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1185,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1203,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1221,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1239,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1257,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1275,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case2869pegase.json b/pandapower/networks/power_system_test_case_jsons/case2869pegase.json index 1834b4dbf..311d9adab 100644 --- a/pandapower/networks/power_system_test_case_jsons/case2869pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case2869pegase.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -929,7 +929,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -947,7 +947,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -965,7 +965,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -983,7 +983,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1001,7 +1001,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1019,7 +1019,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1037,7 +1037,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1055,7 +1055,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1073,7 +1073,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1091,7 +1091,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1109,7 +1109,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1127,7 +1127,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1145,7 +1145,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1163,7 +1163,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1181,7 +1181,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1199,7 +1199,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1217,7 +1217,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1235,7 +1235,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1253,7 +1253,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1271,7 +1271,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case30.json b/pandapower/networks/power_system_test_case_jsons/case30.json index 68d2f55a8..c9e98641d 100644 --- a/pandapower/networks/power_system_test_case_jsons/case30.json +++ b/pandapower/networks/power_system_test_case_jsons/case30.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -927,7 +927,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -945,7 +945,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -963,7 +963,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -981,7 +981,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -999,7 +999,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1017,7 +1017,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1035,7 +1035,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1053,7 +1053,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1071,7 +1071,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1089,7 +1089,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1107,7 +1107,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1125,7 +1125,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1143,7 +1143,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1161,7 +1161,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1179,7 +1179,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1197,7 +1197,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1215,7 +1215,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1233,7 +1233,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1251,7 +1251,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1269,7 +1269,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case300.json b/pandapower/networks/power_system_test_case_jsons/case300.json index a3af72513..9831cf3a0 100644 --- a/pandapower/networks/power_system_test_case_jsons/case300.json +++ b/pandapower/networks/power_system_test_case_jsons/case300.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -929,7 +929,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -947,7 +947,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -965,7 +965,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -983,7 +983,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1001,7 +1001,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1019,7 +1019,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1037,7 +1037,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1055,7 +1055,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1073,7 +1073,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1091,7 +1091,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1109,7 +1109,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1127,7 +1127,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1145,7 +1145,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1163,7 +1163,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1181,7 +1181,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1199,7 +1199,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1217,7 +1217,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1235,7 +1235,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1253,7 +1253,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1271,7 +1271,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case3120sp.json b/pandapower/networks/power_system_test_case_jsons/case3120sp.json index cf9adb5b1..79f00771c 100644 --- a/pandapower/networks/power_system_test_case_jsons/case3120sp.json +++ b/pandapower/networks/power_system_test_case_jsons/case3120sp.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -933,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -951,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -969,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -987,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1005,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1023,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1041,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1059,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1077,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1095,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1113,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1131,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1149,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1167,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1185,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1203,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1221,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1239,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1257,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1275,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case33bw.json b/pandapower/networks/power_system_test_case_jsons/case33bw.json index 9ef5276c6..ccff274db 100644 --- a/pandapower/networks/power_system_test_case_jsons/case33bw.json +++ b/pandapower/networks/power_system_test_case_jsons/case33bw.json @@ -295,7 +295,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -317,7 +317,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -921,7 +921,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -939,7 +939,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -957,7 +957,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -975,7 +975,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -993,7 +993,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1011,7 +1011,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1029,7 +1029,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1047,7 +1047,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1065,7 +1065,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1083,7 +1083,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1101,7 +1101,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1119,7 +1119,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1137,7 +1137,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1155,7 +1155,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1173,7 +1173,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1191,7 +1191,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1209,7 +1209,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1227,7 +1227,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1245,7 +1245,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1263,7 +1263,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, diff --git a/pandapower/networks/power_system_test_case_jsons/case39.json b/pandapower/networks/power_system_test_case_jsons/case39.json index abbc39f57..0735ff541 100644 --- a/pandapower/networks/power_system_test_case_jsons/case39.json +++ b/pandapower/networks/power_system_test_case_jsons/case39.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,2,3,4,5,6,7,8,9],\"data\":[[null,null,1,29,900.0,345.0,345.0,16.289999999999999,0.0,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,5,30,1800.0,345.0,345.0,45.0,0.0,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,28,37,1200.0,345.0,345.0,18.744599222175971,0.96,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,9,31,900.0,345.0,345.0,18.0,0.0,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,11,10,500.0,345.0,345.0,21.76470767090613,0.8,0.0,0.0,0.0,\"hv\",0,null,null,0.6,null,1,false,1,1.0,true,100.0],[null,null,11,12,500.0,345.0,345.0,21.76470767090613,0.8,0.0,0.0,0.0,\"hv\",0,null,null,0.6,null,1,false,1,1.0,true,100.0],[null,null,18,19,900.0,345.0,345.0,12.435967996099061,0.63,0.0,0.0,0.0,\"hv\",0,null,null,6.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,18,32,900.0,345.0,345.0,12.79551874681132,0.63,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,19,33,900.0,345.0,345.0,16.220237359545639,0.81,0.0,0.0,0.0,\"hv\",0,null,null,0.89999999999999,null,1,false,1,1.0,true,100.0],[null,null,21,34,900.0,345.0,345.0,12.869999999999999,0.0,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,24,36,900.0,345.0,345.0,20.88698159141239,0.54,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,2,3,4,5,6,7,8,9],\"data\":[[null,null,1,29,900.0,345.0,345.0,16.289999999999999,0.0,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,5,30,1800.0,345.0,345.0,45.0,0.0,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,28,37,1200.0,345.0,345.0,18.744599222175971,0.96,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,9,31,900.0,345.0,345.0,18.0,0.0,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,11,10,500.0,345.0,345.0,21.76470767090613,0.8,0.0,0.0,0.0,\"hv\",0,null,null,0.6,null,1,false,1,1.0,true,100.0],[null,null,11,12,500.0,345.0,345.0,21.76470767090613,0.8,0.0,0.0,0.0,\"hv\",0,null,null,0.6,null,1,false,1,1.0,true,100.0],[null,null,18,19,900.0,345.0,345.0,12.435967996099061,0.63,0.0,0.0,0.0,\"hv\",0,null,null,6.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,18,32,900.0,345.0,345.0,12.79551874681132,0.63,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,19,33,900.0,345.0,345.0,16.220237359545639,0.81,0.0,0.0,0.0,\"hv\",0,null,null,0.89999999999999,null,1,false,1,1.0,true,100.0],[null,null,21,34,900.0,345.0,345.0,12.869999999999999,0.0,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,24,36,900.0,345.0,345.0,20.88698159141239,0.54,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -928,7 +928,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -946,7 +946,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -964,7 +964,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -982,7 +982,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1000,7 +1000,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1018,7 +1018,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1036,7 +1036,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1054,7 +1054,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1072,7 +1072,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1090,7 +1090,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1108,7 +1108,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1126,7 +1126,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1144,7 +1144,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1162,7 +1162,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1180,7 +1180,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1198,7 +1198,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1216,7 +1216,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1234,7 +1234,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1252,7 +1252,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1270,7 +1270,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case4gs.json b/pandapower/networks/power_system_test_case_jsons/case4gs.json index 001a9c68b..e956f9699 100644 --- a/pandapower/networks/power_system_test_case_jsons/case4gs.json +++ b/pandapower/networks/power_system_test_case_jsons/case4gs.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -924,7 +924,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -942,7 +942,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -960,7 +960,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -978,7 +978,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -996,7 +996,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1014,7 +1014,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1032,7 +1032,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1050,7 +1050,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1068,7 +1068,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1086,7 +1086,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1104,7 +1104,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1122,7 +1122,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1140,7 +1140,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1158,7 +1158,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1176,7 +1176,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1194,7 +1194,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1212,7 +1212,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1230,7 +1230,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1248,7 +1248,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1266,7 +1266,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, diff --git a/pandapower/networks/power_system_test_case_jsons/case5.json b/pandapower/networks/power_system_test_case_jsons/case5.json index 65ec9fc5e..8dcfb6f84 100644 --- a/pandapower/networks/power_system_test_case_jsons/case5.json +++ b/pandapower/networks/power_system_test_case_jsons/case5.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -929,7 +929,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -947,7 +947,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -965,7 +965,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -983,7 +983,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1001,7 +1001,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1019,7 +1019,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1037,7 +1037,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1055,7 +1055,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1073,7 +1073,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1091,7 +1091,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1109,7 +1109,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1127,7 +1127,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1145,7 +1145,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1163,7 +1163,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1181,7 +1181,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1199,7 +1199,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1217,7 +1217,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1235,7 +1235,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1253,7 +1253,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1271,7 +1271,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, diff --git a/pandapower/networks/power_system_test_case_jsons/case57.json b/pandapower/networks/power_system_test_case_jsons/case57.json index 7cdbbbb4c..d70bf2bfe 100644 --- a/pandapower/networks/power_system_test_case_jsons/case57.json +++ b/pandapower/networks/power_system_test_case_jsons/case57.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,11,12,13,14,15,16,2,3,4,5,6,7,8,9],\"data\":[[null,null,17,3,9900.0,500.0,115.0,5494.50000000000091,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.0,null,-1.0,false,1,1.0,true,100.0],[null,null,17,3,9900.0,500.0,115.0,4257.0,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,45,13,9900.0,138.0,115.0,727.649999999999977,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,10.0,null,-1.0,false,1,1.0,true,100.0],[null,null,50,9,9900.0,138.0,115.0,704.879999999999996,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.99999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,48,12,9900.0,138.0,115.0,1890.900000000000091,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,10.5,null,-1.0,false,1,1.0,true,100.0],[null,null,42,10,9900.0,230.0,115.0,1514.700000000000046,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.2,null,-1.0,false,1,1.0,true,100.0],[null,null,55,39,9900.0,230.0,138.0,11830.5,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.2,null,-1.0,false,1,1.0,true,100.0],[null,null,56,38,9900.0,230.0,138.0,13414.5,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.0,null,-1.0,false,1,1.0,true,100.0],[null,null,54,8,9900.0,161.0,115.0,1192.950000000000046,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.00000000000001,null,-1.0,false,1,1.0,true,100.0],[null,null,19,20,9900.0,500.0,138.0,7689.329999999999018,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.29999999999999,null,1.0,false,1,1.0,true,100.0],[null,null,24,23,9900.0,345.0,138.0,11701.799999999999272,0.0,0.0,0.0,0.0,\"hv\",null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,24,23,9900.0,345.0,138.0,12177.0,0.0,0.0,0.0,0.0,\"hv\",null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,25,23,9900.0,161.0,138.0,468.269999999999982,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.29999999999999,null,1.0,false,1,1.0,true,100.0],[null,null,28,6,9900.0,161.0,115.0,641.519999999999982,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.3,null,-1.0,false,1,1.0,true,100.0],[null,null,31,33,9900.0,345.0,138.0,9434.700000000000728,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.5,null,-1.0,false,1,1.0,true,100.0],[null,null,40,10,9900.0,230.0,115.0,7415.100000000000364,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.5,null,-1.0,false,1,1.0,true,100.0],[null,null,44,14,9900.0,138.0,115.0,1031.579999999999927,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.5,null,-1.0,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,11,12,13,14,15,16,2,3,4,5,6,7,8,9],\"data\":[[null,null,17,3,9900.0,500.0,115.0,5494.50000000000091,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.0,null,-1.0,false,1,1.0,true,100.0],[null,null,17,3,9900.0,500.0,115.0,4257.0,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,45,13,9900.0,138.0,115.0,727.649999999999977,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,10.0,null,-1.0,false,1,1.0,true,100.0],[null,null,50,9,9900.0,138.0,115.0,704.879999999999996,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.99999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,48,12,9900.0,138.0,115.0,1890.900000000000091,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,10.5,null,-1.0,false,1,1.0,true,100.0],[null,null,42,10,9900.0,230.0,115.0,1514.700000000000046,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.2,null,-1.0,false,1,1.0,true,100.0],[null,null,55,39,9900.0,230.0,138.0,11830.5,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.2,null,-1.0,false,1,1.0,true,100.0],[null,null,56,38,9900.0,230.0,138.0,13414.5,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.0,null,-1.0,false,1,1.0,true,100.0],[null,null,54,8,9900.0,161.0,115.0,1192.950000000000046,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.00000000000001,null,-1.0,false,1,1.0,true,100.0],[null,null,19,20,9900.0,500.0,138.0,7689.329999999999018,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.29999999999999,null,1.0,false,1,1.0,true,100.0],[null,null,24,23,9900.0,345.0,138.0,11701.799999999999272,0.0,0.0,0.0,0.0,\"hv\",null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,24,23,9900.0,345.0,138.0,12177.0,0.0,0.0,0.0,0.0,\"hv\",null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,25,23,9900.0,161.0,138.0,468.269999999999982,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.29999999999999,null,1.0,false,1,1.0,true,100.0],[null,null,28,6,9900.0,161.0,115.0,641.519999999999982,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.3,null,-1.0,false,1,1.0,true,100.0],[null,null,31,33,9900.0,345.0,138.0,9434.700000000000728,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.5,null,-1.0,false,1,1.0,true,100.0],[null,null,40,10,9900.0,230.0,115.0,7415.100000000000364,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.5,null,-1.0,false,1,1.0,true,100.0],[null,null,44,14,9900.0,138.0,115.0,1031.579999999999927,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.5,null,-1.0,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -928,7 +928,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -946,7 +946,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -964,7 +964,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -982,7 +982,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1000,7 +1000,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1018,7 +1018,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1036,7 +1036,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1054,7 +1054,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1072,7 +1072,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1090,7 +1090,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1108,7 +1108,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1126,7 +1126,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1144,7 +1144,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1162,7 +1162,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1180,7 +1180,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1198,7 +1198,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1216,7 +1216,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1234,7 +1234,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1252,7 +1252,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1270,7 +1270,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json b/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json index d15720489..36704e677 100644 --- a/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json +++ b/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json @@ -293,7 +293,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -315,7 +315,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" diff --git a/pandapower/networks/power_system_test_case_jsons/case6470rte.json b/pandapower/networks/power_system_test_case_jsons/case6470rte.json index 890907f16..612d183ba 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6470rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6470rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -933,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -951,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -969,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -987,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1005,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1023,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1041,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1059,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1077,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1095,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1113,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1131,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1149,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1167,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1185,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1203,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1221,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1239,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1257,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1275,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case6495rte.json b/pandapower/networks/power_system_test_case_jsons/case6495rte.json index 51bb284df..67dcc6410 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6495rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6495rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -933,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -951,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -969,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -987,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1005,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1023,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1041,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1059,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1077,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1095,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1113,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1131,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1149,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1167,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1185,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1203,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1221,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1239,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1257,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1275,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case6515rte.json b/pandapower/networks/power_system_test_case_jsons/case6515rte.json index b56734e7c..9281e83f9 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6515rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6515rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -933,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -951,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -969,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -987,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1005,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1023,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1041,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1059,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1077,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1095,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1113,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1131,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1149,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1167,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1185,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1203,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1221,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1239,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1257,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1275,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case6ww.json b/pandapower/networks/power_system_test_case_jsons/case6ww.json index ca355d32d..d139511e1 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6ww.json +++ b/pandapower/networks/power_system_test_case_jsons/case6ww.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -924,7 +924,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -942,7 +942,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -960,7 +960,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -978,7 +978,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -996,7 +996,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1014,7 +1014,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1032,7 +1032,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1050,7 +1050,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1068,7 +1068,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1086,7 +1086,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1104,7 +1104,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1122,7 +1122,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1140,7 +1140,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1158,7 +1158,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1176,7 +1176,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1194,7 +1194,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1212,7 +1212,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1230,7 +1230,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1248,7 +1248,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1266,7 +1266,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, diff --git a/pandapower/networks/power_system_test_case_jsons/case89pegase.json b/pandapower/networks/power_system_test_case_jsons/case89pegase.json index 14941bbb1..cfb7acbb8 100644 --- a/pandapower/networks/power_system_test_case_jsons/case89pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case89pegase.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -929,7 +929,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -947,7 +947,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -965,7 +965,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -983,7 +983,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1001,7 +1001,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1019,7 +1019,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1037,7 +1037,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1055,7 +1055,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1073,7 +1073,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1091,7 +1091,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1109,7 +1109,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1127,7 +1127,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1145,7 +1145,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1163,7 +1163,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1181,7 +1181,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1199,7 +1199,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1217,7 +1217,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1235,7 +1235,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1253,7 +1253,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1271,7 +1271,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case9.json b/pandapower/networks/power_system_test_case_jsons/case9.json index 1a2e4ff14..ad2a92db2 100644 --- a/pandapower/networks/power_system_test_case_jsons/case9.json +++ b/pandapower/networks/power_system_test_case_jsons/case9.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -924,7 +924,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -942,7 +942,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -960,7 +960,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -978,7 +978,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -996,7 +996,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1014,7 +1014,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1032,7 +1032,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1050,7 +1050,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1068,7 +1068,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1086,7 +1086,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1104,7 +1104,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1122,7 +1122,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1140,7 +1140,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1158,7 +1158,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1176,7 +1176,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1194,7 +1194,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1212,7 +1212,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1230,7 +1230,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1248,7 +1248,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1266,7 +1266,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, diff --git a/pandapower/networks/power_system_test_case_jsons/case9241pegase.json b/pandapower/networks/power_system_test_case_jsons/case9241pegase.json index 5697621c9..1e29d7e6e 100644 --- a/pandapower/networks/power_system_test_case_jsons/case9241pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case9241pegase.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -929,7 +929,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -947,7 +947,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -965,7 +965,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -983,7 +983,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1001,7 +1001,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 11.2 }, @@ -1019,7 +1019,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1037,7 +1037,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1055,7 +1055,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1073,7 +1073,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.2 }, @@ -1091,7 +1091,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1109,7 +1109,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 6.0 }, @@ -1127,7 +1127,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1145,7 +1145,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "vk_percent": 4.0 }, @@ -1163,7 +1163,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 18.0 }, @@ -1181,7 +1181,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1199,7 +1199,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1217,7 +1217,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 }, @@ -1235,7 +1235,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 10.04 }, @@ -1253,7 +1253,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 12.0 }, @@ -1271,7 +1271,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 9, "vk_percent": 16.2 } diff --git a/pandapower/networks/power_system_test_case_jsons/case_ieee30.json b/pandapower/networks/power_system_test_case_jsons/case_ieee30.json index bea49d968..900ab606b 100644 --- a/pandapower/networks/power_system_test_case_jsons/case_ieee30.json +++ b/pandapower/networks/power_system_test_case_jsons/case_ieee30.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4,5,6],\"data\":[[null,null,5,8,99.998999999999995,132.0,1.0,20.799792,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,5,9,99.998999999999995,132.0,33.0,55.599444000000012,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.1,null,-1.0,false,1,1.0,true,100.0],[null,null,10,8,99.998999999999995,11.0,1.0,20.799792,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,9,8,99.998999999999995,33.0,1.0,10.999890000000001,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,3,11,99.998999999999995,132.0,33.0,25.599744000000001,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.8,null,-1.0,false,1,1.0,true,100.0],[null,null,11,12,99.998999999999995,33.0,11.0,13.99986,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,27,26,99.998999999999995,132.0,33.0,39.599603999999999,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.2,null,-1.0,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4,5,6],\"data\":[[null,null,5,8,99.998999999999995,132.0,1.0,20.799792,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,5,9,99.998999999999995,132.0,33.0,55.599444000000012,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.1,null,-1.0,false,1,1.0,true,100.0],[null,null,10,8,99.998999999999995,11.0,1.0,20.799792,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,9,8,99.998999999999995,33.0,1.0,10.999890000000001,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,3,11,99.998999999999995,132.0,33.0,25.599744000000001,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.8,null,-1.0,false,1,1.0,true,100.0],[null,null,11,12,99.998999999999995,33.0,11.0,13.99986,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,27,26,99.998999999999995,132.0,33.0,39.599603999999999,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.2,null,-1.0,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -925,7 +925,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -943,7 +943,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -961,7 +961,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -979,7 +979,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -997,7 +997,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1015,7 +1015,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1033,7 +1033,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1051,7 +1051,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1069,7 +1069,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1087,7 +1087,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1105,7 +1105,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1123,7 +1123,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1141,7 +1141,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1159,7 +1159,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1177,7 +1177,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1195,7 +1195,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1213,7 +1213,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1231,7 +1231,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1249,7 +1249,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1267,7 +1267,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, diff --git a/pandapower/networks/power_system_test_case_jsons/case_illinois200.json b/pandapower/networks/power_system_test_case_jsons/case_illinois200.json index 7dc673b32..b1f04d6dc 100644 --- a/pandapower/networks/power_system_test_case_jsons/case_illinois200.json +++ b/pandapower/networks/power_system_test_case_jsons/case_illinois200.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -930,7 +930,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -948,7 +948,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -966,7 +966,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -984,7 +984,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1002,7 +1002,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1020,7 +1020,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1038,7 +1038,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1056,7 +1056,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1074,7 +1074,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1092,7 +1092,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1110,7 +1110,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1128,7 +1128,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1146,7 +1146,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1164,7 +1164,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1182,7 +1182,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1200,7 +1200,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1218,7 +1218,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1236,7 +1236,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1254,7 +1254,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1272,7 +1272,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, diff --git a/pandapower/networks/power_system_test_case_jsons/iceland.json b/pandapower/networks/power_system_test_case_jsons/iceland.json index 7a51b132c..2b4f97b08 100644 --- a/pandapower/networks/power_system_test_case_jsons/iceland.json +++ b/pandapower/networks/power_system_test_case_jsons/iceland.json @@ -296,7 +296,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -318,7 +318,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" diff --git a/pandapower/test/api/test_create.py b/pandapower/test/api/test_create.py index 1e1ed8dd7..93a6825cb 100644 --- a/pandapower/test/api/test_create.py +++ b/pandapower/test/api/test_create.py @@ -229,20 +229,6 @@ def test_nonexistent_bus(): func() -def test_tap_phase_shifter_default(): - expected_default = False - net = pp.create_empty_network() - pp.create_bus(net, 110) - pp.create_bus(net, 20) - data = pp.load_std_type(net, "25 MVA 110/20 kV", "trafo") - if "tap_phase_shifter" in data: - del data["tap_phase_shifter"] - pp.create_std_type(net, data, "without_tap_shifter_info", "trafo") - pp.create_transformer_from_parameters(net, 0, 1, 25e3, 110, 20, 0.4, 12, 20, 0.07) - pp.create_transformer(net, 0, 1, "without_tap_shifter_info") - assert (net.trafo.tap_phase_shifter == expected_default).all() - - def test_create_line_conductance(): net = pp.create_empty_network() pp.create_bus(net, 20) @@ -885,7 +871,7 @@ def test_trafo_2_tap_changers(): "tap2_min": -10, "tap2_step_percent": 1, "tap2_step_degree": 0, - "tap2_phase_shifter": False} + "tap2_phase_shifter_type": 0} for c in tap2_data.keys(): assert c not in net.trafo.columns @@ -913,7 +899,7 @@ def test_trafo_2_tap_changers_parameters(): "tap2_min": -10, "tap2_step_percent": 1, "tap2_step_degree": 0, - "tap2_phase_shifter": False} + "tap2_phase_shifter_type": 0} pp.create_transformer_from_parameters(net, b1, b2, **std_type) @@ -939,7 +925,7 @@ def test_trafos_2_tap_changers_parameters(): "tap2_min": -10, "tap2_step_percent": 1, "tap2_step_degree": 0, - "tap2_phase_shifter": False} + "tap2_phase_shifter_type": 0} std_type_p = {k: np.array([v, v]) if not isinstance(v, str) else v for k, v in std_type.items()} diff --git a/pandapower/test/control/testfiles/stactrl_test.json b/pandapower/test/control/testfiles/stactrl_test.json index 233a3955a..b6e8c14e7 100644 --- a/pandapower/test/control/testfiles/stactrl_test.json +++ b/pandapower/test/control/testfiles/stactrl_test.json @@ -314,7 +314,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0,1,2,3],\"data\":[[\"Trafo\",\"90 MVA 132\\/33 kV\",11,49,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"],[\"Trafo(1)\",\"90 MVA 132\\/33 kV\",53,63,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"],[\"Trafo(2)\",\"90 MVA 132\\/33 kV\",75,85,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"],[\"Trafo(3)\",\"90 MVA 132\\/33 kV\",94,88,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0,1,2,3],\"data\":[[\"Trafo\",\"90 MVA 132\\/33 kV\",11,49,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"],[\"Trafo(1)\",\"90 MVA 132\\/33 kV\",53,63,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"],[\"Trafo(2)\",\"90 MVA 132\\/33 kV\",75,85,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"],[\"Trafo(3)\",\"90 MVA 132\\/33 kV\",94,88,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -336,7 +336,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -1132,7 +1132,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1150,7 +1150,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1168,7 +1168,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1186,7 +1186,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1204,7 +1204,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1222,7 +1222,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1240,7 +1240,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1258,7 +1258,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1276,7 +1276,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1294,7 +1294,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1312,7 +1312,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1330,7 +1330,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1348,7 +1348,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1366,7 +1366,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "90 MVA 132/33 kV": { "sn_mva": 90.0, @@ -1386,7 +1386,7 @@ "tap_side": "hv", "tap_step_percent": 1.6699999570846558, "tap_step_degree": 0.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 6, "tap_min": -9, "tap_neutral": 0 diff --git a/pandapower/test/converter/case2_2_by_code.json b/pandapower/test/converter/case2_2_by_code.json index be11c4820..6eb650127 100644 --- a/pandapower/test/converter/case2_2_by_code.json +++ b/pandapower/test/converter/case2_2_by_code.json @@ -318,7 +318,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -1097,7 +1097,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1115,7 +1115,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1133,7 +1133,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1151,7 +1151,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1169,7 +1169,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1187,7 +1187,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1205,7 +1205,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1223,7 +1223,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1241,7 +1241,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1259,7 +1259,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1277,7 +1277,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1295,7 +1295,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1313,7 +1313,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1331,7 +1331,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/converter/testfiles/test_line_3ph.json b/pandapower/test/converter/testfiles/test_line_3ph.json index ee01cd8c2..b412776e8 100644 --- a/pandapower/test/converter/testfiles/test_line_3ph.json +++ b/pandapower/test/converter/testfiles/test_line_3ph.json @@ -247,7 +247,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -269,7 +269,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -959,7 +959,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -977,7 +977,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -995,7 +995,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1013,7 +1013,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1031,7 +1031,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1049,7 +1049,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1067,7 +1067,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1085,7 +1085,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1103,7 +1103,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1121,7 +1121,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1139,7 +1139,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1157,7 +1157,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1175,7 +1175,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1193,7 +1193,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json b/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json index 3b76cde0e..f67943127 100644 --- a/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json +++ b/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json @@ -247,7 +247,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",null,0,1,0.629999995231628,20.0,0.400000005960464,6.0,1.095238089561462,1.649999976158142,0.261914998292923,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,1.095237970352173,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",null,0,1,0.629999995231628,20.0,0.400000005960464,6.0,1.095238089561462,1.649999976158142,0.261914998292923,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,1.095237970352173,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -269,7 +269,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -968,7 +968,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -986,7 +986,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1004,7 +1004,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1022,7 +1022,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1040,7 +1040,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1058,7 +1058,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1076,7 +1076,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1094,7 +1094,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1112,7 +1112,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1130,7 +1130,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV Dyn ASEA": { "sn_mva": 0.6299999952316284, @@ -1150,7 +1150,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1171,7 +1171,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1189,7 +1189,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1207,7 +1207,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1225,7 +1225,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/converter/testfiles/test_trafo_3ph.json b/pandapower/test/converter/testfiles/test_trafo_3ph.json index 64c5eefe2..119829a91 100644 --- a/pandapower/test/converter/testfiles/test_trafo_3ph.json +++ b/pandapower/test/converter/testfiles/test_trafo_3ph.json @@ -239,7 +239,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",null,0,1,0.629999995231628,20.0,0.400000005960464,6.0,1.095238089561462,1.649999976158142,0.261914998292923,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,1.095237970352173,100.0,0.0,0.899999976158142,\"Yzn\",1.0,\"\",\"\"]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",null,0,1,0.629999995231628,20.0,0.400000005960464,6.0,1.095238089561462,1.649999976158142,0.261914998292923,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,1.095237970352173,100.0,0.0,0.899999976158142,\"Yzn\",1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -261,7 +261,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -947,7 +947,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -965,7 +965,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -983,7 +983,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV Yzn ASEA": { "sn_mva": 0.6299999952316284, @@ -1003,7 +1003,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1024,7 +1024,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1042,7 +1042,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1060,7 +1060,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1078,7 +1078,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1096,7 +1096,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1114,7 +1114,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1132,7 +1132,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1150,7 +1150,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1168,7 +1168,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1186,7 +1186,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1204,7 +1204,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/converter/testfiles/trafo_tap_model.json b/pandapower/test/converter/testfiles/trafo_tap_model.json index 428711c08..0fefbcd52 100644 --- a/pandapower/test/converter/testfiles/trafo_tap_model.json +++ b/pandapower/test/converter/testfiles/trafo_tap_model.json @@ -305,7 +305,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"tap2_phase_shifter\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"tap2_neutral\",\"tap2_max\",\"tap2_min\",\"tap2_side\",\"tap2_step_percent\",\"tap2_step_degree\",\"tap2_pos\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20],\"data\":[[\"2-Winding Transformer(3)\",\"2-Winding Transformer 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LV-d\",393,328,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,0.0,5.0,0.0,true,1,1.0,true,true,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",0.0,-10.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer(14)\",\"2-W HV-d LV-d\",367,341,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,0.0,5.0,5.0,true,1,1.0,true,true,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",0.0,-10.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer(12)\",\"2-W HV-d LV-d\",354,315,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,0.0,5.0,0.0,true,1,1.0,true,true,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",0.0,-10.0,-5.0,1.0,\"\",\"\"],[\"2-Winding Transformer(15)\",\"2-W HV-d LV-d\",380,406,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,0.0,5.0,3.0,true,1,1.0,true,true,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",0.0,-10.0,-2.0,1.0,\"\",\"\"],[\"2-Winding Transformer(19)\",\"2-W HV-V HV-V\",471,484,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,0.0,0.0,false,1,1.0,true,false,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"hv\",2.0,90.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer(16)\",\"2-W HV-V HV-V\",419,447,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,0.0,5.0,false,1,1.0,true,false,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"hv\",2.0,90.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer(18)\",\"2-W HV-V HV-V\",510,458,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,0.0,0.0,false,1,1.0,true,false,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"hv\",2.0,90.0,-5.0,1.0,\"\",\"\"],[\"2-Winding Transformer(17)\",\"2-W HV-V HV-V\",497,432,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,0.0,3.0,false,1,1.0,true,false,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"hv\",2.0,90.0,-2.0,1.0,\"\",\"\"],[\"2-Winding Transformer(20)\",\"2-W no tap changer\",562,549,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,null,null,null,null,null,null,null,false,1,1.0,true,false,3.0,0.0,100.0,0.0,0.899999976158142,null,null,null,null,null,null,null,1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -327,11 +327,11 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", - "tap2_phase_shifter": "bool", + "tap2_phase_shifter_type": "uint32", "vk0_percent": "float64", "vkr0_percent": "float64", "mag0_percent": "float64", @@ -1091,7 +1091,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1109,7 +1109,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "2-W HV-V LV-d": { "sn_mva": 100.0, @@ -1129,14 +1129,14 @@ "tap_side": "hv", "tap_step_percent": 2.0, "tap_step_degree": 10.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 10, "tap_min": -10, "tap_neutral": 0, "tap2_side": "lv", "tap2_step_percent": 0, "tap2_step_degree": 5.0, - "tap2_phase_shifter": true, + "tap2_phase_shifter_type": 2, "tap2_max": 10, "tap2_min": -10, "tap2_neutral": 0 @@ -1175,14 +1175,14 @@ "tap_side": "hv", "tap_step_percent": 0, "tap_step_degree": 5.0, - "tap_phase_shifter": true, + "tap_phase_shifter_type": 2, "tap_max": 10, "tap_min": -10, "tap_neutral": 0, "tap2_side": "lv", "tap2_step_percent": 0, "tap2_step_degree": -10.0, - "tap2_phase_shifter": true, + "tap2_phase_shifter_type": 2, "tap2_max": 10, "tap2_min": -10, "tap2_neutral": 0 @@ -1205,14 +1205,14 @@ "tap_side": "hv", "tap_step_percent": 2.0, "tap_step_degree": 0.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 10, "tap_min": -10, "tap_neutral": 0, "tap2_side": "hv", "tap2_step_percent": 2.0, "tap2_step_degree": 90.0, - "tap2_phase_shifter": false, + "tap2_phase_shifter_type": 1, "tap2_max": 10, "tap2_min": -10, "tap2_neutral": 0 @@ -1233,7 +1233,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1251,7 +1251,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1269,7 +1269,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "2-W HV-d LV-V": { "sn_mva": 100.0, @@ -1289,14 +1289,14 @@ "tap_side": "hv", "tap_step_percent": 0, "tap_step_degree": 5.0, - "tap_phase_shifter": true, + "tap_phase_shifter_type": 2, "tap_max": 10, "tap_min": -10, "tap_neutral": 0, "tap2_side": "lv", "tap2_step_percent": 2.0, "tap2_step_degree": 30.0, - "tap2_phase_shifter": false, + "tap2_phase_shifter_type": 0, "tap2_max": 10, "tap2_min": -10, "tap2_neutral": 0 @@ -1317,7 +1317,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1335,7 +1335,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1353,7 +1353,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1371,7 +1371,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1389,7 +1389,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1407,7 +1407,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "2-Winding Transformer Type": { "sn_mva": 100.0, @@ -1427,14 +1427,14 @@ "tap_side": "hv", "tap_step_percent": 2.0, "tap_step_degree": 10.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 10, "tap_min": -10, "tap_neutral": 0, "tap2_side": "lv", "tap2_step_percent": 2.0, "tap2_step_degree": 30.0, - "tap2_phase_shifter": false, + "tap2_phase_shifter_type": 0, "tap2_max": 10, "tap2_min": -10, "tap2_neutral": 0 @@ -1455,7 +1455,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1473,7 +1473,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1491,7 +1491,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/estimation/3bus_wls.json b/pandapower/test/estimation/3bus_wls.json index eefe2d22f..7fe04d3d1 100644 --- a/pandapower/test/estimation/3bus_wls.json +++ b/pandapower/test/estimation/3bus_wls.json @@ -157,7 +157,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "dtype": { "name": "object", "std_type": "object", @@ -178,7 +178,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" diff --git a/pandapower/test/estimation/test_wls_estimation.py b/pandapower/test/estimation/test_wls_estimation.py index 7a23e185a..3209b2812 100644 --- a/pandapower/test/estimation/test_wls_estimation.py +++ b/pandapower/test/estimation/test_wls_estimation.py @@ -212,7 +212,7 @@ def test_3bus_with_transformer(): pp.create_std_type(net, {"sn_mva": 25, "vn_hv_kv": 110, "vn_lv_kv": 10, "vk_percent": 10.04, "vkr_percent": 0.276, "pfe_kw": 28.51, "i0_percent": 0.073, "shift_degree": 150, "tap_side": "hv", "tap_neutral": 0, "tap_min": -9, "tap_max": 9, "tap_step_degree": 0, - "tap_step_percent": 1.5, "tap_phase_shifter": False}, + "tap_step_percent": 1.5, "tap_phase_shifter_type": 0}, "25 MVA 110/10 kV v1.4.3 and older", element="trafo") pp.create_transformer(net, 3, 0, std_type="25 MVA 110/10 kV v1.4.3 and older") @@ -498,7 +498,7 @@ def test_init_slack_with_multiple_transformers(angles=True): pp.create_std_type(net, {"sn_mva": 63, "vn_hv_kv": 110, "vn_lv_kv": 10, "vk_percent": 10.04, "vkr_percent": 0.31, "pfe_kw": 31.51, "i0_percent": 0.078, "shift_degree": 150, "tap_side": "hv", "tap_neutral": 0, "tap_min": -9, "tap_max": 9, "tap_step_degree": 0, - "tap_step_percent": 1.5, "tap_phase_shifter": False}, + "tap_step_percent": 1.5, "tap_phase_shifter_type": 0}, "63 MVA 110/10 kV v1.4.3 and older", element="trafo") pp.create_transformer(net, 3, 7, std_type="63 MVA 110/10 kV v1.4.3 and older", in_service=False) diff --git a/pandapower/test/loadflow/runpp_3ph Validation.json b/pandapower/test/loadflow/runpp_3ph Validation.json index f7d418e4d..648556f3c 100644 --- a/pandapower/test/loadflow/runpp_3ph Validation.json +++ b/pandapower/test/loadflow/runpp_3ph Validation.json @@ -253,7 +253,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0,1],\"data\":[[\"Trafo 2\",null,0,6,1.600000023841858,10.0,0.400000005960464,6.0,0.78125,2.700000047683716,0.168750002980232,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,0.78125,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"],[\"Trafo 1\",null,1,2,1.600000023841858,10.0,0.400000005960464,6.0,0.78125,2.700000047683716,0.168750002980232,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,0.78125,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0,1],\"data\":[[\"Trafo 2\",null,0,6,1.600000023841858,10.0,0.400000005960464,6.0,0.78125,2.700000047683716,0.168750002980232,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,0.78125,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"],[\"Trafo 1\",null,1,2,1.600000023841858,10.0,0.400000005960464,6.0,0.78125,2.700000047683716,0.168750002980232,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,0.78125,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -275,7 +275,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -990,7 +990,7 @@ "tap_side": "lv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1011,7 +1011,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1029,7 +1029,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1047,7 +1047,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1065,7 +1065,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1083,7 +1083,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1101,7 +1101,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1119,7 +1119,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1137,7 +1137,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1155,7 +1155,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1173,7 +1173,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1191,7 +1191,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1209,7 +1209,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "2-Wicklungstransformatortyp": { "sn_mva": 1.600000023841858, @@ -1229,7 +1229,7 @@ "tap_side": "lv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1250,7 +1250,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1268,7 +1268,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/loadflow/test_recycle.py b/pandapower/test/loadflow/test_recycle.py index a6bd3ef7d..cd2131896 100644 --- a/pandapower/test/loadflow/test_recycle.py +++ b/pandapower/test/loadflow/test_recycle.py @@ -167,7 +167,6 @@ def test_recycle_dc_trafo_shift(recycle_net): pp.create_transformer(net, 3, b4, std_type="0.4 MVA 10/0.4 kV") net["trafo"].at[0, "tap_pos"] = 0 net["trafo"].at[0, "tap_step_percent"] = 1 - #net["trafo"].at[0, "tap_phase_shifter"] = True net["trafo"].at[0, "tap_step_degree"] = 30 net2 = net.deepcopy() pl = 1.2 @@ -195,9 +194,11 @@ def test_recycle_dc_trafo_ideal(recycle_net): pp.set_user_pf_options(net, calculate_voltage_angles=True) v = net.bus.vn_kv.at[3] b4 = pp.create_bus(net, vn_kv=v) - pp.create_transformer_from_parameters(net, 3, b4, 10, v, v, 0.5, 12, 10, 0.1, 0, + pp.create_transformer_from_parameters(net, 3, b4, 10, v, v, 0.5, + 12, 10, 0.1, 0, tap_side='hv', tap_neutral=0, tap_max=10, tap_min=-10, - tap_step_percent=0, tap_step_degree=30, tap_pos=0, tap_phase_shifter=True) + tap_step_percent=0, tap_step_degree=30, tap_pos=0, + tap_phase_shifter_type=2) net2 = net.deepcopy() pl = 1.2 ql = 0. diff --git a/pandapower/test/loadflow/test_results.py b/pandapower/test/loadflow/test_results.py index 58dc709ed..58fb73df1 100644 --- a/pandapower/test/loadflow/test_results.py +++ b/pandapower/test/loadflow/test_results.py @@ -249,10 +249,10 @@ def test_trafo_2_taps(v_tol=1e-6, i_tol=1e-6, s_tol=1e-2, l_tol=1e-3, va_tol=1e- pp.create_transformer_from_parameters(net, 0, 1, 100, 110, 20, 0.5, 12, 14, 0.5, tap_side="hv", tap_neutral=0, tap_max=10, tap_min=-10, tap_step_percent=2, tap_step_degree=0, - tap_pos=0, tap_phase_shifter=False, + tap_pos=0, tap_phase_shifter_type=0, tap2_side="hv", tap2_neutral=0, tap2_max=10, tap2_min=-10, tap2_step_percent=2, tap2_step_degree=0, - tap2_pos=0, tap2_phase_shifter=False) + tap2_pos=0, tap2_phase_shifter_type=0) pp.create_load(net, 1, 10) @@ -260,156 +260,164 @@ def test_trafo_2_taps(v_tol=1e-6, i_tol=1e-6, s_tol=1e-2, l_tol=1e-3, va_tol=1e- net.res_bus -def test_tap_dependent_impedance(result_test_network): - net = result_test_network - - # first, basic example with piecewise linear characteristic - characteristic_vk = pp.control.Characteristic.from_points(net, ((net.trafo.at[0, 'tap_min'], 0.9 * net.trafo.at[0, 'vk_percent']), - (net.trafo.at[0, 'tap_neutral'], net.trafo.at[0, 'vk_percent']), - (net.trafo.at[0, 'tap_max'], 1.1 * net.trafo.at[0, 'vk_percent']))) - characteristic_vkr = pp.control.Characteristic.from_points(net, ((net.trafo.at[0, 'tap_min'], 0.9 * net.trafo.at[0, 'vkr_percent']), - (net.trafo.at[0, 'tap_neutral'], net.trafo.at[0, 'vkr_percent']), - (net.trafo.at[0, 'tap_max'], 1.1 * net.trafo.at[0, 'vkr_percent']))) - idx_vk = characteristic_vk.index - idx_vkr = characteristic_vkr.index - - # we use for reference - net0 = net.deepcopy() - - net.trafo["tap_dependent_impedance"] = pd.Series(index=net.trafo.index, dtype=bool, data=False) - net.trafo.loc[0, 'tap_dependent_impedance'] = True - net.trafo.loc[0, ['vk_percent_characteristic', 'vkr_percent_characteristic']] = idx_vk, idx_vkr - - # first, make sure there is no change for neutral - net.trafo.at[0, "tap_pos"] = net.trafo.tap_neutral.at[0] - net0.trafo.at[0, "tap_pos"] = net.trafo.tap_neutral.at[0] - pp.runpp(net) - pp.runpp(net0) - assert_res_equal(net, net0) - - - # now check the min and max positions - for pos, factor in (("tap_min", 0.9), ("tap_max", 1.1)): - assert isclose(characteristic_vk(net.trafo[pos].at[0]), net.trafo.vk_percent.at[0]*factor, rtol=0, atol=1e-12) - assert isclose(characteristic_vkr(net.trafo[pos].at[0]), net.trafo.vkr_percent.at[0]*factor, rtol=0, atol=1e-12) - net0.trafo.at[0, "vk_percent"] = net.trafo.vk_percent.at[0]*factor - net0.trafo.at[0, "vkr_percent"] = net.trafo.vkr_percent.at[0]*factor - net0.trafo.at[0, "tap_pos"] = net.trafo[pos].at[0] - pp.runpp(net0) - net.trafo.at[0, "tap_pos"] = net.trafo[pos].at[0] - pp.runpp(net) - assert_res_equal(net, net0) - - -def test_tap_dependent_impedance_controller_comparison(): - net1 = create_net() - net2 = create_net() - - pp.control.create_trafo_characteristics(net1, 'trafo', [0], 'vk_percent', [[-2, -1, 0, 1, 2]], [[5, 5.2, 6, 6.8, 7]]) - pp.control.create_trafo_characteristics(net1, 'trafo', [0], 'vkr_percent', [[-2, -1, 0, 1, 2]], [[1.3, 1.4, 1.44, 1.5, 1.6]]) - - pp.control.SplineCharacteristic(net2, [-2, -1, 0, 1, 2], [5, 5.2, 6, 6.8, 7]) - pp.control.SplineCharacteristic(net2, [-2, -1, 0, 1, 2], [1.3, 1.4, 1.44, 1.5, 1.6]) - pp.control.TapDependentImpedance(net2, [0], 0, output_variable="vk_percent") - pp.control.TapDependentImpedance(net2, [0], 1, output_variable="vkr_percent") - - pp.runpp(net1) - pp.runpp(net2, run_control=True) - - assert_res_equal(net1, net2) - - -def test_tap_dependent_impedance_controller_comparison_3w(): - net1 = create_net() - net2 = create_net() - for i in range(2): - add_trafo_connection(net1, net1.trafo.at[0, 'hv_bus'], "3W") - add_trafo_connection(net2, net2.trafo.at[0, 'hv_bus'], "3W") - - pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vk_hv_percent', [[-2, -1, 0, 1, 2]], [[0.85, 0.9, 1, 1.1, 1.15]]) - pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vkr_hv_percent', [[-2, -1, 0, 1, 2]], [[0.27, 0.28, 0.3, 0.32, 0.33]]) - pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vk_mv_percent', [[-2, -1, 0, 1, 2]], [[0.85, 0.9, 1, 1.1, 1.15]]) - pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vkr_mv_percent', [[-2, -1, 0, 1, 2]], [[0.27, 0.28, 0.3, 0.32, 0.33]]) - pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vk_lv_percent', [[-2, -1, 0, 1, 2]], [[0.85, 0.9, 1, 1.1, 1.15]]) - pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vkr_lv_percent', [[-2, -1, 0, 1, 2]], [[0.27, 0.28, 0.3, 0.32, 0.33]]) - - pp.control.SplineCharacteristic(net2, [-2, -1, 0, 1, 2], [0.85, 0.9, 1, 1.1, 1.15]) - pp.control.SplineCharacteristic(net2, [-2, -1, 0, 1, 2], [0.27, 0.28, 0.3, 0.32, 0.33]) - - pp.control.TapDependentImpedance(net2, [0], 0, element="trafo3w", output_variable="vk_hv_percent") - pp.control.TapDependentImpedance(net2, [0], 1, element="trafo3w", output_variable="vkr_hv_percent") - pp.control.TapDependentImpedance(net2, [0], 0, element="trafo3w", output_variable="vk_mv_percent") - pp.control.TapDependentImpedance(net2, [0], 1, element="trafo3w", output_variable="vkr_mv_percent") - pp.control.TapDependentImpedance(net2, [0], 0, element="trafo3w", output_variable="vk_lv_percent") - pp.control.TapDependentImpedance(net2, [0], 1, element="trafo3w", output_variable="vkr_lv_percent") - - pp.runpp(net1) - pp.runpp(net2, run_control=True) - - assert_res_equal(net1, net2) - - -def test_undefined_tap_dependent_impedance_characteristics(): - # if some characteristic per 1 trafo are undefined, but at least 1 is defined -> OK - # if all characteristic per 1 trafo are undefined -> raise error - net = create_net() - pp.control.create_trafo_characteristics(net, 'trafo', [0], 'vk_percent', [[-2, -1, 0, 1, 2]], [[5, 5.2, 6, 6.8, 7]]) - pp.control.create_trafo_characteristics(net, 'trafo', [0], 'vkr_percent', [[-2, -1, 0, 1, 2]], [[1.3, 1.4, 1.44, 1.5, 1.6]]) - pp.control.create_trafo_characteristics(net, 'trafo', [1], 'vk_percent', [[-2, -1, 0, 1, 2]], [[5, 5.2, 6, 6.8, 7]]) - - # does not raise error - pp.runpp(net) - - # this will raise error - net.trafo.at[1, "vk_percent_characteristic"] = None - with pytest.raises(UserWarning): - pp.runpp(net) - - -def test_undefined_tap_dependent_impedance_characteristics_trafo3w(): - # if some characteristic per 1 trafo are undefined, but at least 1 is defined -> OK - # if all characteristic per 1 trafo are undefined -> raise error - net = create_net() - add_trafo_connection(net, 1, "3W") - add_trafo_connection(net, 1, "3W") - net2 = create_net() - add_trafo_connection(net2, 1, "3W") - add_trafo_connection(net2, 1, "3W") - - pp.control.create_trafo_characteristics( - net, 'trafo3w', [0, 1], 'vk_mv_percent', [[-2, -1, 0, 1, 2], [-2, -1, 0, 1, 2]], - [[0.7, 0.9, 1, 1.1, 1.3], [0.7, 0.9, 1, 1.1, 1.3]]) - pp.control.create_trafo_characteristics( - net, 'trafo3w', [0, 1], 'vkr_mv_percent', [[-2, -1, 0, 1, 2], [-2, -1, 0, 1, 2]], - [[0.3, 0.45, 0.5, 0.55, 0.7], [0.3, 0.45, 0.5, 0.55, 0.7]]) - - pp.control.Characteristic(net2, [-2, -1, 0, 1, 2], [0.7, 0.9, 1, 1.1, 1.3]) - pp.control.Characteristic(net2, [-2, -1, 0, 1, 2], [0.3, 0.45, 0.5, 0.55, 0.7]) - - pp.control.TapDependentImpedance(net2, [0], 0, element="trafo3w", output_variable="vk_mv_percent") - pp.control.TapDependentImpedance(net2, [0], 1, element="trafo3w", output_variable="vkr_mv_percent") - pp.control.TapDependentImpedance(net2, [1], 0, element="trafo3w", output_variable="vk_mv_percent") - pp.control.TapDependentImpedance(net2, [1], 1, element="trafo3w", output_variable="vkr_mv_percent") - - pp.runpp(net) - pp.runpp(net2, run_control=True) - assert_res_equal(net, net2) - - net.trafo3w.at[0, "vk_mv_percent_characteristic"] = None - pp.runpp(net) - net2.controller.at[0, "in_service"] = False - pp.runpp(net2, run_control=True) - assert_res_equal(net, net2) - - net.trafo3w.at[0, "vkr_mv_percent_characteristic"] = None - net2.controller.at[1, "in_service"] = False - with pytest.raises(UserWarning): - pp.runpp(net) - - net.trafo3w.at[0, "tap_dependent_impedance"] = False - pp.runpp(net) - pp.runpp(net2, run_control=True) - assert_res_equal(net, net2) +# todo create new test for new tap_characteristic_table logic +# commented out due to new logic on characteristics +# def test_tap_dependent_impedance(result_test_network): +# net = result_test_network +# +# # first, basic example with piecewise linear characteristic +# characteristic_vk = pp.control.Characteristic.from_points( +# net, ((net.trafo.at[0, 'tap_min'], 0.9 * net.trafo.at[0, 'vk_percent']), +# (net.trafo.at[0, 'tap_neutral'], net.trafo.at[0, 'vk_percent']), +# (net.trafo.at[0, 'tap_max'], 1.1 * net.trafo.at[0, 'vk_percent']))) +# characteristic_vkr = pp.control.Characteristic.from_points( +# net, ((net.trafo.at[0, 'tap_min'], 0.9 * net.trafo.at[0, 'vkr_percent']), +# (net.trafo.at[0, 'tap_neutral'], net.trafo.at[0, 'vkr_percent']), +# (net.trafo.at[0, 'tap_max'], 1.1 * net.trafo.at[0, 'vkr_percent']))) +# idx_vk = characteristic_vk.index +# idx_vkr = characteristic_vkr.index +# +# # we use for reference +# net0 = net.deepcopy() +# +# net.trafo["tap_dependent_impedance"] = pd.Series(index=net.trafo.index, dtype=bool, data=False) +# net.trafo.loc[0, 'tap_dependent_impedance'] = True +# net.trafo.loc[0, ['vk_percent_characteristic', 'vkr_percent_characteristic']] = idx_vk, idx_vkr +# +# # first, make sure there is no change for neutral +# net.trafo.at[0, "tap_pos"] = net.trafo.tap_neutral.at[0] +# net0.trafo.at[0, "tap_pos"] = net.trafo.tap_neutral.at[0] +# pp.runpp(net) +# pp.runpp(net0) +# assert_res_equal(net, net0) +# +# +# # now check the min and max positions +# for pos, factor in (("tap_min", 0.9), ("tap_max", 1.1)): +# assert isclose(characteristic_vk(net.trafo[pos].at[0]), net.trafo.vk_percent.at[0]*factor, rtol=0, atol=1e-12) +# assert isclose(characteristic_vkr(net.trafo[pos].at[0]), net.trafo.vkr_percent.at[0]*factor, rtol=0, atol=1e-12) +# net0.trafo.at[0, "vk_percent"] = net.trafo.vk_percent.at[0]*factor +# net0.trafo.at[0, "vkr_percent"] = net.trafo.vkr_percent.at[0]*factor +# net0.trafo.at[0, "tap_pos"] = net.trafo[pos].at[0] +# pp.runpp(net0) +# net.trafo.at[0, "tap_pos"] = net.trafo[pos].at[0] +# pp.runpp(net) +# assert_res_equal(net, net0) +# +# +# commented out due to new logic on characteristics +# def test_tap_dependent_impedance_controller_comparison(): +# net1 = create_net() +# net2 = create_net() +# +# pp.control.create_trafo_characteristics(net1, 'trafo', [0], 'vk_percent', [[-2, -1, 0, 1, 2]], [[5, 5.2, 6, 6.8, 7]]) +# pp.control.create_trafo_characteristics(net1, 'trafo', [0], 'vkr_percent', [[-2, -1, 0, 1, 2]], [[1.3, 1.4, 1.44, 1.5, 1.6]]) +# +# pp.control.SplineCharacteristic(net2, [-2, -1, 0, 1, 2], [5, 5.2, 6, 6.8, 7]) +# pp.control.SplineCharacteristic(net2, [-2, -1, 0, 1, 2], [1.3, 1.4, 1.44, 1.5, 1.6]) +# pp.control.TapDependentImpedance(net2, [0], 0, output_variable="vk_percent") +# pp.control.TapDependentImpedance(net2, [0], 1, output_variable="vkr_percent") +# +# pp.runpp(net1) +# pp.runpp(net2, run_control=True) +# +# assert_res_equal(net1, net2) +# +# +# commented out due to new logic on characteristics +# def test_tap_dependent_impedance_controller_comparison_3w(): +# net1 = create_net() +# net2 = create_net() +# for i in range(2): +# add_trafo_connection(net1, net1.trafo.at[0, 'hv_bus'], "3W") +# add_trafo_connection(net2, net2.trafo.at[0, 'hv_bus'], "3W") +# +# pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vk_hv_percent', [[-2, -1, 0, 1, 2]], [[0.85, 0.9, 1, 1.1, 1.15]]) +# pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vkr_hv_percent', [[-2, -1, 0, 1, 2]], [[0.27, 0.28, 0.3, 0.32, 0.33]]) +# pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vk_mv_percent', [[-2, -1, 0, 1, 2]], [[0.85, 0.9, 1, 1.1, 1.15]]) +# pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vkr_mv_percent', [[-2, -1, 0, 1, 2]], [[0.27, 0.28, 0.3, 0.32, 0.33]]) +# pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vk_lv_percent', [[-2, -1, 0, 1, 2]], [[0.85, 0.9, 1, 1.1, 1.15]]) +# pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vkr_lv_percent', [[-2, -1, 0, 1, 2]], [[0.27, 0.28, 0.3, 0.32, 0.33]]) +# +# pp.control.SplineCharacteristic(net2, [-2, -1, 0, 1, 2], [0.85, 0.9, 1, 1.1, 1.15]) +# pp.control.SplineCharacteristic(net2, [-2, -1, 0, 1, 2], [0.27, 0.28, 0.3, 0.32, 0.33]) +# +# pp.control.TapDependentImpedance(net2, [0], 0, element="trafo3w", output_variable="vk_hv_percent") +# pp.control.TapDependentImpedance(net2, [0], 1, element="trafo3w", output_variable="vkr_hv_percent") +# pp.control.TapDependentImpedance(net2, [0], 0, element="trafo3w", output_variable="vk_mv_percent") +# pp.control.TapDependentImpedance(net2, [0], 1, element="trafo3w", output_variable="vkr_mv_percent") +# pp.control.TapDependentImpedance(net2, [0], 0, element="trafo3w", output_variable="vk_lv_percent") +# pp.control.TapDependentImpedance(net2, [0], 1, element="trafo3w", output_variable="vkr_lv_percent") +# +# pp.runpp(net1) +# pp.runpp(net2, run_control=True) +# +# assert_res_equal(net1, net2) + + +# commented out due to new logic on characteristics +# def test_undefined_tap_dependent_impedance_characteristics(): +# # if some characteristic per 1 trafo are undefined, but at least 1 is defined -> OK +# # if all characteristic per 1 trafo are undefined -> raise error +# net = create_net() +# pp.control.create_trafo_characteristics(net, 'trafo', [0], 'vk_percent', [[-2, -1, 0, 1, 2]], [[5, 5.2, 6, 6.8, 7]]) +# pp.control.create_trafo_characteristics(net, 'trafo', [0], 'vkr_percent', [[-2, -1, 0, 1, 2]], [[1.3, 1.4, 1.44, 1.5, 1.6]]) +# pp.control.create_trafo_characteristics(net, 'trafo', [1], 'vk_percent', [[-2, -1, 0, 1, 2]], [[5, 5.2, 6, 6.8, 7]]) +# +# # does not raise error +# pp.runpp(net) +# +# # this will raise error +# net.trafo.at[1, "vk_percent_characteristic"] = None +# with pytest.raises(UserWarning): +# pp.runpp(net) + + +# commented out due to new logic on characteristics +# def test_undefined_tap_dependent_impedance_characteristics_trafo3w(): +# # if some characteristic per 1 trafo are undefined, but at least 1 is defined -> OK +# # if all characteristic per 1 trafo are undefined -> raise error +# net = create_net() +# add_trafo_connection(net, 1, "3W") +# add_trafo_connection(net, 1, "3W") +# net2 = create_net() +# add_trafo_connection(net2, 1, "3W") +# add_trafo_connection(net2, 1, "3W") +# +# pp.control.create_trafo_characteristics( +# net, 'trafo3w', [0, 1], 'vk_mv_percent', [[-2, -1, 0, 1, 2], [-2, -1, 0, 1, 2]], +# [[0.7, 0.9, 1, 1.1, 1.3], [0.7, 0.9, 1, 1.1, 1.3]]) +# pp.control.create_trafo_characteristics( +# net, 'trafo3w', [0, 1], 'vkr_mv_percent', [[-2, -1, 0, 1, 2], [-2, -1, 0, 1, 2]], +# [[0.3, 0.45, 0.5, 0.55, 0.7], [0.3, 0.45, 0.5, 0.55, 0.7]]) +# +# pp.control.Characteristic(net2, [-2, -1, 0, 1, 2], [0.7, 0.9, 1, 1.1, 1.3]) +# pp.control.Characteristic(net2, [-2, -1, 0, 1, 2], [0.3, 0.45, 0.5, 0.55, 0.7]) +# +# pp.control.TapDependentImpedance(net2, [0], 0, element="trafo3w", output_variable="vk_mv_percent") +# pp.control.TapDependentImpedance(net2, [0], 1, element="trafo3w", output_variable="vkr_mv_percent") +# pp.control.TapDependentImpedance(net2, [1], 0, element="trafo3w", output_variable="vk_mv_percent") +# pp.control.TapDependentImpedance(net2, [1], 1, element="trafo3w", output_variable="vkr_mv_percent") +# +# pp.runpp(net) +# pp.runpp(net2, run_control=True) +# assert_res_equal(net, net2) +# +# net.trafo3w.at[0, "vk_mv_percent_characteristic"] = None +# pp.runpp(net) +# net2.controller.at[0, "in_service"] = False +# pp.runpp(net2, run_control=True) +# assert_res_equal(net, net2) +# +# net.trafo3w.at[0, "vkr_mv_percent_characteristic"] = None +# net2.controller.at[1, "in_service"] = False +# with pytest.raises(UserWarning): +# pp.runpp(net) +# +# net.trafo3w.at[0, "tap_dependent_impedance"] = False +# pp.runpp(net) +# pp.runpp(net2, run_control=True) +# assert_res_equal(net, net2) def test_ext_grid(result_test_network, v_tol=1e-6, va_tol=1e-2, i_tol=1e-6, s_tol=5e-3, l_tol=1e-3): diff --git a/pandapower/test/loadflow/test_runpp.py b/pandapower/test/loadflow/test_runpp.py index e6c7e764b..ce1e91b7f 100644 --- a/pandapower/test/loadflow/test_runpp.py +++ b/pandapower/test/loadflow/test_runpp.py @@ -1331,14 +1331,24 @@ def test_tap_dependent_impedance(): net_backup = net.deepcopy() - pp.control.create_trafo_characteristics(net, 'trafo', [0], "vk_percent", [[-2, -1, 0, 1, 2]], [[5.5, 5.8, 6, 6.2, 6.5]]) - pp.control.create_trafo_characteristics(net, 'trafo', [0], "vkr_percent", [[-2, -1, 0, 1, 2]], [[1.4, 1.42, 1.44, 1.46, 1.48]]) - pp.control.create_trafo_characteristics(net, 'trafo', [1], "vk_percent", [[-2, -1, 0, 1, 2]], [[5.4, 5.7, 6, 6.1, 6.4]]) - - # test alternative way to set up tap dependence impedance characteristic - pp.control.SplineCharacteristic(net, [-2, -1, 0, 1, 2], [0.95, 0.98, 1, 1.02, 1.05]) - net.trafo3w['tap_dependent_impedance'] = True - net.trafo3w['vk_hv_percent_characteristic'] = 3 + net["trafo_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [1, 1, 1, 1, 1], + 'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [5.5, 5.8, 6, 6.2, 6.5], + 'vkr_percent': [1.4, 1.42, 1.44, 1.46, 1.48], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan, + 'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan}) + net.trafo['id_characteristic_table'].at[0] = 0 + net.trafo['tap_dependency_table'].at[0] = True + net.trafo['tap_dependency_table'].at[1] = False + + new_rows = pd.DataFrame( + {'id_characteristic': [1, 1, 1, 1, 1], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [1, 1, 1, 1, 1], + 'angle_deg': [0, 0, 0, 0, 0], 'vk_hv_percent': [0.95, 0.98, 1, 1.02, 1.05], + 'vkr_hv_percent': [0.3, 0.3, 0.3, 0.3, 0.3], 'vk_mv_percent': [1, 1, 1, 1, 1], + 'vkr_mv_percent': [0.3, 0.3, 0.3, 0.3, 0.3], 'vk_lv_percent': [1, 1, 1, 1, 1], + 'vkr_lv_percent': [0.3, 0.3, 0.3, 0.3, 0.3]}) + net["trafo_characteristic_table"] = pd.concat([net["trafo_characteristic_table"], new_rows], ignore_index=True) + net.trafo3w['id_characteristic_table'].at[0] = 1 + net.trafo3w['tap_dependency_table'].at[0] = True pp.runpp(net) pp.runpp(net_backup) @@ -1353,14 +1363,6 @@ def test_tap_dependent_impedance(): pp.runpp(net_backup) assert_res_equal(net, net_backup) - net.trafo.at[1, "tap_pos"] = -2 - net_backup.trafo.at[1, "tap_pos"] = -2 - net_backup.trafo.at[1, "vk_percent"] = 5.4 - - pp.runpp(net) - pp.runpp(net_backup) - assert_res_equal(net, net_backup) - net.trafo3w.at[0, "tap_pos"] = 2 net_backup.trafo3w.at[0, "tap_pos"] = 2 net_backup.trafo3w.at[0, "vk_hv_percent"] = 1.05 diff --git a/pandapower/test/loadflow/test_runpp_3ph.py b/pandapower/test/loadflow/test_runpp_3ph.py index 440fc6617..0c9720aa3 100644 --- a/pandapower/test/loadflow/test_runpp_3ph.py +++ b/pandapower/test/loadflow/test_runpp_3ph.py @@ -411,7 +411,7 @@ def make_nw(net, bushv, tap_ps, case, vector_group): tap_min=-2, tap_max=2, tap_step_degree=0, tap_step_percent=2.5, - tap_phase_shifter=False, + tap_phase_shifter_type=0, vk0_percent=6, vkr0_percent=0.78125, mag0_percent=100, mag0_rx=0., si0_hv_partial=0.9, vector_group=vector_group, diff --git a/pandapower/test/shortcircuit/sc_test_meshed_grid.json b/pandapower/test/shortcircuit/sc_test_meshed_grid.json index 26065891a..14b20dad8 100644 --- a/pandapower/test/shortcircuit/sc_test_meshed_grid.json +++ b/pandapower/test/shortcircuit/sc_test_meshed_grid.json @@ -165,7 +165,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"2-Wicklungstransformator(2)\",\"0.63 MVA 10\\/0.4 kV Yyn0 6 ASEA\",0,1,0.629999995231628,10.0,0.400000005960464,6.0,1.047619104385376,1.399999976158142,0.22223199903965,0.0,\"hv\",0,-2,2,2.5,null,0,false,1,1.0,true],[\"2-Wicklungstransformator\",\"0.4 MVA 10\\/0.4 kV Yyn6 4 ASEA\",3,4,0.400000005960464,10.0,0.400000005960464,4.0,1.075000047683716,1.149999976158142,0.287510007619858,180.0,\"hv\",0,-2,2,2.5,null,0,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"2-Wicklungstransformator(2)\",\"0.63 MVA 10\\/0.4 kV Yyn0 6 ASEA\",0,1,0.629999995231628,10.0,0.400000005960464,6.0,1.047619104385376,1.399999976158142,0.22223199903965,0.0,\"hv\",0,-2,2,2.5,null,0,false,1,1.0,true],[\"2-Wicklungstransformator\",\"0.4 MVA 10\\/0.4 kV Yyn6 4 ASEA\",3,4,0.400000005960464,10.0,0.400000005960464,4.0,1.075000047683716,1.149999976158142,0.287510007619858,180.0,\"hv\",0,-2,2,2.5,null,0,false,1,1.0,true]]}", "dtype": { "name": "object", "std_type": "object", @@ -186,7 +186,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" diff --git a/pandapower/test/shortcircuit/test_1ph.py b/pandapower/test/shortcircuit/test_1ph.py index fce8387dd..105fd73fe 100644 --- a/pandapower/test/shortcircuit/test_1ph.py +++ b/pandapower/test/shortcircuit/test_1ph.py @@ -44,7 +44,7 @@ def add_network(net, vector_group): "sn_mva": 25, "vn_lv_kv": 20.0, "vn_hv_kv": 110.0, "vk_percent": 11.2, "shift_degree": 150, "vector_group": vector_group, "tap_side": "hv", "tap_neutral": 0, "tap_min": -9, "tap_max": 9, "tap_step_degree": 0, - "tap_step_percent": 1.5, "tap_phase_shifter": False, "vk0_percent": 5, + "tap_step_percent": 1.5, "tap_phase_shifter_type": 0, "vk0_percent": 5, "vkr0_percent": 0.4, "mag0_percent": 10, "mag0_rx": 0.4, "si0_hv_partial": 0.9} pp.create_std_type(net, transformer_type, vector_group, "trafo") diff --git a/pandapower/test/test_files/IEC60909-4_example.json b/pandapower/test/test_files/IEC60909-4_example.json index 9ae262e56..b7328cd86 100644 --- a/pandapower/test/test_files/IEC60909-4_example.json +++ b/pandapower/test/test_files/IEC60909-4_example.json @@ -179,7 +179,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"_ppc_idx\",\"description\",\"df\",\"equipment\",\"hv_bus\",\"i0_percent\",\"in_service\",\"lv_bus\",\"mag0_percent\",\"mag0_rx\",\"name\",\"parallel\",\"shift_degree\",\"si0_hv_partial\",\"sn_mva\",\"std_type\",\"tap_max\",\"tap_neutral\",\"tap_min\",\"tap_phase_shifter\",\"tap_pos\",\"tap_set_vm_pu\",\"tap_side\",\"tap_step_degree\",\"tap_step_percent\",\"vector_group\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk0_percent\",\"vk_percent\",\"vkr0_percent\",\"vkr_percent\",\"pfe_kw\"],\"index\":[0,1],\"data\":[[4,\"\",1.0,\"\",0,0.0,true,3,100,0,\"T1\",1,150.0,0.8999999762,0.6299999952316,\"20\\/0.4 kV 630 kVA\",null,null,null,false,0,1.0,null,null,null,\"YNyn\",20.0,0.4099999964,3.8136322498,4.0,1.0317460299,1.0317460299,0.0],[5,\"\",1.0,\"\",0,0.0,true,4,100,0,\"T2\",1,150.0,0.8999999762,0.4000000059605,\"20\\/0.4 kV 400 kVA\",null,null,null,false,0,1.0,null,null,null,\"Dyn\",20.0,0.4099999964,3.8169283867,4.0,1.1499999762,1.1499999762,0.0]]}", + "_object": "{\"columns\":[\"_ppc_idx\",\"description\",\"df\",\"equipment\",\"hv_bus\",\"i0_percent\",\"in_service\",\"lv_bus\",\"mag0_percent\",\"mag0_rx\",\"name\",\"parallel\",\"shift_degree\",\"si0_hv_partial\",\"sn_mva\",\"std_type\",\"tap_max\",\"tap_neutral\",\"tap_min\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_set_vm_pu\",\"tap_side\",\"tap_step_degree\",\"tap_step_percent\",\"vector_group\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk0_percent\",\"vk_percent\",\"vkr0_percent\",\"vkr_percent\",\"pfe_kw\"],\"index\":[0,1],\"data\":[[4,\"\",1.0,\"\",0,0.0,true,3,100,0,\"T1\",1,150.0,0.8999999762,0.6299999952316,\"20\\/0.4 kV 630 kVA\",null,null,null,false,0,1.0,null,null,null,\"YNyn\",20.0,0.4099999964,3.8136322498,4.0,1.0317460299,1.0317460299,0.0],[5,\"\",1.0,\"\",0,0.0,true,4,100,0,\"T2\",1,150.0,0.8999999762,0.4000000059605,\"20\\/0.4 kV 400 kVA\",null,null,null,false,0,1.0,null,null,null,\"Dyn\",20.0,0.4099999964,3.8169283867,4.0,1.1499999762,1.1499999762,0.0]]}", "dtype": { "_ppc_idx": "int32", "description": "object", @@ -200,7 +200,7 @@ "tap_max": "float64", "tap_neutral": "float64", "tap_min": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_set_vm_pu": "float64", "tap_side": "object", @@ -972,7 +972,7 @@ "tap_max": 2.0, "tap_neutral": 0.0, "tap_min": -2.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 2.5, @@ -995,7 +995,7 @@ "tap_max": 2.0, "tap_neutral": 0.0, "tap_min": -2.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 2.5, @@ -1018,7 +1018,7 @@ "tap_max": 2.0, "tap_neutral": 0.0, "tap_min": -2.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 2.5, @@ -1041,7 +1041,7 @@ "tap_max": 2.0, "tap_neutral": 0.0, "tap_min": -2.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 2.5, @@ -1064,7 +1064,7 @@ "tap_max": 2.0, "tap_neutral": 0.0, "tap_min": -2.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 2.5, @@ -1087,7 +1087,7 @@ "tap_max": 2.0, "tap_neutral": 0.0, "tap_min": -2.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 2.5, @@ -1110,7 +1110,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1133,7 +1133,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1156,7 +1156,7 @@ "tap_max": NaN, "tap_neutral": NaN, "tap_min": NaN, - "tap_phase_shifter": null, + "tap_phase_shifter_type": NaN, "tap_side": null, "tap_step_degree": NaN, "tap_step_percent": NaN, @@ -1179,7 +1179,7 @@ "tap_max": NaN, "tap_neutral": NaN, "tap_min": NaN, - "tap_phase_shifter": null, + "tap_phase_shifter_type": NaN, "tap_side": null, "tap_step_degree": NaN, "tap_step_percent": NaN, @@ -1202,7 +1202,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1225,7 +1225,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1248,7 +1248,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1271,7 +1271,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1294,7 +1294,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1317,7 +1317,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1340,7 +1340,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1363,7 +1363,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1386,7 +1386,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1409,7 +1409,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1432,7 +1432,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1455,7 +1455,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, diff --git a/pandapower/test/test_files/controller_containing_NoneNan.json b/pandapower/test/test_files/controller_containing_NoneNan.json index 5d95a82d8..133e3329f 100644 --- a/pandapower/test/test_files/controller_containing_NoneNan.json +++ b/pandapower/test/test_files/controller_containing_NoneNan.json @@ -198,7 +198,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -220,7 +220,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -897,7 +897,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -915,7 +915,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -933,7 +933,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -951,7 +951,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -969,7 +969,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -987,7 +987,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1005,7 +1005,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1023,7 +1023,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1041,7 +1041,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1059,7 +1059,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1077,7 +1077,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1095,7 +1095,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1113,7 +1113,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1131,7 +1131,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.0.0.json b/pandapower/test/test_files/old_versions/example_2.0.0.json index 7dc5ffe9c..5845dd99b 100644 --- a/pandapower/test/test_files/old_versions/example_2.0.0.json +++ b/pandapower/test/test_files/old_versions/example_2.0.0.json @@ -1,5 +1,5 @@ { "_class": "pandapowerNet", "_module": "pandapower.auxiliary", - "_object": "{\"OPF_converged\":false,\"bus\":{\n \"dtype\": {\n \"type\": \"object\",\n \"name\": \"object\",\n \"zone\": \"object\",\n \"in_service\": \"bool\",\n \"vn_kv\": \"float64\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"vn_kv\\\",\\\"type\\\",\\\"zone\\\",\\\"in_service\\\"],\\\"index\\\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56],\\\"data\\\":[[\\\"Double Busbar 1\\\",380.0,\\\"b\\\",null,true],[\\\"Double Busbar 2\\\",380.0,\\\"b\\\",null,true],[\\\"Bus DB T0\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T1\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T2\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T3\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T4\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T5\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T6\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T7\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T8\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T9\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB 1\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB 2\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB 3\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB 4\\\",380.0,\\\"n\\\",null,true],[\\\"Single Busbar\\\",110.0,\\\"b\\\",null,true],[\\\"Bus SB 1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 3\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 4\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 5\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T1.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T1.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T2.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T2.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T3.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T3.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T4.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T4.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T5.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T5.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV3\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV4\\\",110.0,\\\"n\\\",null,true],[\\\"Bus MV0 20kV\\\",20.0,\\\"n\\\",null,true],[\\\"Bus MV0\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV1\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV2\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV3\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV4\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV5\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV6\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV7\\\",10.0,\\\"n\\\",null,true],[\\\"Bus LV0\\\",0.4,\\\"n\\\",null,true],[\\\"Bus LV1.1\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV1.2\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV1.3\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV1.4\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV1.5\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV2.1\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV2.2\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV2.3\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV2.4\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV2.2.1\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV2.2.2\\\",0.4,\\\"m\\\",null,true]]}\"\n},\"bus_geodata\":{\n \"dtype\": {\n \"x\": \"float64\",\n \"y\": \"float64\",\n \"coords\": \"object\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": \"{\\\"columns\\\":[\\\"x\\\",\\\"y\\\",\\\"coords\\\"],\\\"index\\\":[],\\\"data\\\":[]}\"\n},\"converged\":true,\"dcline\":{\n \"dtype\": {\n \"from_bus\": \"uint32\",\n \"loss_percent\": \"float64\",\n \"vm_to_pu\": \"float64\",\n \"max_q_to_mvar\": \"float64\",\n \"in_service\": \"bool\",\n \"loss_mw\": \"float64\",\n \"min_q_from_mvar\": \"float64\",\n \"p_mw\": \"float64\",\n \"max_q_from_mvar\": \"float64\",\n \"vm_from_pu\": \"float64\",\n \"to_bus\": \"uint32\",\n \"max_p_mw\": \"float64\",\n \"name\": \"object\",\n \"min_q_to_mvar\": \"float64\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"from_bus\\\",\\\"to_bus\\\",\\\"p_mw\\\",\\\"loss_percent\\\",\\\"loss_mw\\\",\\\"vm_from_pu\\\",\\\"vm_to_pu\\\",\\\"max_p_mw\\\",\\\"min_q_from_mvar\\\",\\\"min_q_to_mvar\\\",\\\"max_q_from_mvar\\\",\\\"max_q_to_mvar\\\",\\\"in_service\\\"],\\\"index\\\":[],\\\"data\\\":[]}\"\n},\"ext_grid\":{\n \"dtype\": {\n \"vm_pu\": \"float64\",\n \"rx_max\": \"float64\",\n \"in_service\": \"bool\",\n \"name\": \"object\",\n \"s_sc_max_mva\": \"float64\",\n \"bus\": \"uint32\",\n \"rx_min\": \"float64\",\n \"va_degree\": \"float64\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"bus\\\",\\\"vm_pu\\\",\\\"va_degree\\\",\\\"in_service\\\",\\\"s_sc_max_mva\\\",\\\"rx_min\\\",\\\"rx_max\\\"],\\\"index\\\":[0],\\\"data\\\":[[\\\"External grid\\\",0,1.03,0.0,true,10000.0,0.1,0.1]]}\"\n},\"f_hz\":50.0,\"gen\":{\n \"dtype\": {\n \"vm_pu\": \"float64\",\n \"sn_mva\": \"float64\",\n \"max_q_mvar\": \"float64\",\n \"slack\": \"bool\",\n \"in_service\": \"bool\",\n \"scaling\": \"float64\",\n \"min_q_mvar\": \"float64\",\n \"name\": \"object\",\n \"type\": \"object\",\n \"p_mw\": \"float64\",\n \"bus\": \"uint32\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"bus\\\",\\\"p_mw\\\",\\\"vm_pu\\\",\\\"sn_mva\\\",\\\"min_q_mvar\\\",\\\"max_q_mvar\\\",\\\"scaling\\\",\\\"slack\\\",\\\"in_service\\\",\\\"type\\\"],\\\"index\\\":[0],\\\"data\\\":[[\\\"Gas turbine\\\",35,100.0,1.03,null,null,null,1.0,false,true,null]]}\"\n},\"impedance\":{\n \"dtype\": {\n \"from_bus\": \"uint32\",\n \"xft_pu\": \"float64\",\n \"xtf_pu\": \"float64\",\n \"to_bus\": \"uint32\",\n \"in_service\": \"bool\",\n \"rtf_pu\": \"float64\",\n \"name\": \"object\",\n \"sn_mva\": \"float64\",\n \"rft_pu\": \"float64\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n 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1.206,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 0.4,\n \"tap_neutral\": 0\n },\n \"25 MVA 110/20 kV\": {\n \"tap_max\": 9,\n \"vector_group\": \"YNd5\",\n \"shift_degree\": 150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"i0_percent\": 0.07,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 14,\n \"sn_mva\": 25,\n \"vn_hv_kv\": 110.0,\n \"tap_min\": -9,\n \"vk_percent\": 12,\n \"vkr_percent\": 0.41,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 20.0,\n \"tap_neutral\": 0\n },\n \"100 MVA 220/110 kV\": {\n \"tap_max\": 9,\n \"vector_group\": \"Yy0\",\n \"shift_degree\": 0,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"i0_percent\": 0.06,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 55,\n \"sn_mva\": 100,\n \"vn_hv_kv\": 220.0,\n \"tap_min\": -9,\n \"vk_percent\": 12.0,\n \"vkr_percent\": 0.26,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 110.0,\n \"tap_neutral\": 0\n },\n \"63 MVA 110/10 kV\": {\n \"tap_max\": 9,\n \"vector_group\": \"YNd5\",\n \"shift_degree\": 150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"vn_hv_kv\": 110,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 22,\n \"sn_mva\": 63,\n \"i0_percent\": 0.04,\n \"tap_min\": -9,\n \"vk_percent\": 18,\n \"vkr_percent\": 0.32,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 10,\n \"tap_neutral\": 0\n },\n \"63 MVA 110/20 kV\": {\n \"tap_max\": 9,\n \"vector_group\": \"YNd5\",\n \"shift_degree\": 150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"i0_percent\": 0.04,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 22,\n \"sn_mva\": 63,\n \"vn_hv_kv\": 110.0,\n \"tap_min\": -9,\n \"vk_percent\": 18,\n \"vkr_percent\": 0.32,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 20.0,\n \"tap_neutral\": 0\n },\n \"25 MVA 110/10 kV\": {\n \"tap_max\": 9,\n \"vector_group\": \"YNd5\",\n \"shift_degree\": 150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"vn_hv_kv\": 110,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 14,\n \"sn_mva\": 25,\n \"i0_percent\": 0.07,\n \"tap_min\": -9,\n \"vk_percent\": 12,\n \"vkr_percent\": 0.41,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 10,\n \"tap_neutral\": 0\n },\n \"0.63 MVA 10/0.4 kV\": {\n \"tap_max\": 2,\n \"vector_group\": \"Dyn5\",\n \"shift_degree\": 150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"vn_hv_kv\": 10,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 1.18,\n \"sn_mva\": 0.63,\n \"i0_percent\": 0.1873,\n \"tap_min\": -2,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.0794,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 0.4,\n \"tap_neutral\": 0\n },\n \"40 MVA 110/10 kV\": {\n \"tap_max\": 9,\n \"vector_group\": \"YNd5\",\n \"shift_degree\": 150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"vn_hv_kv\": 110,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 18,\n \"sn_mva\": 40,\n \"i0_percent\": 0.05,\n \"tap_min\": -9,\n \"vk_percent\": 16.2,\n \"vkr_percent\": 0.34,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 10,\n \"tap_neutral\": 0\n },\n \"0.4 MVA 20/0.4 kV\": {\n \"tap_max\": 2,\n \"vector_group\": \"Dyn5\",\n \"shift_degree\": 150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"vn_hv_kv\": 20,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 1.35,\n \"sn_mva\": 0.4,\n \"i0_percent\": 0.3375,\n \"tap_min\": -2,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.425,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 0.4,\n \"tap_neutral\": 0\n },\n \"40 MVA 110/20 kV\": {\n \"tap_max\": 9,\n \"vector_group\": \"YNd5\",\n \"shift_degree\": 150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"i0_percent\": 0.05,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 18,\n \"sn_mva\": 40,\n \"vn_hv_kv\": 110.0,\n \"tap_min\": -9,\n \"vk_percent\": 16.2,\n \"vkr_percent\": 0.34,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 20.0,\n \"tap_neutral\": 0\n },\n \"160 MVA 380/110 kV\": {\n \"tap_max\": 9,\n \"vector_group\": \"Yy0\",\n \"shift_degree\": 0,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"i0_percent\": 0.06,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 60,\n \"sn_mva\": 160,\n \"vn_hv_kv\": 380.0,\n \"tap_min\": -9,\n \"vk_percent\": 12.2,\n \"vkr_percent\": 0.25,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 110.0,\n \"tap_neutral\": 0\n },\n \"0.4 MVA 10/0.4 kV\": {\n \"tap_max\": 2,\n \"vector_group\": \"Dyn5\",\n \"shift_degree\": 150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"vn_hv_kv\": 10,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 0.95,\n \"sn_mva\": 0.4,\n \"i0_percent\": 0.2375,\n \"tap_min\": -2,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.325,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 0.4,\n \"tap_neutral\": 0\n },\n \"0.25 MVA 10/0.4 kV\": {\n \"tap_max\": 2,\n \"vector_group\": \"Dyn5\",\n \"shift_degree\": 150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"vn_hv_kv\": 10,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 0.6,\n \"sn_mva\": 0.25,\n \"i0_percent\": 0.24,\n \"tap_min\": -2,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.2,\n \"tap_phase_shifter\": false,\n \"vn_lv_kv\": 0.4,\n \"tap_neutral\": 0\n }\n },\n \"line\": {\n \"70-AL1/11-ST1A 20.0\": {\n \"x_ohm_per_km\": 0.36,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.4132,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 9.7,\n \"q_mm2\": 70,\n \"max_i_ka\": 0.29\n },\n \"48-AL1/8-ST1A 20.0\": {\n \"x_ohm_per_km\": 0.372,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.5939,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 9.5,\n \"q_mm2\": 48,\n \"max_i_ka\": 0.21\n },\n \"149-AL1/24-ST1A 110.0\": {\n \"x_ohm_per_km\": 0.41,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.194,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 8.75,\n \"q_mm2\": 149,\n \"max_i_ka\": 0.47\n },\n \"N2XS(FL)2Y 1x240 RM/35 64/110 kV\": {\n \"x_ohm_per_km\": 0.149,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.075,\n \"alpha\": 0.00393,\n \"c_nf_per_km\": 135,\n \"q_mm2\": 240,\n \"max_i_ka\": 0.526\n },\n \"490-AL1/64-ST1A 220.0\": {\n \"x_ohm_per_km\": 0.285,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.059,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 10,\n \"q_mm2\": 490,\n \"max_i_ka\": 0.96\n },\n \"94-AL1/15-ST1A 0.4\": {\n \"x_ohm_per_km\": 0.29,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.306,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 13.2,\n \"q_mm2\": 94,\n \"max_i_ka\": 0.35\n },\n \"243-AL1/39-ST1A 20.0\": {\n \"x_ohm_per_km\": 0.32,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.1188,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 11,\n \"q_mm2\": 243,\n \"max_i_ka\": 0.645\n },\n \"94-AL1/15-ST1A 10.0\": {\n \"x_ohm_per_km\": 0.33,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.306,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 10.75,\n \"q_mm2\": 94,\n \"max_i_ka\": 0.35\n },\n \"490-AL1/64-ST1A 380.0\": {\n \"x_ohm_per_km\": 0.253,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.059,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 11,\n \"q_mm2\": 490,\n \"max_i_ka\": 0.96\n },\n \"NA2XS2Y 1x95 RM/25 12/20 kV\": {\n \"x_ohm_per_km\": 0.132,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.313,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 216,\n \"q_mm2\": 95,\n \"max_i_ka\": 0.252\n },\n \"NA2XS2Y 1x185 RM/25 6/10 kV\": {\n \"x_ohm_per_km\": 0.11,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.161,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 406,\n \"q_mm2\": 185,\n \"max_i_ka\": 0.358\n },\n \"NAYY 4x120 SE\": {\n \"x_ohm_per_km\": 0.08,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.225,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 264,\n \"q_mm2\": 120,\n \"max_i_ka\": 0.242\n },\n \"NA2XS2Y 1x185 RM/25 12/20 kV\": {\n \"x_ohm_per_km\": 0.117,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.161,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 273,\n \"q_mm2\": 185,\n \"max_i_ka\": 0.362\n },\n \"122-AL1/20-ST1A 20.0\": {\n \"x_ohm_per_km\": 0.344,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.2376,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 10.3,\n \"q_mm2\": 122,\n \"max_i_ka\": 0.41\n },\n \"NA2XS2Y 1x95 RM/25 6/10 kV\": {\n \"x_ohm_per_km\": 0.123,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.313,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 315,\n \"q_mm2\": 95,\n \"max_i_ka\": 0.249\n },\n \"NA2XS2Y 1x240 RM/25 6/10 kV\": {\n \"x_ohm_per_km\": 0.105,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.122,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 456,\n \"q_mm2\": 240,\n \"max_i_ka\": 0.416\n },\n \"184-AL1/30-ST1A 20.0\": {\n \"x_ohm_per_km\": 0.33,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.1571,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 10.75,\n \"q_mm2\": 184,\n \"max_i_ka\": 0.535\n },\n \"149-AL1/24-ST1A 20.0\": {\n \"x_ohm_per_km\": 0.337,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.194,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 10.5,\n \"q_mm2\": 149,\n \"max_i_ka\": 0.47\n },\n \"NA2XS2Y 1x70 RM/25 12/20 kV\": {\n \"x_ohm_per_km\": 0.132,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.443,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 190,\n \"q_mm2\": 70,\n \"max_i_ka\": 0.22\n },\n \"NA2XS2Y 1x120 RM/25 6/10 kV\": {\n \"x_ohm_per_km\": 0.113,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.253,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 340,\n \"q_mm2\": 120,\n \"max_i_ka\": 0.28\n },\n \"NA2XS2Y 1x150 RM/25 12/20 kV\": {\n \"x_ohm_per_km\": 0.116,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.206,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 250,\n \"q_mm2\": 150,\n \"max_i_ka\": 0.319\n },\n \"70-AL1/11-ST1A 10.0\": {\n \"x_ohm_per_km\": 0.339,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.4132,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 10.4,\n \"q_mm2\": 70,\n \"max_i_ka\": 0.29\n },\n \"48-AL1/8-ST1A 0.4\": {\n \"x_ohm_per_km\": 0.3,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.5939,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 12.2,\n \"q_mm2\": 48,\n \"max_i_ka\": 0.21\n },\n \"N2XS(FL)2Y 1x300 RM/35 64/110 kV\": {\n \"x_ohm_per_km\": 0.144,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.06,\n \"alpha\": 0.00393,\n \"c_nf_per_km\": 144,\n \"q_mm2\": 300,\n \"max_i_ka\": 0.588\n },\n \"34-AL1/6-ST1A 10.0\": {\n \"x_ohm_per_km\": 0.36,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.8342,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 9.7,\n \"q_mm2\": 34,\n \"max_i_ka\": 0.17\n },\n \"N2XS(FL)2Y 1x185 RM/35 64/110 kV\": {\n \"x_ohm_per_km\": 0.156,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.099,\n \"alpha\": 0.00393,\n \"c_nf_per_km\": 125,\n \"q_mm2\": 185,\n \"max_i_ka\": 0.457\n },\n \"NA2XS2Y 1x70 RM/25 6/10 kV\": {\n \"x_ohm_per_km\": 0.123,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.443,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 280,\n \"q_mm2\": 70,\n \"max_i_ka\": 0.217\n },\n \"N2XS(FL)2Y 1x120 RM/35 64/110 kV\": {\n \"x_ohm_per_km\": 0.166,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.153,\n \"alpha\": 0.00393,\n \"c_nf_per_km\": 112,\n \"q_mm2\": 120,\n \"max_i_ka\": 0.366\n },\n \"NAYY 4x150 SE\": {\n \"x_ohm_per_km\": 0.08,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.208,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 261,\n \"q_mm2\": 150,\n \"max_i_ka\": 0.27\n },\n \"94-AL1/15-ST1A 20.0\": {\n \"x_ohm_per_km\": 0.35,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.306,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 10,\n \"q_mm2\": 94,\n \"max_i_ka\": 0.35\n },\n \"NA2XS2Y 1x150 RM/25 6/10 kV\": {\n \"x_ohm_per_km\": 0.11,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.206,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 360,\n \"q_mm2\": 150,\n \"max_i_ka\": 0.315\n },\n \"NA2XS2Y 1x240 RM/25 12/20 kV\": {\n \"x_ohm_per_km\": 0.112,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.122,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 304,\n \"q_mm2\": 240,\n \"max_i_ka\": 0.421\n },\n \"243-AL1/39-ST1A 110.0\": {\n \"x_ohm_per_km\": 0.39,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.1188,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 9,\n \"q_mm2\": 243,\n \"max_i_ka\": 0.645\n },\n \"15-AL1/3-ST1A 0.4\": {\n \"x_ohm_per_km\": 0.35,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 1.8769,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 11,\n \"q_mm2\": 16,\n \"max_i_ka\": 0.105\n },\n \"NA2XS2Y 1x120 RM/25 12/20 kV\": {\n \"x_ohm_per_km\": 0.119,\n \"type\": \"cs\",\n \"r_ohm_per_km\": 0.253,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 230,\n \"q_mm2\": 120,\n \"max_i_ka\": 0.283\n },\n \"184-AL1/30-ST1A 110.0\": {\n \"x_ohm_per_km\": 0.4,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.1571,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 8.8,\n \"q_mm2\": 184,\n \"max_i_ka\": 0.535\n },\n \"24-AL1/4-ST1A 0.4\": {\n \"x_ohm_per_km\": 0.335,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 1.2012,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 11.25,\n \"q_mm2\": 24,\n \"max_i_ka\": 0.14\n },\n \"305-AL1/39-ST1A 110.0\": {\n \"x_ohm_per_km\": 0.38,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.0949,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 9.2,\n \"q_mm2\": 305,\n \"max_i_ka\": 0.74\n },\n \"122-AL1/20-ST1A 10.0\": {\n \"x_ohm_per_km\": 0.323,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.2376,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 11.1,\n \"q_mm2\": 122,\n \"max_i_ka\": 0.41\n },\n \"149-AL1/24-ST1A 10.0\": {\n \"x_ohm_per_km\": 0.315,\n \"type\": \"ol\",\n \"r_ohm_per_km\": 0.194,\n \"alpha\": 0.00403,\n \"c_nf_per_km\": 11.25,\n \"q_mm2\": 149,\n \"max_i_ka\": 0.47\n },\n \"34-AL1/6-ST1A 20.0\": {\n \"x_ohm_per_km\": 0.382,\n 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150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"vn_hv_kv\": 110,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 22,\n \"sn_mva\": 63,\n \"i0_percent\": 0.04,\n \"tap_min\": -9,\n \"vk_percent\": 18,\n \"vkr_percent\": 0.32,\n \"tap_phase_shifter_type\": 0,\n \"vn_lv_kv\": 10,\n \"tap_neutral\": 0\n },\n \"63 MVA 110/20 kV\": {\n \"tap_max\": 9,\n \"vector_group\": \"YNd5\",\n \"shift_degree\": 150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"i0_percent\": 0.04,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 22,\n \"sn_mva\": 63,\n \"vn_hv_kv\": 110.0,\n \"tap_min\": -9,\n \"vk_percent\": 18,\n \"vkr_percent\": 0.32,\n \"tap_phase_shifter_type\": 0,\n \"vn_lv_kv\": 20.0,\n \"tap_neutral\": 0\n },\n \"25 MVA 110/10 kV\": {\n \"tap_max\": 9,\n \"vector_group\": \"YNd5\",\n \"shift_degree\": 150,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"vn_hv_kv\": 110,\n \"tap_side\": \"hv\",\n \"pfe_kw\": 14,\n \"sn_mva\": 25,\n \"i0_percent\": 0.07,\n \"tap_min\": -9,\n 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\"float64\",\n \"vkr_lv_percent\": \"float64\",\n \"std_type\": \"object\",\n \"name\": \"object\",\n \"i0_percent\": \"float64\",\n \"vkr_hv_percent\": \"float64\",\n \"vkr_mv_percent\": \"float64\",\n \"vn_lv_kv\": \"float64\",\n \"in_service\": \"bool\",\n \"tap_max\": \"int32\",\n \"vk_hv_percent\": \"float64\",\n \"tap_step_degree\": \"float64\",\n \"tap_neutral\": \"int32\",\n \"sn_lv_mva\": \"float64\",\n \"mv_bus\": \"uint32\",\n \"tap_side\": \"object\",\n \"vn_mv_kv\": \"float64\",\n \"vk_lv_percent\": \"float64\",\n \"vn_hv_kv\": \"float64\",\n \"tap_min\": \"int32\",\n \"lv_bus\": \"uint32\",\n \"shift_mv_degree\": \"float64\",\n \"sn_mv_mva\": \"float64\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": 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4\\\",380.0,\\\"n\\\",null,true],[\\\"Single Busbar\\\",110.0,\\\"b\\\",null,true],[\\\"Bus SB 1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 3\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 4\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 5\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T1.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T1.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T2.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T2.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T3.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T3.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T4.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T4.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T5.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T5.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV3\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV4\\\",110.0,\\\"n\\\",null,true],[\\\"Bus MV0 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0.27,\n \"type\": \"cs\",\n \"q_mm2\": 150,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x95 RM/25 12/20 kV\": {\n \"c_nf_per_km\": 216,\n \"r_ohm_per_km\": 0.313,\n \"x_ohm_per_km\": 0.132,\n \"max_i_ka\": 0.252,\n \"type\": \"cs\",\n \"q_mm2\": 95,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x185 RM/25 12/20 kV\": {\n \"c_nf_per_km\": 273,\n \"r_ohm_per_km\": 0.161,\n \"x_ohm_per_km\": 0.117,\n \"max_i_ka\": 0.362,\n \"type\": \"cs\",\n \"q_mm2\": 185,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x240 RM/25 12/20 kV\": {\n \"c_nf_per_km\": 304,\n \"r_ohm_per_km\": 0.122,\n \"x_ohm_per_km\": 0.112,\n \"max_i_ka\": 0.421,\n \"type\": \"cs\",\n \"q_mm2\": 240,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x95 RM/25 6/10 kV\": {\n \"c_nf_per_km\": 315,\n \"r_ohm_per_km\": 0.313,\n \"x_ohm_per_km\": 0.123,\n \"max_i_ka\": 0.249,\n \"type\": \"cs\",\n \"q_mm2\": 95,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x185 RM/25 6/10 kV\": {\n \"c_nf_per_km\": 406,\n \"r_ohm_per_km\": 0.161,\n \"x_ohm_per_km\": 0.11,\n \"max_i_ka\": 0.358,\n \"type\": \"cs\",\n \"q_mm2\": 185,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x240 RM/25 6/10 kV\": {\n \"c_nf_per_km\": 456,\n \"r_ohm_per_km\": 0.122,\n \"x_ohm_per_km\": 0.105,\n \"max_i_ka\": 0.416,\n \"type\": \"cs\",\n \"q_mm2\": 240,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x150 RM/25 12/20 kV\": {\n \"c_nf_per_km\": 250,\n \"r_ohm_per_km\": 0.206,\n \"x_ohm_per_km\": 0.116,\n \"max_i_ka\": 0.319,\n \"type\": \"cs\",\n \"q_mm2\": 150,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x120 RM/25 12/20 kV\": {\n \"c_nf_per_km\": 230,\n \"r_ohm_per_km\": 0.253,\n \"x_ohm_per_km\": 0.119,\n \"max_i_ka\": 0.283,\n \"type\": \"cs\",\n \"q_mm2\": 120,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x70 RM/25 12/20 kV\": {\n \"c_nf_per_km\": 190,\n \"r_ohm_per_km\": 0.443,\n \"x_ohm_per_km\": 0.132,\n \"max_i_ka\": 0.22,\n \"type\": \"cs\",\n \"q_mm2\": 70,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x150 RM/25 6/10 kV\": {\n \"c_nf_per_km\": 360,\n \"r_ohm_per_km\": 0.206,\n \"x_ohm_per_km\": 0.11,\n \"max_i_ka\": 0.315,\n \"type\": \"cs\",\n \"q_mm2\": 150,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x120 RM/25 6/10 kV\": {\n \"c_nf_per_km\": 340,\n \"r_ohm_per_km\": 0.253,\n \"x_ohm_per_km\": 0.113,\n \"max_i_ka\": 0.28,\n \"type\": \"cs\",\n \"q_mm2\": 120,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x70 RM/25 6/10 kV\": {\n \"c_nf_per_km\": 280,\n \"r_ohm_per_km\": 0.443,\n \"x_ohm_per_km\": 0.123,\n \"max_i_ka\": 0.217,\n \"type\": \"cs\",\n \"q_mm2\": 70,\n \"alpha\": 0.00403\n },\n \"N2XS(FL)2Y 1x120 RM/35 64/110 kV\": {\n \"c_nf_per_km\": 112,\n \"r_ohm_per_km\": 0.153,\n \"x_ohm_per_km\": 0.166,\n \"max_i_ka\": 0.366,\n \"type\": \"cs\",\n \"q_mm2\": 120,\n \"alpha\": 0.00393\n },\n \"N2XS(FL)2Y 1x185 RM/35 64/110 kV\": {\n \"c_nf_per_km\": 125,\n \"r_ohm_per_km\": 0.099,\n \"x_ohm_per_km\": 0.156,\n \"max_i_ka\": 0.457,\n \"type\": \"cs\",\n \"q_mm2\": 185,\n \"alpha\": 0.00393\n },\n \"N2XS(FL)2Y 1x240 RM/35 64/110 kV\": {\n \"c_nf_per_km\": 135,\n \"r_ohm_per_km\": 0.075,\n \"x_ohm_per_km\": 0.149,\n \"max_i_ka\": 0.526,\n \"type\": \"cs\",\n \"q_mm2\": 240,\n \"alpha\": 0.00393\n },\n \"N2XS(FL)2Y 1x300 RM/35 64/110 kV\": {\n \"c_nf_per_km\": 144,\n \"r_ohm_per_km\": 0.06,\n \"x_ohm_per_km\": 0.144,\n \"max_i_ka\": 0.588,\n \"type\": \"cs\",\n \"q_mm2\": 300,\n \"alpha\": 0.00393\n },\n \"15-AL1/3-ST1A 0.4\": {\n \"c_nf_per_km\": 11,\n \"r_ohm_per_km\": 1.8769,\n \"x_ohm_per_km\": 0.35,\n \"max_i_ka\": 0.105,\n \"type\": \"ol\",\n \"q_mm2\": 16,\n \"alpha\": 0.00403\n },\n \"24-AL1/4-ST1A 0.4\": {\n \"c_nf_per_km\": 11.25,\n \"r_ohm_per_km\": 1.2012,\n \"x_ohm_per_km\": 0.335,\n \"max_i_ka\": 0.14,\n \"type\": \"ol\",\n \"q_mm2\": 24,\n \"alpha\": 0.00403\n },\n \"48-AL1/8-ST1A 0.4\": {\n \"c_nf_per_km\": 12.2,\n \"r_ohm_per_km\": 0.5939,\n \"x_ohm_per_km\": 0.3,\n \"max_i_ka\": 0.21,\n \"type\": \"ol\",\n \"q_mm2\": 48,\n \"alpha\": 0.00403\n },\n \"94-AL1/15-ST1A 0.4\": {\n \"c_nf_per_km\": 13.2,\n \"r_ohm_per_km\": 0.306,\n \"x_ohm_per_km\": 0.29,\n \"max_i_ka\": 0.35,\n \"type\": \"ol\",\n \"q_mm2\": 94,\n \"alpha\": 0.00403\n },\n \"34-AL1/6-ST1A 10.0\": {\n \"c_nf_per_km\": 9.7,\n \"r_ohm_per_km\": 0.8342,\n \"x_ohm_per_km\": 0.36,\n \"max_i_ka\": 0.17,\n \"type\": \"ol\",\n \"q_mm2\": 34,\n \"alpha\": 0.00403\n },\n \"48-AL1/8-ST1A 10.0\": {\n \"c_nf_per_km\": 10.1,\n \"r_ohm_per_km\": 0.5939,\n \"x_ohm_per_km\": 0.35,\n \"max_i_ka\": 0.21,\n \"type\": \"ol\",\n \"q_mm2\": 48,\n \"alpha\": 0.00403\n },\n \"70-AL1/11-ST1A 10.0\": {\n \"c_nf_per_km\": 10.4,\n \"r_ohm_per_km\": 0.4132,\n \"x_ohm_per_km\": 0.339,\n \"max_i_ka\": 0.29,\n \"type\": \"ol\",\n \"q_mm2\": 70,\n \"alpha\": 0.00403\n },\n \"94-AL1/15-ST1A 10.0\": {\n \"c_nf_per_km\": 10.75,\n \"r_ohm_per_km\": 0.306,\n \"x_ohm_per_km\": 0.33,\n \"max_i_ka\": 0.35,\n \"type\": \"ol\",\n \"q_mm2\": 94,\n \"alpha\": 0.00403\n },\n \"122-AL1/20-ST1A 10.0\": {\n \"c_nf_per_km\": 11.1,\n \"r_ohm_per_km\": 0.2376,\n \"x_ohm_per_km\": 0.323,\n \"max_i_ka\": 0.41,\n \"type\": \"ol\",\n \"q_mm2\": 122,\n \"alpha\": 0.00403\n },\n \"149-AL1/24-ST1A 10.0\": {\n \"c_nf_per_km\": 11.25,\n \"r_ohm_per_km\": 0.194,\n \"x_ohm_per_km\": 0.315,\n \"max_i_ka\": 0.47,\n \"type\": \"ol\",\n \"q_mm2\": 149,\n \"alpha\": 0.00403\n },\n \"34-AL1/6-ST1A 20.0\": {\n \"c_nf_per_km\": 9.15,\n \"r_ohm_per_km\": 0.8342,\n \"x_ohm_per_km\": 0.382,\n \"max_i_ka\": 0.17,\n \"type\": \"ol\",\n \"q_mm2\": 34,\n \"alpha\": 0.00403\n },\n \"48-AL1/8-ST1A 20.0\": {\n \"c_nf_per_km\": 9.5,\n \"r_ohm_per_km\": 0.5939,\n \"x_ohm_per_km\": 0.372,\n \"max_i_ka\": 0.21,\n \"type\": \"ol\",\n \"q_mm2\": 48,\n \"alpha\": 0.00403\n },\n \"70-AL1/11-ST1A 20.0\": {\n \"c_nf_per_km\": 9.7,\n \"r_ohm_per_km\": 0.4132,\n \"x_ohm_per_km\": 0.36,\n \"max_i_ka\": 0.29,\n \"type\": \"ol\",\n \"q_mm2\": 70,\n \"alpha\": 0.00403\n },\n \"94-AL1/15-ST1A 20.0\": {\n \"c_nf_per_km\": 10,\n \"r_ohm_per_km\": 0.306,\n \"x_ohm_per_km\": 0.35,\n \"max_i_ka\": 0.35,\n \"type\": \"ol\",\n \"q_mm2\": 94,\n \"alpha\": 0.00403\n },\n \"122-AL1/20-ST1A 20.0\": {\n \"c_nf_per_km\": 10.3,\n \"r_ohm_per_km\": 0.2376,\n \"x_ohm_per_km\": 0.344,\n \"max_i_ka\": 0.41,\n \"type\": \"ol\",\n \"q_mm2\": 122,\n \"alpha\": 0.00403\n },\n \"149-AL1/24-ST1A 20.0\": {\n \"c_nf_per_km\": 10.5,\n \"r_ohm_per_km\": 0.194,\n \"x_ohm_per_km\": 0.337,\n \"max_i_ka\": 0.47,\n \"type\": \"ol\",\n \"q_mm2\": 149,\n \"alpha\": 0.00403\n },\n \"184-AL1/30-ST1A 20.0\": {\n \"c_nf_per_km\": 10.75,\n \"r_ohm_per_km\": 0.1571,\n \"x_ohm_per_km\": 0.33,\n \"max_i_ka\": 0.535,\n \"type\": \"ol\",\n \"q_mm2\": 184,\n \"alpha\": 0.00403\n },\n \"243-AL1/39-ST1A 20.0\": {\n \"c_nf_per_km\": 11,\n \"r_ohm_per_km\": 0.1188,\n \"x_ohm_per_km\": 0.32,\n \"max_i_ka\": 0.645,\n \"type\": \"ol\",\n \"q_mm2\": 243,\n \"alpha\": 0.00403\n },\n \"149-AL1/24-ST1A 110.0\": {\n \"c_nf_per_km\": 8.75,\n \"r_ohm_per_km\": 0.194,\n \"x_ohm_per_km\": 0.41,\n \"max_i_ka\": 0.47,\n \"type\": \"ol\",\n \"q_mm2\": 149,\n \"alpha\": 0.00403\n },\n \"184-AL1/30-ST1A 110.0\": {\n \"c_nf_per_km\": 8.8,\n \"r_ohm_per_km\": 0.1571,\n \"x_ohm_per_km\": 0.4,\n \"max_i_ka\": 0.535,\n \"type\": \"ol\",\n \"q_mm2\": 184,\n \"alpha\": 0.00403\n },\n \"243-AL1/39-ST1A 110.0\": {\n \"c_nf_per_km\": 9,\n \"r_ohm_per_km\": 0.1188,\n \"x_ohm_per_km\": 0.39,\n \"max_i_ka\": 0.645,\n \"type\": \"ol\",\n \"q_mm2\": 243,\n \"alpha\": 0.00403\n },\n \"305-AL1/39-ST1A 110.0\": {\n \"c_nf_per_km\": 9.2,\n \"r_ohm_per_km\": 0.0949,\n \"x_ohm_per_km\": 0.38,\n \"max_i_ka\": 0.74,\n \"type\": \"ol\",\n \"q_mm2\": 305,\n \"alpha\": 0.00403\n },\n \"490-AL1/64-ST1A 220.0\": {\n \"c_nf_per_km\": 10,\n \"r_ohm_per_km\": 0.059,\n \"x_ohm_per_km\": 0.285,\n \"max_i_ka\": 0.96,\n \"type\": \"ol\",\n \"q_mm2\": 490,\n \"alpha\": 0.00403\n },\n \"490-AL1/64-ST1A 380.0\": {\n \"c_nf_per_km\": 11,\n \"r_ohm_per_km\": 0.059,\n \"x_ohm_per_km\": 0.253,\n \"max_i_ka\": 0.96,\n \"type\": \"ol\",\n \"q_mm2\": 490,\n \"alpha\": 0.00403\n }\n },\n \"trafo\": {\n \"160 MVA 380/110 kV\": {\n \"i0_percent\": 0.06,\n \"pfe_kw\": 60,\n \"vkr_percent\": 0.25,\n \"sn_mva\": 160,\n \"vn_lv_kv\": 110.0,\n \"vn_hv_kv\": 380.0,\n \"vk_percent\": 12.2,\n \"shift_degree\": 0,\n \"vector_group\": \"Yy0\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter\": false\n },\n \"100 MVA 220/110 kV\": {\n \"i0_percent\": 0.06,\n \"pfe_kw\": 55,\n \"vkr_percent\": 0.26,\n \"sn_mva\": 100,\n \"vn_lv_kv\": 110.0,\n \"vn_hv_kv\": 220.0,\n \"vk_percent\": 12.0,\n \"shift_degree\": 0,\n \"vector_group\": \"Yy0\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter\": false\n },\n \"63 MVA 110/20 kV\": {\n \"i0_percent\": 0.04,\n \"pfe_kw\": 22,\n \"vkr_percent\": 0.32,\n \"sn_mva\": 63,\n \"vn_lv_kv\": 20.0,\n \"vn_hv_kv\": 110.0,\n \"vk_percent\": 18,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter\": false\n },\n \"40 MVA 110/20 kV\": {\n \"i0_percent\": 0.05,\n \"pfe_kw\": 18,\n \"vkr_percent\": 0.34,\n \"sn_mva\": 40,\n \"vn_lv_kv\": 20.0,\n \"vn_hv_kv\": 110.0,\n \"vk_percent\": 16.2,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter\": false\n },\n \"25 MVA 110/20 kV\": {\n \"i0_percent\": 0.07,\n \"pfe_kw\": 14,\n \"vkr_percent\": 0.41,\n \"sn_mva\": 25,\n \"vn_lv_kv\": 20.0,\n \"vn_hv_kv\": 110.0,\n \"vk_percent\": 12,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter\": false\n },\n \"63 MVA 110/10 kV\": {\n \"sn_mva\": 63,\n \"vn_hv_kv\": 110,\n \"vn_lv_kv\": 10,\n \"vk_percent\": 18,\n \"vkr_percent\": 0.32,\n \"pfe_kw\": 22,\n \"i0_percent\": 0.04,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter\": false\n },\n \"40 MVA 110/10 kV\": {\n \"sn_mva\": 40,\n \"vn_hv_kv\": 110,\n \"vn_lv_kv\": 10,\n \"vk_percent\": 16.2,\n \"vkr_percent\": 0.34,\n \"pfe_kw\": 18,\n \"i0_percent\": 0.05,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter\": false\n },\n \"25 MVA 110/10 kV\": {\n \"sn_mva\": 25,\n \"vn_hv_kv\": 110,\n \"vn_lv_kv\": 10,\n \"vk_percent\": 12,\n \"vkr_percent\": 0.41,\n \"pfe_kw\": 14,\n \"i0_percent\": 0.07,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter\": false\n },\n \"0.25 MVA 20/0.4 kV\": {\n \"sn_mva\": 0.25,\n \"vn_hv_kv\": 20,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.44,\n \"pfe_kw\": 0.8,\n \"i0_percent\": 0.32,\n \"shift_degree\": 150,\n \"vector_group\": \"Yzn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter\": false\n },\n \"0.4 MVA 20/0.4 kV\": {\n \"sn_mva\": 0.4,\n \"vn_hv_kv\": 20,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.425,\n \"pfe_kw\": 1.35,\n \"i0_percent\": 0.3375,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter\": false\n },\n \"0.63 MVA 20/0.4 kV\": {\n \"sn_mva\": 0.63,\n \"vn_hv_kv\": 20,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.206,\n \"pfe_kw\": 1.65,\n \"i0_percent\": 0.2619,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter\": false\n },\n \"0.25 MVA 10/0.4 kV\": {\n \"sn_mva\": 0.25,\n \"vn_hv_kv\": 10,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.2,\n \"pfe_kw\": 0.6,\n \"i0_percent\": 0.24,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter\": false\n },\n \"0.4 MVA 10/0.4 kV\": {\n \"sn_mva\": 0.4,\n \"vn_hv_kv\": 10,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.325,\n \"pfe_kw\": 0.95,\n \"i0_percent\": 0.2375,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter\": false\n },\n \"0.63 MVA 10/0.4 kV\": {\n \"sn_mva\": 0.63,\n \"vn_hv_kv\": 10,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.0794,\n \"pfe_kw\": 1.18,\n \"i0_percent\": 0.1873,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter\": false\n }\n },\n \"trafo3w\": {\n \"63/25/38 MVA 110/20/10 kV\": {\n \"sn_hv_mva\": 63,\n \"sn_mv_mva\": 25,\n \"sn_lv_mva\": 38,\n \"vn_hv_kv\": 110,\n \"vn_mv_kv\": 20,\n \"vn_lv_kv\": 10,\n \"vk_hv_percent\": 10.4,\n \"vk_mv_percent\": 10.4,\n \"vk_lv_percent\": 10.4,\n 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\"tap_step_percent\": 1.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"63 MVA 110/10 kV\": {\n \"sn_mva\": 63,\n \"vn_hv_kv\": 110,\n \"vn_lv_kv\": 10,\n \"vk_percent\": 18,\n \"vkr_percent\": 0.32,\n \"pfe_kw\": 22,\n \"i0_percent\": 0.04,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"40 MVA 110/10 kV\": {\n \"sn_mva\": 40,\n \"vn_hv_kv\": 110,\n \"vn_lv_kv\": 10,\n \"vk_percent\": 16.2,\n \"vkr_percent\": 0.34,\n \"pfe_kw\": 18,\n \"i0_percent\": 0.05,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"25 MVA 110/10 kV\": {\n \"sn_mva\": 25,\n \"vn_hv_kv\": 110,\n \"vn_lv_kv\": 10,\n \"vk_percent\": 12,\n \"vkr_percent\": 0.41,\n \"pfe_kw\": 14,\n \"i0_percent\": 0.07,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"0.25 MVA 20/0.4 kV\": {\n \"sn_mva\": 0.25,\n \"vn_hv_kv\": 20,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.44,\n \"pfe_kw\": 0.8,\n \"i0_percent\": 0.32,\n \"shift_degree\": 150,\n \"vector_group\": \"Yzn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"0.4 MVA 20/0.4 kV\": {\n \"sn_mva\": 0.4,\n \"vn_hv_kv\": 20,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.425,\n \"pfe_kw\": 1.35,\n \"i0_percent\": 0.3375,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"0.63 MVA 20/0.4 kV\": {\n \"sn_mva\": 0.63,\n \"vn_hv_kv\": 20,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.206,\n \"pfe_kw\": 1.65,\n \"i0_percent\": 0.2619,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"0.25 MVA 10/0.4 kV\": {\n \"sn_mva\": 0.25,\n \"vn_hv_kv\": 10,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.2,\n \"pfe_kw\": 0.6,\n \"i0_percent\": 0.24,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"0.4 MVA 10/0.4 kV\": {\n \"sn_mva\": 0.4,\n \"vn_hv_kv\": 10,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.325,\n \"pfe_kw\": 0.95,\n \"i0_percent\": 0.2375,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"0.63 MVA 10/0.4 kV\": {\n \"sn_mva\": 0.63,\n \"vn_hv_kv\": 10,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.0794,\n \"pfe_kw\": 1.18,\n \"i0_percent\": 0.1873,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter_type\": 0,\n }\n },\n \"trafo3w\": {\n \"63/25/38 MVA 110/20/10 kV\": {\n \"sn_hv_mva\": 63,\n \"sn_mv_mva\": 25,\n \"sn_lv_mva\": 38,\n \"vn_hv_kv\": 110,\n \"vn_mv_kv\": 20,\n \"vn_lv_kv\": 10,\n \"vk_hv_percent\": 10.4,\n \"vk_mv_percent\": 10.4,\n 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\"{\\\"columns\\\":[\\\"name\\\",\\\"std_type\\\",\\\"hv_bus\\\",\\\"mv_bus\\\",\\\"lv_bus\\\",\\\"sn_hv_mva\\\",\\\"sn_mv_mva\\\",\\\"sn_lv_mva\\\",\\\"vn_hv_kv\\\",\\\"vn_mv_kv\\\",\\\"vn_lv_kv\\\",\\\"vk_hv_percent\\\",\\\"vk_mv_percent\\\",\\\"vk_lv_percent\\\",\\\"vkr_hv_percent\\\",\\\"vkr_mv_percent\\\",\\\"vkr_lv_percent\\\",\\\"pfe_kw\\\",\\\"i0_percent\\\",\\\"shift_mv_degree\\\",\\\"shift_lv_degree\\\",\\\"tap_side\\\",\\\"tap_neutral\\\",\\\"tap_min\\\",\\\"tap_max\\\",\\\"tap_step_percent\\\",\\\"tap_step_degree\\\",\\\"tap_pos\\\",\\\"tap_at_star_point\\\",\\\"in_service\\\"],\\\"index\\\":[0],\\\"data\\\":[[\\\"HV-MV-MV-Trafo\\\",null,33,36,37,40.0,15.0,25.0,110.0,20.0,10.0,10.1,10.1,10.1,0.266667,0.033333,0.04,0.0,0.0,30.0,30.0,\\\"hv\\\",0,-8,8,1.25,null,0,false,true]]}\",\n \"dtype\": {\n \"name\": \"object\",\n \"std_type\": \"object\",\n \"hv_bus\": \"uint32\",\n \"mv_bus\": \"uint32\",\n \"lv_bus\": \"uint32\",\n \"sn_hv_mva\": \"float64\",\n \"sn_mv_mva\": \"float64\",\n \"sn_lv_mva\": \"float64\",\n \"vn_hv_kv\": \"float64\",\n \"vn_mv_kv\": \"float64\",\n \"vn_lv_kv\": \"float64\",\n \"vk_hv_percent\": \"float64\",\n \"vk_mv_percent\": \"float64\",\n \"vk_lv_percent\": \"float64\",\n \"vkr_hv_percent\": \"float64\",\n \"vkr_mv_percent\": \"float64\",\n \"vkr_lv_percent\": \"float64\",\n \"pfe_kw\": \"float64\",\n \"i0_percent\": \"float64\",\n \"shift_mv_degree\": \"float64\",\n \"shift_lv_degree\": \"float64\",\n \"tap_side\": \"object\",\n \"tap_neutral\": \"int32\",\n \"tap_min\": \"int32\",\n \"tap_max\": \"int32\",\n \"tap_step_percent\": \"float64\",\n \"tap_step_degree\": \"float64\",\n \"tap_pos\": \"int32\",\n \"tap_at_star_point\": \"bool\",\n \"in_service\": \"bool\"\n },\n \"orient\": \"split\"\n},\"user_pf_options\":{},\"version\":\"2.0.1\",\"ward\":{\n \"_module\": \"pandas.core.frame\",\n \"_class\": \"DataFrame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"bus\\\",\\\"ps_mw\\\",\\\"qs_mvar\\\",\\\"qz_mvar\\\",\\\"pz_mw\\\",\\\"in_service\\\"],\\\"index\\\":[],\\\"data\\\":[]}\",\n \"dtype\": {\n \"name\": \"object\",\n \"bus\": \"uint32\",\n \"ps_mw\": \"float64\",\n \"qs_mvar\": \"float64\",\n \"qz_mvar\": \"float64\",\n \"pz_mw\": \"float64\",\n \"in_service\": \"bool\"\n },\n \"orient\": \"split\"\n},\"xward\":{\n \"_module\": \"pandas.core.frame\",\n \"_class\": \"DataFrame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"bus\\\",\\\"ps_mw\\\",\\\"qs_mvar\\\",\\\"qz_mvar\\\",\\\"pz_mw\\\",\\\"r_ohm\\\",\\\"x_ohm\\\",\\\"vm_pu\\\",\\\"in_service\\\"],\\\"index\\\":[0,1],\\\"data\\\":[[\\\"XWard 1\\\",34,23.942,-12.24187,0.0,2.814571,0.0,12.18951,1.02616,true],[\\\"XWard 2\\\",32,3.776,-7.769979,0.0,9.174917000000001,0.0,50.562170000000002,1.024001,true]]}\",\n \"dtype\": {\n \"name\": \"object\",\n \"bus\": \"uint32\",\n \"ps_mw\": \"float64\",\n \"qs_mvar\": \"float64\",\n \"qz_mvar\": \"float64\",\n \"pz_mw\": \"float64\",\n \"r_ohm\": \"float64\",\n \"x_ohm\": \"float64\",\n \"vm_pu\": \"float64\",\n \"in_service\": \"bool\"\n },\n \"orient\": \"split\"\n}}\n" } \ No newline at end of file diff --git a/pandapower/test/test_files/old_versions/example_2.1.0.json b/pandapower/test/test_files/old_versions/example_2.1.0.json index c5b94d15d..ab067b8fd 100644 --- a/pandapower/test/test_files/old_versions/example_2.1.0.json +++ b/pandapower/test/test_files/old_versions/example_2.1.0.json @@ -840,7 +840,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -858,7 +858,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -876,7 +876,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -894,7 +894,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -912,7 +912,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -930,7 +930,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -948,7 +948,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -966,7 +966,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -984,7 +984,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1002,7 +1002,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1020,7 +1020,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1038,7 +1038,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1056,7 +1056,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1074,7 +1074,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { @@ -1165,7 +1165,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,\"hv\",0.0,-10.0,10.0,1.25,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,0,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,\"hv\",0.0,-10.0,10.0,1.25,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,0,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -1187,7 +1187,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" diff --git a/pandapower/test/test_files/old_versions/example_2.10.0.json b/pandapower/test/test_files/old_versions/example_2.10.0.json index 90fff4883..4e795e039 100644 --- a/pandapower/test/test_files/old_versions/example_2.10.0.json +++ b/pandapower/test/test_files/old_versions/example_2.10.0.json @@ -226,7 +226,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -248,7 +248,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -943,7 +943,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -961,7 +961,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -979,7 +979,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -997,7 +997,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1015,7 +1015,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1033,7 +1033,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1051,7 +1051,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1069,7 +1069,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1087,7 +1087,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1105,7 +1105,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1123,7 +1123,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1141,7 +1141,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1159,7 +1159,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1177,7 +1177,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.10.1.json b/pandapower/test/test_files/old_versions/example_2.10.1.json index 14197ef07..eb2e20bd6 100644 --- a/pandapower/test/test_files/old_versions/example_2.10.1.json +++ b/pandapower/test/test_files/old_versions/example_2.10.1.json @@ -226,7 +226,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -248,7 +248,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -943,7 +943,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -961,7 +961,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -979,7 +979,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -997,7 +997,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1015,7 +1015,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1033,7 +1033,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1051,7 +1051,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1069,7 +1069,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1087,7 +1087,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1105,7 +1105,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1123,7 +1123,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1141,7 +1141,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1159,7 +1159,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1177,7 +1177,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.11.0.json b/pandapower/test/test_files/old_versions/example_2.11.0.json index 178c0d40d..e0143acb9 100644 --- a/pandapower/test/test_files/old_versions/example_2.11.0.json +++ b/pandapower/test/test_files/old_versions/example_2.11.0.json @@ -226,7 +226,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -248,7 +248,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -956,7 +956,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -974,7 +974,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -992,7 +992,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1010,7 +1010,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1028,7 +1028,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1064,7 +1064,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1082,7 +1082,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1100,7 +1100,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1118,7 +1118,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1136,7 +1136,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1154,7 +1154,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1172,7 +1172,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1190,7 +1190,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.11.1.json b/pandapower/test/test_files/old_versions/example_2.11.1.json index b4d291714..697c8b68f 100644 --- a/pandapower/test/test_files/old_versions/example_2.11.1.json +++ b/pandapower/test/test_files/old_versions/example_2.11.1.json @@ -226,7 +226,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -248,7 +248,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -956,7 +956,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -974,7 +974,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -992,7 +992,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1010,7 +1010,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1028,7 +1028,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1064,7 +1064,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1082,7 +1082,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1100,7 +1100,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1118,7 +1118,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1136,7 +1136,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1154,7 +1154,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1172,7 +1172,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1190,7 +1190,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.12.0.json b/pandapower/test/test_files/old_versions/example_2.12.0.json index b41af38b3..72fe58c2f 100644 --- a/pandapower/test/test_files/old_versions/example_2.12.0.json +++ b/pandapower/test/test_files/old_versions/example_2.12.0.json @@ -269,7 +269,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -291,7 +291,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1064,7 +1064,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1082,7 +1082,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1100,7 +1100,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1118,7 +1118,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1136,7 +1136,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1154,7 +1154,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1172,7 +1172,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1190,7 +1190,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1208,7 +1208,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1226,7 +1226,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1244,7 +1244,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1262,7 +1262,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1280,7 +1280,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.12.1.json b/pandapower/test/test_files/old_versions/example_2.12.1.json index 13d627693..af78c92ae 100644 --- a/pandapower/test/test_files/old_versions/example_2.12.1.json +++ b/pandapower/test/test_files/old_versions/example_2.12.1.json @@ -269,7 +269,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -291,7 +291,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1064,7 +1064,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1082,7 +1082,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1100,7 +1100,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1118,7 +1118,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1136,7 +1136,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1154,7 +1154,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1172,7 +1172,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1190,7 +1190,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1208,7 +1208,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1226,7 +1226,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1244,7 +1244,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1262,7 +1262,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1280,7 +1280,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.13.0.1.json b/pandapower/test/test_files/old_versions/example_2.13.0.1.json index 1dca951db..e072a42c8 100644 --- a/pandapower/test/test_files/old_versions/example_2.13.0.1.json +++ b/pandapower/test/test_files/old_versions/example_2.13.0.1.json @@ -269,7 +269,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"tap_dependent_impedance\",\"vk_percent_characteristic\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,false,null],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,true,0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"tap_characteristic_table\",\"id_characteristic_table\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,false,null],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,true,0]]}", "orient": "split", "dtype": { "name": "object", @@ -291,12 +291,12 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", - "tap_dependent_impedance": "bool", - "vk_percent_characteristic": "Int64" + "tap_characteristic_table": "bool", + "id_characteristic_table": "Int64" }, "is_multiindex": false, "is_multicolumn": false @@ -1048,7 +1048,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1066,7 +1066,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1084,7 +1084,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1102,7 +1102,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1120,7 +1120,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1138,7 +1138,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1156,7 +1156,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1174,7 +1174,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1192,7 +1192,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1210,7 +1210,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1228,7 +1228,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1246,7 +1246,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1264,7 +1264,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1282,7 +1282,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.13.0.json b/pandapower/test/test_files/old_versions/example_2.13.0.json index ac0f0c9d7..2b63d383f 100644 --- a/pandapower/test/test_files/old_versions/example_2.13.0.json +++ b/pandapower/test/test_files/old_versions/example_2.13.0.json @@ -269,7 +269,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -291,7 +291,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1064,7 +1064,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1082,7 +1082,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1100,7 +1100,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1118,7 +1118,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1136,7 +1136,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1154,7 +1154,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1172,7 +1172,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1190,7 +1190,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1208,7 +1208,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1226,7 +1226,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1244,7 +1244,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1262,7 +1262,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1280,7 +1280,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.14.0.json b/pandapower/test/test_files/old_versions/example_2.14.0.json index 817259499..23518736f 100644 --- a/pandapower/test/test_files/old_versions/example_2.14.0.json +++ b/pandapower/test/test_files/old_versions/example_2.14.0.json @@ -288,7 +288,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"tap_dependent_impedance\",\"vk_percent_characteristic\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,false,null],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,true,0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"tap_characteristic_table\",\"id_characteristic_table\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,false,null],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,true,0]]}", "orient": "split", "dtype": { "name": "object", @@ -310,12 +310,12 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", - "tap_dependent_impedance": "bool", - "vk_percent_characteristic": "Int64" + "tap_characteristic_table": "bool", + "id_characteristic_table": "Int64" }, "is_multiindex": false, "is_multicolumn": false @@ -1118,7 +1118,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1136,7 +1136,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1154,7 +1154,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1172,7 +1172,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1190,7 +1190,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1208,7 +1208,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1226,7 +1226,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1244,7 +1244,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1262,7 +1262,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1280,7 +1280,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1298,7 +1298,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1316,7 +1316,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1334,7 +1334,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1352,7 +1352,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.2.0.json b/pandapower/test/test_files/old_versions/example_2.2.0.json index 2991ddb73..4b10e0bb9 100644 --- a/pandapower/test/test_files/old_versions/example_2.2.0.json +++ b/pandapower/test/test_files/old_versions/example_2.2.0.json @@ -160,7 +160,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -182,7 +182,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -858,7 +858,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -876,7 +876,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -894,7 +894,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -912,7 +912,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -930,7 +930,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -948,7 +948,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -966,7 +966,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -984,7 +984,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1002,7 +1002,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1020,7 +1020,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1038,7 +1038,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1056,7 +1056,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1074,7 +1074,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1092,7 +1092,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.3.0.json b/pandapower/test/test_files/old_versions/example_2.3.0.json index 82de727db..46b7e6194 100644 --- a/pandapower/test/test_files/old_versions/example_2.3.0.json +++ b/pandapower/test/test_files/old_versions/example_2.3.0.json @@ -201,7 +201,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -223,7 +223,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -899,7 +899,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -917,7 +917,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -935,7 +935,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -953,7 +953,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -971,7 +971,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -989,7 +989,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1007,7 +1007,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1025,7 +1025,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1043,7 +1043,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1061,7 +1061,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1079,7 +1079,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1097,7 +1097,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1115,7 +1115,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1133,7 +1133,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.3.1.json b/pandapower/test/test_files/old_versions/example_2.3.1.json index 437514f4a..1d2ea9a7c 100644 --- a/pandapower/test/test_files/old_versions/example_2.3.1.json +++ b/pandapower/test/test_files/old_versions/example_2.3.1.json @@ -198,7 +198,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0],\"data\":[[\"transformer\",\"0.25 MVA 10\\/0.4 kV\",0,1,0.25,10.0,0.4,4.0,1.2,0.6,0.24,150.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0],\"data\":[[\"transformer\",\"0.25 MVA 10\\/0.4 kV\",0,1,0.25,10.0,0.4,4.0,1.2,0.6,0.24,150.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -220,7 +220,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -896,7 +896,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -914,7 +914,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -932,7 +932,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -950,7 +950,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -968,7 +968,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -986,7 +986,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1004,7 +1004,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1022,7 +1022,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1040,7 +1040,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1058,7 +1058,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1076,7 +1076,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1094,7 +1094,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1112,7 +1112,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1130,7 +1130,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.4.0.json b/pandapower/test/test_files/old_versions/example_2.4.0.json index 8c601ff17..040364988 100644 --- a/pandapower/test/test_files/old_versions/example_2.4.0.json +++ b/pandapower/test/test_files/old_versions/example_2.4.0.json @@ -222,7 +222,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -244,7 +244,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -920,7 +920,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -938,7 +938,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -956,7 +956,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -974,7 +974,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -992,7 +992,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1010,7 +1010,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1028,7 +1028,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1064,7 +1064,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1082,7 +1082,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1100,7 +1100,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1118,7 +1118,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1136,7 +1136,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1154,7 +1154,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.5.0.json b/pandapower/test/test_files/old_versions/example_2.5.0.json index 5a1e7ea24..a6ff69afe 100644 --- a/pandapower/test/test_files/old_versions/example_2.5.0.json +++ b/pandapower/test/test_files/old_versions/example_2.5.0.json @@ -222,7 +222,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -244,7 +244,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -921,7 +921,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -939,7 +939,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -957,7 +957,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -975,7 +975,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -993,7 +993,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1011,7 +1011,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1029,7 +1029,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1047,7 +1047,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1065,7 +1065,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1083,7 +1083,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1101,7 +1101,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1119,7 +1119,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1137,7 +1137,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1155,7 +1155,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.6.0.json b/pandapower/test/test_files/old_versions/example_2.6.0.json index 77566df8a..c9bd794ef 100644 --- a/pandapower/test/test_files/old_versions/example_2.6.0.json +++ b/pandapower/test/test_files/old_versions/example_2.6.0.json @@ -222,7 +222,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -244,7 +244,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -921,7 +921,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -939,7 +939,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -957,7 +957,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -975,7 +975,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -993,7 +993,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1011,7 +1011,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1029,7 +1029,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1047,7 +1047,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1065,7 +1065,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1083,7 +1083,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1101,7 +1101,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1119,7 +1119,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1137,7 +1137,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1155,7 +1155,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.7.0.json b/pandapower/test/test_files/old_versions/example_2.7.0.json index 6e4210252..f3089a980 100644 --- a/pandapower/test/test_files/old_versions/example_2.7.0.json +++ b/pandapower/test/test_files/old_versions/example_2.7.0.json @@ -223,7 +223,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"pt_percent\",\"oltc\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,null,false],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,null,false]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"pt_percent\",\"oltc\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,null,false],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,null,false]]}", "orient": "split", "dtype": { "name": "object", @@ -245,7 +245,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -931,7 +931,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -949,7 +949,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -967,7 +967,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -985,7 +985,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1003,7 +1003,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1021,7 +1021,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1039,7 +1039,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1057,7 +1057,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1075,7 +1075,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1093,7 +1093,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1111,7 +1111,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1129,7 +1129,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1147,7 +1147,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1165,7 +1165,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.8.0.json b/pandapower/test/test_files/old_versions/example_2.8.0.json index 448d724f9..c8da25aea 100644 --- a/pandapower/test/test_files/old_versions/example_2.8.0.json +++ b/pandapower/test/test_files/old_versions/example_2.8.0.json @@ -225,7 +225,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"pt_percent\",\"oltc\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,null,false],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,null,false]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"pt_percent\",\"oltc\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,null,false],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,null,false]]}", "orient": "split", "dtype": { "name": "object", @@ -247,7 +247,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -943,7 +943,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -961,7 +961,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -979,7 +979,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -997,7 +997,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1015,7 +1015,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1033,7 +1033,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1051,7 +1051,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1069,7 +1069,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1087,7 +1087,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1105,7 +1105,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1123,7 +1123,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1141,7 +1141,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1159,7 +1159,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1177,7 +1177,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.9.0.json b/pandapower/test/test_files/old_versions/example_2.9.0.json index d8cecfdab..0cda5c0b1 100644 --- a/pandapower/test/test_files/old_versions/example_2.9.0.json +++ b/pandapower/test/test_files/old_versions/example_2.9.0.json @@ -225,7 +225,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"pt_percent\",\"oltc\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,null,false],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,null,false]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"pt_percent\",\"oltc\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,null,false],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,null,false]]}", "orient": "split", "dtype": { "name": "object", @@ -247,7 +247,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -943,7 +943,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -961,7 +961,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -979,7 +979,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -997,7 +997,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1015,7 +1015,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1033,7 +1033,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1051,7 +1051,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1069,7 +1069,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1087,7 +1087,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1105,7 +1105,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1123,7 +1123,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1141,7 +1141,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1159,7 +1159,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1177,7 +1177,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/test_ac_dc.json b/pandapower/test/test_files/test_ac_dc.json index d31326a86..2e2521e5e 100644 --- a/pandapower/test/test_files/test_ac_dc.json +++ b/pandapower/test/test_files/test_ac_dc.json @@ -388,7 +388,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",\"2-Winding Transformer Type\",3,1,250.0,380.0,110.0,10.0,0.000199999994948,5.0,0.100000001490116,0.0,\"hv\",0,0,0,0.0,0.0,0,false,1,1.0,true,10.0,0.5,100.0,0.0,0.899999976158142,1.0,\"\",\"\"]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",\"2-Winding Transformer Type\",3,1,250.0,380.0,110.0,10.0,0.000199999994948,5.0,0.100000001490116,0.0,\"hv\",0,0,0,0.0,0.0,0,false,1,1.0,true,10.0,0.5,100.0,0.0,0.899999976158142,1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -410,7 +410,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -1284,7 +1284,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1302,7 +1302,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1320,7 +1320,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1338,7 +1338,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1356,7 +1356,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1374,7 +1374,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1392,7 +1392,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1410,7 +1410,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1428,7 +1428,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1446,7 +1446,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1464,7 +1464,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1482,7 +1482,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "2-Winding Transformer Type": { "sn_mva": 250.0, @@ -1502,7 +1502,7 @@ "tap_side": "hv", "tap_step_percent": 0.0, "tap_step_degree": 0.0, - "tap_phase_shifter": false, + "tap_phase_shifter_type": 0, "tap_max": 0, "tap_min": 0, "tap_neutral": 0 @@ -1523,7 +1523,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1541,7 +1541,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/test_files/test_trafo3w_tap.json b/pandapower/test/test_files/test_trafo3w_tap.json index 8f4d8aee0..f4fd23ea2 100644 --- a/pandapower/test/test_files/test_trafo3w_tap.json +++ b/pandapower/test/test_files/test_trafo3w_tap.json @@ -368,7 +368,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -390,7 +390,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter": "bool", + "tap_phase_shifter_type": "uint32", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -1293,7 +1293,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1311,7 +1311,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1329,7 +1329,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1347,7 +1347,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1365,7 +1365,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1383,7 +1383,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1401,7 +1401,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1419,7 +1419,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1437,7 +1437,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1455,7 +1455,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1473,7 +1473,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1491,7 +1491,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1509,7 +1509,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1527,7 +1527,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter": false + "tap_phase_shifter_type": 0 } }, "trafo3w": { diff --git a/pandapower/test/timeseries/test_timeseries_recycle.py b/pandapower/test/timeseries/test_timeseries_recycle.py index bc0b18845..a38a4476e 100644 --- a/pandapower/test/timeseries/test_timeseries_recycle.py +++ b/pandapower/test/timeseries/test_timeseries_recycle.py @@ -298,7 +298,7 @@ def test_const_pq_gen_trafo_tap_dc(simple_test_net, run_function=pp.rundcpp): def test_const_pq_gen_trafo_tap_ideal(simple_test_net, run_function): # allows to use recycle = {"bus_pq", "gen", "trafo"} net = simple_test_net - net.trafo.loc[0, ["tap_step_percent", "tap_step_degree", "tap_phase_shifter"]] = 0, 5, True + net.trafo.loc[0, ["tap_step_percent", "tap_step_degree", "tap_phase_shifter_type"]] = 0, 5, 2 profiles, _ = create_data_source(n_timesteps) profiles['ext_grid'] = np.ones(n_timesteps) + np.arange(0, n_timesteps) * 1e-2 ds = DFData(profiles) @@ -326,7 +326,7 @@ def test_const_pq_gen_trafo_tap_ideal(simple_test_net, run_function): def test_const_pq_gen_trafo_tap_shifter(simple_test_net, run_function): # allows to use recycle = {"bus_pq", "gen", "trafo"} net = simple_test_net - net.trafo.loc[0, ["tap_step_percent", "tap_step_degree", "tap_phase_shifter"]] = 1, 10, False + net.trafo.loc[0, ["tap_step_percent", "tap_step_degree", "tap_phase_shifter_type"]] = 1, 10, 0 profiles, _ = create_data_source(n_timesteps) profiles['ext_grid'] = np.ones(n_timesteps) + np.arange(0, n_timesteps) * 1e-2 ds = DFData(profiles) diff --git a/pandapower/test/toolbox/test_grid_modification.py b/pandapower/test/toolbox/test_grid_modification.py index 717759016..167423a2d 100644 --- a/pandapower/test/toolbox/test_grid_modification.py +++ b/pandapower/test/toolbox/test_grid_modification.py @@ -190,27 +190,28 @@ def test_merge_with_groups(): assert list(pp.group_element_index(net, 4, "line")) == list(np.array([1, 3], dtype=np.int64) + \ net1.line.shape[0]) -def test_merge_with_characteristics(): - from pandapower.networks.simple_pandapower_test_networks import simple_four_bus_system - from pandapower.control.util.characteristic import Characteristic - - # create two networks - net1 = simple_four_bus_system() - net2 = simple_four_bus_system() - - # create two characteristic - Characteristic(net1, x_values=[0.85, 1.15], y_values=[5, 15]) - Characteristic(net2, x_values=[0.95, 1.05], y_values=[10, 20]) - - # assign the characteristic ids to the trafos - net1.trafo.loc[:, "vk_percent_characteristic"] = 0 - net2.trafo.loc[:, "vk_percent_characteristic"] = 0 - - # merge networks - merged, lookup = pp.merge_nets(net1, net2, validate=False, return_net2_reindex_lookup=True) - - # The second transformer should have the second characteristic - assert merged.trafo.loc[1, "vk_percent_characteristic"] == 1 +# commented out due to change in logic of characteristics +# def test_merge_with_characteristics(): +# from pandapower.networks.simple_pandapower_test_networks import simple_four_bus_system +# from pandapower.control.util.characteristic import Characteristic +# +# # create two networks +# net1 = simple_four_bus_system() +# net2 = simple_four_bus_system() +# +# # create two characteristic +# Characteristic(net1, x_values=[0.85, 1.15], y_values=[5, 15]) +# Characteristic(net2, x_values=[0.95, 1.05], y_values=[10, 20]) +# +# # assign the characteristic ids to the trafos +# net1.trafo.loc[:, "vk_percent_characteristic"] = 0 +# net2.trafo.loc[:, "vk_percent_characteristic"] = 0 +# +# # merge networks +# merged, lookup = pp.merge_nets(net1, net2, validate=False, return_net2_reindex_lookup=True) +# +# # The second transformer should have the second characteristic +# assert merged.trafo.loc[1, "vk_percent_characteristic"] == 1 def test_select_subnet(): diff --git a/pandapower/toolbox/data_modification.py b/pandapower/toolbox/data_modification.py index a8164fedb..0150f8ead 100644 --- a/pandapower/toolbox/data_modification.py +++ b/pandapower/toolbox/data_modification.py @@ -284,17 +284,6 @@ def reindex_elements(net, element_type, new_indices=None, old_indices=None, look reindex_buses(net, lookup) return - if element_type == "characteristic": - for old_id, new_id in lookup.items(): - for ele in ['vk_percent_characteristic', 'vkr_percent_characteristic']: - if ele in net.trafo: - net.trafo.loc[net.trafo[ele] == old_id, ele] = new_id - - for ele in ['vk_hv_percent_characteristic', 'vkr_hv_percent_characteristic', 'vk_mv_percent_characteristic', - 'vkr_mv_percent_characteristic', 'vk_lv_percent_characteristic', 'vkr_lv_percent_characteristic']: - if ele in net.trafo3w: - net.trafo3w.loc[net.trafo3w[ele] == old_id, ele] = new_id - # --- reindex new_index = pd.Series(net[element_type].index, index=net[element_type].index) if element_type != "group": diff --git a/pandapower/toolbox/grid_modification.py b/pandapower/toolbox/grid_modification.py index 9652b2671..5de259531 100644 --- a/pandapower/toolbox/grid_modification.py +++ b/pandapower/toolbox/grid_modification.py @@ -96,16 +96,22 @@ def select_subnet(net, buses, include_switch_buses=False, include_results=False, (net.measurement.element.isin(p2.trafo.index))) | ((net.measurement.element_type == "trafo3w") & (net.measurement.element.isin(p2.trafo3w.index)))] - relevant_characteristics = set() - for col in ("vk_percent_characteristic", "vkr_percent_characteristic"): - if col in net.trafo.columns: - relevant_characteristics |= set(net.trafo.loc[~net.trafo[col].isnull(), col].values) - for col in (f"vk_hv_percent_characteristic", f"vkr_hv_percent_characteristic", - f"vk_mv_percent_characteristic", f"vkr_mv_percent_characteristic", - f"vk_lv_percent_characteristic", f"vkr_lv_percent_characteristic"): - if col in net.trafo3w.columns: - relevant_characteristics |= set(net.trafo3w.loc[~net.trafo3w[col].isnull(), col].values) - p2.characteristic = net.characteristic.loc[list(relevant_characteristics)] + + if "trafo_characteristic_table" in net: + p2["trafo_characteristic_table"] = net["trafo_characteristic_table"][ + net["trafo_characteristic_table"].id_characteristic.isin(p2["trafo"].id_characteristic_table.values) | + net["trafo_characteristic_table"].id_characteristic.isin(p2["trafo3w"].id_characteristic_table.values)] + for table in ["shunt_characteristic_table", "gen_characteristic_table"]: + if table in net: + p2[table] = net[table][net[table].id_characteristic.isin(p2[table[:-21]].id_characteristic_table.values)] + + if "trafo_characteristic_spline" in net: + p2["trafo_characteristic_spline"] = net["trafo_characteristic_spline"][ + net["trafo_characteristic_spline"].id_characteristic.isin(p2["trafo"].id_characteristic_spline.values) | + net["trafo_characteristic_spline"].id_characteristic.isin(p2["trafo3w"].id_characteristic_spline.values)] + for table in ["shunt_characteristic_spline", "gen_characteristic_spline"]: + if table in net: + p2[table] = net[table][net[table].id_characteristic.isin(p2[table[:-22]].id_characteristic_spline.values)] _select_cost_df(net, p2, "poly_cost") _select_cost_df(net, p2, "pwl_cost") From 0d7b6ecfbef3c6ba42930d3faa69de7b06feb18b Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Tue, 3 Dec 2024 13:30:26 +0200 Subject: [PATCH 021/125] change data type from 'i4' to 'u4' --- pandapower/create.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/pandapower/create.py b/pandapower/create.py index 58f3f940a..aeb7a7064 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -158,7 +158,7 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("vn_kv", "f8"), ("step", "u4"), ("max_step", "u4"), - ('id_characteristic_table', 'i4'), + ('id_characteristic_table', 'u4'), ('step_dependency_table', 'bool'), ("in_service", "bool")], "svc": [("name", dtype(object)), @@ -247,7 +247,7 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("tap_step_degree", "f8"), ("tap_pos", "i4"), ("tap_phase_shifter_type", 'i4'), - ('id_characteristic_table', 'i4'), + ('id_characteristic_table', 'u4'), ('tap_dependency_table', 'bool'), ("parallel", "u4"), ("df", "f8"), @@ -282,7 +282,7 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("tap_pos", "i4"), ("tap_at_star_point", 'bool'), ("tap_phase_shifter_type", 'i4'), - ('id_characteristic_table', 'i4'), + ('id_characteristic_table', 'u4'), ('tap_dependency_table', 'bool'), ("in_service", 'bool')], "impedance": [("name", dtype(object)), From 999e1eaf2121fdccd53dd8e9907b5c8b4bcfaedc Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Wed, 4 Dec 2024 14:04:18 +0100 Subject: [PATCH 022/125] WIP trafo phase shifter reworking --- pandapower/build_branch.py | 146 +++++++++++++++++++++++++++++-------- 1 file changed, 116 insertions(+), 30 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 99c88e857..000d44b54 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -428,10 +428,14 @@ def _calc_branch_values_from_trafo_df(net, ppc, trafo_df=None, sequence=1, updat def _calc_r_x_y_from_dataframe(net, trafo_df, vn_trafo_lv, vn_lv, ppc, sequence=1, update_vk_values=True): mode = net["_options"]["mode"] trafo_model = net["_options"]["trafo_model"] - - r, x = _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net.sn_mva, + if 'tap_dependency_table' in trafo_df: + r, x = _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net.sn_mva, sequence=sequence, characteristic=net.get("characteristic"), - update_vk_values=update_vk_values) + update_vk_values=update_vk_values, trafo_characteristic_table=net.trafo_characteristic_table) + else: + r, x = _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net.sn_mva, + sequence=sequence, characteristic=net.get("characteristic"), + update_vk_values=update_vk_values) if mode == "sc": if net._options.get("use_pre_fault_voltage", False): @@ -570,11 +574,17 @@ def _calc_tap_from_dataframe(net, trafo_df): sin = lambda x: np.sin(np.deg2rad(x)) arctan = lambda x: np.rad2deg(np.arctan(x)) - if 'tap_dependency_table' in trafo_df: + if 'tap_phase_shifter_type' in trafo_df: phase_shifter_type = get_trafo_values(trafo_df, f"tap{t}_phase_shifter_type") - tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") - id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") - phase_shifter_type = phase_shifter_type.to_numpy() if not isinstance(trafo_df, dict) else phase_shifter_type + if 'tap_dependency_table' in trafo_df: + tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") + tap_dependency = np.array([False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency]) + id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") + else: + tap_table = [False] + tap_dependency = [False] + if not isinstance(trafo_df, dict) and not isinstance(phase_shifter_type, np.ndarray): + phase_shifter_type = phase_shifter_type.to_numpy() if not isinstance(trafo_df, dict) else phase_shifter_type phase_shifter_type = np.nan_to_num(phase_shifter_type, nan=-1) tap_table = np.logical_and(tap_dependency, np.logical_not(phase_shifter_type == -1)) tap_no_table = np.logical_and(tap_dependency == False, np.logical_not(phase_shifter_type == -1)) @@ -649,7 +659,56 @@ def _replace_nan(array, value=0): return array -# todo create similar or expand/rename function to include voltage_ratio and angle_deg +def _get_vk_values_from_table(trafo_df, trafo_characteristic_table, trafotype="2W"): + if trafotype == "2W": + vk_variables = ("vk_percent", "vkr_percent") + elif trafotype == "3W": + vk_variables = ("vk_hv_percent", "vkr_hv_percent", "vk_mv_percent", "vkr_mv_percent", + "vk_lv_percent", "vkr_lv_percent") + else: + raise UserWarning("Unknown trafotype") + + tap_dependency_table = get_trafo_values(trafo_df, "tap_dependency_table") + tap_dependency_table = np.array( + [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency_table]) + if np.any(np.isnan(tap_dependency_table)): + raise UserWarning("tap_dependent_impedance has NaN values, but must be of type " + "bool and set to True or False") + tap_pos = get_trafo_values(trafo_df, "tap_pos") + + if any(tap_dependency_table): + use_tap_dependent_impedance = True + + vals = () + + for c, vk_var in enumerate(vk_variables): + vk_value = get_trafo_values(trafo_df, vk_var) + if use_tap_dependent_impedance: + #if 'tap_dependency_table' in trafo_df: + # tap_dependency_table = get_trafo_values(trafo_df, "tap_dependency_table") + id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") + # if isinstance(trafo_df, dict): + # mask = np.concatenate((tap_dependency_table, tap_dependency_table, tap_dependency_table)) + # else: + mask = tap_dependency_table + filter = pd.DataFrame({ + 'id_characteristic': id_characteristic_table, + 'step': tap_pos, + 'mask': mask + }) + + filtered_df = trafo_characteristic_table.merge(filter[filter['mask']], on=['id_characteristic', 'step']) + if np.sum(mask) == 3 * len(filtered_df): + cut_index = len(mask) // 3 + mask = mask[:cut_index] + vk_value[mask] = filtered_df[vk_var] + vals += (vk_value,) + else: + vals += (vk_value,) + + return vals + + def _get_vk_values(trafo_df, characteristic, trafotype="2W"): if trafotype == "2W": vk_variables = ("vk_percent", "vkr_percent") @@ -696,16 +755,16 @@ def _get_vk_values(trafo_df, characteristic, trafotype="2W"): raise UserWarning(f"At least one characteristic must be defined for {trafotype} " f"trafo: {trafo_index[all_missing]}") - vals = () + vals = () - for c, vk_var in enumerate(vk_variables): - vk_value = get_trafo_values(trafo_df, vk_var) - if use_tap_dependent_impedance and vk_var in char_columns: - vals += (_calc_tap_dependent_value( - tap_pos, vk_value, tap_dependent_impedance, - characteristic, all_characteristic_idx[:, index_column[vk_var]]),) - else: - vals += (vk_value,) + for c, vk_var in enumerate(vk_variables): + vk_value = get_trafo_values(trafo_df, vk_var) + if use_tap_dependent_impedance and vk_var in char_columns: + vals += (_calc_tap_dependent_value( + tap_pos, vk_value, tap_dependent_impedance, + characteristic, all_characteristic_idx[:, index_column[vk_var]]),) + else: + vals += (vk_value,) return vals @@ -726,18 +785,29 @@ def custom_func(f, t, c): def _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, sn_mva, sequence=1, characteristic=None, - update_vk_values=True): + update_vk_values=True, trafo_characteristic_table=None): """ Calculates (Vectorized) the resistance and reactance according to the transformer values """ parallel = get_trafo_values(trafo_df, "parallel") if sequence == 1: - if update_vk_values: - vk_percent, vkr_percent = _get_vk_values(trafo_df, characteristic) + if "tap_dependency_table" in trafo_df: + tap_dependency_table = get_trafo_values(trafo_df, "tap_dependency_table") + tap_dependency_table = np.array( + [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency_table]) + if any(tap_dependency_table): + print("do something") + vk_percent, vkr_percent = _get_vk_values_from_table(trafo_df, trafo_characteristic_table) + else: + vk_percent = get_trafo_values(trafo_df, "vk_percent") + vkr_percent = get_trafo_values(trafo_df, "vkr_percent") else: - vk_percent = get_trafo_values(trafo_df, "vk_percent") - vkr_percent = get_trafo_values(trafo_df, "vkr_percent") + if update_vk_values: + vk_percent, vkr_percent = _get_vk_values(trafo_df, characteristic) + else: + vk_percent = get_trafo_values(trafo_df, "vk_percent") + vkr_percent = get_trafo_values(trafo_df, "vkr_percent") elif sequence == 0: vk_percent = get_trafo_values(trafo_df, "vk0_percent") @@ -1221,9 +1291,14 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): net._options["trafo3w_losses"].lower()) nr_trafos = len(net["trafo3w"]) if sequence==1: - mode_tmp = "type_c" if mode == "sc" and net._options.get("use_pre_fault_voltage", False) else mode - _calculate_sc_voltages_of_equivalent_transformers(t3, trafo2, mode_tmp, characteristic=net.get( - 'characteristic'), update_vk_values=update_vk_values) + if 'tap_dependency_table' in t3: + print("do something") + mode_tmp = "type_c" if mode == "sc" and net._options.get("use_pre_fault_voltage", False) else mode + _calculate_sc_voltages_of_equivalent_transformers(t3, trafo2, mode_tmp, trafo_characteristic_table=net.trafo_characteristic_table) + else: + mode_tmp = "type_c" if mode == "sc" and net._options.get("use_pre_fault_voltage", False) else mode + _calculate_sc_voltages_of_equivalent_transformers(t3, trafo2, mode_tmp, characteristic=net.get( + 'characteristic'), update_vk_values=update_vk_values) elif sequence==0: if mode != "sc": raise NotImplementedError( @@ -1262,12 +1337,23 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): return {var: np.concatenate([trafo2[var][side] for side in sides]) for var in trafo2.keys()} -def _calculate_sc_voltages_of_equivalent_transformers(t3, t2, mode, characteristic, update_vk_values=True): - if update_vk_values: - vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = _get_vk_values(t3, characteristic, "3W") +def _calculate_sc_voltages_of_equivalent_transformers(t3, t2, mode, characteristic=None, update_vk_values=True, trafo_characteristic_table=None): + if "tap_dependency_table" in t3: + tap_dependency_table = get_trafo_values(t3, "tap_dependency_table") + tap_dependency_table = np.array( + [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency_table]) + if any(tap_dependency_table): + vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = _get_vk_values_from_table(t3, trafo_characteristic_table, "3W") + else: + vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = ( + t3['vk_hv_percent'], t3['vkr_hv_percent'], t3['vk_mv_percent'], + t3['vkr_mv_percent'], t3['vk_lv_percent'], t3['vkr_lv_percent']) else: - vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = (t3['vk_hv_percent'], t3['vkr_hv_percent'], t3['vk_mv_percent'], - t3['vkr_mv_percent'], t3['vk_lv_percent'], t3['vkr_lv_percent']) + if update_vk_values: + vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = _get_vk_values(t3, characteristic, "3W") + else: + vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = (t3['vk_hv_percent'], t3['vkr_hv_percent'], t3['vk_mv_percent'], + t3['vkr_mv_percent'], t3['vk_lv_percent'], t3['vkr_lv_percent']) vk_3w = np.stack([vk_hv, vk_mv, vk_lv]) vkr_3w = np.stack([vkr_hv, vkr_mv, vkr_lv]) From 39cbc679c4912dbdf085ec11bd860f74a0d43d29 Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Wed, 4 Dec 2024 14:26:22 +0100 Subject: [PATCH 023/125] WIP trafo phase shifter reworking --- pandapower/build_branch.py | 1 - 1 file changed, 1 deletion(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 8d65cf3ba..ca446a508 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -797,7 +797,6 @@ def _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, sn_mva, sequenc tap_dependency_table = np.array( [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency_table]) if any(tap_dependency_table): - print("do something") vk_percent, vkr_percent = _get_vk_values_from_table(trafo_df, trafo_characteristic_table) else: vk_percent = get_trafo_values(trafo_df, "vk_percent") From da21da823d9101ac4e90edc057792874dd1abd88 Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Wed, 4 Dec 2024 15:00:28 +0100 Subject: [PATCH 024/125] Final Implementation --- pandapower/build_branch.py | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index ca446a508..179c18ce3 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -699,10 +699,10 @@ def _get_vk_values_from_table(trafo_df, trafo_characteristic_table, trafotype="2 filtered_df = trafo_characteristic_table.merge(filter[filter['mask']], on=['id_characteristic', 'step']) if np.sum(mask) == 3 * len(filtered_df): - cut_index = len(mask) // 3 - mask = mask[:cut_index] - vk_value[mask] = filtered_df[vk_var] - vals += (vk_value,) + vals += (vk_value,) + else: + vk_value[mask] = filtered_df[vk_var] + vals += (vk_value,) else: vals += (vk_value,) @@ -796,7 +796,7 @@ def _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, sn_mva, sequenc tap_dependency_table = get_trafo_values(trafo_df, "tap_dependency_table") tap_dependency_table = np.array( [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency_table]) - if any(tap_dependency_table): + if any(tap_dependency_table) and not isinstance(trafo_df, dict): vk_percent, vkr_percent = _get_vk_values_from_table(trafo_df, trafo_characteristic_table) else: vk_percent = get_trafo_values(trafo_df, "vk_percent") @@ -1291,7 +1291,6 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): nr_trafos = len(net["trafo3w"]) if sequence==1: if 'tap_dependency_table' in t3: - print("do something") mode_tmp = "type_c" if mode == "sc" and net._options.get("use_pre_fault_voltage", False) else mode _calculate_sc_voltages_of_equivalent_transformers(t3, trafo2, mode_tmp, trafo_characteristic_table=net.trafo_characteristic_table) else: From ee9d456cc474e3adcf9f25d4afc469312e3cd7e8 Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Thu, 5 Dec 2024 07:23:01 +0100 Subject: [PATCH 025/125] Trafo adaption bugfix and adjusted some tests --- pandapower/build_branch.py | 73 +++++++++---------- pandapower/create.py | 4 +- .../loadflow/result_test_network_generator.py | 6 +- pandapower/test/loadflow/test_results.py | 2 +- pandapower/test/loadflow/test_runpp.py | 6 +- 5 files changed, 43 insertions(+), 48 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 179c18ce3..537d659cf 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -431,7 +431,7 @@ def _calc_r_x_y_from_dataframe(net, trafo_df, vn_trafo_lv, vn_lv, ppc, sequence= if 'tap_dependency_table' in trafo_df: r, x = _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net.sn_mva, sequence=sequence, characteristic=net.get("characteristic"), - update_vk_values=update_vk_values, trafo_characteristic_table=net.trafo_characteristic_table) + update_vk_values=update_vk_values, net=net) else: r, x = _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net.sn_mva, sequence=sequence, characteristic=net.get("characteristic"), @@ -599,30 +599,32 @@ def _calc_tap_from_dataframe(net, trafo_df): filtered_df = net.trafo_characteristic_table.merge(filter[filter['mask']], on=['id_characteristic', 'step']) vn[mask] = vn[mask] * filtered_df['voltage_ratio'] - trafo_shift[mask] = filtered_df['angle_deg'] + trafo_shift[mask] += filtered_df['angle_deg'] if any(tap_no_table): tap_ideal = np.logical_and(phase_shifter_type == 2, tap_no_table) tap_complex = np.logical_and(np.logical_or(phase_shifter_type == 0, phase_shifter_type == 1), tap_no_table) for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: - if any(tap_ideal): - degree_is_set = _replace_nan(tap_step_degree[tap_ideal]) != 0 - percent_is_set = _replace_nan(tap_step_percent[tap_ideal]) != 0 + mask_ideal = ((tap_ideal) & (tap_side == side)) + mask_complex = ((tap_complex) & (tap_side == side)) + if any(mask_ideal): + degree_is_set = _replace_nan(tap_step_degree[mask_ideal]) != 0 + percent_is_set = _replace_nan(tap_step_percent[mask_ideal]) != 0 if (degree_is_set & percent_is_set).any(): raise UserWarning( "Both tap_step_degree and tap_step_percent set for ideal phase shifter") - trafo_shift[tap_ideal] += np.where( + trafo_shift[mask_ideal] += np.where( (degree_is_set), (direction * tap_diff[phase_shifter_type == 2] * tap_step_degree[phase_shifter_type == 2]), (direction * 2 * np.rad2deg(np.arcsin(tap_diff[phase_shifter_type == 2] * \ tap_step_percent[phase_shifter_type == 2] / 100 / 2))) ) - elif any(tap_complex): - tap_steps = tap_step_percent[tap_complex] * tap_diff[tap_complex] / 100 - tap_angles = _replace_nan(tap_step_degree[tap_complex]) - u1 = vn[tap_complex] + elif any(mask_complex): + tap_steps = tap_step_percent[mask_complex] * tap_diff[mask_complex] / 100 + tap_angles = _replace_nan(tap_step_degree[mask_complex]) + u1 = vn[mask_complex] du = u1 * _replace_nan(tap_steps) - vn[tap_complex] = np.sqrt((u1 + du * cos(tap_angles)) ** 2 + (du * sin(tap_angles)) ** 2) - trafo_shift[tap_complex] += (arctan(direction * du * sin(tap_angles) / + vn[mask_complex] = np.sqrt((u1 + du * cos(tap_angles)) ** 2 + (du * sin(tap_angles)) ** 2) + trafo_shift[mask_complex] += (arctan(direction * du * sin(tap_angles) / (u1 + du * cos(tap_angles)))) else: tap_phase_shifter = get_trafo_values(trafo_df, f"tap{t}_phase_shifter") @@ -676,20 +678,13 @@ def _get_vk_values_from_table(trafo_df, trafo_characteristic_table, trafotype="2 "bool and set to True or False") tap_pos = get_trafo_values(trafo_df, "tap_pos") - if any(tap_dependency_table): - use_tap_dependent_impedance = True - vals = () for c, vk_var in enumerate(vk_variables): vk_value = get_trafo_values(trafo_df, vk_var) - if use_tap_dependent_impedance: - #if 'tap_dependency_table' in trafo_df: - # tap_dependency_table = get_trafo_values(trafo_df, "tap_dependency_table") + if any(tap_dependency_table): id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") - # if isinstance(trafo_df, dict): - # mask = np.concatenate((tap_dependency_table, tap_dependency_table, tap_dependency_table)) - # else: + mask = tap_dependency_table filter = pd.DataFrame({ 'id_characteristic': id_characteristic_table, @@ -698,11 +693,9 @@ def _get_vk_values_from_table(trafo_df, trafo_characteristic_table, trafotype="2 }) filtered_df = trafo_characteristic_table.merge(filter[filter['mask']], on=['id_characteristic', 'step']) - if np.sum(mask) == 3 * len(filtered_df): - vals += (vk_value,) - else: - vk_value[mask] = filtered_df[vk_var] - vals += (vk_value,) + vk_value[mask] = filtered_df[vk_var] + + vals += (vk_value,) else: vals += (vk_value,) @@ -755,16 +748,16 @@ def _get_vk_values(trafo_df, characteristic, trafotype="2W"): raise UserWarning(f"At least one characteristic must be defined for {trafotype} " f"trafo: {trafo_index[all_missing]}") - vals = () + vals = () - for c, vk_var in enumerate(vk_variables): - vk_value = get_trafo_values(trafo_df, vk_var) - if use_tap_dependent_impedance and vk_var in char_columns: - vals += (_calc_tap_dependent_value( - tap_pos, vk_value, tap_dependent_impedance, - characteristic, all_characteristic_idx[:, index_column[vk_var]]),) - else: - vals += (vk_value,) + for c, vk_var in enumerate(vk_variables): + vk_value = get_trafo_values(trafo_df, vk_var) + if use_tap_dependent_impedance and vk_var in char_columns: + vals += (_calc_tap_dependent_value( + tap_pos, vk_value, tap_dependent_impedance, + characteristic, all_characteristic_idx[:, index_column[vk_var]]),) + else: + vals += (vk_value,) return vals @@ -785,7 +778,7 @@ def custom_func(f, t, c): def _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, sn_mva, sequence=1, characteristic=None, - update_vk_values=True, trafo_characteristic_table=None): + update_vk_values=True, net=None): """ Calculates (Vectorized) the resistance and reactance according to the transformer values @@ -797,7 +790,7 @@ def _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, sn_mva, sequenc tap_dependency_table = np.array( [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency_table]) if any(tap_dependency_table) and not isinstance(trafo_df, dict): - vk_percent, vkr_percent = _get_vk_values_from_table(trafo_df, trafo_characteristic_table) + vk_percent, vkr_percent = _get_vk_values_from_table(trafo_df, net.trafo_characteristic_table) else: vk_percent = get_trafo_values(trafo_df, "vk_percent") vkr_percent = get_trafo_values(trafo_df, "vkr_percent") @@ -1292,7 +1285,7 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): if sequence==1: if 'tap_dependency_table' in t3: mode_tmp = "type_c" if mode == "sc" and net._options.get("use_pre_fault_voltage", False) else mode - _calculate_sc_voltages_of_equivalent_transformers(t3, trafo2, mode_tmp, trafo_characteristic_table=net.trafo_characteristic_table) + _calculate_sc_voltages_of_equivalent_transformers(t3, trafo2, mode_tmp, net=net) else: mode_tmp = "type_c" if mode == "sc" and net._options.get("use_pre_fault_voltage", False) else mode _calculate_sc_voltages_of_equivalent_transformers(t3, trafo2, mode_tmp, characteristic=net.get( @@ -1335,13 +1328,13 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): return {var: np.concatenate([trafo2[var][side] for side in sides]) for var in trafo2.keys()} -def _calculate_sc_voltages_of_equivalent_transformers(t3, t2, mode, characteristic=None, update_vk_values=True, trafo_characteristic_table=None): +def _calculate_sc_voltages_of_equivalent_transformers(t3, t2, mode, characteristic=None, update_vk_values=True, net=None): if "tap_dependency_table" in t3: tap_dependency_table = get_trafo_values(t3, "tap_dependency_table") tap_dependency_table = np.array( [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency_table]) if any(tap_dependency_table): - vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = _get_vk_values_from_table(t3, trafo_characteristic_table, "3W") + vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = _get_vk_values_from_table(t3, net.trafo_characteristic_table, "3W") else: vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = ( t3['vk_hv_percent'], t3['vkr_hv_percent'], t3['vk_mv_percent'], diff --git a/pandapower/create.py b/pandapower/create.py index aeb7a7064..045814946 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -3929,7 +3929,7 @@ def create_transformer3w_from_parameters( vkr_mv_percent, vkr_lv_percent, pfe_kw, i0_percent, shift_mv_degree=0., shift_lv_degree=0., tap_side=None, tap_step_percent=nan, tap_step_degree=nan, tap_pos=nan, - tap_neutral=nan, tap_max=nan, + tap_neutral=nan, tap_max=nan, tap_phase_shifter_type=nan, tap_min=nan, name=None, in_service=True, index=None, max_loading_percent=nan, tap_at_star_point=False, vk0_hv_percent=nan, vk0_mv_percent=nan, vk0_lv_percent=nan, @@ -4075,6 +4075,8 @@ def create_transformer3w_from_parameters( _set_value_if_not_nan(net, index, max_loading_percent, "max_loading_percent", "trafo3w") _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo3w", dtype="Int64") + _set_value_if_not_nan(net, index, tap_phase_shifter_type, + "tap_phase_shifter_type", "trafo3w", dtype="Int64") return index diff --git a/pandapower/test/loadflow/result_test_network_generator.py b/pandapower/test/loadflow/result_test_network_generator.py index 21e349ff5..2e8466921 100644 --- a/pandapower/test/loadflow/result_test_network_generator.py +++ b/pandapower/test/loadflow/result_test_network_generator.py @@ -175,12 +175,12 @@ def add_test_trafo(net): pp.create_transformer_from_parameters(net, b2, b3, vk_percent=5., vkr_percent=2., i0_percent=.4, pfe_kw=2., sn_mva=0.4, vn_hv_kv=22, vn_lv_kv=0.42, tap_max=10, tap_neutral=5, tap_min=0, - tap_step_percent=1.25, tap_pos=3, shift_degree=150, + tap_step_percent=1.25, tap_pos=3, tap_phase_shifter_type=0, shift_degree=150, tap_side="hv", parallel=2) t2 = pp.create_transformer_from_parameters(net, b2, b3, vk_percent=5., vkr_percent=2., i0_percent=.4, pfe_kw=2, sn_mva=0.4, vn_hv_kv=22, vn_lv_kv=0.42, tap_max=10, tap_neutral=5, tap_min=0, - tap_step_percent=1.25, tap_pos=3, tap_side="hv", + tap_step_percent=1.25, tap_pos=3, tap_phase_shifter_type=0, tap_side="hv", shift_degree=150, index=pp.get_free_id(net.trafo) + 1) pp.create_switch(net, b3, t2, et="t", closed=False) pp.create_transformer_from_parameters(net, b2, b3, vk_percent=5., vkr_percent=2., @@ -325,7 +325,7 @@ def add_test_trafo3w(net): vkr_mv_percent=.02, vk_lv_percent=.25, vkr_lv_percent=.01, pfe_kw=0.5, i0_percent=0.1, name="test", index=pp.get_free_id(net.trafo3w) + 1, - tap_side="hv", tap_pos=2, tap_step_percent=1.25, + tap_side="hv", tap_pos=2, tap_phase_shifter_type=0, tap_step_percent=1.25, tap_min=-5, tap_neutral=0, tap_max=5) # adding out of service 3w trafo should not change results pp.create_transformer3w_from_parameters(net, hv_bus=b2, mv_bus=b3, lv_bus=b4, vn_hv_kv=20, diff --git a/pandapower/test/loadflow/test_results.py b/pandapower/test/loadflow/test_results.py index bcdc76504..70306c27c 100644 --- a/pandapower/test/loadflow/test_results.py +++ b/pandapower/test/loadflow/test_results.py @@ -890,7 +890,7 @@ def test_trafo_unequal_r_x_hv_lv(): pp.create_transformer_from_parameters(net, 0, 1, 150, 120, 19, 1, 3, 20, 0.12, tap_side="hv", tap_neutral=0, tap_max=2, tap_min=-2, tap_step_percent=5, tap_step_degree=30, - tap_pos=-2, leakage_resistance_ratio_hv=0.6, leakage_reactance_ratio_hv=0.2) + tap_pos=-2, tap_phase_shifter_type=0, leakage_resistance_ratio_hv=0.6, leakage_reactance_ratio_hv=0.2) pp.create_load(net, 1, 100, 20) runpp_with_consistency_checks(net) diff --git a/pandapower/test/loadflow/test_runpp.py b/pandapower/test/loadflow/test_runpp.py index ce1e91b7f..b71da8a42 100644 --- a/pandapower/test/loadflow/test_runpp.py +++ b/pandapower/test/loadflow/test_runpp.py @@ -1326,13 +1326,13 @@ def test_tap_dependent_impedance(): vn_hv_kv=20., vn_mv_kv=0.9, vn_lv_kv=0.45, sn_hv_mva=0.6, sn_mv_mva=0.5, sn_lv_mva=0.4, vk_hv_percent=1., vk_mv_percent=1., vk_lv_percent=1., vkr_hv_percent=0.3, vkr_mv_percent=0.3, vkr_lv_percent=0.3, - pfe_kw=0.2, i0_percent=0.3, tap_neutral=0., - tap_pos=0, tap_step_percent=1., tap_min=-2, tap_max=2) + pfe_kw=0.2, i0_percent=0.3, tap_neutral=0., tap_side='hv', + tap_pos=0, tap_step_percent=0., tap_min=-2, tap_max=2) net_backup = net.deepcopy() net["trafo_characteristic_table"] = pd.DataFrame( - {'id_characteristic': [0, 0, 0, 0, 0], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [1, 1, 1, 1, 1], + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [0.95, 0.975, 1, 1.025, 1.05], 'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [5.5, 5.8, 6, 6.2, 6.5], 'vkr_percent': [1.4, 1.42, 1.44, 1.46, 1.48], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan, 'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan}) From a3a45a66e0e418f829bffb31b3e7cd60a670b449 Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Thu, 5 Dec 2024 13:18:02 +0100 Subject: [PATCH 026/125] WIP Station Controllers Options --- pandapower/build_branch.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 537d659cf..3750a5fce 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -533,7 +533,7 @@ def _calc_y_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net_sn_mva): # todo: add characteristics for tap percent and degree changes here def _calc_tap_from_dataframe(net, trafo_df): """ - Adjust the nominal voltage vnh and vnl to the active tab position "tap_pos". + Adjust the nominal voltage vnh, vnl and phase shift to the active tab position "tap_pos". If "side" is 1 (high-voltage side) the high voltage vnh is adjusted. If "side" is 2 (low-voltage side) the low voltage vnl is adjusted @@ -575,11 +575,11 @@ def _calc_tap_from_dataframe(net, trafo_df): arctan = lambda x: np.rad2deg(np.arctan(x)) if 'tap_phase_shifter_type' in trafo_df: + # tap_phase_shift_type is only in dataframe starting from pp Version 3.0, older version use different logic phase_shifter_type = get_trafo_values(trafo_df, f"tap{t}_phase_shifter_type") if 'tap_dependency_table' in trafo_df: tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") tap_dependency = np.array([False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency]) - id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") else: tap_table = [False] tap_dependency = [False] @@ -589,6 +589,7 @@ def _calc_tap_from_dataframe(net, trafo_df): tap_table = np.logical_and(tap_dependency, np.logical_not(phase_shifter_type == -1)) tap_no_table = np.logical_and(tap_dependency == False, np.logical_not(phase_shifter_type == -1)) if any(tap_table): + id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: mask = tap_table & (side == tap_side) filter = pd.DataFrame({ From 9c9c8abb99be93a58fe9d18aa80b6b19374b9d2a Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 5 Dec 2024 14:20:55 +0200 Subject: [PATCH 027/125] remove commented code --- .../transformers/tapController.py | 44 ------------------- 1 file changed, 44 deletions(-) diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py index bb0c423ad..89ecc150a 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py @@ -22,53 +22,9 @@ def __init__(self, cimConverter: build_pp_net.CimConverter): def create_tap_controller_for_power_transformers(self): if self.cimConverter.power_trafo2w.index.size > 0: - # create transformer tap controller self._create_tap_controller(self.cimConverter.power_trafo2w, 'trafo') - # moved out of converter - # time_start = time.time() - # self.logger.info("Creating the tap dependent characteristic objects for 2w-trafos.") - # # create the characteristic objects for transformers - # characteristic_df_temp = \ - # self.cimConverter.net['trafo_characteristic_table'][ - # ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent']] - # for trafo_id, trafo_row in self.cimConverter.net.trafo.dropna( - # subset=['id_characteristic_table']).iterrows(): - # characteristic_df = characteristic_df_temp.loc[ - # characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic_table']] - # self._create_trafo_characteristic_object(net=self.cimConverter.net, trafo_type='trafo', - # trafo_id=[trafo_id], characteristic_df=characteristic_df) - # self.logger.info(f"Finished creating tap dependent characteristic objects for 2w-trafos in " - # f"{time.time() - time_start}.") if self.cimConverter.power_trafo3w.index.size > 0: - # create transformer tap controller self._create_tap_controller(self.cimConverter.power_trafo3w, 'trafo3w') - # moved out of converter - # time_start = time.time() - # self.logger.info("Creating the tap dependent characteristic objects for 3w-trafos.") - # # create the characteristic objects for transformers - # characteristic_df_temp = \ - # self.cimConverter.net['trafo_characteristic_table'][ - # ['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vkr_hv_percent', 'vkr_mv_percent', - # 'vkr_lv_percent', 'vk_hv_percent', 'vk_mv_percent', 'vk_lv_percent']] - # for trafo_id, trafo_row in self.cimConverter.net.trafo3w.dropna( - # subset=['id_characteristic_table']).iterrows(): - # characteristic_df = characteristic_df_temp.loc[ - # characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic_table']] - # self._create_trafo_characteristic_object(net=self.cimConverter.net, trafo_type='trafo3w', - # trafo_id=[trafo_id], characteristic_df=characteristic_df) - # self.logger.info(f"Finished creating tap dependent characteristic objects for 3w-trafos in " - # f"{time.time() - time_start}.") - - # moved out of converter - # def _create_trafo_characteristic_object(self, net, trafo_type: str, trafo_id: List, - # characteristic_df: pd.DataFrame): - # self.logger.info("Adding characteristic object for trafo_type: %s and trafo_id: %s" % (trafo_type, trafo_id)) - # for variable in ['voltage_ratio', 'angle_deg', 'vkr_percent', 'vk_percent', 'vk_hv_percent', 'vkr_hv_percent', - # 'vk_mv_percent', 'vkr_mv_percent', 'vk_lv_percent', 'vkr_lv_percent']: - # if variable in characteristic_df.columns: - # pandapower.control.create_trafo_characteristics(net, trafo_type, trafo_id, variable, - # [characteristic_df['step'].to_list()], - # [characteristic_df[variable].to_list()]) def _create_tap_controller(self, input_df: pd.DataFrame, trafo_type: str): if not self.cimConverter.kwargs.get('create_tap_controller', True): From ea61e910be0a657b0a993a824551194cd0d9b6e4 Mon Sep 17 00:00:00 2001 From: Jakob Kirschner Date: Wed, 4 Dec 2024 16:33:53 +0100 Subject: [PATCH 028/125] get p and q values for shunts from characteristics --- pandapower/build_bus.py | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/pandapower/build_bus.py b/pandapower/build_bus.py index c7a3703e3..230d3f8e9 100644 --- a/pandapower/build_bus.py +++ b/pandapower/build_bus.py @@ -640,8 +640,15 @@ def _calc_shunts_and_add_on_ppc(net, ppc): if len(s) > 0: vl = _is_elements["shunt"] v_ratio = (ppc["bus"][bus_lookup[s["bus"].values], BASE_KV] / s["vn_kv"].values) ** 2 * base_multiplier - q = np.hstack([q, s["q_mvar"].values * s["step"].values * v_ratio * vl]) - p = np.hstack([p, s["p_mw"].values * s["step"].values * v_ratio * vl]) + + s_tmp = s.merge(net.shunt_characteristic_table, how="left", left_on="id_characteristic_table", + right_on="id_characteristic", suffixes=("", "_table")) + s = s_tmp.loc[(s_tmp["step"] == s_tmp["step_table"]) | ~s_tmp["step_dependency_table"]] + + q = np.hstack([q, s["q_mvar"].values * s["step"].values * v_ratio * vl * ~s["step_dependency_table"]]) + p = np.hstack([p, s["p_mw"].values * s["step"].values * v_ratio * vl * ~s["step_dependency_table"]]) + q = q + s["q_mvar_table"].fillna(0).to_numpy() * v_ratio * vl + p = p + s["p_mw_table"].fillna(0).to_numpy() * v_ratio * vl b = np.hstack([b, s["bus"].values]) w = net["ward"] From 697dfb922cc1615cec25837a6fd17a77350fb9de Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 5 Dec 2024 16:12:27 +0200 Subject: [PATCH 029/125] add tap_phase_shifter_type parameter for trafo3w in create.py lib --- pandapower/create.py | 17 +++++++++++++++-- 1 file changed, 15 insertions(+), 2 deletions(-) diff --git a/pandapower/create.py b/pandapower/create.py index 045814946..48aa972bf 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -3811,7 +3811,7 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_pos=nan, - in_service=True, index=None, max_loading_percent=nan, + in_service=True, index=None, max_loading_percent=nan, tap_phase_shifter_type=nan, tap_at_star_point=False, tap_dependency_table=False, id_characteristic_table=nan): """ Creates a three-winding transformer in table net["trafo3w"]. @@ -3836,6 +3836,9 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p **tap_pos** (int, nan) - current tap position of the transformer. Defaults to the medium \ position (tap_neutral) + **tap_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + 1: Symmetrical, 2: Ideal) + **tap_at_star_point** (boolean) - Whether tap changer is located at the star point of the \ 3W-transformer or at the bus @@ -3918,6 +3921,8 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p _set_value_if_not_nan(net, index, max_loading_percent, "max_loading_percent", "trafo3w") _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo3w", dtype="Int64") + _set_value_if_not_nan(net, index, tap_phase_shifter_type, + "tap_phase_shifter_type", "trafo3w", dtype="Int64") return index @@ -3999,6 +4004,9 @@ def create_transformer3w_from_parameters( **tap_pos** (int, nan) - current tap position of the transformer. Defaults to the \ medium position (tap_neutral) + **tap_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + 1: Symmetrical, 2: Ideal) + **tap_at_star_point** (boolean) - Whether tap changer is located at the star point of the \ 3W-transformer or at the bus @@ -4090,7 +4098,7 @@ def create_transformers3w_from_parameters( tap_step_percent=nan, tap_step_degree=nan, tap_pos=nan, tap_neutral=nan, tap_max=nan, tap_min=nan, name=None, in_service=True, index=None, max_loading_percent=nan, - tap_at_star_point=False, + tap_at_star_point=False, tap_phase_shifter_type=nan, vk0_hv_percent=nan, vk0_mv_percent=nan, vk0_lv_percent=nan, vkr0_hv_percent=nan, vkr0_mv_percent=nan, vkr0_lv_percent=nan, vector_group=None, tap_dependency_table=False, id_characteristic_table=nan, **kwargs): @@ -4160,6 +4168,9 @@ def create_transformers3w_from_parameters( **tap_pos** (list of int, nan) - current tap position of the transformer. Defaults to the \ medium position (tap_neutral) + **tap_phase_shifter_type** (list of int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + 1: Symmetrical, 2: Ideal) + **tap_at_star_point** (list of boolean) - Whether tap changer is located at the star point of the \ 3W-transformer or at the bus @@ -4236,6 +4247,8 @@ def create_transformers3w_from_parameters( max_loading_percent) _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "id_characteristic_table", id_characteristic_table, dtype="Int64") + _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "tap_phase_shifter_type", + tap_phase_shifter_type, dtype="Int64") defaults_to_fill = [("tap_dependency_table", False)] _set_multiple_entries(net, "trafo3w", index, defaults_to_fill=defaults_to_fill, **entries, From a6bd8db604689f5efbed4d55047342560522026f Mon Sep 17 00:00:00 2001 From: Jakob Kirschner Date: Thu, 5 Dec 2024 15:38:49 +0100 Subject: [PATCH 030/125] make build bus backward compatible for shunts --- pandapower/build_bus.py | 20 ++++++++++++-------- 1 file changed, 12 insertions(+), 8 deletions(-) diff --git a/pandapower/build_bus.py b/pandapower/build_bus.py index 230d3f8e9..a105e6c83 100644 --- a/pandapower/build_bus.py +++ b/pandapower/build_bus.py @@ -641,14 +641,18 @@ def _calc_shunts_and_add_on_ppc(net, ppc): vl = _is_elements["shunt"] v_ratio = (ppc["bus"][bus_lookup[s["bus"].values], BASE_KV] / s["vn_kv"].values) ** 2 * base_multiplier - s_tmp = s.merge(net.shunt_characteristic_table, how="left", left_on="id_characteristic_table", - right_on="id_characteristic", suffixes=("", "_table")) - s = s_tmp.loc[(s_tmp["step"] == s_tmp["step_table"]) | ~s_tmp["step_dependency_table"]] - - q = np.hstack([q, s["q_mvar"].values * s["step"].values * v_ratio * vl * ~s["step_dependency_table"]]) - p = np.hstack([p, s["p_mw"].values * s["step"].values * v_ratio * vl * ~s["step_dependency_table"]]) - q = q + s["q_mvar_table"].fillna(0).to_numpy() * v_ratio * vl - p = p + s["p_mw_table"].fillna(0).to_numpy() * v_ratio * vl + if "step_dependency_table" in s: + s_tmp = s.merge(net.shunt_characteristic_table, how="left", left_on="id_characteristic_table", + right_on="id_characteristic", suffixes=("", "_table")) + s = s_tmp.loc[(s_tmp["step"] == s_tmp["step_table"]) | ~s_tmp["step_dependency_table"]] + + q = np.hstack([q, s["q_mvar"].values * s["step"].values * v_ratio * vl * ~s["step_dependency_table"]]) + p = np.hstack([p, s["p_mw"].values * s["step"].values * v_ratio * vl * ~s["step_dependency_table"]]) + q = q + s["q_mvar_table"].fillna(0).to_numpy() * v_ratio * vl + p = p + s["p_mw_table"].fillna(0).to_numpy() * v_ratio * vl + else: + q = np.hstack([q, s["q_mvar"].values * s["step"].values * v_ratio * vl]) + p = np.hstack([p, s["p_mw"].values * s["step"].values * v_ratio * vl]) b = np.hstack([b, s["bus"].values]) w = net["ward"] From 5c95d3ed869c8937ad3823b9712028f58b78e4d2 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 5 Dec 2024 17:38:53 +0200 Subject: [PATCH 031/125] update std_types.py for trafo3w --- pandapower/std_types.py | 64 ++++++++++++++++++++++++++--------------- 1 file changed, 41 insertions(+), 23 deletions(-) diff --git a/pandapower/std_types.py b/pandapower/std_types.py index 4554ca009..68ef31def 100644 --- a/pandapower/std_types.py +++ b/pandapower/std_types.py @@ -85,16 +85,16 @@ def create_std_type(net, data, name, element="line", overwrite=True, check_requi required = ["r_ohm_per_km","max_i_ka"] elif element == "trafo": required = ["sn_mva", "vn_hv_kv", "vn_lv_kv", "vk_percent", "vkr_percent", - "pfe_kw", "i0_percent", "shift_degree"] + "pfe_kw", "i0_percent", "shift_degree", "tap_phase_shifter_type", "trafo_characteristic_table"] elif element == "trafo3w": required = ["sn_hv_mva", "sn_mv_mva", "sn_lv_mva", "vn_hv_kv", "vn_mv_kv", "vn_lv_kv", "vk_hv_percent", "vk_mv_percent", "vk_lv_percent", "vkr_hv_percent", "vkr_mv_percent", "vkr_lv_percent", "pfe_kw", "i0_percent", "shift_mv_degree", - "shift_lv_degree"] + "shift_lv_degree", "tap_phase_shifter_type", "trafo_characteristic_table"] elif element == "fuse": required = ["fuse_type", "i_rated_a"] else: - raise ValueError("Unkown element type %s" % element) + raise ValueError("Unknown element type %s" % element) for par in required: if par not in data: raise UserWarning("%s is required as %s type parameter" % (par, element)) @@ -111,7 +111,7 @@ def create_std_types(net, data, element="line", overwrite=True, check_required=T **net** - The pandapower network **data** - dictionary of standard type parameter sets - **element** - "line","line_dc", "trafo" or "trafo3w" + **element** - "line", "line_dc", "trafo" or "trafo3w" EXAMPLE: @@ -146,7 +146,7 @@ def copy_std_types(to_net, from_net, element="line", overwrite=True): def load_std_type(net, name, element="line"): """ - Loads standard type data from the linetypes data base. Issues a warning if + Loads standard type data from the linetypes database. Issues a warning if linetype is unknown. INPUT: @@ -154,7 +154,7 @@ def load_std_type(net, name, element="line"): **name** - name of the standard type as string - **element** - "line","line_dc","trafo" or "trafo3w" + **element** - "line", "line_dc", "trafo" or "trafo3w" OUTPUT: **typedata** - dictionary containing type data @@ -225,7 +225,7 @@ def available_std_types(net, element="line"): return std_types.convert_objects() -def parameter_from_std_type(net, parameter, element="line",fill=None): +def parameter_from_std_type(net, parameter, element="line", fill=None): """ Loads standard types data for a parameter, which can be used to add an additional parameter, that is not included in the original pandapower datastructure but is available in the standard @@ -984,7 +984,8 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, "100 MVA 220/110 kV": {"i0_percent": 0.06, "pfe_kw": 55, @@ -1001,7 +1002,8 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, # compare to IFT Ingenieurbüro data and Schlabbach book "63 MVA 110/20 kV": @@ -1020,7 +1022,8 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, "40 MVA 110/20 kV": {"i0_percent": 0.05, "pfe_kw": 18, @@ -1037,7 +1040,8 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, "25 MVA 110/20 kV": {"i0_percent": 0.07, "pfe_kw": 14, @@ -1054,7 +1058,8 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, "63 MVA 110/10 kV": {"sn_mva": 63, "vn_hv_kv": 110, @@ -1071,7 +1076,8 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, "40 MVA 110/10 kV": {"sn_mva": 40, "vn_hv_kv": 110, @@ -1088,7 +1094,8 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, "25 MVA 110/10 kV": {"sn_mva": 25, "vn_hv_kv": 110, @@ -1105,7 +1112,8 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, # Trafo 20/0.4 # 0.25 MVA 20/0.4 kV 0.45 Trafo Union "0.25 MVA 20/0.4 kV": @@ -1124,7 +1132,8 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, # 0.4 MVA 20/0.4 kV Trafo Union "0.4 MVA 20/0.4 kV": {"sn_mva": 0.4, "vn_hv_kv": 20, "vn_lv_kv": 0.4, @@ -1140,7 +1149,8 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, # 0.63 MVA 20/0.4 kV Trafo Union "0.63 MVA 20/0.4 kV": {"sn_mva": 0.63, @@ -1158,7 +1168,8 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, # Trafo 10/0.4: # 0.25 MVA 10/0.4 kV 0.4 Trafo Union wnr "0.25 MVA 10/0.4 kV": @@ -1177,7 +1188,8 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, # 0.4 MVA 10/0.4 kV Trafo Union wnr "0.4 MVA 10/0.4 kV": {"sn_mva": 0.4, @@ -1195,7 +1207,8 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, # 0.63 MVA 10/0.4 kV Trafo Union wnr "0.63 MVA 10/0.4 kV": {"sn_mva": 0.63, @@ -1213,7 +1226,8 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0}, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, } return trafotypes @@ -1243,7 +1257,9 @@ def basic_trafo3w_std_types(): "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2}, + "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False}, "63/25/38 MVA 110/10/10 kV": {"sn_hv_mva": 63, "sn_mv_mva": 25, @@ -1266,7 +1282,9 @@ def basic_trafo3w_std_types(): "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2} + "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, + "trafo_characteristic_table": False} } return trafo3wtypes From 73f555bbeec8eadf3a9b236c1dec0f98c53d735c Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Thu, 5 Dec 2024 16:47:48 +0100 Subject: [PATCH 032/125] Update on shunts --- pandapower/test/control/test_shunt_control.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/pandapower/test/control/test_shunt_control.py b/pandapower/test/control/test_shunt_control.py index 2f53ad098..b3128a0d7 100644 --- a/pandapower/test/control/test_shunt_control.py +++ b/pandapower/test/control/test_shunt_control.py @@ -33,6 +33,8 @@ def test_discrete_shunt_control(tol=1e-6): pp.runpp(net, run_control=True) assert (abs(net.res_bus.loc[1, "vm_pu"] - 1.077258) < tol) assert net.shunt.loc[0, "step"] == 2 + # net.shunt.step_dependency_table.loc[0] = True + # net.shunt.id_characteristic.loc[0] = 0 if __name__ == '__main__': pytest.main(['-s', __file__]) From 35611fa157f36b604bb193004bfab44e55297a96 Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Thu, 5 Dec 2024 16:48:15 +0100 Subject: [PATCH 033/125] Update on shunts --- pandapower/build_branch.py | 10 +++++----- pandapower/build_bus.py | 21 +++++++++++++-------- 2 files changed, 18 insertions(+), 13 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 3750a5fce..abea0a09a 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -574,20 +574,20 @@ def _calc_tap_from_dataframe(net, trafo_df): sin = lambda x: np.sin(np.deg2rad(x)) arctan = lambda x: np.rad2deg(np.arctan(x)) - if 'tap_phase_shifter_type' in trafo_df: + if f'tap{t}_phase_shifter_type' in trafo_df: # tap_phase_shift_type is only in dataframe starting from pp Version 3.0, older version use different logic phase_shifter_type = get_trafo_values(trafo_df, f"tap{t}_phase_shifter_type") - if 'tap_dependency_table' in trafo_df: + if f'tap{t}_dependency_table' in trafo_df: tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") tap_dependency = np.array([False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency]) else: - tap_table = [False] - tap_dependency = [False] + tap_table = np.array([False]) + tap_dependency = np.array([False]) if not isinstance(trafo_df, dict) and not isinstance(phase_shifter_type, np.ndarray): phase_shifter_type = phase_shifter_type.to_numpy() if not isinstance(trafo_df, dict) else phase_shifter_type phase_shifter_type = np.nan_to_num(phase_shifter_type, nan=-1) tap_table = np.logical_and(tap_dependency, np.logical_not(phase_shifter_type == -1)) - tap_no_table = np.logical_and(tap_dependency == False, np.logical_not(phase_shifter_type == -1)) + tap_no_table = np.logical_and(~(tap_dependency), np.logical_not(phase_shifter_type == -1)) if any(tap_table): id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: diff --git a/pandapower/build_bus.py b/pandapower/build_bus.py index a105e6c83..8b5b3cc18 100644 --- a/pandapower/build_bus.py +++ b/pandapower/build_bus.py @@ -642,14 +642,19 @@ def _calc_shunts_and_add_on_ppc(net, ppc): v_ratio = (ppc["bus"][bus_lookup[s["bus"].values], BASE_KV] / s["vn_kv"].values) ** 2 * base_multiplier if "step_dependency_table" in s: - s_tmp = s.merge(net.shunt_characteristic_table, how="left", left_on="id_characteristic_table", - right_on="id_characteristic", suffixes=("", "_table")) - s = s_tmp.loc[(s_tmp["step"] == s_tmp["step_table"]) | ~s_tmp["step_dependency_table"]] - - q = np.hstack([q, s["q_mvar"].values * s["step"].values * v_ratio * vl * ~s["step_dependency_table"]]) - p = np.hstack([p, s["p_mw"].values * s["step"].values * v_ratio * vl * ~s["step_dependency_table"]]) - q = q + s["q_mvar_table"].fillna(0).to_numpy() * v_ratio * vl - p = p + s["p_mw_table"].fillna(0).to_numpy() * v_ratio * vl + s.step_dependency_table.fillna(False) + if s.step_dependency_table.any(): + s_tmp = s.merge(net.shunt_characteristic_table, how="left", left_on="id_characteristic_table", + right_on="id_characteristic", suffixes=("", "_table")) + s = s_tmp.loc[(s_tmp["step"] == s_tmp["step_table"]) | ~s_tmp["step_dependency_table"]] + + q = np.hstack([q, s["q_mvar"].values * s["step"].values * v_ratio * vl * ~s["step_dependency_table"]]) + p = np.hstack([p, s["p_mw"].values * s["step"].values * v_ratio * vl * ~s["step_dependency_table"]]) + q = q + s["q_mvar_table"].fillna(0).to_numpy() * v_ratio * vl + p = p + s["p_mw_table"].fillna(0).to_numpy() * v_ratio * vl + else: + q = np.hstack([q, s["q_mvar"].values * s["step"].values * v_ratio * vl]) + p = np.hstack([p, s["p_mw"].values * s["step"].values * v_ratio * vl]) else: q = np.hstack([q, s["q_mvar"].values * s["step"].values * v_ratio * vl]) p = np.hstack([p, s["p_mw"].values * s["step"].values * v_ratio * vl]) From 1b540e6174a534f038de3d7fdb88b1bdc98f9ed9 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 6 Dec 2024 18:20:15 +0200 Subject: [PATCH 034/125] fix loadflow tests --- pandapower/build_branch.py | 153 ++++++++++-------- pandapower/contingency/contingency.py | 7 +- pandapower/control/__init__.py | 2 +- pandapower/control/util/auxiliary.py | 14 +- pandapower/convert_format.py | 2 + .../powerfactory/pp_import_functions.py | 20 +-- pandapower/create.py | 2 +- pandapower/grid_equivalents/auxiliary.py | 2 +- pandapower/networks/create_examples.py | 4 +- pandapower/test/api/test_auxiliary.py | 22 +-- .../test/contingency/test_contingency.py | 6 +- .../control/test_tap_dependent_impedance.py | 10 +- .../grid_equivalents/test_get_equivalent.py | 4 +- pandapower/test/helper_functions.py | 2 +- pandapower/test/loadflow/test_results.py | 2 +- pandapower/test/loadflow/test_runpp.py | 3 +- pandapower/test/loadflow/test_scenarios.py | 25 +-- pandapower/test/opf/test_basic.py | 10 +- pandapower/test/shortcircuit/test_1ph.py | 2 +- .../test/shortcircuit/test_all_currents.py | 11 +- .../test/shortcircuit/test_iec60909_4.py | 10 +- .../test/shortcircuit/test_transformer.py | 3 +- pandapower/test/test_files/save_version.py | 2 +- pandapower/test/timeseries/test_timeseries.py | 2 +- tutorials/create_advanced.ipynb | 5 +- tutorials/tap_dependent_impedance.ipynb | 2 +- ...three_phase_loadflow_tutorial_simple.ipynb | 2 +- 27 files changed, 181 insertions(+), 148 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index abea0a09a..7cef82b8d 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -27,7 +27,7 @@ TCSC_THYRISTOR_FIRING_ANGLE, TCSC_STATUS, TCSC_CONTROLLABLE, tcsc_cols, TCSC_MIN_FIRING_ANGLE, TCSC_MAX_FIRING_ANGLE -def _build_branch_ppc(net, ppc, update_vk_values: bool=True): +def _build_branch_ppc(net, ppc, update_vk_values: bool = True): """ Takes the empty ppc network and fills it with the branch values. The branch datatype will be np.complex 128 afterwards. @@ -140,7 +140,7 @@ def _initialize_branch_lookup(net, dc=False): return end -def _calc_trafo3w_parameter(net, ppc, update_vk_values: bool=True): +def _calc_trafo3w_parameter(net, ppc, update_vk_values: bool = True): bus_lookup = net["_pd2ppc_lookups"]["bus"] branch = ppc["branch"] f, t = net["_pd2ppc_lookups"]["branch"]["trafo3w"] @@ -187,7 +187,7 @@ def _calc_line_parameter(net, ppc, elm="line", ppc_elm="branch"): **RETURN**: **t** - Temporary line parameter. Which is a complex128 - Nunmpy array. with the following order: + Numpy array. with the following order: 0:bus_a; 1:bus_b; 2:r_pu; 3:x_pu; 4:b_pu """ f, t = net._pd2ppc_lookups[ppc_elm][elm] @@ -243,7 +243,7 @@ def _calc_line_parameter(net, ppc, elm="line", ppc_elm="branch"): # in service of lines branch[f:t, BR_STATUS] = line["in_service"].values # always set RATE_A for completeness: - # RATE_A is conisdered by the (PowerModels) OPF. If zero -> unlimited + # RATE_A is considered by the (PowerModels) OPF. If zero -> unlimited # TODO: check why OPF test fails if 100 instead of 0 max_load = line.max_loading_percent.values if "max_loading_percent" in line else 0. vr = net.bus.loc[line["from_bus"].values, "vn_kv"].values * np.sqrt(3.) @@ -269,7 +269,7 @@ def _calc_line_dc_parameter(net, ppc, elm="line_dc", ppc_elm="branch_dc"): **RETURN**: **t** - Temporary line_dc parameter. Which is a complex128 - Nunmpy array. with the following order: + Numpy array. with the following order: 0:bus_a; 1:bus_b; 2:r_pu; 3:x_pu; 4:b_pu """ f, t = net._pd2ppc_lookups[ppc_elm][elm] @@ -320,7 +320,7 @@ def _calc_line_dc_parameter(net, ppc, elm="line_dc", ppc_elm="branch_dc"): # in service of lines branch_dc[f:t, DC_BR_STATUS] = line_dc["in_service"].values # always set RATE_A for completeness: - # RATE_A is conisdered by the (PowerModels) OPF. If zero -> unlimited + # RATE_A is considered by the (PowerModels) OPF. If zero -> unlimited max_load = line_dc.max_loading_percent.values if "max_loading_percent" in line_dc else 0. vr = net.bus_dc.loc[line_dc["from_bus_dc"].values, "vn_kv"].values * np.sqrt(3.) max_i_ka = line_dc.max_i_ka.values @@ -329,8 +329,8 @@ def _calc_line_dc_parameter(net, ppc, elm="line_dc", ppc_elm="branch_dc"): branch_dc[f:t, DC_RATE_A] = max_load / 100. * max_i_ka * df * parallel * vr -def _calc_trafo_parameter(net, ppc, update_vk_values: bool=True): - ''' +def _calc_trafo_parameter(net, ppc, update_vk_values: bool = True): + """ Calculates the transformer parameter in per unit. **INPUT**: @@ -341,7 +341,7 @@ def _calc_trafo_parameter(net, ppc, update_vk_values: bool=True): Temporary transformer parameter. Which is a np.complex128 Numpy array. with the following order: 0:hv_bus; 1:lv_bus; 2:r_pu; 3:x_pu; 4:b_pu; 5:tab, 6:shift - ''' + """ bus_lookup = net["_pd2ppc_lookups"]["bus"] f, t = net["_pd2ppc_lookups"]["branch"]["trafo"] @@ -350,7 +350,8 @@ def _calc_trafo_parameter(net, ppc, update_vk_values: bool=True): parallel = trafo["parallel"].values branch[f:t, F_BUS] = bus_lookup[trafo["hv_bus"].values] branch[f:t, T_BUS] = bus_lookup[trafo["lv_bus"].values] - r, x, g, b, g_asym, b_asym, ratio, shift = _calc_branch_values_from_trafo_df(net, ppc, update_vk_values=update_vk_values) + r, x, g, b, g_asym, b_asym, ratio, shift = _calc_branch_values_from_trafo_df( + net, ppc, update_vk_values=update_vk_values) branch[f:t, BR_R] = r branch[f:t, BR_X] = x branch[f:t, BR_G] = g @@ -385,10 +386,10 @@ def _calc_branch_values_from_trafo_df(net, ppc, trafo_df=None, sequence=1, updat This function calculates the resistance r, reactance x, complex susceptance c and the tap ratio according to the given parameters. - .. warning:: This function returns the subsceptance b as a complex number + .. warning:: This function returns the susceptance b as a complex number **(-img + -re*i)**. MAT/PYPOWER is only intended to calculate the - imaginary part of the subceptance. However, internally c is - multiplied by i. By using subsceptance in this way, it is possible + imaginary part of the susceptance. However, internally c is + multiplied by i. By using susceptance in this way, it is possible to consider the ferromagnetic loss of the coil. Which would otherwise be neglected. @@ -402,11 +403,11 @@ def _calc_branch_values_from_trafo_df(net, ppc, trafo_df=None, sequence=1, updat **INPUT**: **pd_trafo** - The pandapower format Transformer Dataframe. - The Transformer modell will only readfrom pd_net + The Transformer model will only read from pd_net **RETURN**: **temp_para** - Temporary transformer parameter. Which is a complex128 - Nunmpy array. with the following order: + Numpy array. with the following order: 0:r_pu; 1:x_pu; 2:b_pu; 3:tab; """ @@ -430,8 +431,8 @@ def _calc_r_x_y_from_dataframe(net, trafo_df, vn_trafo_lv, vn_lv, ppc, sequence= trafo_model = net["_options"]["trafo_model"] if 'tap_dependency_table' in trafo_df: r, x = _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net.sn_mva, - sequence=sequence, characteristic=net.get("characteristic"), - update_vk_values=update_vk_values, net=net) + sequence=sequence, characteristic=net.get("characteristic"), + update_vk_values=update_vk_values, net=net) else: r, x = _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net.sn_mva, sequence=sequence, characteristic=net.get("characteristic"), @@ -448,7 +449,8 @@ def _calc_r_x_y_from_dataframe(net, trafo_df, vn_trafo_lv, vn_lv, ppc, sequence= # todo: kt is only used for case = max and only for network transformers! (IEC 60909-0:2016 section 6.3.3) # kt is only calculated for network transformers (IEC 60909-0:2016 section 6.3.3) if not net._options.get("use_pre_fault_voltage", False): - kt = _transformer_correction_factor(trafo_df, trafo_df.vk_percent, trafo_df.vkr_percent, trafo_df.sn_mva, cmax) + kt = _transformer_correction_factor( + trafo_df, trafo_df.vk_percent, trafo_df.vkr_percent, trafo_df.sn_mva, cmax) r *= kt x *= kt else: @@ -457,11 +459,13 @@ def _calc_r_x_y_from_dataframe(net, trafo_df, vn_trafo_lv, vn_lv, ppc, sequence= if trafo_model == "pi": return r, x, g, b, 0, 0 # g_asym and b_asym are 0 here elif trafo_model == "t": - r_ratio = get_trafo_values(trafo_df, "leakage_resistance_ratio_hv") if "leakage_resistance_ratio_hv" in trafo_df else np.full_like(r, fill_value=0.5, dtype=np.float64) - x_ratio = get_trafo_values(trafo_df, "leakage_reactance_ratio_hv") if "leakage_reactance_ratio_hv" in trafo_df else np.full_like(r, fill_value=0.5, dtype=np.float64) + r_ratio = get_trafo_values(trafo_df, "leakage_resistance_ratio_hv") \ + if "leakage_resistance_ratio_hv" in trafo_df else np.full_like(r, fill_value=0.5, dtype=np.float64) + x_ratio = get_trafo_values(trafo_df, "leakage_reactance_ratio_hv") \ + if "leakage_reactance_ratio_hv" in trafo_df else np.full_like(r, fill_value=0.5, dtype=np.float64) return _wye_delta(r, x, g, b, r_ratio, x_ratio) else: - raise ValueError("Unkonwn Transformer Model %s - valid values ar 'pi' or 't'" % trafo_model) + raise ValueError("Unknown Transformer Model %s - valid values ar 'pi' or 't'" % trafo_model) @np.errstate(all="raise") @@ -496,7 +500,7 @@ def _wye_delta(r, x, g, b, r_ratio, x_ratio): def _calc_y_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net_sn_mva): """ - Calculate the subsceptance y from the transformer dataframe. + Calculate the susceptance y from the transformer dataframe. INPUT: @@ -504,7 +508,7 @@ def _calc_y_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net_sn_mva): which contains transformer calculation values. OUTPUT: - **subsceptance** (1d array, np.complex128) - The subsceptance in pu in + **susceptance** (1d array, np.complex128) - The susceptance in pu in the form (-b_img, -b_real) """ @@ -515,7 +519,7 @@ def _calc_y_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net_sn_mva): parallel = get_trafo_values(trafo_df, "parallel") trafo_sn_mva = get_trafo_values(trafo_df, "sn_mva") - ### Calculate subsceptance ### + ### Calculate susceptance ### vnl_squared = (vn_lv_kv ** 2)/3 if mode == 'pf_3ph' else vn_lv_kv ** 2 g_mva = pfe_mw i0 = get_trafo_values(trafo_df, "i0_percent") / 3 if mode == 'pf_3ph'\ @@ -530,7 +534,7 @@ def _calc_y_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net_sn_mva): b_pu = b_mva / vnl_squared * baseZ * parallel / np.square(vn_trafo_lv / vn_lv_kv) return g_pu, b_pu -# todo: add characteristics for tap percent and degree changes here + def _calc_tap_from_dataframe(net, trafo_df): """ Adjust the nominal voltage vnh, vnl and phase shift to the active tab position "tap_pos". @@ -544,7 +548,7 @@ def _calc_tap_from_dataframe(net, trafo_df): which contains transformer calculation values. OUTPUT: - **vn_hv_kv** (1d array, float) - The adusted high voltages + **vn_hv_kv** (1d array, float) - The adjusted high voltages **vn_lv_kv** (1d array, float) - The adjusted low voltages @@ -557,7 +561,7 @@ def _calc_tap_from_dataframe(net, trafo_df): vnl = copy.copy(get_trafo_values(trafo_df, "vn_lv_kv").astype(float)) trafo_shift = get_trafo_values(trafo_df, "shift_degree").astype(float) if calculate_voltage_angles else \ np.zeros(len(vnh)) - if mode == "sc" and not net._options.get("use_pre_fault_voltage", False): # todo type c? + if mode == "sc" and not net._options.get("use_pre_fault_voltage", False): # todo type c? return vnh, vnl, trafo_shift for t in ("", "2"): @@ -579,15 +583,17 @@ def _calc_tap_from_dataframe(net, trafo_df): phase_shifter_type = get_trafo_values(trafo_df, f"tap{t}_phase_shifter_type") if f'tap{t}_dependency_table' in trafo_df: tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") - tap_dependency = np.array([False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency]) + tap_dependency = np.array( + [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency]) else: tap_table = np.array([False]) tap_dependency = np.array([False]) if not isinstance(trafo_df, dict) and not isinstance(phase_shifter_type, np.ndarray): - phase_shifter_type = phase_shifter_type.to_numpy() if not isinstance(trafo_df, dict) else phase_shifter_type + phase_shifter_type = phase_shifter_type.to_numpy() \ + if not isinstance(trafo_df, dict) else phase_shifter_type phase_shifter_type = np.nan_to_num(phase_shifter_type, nan=-1) tap_table = np.logical_and(tap_dependency, np.logical_not(phase_shifter_type == -1)) - tap_no_table = np.logical_and(~(tap_dependency), np.logical_not(phase_shifter_type == -1)) + tap_no_table = np.logical_and(~tap_dependency, np.logical_not(phase_shifter_type == -1)) if any(tap_table): id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: @@ -598,15 +604,17 @@ def _calc_tap_from_dataframe(net, trafo_df): 'mask': mask }) - filtered_df = net.trafo_characteristic_table.merge(filter[filter['mask']], on=['id_characteristic', 'step']) + filtered_df = net.trafo_characteristic_table.merge(filter[filter['mask']], + on=['id_characteristic', 'step']) vn[mask] = vn[mask] * filtered_df['voltage_ratio'] trafo_shift[mask] += filtered_df['angle_deg'] if any(tap_no_table): tap_ideal = np.logical_and(phase_shifter_type == 2, tap_no_table) - tap_complex = np.logical_and(np.logical_or(phase_shifter_type == 0, phase_shifter_type == 1), tap_no_table) + tap_complex = np.logical_and(np.logical_or(phase_shifter_type == 0, phase_shifter_type == 1), + tap_no_table) for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: - mask_ideal = ((tap_ideal) & (tap_side == side)) - mask_complex = ((tap_complex) & (tap_side == side)) + mask_ideal = (tap_ideal & (tap_side == side)) + mask_complex = (tap_complex & (tap_side == side)) if any(mask_ideal): degree_is_set = _replace_nan(tap_step_degree[mask_ideal]) != 0 percent_is_set = _replace_nan(tap_step_percent[mask_ideal]) != 0 @@ -614,10 +622,10 @@ def _calc_tap_from_dataframe(net, trafo_df): raise UserWarning( "Both tap_step_degree and tap_step_percent set for ideal phase shifter") trafo_shift[mask_ideal] += np.where( - (degree_is_set), - (direction * tap_diff[phase_shifter_type == 2] * tap_step_degree[phase_shifter_type == 2]), - (direction * 2 * np.rad2deg(np.arcsin(tap_diff[phase_shifter_type == 2] * \ - tap_step_percent[phase_shifter_type == 2] / 100 / 2))) + degree_is_set, + (direction * tap_diff[mask_ideal] * tap_step_degree[mask_ideal]), + (direction * 2 * np.rad2deg(np.arcsin(tap_diff[mask_ideal] * \ + tap_step_percent[mask_ideal] / 100 / 2))) ) elif any(mask_complex): tap_steps = tap_step_percent[mask_complex] * tap_diff[mask_complex] / 100 @@ -626,7 +634,7 @@ def _calc_tap_from_dataframe(net, trafo_df): du = u1 * _replace_nan(tap_steps) vn[mask_complex] = np.sqrt((u1 + du * cos(tap_angles)) ** 2 + (du * sin(tap_angles)) ** 2) trafo_shift[mask_complex] += (arctan(direction * du * sin(tap_angles) / - (u1 + du * cos(tap_angles)))) + (u1 + du * cos(tap_angles)))) else: tap_phase_shifter = get_trafo_values(trafo_df, f"tap{t}_phase_shifter") for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: @@ -648,9 +656,9 @@ def _calc_tap_from_dataframe(net, trafo_df): raise UserWarning( "Both tap_step_degree and tap_step_percent set for ideal phase shifter") trafo_shift[tap_ideal] += np.where( - (degree_is_set), + degree_is_set, (direction * tap_diff[tap_ideal] * tap_step_degree[tap_ideal]), - (direction * 2 * np.rad2deg(np.arcsin(tap_diff[tap_ideal] * \ + (direction * 2 * np.rad2deg(np.arcsin(tap_diff[tap_ideal] * tap_step_percent[tap_ideal] / 100 / 2))) ) return vnh, vnl, trafo_shift @@ -667,7 +675,7 @@ def _get_vk_values_from_table(trafo_df, trafo_characteristic_table, trafotype="2 vk_variables = ("vk_percent", "vkr_percent") elif trafotype == "3W": vk_variables = ("vk_hv_percent", "vkr_hv_percent", "vk_mv_percent", "vkr_mv_percent", - "vk_lv_percent", "vkr_lv_percent") + "vk_lv_percent", "vkr_lv_percent") else: raise UserWarning("Unknown trafotype") @@ -708,7 +716,7 @@ def _get_vk_values(trafo_df, characteristic, trafotype="2W"): vk_variables = ("vk_percent", "vkr_percent") elif trafotype == "3W": vk_variables = ("vk_hv_percent", "vkr_hv_percent", "vk_mv_percent", "vkr_mv_percent", - "vk_lv_percent", "vkr_lv_percent") + "vk_lv_percent", "vkr_lv_percent") else: raise UserWarning("Unknown trafotype") @@ -729,7 +737,8 @@ def _get_vk_values(trafo_df, characteristic, trafotype="2W"): if characteristic is None: raise UserWarning("tap_dependent_impedance of transformers requires net.characteristic") - # if any but 1 characteristic is missing per trafo, we assume it's by design; but if all are misiing, we raise error + # if any but 1 characteristic is missing per trafo, we assume it's by design; + # but if all are missing, we raise an error # first, we read all characteristic indices # we also allow that some columns are not included in the net.trafo table all_columns = trafo_df.keys() if isinstance(trafo_df, dict) else trafo_df.columns.values @@ -738,11 +747,12 @@ def _get_vk_values(trafo_df, characteristic, trafotype="2W"): raise UserWarning(f"At least one of the columns for characteristics " f"({[v+'_characteristic' for v in vk_variables]}) " f"must be defined for {trafotype} trafo") - # must cast to float64 unfortunately, because numpy.vstack casts arrays to object because it doesn't know pandas.NA, np.isnan fails + # must cast to float64 unfortunately, because numpy.vstack casts arrays to object + # because it doesn't know pandas.NA, np.isnan fails all_characteristic_idx = np.vstack([get_trafo_values( trafo_df, f"{c}_characteristic").astype(np.float64) for c in char_columns]).T index_column = {c: i for i, c in enumerate(char_columns)} - # now we check if any trafos that have tap_dependent_impedance have all of the characteristics missing + # now we check if any trafos that have tap_dependent_impedance have all characteristics missing all_missing = np.isnan(all_characteristic_idx).all(axis=1) & tap_dependent_impedance if np.any(all_missing): trafo_index = trafo_df['index'] if isinstance(trafo_df, dict) else trafo_df.index.values @@ -764,8 +774,8 @@ def _get_vk_values(trafo_df, characteristic, trafotype="2W"): def _calc_tap_dependent_value(tap_pos, value, tap_dependent_impedance, characteristic, characteristic_idx): -# todo expand to include voltage_ratio & angle_deg or probably better to write own function - # we skip the trafos with NaN characteristics even if tap_dependent_impedance is True (we already checked for missing characteristics) + # we skip the trafos with NaN characteristics even if tap_dependent_impedance is True + # (we already checked for missing characteristics) relevant_idx = tap_dependent_impedance & ~np.isnan(characteristic_idx) vk_characteristic = np.zeros_like(tap_dependent_impedance, dtype="object") vk_characteristic[relevant_idx] = characteristic.loc[characteristic_idx[relevant_idx], 'object'].values @@ -836,7 +846,7 @@ def _calc_nominal_ratio_from_dataframe(ppc, trafo_df, vn_hv_kv, vn_lv_kv, bus_lo OUTPUT: **tab** (1d array, float) - The off-nominal tap ratio """ - # Calculating tab (trasformer off nominal turns ratio) + # Calculating tab (transformer off nominal turns ratio) tap_rat = vn_hv_kv / vn_lv_kv hv_bus = get_trafo_values(trafo_df, "hv_bus") lv_bus = get_trafo_values(trafo_df, "lv_bus") @@ -892,7 +902,8 @@ def _calc_tcsc_parameter(net, ppc): tcsc[f:t, TCSC_MAX_FIRING_ANGLE] = np.deg2rad(net["tcsc"]["max_angle_degree"].values) tcsc[f:t, TCSC_STATUS] = net["tcsc"]["in_service"].values - tcsc[f:t, TCSC_CONTROLLABLE] = net["tcsc"]["controllable"].values.astype(bool) & net["tcsc"]["in_service"].values.astype(bool) + tcsc[f:t, TCSC_CONTROLLABLE] = (net["tcsc"]["controllable"].values.astype(bool) & + net["tcsc"]["in_service"].values.astype(bool)) def _calc_impedance_parameters_from_dataframe(net, zero_sequence=False): @@ -914,9 +925,9 @@ def _calc_impedance_parameters_from_dataframe(net, zero_sequence=False): sn_net = net.sn_mva # background for the sn_calculations in the next lines: - # r_ij_ohm = r_ij * v**2 / sn_impedance - # r_ij_pu_branch = r_ij_ohm / (v**2 / sn_net) - # r_ij_pu_branch = r_ij / sn_impedance / (1 / sn_net) + # r_ij_ohm = r_ij * v**2 / sn_impedance + # r_ij_pu_branch = r_ij_ohm / (v**2 / sn_net) + # r_ij_pu_branch = r_ij / sn_impedance / (1 / sn_net) r_f = (rij * sn_factor) / sn_impedance * sn_net x_f = (xij * sn_factor) / sn_impedance * sn_net @@ -1149,7 +1160,7 @@ def _calc_switch_parameter(net, ppc): **RETURN**: **t** - Temporary line parameter. Which is a complex128 - Nunmpy array. with the following order: + Numpy array. with the following order: 0:bus_a; 1:bus_b; 2:r_pu; 3:x_pu; 4:b_pu """ rx_ratio = net["_options"]["switch_rx_ratio"] @@ -1279,11 +1290,11 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): mode = net._options["mode"] t3 = net["trafo3w"] # todo check magnetizing impedance implementation: - #loss_side = net._options["trafo3w_losses"].lower() + # loss_side = net._options["trafo3w_losses"].lower() loss_side = t3.loss_side.values if "loss_side" in t3.columns else np.full(len(t3), net._options["trafo3w_losses"].lower()) nr_trafos = len(net["trafo3w"]) - if sequence==1: + if sequence == 1: if 'tap_dependency_table' in t3: mode_tmp = "type_c" if mode == "sc" and net._options.get("use_pre_fault_voltage", False) else mode _calculate_sc_voltages_of_equivalent_transformers(t3, trafo2, mode_tmp, net=net) @@ -1291,7 +1302,7 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): mode_tmp = "type_c" if mode == "sc" and net._options.get("use_pre_fault_voltage", False) else mode _calculate_sc_voltages_of_equivalent_transformers(t3, trafo2, mode_tmp, characteristic=net.get( 'characteristic'), update_vk_values=update_vk_values) - elif sequence==0: + elif sequence == 0: if mode != "sc": raise NotImplementedError( "0 seq impedance calculation only implemented for short-circuit calculation!") @@ -1305,8 +1316,8 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): trafo2["lv_bus"] = {"hv": aux_buses, "mv": t3.mv_bus.values, "lv": t3.lv_bus.values} trafo2["in_service"] = {side: t3.in_service.values for side in sides} # todo check magnetizing impedance implementation: - #trafo2["i0_percent"] = {side: t3.i0_percent.values if loss_side == side else zeros for side in sides} - #trafo2["pfe_kw"] = {side: t3.pfe_kw.values if loss_side == side else zeros for side in sides} + # trafo2["i0_percent"] = {side: t3.i0_percent.values if loss_side == side else zeros for side in sides} + # trafo2["pfe_kw"] = {side: t3.pfe_kw.values if loss_side == side else zeros for side in sides} trafo2["i0_percent"] = {side: np.where(loss_side == side, t3.i0_percent.values, zeros) for side in sides} trafo2["pfe_kw"] = {side: np.where(loss_side == side, t3.pfe_kw.values, zeros) for side in sides} trafo2["vn_hv_kv"] = {side: t3.vn_hv_kv.values for side in sides} @@ -1322,30 +1333,35 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): trafo2["parallel"] = {side: np.ones(nr_trafos) for side in sides} trafo2["df"] = {side: np.ones(nr_trafos) for side in sides} # even though this is not relevant (at least now), the values cannot be empty: - trafo2["leakage_resistance_ratio_hv"] = {side: np.full(nr_trafos, fill_value=0.5, dtype=np.float64) for side in sides} - trafo2["leakage_reactance_ratio_hv"] = {side: np.full(nr_trafos, fill_value=0.5, dtype=np.float64) for side in sides} + trafo2["leakage_resistance_ratio_hv"] = { + side: np.full(nr_trafos, fill_value=0.5, dtype=np.float64) for side in sides} + trafo2["leakage_reactance_ratio_hv"] = { + side: np.full(nr_trafos, fill_value=0.5, dtype=np.float64) for side in sides} if "max_loading_percent" in net.trafo3w: trafo2["max_loading_percent"] = {side: net.trafo3w.max_loading_percent.values for side in sides} return {var: np.concatenate([trafo2[var][side] for side in sides]) for var in trafo2.keys()} -def _calculate_sc_voltages_of_equivalent_transformers(t3, t2, mode, characteristic=None, update_vk_values=True, net=None): +def _calculate_sc_voltages_of_equivalent_transformers( + t3, t2, mode, characteristic=None, update_vk_values=True, net=None): if "tap_dependency_table" in t3: tap_dependency_table = get_trafo_values(t3, "tap_dependency_table") tap_dependency_table = np.array( [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency_table]) if any(tap_dependency_table): - vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = _get_vk_values_from_table(t3, net.trafo_characteristic_table, "3W") + vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = _get_vk_values_from_table( + t3, net.trafo_characteristic_table, "3W") else: vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = ( - t3['vk_hv_percent'], t3['vkr_hv_percent'], t3['vk_mv_percent'], - t3['vkr_mv_percent'], t3['vk_lv_percent'], t3['vkr_lv_percent']) + t3['vk_hv_percent'], t3['vkr_hv_percent'], t3['vk_mv_percent'], + t3['vkr_mv_percent'], t3['vk_lv_percent'], t3['vkr_lv_percent']) else: if update_vk_values: vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = _get_vk_values(t3, characteristic, "3W") else: - vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = (t3['vk_hv_percent'], t3['vkr_hv_percent'], t3['vk_mv_percent'], - t3['vkr_mv_percent'], t3['vk_lv_percent'], t3['vkr_lv_percent']) + vk_hv, vkr_hv, vk_mv, vkr_mv, vk_lv, vkr_lv = ( + t3['vk_hv_percent'], t3['vkr_hv_percent'], t3['vk_mv_percent'], + t3['vkr_mv_percent'], t3['vk_lv_percent'], t3['vkr_lv_percent']) vk_3w = np.stack([vk_hv, vk_mv, vk_lv]) vkr_3w = np.stack([vkr_hv, vkr_mv, vkr_lv]) @@ -1432,7 +1448,8 @@ def _calculate_3w_tap_changers(t3, t2, sides): # t3 trafos with tap changer at star points if any_at_star_point & np.any(mask_star_point := (tap_mask & at_star_point)): - t = tap_arrays["tap_step_percent"][side][mask_star_point] * np.exp(1j * np.deg2rad(tap_arrays["tap_step_degree"][side][mask_star_point])) + t = (tap_arrays["tap_step_percent"][side][mask_star_point] * + np.exp(1j * np.deg2rad(tap_arrays["tap_step_degree"][side][mask_star_point]))) tap_pos = tap_arrays["tap_pos"][side][mask_star_point] tap_neutral = tap_arrays["tap_neutral"][side][mask_star_point] t_corrected = 100 * t / (100 + (t * (tap_pos-tap_neutral))) diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index 6b6b51d7e..91540f8e5 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -177,9 +177,10 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. contingency_evaluation_function(net, **kwargs) trafo_flag = False - if np.any(net.trafo.tap_phase_shifter): - trafo_flag = True - tap_phase_shifter, tap_pos, shift_degree = _convert_trafo_phase_shifter(net) + if "tap_phase_shifter" in net.trafo.columns: + if np.any(net.trafo.tap_phase_shifter): + trafo_flag = True + tap_phase_shifter, tap_pos, shift_degree = _convert_trafo_phase_shifter(net) # setting "slack" back-and-forth is due to the difference in interpretation of generators as "distributed slack" if net._options.get("distributed_slack", False): diff --git a/pandapower/control/__init__.py b/pandapower/control/__init__.py index c2905f713..a167ce4bd 100644 --- a/pandapower/control/__init__.py +++ b/pandapower/control/__init__.py @@ -19,6 +19,6 @@ # --- Other --- from pandapower.control.run_control import * from pandapower.control.util.characteristic import Characteristic, SplineCharacteristic -from pandapower.control.util.auxiliary import (get_controller_index, plot_characteristic, create_trafo_characteristics, +from pandapower.control.util.auxiliary import (get_controller_index, plot_characteristic, _create_trafo_characteristics, create_trafo_characteristic_object) from pandapower.control.util.diagnostic import control_diagnostic, trafo_characteristic_table_diagnostic diff --git a/pandapower/control/util/auxiliary.py b/pandapower/control/util/auxiliary.py index b1a99479d..d9c647d7d 100644 --- a/pandapower/control/util/auxiliary.py +++ b/pandapower/control/util/auxiliary.py @@ -232,8 +232,8 @@ def create_trafo_characteristic_object(net): y_points = {col: [characteristic_df[col].tolist()] for col in variables_filtered} logger.info("Adding characteristic objects for 2w-trafo with trafo_id %s and variables " "%s" % (trafo_id, variables_filtered)) - create_trafo_characteristics(net, "trafo", [trafo_id], variables_filtered, - x_points, y_points) + _create_trafo_characteristics(net, "trafo", [trafo_id], variables_filtered, + x_points, y_points) logger.info(f"Finished creating tap dependent characteristic objects for 2w-trafos in " f"{time.time() - time_start}.") else: @@ -256,7 +256,7 @@ def create_trafo_characteristic_object(net): y_points = {col: [characteristic_df[col].tolist()] for col in variables_filtered} logger.info("Adding characteristic objects for 3w-trafo with trafo_id %s and variables " "%s" % (trafo_id, variables_filtered)) - create_trafo_characteristics(net, "trafo3w", [trafo_id], variables_filtered, + _create_trafo_characteristics(net, "trafo3w", [trafo_id], variables_filtered, x_points, y_points) logger.info(f"Finished creating tap dependent characteristic objects for 3w-trafos in " f"{time.time() - time_start}.") @@ -273,7 +273,7 @@ def create_trafo_characteristic_object(net): del net["trafo_characteristic_spline_temp"] -def create_trafo_characteristics(net, trafotable, trafo_index, variable, x_points, y_points): +def _create_trafo_characteristics(net, trafotable, trafo_index, variable, x_points, y_points): supported_columns = {"trafo": ["voltage_ratio_characteristic", "angle_deg_characteristic", "vk_percent_characteristic", "vkr_percent_characteristic"], "trafo3w": ["voltage_ratio_characteristic", "angle_deg_characteristic", @@ -334,8 +334,8 @@ def create_shunt_characteristic_object(net): y_points = {col: [characteristic_df[col].tolist()] for col in variables_filtered} logger.info("Adding characteristic objects for shunt with shunt_id %s and variables " "%s" % (shunt_id, variables_filtered)) - create_shunt_characteristics(net, [shunt_id], variables_filtered, - x_points, y_points) + _create_shunt_characteristics(net, [shunt_id], variables_filtered, + x_points, y_points) logger.info(f"Finished creating step dependent power characteristic objects for shunts in" f"{time.time() - time_start}.") else: @@ -351,7 +351,7 @@ def create_shunt_characteristic_object(net): del net["shunt_characteristic_spline_temp"] -def create_shunt_characteristics(net, shunt_index, variable, x_points, y_points): +def _create_shunt_characteristics(net, shunt_index, variable, x_points, y_points): supported_columns = ["q_mvar_characteristic", "p_mw_characteristic"] # create id_characteristic_spline column - same indices as id_characteristic_table diff --git a/pandapower/convert_format.py b/pandapower/convert_format.py index 7c85053a2..dd19e295f 100644 --- a/pandapower/convert_format.py +++ b/pandapower/convert_format.py @@ -95,6 +95,8 @@ def correct_dtypes(net, error): raised. """ empty_net = create_empty_network() + empty_net.trafo['tap_phase_shifter_type'] = empty_net.trafo['tap_phase_shifter_type'].astype("Int64") + empty_net.trafo3w['tap_phase_shifter_type'] = empty_net.trafo3w['tap_phase_shifter_type'].astype("Int64") not_corrected = list() failed = dict() for key, table in empty_net.items(): diff --git a/pandapower/converter/powerfactory/pp_import_functions.py b/pandapower/converter/powerfactory/pp_import_functions.py index 065cd3364..63af4774d 100644 --- a/pandapower/converter/powerfactory/pp_import_functions.py +++ b/pandapower/converter/powerfactory/pp_import_functions.py @@ -2434,10 +2434,10 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc # todo # vk0_min, vk0_max = pf_type.uk0tmn, pf_type.uk0tmx # vkr0_min, vkr0_max = pf_type.uk0rtmn, pf_type.uk0rtmx - pp.control.create_trafo_characteristics(net, trafotable="trafo", trafo_index=tid, variable="vk_percent", - x_points=x_points, y_points=(vk_min, vk_neutral, vk_max)) - pp.control.create_trafo_characteristics(net, trafotable="trafo", trafo_index=tid, variable="vkr_percent", - x_points=x_points, y_points=(vkr_min, vkr_neutral, vkr_max)) + pp.control._create_trafo_characteristics(net, trafotable="trafo", trafo_index=tid, variable="vk_percent", + x_points=x_points, y_points=(vk_min, vk_neutral, vk_max)) + pp.control._create_trafo_characteristics(net, trafotable="trafo", trafo_index=tid, variable="vkr_percent", + x_points=x_points, y_points=(vkr_min, vkr_neutral, vkr_max)) def get_pf_trafo_results(net, item, tid, is_unbalanced): @@ -2594,12 +2594,12 @@ def create_trafo3w(net, item, tap_opt='nntap'): vkr_neutral = net.trafo3w.at[tid, f"vkr_{side}_percent"] vkr_max = ga(pf_type, f"uktrr3mx_{side[0]}") # todo zero-sequence parameters (must be implemented in build_branch first) - pp.control.create_trafo_characteristics(net, trafotable="trafo3w", trafo_index=tid, - variable=f"vk_{side}_percent", x_points=x_points, - y_points=(vk_min, vk_neutral, vk_max)) - pp.control.create_trafo_characteristics(net, trafotable="trafo3w", trafo_index=tid, - variable=f"vkr_{side}_percent", x_points=x_points, - y_points=(vkr_min, vkr_neutral, vkr_max)) + pp.control._create_trafo_characteristics(net, trafotable="trafo3w", trafo_index=tid, + variable=f"vk_{side}_percent", x_points=x_points, + y_points=(vk_min, vk_neutral, vk_max)) + pp.control._create_trafo_characteristics(net, trafotable="trafo3w", trafo_index=tid, + variable=f"vkr_{side}_percent", x_points=x_points, + y_points=(vkr_min, vkr_neutral, vkr_max)) def propagate_bus_coords(net, bus1, bus2): diff --git a/pandapower/create.py b/pandapower/create.py index 48aa972bf..7b3934328 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -246,7 +246,7 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("tap_step_percent", "f8"), ("tap_step_degree", "f8"), ("tap_pos", "i4"), - ("tap_phase_shifter_type", 'i4'), + ("tap_phase_shifter_type", "i4"), ('id_characteristic_table', 'u4'), ('tap_dependency_table', 'bool'), ("parallel", "u4"), diff --git a/pandapower/grid_equivalents/auxiliary.py b/pandapower/grid_equivalents/auxiliary.py index f063bf18b..1ea48a8e5 100644 --- a/pandapower/grid_equivalents/auxiliary.py +++ b/pandapower/grid_equivalents/auxiliary.py @@ -498,7 +498,7 @@ def adaptation_phase_shifter(net, v_boundary, p_boundary): pfe_kw=.0, i0_percent=.0, # shift_degree=-phase_errors[idx], tap_step_degree=-phase_errors[idx], - # tap_phase_shifter=True, + # tap_phase_shifter_type=2, name="phase_shifter_adapter_"+str(lb)) # pp.create_load(net, lb, -p_errors[idx], -q_errors[idx], # name="phase_shifter_adapter_"+str(lb)) diff --git a/pandapower/networks/create_examples.py b/pandapower/networks/create_examples.py index 699ed7a89..18a3bedcf 100644 --- a/pandapower/networks/create_examples.py +++ b/pandapower/networks/create_examples.py @@ -203,7 +203,7 @@ def example_multivoltage(): pfe_kw=0.95, i0_percent=0.2375, tap_side="hv", tap_neutral=0, tap_min=-2, tap_max=2, tap_step_percent=2.5, tap_pos=0, - shift_degree=150, name='MV-LV-Trafo') + shift_degree=150, name='MV-LV-Trafo', tap_phase_shifter_type=0) # Trafo3w hv_bus = pp.get_element_index(net, "bus", "Bus HV2") @@ -218,7 +218,7 @@ def example_multivoltage(): pfe_kw=0, i0_percent=0, shift_mv_degree=30, shift_lv_degree=30, tap_side="hv", tap_neutral=0, tap_min=-8, tap_max=8, tap_step_percent=1.25, - tap_pos=0, name='HV-MV-MV-Trafo') + tap_pos=0, name='HV-MV-MV-Trafo', tap_phase_shifter_type=0) # --- Static generators diff --git a/pandapower/test/api/test_auxiliary.py b/pandapower/test/api/test_auxiliary.py index 5a77d776c..a4a083673 100644 --- a/pandapower/test/api/test_auxiliary.py +++ b/pandapower/test/api/test_auxiliary.py @@ -290,26 +290,26 @@ def test_create_trafo_characteristics(): # invalid variable with pytest.raises(UserWarning): - pp.control.create_trafo_characteristics(net, "trafo3w", 0, 'vk_percent', - [-8, -4, 0, 4, 8], [8.1, 9.1, 10.1, 11.1, 12.1]) + pp.control._create_trafo_characteristics(net, "trafo3w", 0, 'vk_percent', + [-8, -4, 0, 4, 8], [8.1, 9.1, 10.1, 11.1, 12.1]) # invalid shapes with pytest.raises(UserWarning): - pp.control.create_trafo_characteristics(net, "trafo3w", 0, 'vk_hv_percent', - [-8, -4, 0, 4, 8], [8.1, 9.1, 10.1, 11.1]) + pp.control._create_trafo_characteristics(net, "trafo3w", 0, 'vk_hv_percent', + [-8, -4, 0, 4, 8], [8.1, 9.1, 10.1, 11.1]) with pytest.raises(UserWarning): - pp.control.create_trafo_characteristics(net, "trafo3w", [0], 'vk_hv_percent', - [-8, -4, 0, 4, 8], [8.1, 9.1, 10.1, 11.1, 12.1]) + pp.control._create_trafo_characteristics(net, "trafo3w", [0], 'vk_hv_percent', + [-8, -4, 0, 4, 8], [8.1, 9.1, 10.1, 11.1, 12.1]) with pytest.raises(UserWarning): - pp.control.create_trafo_characteristics(net, "trafo3w", [0, 1], 'vk_hv_percent', - [[-8, -4, 0, 4, 8]], [[8.1, 9.1, 10.1, 11.1, 12.1]]) + pp.control._create_trafo_characteristics(net, "trafo3w", [0, 1], 'vk_hv_percent', + [[-8, -4, 0, 4, 8]], [[8.1, 9.1, 10.1, 11.1, 12.1]]) with pytest.raises(UserWarning): - pp.control.create_trafo_characteristics(net, "trafo3w", [0, 1], 'vk_hv_percent', - [[-8, -4, 0, 4, 8], [-8, -4, 0, 4, 8]], - [[8.1, 9.1, 10.1, 11.1, 12.1]]) + pp.control._create_trafo_characteristics(net, "trafo3w", [0, 1], 'vk_hv_percent', + [[-8, -4, 0, 4, 8], [-8, -4, 0, 4, 8]], + [[8.1, 9.1, 10.1, 11.1, 12.1]]) @pytest.mark.parametrize("file_io", (False, True), ids=("Without JSON I/O", "With JSON I/O")) diff --git a/pandapower/test/contingency/test_contingency.py b/pandapower/test/contingency/test_contingency.py index a2a07fe2e..e171a2961 100644 --- a/pandapower/test/contingency/test_contingency.py +++ b/pandapower/test/contingency/test_contingency.py @@ -165,7 +165,7 @@ def test_unequal_trafo_hv_lv_impedances(): pp.create_transformer_from_parameters(net, 1, 2, 150, 110, 110, 0.5, 10, 15, 0.1, 150, 'hv', 0, 10, -10, 0, - 1, 5, max_loading_percent=100, + 1, 5, max_loading_percent=100, tap_phase_shifter_type=2, leakage_resistance_ratio_hv=0.2, leakage_reactance_ratio_hv=0.4) pp.create_lines(net, [2, 2], [3, 3], 25, "243-AL1/39-ST1A 110.0", max_loading_percent=100) @@ -225,7 +225,7 @@ def test_lightsim2grid_phase_shifters(): pp.create_lines(net, [0, 0], [1, 1], 40, "243-AL1/39-ST1A 110.0", max_loading_percent=100) pp.create_transformer_from_parameters(net, 1, 2, 150, 110, 110, 0.5, 10, 15, 0.1, 150, - 'hv', 0, 10, -10, 0, 1, 5, True, max_loading_percent=100) + 'hv', 0, 10, -10, 0, 1, 5, 2, max_loading_percent=100) pp.create_lines(net, [2, 2], [3, 3], 25, "243-AL1/39-ST1A 110.0", max_loading_percent=100) pp.create_load(net, 3, 110) @@ -238,7 +238,7 @@ def test_lightsim2grid_phase_shifters(): assert net.trafo.shift_degree.values[0] == 150 assert net.trafo.tap_pos.values[0] == 5 - assert net.trafo.tap_phase_shifter.values[0] + assert net.trafo.tap_phase_shifter_type.values[0] == 2 assert np.array_equal(res["line"]["causes_overloading"], net.res_line.causes_overloading.values) if len(net.trafo) > 0: diff --git a/pandapower/test/control/test_tap_dependent_impedance.py b/pandapower/test/control/test_tap_dependent_impedance.py index ccc0ad3f9..4c58d9761 100644 --- a/pandapower/test/control/test_tap_dependent_impedance.py +++ b/pandapower/test/control/test_tap_dependent_impedance.py @@ -18,7 +18,10 @@ def test_tap_dependent_impedance_control(): b1 = pp.create_bus(net, 110) b2 = pp.create_bus(net, 20) pp.create_ext_grid(net, b1) - pp.create_transformer_from_parameters(net, b1, b2, 40, 110, 21, 0.5, 12.3, 25, 0.11, 0, 'hv', 10, 20, 0, 1.8, 180, 10) + pp.create_transformer_from_parameters(net, b1, b2, 40, 110, 21, 0.5, + 12.3, 25, 0.11, 0, 'hv', + 10, 20, 0, 1.8, 180, + 10, tap_phase_shifter_type=0) characteristic_vk = Characteristic.from_points(net, ((0, 13.5), (10, 12.3), (20, 11.1))) characteristic_vkr = Characteristic.from_points(net, ((0, 0.52), (10, 0.5), (20, 0.53))) @@ -46,7 +49,10 @@ def test_tap_dependent_impedance_restore(): b2 = pp.create_bus(net, 20) pp.create_ext_grid(net, b1) pp.create_load(net, b2, 20) - pp.create_transformer_from_parameters(net, b1, b2, 40, 110, 21, 0.5, 12.3, 25, 0.11, 0, 'hv', 10, 20, 0, 1.8, 180, 10) + pp.create_transformer_from_parameters(net, b1, b2, 40, 110, 21, 0.5, + 12.3, 25, 0.11, 0, 'hv', + 10, 20, 0, 1.8, 180, + 10, tap_phase_shifter_type=0) characteristic_vk = Characteristic.from_points(net, ((0, 13.5), (10, 12.3), (20, 11.1))) characteristic_vkr = Characteristic.from_points(net, ((0, 0.52), (10, 0.5), (20, 0.53))) diff --git a/pandapower/test/grid_equivalents/test_get_equivalent.py b/pandapower/test/grid_equivalents/test_get_equivalent.py index 1f0f926a7..ad831396c 100644 --- a/pandapower/test/grid_equivalents/test_get_equivalent.py +++ b/pandapower/test/grid_equivalents/test_get_equivalent.py @@ -476,8 +476,8 @@ def test_switch_sgens(): def test_characteristic(): net = pp.networks.example_multivoltage() - pp.control.create_trafo_characteristics(net, "trafo", [1], 'vk_percent', - [[-2,-1,0,1,2]], [[2,3,4,5,6]]) + pp.control._create_trafo_characteristics(net, "trafo", [1], 'vk_percent', + [[-2,-1,0,1,2]], [[2,3,4,5,6]]) pp.runpp(net) net_eq = pp.grid_equivalents.get_equivalent(net, "rei", [41], [0]) assert len(net_eq.characteristic) == 1 diff --git a/pandapower/test/helper_functions.py b/pandapower/test/helper_functions.py index 02945ca09..bd6d0e350 100644 --- a/pandapower/test/helper_functions.py +++ b/pandapower/test/helper_functions.py @@ -47,7 +47,7 @@ def create_test_network(): tap_pos=0, tap_side="hv", tap_min=-2, tap_step_percent=2.5, i0_percent=0.68751, sn_mva=0.016, pfe_kw=0.11, name=None, - in_service=True, index=None) + in_service=True, index=None, tap_phase_shifter_type=0) # 0.016 MVA 10/0.4 kV ET 16/23 SGB pp.create_line_from_parameters(net, b2, b3, 1, name="line1", r_ohm_per_km=0.2067, diff --git a/pandapower/test/loadflow/test_results.py b/pandapower/test/loadflow/test_results.py index 70306c27c..da5904bc8 100644 --- a/pandapower/test/loadflow/test_results.py +++ b/pandapower/test/loadflow/test_results.py @@ -30,7 +30,7 @@ def add_trafo_connection(net, hv_bus, trafotype="2W"): vn_hv_kv=20., vn_mv_kv=0.9, vn_lv_kv=0.45, sn_hv_mva=0.6, sn_mv_mva=0.5, sn_lv_mva=0.4, vk_hv_percent=1., vk_mv_percent=1., vk_lv_percent=1., vkr_hv_percent=0.3, vkr_mv_percent=0.3, vkr_lv_percent=0.3, - pfe_kw=0.2, i0_percent=0.3, tap_neutral=0., + pfe_kw=0.2, i0_percent=0.3, tap_neutral=0., tap_phase_shifter_type=0, tap_pos=2, tap_step_percent=1., tap_min=-2, tap_max=2) else: pp.create_transformer(net, hv_bus=hv_bus, lv_bus=cb, std_type="0.25 MVA 20/0.4 kV", tap_pos=2) diff --git a/pandapower/test/loadflow/test_runpp.py b/pandapower/test/loadflow/test_runpp.py index b71da8a42..89ddcc231 100644 --- a/pandapower/test/loadflow/test_runpp.py +++ b/pandapower/test/loadflow/test_runpp.py @@ -1327,7 +1327,8 @@ def test_tap_dependent_impedance(): sn_lv_mva=0.4, vk_hv_percent=1., vk_mv_percent=1., vk_lv_percent=1., vkr_hv_percent=0.3, vkr_mv_percent=0.3, vkr_lv_percent=0.3, pfe_kw=0.2, i0_percent=0.3, tap_neutral=0., tap_side='hv', - tap_pos=0, tap_step_percent=0., tap_min=-2, tap_max=2) + tap_pos=0, tap_step_percent=0., tap_min=-2, tap_max=2, + tap_phase_shifter_type=0) net_backup = net.deepcopy() diff --git a/pandapower/test/loadflow/test_scenarios.py b/pandapower/test/loadflow/test_scenarios.py index bb0c8b85d..c6f44c8f5 100644 --- a/pandapower/test/loadflow/test_scenarios.py +++ b/pandapower/test/loadflow/test_scenarios.py @@ -15,7 +15,7 @@ import pandapower.networks as nw import pandapower.shortcircuit as sc -#TODO: 2 gen 2 ext_grid missing +# TODO: 2 gen 2 ext_grid missing def test_2gen_1ext_grid(): @@ -23,6 +23,7 @@ def test_2gen_1ext_grid(): net.shunt.q_mvar *= -1 pp.create_gen(net, 2, p_mw=0.100) net.trafo.shift_degree = 150 + net.trafo.tap_phase_shifter_type = 0 pp.runpp(net, init='dc', calculate_voltage_angles=True) assert np.allclose(net.res_gen.p_mw.values, [0.100, 0.100]) @@ -47,6 +48,7 @@ def test_0gen_2ext_grid(): pp.create_ext_grid(net, 1) net.gen = net.gen.drop(0) net.trafo.shift_degree = 150 + net.trafo.tap_phase_shifter_type = 0 net.ext_grid.at[1, "in_service"] = False pp.create_ext_grid(net, 3) @@ -73,6 +75,7 @@ def test_0gen_2ext_grid_decoupled(): net.ext_grid.at[2, "in_service"] = False auxbus = pp.create_bus(net, name="bus1", vn_kv=10.) net.trafo.shift_degree = 150 + net.trafo.tap_phase_shifter_type = 0 pp.create_std_type(net, {"type": "cs", "r_ohm_per_km": 0.876, "q_mm2": 35.0, "endtmp_deg": 160.0, "c_nf_per_km": 260.0, "max_i_ka": 0.123, "x_ohm_per_km": 0.1159876}, @@ -214,11 +217,12 @@ def test_transformer_phase_shift(): b3 = pp.create_bus(net, vn_kv=0.4) pp.create_ext_grid(net, b1) pp.create_transformer_from_parameters( - net, b1, b2, 40000, 110, 20, 0.1, 5, 0, 0.1, 30, side, + net, b1, b2, 40000, 110, 20, 0.1, 5, 0, 0.1, + 30, side, # 0, 2, -2, 1.25, 10, 0) - 0, 2, -2, 0, 10, 0, True) + 0, 2, -2, 0, 10, 0, 2) pp.create_transformer_from_parameters( - net, b2, b3, 630, 20, 0.4, 0.1, 5, 0, 0.1, 20, tap_phase_shifter=True) + net, b2, b3, 630, 20, 0.4, 0.1, 5, 0, 0.1, 20) pp.runpp(net, init="dc", calculate_voltage_angles=True) b2a_angle = net.res_bus.va_degree.at[1] b3a_angle = net.res_bus.va_degree.at[2] @@ -254,7 +258,8 @@ def test_transformer_phase_shift_complex(): vn_lv_kv=20, vkr_percent=0.1, vk_percent=5, pfe_kw=0, i0_percent=0.1, shift_degree=30, tap_side=side, tap_neutral=0, tap_max=2, tap_min=-2, - tap_step_percent=2, tap_step_degree=10, tap_pos=0) + tap_step_percent=2, tap_step_degree=10, tap_pos=0, + tap_phase_shifter_type=0) pp.runpp(net, init="dc", calculate_voltage_angles=True) assert np.isclose(net.res_bus.vm_pu.at[b2], test_ref[0], rtol=1e-4) assert np.isclose(net.res_bus.va_degree.at[b2], test_ref[1], rtol=1e-4) @@ -300,7 +305,7 @@ def test_transformer3w_phase_shift(): shift_lv_degree=60, tap_side=side, tap_step_percent=2, tap_step_degree=10, tap_pos=0, tap_neutral=0, tap_min=-2, - tap_max=2) + tap_max=2, tap_phase_shifter_type=0) pp.runpp(net, init="dc", calculate_voltage_angles=True) assert np.isclose(net.res_bus.vm_pu.at[b2], test_ref[0][0], rtol=1e-4) assert np.isclose(net.res_bus.va_degree.at[b2], test_ref[0][1], rtol=1e-4) @@ -394,7 +399,7 @@ def test_oos_buses_at_trafo3w(): tidx = pp.create_transformer3w( net, b3, b4, b5, std_type='63/25/38 MVA 110/20/10 kV', in_service=True) - pp.runpp(net, trafo3w_losses = 'star', trafo_model= 'pi', init='flat') + pp.runpp(net, trafo3w_losses='star', trafo_model='pi', init='flat') assert net.res_line.loading_percent.at[l1] > 0 assert np.isnan(net.res_trafo3w.i_hv_ka.at[tidx]) @@ -419,8 +424,8 @@ def network_with_trafo3ws(): vkr_lv_percent=.01, pfe_kw=.5, i0_percent=0.1, name="test", index=pp.get_free_id(net.trafo3w) + 1, tap_side="hv", tap_pos=2, tap_step_percent=1.25, - tap_min=-5, tap_neutral=0, tap_max=5) - return (net, t3, hv, mv, lv) + tap_min=-5, tap_neutral=0, tap_max=5, tap_phase_shifter_type=0) + return net, t3, hv, mv, lv def test_trafo3w_switches(network_with_trafo3ws): @@ -561,7 +566,6 @@ def test_switch_results(): pp.create_load(net, new_bus, p_mw=1.5) open_bb_switch = pp.create_switch(net, bus=new_bus, element=6, et="b", closed=False) - pp.runpp(net) assert np.isclose(net.res_switch.i_ka.at[open_line_switch], 0) @@ -579,7 +583,6 @@ def test_switch_results(): assert np.isclose(net.res_switch.i_ka.at[switch_trafo_hv], abs(net.res_trafo.i_hv_ka.at[trafo])) assert np.isclose(net.res_switch.i_ka.at[switch_trafo_lv], abs(net.res_trafo.i_lv_ka.at[trafo])) - sc.calc_sc(net, branch_results=True) assert np.isclose(net.res_switch_sc.ikss_ka.at[open_line_switch], 0) diff --git a/pandapower/test/opf/test_basic.py b/pandapower/test/opf/test_basic.py index ec63d061e..eccac3620 100644 --- a/pandapower/test/opf/test_basic.py +++ b/pandapower/test/opf/test_basic.py @@ -253,7 +253,7 @@ def test_opf_gen_voltage(): vn_hv_kv=10.0, vkr_percent=2.8125, tap_pos=0, tap_side="hv", tap_min=-2, tap_step_percent=2.5, i0_percent=0.68751, - sn_mva=0.016, pfe_kw=0.11, name=None, + sn_mva=0.016, pfe_kw=0.11, name=None, tap_phase_shifter_type=0, in_service=True, index=None, max_loading_percent=200) pp.create_gen(net, 3, p_mw=0.01, controllable=True, min_p_mw=0, max_p_mw=0.025, max_q_mvar=0.5, min_q_mvar=-0.5) @@ -299,7 +299,7 @@ def test_opf_sgen_voltage(): vn_hv_kv=10.0, vkr_percent=2.8125, tap_pos=0, tap_side="hv", tap_min=-2, tap_step_percent=2.5, i0_percent=0.68751, - sn_mva=0.016, pfe_kw=0.11, name=None, + sn_mva=0.016, pfe_kw=0.11, name=None, tap_phase_shifter_type=0, in_service=True, index=None, max_loading_percent=1000000) pp.create_sgen(net, 3, p_mw=0.01, controllable=True, min_p_mw=-0.005, max_p_mw=0.015, max_q_mvar=0.025, min_q_mvar=-0.025) @@ -346,7 +346,7 @@ def test_opf_gen_loading(): vn_hv_kv=10.0, vkr_percent=2.8125, tap_pos=0, tap_side="hv", tap_min=-2, tap_step_percent=2.5, i0_percent=0.68751, - sn_mva=0.016, pfe_kw=0.11, name=None, + sn_mva=0.016, pfe_kw=0.11, name=None, tap_phase_shifter_type=0, in_service=True, index=None, max_loading_percent=145) pp.create_gen(net, 3, p_mw=0.01, controllable=True, min_p_mw=0.005, max_p_mw=0.015, max_q_mvar=0.05, min_q_mvar=-0.05) @@ -399,7 +399,7 @@ def test_opf_sgen_loading(): vkr_percent=2.8125, tap_pos=0, tap_side="hv", tap_min=-2, tap_step_percent=2.5, i0_percent=0.68751, sn_mva=0.016, pfe_kw=0.11, name=None, in_service=True, index=None, - max_loading_percent=max_trafo_loading) + max_loading_percent=max_trafo_loading, tap_phase_shifter_type=0) pp.create_sgen(net, 3, p_mw=0.01, controllable=True, min_p_mw=0.005, max_p_mw=.015, max_q_mvar=0.025, min_q_mvar=-0.025) pp.create_poly_cost(net, 0, "sgen", cp1_eur_per_mw=-10) @@ -569,7 +569,7 @@ def test_opf_varying_max_line_loading(): vkr_percent=2.8125, tap_pos=0, tap_side="hv", tap_min=-2, tap_step_percent=2.5, i0_percent=0.68751, sn_mva=0.016, pfe_kw=0.11, name=None, in_service=True, index=None, - max_loading_percent=max_trafo_loading) + max_loading_percent=max_trafo_loading, tap_phase_shifter_type=0) pp.create_sgen(net, 3, p_mw=0.1, controllable=True, min_p_mw=0.005, max_p_mw=0.15, max_q_mvar=0.025, min_q_mvar=-0.025) diff --git a/pandapower/test/shortcircuit/test_1ph.py b/pandapower/test/shortcircuit/test_1ph.py index 105fd73fe..9a0846ed3 100644 --- a/pandapower/test/shortcircuit/test_1ph.py +++ b/pandapower/test/shortcircuit/test_1ph.py @@ -327,7 +327,7 @@ def vde_232(): si0_hv_partial=0.9, pt_percent=12, oltc=True, power_station_unit=True, - xn_ohm=22) + xn_ohm=22, tap_phase_shifter_type=0) pp.create_gen(net, 1, 150, 1, 150, vn_kv=21, xdss_pu=0.14, rdss_ohm=0.002, cos_phi=0.85, power_station_trafo=0, pg_percent=5) diff --git a/pandapower/test/shortcircuit/test_all_currents.py b/pandapower/test/shortcircuit/test_all_currents.py index 2e996ce91..8aaf8f546 100644 --- a/pandapower/test/shortcircuit/test_all_currents.py +++ b/pandapower/test/shortcircuit/test_all_currents.py @@ -80,7 +80,8 @@ def net_transformer_simple(): pp.create_transformer_from_parameters(net, b1, b2, vn_hv_kv=10., vn_lv_kv=0.4, vk_percent=6., vkr_percent=0.5, pfe_kw=14, shift_degree=0.0, tap_side="hv", tap_neutral=0, tap_min=-2, tap_max=2, tap_pos=0, - tap_step_percent=2.5, parallel=1, sn_mva=0.4, i0_percent=0.5) + tap_step_percent=2.5, parallel=1, sn_mva=0.4, i0_percent=0.5, + tap_phase_shifter_type=0) return net @@ -117,7 +118,7 @@ def net_transformer_simple_3(): pp.create_transformer_from_parameters(net, 4, 5, sn_mva=0.4, vn_hv_kv=10., vn_lv_kv=0.4, vk_percent=6., vkr_percent=0.5, pfe_kw=14, i0_percent=0.5, shift_degree=0.0, tap_side="hv", tap_neutral=0, tap_min=-2, tap_max=2, tap_pos=0, - tap_step_percent=2.5, parallel=1) + tap_step_percent=2.5, parallel=1, tap_phase_shifter_type=0) pp.create_lines_from_parameters(net, [0, 3, 5], [1, 4, 6], 1, 0.099, 0.156, 400, 0.457) return net @@ -131,7 +132,7 @@ def net_transformer_simple_4(): pp.create_transformer_from_parameters(net, 7, 8, sn_mva=0.4, vn_hv_kv=10., vn_lv_kv=0.4, vk_percent=6., vkr_percent=0.5, pfe_kw=14, i0_percent=0.5, shift_degree=0.0, tap_side="hv", tap_neutral=0, tap_min=-2, tap_max=2, tap_pos=0, - tap_step_percent=2.5, parallel=1) + tap_step_percent=2.5, parallel=1, tap_phase_shifter_type=0) pp.create_switch(net, 6, 4, "l", closed=True) pp.create_sgen(net, 3, 0, 0, 20, k=1.2, kappa=1) pp.create_load(net, 6, 0.1) @@ -147,10 +148,10 @@ def net_transformer(): pp.create_ext_grid(net, b1a, s_sc_max_mva=100., s_sc_min_mva=40., rx_min=0.1, rx_max=0.1) pp.create_switch(net, b1a, b1b, et="b") pp.create_transformer_from_parameters(net, b1b, b2, vn_hv_kv=11., vn_lv_kv=0.42, vk_percent=6., - vkr_percent=0.5, pfe_kw=14, shift_degree=0.0, + vkr_percent=0.5, pfe_kw=14, shift_degree=0.0, tap_phase_shifter_type=0, tap_side="hv", tap_neutral=0, tap_min=-2, tap_max=2, tap_pos=2, tap_step_percent=2.5, parallel=2, sn_mva=0.4, i0_percent=0.5) - pp.create_shunt(net, b2, q_mvar=0.050, p_mw=0.0500) #adding a shunt shouldn't change the result + pp.create_shunt(net, b2, q_mvar=0.050, p_mw=0.0500) # adding a shunt shouldn't change the result return net diff --git a/pandapower/test/shortcircuit/test_iec60909_4.py b/pandapower/test/shortcircuit/test_iec60909_4.py index 2bd7b5a01..4f69fff75 100644 --- a/pandapower/test/shortcircuit/test_iec60909_4.py +++ b/pandapower/test/shortcircuit/test_iec60909_4.py @@ -76,7 +76,7 @@ def iec_60909_4(): vk0_hv_percent=44.1, vkr0_hv_percent=0.26, vk0_mv_percent=6.299627, vkr0_mv_percent=0.03714286, vk0_lv_percent=6.299627, vkr0_lv_percent=0.03714286, - vector_group="YNyd", + vector_group="YNyd", tap_phase_shifter_type=0, tap_max=10, tap_min=-10, tap_pos=0, tap_neutral=0, tap_side="hv", tap_step_percent=0.1) # vk0 = sqrt(vkr0^2 + vki0^2) = sqrt(vkr^2 + (2.1 * vki)^2) = sqrt(vkr^2 + (2.1)^2 * (vk^2 - vkr^2)) pp.create_transformer3w_from_parameters(net, @@ -90,7 +90,7 @@ def iec_60909_4(): vk0_hv_percent=44.1, vkr0_hv_percent=0.26, vk0_mv_percent=6.299627, vkr0_mv_percent=0.03714286, vk0_lv_percent=6.299627, vkr0_lv_percent=0.03714286, - vector_group="Yynd", + vector_group="Yynd", tap_phase_shifter_type=0, tap_max=10, tap_min=-10, tap_pos=0, tap_neutral=0, tap_side="hv", tap_step_percent=0.1) @@ -105,7 +105,7 @@ def iec_60909_4(): vk0_hv_percent=12, vkr0_hv_percent=0.5, vk0_mv_percent=12, vkr0_mv_percent=0.5, vk0_lv_percent=12, vkr0_lv_percent=0.5, - vector_group="Yyd", + vector_group="Yyd", tap_phase_shifter_type=0, tap_max=10, tap_min=-10, tap_pos=0, tap_neutral=0, tap_side="hv", tap_step_percent=0.1) pp.create_transformer3w_from_parameters(net, @@ -119,7 +119,7 @@ def iec_60909_4(): vk0_hv_percent=12, vkr0_hv_percent=0.5, vk0_mv_percent=12, vkr0_mv_percent=0.5, vk0_lv_percent=12, vkr0_lv_percent=0.5, - vector_group="Yynd", + vector_group="Yynd", tap_phase_shifter_type=0, tap_max=10, tap_min=-10, tap_pos=0, tap_neutral=0, tap_side="hv", tap_step_percent=0.1) # reactor is 100 Ohm @@ -287,7 +287,7 @@ def vde_232(): pp.create_ext_grid(net, 0, s_sc_max_mva=13.61213 * 110 * np.sqrt(3), rx_max=0.20328, x0x_max=3.47927, r0x0_max=3.03361) pp.create_transformer_from_parameters(net, 0, 1, 150, 115, 21, 0.5, 16, - pfe_kw=0, i0_percent=0, tap_step_percent=1, + pfe_kw=0, i0_percent=0, tap_step_percent=1, tap_phase_shifter_type=0, tap_max=12, tap_min=-12, tap_neutral=0, tap_side='hv', vector_group="YNd", vk0_percent=np.sqrt(np.square(0.95*15.99219) + np.square(0.5)), diff --git a/pandapower/test/shortcircuit/test_transformer.py b/pandapower/test/shortcircuit/test_transformer.py index 6045e1c41..4f72119c8 100644 --- a/pandapower/test/shortcircuit/test_transformer.py +++ b/pandapower/test/shortcircuit/test_transformer.py @@ -22,7 +22,8 @@ def net_transformer(): pp.create_transformer_from_parameters(net, b1b, b2, vn_hv_kv=11., vn_lv_kv=0.42, vk_percent=6., vkr_percent=0.5, pfe_kw=14, shift_degree=0.0, tap_side="hv", tap_neutral=0, tap_min=-2, tap_max=2, tap_pos=2, - tap_step_percent=2.5, parallel=2, sn_mva=0.4, i0_percent=0.5) + tap_step_percent=2.5, parallel=2, sn_mva=0.4, i0_percent=0.5, + tap_phase_shifter_type=0) # adding a shunt shouldn't change the result: pp.create_shunt(net, b2, q_mvar=0.050, p_mw=0.0500) return net diff --git a/pandapower/test/test_files/save_version.py b/pandapower/test/test_files/save_version.py index 853095c5c..5e50cc68b 100644 --- a/pandapower/test/test_files/save_version.py +++ b/pandapower/test/test_files/save_version.py @@ -9,6 +9,6 @@ net = pp.networks.example_multivoltage() pp.control.DiscreteTapControl(net, 1, 1.02, 1.03) -pp.control.create_trafo_characteristics(net, "trafo", 1, "vk_percent", [-2, 0, 2], [3.5, 4, 4.5]) +pp.control._create_trafo_characteristics(net, "trafo", 1, "vk_percent", [-2, 0, 2], [3.5, 4, 4.5]) pp.runpp(net, run_control=True) pp.to_json(net, os.path.join("old_versions", "example_%s.json" % pp.__version__)) diff --git a/pandapower/test/timeseries/test_timeseries.py b/pandapower/test/timeseries/test_timeseries.py index 0a75f3665..4af9554c6 100644 --- a/pandapower/test/timeseries/test_timeseries.py +++ b/pandapower/test/timeseries/test_timeseries.py @@ -38,7 +38,7 @@ def simple_test_net(): pp.create_transformer3w_from_parameters(net, b1, b3, b4, 110, 20, 6, 1e2, 1e2, 1e1, 3, 2, 2, 1, 1, 1, 100, 1, 60, 30, 'hv', tap_step_percent=1.5, tap_step_degree=0, tap_pos=0, tap_neutral=0, tap_max=10, - tap_min=-10, name='tr2') + tap_min=-10, name='tr2', tap_phase_shifter_type=0) pp.create_load(net, b2, 1.5e1, 1, name='trafo1') pp.create_load(net, b3, 3e1, 1.5, name='trafo2_mv') diff --git a/tutorials/create_advanced.ipynb b/tutorials/create_advanced.ipynb index 3e6ca8e2e..7e913e863 100644 --- a/tutorials/create_advanced.ipynb +++ b/tutorials/create_advanced.ipynb @@ -3284,7 +3284,8 @@ " vk_mv_percent=10.1, vk_lv_percent=10.1, vkr_hv_percent=0.266667, \n", " vkr_mv_percent=0.033333, vkr_lv_percent=0.04, pfe_kw=0, i0_percent=0, \n", " shift_mv_degree=30, shift_lv_degree=30, tap_side=\"hv\", tap_neutral=0, tap_min=-8, \n", - " tap_max=8, tap_step_percent=1.25, tap_pos=0, name='HV-MV-MV-Trafo')\n", + " tap_max=8, tap_step_percent=1.25, tap_pos=0, name='HV-MV-MV-Trafo', \n", + " tap_phase_shifter_type=0)\n", "\n", "# show transformer3w table\n", "net.trafo3w" @@ -4474,7 +4475,7 @@ "source": [ "hv_bus = pp.get_element_index(net, \"bus\", \"Bus MV4\")\n", "lv_bus = pp.get_element_index(net, \"bus\",\"Bus LV0\")\n", - "pp.create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva=.4, vn_hv_kv=10, vn_lv_kv=0.4, vkr_percent=1.325, vk_percent=4, pfe_kw=0.95, i0_percent=0.2375, tap_side=\"hv\", tap_neutral=0, tap_min=-2, tap_max=2, tap_step_percent=2.5, tp_pos=0, shift_degree=150, name='MV-LV-Trafo')\n", + "pp.create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva=.4, vn_hv_kv=10, vn_lv_kv=0.4, vkr_percent=1.325, vk_percent=4, pfe_kw=0.95, i0_percent=0.2375, tap_side=\"hv\", tap_neutral=0, tap_min=-2, tap_max=2, tap_step_percent=2.5, tap_phase_shifter_type=0, tp_pos=0, shift_degree=150, name='MV-LV-Trafo')\n", "\n", "#show only low voltage transformer\n", "net.trafo[net.trafo.lv_bus.isin(lv_buses.index)]" diff --git a/tutorials/tap_dependent_impedance.ipynb b/tutorials/tap_dependent_impedance.ipynb index cbd6fa5b1..514ee7875 100644 --- a/tutorials/tap_dependent_impedance.ipynb +++ b/tutorials/tap_dependent_impedance.ipynb @@ -45,7 +45,7 @@ " sn_mv_mva=0.5, sn_lv_mva=0.4, vk_hv_percent=1., \n", " vk_mv_percent=1., vk_lv_percent=1., vkr_hv_percent=0.3, \n", " vkr_mv_percent=0.3, vkr_lv_percent=0.3, pfe_kw=0.2, \n", - " i0_percent=0.3, tap_neutral=0., tap_pos=2, \n", + " i0_percent=0.3, tap_neutral=0., tap_pos=2, tap_phase_shifter_type=0, \n", " tap_step_percent=1., tap_min=-2, tap_max=2)\n", " else:\n", " pp.create_transformer(net, hv_bus=hv_bus, lv_bus=cb, std_type=\"0.25 MVA 20/0.4 kV\", tap_pos=2)\n", diff --git a/tutorials/three_phase_loadflow_tutorial_simple.ipynb b/tutorials/three_phase_loadflow_tutorial_simple.ipynb index 797ed081b..1bc69efda 100644 --- a/tutorials/three_phase_loadflow_tutorial_simple.ipynb +++ b/tutorials/three_phase_loadflow_tutorial_simple.ipynb @@ -401,7 +401,7 @@ " tap_min= -2, tap_max= 2,\n", " tap_step_degree= 0,\n", " tap_step_percent= 2.5,\n", - " tap_phase_shifter= False,\n", + " tap_phase_shifter_type=0,\n", " vk0_percent= 6, vkr0_percent= 0.78125, \n", " mag0_percent= 100, mag0_rx= 0.,\n", " si0_hv_partial= 0.9,vector_group= \"Dyn\",\n", From d016080a13657eb88672328968411b082b038795 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 6 Dec 2024 18:35:29 +0200 Subject: [PATCH 035/125] minor PEP8 fix --- pandapower/build_branch.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 7cef82b8d..1141ae43f 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -624,7 +624,7 @@ def _calc_tap_from_dataframe(net, trafo_df): trafo_shift[mask_ideal] += np.where( degree_is_set, (direction * tap_diff[mask_ideal] * tap_step_degree[mask_ideal]), - (direction * 2 * np.rad2deg(np.arcsin(tap_diff[mask_ideal] * \ + (direction * 2 * np.rad2deg(np.arcsin(tap_diff[mask_ideal] * tap_step_percent[mask_ideal] / 100 / 2))) ) elif any(mask_complex): From 9348373b8e3959638f6dd5e4870e02f0ed8b66e1 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Mon, 9 Dec 2024 12:38:17 +0200 Subject: [PATCH 036/125] revert changes in old_versions json files --- .../old_versions/example_2.0.0.json | 2 +- .../old_versions/example_2.0.1.json | 2 +- .../old_versions/example_2.1.0.json | 32 ++++++++--------- .../old_versions/example_2.10.0.json | 32 ++++++++--------- .../old_versions/example_2.10.1.json | 32 ++++++++--------- .../old_versions/example_2.11.0.json | 32 ++++++++--------- .../old_versions/example_2.11.1.json | 32 ++++++++--------- .../old_versions/example_2.12.0.json | 32 ++++++++--------- .../old_versions/example_2.12.1.json | 32 ++++++++--------- .../old_versions/example_2.13.0.1.json | 36 +++++++++---------- .../old_versions/example_2.13.0.json | 32 ++++++++--------- .../old_versions/example_2.14.0.json | 36 +++++++++---------- .../old_versions/example_2.2.0.json | 32 ++++++++--------- .../old_versions/example_2.3.0.json | 32 ++++++++--------- .../old_versions/example_2.3.1.json | 32 ++++++++--------- .../old_versions/example_2.4.0.json | 32 ++++++++--------- .../old_versions/example_2.5.0.json | 32 ++++++++--------- .../old_versions/example_2.6.0.json | 32 ++++++++--------- .../old_versions/example_2.7.0.json | 32 ++++++++--------- .../old_versions/example_2.8.0.json | 32 ++++++++--------- .../old_versions/example_2.9.0.json | 32 ++++++++--------- 21 files changed, 310 insertions(+), 310 deletions(-) diff --git a/pandapower/test/test_files/old_versions/example_2.0.0.json b/pandapower/test/test_files/old_versions/example_2.0.0.json index 5845dd99b..7dc5ffe9c 100644 --- a/pandapower/test/test_files/old_versions/example_2.0.0.json +++ b/pandapower/test/test_files/old_versions/example_2.0.0.json @@ -1,5 +1,5 @@ { "_class": "pandapowerNet", "_module": "pandapower.auxiliary", - "_object": "{\"OPF_converged\":false,\"bus\":{\n \"dtype\": {\n \"type\": \"object\",\n \"name\": \"object\",\n \"zone\": \"object\",\n \"in_service\": \"bool\",\n \"vn_kv\": \"float64\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"vn_kv\\\",\\\"type\\\",\\\"zone\\\",\\\"in_service\\\"],\\\"index\\\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56],\\\"data\\\":[[\\\"Double Busbar 1\\\",380.0,\\\"b\\\",null,true],[\\\"Double Busbar 2\\\",380.0,\\\"b\\\",null,true],[\\\"Bus DB T0\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T1\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T2\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T3\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T4\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T5\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T6\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T7\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T8\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T9\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB 1\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB 2\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB 3\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB 4\\\",380.0,\\\"n\\\",null,true],[\\\"Single Busbar\\\",110.0,\\\"b\\\",null,true],[\\\"Bus SB 1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 3\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 4\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 5\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T1.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T1.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T2.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T2.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T3.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T3.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T4.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T4.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T5.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T5.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV3\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV4\\\",110.0,\\\"n\\\",null,true],[\\\"Bus MV0 20kV\\\",20.0,\\\"n\\\",null,true],[\\\"Bus MV0\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV1\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV2\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV3\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV4\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV5\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV6\\\",10.0,\\\"n\\\",null,true],[\\\"Bus MV7\\\",10.0,\\\"n\\\",null,true],[\\\"Bus LV0\\\",0.4,\\\"n\\\",null,true],[\\\"Bus LV1.1\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV1.2\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV1.3\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV1.4\\\",0.4,\\\"m\\\",null,true],[\\\"Bus LV1.5\\\",0.4,\\\"m\\\",null,true],[\\\"Bus 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\"float64\",\n \"bus\": \"int64\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"bus\\\",\\\"p_mw\\\",\\\"q_mvar\\\",\\\"sn_mva\\\",\\\"soc_percent\\\",\\\"min_e_mwh\\\",\\\"max_e_mwh\\\",\\\"scaling\\\",\\\"in_service\\\",\\\"type\\\"],\\\"index\\\":[],\\\"data\\\":[]}\"\n},\"switch\":{\n \"dtype\": {\n \"type\": \"object\",\n \"et\": \"object\",\n \"element\": \"int64\",\n \"name\": \"object\",\n \"closed\": \"bool\",\n \"bus\": \"int64\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": 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\"float64\",\n \"hv_bus\": \"uint32\",\n \"pfe_kw\": \"float64\",\n \"sn_mva\": \"float64\",\n \"tap_pos\": \"int32\",\n \"std_type\": \"object\",\n \"vkr_percent\": \"float64\",\n \"name\": \"object\",\n \"vn_lv_kv\": \"float64\",\n \"tap_max\": \"float64\",\n \"shift_degree\": \"float64\",\n \"vn_hv_kv\": \"float64\",\n \"tap_side\": \"object\",\n \"parallel\": \"uint32\",\n \"i0_percent\": \"float64\",\n \"tap_min\": \"float64\",\n \"vk_percent\": \"float64\",\n \"df\": \"float64\",\n \"tap_phase_shifter\": \"bool\",\n \"lv_bus\": \"uint32\",\n \"tap_neutral\": \"float64\",\n \"in_service\": \"bool\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"std_type\\\",\\\"hv_bus\\\",\\\"lv_bus\\\",\\\"sn_mva\\\",\\\"vn_hv_kv\\\",\\\"vn_lv_kv\\\",\\\"vk_percent\\\",\\\"vkr_percent\\\",\\\"pfe_kw\\\",\\\"i0_percent\\\",\\\"shift_degree\\\",\\\"tap_side\\\",\\\"tap_neutral\\\",\\\"tap_min\\\",\\\"tap_max\\\",\\\"tap_step_percent\\\",\\\"tap_step_degree\\\",\\\"tap_pos\\\",\\\"tap_phase_shifter\\\",\\\"parallel\\\",\\\"df\\\",\\\"in_service\\\"],\\\"index\\\":[0,1],\\\"data\\\":[[\\\"EHV-HV-Trafo\\\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\\\"MV-LV-Trafo\\\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\\\"hv\\\",0.0,-2.0,2.0,2.5,null,0,false,1,1.0,true]]}\"\n},\"trafo3w\":{\n \"dtype\": {\n \"tap_at_star_point\": \"bool\",\n \"shift_lv_degree\": \"float64\",\n \"tap_step_percent\": \"float64\",\n \"hv_bus\": \"uint32\",\n \"pfe_kw\": \"float64\",\n \"vk_mv_percent\": \"float64\",\n \"tap_pos\": \"int32\",\n \"sn_hv_mva\": \"float64\",\n \"vkr_lv_percent\": \"float64\",\n \"std_type\": \"object\",\n \"name\": \"object\",\n \"i0_percent\": \"float64\",\n \"vkr_hv_percent\": \"float64\",\n \"vkr_mv_percent\": \"float64\",\n \"vn_lv_kv\": \"float64\",\n \"in_service\": \"bool\",\n \"tap_max\": \"int32\",\n \"vk_hv_percent\": \"float64\",\n \"tap_step_degree\": \"float64\",\n \"tap_neutral\": \"int32\",\n \"sn_lv_mva\": \"float64\",\n \"mv_bus\": \"uint32\",\n \"tap_side\": \"object\",\n \"vn_mv_kv\": \"float64\",\n \"vk_lv_percent\": \"float64\",\n \"vn_hv_kv\": \"float64\",\n \"tap_min\": \"int32\",\n \"lv_bus\": \"uint32\",\n \"shift_mv_degree\": \"float64\",\n \"sn_mv_mva\": \"float64\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"std_type\\\",\\\"hv_bus\\\",\\\"mv_bus\\\",\\\"lv_bus\\\",\\\"sn_hv_mva\\\",\\\"sn_mv_mva\\\",\\\"sn_lv_mva\\\",\\\"vn_hv_kv\\\",\\\"vn_mv_kv\\\",\\\"vn_lv_kv\\\",\\\"vk_hv_percent\\\",\\\"vk_mv_percent\\\",\\\"vk_lv_percent\\\",\\\"vkr_hv_percent\\\",\\\"vkr_mv_percent\\\",\\\"vkr_lv_percent\\\",\\\"pfe_kw\\\",\\\"i0_percent\\\",\\\"shift_mv_degree\\\",\\\"shift_lv_degree\\\",\\\"tap_side\\\",\\\"tap_neutral\\\",\\\"tap_min\\\",\\\"tap_max\\\",\\\"tap_step_percent\\\",\\\"tap_step_degree\\\",\\\"tap_pos\\\",\\\"tap_at_star_point\\\",\\\"in_service\\\"],\\\"index\\\":[0],\\\"data\\\":[[\\\"HV-MV-MV-Trafo\\\",null,33,36,37,40.0,15.0,25.0,110.0,20.0,10.0,10.1,10.1,10.1,0.266667,0.033333,0.04,0.0,0.0,30.0,30.0,\\\"hv\\\",0,-8,8,1.25,null,0,false,true]]}\"\n},\"user_pf_options\":{},\"version\":2.0,\"ward\":{\n \"dtype\": {\n \"qz_mvar\": \"float64\",\n \"in_service\": \"bool\",\n \"pz_mw\": \"float64\",\n \"qs_mvar\": \"float64\",\n \"name\": \"object\",\n \"ps_mw\": \"float64\",\n \"bus\": \"uint32\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"bus\\\",\\\"ps_mw\\\",\\\"qs_mvar\\\",\\\"qz_mvar\\\",\\\"pz_mw\\\",\\\"in_service\\\"],\\\"index\\\":[],\\\"data\\\":[]}\"\n},\"xward\":{\n \"dtype\": {\n \"vm_pu\": \"float64\",\n \"qz_mvar\": \"float64\",\n \"in_service\": \"bool\",\n \"pz_mw\": \"float64\",\n \"qs_mvar\": \"float64\",\n \"x_ohm\": \"float64\",\n \"name\": \"object\",\n \"ps_mw\": \"float64\",\n \"r_ohm\": \"float64\",\n \"bus\": \"uint32\"\n },\n \"orient\": \"split\",\n \"_class\": \"DataFrame\",\n \"_module\": \"pandas.core.frame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"bus\\\",\\\"ps_mw\\\",\\\"qs_mvar\\\",\\\"qz_mvar\\\",\\\"pz_mw\\\",\\\"r_ohm\\\",\\\"x_ohm\\\",\\\"vm_pu\\\",\\\"in_service\\\"],\\\"index\\\":[0,1],\\\"data\\\":[[\\\"XWard 1\\\",34,23.942,-12.24187,0.0,2.814571,0.0,12.18951,1.02616,true],[\\\"XWard 2\\\",32,3.776,-7.769979,0.0,9.174917000000001,0.0,50.562170000000002,1.024001,true]]}\"\n}}\n" } \ No newline at end of file diff --git a/pandapower/test/test_files/old_versions/example_2.0.1.json b/pandapower/test/test_files/old_versions/example_2.0.1.json index d08e31ad3..6ce7cc91a 100644 --- a/pandapower/test/test_files/old_versions/example_2.0.1.json +++ b/pandapower/test/test_files/old_versions/example_2.0.1.json @@ -1,5 +1,5 @@ { "_module": "pandapower.auxiliary", "_class": "pandapowerNet", - "_object": "{\"OPF_converged\":false,\"bus\":{\n \"_module\": \"pandas.core.frame\",\n \"_class\": \"DataFrame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"vn_kv\\\",\\\"type\\\",\\\"zone\\\",\\\"in_service\\\"],\\\"index\\\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56],\\\"data\\\":[[\\\"Double Busbar 1\\\",380.0,\\\"b\\\",null,true],[\\\"Double Busbar 2\\\",380.0,\\\"b\\\",null,true],[\\\"Bus DB T0\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T1\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T2\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T3\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T4\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T5\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T6\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T7\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T8\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB T9\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB 1\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB 2\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB 3\\\",380.0,\\\"n\\\",null,true],[\\\"Bus DB 4\\\",380.0,\\\"n\\\",null,true],[\\\"Single Busbar\\\",110.0,\\\"b\\\",null,true],[\\\"Bus SB 1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 3\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 4\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB 5\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T1.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T1.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T2.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T2.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T3.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T3.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T4.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T4.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T5.1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus SB T5.2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV1\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV2\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV3\\\",110.0,\\\"n\\\",null,true],[\\\"Bus HV4\\\",110.0,\\\"n\\\",null,true],[\\\"Bus MV0 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0.27,\n \"type\": \"cs\",\n \"q_mm2\": 150,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x95 RM/25 12/20 kV\": {\n \"c_nf_per_km\": 216,\n \"r_ohm_per_km\": 0.313,\n \"x_ohm_per_km\": 0.132,\n \"max_i_ka\": 0.252,\n \"type\": \"cs\",\n \"q_mm2\": 95,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x185 RM/25 12/20 kV\": {\n \"c_nf_per_km\": 273,\n \"r_ohm_per_km\": 0.161,\n \"x_ohm_per_km\": 0.117,\n \"max_i_ka\": 0.362,\n \"type\": \"cs\",\n \"q_mm2\": 185,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x240 RM/25 12/20 kV\": {\n \"c_nf_per_km\": 304,\n \"r_ohm_per_km\": 0.122,\n \"x_ohm_per_km\": 0.112,\n \"max_i_ka\": 0.421,\n \"type\": \"cs\",\n \"q_mm2\": 240,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x95 RM/25 6/10 kV\": {\n \"c_nf_per_km\": 315,\n \"r_ohm_per_km\": 0.313,\n \"x_ohm_per_km\": 0.123,\n \"max_i_ka\": 0.249,\n \"type\": \"cs\",\n \"q_mm2\": 95,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x185 RM/25 6/10 kV\": {\n \"c_nf_per_km\": 406,\n \"r_ohm_per_km\": 0.161,\n \"x_ohm_per_km\": 0.11,\n \"max_i_ka\": 0.358,\n \"type\": \"cs\",\n \"q_mm2\": 185,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x240 RM/25 6/10 kV\": {\n \"c_nf_per_km\": 456,\n \"r_ohm_per_km\": 0.122,\n \"x_ohm_per_km\": 0.105,\n \"max_i_ka\": 0.416,\n \"type\": \"cs\",\n \"q_mm2\": 240,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x150 RM/25 12/20 kV\": {\n \"c_nf_per_km\": 250,\n \"r_ohm_per_km\": 0.206,\n \"x_ohm_per_km\": 0.116,\n \"max_i_ka\": 0.319,\n \"type\": \"cs\",\n \"q_mm2\": 150,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x120 RM/25 12/20 kV\": {\n \"c_nf_per_km\": 230,\n \"r_ohm_per_km\": 0.253,\n \"x_ohm_per_km\": 0.119,\n \"max_i_ka\": 0.283,\n \"type\": \"cs\",\n \"q_mm2\": 120,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x70 RM/25 12/20 kV\": {\n \"c_nf_per_km\": 190,\n \"r_ohm_per_km\": 0.443,\n \"x_ohm_per_km\": 0.132,\n \"max_i_ka\": 0.22,\n \"type\": \"cs\",\n \"q_mm2\": 70,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x150 RM/25 6/10 kV\": {\n \"c_nf_per_km\": 360,\n \"r_ohm_per_km\": 0.206,\n \"x_ohm_per_km\": 0.11,\n \"max_i_ka\": 0.315,\n \"type\": \"cs\",\n \"q_mm2\": 150,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x120 RM/25 6/10 kV\": {\n \"c_nf_per_km\": 340,\n \"r_ohm_per_km\": 0.253,\n \"x_ohm_per_km\": 0.113,\n \"max_i_ka\": 0.28,\n \"type\": \"cs\",\n \"q_mm2\": 120,\n \"alpha\": 0.00403\n },\n \"NA2XS2Y 1x70 RM/25 6/10 kV\": {\n \"c_nf_per_km\": 280,\n \"r_ohm_per_km\": 0.443,\n \"x_ohm_per_km\": 0.123,\n \"max_i_ka\": 0.217,\n \"type\": \"cs\",\n \"q_mm2\": 70,\n \"alpha\": 0.00403\n },\n \"N2XS(FL)2Y 1x120 RM/35 64/110 kV\": {\n \"c_nf_per_km\": 112,\n \"r_ohm_per_km\": 0.153,\n \"x_ohm_per_km\": 0.166,\n \"max_i_ka\": 0.366,\n \"type\": \"cs\",\n \"q_mm2\": 120,\n \"alpha\": 0.00393\n },\n \"N2XS(FL)2Y 1x185 RM/35 64/110 kV\": {\n \"c_nf_per_km\": 125,\n \"r_ohm_per_km\": 0.099,\n \"x_ohm_per_km\": 0.156,\n \"max_i_ka\": 0.457,\n \"type\": \"cs\",\n \"q_mm2\": 185,\n \"alpha\": 0.00393\n },\n \"N2XS(FL)2Y 1x240 RM/35 64/110 kV\": {\n \"c_nf_per_km\": 135,\n \"r_ohm_per_km\": 0.075,\n \"x_ohm_per_km\": 0.149,\n \"max_i_ka\": 0.526,\n \"type\": \"cs\",\n \"q_mm2\": 240,\n \"alpha\": 0.00393\n },\n \"N2XS(FL)2Y 1x300 RM/35 64/110 kV\": {\n \"c_nf_per_km\": 144,\n \"r_ohm_per_km\": 0.06,\n \"x_ohm_per_km\": 0.144,\n \"max_i_ka\": 0.588,\n \"type\": \"cs\",\n \"q_mm2\": 300,\n \"alpha\": 0.00393\n },\n \"15-AL1/3-ST1A 0.4\": {\n \"c_nf_per_km\": 11,\n \"r_ohm_per_km\": 1.8769,\n \"x_ohm_per_km\": 0.35,\n \"max_i_ka\": 0.105,\n \"type\": \"ol\",\n \"q_mm2\": 16,\n \"alpha\": 0.00403\n },\n \"24-AL1/4-ST1A 0.4\": {\n \"c_nf_per_km\": 11.25,\n \"r_ohm_per_km\": 1.2012,\n \"x_ohm_per_km\": 0.335,\n \"max_i_ka\": 0.14,\n \"type\": \"ol\",\n \"q_mm2\": 24,\n \"alpha\": 0.00403\n },\n \"48-AL1/8-ST1A 0.4\": {\n \"c_nf_per_km\": 12.2,\n \"r_ohm_per_km\": 0.5939,\n \"x_ohm_per_km\": 0.3,\n \"max_i_ka\": 0.21,\n \"type\": \"ol\",\n \"q_mm2\": 48,\n \"alpha\": 0.00403\n },\n \"94-AL1/15-ST1A 0.4\": {\n \"c_nf_per_km\": 13.2,\n \"r_ohm_per_km\": 0.306,\n \"x_ohm_per_km\": 0.29,\n \"max_i_ka\": 0.35,\n \"type\": \"ol\",\n \"q_mm2\": 94,\n \"alpha\": 0.00403\n },\n \"34-AL1/6-ST1A 10.0\": {\n \"c_nf_per_km\": 9.7,\n \"r_ohm_per_km\": 0.8342,\n \"x_ohm_per_km\": 0.36,\n \"max_i_ka\": 0.17,\n \"type\": \"ol\",\n \"q_mm2\": 34,\n \"alpha\": 0.00403\n },\n \"48-AL1/8-ST1A 10.0\": {\n \"c_nf_per_km\": 10.1,\n \"r_ohm_per_km\": 0.5939,\n \"x_ohm_per_km\": 0.35,\n \"max_i_ka\": 0.21,\n \"type\": \"ol\",\n \"q_mm2\": 48,\n \"alpha\": 0.00403\n },\n \"70-AL1/11-ST1A 10.0\": {\n \"c_nf_per_km\": 10.4,\n \"r_ohm_per_km\": 0.4132,\n \"x_ohm_per_km\": 0.339,\n \"max_i_ka\": 0.29,\n \"type\": \"ol\",\n \"q_mm2\": 70,\n \"alpha\": 0.00403\n },\n \"94-AL1/15-ST1A 10.0\": {\n \"c_nf_per_km\": 10.75,\n \"r_ohm_per_km\": 0.306,\n \"x_ohm_per_km\": 0.33,\n \"max_i_ka\": 0.35,\n \"type\": \"ol\",\n \"q_mm2\": 94,\n \"alpha\": 0.00403\n },\n \"122-AL1/20-ST1A 10.0\": {\n \"c_nf_per_km\": 11.1,\n \"r_ohm_per_km\": 0.2376,\n \"x_ohm_per_km\": 0.323,\n \"max_i_ka\": 0.41,\n \"type\": \"ol\",\n \"q_mm2\": 122,\n \"alpha\": 0.00403\n },\n \"149-AL1/24-ST1A 10.0\": {\n \"c_nf_per_km\": 11.25,\n \"r_ohm_per_km\": 0.194,\n \"x_ohm_per_km\": 0.315,\n \"max_i_ka\": 0.47,\n \"type\": \"ol\",\n \"q_mm2\": 149,\n \"alpha\": 0.00403\n },\n \"34-AL1/6-ST1A 20.0\": {\n \"c_nf_per_km\": 9.15,\n \"r_ohm_per_km\": 0.8342,\n \"x_ohm_per_km\": 0.382,\n \"max_i_ka\": 0.17,\n \"type\": \"ol\",\n \"q_mm2\": 34,\n \"alpha\": 0.00403\n },\n \"48-AL1/8-ST1A 20.0\": {\n \"c_nf_per_km\": 9.5,\n \"r_ohm_per_km\": 0.5939,\n \"x_ohm_per_km\": 0.372,\n \"max_i_ka\": 0.21,\n \"type\": \"ol\",\n \"q_mm2\": 48,\n \"alpha\": 0.00403\n },\n \"70-AL1/11-ST1A 20.0\": {\n \"c_nf_per_km\": 9.7,\n \"r_ohm_per_km\": 0.4132,\n \"x_ohm_per_km\": 0.36,\n \"max_i_ka\": 0.29,\n \"type\": \"ol\",\n \"q_mm2\": 70,\n \"alpha\": 0.00403\n },\n \"94-AL1/15-ST1A 20.0\": {\n \"c_nf_per_km\": 10,\n \"r_ohm_per_km\": 0.306,\n \"x_ohm_per_km\": 0.35,\n \"max_i_ka\": 0.35,\n \"type\": \"ol\",\n \"q_mm2\": 94,\n \"alpha\": 0.00403\n },\n \"122-AL1/20-ST1A 20.0\": {\n \"c_nf_per_km\": 10.3,\n \"r_ohm_per_km\": 0.2376,\n \"x_ohm_per_km\": 0.344,\n \"max_i_ka\": 0.41,\n \"type\": \"ol\",\n \"q_mm2\": 122,\n \"alpha\": 0.00403\n },\n \"149-AL1/24-ST1A 20.0\": {\n \"c_nf_per_km\": 10.5,\n \"r_ohm_per_km\": 0.194,\n \"x_ohm_per_km\": 0.337,\n \"max_i_ka\": 0.47,\n \"type\": \"ol\",\n \"q_mm2\": 149,\n \"alpha\": 0.00403\n },\n \"184-AL1/30-ST1A 20.0\": {\n \"c_nf_per_km\": 10.75,\n \"r_ohm_per_km\": 0.1571,\n \"x_ohm_per_km\": 0.33,\n \"max_i_ka\": 0.535,\n \"type\": \"ol\",\n \"q_mm2\": 184,\n \"alpha\": 0.00403\n },\n \"243-AL1/39-ST1A 20.0\": {\n \"c_nf_per_km\": 11,\n \"r_ohm_per_km\": 0.1188,\n \"x_ohm_per_km\": 0.32,\n \"max_i_ka\": 0.645,\n \"type\": \"ol\",\n \"q_mm2\": 243,\n \"alpha\": 0.00403\n },\n \"149-AL1/24-ST1A 110.0\": {\n \"c_nf_per_km\": 8.75,\n \"r_ohm_per_km\": 0.194,\n \"x_ohm_per_km\": 0.41,\n \"max_i_ka\": 0.47,\n \"type\": \"ol\",\n \"q_mm2\": 149,\n \"alpha\": 0.00403\n },\n \"184-AL1/30-ST1A 110.0\": {\n \"c_nf_per_km\": 8.8,\n \"r_ohm_per_km\": 0.1571,\n \"x_ohm_per_km\": 0.4,\n \"max_i_ka\": 0.535,\n \"type\": \"ol\",\n \"q_mm2\": 184,\n \"alpha\": 0.00403\n },\n \"243-AL1/39-ST1A 110.0\": {\n \"c_nf_per_km\": 9,\n \"r_ohm_per_km\": 0.1188,\n \"x_ohm_per_km\": 0.39,\n \"max_i_ka\": 0.645,\n \"type\": \"ol\",\n \"q_mm2\": 243,\n \"alpha\": 0.00403\n },\n \"305-AL1/39-ST1A 110.0\": {\n \"c_nf_per_km\": 9.2,\n \"r_ohm_per_km\": 0.0949,\n \"x_ohm_per_km\": 0.38,\n \"max_i_ka\": 0.74,\n \"type\": \"ol\",\n \"q_mm2\": 305,\n \"alpha\": 0.00403\n },\n \"490-AL1/64-ST1A 220.0\": {\n \"c_nf_per_km\": 10,\n \"r_ohm_per_km\": 0.059,\n \"x_ohm_per_km\": 0.285,\n \"max_i_ka\": 0.96,\n \"type\": \"ol\",\n \"q_mm2\": 490,\n \"alpha\": 0.00403\n },\n \"490-AL1/64-ST1A 380.0\": {\n \"c_nf_per_km\": 11,\n \"r_ohm_per_km\": 0.059,\n \"x_ohm_per_km\": 0.253,\n \"max_i_ka\": 0.96,\n \"type\": \"ol\",\n \"q_mm2\": 490,\n \"alpha\": 0.00403\n }\n },\n \"trafo\": {\n \"160 MVA 380/110 kV\": {\n \"i0_percent\": 0.06,\n \"pfe_kw\": 60,\n \"vkr_percent\": 0.25,\n \"sn_mva\": 160,\n \"vn_lv_kv\": 110.0,\n \"vn_hv_kv\": 380.0,\n \"vk_percent\": 12.2,\n \"shift_degree\": 0,\n \"vector_group\": \"Yy0\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"100 MVA 220/110 kV\": {\n \"i0_percent\": 0.06,\n \"pfe_kw\": 55,\n \"vkr_percent\": 0.26,\n \"sn_mva\": 100,\n \"vn_lv_kv\": 110.0,\n \"vn_hv_kv\": 220.0,\n \"vk_percent\": 12.0,\n \"shift_degree\": 0,\n \"vector_group\": \"Yy0\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"63 MVA 110/20 kV\": {\n \"i0_percent\": 0.04,\n \"pfe_kw\": 22,\n \"vkr_percent\": 0.32,\n \"sn_mva\": 63,\n \"vn_lv_kv\": 20.0,\n \"vn_hv_kv\": 110.0,\n \"vk_percent\": 18,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"40 MVA 110/20 kV\": {\n \"i0_percent\": 0.05,\n \"pfe_kw\": 18,\n \"vkr_percent\": 0.34,\n \"sn_mva\": 40,\n \"vn_lv_kv\": 20.0,\n \"vn_hv_kv\": 110.0,\n \"vk_percent\": 16.2,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"25 MVA 110/20 kV\": {\n \"i0_percent\": 0.07,\n \"pfe_kw\": 14,\n \"vkr_percent\": 0.41,\n \"sn_mva\": 25,\n \"vn_lv_kv\": 20.0,\n \"vn_hv_kv\": 110.0,\n \"vk_percent\": 12,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"63 MVA 110/10 kV\": {\n \"sn_mva\": 63,\n \"vn_hv_kv\": 110,\n \"vn_lv_kv\": 10,\n \"vk_percent\": 18,\n \"vkr_percent\": 0.32,\n \"pfe_kw\": 22,\n \"i0_percent\": 0.04,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"40 MVA 110/10 kV\": {\n \"sn_mva\": 40,\n \"vn_hv_kv\": 110,\n \"vn_lv_kv\": 10,\n \"vk_percent\": 16.2,\n \"vkr_percent\": 0.34,\n \"pfe_kw\": 18,\n \"i0_percent\": 0.05,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"25 MVA 110/10 kV\": {\n \"sn_mva\": 25,\n \"vn_hv_kv\": 110,\n \"vn_lv_kv\": 10,\n \"vk_percent\": 12,\n \"vkr_percent\": 0.41,\n \"pfe_kw\": 14,\n \"i0_percent\": 0.07,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"0.25 MVA 20/0.4 kV\": {\n \"sn_mva\": 0.25,\n \"vn_hv_kv\": 20,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.44,\n \"pfe_kw\": 0.8,\n \"i0_percent\": 0.32,\n \"shift_degree\": 150,\n \"vector_group\": \"Yzn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"0.4 MVA 20/0.4 kV\": {\n \"sn_mva\": 0.4,\n \"vn_hv_kv\": 20,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.425,\n \"pfe_kw\": 1.35,\n \"i0_percent\": 0.3375,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"0.63 MVA 20/0.4 kV\": {\n \"sn_mva\": 0.63,\n \"vn_hv_kv\": 20,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.206,\n \"pfe_kw\": 1.65,\n \"i0_percent\": 0.2619,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"0.25 MVA 10/0.4 kV\": {\n \"sn_mva\": 0.25,\n \"vn_hv_kv\": 10,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.2,\n \"pfe_kw\": 0.6,\n \"i0_percent\": 0.24,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"0.4 MVA 10/0.4 kV\": {\n \"sn_mva\": 0.4,\n \"vn_hv_kv\": 10,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.325,\n \"pfe_kw\": 0.95,\n \"i0_percent\": 0.2375,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter_type\": 0,\n },\n \"0.63 MVA 10/0.4 kV\": {\n \"sn_mva\": 0.63,\n \"vn_hv_kv\": 10,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.0794,\n \"pfe_kw\": 1.18,\n \"i0_percent\": 0.1873,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter_type\": 0,\n }\n },\n \"trafo3w\": {\n \"63/25/38 MVA 110/20/10 kV\": {\n \"sn_hv_mva\": 63,\n \"sn_mv_mva\": 25,\n \"sn_lv_mva\": 38,\n \"vn_hv_kv\": 110,\n \"vn_mv_kv\": 20,\n \"vn_lv_kv\": 10,\n \"vk_hv_percent\": 10.4,\n \"vk_mv_percent\": 10.4,\n 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0.41,\n \"pfe_kw\": 14,\n \"i0_percent\": 0.07,\n \"shift_degree\": 150,\n \"vector_group\": \"YNd5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -9,\n \"tap_max\": 9,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 1.5,\n \"tap_phase_shifter\": false\n },\n \"0.25 MVA 20/0.4 kV\": {\n \"sn_mva\": 0.25,\n \"vn_hv_kv\": 20,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.44,\n \"pfe_kw\": 0.8,\n \"i0_percent\": 0.32,\n \"shift_degree\": 150,\n \"vector_group\": \"Yzn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter\": false\n },\n \"0.4 MVA 20/0.4 kV\": {\n \"sn_mva\": 0.4,\n \"vn_hv_kv\": 20,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.425,\n \"pfe_kw\": 1.35,\n \"i0_percent\": 0.3375,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter\": false\n },\n \"0.63 MVA 20/0.4 kV\": {\n \"sn_mva\": 0.63,\n \"vn_hv_kv\": 20,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 6,\n \"vkr_percent\": 1.206,\n \"pfe_kw\": 1.65,\n \"i0_percent\": 0.2619,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter\": false\n },\n \"0.25 MVA 10/0.4 kV\": {\n \"sn_mva\": 0.25,\n \"vn_hv_kv\": 10,\n \"vn_lv_kv\": 0.4,\n \"vk_percent\": 4,\n \"vkr_percent\": 1.2,\n \"pfe_kw\": 0.6,\n \"i0_percent\": 0.24,\n \"shift_degree\": 150,\n \"vector_group\": \"Dyn5\",\n \"tap_side\": \"hv\",\n \"tap_neutral\": 0,\n \"tap_min\": -2,\n \"tap_max\": 2,\n \"tap_step_degree\": 0,\n \"tap_step_percent\": 2.5,\n \"tap_phase_shifter\": false\n },\n \"0.4 MVA 10/0.4 kV\": {\n \"sn_mva\": 0.4,\n \"vn_hv_kv\": 10,\n \"vn_lv_kv\": 0.4,\n 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\"{\\\"columns\\\":[\\\"name\\\",\\\"std_type\\\",\\\"hv_bus\\\",\\\"lv_bus\\\",\\\"sn_mva\\\",\\\"vn_hv_kv\\\",\\\"vn_lv_kv\\\",\\\"vk_percent\\\",\\\"vkr_percent\\\",\\\"pfe_kw\\\",\\\"i0_percent\\\",\\\"shift_degree\\\",\\\"tap_side\\\",\\\"tap_neutral\\\",\\\"tap_min\\\",\\\"tap_max\\\",\\\"tap_step_percent\\\",\\\"tap_step_degree\\\",\\\"tap_pos\\\",\\\"tap_phase_shifter\\\",\\\"parallel\\\",\\\"df\\\",\\\"in_service\\\"],\\\"index\\\":[0,1],\\\"data\\\":[[\\\"EHV-HV-Trafo\\\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\\\"MV-LV-Trafo\\\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\\\"hv\\\",0.0,-2.0,2.0,2.5,null,0,false,1,1.0,true]]}\",\n \"dtype\": {\n \"name\": \"object\",\n \"std_type\": \"object\",\n \"hv_bus\": \"uint32\",\n \"lv_bus\": \"uint32\",\n \"sn_mva\": \"float64\",\n \"vn_hv_kv\": \"float64\",\n \"vn_lv_kv\": \"float64\",\n \"vk_percent\": \"float64\",\n \"vkr_percent\": \"float64\",\n \"pfe_kw\": \"float64\",\n \"i0_percent\": \"float64\",\n \"shift_degree\": \"float64\",\n \"tap_side\": \"object\",\n \"tap_neutral\": \"float64\",\n \"tap_min\": \"float64\",\n \"tap_max\": \"float64\",\n \"tap_step_percent\": \"float64\",\n \"tap_step_degree\": \"float64\",\n \"tap_pos\": \"int32\",\n \"tap_phase_shifter\": \"bool\",\n \"parallel\": \"uint32\",\n \"df\": \"float64\",\n \"in_service\": \"bool\"\n },\n \"orient\": \"split\"\n},\"trafo3w\":{\n \"_module\": \"pandas.core.frame\",\n \"_class\": \"DataFrame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"std_type\\\",\\\"hv_bus\\\",\\\"mv_bus\\\",\\\"lv_bus\\\",\\\"sn_hv_mva\\\",\\\"sn_mv_mva\\\",\\\"sn_lv_mva\\\",\\\"vn_hv_kv\\\",\\\"vn_mv_kv\\\",\\\"vn_lv_kv\\\",\\\"vk_hv_percent\\\",\\\"vk_mv_percent\\\",\\\"vk_lv_percent\\\",\\\"vkr_hv_percent\\\",\\\"vkr_mv_percent\\\",\\\"vkr_lv_percent\\\",\\\"pfe_kw\\\",\\\"i0_percent\\\",\\\"shift_mv_degree\\\",\\\"shift_lv_degree\\\",\\\"tap_side\\\",\\\"tap_neutral\\\",\\\"tap_min\\\",\\\"tap_max\\\",\\\"tap_step_percent\\\",\\\"tap_step_degree\\\",\\\"tap_pos\\\",\\\"tap_at_star_point\\\",\\\"in_service\\\"],\\\"index\\\":[0],\\\"data\\\":[[\\\"HV-MV-MV-Trafo\\\",null,33,36,37,40.0,15.0,25.0,110.0,20.0,10.0,10.1,10.1,10.1,0.266667,0.033333,0.04,0.0,0.0,30.0,30.0,\\\"hv\\\",0,-8,8,1.25,null,0,false,true]]}\",\n \"dtype\": {\n \"name\": \"object\",\n \"std_type\": \"object\",\n \"hv_bus\": \"uint32\",\n \"mv_bus\": \"uint32\",\n \"lv_bus\": \"uint32\",\n \"sn_hv_mva\": \"float64\",\n \"sn_mv_mva\": \"float64\",\n \"sn_lv_mva\": \"float64\",\n \"vn_hv_kv\": \"float64\",\n \"vn_mv_kv\": \"float64\",\n \"vn_lv_kv\": \"float64\",\n \"vk_hv_percent\": \"float64\",\n \"vk_mv_percent\": \"float64\",\n \"vk_lv_percent\": \"float64\",\n \"vkr_hv_percent\": \"float64\",\n \"vkr_mv_percent\": \"float64\",\n \"vkr_lv_percent\": \"float64\",\n \"pfe_kw\": \"float64\",\n \"i0_percent\": \"float64\",\n \"shift_mv_degree\": \"float64\",\n \"shift_lv_degree\": \"float64\",\n \"tap_side\": \"object\",\n \"tap_neutral\": \"int32\",\n \"tap_min\": \"int32\",\n \"tap_max\": \"int32\",\n \"tap_step_percent\": \"float64\",\n \"tap_step_degree\": \"float64\",\n \"tap_pos\": \"int32\",\n \"tap_at_star_point\": \"bool\",\n \"in_service\": \"bool\"\n },\n \"orient\": \"split\"\n},\"user_pf_options\":{},\"version\":\"2.0.1\",\"ward\":{\n \"_module\": \"pandas.core.frame\",\n \"_class\": \"DataFrame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"bus\\\",\\\"ps_mw\\\",\\\"qs_mvar\\\",\\\"qz_mvar\\\",\\\"pz_mw\\\",\\\"in_service\\\"],\\\"index\\\":[],\\\"data\\\":[]}\",\n \"dtype\": {\n \"name\": \"object\",\n \"bus\": \"uint32\",\n \"ps_mw\": \"float64\",\n \"qs_mvar\": \"float64\",\n \"qz_mvar\": \"float64\",\n \"pz_mw\": \"float64\",\n \"in_service\": \"bool\"\n },\n \"orient\": \"split\"\n},\"xward\":{\n \"_module\": \"pandas.core.frame\",\n \"_class\": \"DataFrame\",\n \"_object\": \"{\\\"columns\\\":[\\\"name\\\",\\\"bus\\\",\\\"ps_mw\\\",\\\"qs_mvar\\\",\\\"qz_mvar\\\",\\\"pz_mw\\\",\\\"r_ohm\\\",\\\"x_ohm\\\",\\\"vm_pu\\\",\\\"in_service\\\"],\\\"index\\\":[0,1],\\\"data\\\":[[\\\"XWard 1\\\",34,23.942,-12.24187,0.0,2.814571,0.0,12.18951,1.02616,true],[\\\"XWard 2\\\",32,3.776,-7.769979,0.0,9.174917000000001,0.0,50.562170000000002,1.024001,true]]}\",\n \"dtype\": {\n \"name\": \"object\",\n \"bus\": \"uint32\",\n \"ps_mw\": \"float64\",\n \"qs_mvar\": \"float64\",\n \"qz_mvar\": \"float64\",\n \"pz_mw\": \"float64\",\n \"r_ohm\": \"float64\",\n \"x_ohm\": \"float64\",\n \"vm_pu\": \"float64\",\n \"in_service\": \"bool\"\n },\n \"orient\": \"split\"\n}}\n" } \ No newline at end of file diff --git a/pandapower/test/test_files/old_versions/example_2.1.0.json b/pandapower/test/test_files/old_versions/example_2.1.0.json index ab067b8fd..c5b94d15d 100644 --- a/pandapower/test/test_files/old_versions/example_2.1.0.json +++ b/pandapower/test/test_files/old_versions/example_2.1.0.json @@ -840,7 +840,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -858,7 +858,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -876,7 +876,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -894,7 +894,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -912,7 +912,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -930,7 +930,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -948,7 +948,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -966,7 +966,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -984,7 +984,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1002,7 +1002,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1020,7 +1020,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1038,7 +1038,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1056,7 +1056,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1074,7 +1074,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { @@ -1165,7 +1165,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,\"hv\",0.0,-10.0,10.0,1.25,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,0,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,\"hv\",0.0,-10.0,10.0,1.25,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,0,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -1187,7 +1187,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" diff --git a/pandapower/test/test_files/old_versions/example_2.10.0.json b/pandapower/test/test_files/old_versions/example_2.10.0.json index 4e795e039..90fff4883 100644 --- a/pandapower/test/test_files/old_versions/example_2.10.0.json +++ b/pandapower/test/test_files/old_versions/example_2.10.0.json @@ -226,7 +226,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -248,7 +248,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -943,7 +943,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -961,7 +961,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -979,7 +979,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -997,7 +997,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1015,7 +1015,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1033,7 +1033,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1051,7 +1051,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1069,7 +1069,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1087,7 +1087,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1105,7 +1105,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1123,7 +1123,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1141,7 +1141,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1159,7 +1159,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1177,7 +1177,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.10.1.json b/pandapower/test/test_files/old_versions/example_2.10.1.json index eb2e20bd6..14197ef07 100644 --- a/pandapower/test/test_files/old_versions/example_2.10.1.json +++ b/pandapower/test/test_files/old_versions/example_2.10.1.json @@ -226,7 +226,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -248,7 +248,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -943,7 +943,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -961,7 +961,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -979,7 +979,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -997,7 +997,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1015,7 +1015,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1033,7 +1033,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1051,7 +1051,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1069,7 +1069,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1087,7 +1087,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1105,7 +1105,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1123,7 +1123,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1141,7 +1141,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1159,7 +1159,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1177,7 +1177,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.11.0.json b/pandapower/test/test_files/old_versions/example_2.11.0.json index e0143acb9..178c0d40d 100644 --- a/pandapower/test/test_files/old_versions/example_2.11.0.json +++ b/pandapower/test/test_files/old_versions/example_2.11.0.json @@ -226,7 +226,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -248,7 +248,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -956,7 +956,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -974,7 +974,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -992,7 +992,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1010,7 +1010,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1028,7 +1028,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1064,7 +1064,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1082,7 +1082,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1100,7 +1100,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1118,7 +1118,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1136,7 +1136,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1154,7 +1154,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1172,7 +1172,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1190,7 +1190,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.11.1.json b/pandapower/test/test_files/old_versions/example_2.11.1.json index 697c8b68f..b4d291714 100644 --- a/pandapower/test/test_files/old_versions/example_2.11.1.json +++ b/pandapower/test/test_files/old_versions/example_2.11.1.json @@ -226,7 +226,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -248,7 +248,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -956,7 +956,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -974,7 +974,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -992,7 +992,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1010,7 +1010,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1028,7 +1028,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1064,7 +1064,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1082,7 +1082,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1100,7 +1100,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1118,7 +1118,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1136,7 +1136,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1154,7 +1154,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1172,7 +1172,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1190,7 +1190,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.12.0.json b/pandapower/test/test_files/old_versions/example_2.12.0.json index 72fe58c2f..b41af38b3 100644 --- a/pandapower/test/test_files/old_versions/example_2.12.0.json +++ b/pandapower/test/test_files/old_versions/example_2.12.0.json @@ -269,7 +269,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -291,7 +291,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1064,7 +1064,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1082,7 +1082,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1100,7 +1100,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1118,7 +1118,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1136,7 +1136,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1154,7 +1154,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1172,7 +1172,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1190,7 +1190,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1208,7 +1208,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1226,7 +1226,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1244,7 +1244,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1262,7 +1262,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1280,7 +1280,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.12.1.json b/pandapower/test/test_files/old_versions/example_2.12.1.json index af78c92ae..13d627693 100644 --- a/pandapower/test/test_files/old_versions/example_2.12.1.json +++ b/pandapower/test/test_files/old_versions/example_2.12.1.json @@ -269,7 +269,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -291,7 +291,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1064,7 +1064,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1082,7 +1082,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1100,7 +1100,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1118,7 +1118,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1136,7 +1136,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1154,7 +1154,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1172,7 +1172,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1190,7 +1190,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1208,7 +1208,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1226,7 +1226,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1244,7 +1244,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1262,7 +1262,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1280,7 +1280,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.13.0.1.json b/pandapower/test/test_files/old_versions/example_2.13.0.1.json index e072a42c8..1dca951db 100644 --- a/pandapower/test/test_files/old_versions/example_2.13.0.1.json +++ b/pandapower/test/test_files/old_versions/example_2.13.0.1.json @@ -269,7 +269,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"tap_characteristic_table\",\"id_characteristic_table\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,false,null],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,true,0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"tap_dependent_impedance\",\"vk_percent_characteristic\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,false,null],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,true,0]]}", "orient": "split", "dtype": { "name": "object", @@ -291,12 +291,12 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", - "tap_characteristic_table": "bool", - "id_characteristic_table": "Int64" + "tap_dependent_impedance": "bool", + "vk_percent_characteristic": "Int64" }, "is_multiindex": false, "is_multicolumn": false @@ -1048,7 +1048,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1066,7 +1066,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1084,7 +1084,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1102,7 +1102,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1120,7 +1120,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1138,7 +1138,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1156,7 +1156,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1174,7 +1174,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1192,7 +1192,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1210,7 +1210,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1228,7 +1228,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1246,7 +1246,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1264,7 +1264,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1282,7 +1282,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.13.0.json b/pandapower/test/test_files/old_versions/example_2.13.0.json index 2b63d383f..ac0f0c9d7 100644 --- a/pandapower/test/test_files/old_versions/example_2.13.0.json +++ b/pandapower/test/test_files/old_versions/example_2.13.0.json @@ -269,7 +269,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -291,7 +291,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1064,7 +1064,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1082,7 +1082,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1100,7 +1100,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1118,7 +1118,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1136,7 +1136,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1154,7 +1154,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1172,7 +1172,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1190,7 +1190,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1208,7 +1208,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1226,7 +1226,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1244,7 +1244,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1262,7 +1262,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1280,7 +1280,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.14.0.json b/pandapower/test/test_files/old_versions/example_2.14.0.json index 23518736f..817259499 100644 --- a/pandapower/test/test_files/old_versions/example_2.14.0.json +++ b/pandapower/test/test_files/old_versions/example_2.14.0.json @@ -288,7 +288,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"tap_characteristic_table\",\"id_characteristic_table\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,false,null],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,true,0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"tap_dependent_impedance\",\"vk_percent_characteristic\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,false,null],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,true,0]]}", "orient": "split", "dtype": { "name": "object", @@ -310,12 +310,12 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", - "tap_characteristic_table": "bool", - "id_characteristic_table": "Int64" + "tap_dependent_impedance": "bool", + "vk_percent_characteristic": "Int64" }, "is_multiindex": false, "is_multicolumn": false @@ -1118,7 +1118,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1136,7 +1136,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1154,7 +1154,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1172,7 +1172,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1190,7 +1190,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1208,7 +1208,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1226,7 +1226,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1244,7 +1244,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1262,7 +1262,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1280,7 +1280,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1298,7 +1298,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1316,7 +1316,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1334,7 +1334,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1352,7 +1352,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.2.0.json b/pandapower/test/test_files/old_versions/example_2.2.0.json index 4b10e0bb9..2991ddb73 100644 --- a/pandapower/test/test_files/old_versions/example_2.2.0.json +++ b/pandapower/test/test_files/old_versions/example_2.2.0.json @@ -160,7 +160,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -182,7 +182,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -858,7 +858,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -876,7 +876,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -894,7 +894,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -912,7 +912,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -930,7 +930,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -948,7 +948,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -966,7 +966,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -984,7 +984,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1002,7 +1002,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1020,7 +1020,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1038,7 +1038,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1056,7 +1056,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1074,7 +1074,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1092,7 +1092,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.3.0.json b/pandapower/test/test_files/old_versions/example_2.3.0.json index 46b7e6194..82de727db 100644 --- a/pandapower/test/test_files/old_versions/example_2.3.0.json +++ b/pandapower/test/test_files/old_versions/example_2.3.0.json @@ -201,7 +201,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -223,7 +223,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -899,7 +899,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -917,7 +917,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -935,7 +935,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -953,7 +953,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -971,7 +971,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -989,7 +989,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1007,7 +1007,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1025,7 +1025,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1043,7 +1043,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1061,7 +1061,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1079,7 +1079,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1097,7 +1097,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1115,7 +1115,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1133,7 +1133,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.3.1.json b/pandapower/test/test_files/old_versions/example_2.3.1.json index 1d2ea9a7c..437514f4a 100644 --- a/pandapower/test/test_files/old_versions/example_2.3.1.json +++ b/pandapower/test/test_files/old_versions/example_2.3.1.json @@ -198,7 +198,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0],\"data\":[[\"transformer\",\"0.25 MVA 10\\/0.4 kV\",0,1,0.25,10.0,0.4,4.0,1.2,0.6,0.24,150.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0],\"data\":[[\"transformer\",\"0.25 MVA 10\\/0.4 kV\",0,1,0.25,10.0,0.4,4.0,1.2,0.6,0.24,150.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -220,7 +220,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -896,7 +896,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -914,7 +914,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -932,7 +932,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -950,7 +950,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -968,7 +968,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -986,7 +986,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1004,7 +1004,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1022,7 +1022,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1040,7 +1040,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1058,7 +1058,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1076,7 +1076,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1094,7 +1094,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1112,7 +1112,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1130,7 +1130,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.4.0.json b/pandapower/test/test_files/old_versions/example_2.4.0.json index 040364988..8c601ff17 100644 --- a/pandapower/test/test_files/old_versions/example_2.4.0.json +++ b/pandapower/test/test_files/old_versions/example_2.4.0.json @@ -222,7 +222,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -244,7 +244,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -920,7 +920,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -938,7 +938,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -956,7 +956,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -974,7 +974,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -992,7 +992,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1010,7 +1010,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1028,7 +1028,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1064,7 +1064,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1082,7 +1082,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1100,7 +1100,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1118,7 +1118,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1136,7 +1136,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1154,7 +1154,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.5.0.json b/pandapower/test/test_files/old_versions/example_2.5.0.json index a6ff69afe..5a1e7ea24 100644 --- a/pandapower/test/test_files/old_versions/example_2.5.0.json +++ b/pandapower/test/test_files/old_versions/example_2.5.0.json @@ -222,7 +222,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -244,7 +244,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -921,7 +921,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -939,7 +939,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -957,7 +957,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -975,7 +975,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -993,7 +993,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1011,7 +1011,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1029,7 +1029,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1047,7 +1047,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1065,7 +1065,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1083,7 +1083,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1101,7 +1101,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1119,7 +1119,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1137,7 +1137,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1155,7 +1155,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.6.0.json b/pandapower/test/test_files/old_versions/example_2.6.0.json index c9bd794ef..77566df8a 100644 --- a/pandapower/test/test_files/old_versions/example_2.6.0.json +++ b/pandapower/test/test_files/old_versions/example_2.6.0.json @@ -222,7 +222,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -244,7 +244,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -921,7 +921,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -939,7 +939,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -957,7 +957,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -975,7 +975,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -993,7 +993,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1011,7 +1011,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1029,7 +1029,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1047,7 +1047,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1065,7 +1065,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1083,7 +1083,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1101,7 +1101,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1119,7 +1119,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1137,7 +1137,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1155,7 +1155,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.7.0.json b/pandapower/test/test_files/old_versions/example_2.7.0.json index f3089a980..6e4210252 100644 --- a/pandapower/test/test_files/old_versions/example_2.7.0.json +++ b/pandapower/test/test_files/old_versions/example_2.7.0.json @@ -223,7 +223,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"pt_percent\",\"oltc\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,null,false],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,null,false]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"pt_percent\",\"oltc\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,null,false],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,null,false]]}", "orient": "split", "dtype": { "name": "object", @@ -245,7 +245,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -931,7 +931,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -949,7 +949,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -967,7 +967,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -985,7 +985,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1003,7 +1003,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1021,7 +1021,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1039,7 +1039,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1057,7 +1057,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1075,7 +1075,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1093,7 +1093,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1111,7 +1111,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1129,7 +1129,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1147,7 +1147,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1165,7 +1165,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.8.0.json b/pandapower/test/test_files/old_versions/example_2.8.0.json index c8da25aea..448d724f9 100644 --- a/pandapower/test/test_files/old_versions/example_2.8.0.json +++ b/pandapower/test/test_files/old_versions/example_2.8.0.json @@ -225,7 +225,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"pt_percent\",\"oltc\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,null,false],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,null,false]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"pt_percent\",\"oltc\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,null,false],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,null,false]]}", "orient": "split", "dtype": { "name": "object", @@ -247,7 +247,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -943,7 +943,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -961,7 +961,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -979,7 +979,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -997,7 +997,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1015,7 +1015,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1033,7 +1033,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1051,7 +1051,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1069,7 +1069,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1087,7 +1087,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1105,7 +1105,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1123,7 +1123,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1141,7 +1141,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1159,7 +1159,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1177,7 +1177,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/test/test_files/old_versions/example_2.9.0.json b/pandapower/test/test_files/old_versions/example_2.9.0.json index 0cda5c0b1..d8cecfdab 100644 --- a/pandapower/test/test_files/old_versions/example_2.9.0.json +++ b/pandapower/test/test_files/old_versions/example_2.9.0.json @@ -225,7 +225,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"pt_percent\",\"oltc\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,null,false],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,null,false]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"pt_percent\",\"oltc\"],\"index\":[0,1],\"data\":[[\"EHV-HV-Trafo\",null,13,17,300.0,380.0,110.0,8.0,0.06,0.0,0.0,0.0,null,null,null,null,null,null,0,false,1,1.0,true,null,false],[\"MV-LV-Trafo\",null,41,45,0.4,10.0,0.4,4.0,1.325,0.95,0.2375,150.0,\"hv\",0.0,-2.0,2.0,2.5,null,-2,false,1,1.0,true,null,false]]}", "orient": "split", "dtype": { "name": "object", @@ -247,7 +247,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -943,7 +943,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -961,7 +961,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -979,7 +979,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -997,7 +997,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1015,7 +1015,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1033,7 +1033,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1051,7 +1051,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1069,7 +1069,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1087,7 +1087,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1105,7 +1105,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1123,7 +1123,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1141,7 +1141,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1159,7 +1159,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1177,7 +1177,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_phase_shifter": false } }, "trafo3w": { From 6fdd6b2763166291d3501c162a51fed36ec03f3c Mon Sep 17 00:00:00 2001 From: Jakob Kirschner Date: Mon, 9 Dec 2024 14:18:54 +0100 Subject: [PATCH 037/125] add tests and warnings for shunt characteristics --- pandapower/build_bus.py | 9 ++++- pandapower/test/api/test_auxiliary.py | 35 +++++++++++++++++++ pandapower/test/control/test_shunt_control.py | 23 ++++++++++-- pandapower/test/loadflow/test_runpp.py | 14 ++++++++ 4 files changed, 78 insertions(+), 3 deletions(-) diff --git a/pandapower/build_bus.py b/pandapower/build_bus.py index 8b5b3cc18..61adb504f 100644 --- a/pandapower/build_bus.py +++ b/pandapower/build_bus.py @@ -1,5 +1,5 @@ # -*- coding: utf-8 -*- - +import warnings # Copyright (c) 2016-2024 by University of Kassel and Fraunhofer Institute for Energy Economics # and Energy System Technology (IEE), Kassel. All rights reserved. @@ -642,6 +642,13 @@ def _calc_shunts_and_add_on_ppc(net, ppc): v_ratio = (ppc["bus"][bus_lookup[s["bus"].values], BASE_KV] / s["vn_kv"].values) ** 2 * base_multiplier if "step_dependency_table" in s: + if np.any(vl & (s.step_dependency_table == True) & (s.id_characteristic_table.isna())): + raise UserWarning("Shunts with step_dependency_table True and id_characteristic_table NA detected.\n" + "Please set an id_characteristic_table or set step_dependency_table to False.") + elif (np.any(vl & s.step_dependency_table == False + & ~s.id_characteristic_table.isna())): + warnings.warn("Shunts with step_dependency_table False but id_characteristic_table detected.", + category=UserWarning) s.step_dependency_table.fillna(False) if s.step_dependency_table.any(): s_tmp = s.merge(net.shunt_characteristic_table, how="left", left_on="id_characteristic_table", diff --git a/pandapower/test/api/test_auxiliary.py b/pandapower/test/api/test_auxiliary.py index a4a083673..7ab081ece 100644 --- a/pandapower/test/api/test_auxiliary.py +++ b/pandapower/test/api/test_auxiliary.py @@ -11,6 +11,7 @@ import pandas as pd from pandapower.control import SplineCharacteristic +from pandapower.control.util.auxiliary import create_shunt_characteristic_object from pandapower.control.util.characteristic import LogSplineCharacteristic try: @@ -311,6 +312,40 @@ def test_create_trafo_characteristics(): [[-8, -4, 0, 4, 8], [-8, -4, 0, 4, 8]], [[8.1, 9.1, 10.1, 11.1, 12.1]]) +def test_creation_of_shunt_characteristics(): + net = pp.create_empty_network() + b = pp.create_buses(net, 2, 110) + pp.create_shunt(net, bus=b[1], q_mvar=-50, p_mw=0, step=1, max_step=5) + net["shunt_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [1, 2, 3, 4, 5], 'q_mvar': [-25, -55, -75, -120, -125], + 'p_mw': [1, 1.5, 3, 4.5, 5]}) + net.shunt.step_dependency_table.at[0] = True + net.shunt.id_characteristic_table.at[0] = 0 + + create_shunt_characteristic_object(net) + + assert np.isclose(net.shunt_characteristic_spline.loc[0, "q_mvar_characteristic"](1), -25.) + assert np.isclose(net.shunt_characteristic_spline.loc[0, "q_mvar_characteristic"](3), -75.) + assert np.isclose(net.shunt_characteristic_spline.loc[0, "q_mvar_characteristic"](5), -125.) + assert np.isclose(net.shunt_characteristic_spline.loc[0, "p_mw_characteristic"](1), 1) + assert np.isclose(net.shunt_characteristic_spline.loc[0, "p_mw_characteristic"](3), 3) + assert np.isclose(net.shunt_characteristic_spline.loc[0, "p_mw_characteristic"](5), 5) + + # test re-creation of shunt characteristic object (and deletion of old one) + net["shunt_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [1, 1, 1, 1, 1], 'step': [1, 2, 3, 4, 5], 'q_mvar': [25, 55, 75, 120, 125], + 'p_mw': [6, 6.5, 7, 8.5, 10]}) + net.shunt.id_characteristic_table.at[0] = 1 + + create_shunt_characteristic_object(net) + + assert np.isclose(net.shunt_characteristic_spline.loc[0, "q_mvar_characteristic"](1), 25.) + assert np.isclose(net.shunt_characteristic_spline.loc[0, "q_mvar_characteristic"](3), 75.) + assert np.isclose(net.shunt_characteristic_spline.loc[0, "q_mvar_characteristic"](5), 125.) + assert np.isclose(net.shunt_characteristic_spline.loc[0, "p_mw_characteristic"](1), 6) + assert np.isclose(net.shunt_characteristic_spline.loc[0, "p_mw_characteristic"](3), 7) + assert np.isclose(net.shunt_characteristic_spline.loc[0, "p_mw_characteristic"](5), 10) + @pytest.mark.parametrize("file_io", (False, True), ids=("Without JSON I/O", "With JSON I/O")) def test_characteristic(file_io): diff --git a/pandapower/test/control/test_shunt_control.py b/pandapower/test/control/test_shunt_control.py index b3128a0d7..1641d69ca 100644 --- a/pandapower/test/control/test_shunt_control.py +++ b/pandapower/test/control/test_shunt_control.py @@ -1,8 +1,10 @@ +import pandas as pd import pytest import pandapower as pp from pandapower.control.controller.shunt_control import DiscreteShuntController from pandapower.control.controller.station_control import BinarySearchControl + def simple_test_net_shunt_control(): net = pp.create_empty_network() b = pp.create_buses(net, 2, 110) @@ -33,8 +35,25 @@ def test_discrete_shunt_control(tol=1e-6): pp.runpp(net, run_control=True) assert (abs(net.res_bus.loc[1, "vm_pu"] - 1.077258) < tol) assert net.shunt.loc[0, "step"] == 2 - # net.shunt.step_dependency_table.loc[0] = True - # net.shunt.id_characteristic.loc[0] = 0 + +def test_discrete_shunt_control_with_step_dependency_table(tol=1e-6): + net = simple_test_net_shunt_control() + net["shunt_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [1, 2, 3, 4, 5], 'q_mvar': [-25, -50, -75, -100, -125], + 'p_mw': [0, 0, 0, 0, 0]}) + net.shunt.step_dependency_table.at[0] = True + net.shunt.id_characteristic_table.at[0] = 0 + net.shunt.step.at[0] = 2 + + DiscreteShuntController(net, shunt_index=0, bus_index=1, vm_set_pu=1.08, tol=1e-2) + pp.runpp(net, run_control=False) + + assert (abs(net.res_bus.loc[1, "vm_pu"] - 1.041789) < tol) + + pp.runpp(net, run_control=True) + assert (abs(net.res_bus.loc[1, "vm_pu"] - 1.077258) < tol) + assert net.shunt.loc[0, "step"] == 4 + if __name__ == '__main__': pytest.main(['-s', __file__]) diff --git a/pandapower/test/loadflow/test_runpp.py b/pandapower/test/loadflow/test_runpp.py index 89ddcc231..0ce7d9948 100644 --- a/pandapower/test/loadflow/test_runpp.py +++ b/pandapower/test/loadflow/test_runpp.py @@ -21,6 +21,7 @@ from pandapower.pf.run_newton_raphson_pf import _get_pf_variables_from_ppci from pandapower.powerflow import LoadflowNotConverged from pandapower.test.consistency_checks import runpp_with_consistency_checks +from pandapower.test.control.test_shunt_control import simple_test_net_shunt_control from pandapower.test.loadflow.result_test_network_generator import add_test_xward, add_test_trafo3w, \ add_test_line, add_test_oos_bus_with_is_element, result_test_network_generator, add_test_trafo from pandapower.test.helper_functions import add_grid_connection, create_test_line, assert_net_equal, assert_res_equal @@ -1373,6 +1374,19 @@ def test_tap_dependent_impedance(): assert_res_equal(net, net_backup) +def test_shunt_step_dependency_warning(): + net = simple_test_net_shunt_control() + net["shunt_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [1, 2, 3, 4, 5], 'q_mvar': [-25, -50, -75, -100, -125], + 'p_mw': [0, 0, 0, 0, 0]}) + pp.create_shunt(net, bus=0, q_mvar=-10, p_mw=20, step=1, max_step=5) + net.shunt.step_dependency_table.at[0] = True + net.shunt.step.at[0] = 1 + + with pytest.raises(UserWarning): + pp.runpp(net) + + @pytest.mark.skipif(not lightsim2grid_available, reason="lightsim2grid is not installed") def test_lightsim2grid(): # test several nets From fb185d140a75541b8467d481ced9bf1c0f1b94b0 Mon Sep 17 00:00:00 2001 From: Jakob Kirschner Date: Tue, 10 Dec 2024 09:49:29 +0100 Subject: [PATCH 038/125] fix bug in create.py --- pandapower/create.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/pandapower/create.py b/pandapower/create.py index 7b3934328..1d10c0010 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -4485,8 +4485,9 @@ def create_shunt(net, bus, q_mvar, p_mw=0., vn_kv=None, step=1, max_step=1, name vn_kv = net.bus.vn_kv.at[bus] entries = dict(zip(["bus", "name", "p_mw", "q_mvar", "vn_kv", "step", "max_step", "in_service", - "step_dependency_table"], - [bus, name, p_mw, q_mvar, vn_kv, step, max_step, in_service, step_dependency_table])) + "step_dependency_table", "id_characteristic_table"], + [bus, name, p_mw, q_mvar, vn_kv, step, max_step, in_service, step_dependency_table, + id_characteristic_table])) _set_entries(net, "shunt", index, **entries, **kwargs) _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", From 80c0e9ccb47a0bc4f2a680932356d37ebfe87901 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Tue, 10 Dec 2024 11:12:02 +0200 Subject: [PATCH 039/125] update for pytests --- pandapower/convert_format.py | 19 +++++++++++++++++++ pandapower/networks/mv_oberrhein.json | 11 ----------- .../networks/mv_oberrhein_substations.json | 11 ----------- 3 files changed, 19 insertions(+), 22 deletions(-) diff --git a/pandapower/convert_format.py b/pandapower/convert_format.py index dd19e295f..ed1a84858 100644 --- a/pandapower/convert_format.py +++ b/pandapower/convert_format.py @@ -43,6 +43,7 @@ def convert_format(net, elements_to_deserialize=None): _convert_geo_data(net, elements_to_deserialize) _convert_group_element_index(net) _convert_trafo_controller_parameter_names(net) + _convert_trafo_pst_logic(net) if Version(str(net.format_version)) < Version("2.4.0"): _convert_bus_pq_meas_to_load_reference(net, elements_to_deserialize) if Version(str(net.format_version)) < Version("2.0.0"): @@ -548,3 +549,21 @@ def _update_characteristics(net, elements_to_deserialize): continue c.interpolator_kind = "interp1d" c.kwargs = {"kind": c.__dict__.pop("kind"), "bounds_error": False, "fill_value": c.__dict__.pop("fill_value")} + + +def _convert_trafo_pst_logic(net): + for trafotable in ["trafo", "trafo3w"]: + if trafotable in net and isinstance(net[trafotable], pd.DataFrame): + if net[trafotable].index.size > 0: + if "tap_phase_shifter" in net[trafotable]: + net[trafotable] = net[trafotable].drop(columns="tap_phase_shifter") + # ratio/asymmetrical phase shifters + net[trafotable].loc[ + ((net[trafotable]["tap_step_degree"].isna()) | (net[trafotable]["tap_step_degree"] != 90)) & + (net[trafotable]["tap_step_percent"].notna()), "tap_phase_shifter_type"] = 0 + # symmetrical phase shifters + net[trafotable].loc[(net[trafotable]["tap_step_degree"] == 90) & + (net[trafotable]["tap_step_percent"].notna()), "tap_phase_shifter_type"] = 1 + # ideal phase shifters + net[trafotable].loc[(net[trafotable]["tap_step_degree"].notna()) & + (net[trafotable]["tap_step_percent"].isna()), "tap_phase_shifter_type"] = 2 diff --git a/pandapower/networks/mv_oberrhein.json b/pandapower/networks/mv_oberrhein.json index 1384c4dc0..b81d29bac 100644 --- a/pandapower/networks/mv_oberrhein.json +++ b/pandapower/networks/mv_oberrhein.json @@ -514,17 +514,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/mv_oberrhein_substations.json b/pandapower/networks/mv_oberrhein_substations.json index 00ceab33b..d0b8998fb 100644 --- a/pandapower/networks/mv_oberrhein_substations.json +++ b/pandapower/networks/mv_oberrhein_substations.json @@ -514,17 +514,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", From 9b3e40548cfb990cb01ca905c0448d9feb47ff04 Mon Sep 17 00:00:00 2001 From: Jakob Kirschner Date: Tue, 10 Dec 2024 10:53:41 +0100 Subject: [PATCH 040/125] remove required columns in trafo, trafo3w std types --- pandapower/std_types.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pandapower/std_types.py b/pandapower/std_types.py index 68ef31def..c4eae117e 100644 --- a/pandapower/std_types.py +++ b/pandapower/std_types.py @@ -85,12 +85,12 @@ def create_std_type(net, data, name, element="line", overwrite=True, check_requi required = ["r_ohm_per_km","max_i_ka"] elif element == "trafo": required = ["sn_mva", "vn_hv_kv", "vn_lv_kv", "vk_percent", "vkr_percent", - "pfe_kw", "i0_percent", "shift_degree", "tap_phase_shifter_type", "trafo_characteristic_table"] + "pfe_kw", "i0_percent", "shift_degree"] elif element == "trafo3w": required = ["sn_hv_mva", "sn_mv_mva", "sn_lv_mva", "vn_hv_kv", "vn_mv_kv", "vn_lv_kv", "vk_hv_percent", "vk_mv_percent", "vk_lv_percent", "vkr_hv_percent", "vkr_mv_percent", "vkr_lv_percent", "pfe_kw", "i0_percent", "shift_mv_degree", - "shift_lv_degree", "tap_phase_shifter_type", "trafo_characteristic_table"] + "shift_lv_degree"] elif element == "fuse": required = ["fuse_type", "i_rated_a"] else: From 785fa955c4cab7e4cdd9aa3cef4ae671bd1aa5f3 Mon Sep 17 00:00:00 2001 From: Jakob Kirschner Date: Tue, 10 Dec 2024 15:19:33 +0100 Subject: [PATCH 041/125] fix create trafos and std types --- pandapower/create.py | 14 +++++++------- pandapower/test/loadflow/runpp_3ph Validation.json | 6 ++++-- 2 files changed, 11 insertions(+), 9 deletions(-) diff --git a/pandapower/create.py b/pandapower/create.py index 1d10c0010..537bacd0c 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -3383,18 +3383,15 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in "i0_percent": ti["i0_percent"], "parallel": parallel, "df": df, - "shift_degree": ti["shift_degree"] if "shift_degree" in ti else 0, - "tap_phase_shifter_type": ti["tap_phase_shifter_type"] if "tap_phase_shifter_type" in ti else nan + "shift_degree": ti["shift_degree"] if "shift_degree" in ti else 0 } - if "tap2_phase_shifter_type" in ti: - updates["tap2_phase_shifter_type"] = ti["tap2_phase_shifter_type"] for zero_param in ['vk0_percent', 'vkr0_percent', 'mag0_percent', 'mag0_rx', 'si0_hv_partial']: if zero_param in ti: updates[zero_param] = ti[zero_param] v.update(updates) for s, tap_pos_var in (("", tap_pos), ("2", tap2_pos)): # to enable a second tap changer if available for tp in (f"tap{s}_neutral", f"tap{s}_max", f"tap{s}_min", f"tap{s}_side", - f"tap{s}_step_percent", f"tap{s}_step_degree"): + f"tap{s}_step_percent", f"tap{s}_step_degree", f"tap{s}_phase_shifter_type"): if tp in ti: v[tp] = ti[tp] if (f"tap{s}_neutral" in v) and (tap_pos_var is nan): @@ -3812,7 +3809,7 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_pos=nan, in_service=True, index=None, max_loading_percent=nan, tap_phase_shifter_type=nan, - tap_at_star_point=False, tap_dependency_table=False, id_characteristic_table=nan): + tap_at_star_point=False, tap_dependency_table=nan, id_characteristic_table=nan): """ Creates a three-winding transformer in table net["trafo3w"]. The trafo parameters are defined through the standard type library. @@ -3903,7 +3900,8 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p "tap_at_star_point": tap_at_star_point }) for tp in ( - "tap_neutral", "tap_max", "tap_min", "tap_side", "tap_step_percent", "tap_step_degree"): + "tap_neutral", "tap_max", "tap_min", "tap_side", "tap_step_percent", "tap_step_degree", + "tap_phase_shifter_type"): if tp in ti: v.update({tp: ti[tp]}) @@ -3921,6 +3919,8 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p _set_value_if_not_nan(net, index, max_loading_percent, "max_loading_percent", "trafo3w") _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo3w", dtype="Int64") + _set_value_if_not_nan(net, index, tap_dependency_table, + "tap_dependency_table", "trafo3w", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, tap_phase_shifter_type, "tap_phase_shifter_type", "trafo3w", dtype="Int64") diff --git a/pandapower/test/loadflow/runpp_3ph Validation.json b/pandapower/test/loadflow/runpp_3ph Validation.json index 648556f3c..ef86eedf2 100644 --- a/pandapower/test/loadflow/runpp_3ph Validation.json +++ b/pandapower/test/loadflow/runpp_3ph Validation.json @@ -1294,7 +1294,8 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2 + "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0 }, "63/25/38 MVA 110/10/10 kV": { "sn_hv_mva": 63, @@ -1318,7 +1319,8 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2 + "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0 } } }, From 242e7684d5f623efb188898e54814e8787e8a698 Mon Sep 17 00:00:00 2001 From: Jakob Kirschner Date: Tue, 10 Dec 2024 17:34:15 +0100 Subject: [PATCH 042/125] fix tap dependency in build branch --- pandapower/build_branch.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 5dfe23131..63f1fdb3f 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -607,7 +607,7 @@ def _calc_tap_from_dataframe(net, trafo_df): if f'tap{t}_dependency_table' in trafo_df: tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") tap_dependency = np.array( - [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency]) + [False if (isinstance(x, float) and np.isnan(x)) or (x is None) else x for x in tap_dependency]) else: tap_table = np.array([False]) tap_dependency = np.array([False]) From 01ef52a07836c25c6c01cc031829f20695dcbef6 Mon Sep 17 00:00:00 2001 From: Jakob Kirschner Date: Wed, 11 Dec 2024 10:36:47 +0100 Subject: [PATCH 043/125] Revert "fix tap dependency in build branch" This reverts commit 242e7684d5f623efb188898e54814e8787e8a698. --- pandapower/build_branch.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 63f1fdb3f..5dfe23131 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -607,7 +607,7 @@ def _calc_tap_from_dataframe(net, trafo_df): if f'tap{t}_dependency_table' in trafo_df: tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") tap_dependency = np.array( - [False if (isinstance(x, float) and np.isnan(x)) or (x is None) else x for x in tap_dependency]) + [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency]) else: tap_table = np.array([False]) tap_dependency = np.array([False]) From 69e7dc3d35496d7085044c74164fd6495ed53e77 Mon Sep 17 00:00:00 2001 From: Jakob Kirschner Date: Wed, 11 Dec 2024 10:48:36 +0100 Subject: [PATCH 044/125] fix get equivalent tests --- pandapower/grid_equivalents/get_equivalent.py | 15 ++++++++------- pandapower/grid_equivalents/rei_generation.py | 2 ++ 2 files changed, 10 insertions(+), 7 deletions(-) diff --git a/pandapower/grid_equivalents/get_equivalent.py b/pandapower/grid_equivalents/get_equivalent.py index 2cd5ef8c9..6627311ec 100644 --- a/pandapower/grid_equivalents/get_equivalent.py +++ b/pandapower/grid_equivalents/get_equivalent.py @@ -422,13 +422,14 @@ def merge_internal_net_and_equivalent_external_net( def drop_repeated_characteristic(net): idxs = [] repeated_idxs = [] - for m in net.characteristic.index: - idx = net.characteristic.object[m].__dict__["index"] - if idx in idxs: - repeated_idxs.append(m) - else: - idxs.append(idx) - net.characteristic = net.characteristic.drop(repeated_idxs) + if "characteristic" in net: + for m in net.characteristic.index: + idx = net.characteristic.object[m].__dict__["index"] + if idx in idxs: + repeated_idxs.append(m) + else: + idxs.append(idx) + net.characteristic = net.characteristic.drop(repeated_idxs) def _determine_bus_groups(net, boundary_buses, internal_buses, diff --git a/pandapower/grid_equivalents/rei_generation.py b/pandapower/grid_equivalents/rei_generation.py index c217776e7..9192aca6a 100644 --- a/pandapower/grid_equivalents/rei_generation.py +++ b/pandapower/grid_equivalents/rei_generation.py @@ -675,6 +675,8 @@ def _replace_ext_area_by_impedances_and_shunts( new_shunts["step"] = 1 new_shunts["max_step"] = 1 new_shunts["in_service"] = True + if "step_dependency_table" in net_eq.shunt: + new_shunts["step_dependency_table"] = False net_eq["shunt"] = pd.concat([net_eq["shunt"], new_shunts]) if n_disconnected_new_eq_shunts := sum(~isin_sh): msg = f"{n_disconnected_new_eq_shunts=}, missing buses: {new_shunts.bus.loc[~isin_sh]}" From df354e063363e5899770b94eda3188824f22bf5e Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Wed, 11 Dec 2024 12:24:00 +0200 Subject: [PATCH 045/125] remove todo from test_tap_dependent_impedance.py lib --- pandapower/test/control/test_tap_dependent_impedance.py | 1 - 1 file changed, 1 deletion(-) diff --git a/pandapower/test/control/test_tap_dependent_impedance.py b/pandapower/test/control/test_tap_dependent_impedance.py index 4c58d9761..c228171da 100644 --- a/pandapower/test/control/test_tap_dependent_impedance.py +++ b/pandapower/test/control/test_tap_dependent_impedance.py @@ -12,7 +12,6 @@ trafo_characteristic_table_diagnostic -# todo add tests for voltage_ratio and angle_dev def test_tap_dependent_impedance_control(): net = pp.create_empty_network() b1 = pp.create_bus(net, 110) From 6abdada71825a0e4512fb44c76ee109868b1f9ae Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 12 Dec 2024 18:39:28 +0200 Subject: [PATCH 046/125] amend pytests / fix bugs to remove pytest fails --- pandapower/build_branch.py | 20 +++++++------ pandapower/contingency/contingency.py | 17 ++++++----- pandapower/convert_format.py | 30 +++++++++++-------- pandapower/converter/pypower/from_ppc.py | 7 +++-- pandapower/create.py | 9 ++++-- pandapower/grid_equivalents/get_equivalent.py | 18 +++++------ .../GBnetwork.json | 19 +++++++++++- .../GBreducednetwork.json | 19 +++++++++++- .../power_system_test_case_jsons/case118.json | 5 +++- .../case11_iwamoto.json | 9 ++++-- .../case1354pegase.json | 5 +++- .../power_system_test_case_jsons/case14.json | 5 +++- .../power_system_test_case_jsons/case145.json | 5 +++- .../case1888rte.json | 5 +++- .../case24_ieee_rts.json | 5 +++- .../case2848rte.json | 5 +++- .../case2869pegase.json | 5 +++- .../power_system_test_case_jsons/case30.json | 5 +++- .../power_system_test_case_jsons/case300.json | 5 +++- .../case3120sp.json | 5 +++- .../case33bw.json | 5 +++- .../power_system_test_case_jsons/case39.json | 5 +++- .../power_system_test_case_jsons/case4gs.json | 5 +++- .../power_system_test_case_jsons/case5.json | 5 +++- .../power_system_test_case_jsons/case57.json | 5 +++- .../case5_demo_gridcal.json | 19 +++++++++++- .../case6470rte.json | 5 +++- .../case6495rte.json | 5 +++- .../case6515rte.json | 5 +++- .../power_system_test_case_jsons/case6ww.json | 5 +++- .../case89pegase.json | 5 +++- .../power_system_test_case_jsons/case9.json | 5 +++- .../case9241pegase.json | 5 +++- .../case_ieee30.json | 5 +++- .../case_illinois200.json | 5 +++- .../power_system_test_case_jsons/iceland.json | 19 +++++++++++- .../test/converter/test_from_powerfactory.py | 2 +- .../converter/testfiles/test_line_3ph.json | 21 +++++++------ .../test_net_3ph_test_2020_10_19.json | 9 ++++-- .../converter/testfiles/test_trafo_3ph.json | 9 ++++-- .../grid_equivalents/test_get_equivalent.py | 15 ++++++++-- 41 files changed, 273 insertions(+), 94 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 5dfe23131..aef0a8311 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -612,9 +612,8 @@ def _calc_tap_from_dataframe(net, trafo_df): tap_table = np.array([False]) tap_dependency = np.array([False]) if not isinstance(trafo_df, dict) and not isinstance(phase_shifter_type, np.ndarray): - phase_shifter_type = phase_shifter_type.to_numpy() \ - if not isinstance(trafo_df, dict) else phase_shifter_type - phase_shifter_type = np.nan_to_num(phase_shifter_type, nan=-1) + phase_shifter_type = phase_shifter_type.to_numpy() + phase_shifter_type = pd.Series(phase_shifter_type).fillna(-1).to_numpy() tap_table = np.logical_and(tap_dependency, np.logical_not(phase_shifter_type == -1)) tap_no_table = np.logical_and(~tap_dependency, np.logical_not(phase_shifter_type == -1)) if any(tap_table): @@ -1347,12 +1346,15 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): trafo2["vn_lv_kv"] = {side: t3["vn_%s_kv" % side].values for side in sides} trafo2["shift_degree"] = {"hv": np.zeros(nr_trafos), "mv": t3.shift_mv_degree.values, "lv": t3.shift_lv_degree.values} - if 'tap_dependency_table' in t3: - trafo2["tap_phase_shifter_type"] = {side: t3.tap_phase_shifter_type for side in sides} - trafo2["tap_dependency_table"] = {side: t3.tap_dependency_table for side in sides} - trafo2["id_characteristic_table"] = {side: t3.id_characteristic_table for side in sides} - else: - trafo2["tap_phase_shifter"] = {side: np.zeros(nr_trafos).astype(bool) for side in sides} + # if 'tap_dependency_table' in t3: + # trafo2["tap_phase_shifter_type"] = {side: t3.tap_phase_shifter_type for side in sides} + # trafo2["tap_dependency_table"] = {side: t3.tap_dependency_table for side in sides} + # trafo2["id_characteristic_table"] = {side: t3.id_characteristic_table for side in sides} + # else: + # trafo2["tap_phase_shifter"] = {side: np.zeros(nr_trafos).astype(bool) for side in sides} + for param in ["tap_phase_shifter_type", "tap_dependency_table", "id_characteristic_table", "tap_phase_shifter"]: + if param in t3: + trafo2[param] = {side: t3[param] for side in sides} trafo2["parallel"] = {side: np.ones(nr_trafos) for side in sides} trafo2["df"] = {side: np.ones(nr_trafos) for side in sides} # even though this is not relevant (at least now), the values cannot be empty: diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index 91540f8e5..ae0140033 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -177,10 +177,10 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. contingency_evaluation_function(net, **kwargs) trafo_flag = False - if "tap_phase_shifter" in net.trafo.columns: - if np.any(net.trafo.tap_phase_shifter): + if "tap_phase_shifter_type" in net.trafo.columns: + if np.any(net.trafo.tap_phase_shifter_type == 2): trafo_flag = True - tap_phase_shifter, tap_pos, shift_degree = _convert_trafo_phase_shifter(net) + tap_phase_shifter_type, tap_pos, shift_degree = _convert_trafo_phase_shifter(net) # setting "slack" back-and-forth is due to the difference in interpretation of generators as "distributed slack" if net._options.get("distributed_slack", False): @@ -198,7 +198,7 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. solver_type = SolverType.KLUSingleSlack if KLU_solver_available else SolverType.SparseLUSingleSlack if trafo_flag: - net.trafo.tap_phase_shifter = tap_phase_shifter + net.trafo.tap_phase_shifter_type = tap_phase_shifter_type net.trafo.tap_pos = tap_pos net.trafo.shift_degree = shift_degree @@ -294,7 +294,7 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. def _convert_trafo_phase_shifter(net): - tap_phase_shifter = net.trafo.tap_phase_shifter.values.copy() + tap_phase_shifter_type = net.trafo.tap_phase_shifter_type.values.copy() # vn_hv_kv = net.trafo.vn_hv_kv.values.copy() shift_degree = net.trafo.shift_degree.values.copy() @@ -303,11 +303,12 @@ def _convert_trafo_phase_shifter(net): tap_diff = tap_pos - tap_neutral tap_step_degree = net.trafo.tap_step_degree.values.copy() - net.trafo.loc[tap_phase_shifter, 'shift_degree'] += tap_diff[tap_phase_shifter] * tap_step_degree[tap_phase_shifter] + net.trafo.loc[tap_phase_shifter_type == 2, 'shift_degree'] += (tap_diff[tap_phase_shifter_type == 2] * + tap_step_degree[tap_phase_shifter_type == 2]) net.trafo["tap_pos"] = 0 - net.trafo["tap_phase_shifter"] = False + net.trafo["tap_phase_shifter_type"] = pd.NA - return tap_phase_shifter, tap_pos, shift_degree + return tap_phase_shifter_type, tap_pos, shift_degree def _update_contingency_results(net, contingency_results, result_variables, nminus1, cause_element=None, diff --git a/pandapower/convert_format.py b/pandapower/convert_format.py index ed1a84858..c2016fd0d 100644 --- a/pandapower/convert_format.py +++ b/pandapower/convert_format.py @@ -555,15 +555,21 @@ def _convert_trafo_pst_logic(net): for trafotable in ["trafo", "trafo3w"]: if trafotable in net and isinstance(net[trafotable], pd.DataFrame): if net[trafotable].index.size > 0: - if "tap_phase_shifter" in net[trafotable]: - net[trafotable] = net[trafotable].drop(columns="tap_phase_shifter") - # ratio/asymmetrical phase shifters - net[trafotable].loc[ - ((net[trafotable]["tap_step_degree"].isna()) | (net[trafotable]["tap_step_degree"] != 90)) & - (net[trafotable]["tap_step_percent"].notna()), "tap_phase_shifter_type"] = 0 - # symmetrical phase shifters - net[trafotable].loc[(net[trafotable]["tap_step_degree"] == 90) & - (net[trafotable]["tap_step_percent"].notna()), "tap_phase_shifter_type"] = 1 - # ideal phase shifters - net[trafotable].loc[(net[trafotable]["tap_step_degree"].notna()) & - (net[trafotable]["tap_step_percent"].isna()), "tap_phase_shifter_type"] = 2 + for t in ("", "2"): + # drop old tap_phase_shifter flag + if f"tap{t}_phase_shifter" in net[trafotable]: + net[trafotable] = net[trafotable].drop(columns=f"tap{t}_phase_shifter") + if (f"tap{t}_step_degree" in net[trafotable]) or (f"tap{t}_step_percent" in net[trafotable]): + # ratio/asymmetrical phase shifters + net[trafotable].loc[ + ((net[trafotable][f"tap{t}_step_degree"].isna()) | + (net[trafotable][f"tap{t}_step_degree"] != 90)) & + (net[trafotable][f"tap{t}_step_percent"].notna()), f"tap{t}_phase_shifter_type"] = 0 + # symmetrical phase shifters + net[trafotable].loc[ + (net[trafotable][f"tap{t}_step_degree"] == 90) & + (net[trafotable][f"tap{t}_step_percent"].notna()), f"tap{t}_phase_shifter_type"] = 1 + # ideal phase shifters + net[trafotable].loc[ + (net[trafotable][f"tap{t}_step_degree"].notna()) & + (net[trafotable][f"tap{t}_step_percent"].isna()), f"tap{t}_phase_shifter_type"] = 2 diff --git a/pandapower/converter/pypower/from_ppc.py b/pandapower/converter/pypower/from_ppc.py index b851934e7..f25a0bef9 100644 --- a/pandapower/converter/pypower/from_ppc.py +++ b/pandapower/converter/pypower/from_ppc.py @@ -286,14 +286,17 @@ def _from_ppc_branch(net, ppc, f_hz, **kwargs): vkr_percent = rk * sn * 100 / baseMVA vkr_percent[~tap_side_is_hv] /= (1+ratio_1[~tap_side_is_hv])**2 + tap_step_percent = np.abs(ratio_1)*100 + tap_phase_shifter_type = np.where(tap_step_percent > 0, 0, pd.NA) + idx_trafo = create_transformers_from_parameters( net, hv_buses=net.bus.index[hv_bus], lv_buses=net.bus.index[lv_bus], sn_mva=sn, vn_hv_kv=vn_hv_kv, vn_lv_kv=vn_lv_kv, name=bra_name[is_trafo], vk_percent=vk_percent, vkr_percent=vkr_percent, max_loading_percent=100, pfe_kw=pfe_kw, i0_percent=i0_percent, shift_degree=ppc['branch'][is_trafo, SHIFT], - tap_step_percent=np.abs(ratio_1)*100, tap_pos=np.sign(ratio_1), - tap_side=tap_side, tap_neutral=0) + tap_step_percent=tap_step_percent, tap_pos=np.sign(ratio_1), + tap_side=tap_side, tap_neutral=0, tap_phase_shifter_type=tap_phase_shifter_type) else: idx_trafo = [] # unused data from ppc: rateB, rateC diff --git a/pandapower/create.py b/pandapower/create.py index 537bacd0c..d10eb2bb9 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -3583,8 +3583,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn "pfe_kw": pfe_kw, "i0_percent": i0_percent, "tap_neutral": tap_neutral, "tap_max": tap_max, "tap_min": tap_min, "shift_degree": shift_degree, "tap_side": tap_side, "tap_step_percent": tap_step_percent, - "tap_step_degree": tap_step_degree, "tap_phase_shifter_type": tap_phase_shifter_type, - "parallel": parallel, "df": df} + "tap_step_degree": tap_step_degree, "parallel": parallel, "df": df} if ("tap_neutral" in v) and (tap_pos is nan): v["tap_pos"] = v["tap_neutral"] @@ -3598,6 +3597,10 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo", dtype="Int64") + _set_value_if_not_nan(net, index, tap_phase_shifter_type, + "tap_phase_shifter_type", "trafo", dtype="Int64") + _set_value_if_not_nan(net, index, tap_dependency_table, + "tap_dependency_table", "trafo", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, tap2_side, "tap2_side", "trafo", dtype=str) _set_value_if_not_nan(net, index, tap2_neutral, "tap2_neutral", "trafo", dtype=np.float64) @@ -4085,6 +4088,8 @@ def create_transformer3w_from_parameters( "id_characteristic_table", "trafo3w", dtype="Int64") _set_value_if_not_nan(net, index, tap_phase_shifter_type, "tap_phase_shifter_type", "trafo3w", dtype="Int64") + _set_value_if_not_nan(net, index, tap_dependency_table, + "tap_dependency_table", "trafo3w", dtype=bool_, default_val=False) return index diff --git a/pandapower/grid_equivalents/get_equivalent.py b/pandapower/grid_equivalents/get_equivalent.py index 6627311ec..14a6ae1b2 100644 --- a/pandapower/grid_equivalents/get_equivalent.py +++ b/pandapower/grid_equivalents/get_equivalent.py @@ -420,16 +420,14 @@ def merge_internal_net_and_equivalent_external_net( def drop_repeated_characteristic(net): - idxs = [] - repeated_idxs = [] - if "characteristic" in net: - for m in net.characteristic.index: - idx = net.characteristic.object[m].__dict__["index"] - if idx in idxs: - repeated_idxs.append(m) - else: - idxs.append(idx) - net.characteristic = net.characteristic.drop(repeated_idxs) + for characteristic in ["trafo_characteristic_table", "shunt_characteristic_table", + "trafo_characteristic_spline", "shunt_characteristic_spline"]: + if characteristic in net: + # get the list of indices of duplicate rows + repeated_idxs = net[characteristic][ + net[characteristic].fillna("NA_PLACEHOLDER").duplicated()].index.tolist() + # drop repeated rows + net[characteristic] = net[characteristic].drop(repeated_idxs) def _determine_bus_groups(net, boundary_buses, internal_buses, diff --git a/pandapower/networks/power_system_test_case_jsons/GBnetwork.json b/pandapower/networks/power_system_test_case_jsons/GBnetwork.json index feced48bc..70f492749 100644 --- a/pandapower/networks/power_system_test_case_jsons/GBnetwork.json +++ b/pandapower/networks/power_system_test_case_jsons/GBnetwork.json @@ -329,7 +329,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -359,6 +359,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -804,6 +805,7 @@ "tap_min": -2, "vkr_percent": 1.425, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -821,6 +823,7 @@ "tap_min": -2, "vkr_percent": 1.44, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -838,6 +841,7 @@ "tap_min": -2, "vkr_percent": 1.2, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -855,6 +859,7 @@ "tap_min": -9, "vkr_percent": 0.25, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 12.2, "tap_max": 9 @@ -872,6 +877,7 @@ "tap_min": -9, "vkr_percent": 0.31, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -889,6 +895,7 @@ "tap_min": -2, "vkr_percent": 1.206, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -906,6 +913,7 @@ "tap_min": -2, "vkr_percent": 1.325, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -923,6 +931,7 @@ "tap_min": -2, "vkr_percent": 1.0794, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -940,6 +949,7 @@ "tap_min": -9, "vkr_percent": 0.322, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -957,6 +967,7 @@ "tap_min": -9, "vkr_percent": 0.26, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 12.0, "tap_max": 9 @@ -974,6 +985,7 @@ "tap_min": -9, "vkr_percent": 0.276, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -991,6 +1003,7 @@ "tap_min": -9, "vkr_percent": 0.302, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1008,6 +1021,7 @@ "tap_min": -9, "vkr_percent": 0.282, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1025,6 +1039,7 @@ "tap_min": -9, "vkr_percent": 0.295, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -1052,6 +1067,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1076,6 +1092,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json b/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json index 1f5f1baa0..4c9863077 100644 --- a/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json +++ b/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json @@ -334,7 +334,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -364,6 +364,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -809,6 +810,7 @@ "tap_min": -2, "vkr_percent": 1.425, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -825,6 +827,7 @@ "tap_min": -2, "vkr_percent": 1.44, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -841,6 +844,7 @@ "tap_min": -2, "vkr_percent": 1.2, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -857,6 +861,7 @@ "tap_min": -9, "vkr_percent": 0.25, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 12.2, "tap_max": 9 @@ -873,6 +878,7 @@ "tap_min": -9, "vkr_percent": 0.31, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -889,6 +895,7 @@ "tap_min": -2, "vkr_percent": 1.206, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -905,6 +912,7 @@ "tap_min": -2, "vkr_percent": 1.325, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -921,6 +929,7 @@ "tap_min": -2, "vkr_percent": 1.0794, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -937,6 +946,7 @@ "tap_min": -9, "vkr_percent": 0.322, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -953,6 +963,7 @@ "tap_min": -9, "vkr_percent": 0.26, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 12.0, "tap_max": 9 @@ -969,6 +980,7 @@ "tap_min": -9, "vkr_percent": 0.276, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -985,6 +997,7 @@ "tap_min": -9, "vkr_percent": 0.302, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1001,6 +1014,7 @@ "tap_min": -9, "vkr_percent": 0.282, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1017,6 +1031,7 @@ "tap_min": -9, "vkr_percent": 0.295, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -1044,6 +1059,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1068,6 +1084,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case118.json b/pandapower/networks/power_system_test_case_jsons/case118.json index c1e127e0b..56bd2e43d 100644 --- a/pandapower/networks/power_system_test_case_jsons/case118.json +++ b/pandapower/networks/power_system_test_case_jsons/case118.json @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,6 +362,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1297,6 +1298,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1321,6 +1323,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json b/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json index 4ba762bdb..e836218d3 100644 --- a/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json +++ b/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json @@ -320,7 +320,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -350,6 +350,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1286,7 +1287,8 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2 + "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0 }, "63/25/38 MVA 110/10/10 kV": { "vn_hv_kv": 110, @@ -1310,7 +1312,8 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2 + "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0 } }, "fuse": {} diff --git a/pandapower/networks/power_system_test_case_jsons/case1354pegase.json b/pandapower/networks/power_system_test_case_jsons/case1354pegase.json index 4fb86767a..93e584079 100644 --- a/pandapower/networks/power_system_test_case_jsons/case1354pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case1354pegase.json @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,6 +363,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1298,6 +1299,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1322,6 +1324,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case14.json b/pandapower/networks/power_system_test_case_jsons/case14.json index c60707aa5..fe668249f 100644 --- a/pandapower/networks/power_system_test_case_jsons/case14.json +++ b/pandapower/networks/power_system_test_case_jsons/case14.json @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,6 +362,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1297,6 +1298,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1321,6 +1323,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case145.json b/pandapower/networks/power_system_test_case_jsons/case145.json index 1104e61e2..bf0417720 100644 --- a/pandapower/networks/power_system_test_case_jsons/case145.json +++ b/pandapower/networks/power_system_test_case_jsons/case145.json @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,6 +363,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1298,6 +1299,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1322,6 +1324,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case1888rte.json b/pandapower/networks/power_system_test_case_jsons/case1888rte.json index 7a7d0690a..009af257f 100644 --- a/pandapower/networks/power_system_test_case_jsons/case1888rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case1888rte.json @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,6 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1302,6 +1303,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1326,6 +1328,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json b/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json index b68ae2328..00fd00c25 100644 --- a/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json +++ b/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,6 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1302,6 +1303,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1326,6 +1328,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case2848rte.json b/pandapower/networks/power_system_test_case_jsons/case2848rte.json index d8d3f499d..0da9e77f2 100644 --- a/pandapower/networks/power_system_test_case_jsons/case2848rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case2848rte.json @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,6 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1302,6 +1303,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1326,6 +1328,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case2869pegase.json b/pandapower/networks/power_system_test_case_jsons/case2869pegase.json index 311d9adab..8ed783375 100644 --- a/pandapower/networks/power_system_test_case_jsons/case2869pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case2869pegase.json @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,6 +363,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1298,6 +1299,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1322,6 +1324,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case30.json b/pandapower/networks/power_system_test_case_jsons/case30.json index c9e98641d..ed0f5304f 100644 --- a/pandapower/networks/power_system_test_case_jsons/case30.json +++ b/pandapower/networks/power_system_test_case_jsons/case30.json @@ -331,7 +331,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -361,6 +361,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1296,6 +1297,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1320,6 +1322,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case300.json b/pandapower/networks/power_system_test_case_jsons/case300.json index 9831cf3a0..bd01be095 100644 --- a/pandapower/networks/power_system_test_case_jsons/case300.json +++ b/pandapower/networks/power_system_test_case_jsons/case300.json @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,6 +363,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1298,6 +1299,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1322,6 +1324,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case3120sp.json b/pandapower/networks/power_system_test_case_jsons/case3120sp.json index 79f00771c..fc9564e0b 100644 --- a/pandapower/networks/power_system_test_case_jsons/case3120sp.json +++ b/pandapower/networks/power_system_test_case_jsons/case3120sp.json @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,6 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1302,6 +1303,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1326,6 +1328,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case33bw.json b/pandapower/networks/power_system_test_case_jsons/case33bw.json index ccff274db..8f31434af 100644 --- a/pandapower/networks/power_system_test_case_jsons/case33bw.json +++ b/pandapower/networks/power_system_test_case_jsons/case33bw.json @@ -328,7 +328,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -358,6 +358,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1289,6 +1290,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1313,6 +1315,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case39.json b/pandapower/networks/power_system_test_case_jsons/case39.json index 0735ff541..85784f612 100644 --- a/pandapower/networks/power_system_test_case_jsons/case39.json +++ b/pandapower/networks/power_system_test_case_jsons/case39.json @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,6 +362,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1297,6 +1298,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1321,6 +1323,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case4gs.json b/pandapower/networks/power_system_test_case_jsons/case4gs.json index e956f9699..6b2761d03 100644 --- a/pandapower/networks/power_system_test_case_jsons/case4gs.json +++ b/pandapower/networks/power_system_test_case_jsons/case4gs.json @@ -331,7 +331,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -361,6 +361,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1292,6 +1293,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1316,6 +1318,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case5.json b/pandapower/networks/power_system_test_case_jsons/case5.json index 8dcfb6f84..c6a0374ed 100644 --- a/pandapower/networks/power_system_test_case_jsons/case5.json +++ b/pandapower/networks/power_system_test_case_jsons/case5.json @@ -336,7 +336,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -366,6 +366,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1297,6 +1298,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1321,6 +1323,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case57.json b/pandapower/networks/power_system_test_case_jsons/case57.json index d70bf2bfe..bcfe80c86 100644 --- a/pandapower/networks/power_system_test_case_jsons/case57.json +++ b/pandapower/networks/power_system_test_case_jsons/case57.json @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,6 +362,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1297,6 +1298,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1321,6 +1323,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json b/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json index 36704e677..4c556ded6 100644 --- a/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json +++ b/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json @@ -326,7 +326,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -356,6 +356,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -802,6 +803,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "vk_percent": 4.0, "vkr_percent": 1.2 }, @@ -819,6 +821,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "vk_percent": 6.0, "vkr_percent": 1.44 }, @@ -836,6 +839,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "vk_percent": 4.0, "vkr_percent": 1.325 }, @@ -853,6 +857,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "vk_percent": 6.0, "vkr_percent": 1.425 }, @@ -870,6 +875,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "vk_percent": 4.0, "vkr_percent": 1.0794 }, @@ -887,6 +893,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "vk_percent": 6.0, "vkr_percent": 1.206 }, @@ -904,6 +911,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "vk_percent": 12.0, "vkr_percent": 0.26 }, @@ -921,6 +929,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "vk_percent": 12.2, "vkr_percent": 0.25 }, @@ -938,6 +947,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "vk_percent": 10.04, "vkr_percent": 0.276 }, @@ -955,6 +965,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "vk_percent": 11.2, "vkr_percent": 0.282 }, @@ -972,6 +983,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "vk_percent": 10.04, "vkr_percent": 0.295 }, @@ -989,6 +1001,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "vk_percent": 11.2, "vkr_percent": 0.302 }, @@ -1006,6 +1019,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "vk_percent": 10.04, "vkr_percent": 0.31 }, @@ -1023,6 +1037,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "vk_percent": 11.2, "vkr_percent": 0.322 } @@ -1045,6 +1060,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1069,6 +1085,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case6470rte.json b/pandapower/networks/power_system_test_case_jsons/case6470rte.json index 612d183ba..d565bc2b7 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6470rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6470rte.json @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,6 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1302,6 +1303,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1326,6 +1328,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case6495rte.json b/pandapower/networks/power_system_test_case_jsons/case6495rte.json index 67dcc6410..723de1b70 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6495rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6495rte.json @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,6 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1302,6 +1303,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1326,6 +1328,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case6515rte.json b/pandapower/networks/power_system_test_case_jsons/case6515rte.json index 9281e83f9..b9fe8a35d 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6515rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6515rte.json @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,6 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1302,6 +1303,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1326,6 +1328,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case6ww.json b/pandapower/networks/power_system_test_case_jsons/case6ww.json index d139511e1..e6a9e477b 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6ww.json +++ b/pandapower/networks/power_system_test_case_jsons/case6ww.json @@ -331,7 +331,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -361,6 +361,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1292,6 +1293,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1316,6 +1318,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case89pegase.json b/pandapower/networks/power_system_test_case_jsons/case89pegase.json index cfb7acbb8..27b127eb3 100644 --- a/pandapower/networks/power_system_test_case_jsons/case89pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case89pegase.json @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,6 +363,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1298,6 +1299,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1322,6 +1324,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case9.json b/pandapower/networks/power_system_test_case_jsons/case9.json index ad2a92db2..5dc5d798e 100644 --- a/pandapower/networks/power_system_test_case_jsons/case9.json +++ b/pandapower/networks/power_system_test_case_jsons/case9.json @@ -331,7 +331,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -361,6 +361,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1292,6 +1293,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1316,6 +1318,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case9241pegase.json b/pandapower/networks/power_system_test_case_jsons/case9241pegase.json index 1e29d7e6e..14fb711fa 100644 --- a/pandapower/networks/power_system_test_case_jsons/case9241pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case9241pegase.json @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,6 +363,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1298,6 +1299,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1322,6 +1324,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case_ieee30.json b/pandapower/networks/power_system_test_case_jsons/case_ieee30.json index 900ab606b..c53971866 100644 --- a/pandapower/networks/power_system_test_case_jsons/case_ieee30.json +++ b/pandapower/networks/power_system_test_case_jsons/case_ieee30.json @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,6 +362,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1293,6 +1294,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1317,6 +1319,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case_illinois200.json b/pandapower/networks/power_system_test_case_jsons/case_illinois200.json index b1f04d6dc..6ade53507 100644 --- a/pandapower/networks/power_system_test_case_jsons/case_illinois200.json +++ b/pandapower/networks/power_system_test_case_jsons/case_illinois200.json @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,6 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1298,6 +1299,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1322,6 +1324,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/iceland.json b/pandapower/networks/power_system_test_case_jsons/iceland.json index 2b4f97b08..7a4d4d202 100644 --- a/pandapower/networks/power_system_test_case_jsons/iceland.json +++ b/pandapower/networks/power_system_test_case_jsons/iceland.json @@ -329,7 +329,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -359,6 +359,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -804,6 +805,7 @@ "tap_min": -2, "vkr_percent": 1.425, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -821,6 +823,7 @@ "tap_min": -2, "vkr_percent": 1.44, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -838,6 +841,7 @@ "tap_min": -2, "vkr_percent": 1.2, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -855,6 +859,7 @@ "tap_min": -9, "vkr_percent": 0.25, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 12.2, "tap_max": 9 @@ -872,6 +877,7 @@ "tap_min": -9, "vkr_percent": 0.31, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -889,6 +895,7 @@ "tap_min": -2, "vkr_percent": 1.206, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -906,6 +913,7 @@ "tap_min": -2, "vkr_percent": 1.325, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -923,6 +931,7 @@ "tap_min": -2, "vkr_percent": 1.0794, "tap_step_percent": 2.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -940,6 +949,7 @@ "tap_min": -9, "vkr_percent": 0.322, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -957,6 +967,7 @@ "tap_min": -9, "vkr_percent": 0.26, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 12.0, "tap_max": 9 @@ -973,6 +984,7 @@ "tap_neutral": 0, "tap_min": -9, "vkr_percent": 0.276, + "tap_phase_shifter_type": 0, "tap_step_percent": 1.5, "tap_side": "hv", "vk_percent": 10.04, @@ -991,6 +1003,7 @@ "tap_min": -9, "vkr_percent": 0.302, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1008,6 +1021,7 @@ "tap_min": -9, "vkr_percent": 0.282, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1025,6 +1039,7 @@ "tap_min": -9, "vkr_percent": 0.295, "tap_step_percent": 1.5, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -1052,6 +1067,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1076,6 +1092,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0, "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/test/converter/test_from_powerfactory.py b/pandapower/test/converter/test_from_powerfactory.py index 8a2c076a5..06bbb4b02 100644 --- a/pandapower/test/converter/test_from_powerfactory.py +++ b/pandapower/test/converter/test_from_powerfactory.py @@ -96,7 +96,7 @@ def test_trafo_tap2_results(): all_diffs = validate_pf_conversion(net, tolerance_mva=1e-9) tol = 2e-7 for key, diff in all_diffs.items(): - if type(diff)==pd.Series: + if type(diff) == pd.Series: delta = diff.abs().max() else: delta = diff['diff'].abs().max() diff --git a/pandapower/test/converter/testfiles/test_line_3ph.json b/pandapower/test/converter/testfiles/test_line_3ph.json index b412776e8..8f0381568 100644 --- a/pandapower/test/converter/testfiles/test_line_3ph.json +++ b/pandapower/test/converter/testfiles/test_line_3ph.json @@ -278,7 +278,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -308,6 +308,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -959,7 +960,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type_type": 0 + "tap_phase_shifter_type": 0 }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -977,7 +978,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type_type": 0 + "tap_phase_shifter_type": 0 }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -995,7 +996,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type_type": 0 + "tap_phase_shifter_type": 0 }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1013,7 +1014,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type_type": 0 + "tap_phase_shifter_type": 0 }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1031,7 +1032,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type_type": 0 + "tap_phase_shifter_type": 0 }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1049,7 +1050,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type_type": 0 + "tap_phase_shifter_type": 0 }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1219,7 +1220,8 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2 + "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0 }, "63/25/38 MVA 110/10/10 kV": { "sn_hv_mva": 63, @@ -1243,7 +1245,8 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2 + "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0 } } }, diff --git a/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json b/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json index f67943127..09206a3c7 100644 --- a/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json +++ b/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json @@ -287,7 +287,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -317,6 +317,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1251,7 +1252,8 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2 + "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0 }, "63/25/38 MVA 110/20/10 kV": { "sn_hv_mva": 63, @@ -1275,7 +1277,8 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2 + "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0 } } }, diff --git a/pandapower/test/converter/testfiles/test_trafo_3ph.json b/pandapower/test/converter/testfiles/test_trafo_3ph.json index 119829a91..27c34e419 100644 --- a/pandapower/test/converter/testfiles/test_trafo_3ph.json +++ b/pandapower/test/converter/testfiles/test_trafo_3ph.json @@ -279,7 +279,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -309,6 +309,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1230,7 +1231,8 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2 + "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0 }, "63/25/38 MVA 110/20/10 kV": { "sn_hv_mva": 63, @@ -1254,7 +1256,8 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2 + "tap_step_percent": 1.2, + "tap_phase_shifter_type": 0 } } }, diff --git a/pandapower/test/grid_equivalents/test_get_equivalent.py b/pandapower/test/grid_equivalents/test_get_equivalent.py index ad831396c..c537c29cd 100644 --- a/pandapower/test/grid_equivalents/test_get_equivalent.py +++ b/pandapower/test/grid_equivalents/test_get_equivalent.py @@ -476,11 +476,20 @@ def test_switch_sgens(): def test_characteristic(): net = pp.networks.example_multivoltage() - pp.control._create_trafo_characteristics(net, "trafo", [1], 'vk_percent', - [[-2,-1,0,1,2]], [[2,3,4,5,6]]) + # create trafo_characteristic_table + net["trafo_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [1, 1, 1, 1, 1], + 'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [2, 3, 4, 5, 6], + 'vkr_percent': [1.323, 1.324, 1.325, 1.326, 1.327], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan, + 'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan}) + net.trafo['id_characteristic_table'].at[1] = 0 + net.trafo['tap_dependency_table'].at[1] = True + # add spline characteristics for one transformer based on trafo_characteristic_table + pp.control.create_trafo_characteristic_object(net) pp.runpp(net) net_eq = pp.grid_equivalents.get_equivalent(net, "rei", [41], [0]) - assert len(net_eq.characteristic) == 1 + assert len(net_eq.trafo_characteristic_spline) == 1 + assert len(net_eq.trafo_characteristic_table) == 5 def test_controller(): From 08f4a19a55d76ef42323c851a56430957785d1f6 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 13 Dec 2024 09:50:58 +0200 Subject: [PATCH 047/125] fix bug in _convert_trafo_pst_logic function --- pandapower/convert_format.py | 29 +++++++++++++++++++---------- 1 file changed, 19 insertions(+), 10 deletions(-) diff --git a/pandapower/convert_format.py b/pandapower/convert_format.py index c2016fd0d..c4cfa7508 100644 --- a/pandapower/convert_format.py +++ b/pandapower/convert_format.py @@ -560,16 +560,25 @@ def _convert_trafo_pst_logic(net): if f"tap{t}_phase_shifter" in net[trafotable]: net[trafotable] = net[trafotable].drop(columns=f"tap{t}_phase_shifter") if (f"tap{t}_step_degree" in net[trafotable]) or (f"tap{t}_step_percent" in net[trafotable]): + # no phase shifters - check if both tap_step_percent & tap_step_degree are 0 or nan + mask_na = (((net[trafotable][f"tap{t}_step_degree"].isna()) | + (net[trafotable][f"tap{t}_step_degree"] == 0)) & + ((net[trafotable][f"tap{t}_step_percent"].isna()) | + (net[trafotable][f"tap{t}_step_percent"] == 0))) + net[trafotable].loc[mask_na, f"tap{t}_phase_shifter_type"] = pd.NA # ratio/asymmetrical phase shifters - net[trafotable].loc[ - ((net[trafotable][f"tap{t}_step_degree"].isna()) | - (net[trafotable][f"tap{t}_step_degree"] != 90)) & - (net[trafotable][f"tap{t}_step_percent"].notna()), f"tap{t}_phase_shifter_type"] = 0 + mask_ratio_asym = ((net[trafotable][f"tap{t}_step_degree"] != 90) & + ((net[trafotable][f"tap{t}_step_percent"].notna()) & + (net[trafotable][f"tap{t}_step_percent"] != 0))) + net[trafotable].loc[mask_ratio_asym, f"tap{t}_phase_shifter_type"] = 0 # symmetrical phase shifters - net[trafotable].loc[ - (net[trafotable][f"tap{t}_step_degree"] == 90) & - (net[trafotable][f"tap{t}_step_percent"].notna()), f"tap{t}_phase_shifter_type"] = 1 + mask_sym = ((net[trafotable][f"tap{t}_step_degree"] == 90) & + ((net[trafotable][f"tap{t}_step_percent"].notna()) & + (net[trafotable][f"tap{t}_step_percent"] != 0))) + net[trafotable].loc[mask_sym, f"tap{t}_phase_shifter_type"] = 1 # ideal phase shifters - net[trafotable].loc[ - (net[trafotable][f"tap{t}_step_degree"].notna()) & - (net[trafotable][f"tap{t}_step_percent"].isna()), f"tap{t}_phase_shifter_type"] = 2 + mask_ideal = (((net[trafotable][f"tap{t}_step_degree"].notna()) & + (net[trafotable][f"tap{t}_step_degree"] != 0)) & + ((net[trafotable][f"tap{t}_step_percent"].isna()) | + (net[trafotable][f"tap{t}_step_percent"] == 0))) + net[trafotable].loc[mask_ideal, f"tap{t}_phase_shifter_type"] = 2 From bbbb184d7b7cd2f18bdee4b5dca2d35f856f6016 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 13 Dec 2024 15:13:02 +0200 Subject: [PATCH 048/125] fix pandapower PR issues; fix bug in build_branch.py; updates to pass pytests --- pandapower/build_branch.py | 20 +++++++------------ pandapower/contingency/contingency.py | 10 +++------- pandapower/control/__init__.py | 2 +- .../shunts/staticVarCompensatorCim16.py | 1 - .../test/converter/test_from_powerfactory.py | 1 + .../converter/testfiles/trafo_tap_model.json | 5 +++-- 6 files changed, 15 insertions(+), 24 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index aef0a8311..c75390b8c 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -620,13 +620,13 @@ def _calc_tap_from_dataframe(net, trafo_df): id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: mask = tap_table & (side == tap_side) - filter = pd.DataFrame({ + filter_df = pd.DataFrame({ 'id_characteristic': id_characteristic_table, 'step': tap_pos, 'mask': mask }) - filtered_df = net.trafo_characteristic_table.merge(filter[filter['mask']], + filtered_df = net.trafo_characteristic_table.merge(filter_df[filter_df['mask']], on=['id_characteristic', 'step']) vn[mask] = vn[mask] * filtered_df['voltage_ratio'] trafo_shift[mask] += filtered_df['angle_deg'] @@ -649,7 +649,7 @@ def _calc_tap_from_dataframe(net, trafo_df): (direction * 2 * np.rad2deg(np.arcsin(tap_diff[mask_ideal] * tap_step_percent[mask_ideal] / 100 / 2))) ) - elif any(mask_complex): + if any(mask_complex): tap_steps = tap_step_percent[mask_complex] * tap_diff[mask_complex] / 100 tap_angles = _replace_nan(tap_step_degree[mask_complex]) u1 = vn[mask_complex] @@ -711,19 +711,19 @@ def _get_vk_values_from_table(trafo_df, trafo_characteristic_table, trafotype="2 vals = () - for c, vk_var in enumerate(vk_variables): + for _, vk_var in enumerate(vk_variables): vk_value = get_trafo_values(trafo_df, vk_var) if any(tap_dependency_table): id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") mask = tap_dependency_table - filter = pd.DataFrame({ + filter_df = pd.DataFrame({ 'id_characteristic': id_characteristic_table, 'step': tap_pos, 'mask': mask }) - filtered_df = trafo_characteristic_table.merge(filter[filter['mask']], on=['id_characteristic', 'step']) + filtered_df = trafo_characteristic_table.merge(filter_df[filter_df['mask']], on=['id_characteristic', 'step']) vk_value[mask] = filtered_df[vk_var] vals += (vk_value,) @@ -783,7 +783,7 @@ def _get_vk_values(trafo_df, characteristic, trafotype="2W"): vals = () - for c, vk_var in enumerate(vk_variables): + for _, vk_var in enumerate(vk_variables): vk_value = get_trafo_values(trafo_df, vk_var) if use_tap_dependent_impedance and vk_var in char_columns: vals += (_calc_tap_dependent_value( @@ -1346,12 +1346,6 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): trafo2["vn_lv_kv"] = {side: t3["vn_%s_kv" % side].values for side in sides} trafo2["shift_degree"] = {"hv": np.zeros(nr_trafos), "mv": t3.shift_mv_degree.values, "lv": t3.shift_lv_degree.values} - # if 'tap_dependency_table' in t3: - # trafo2["tap_phase_shifter_type"] = {side: t3.tap_phase_shifter_type for side in sides} - # trafo2["tap_dependency_table"] = {side: t3.tap_dependency_table for side in sides} - # trafo2["id_characteristic_table"] = {side: t3.id_characteristic_table for side in sides} - # else: - # trafo2["tap_phase_shifter"] = {side: np.zeros(nr_trafos).astype(bool) for side in sides} for param in ["tap_phase_shifter_type", "tap_dependency_table", "id_characteristic_table", "tap_phase_shifter"]: if param in t3: trafo2[param] = {side: t3[param] for side in sides} diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index 540e771fe..d593fad9c 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -176,11 +176,12 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. raise UserWarning("bus index must be continuous and start with 0 (use pandapower.create_continuous_bus_index)") contingency_evaluation_function(net, **kwargs) - trafo_flag = False if "tap_phase_shifter_type" in net.trafo.columns: if np.any(net.trafo.tap_phase_shifter_type == 2): - trafo_flag = True tap_phase_shifter_type, tap_pos, shift_degree = _convert_trafo_phase_shifter(net) + net.trafo.tap_phase_shifter_type = tap_phase_shifter_type + net.trafo.tap_pos = tap_pos + net.trafo.shift_degree = shift_degree # setting "slack" back-and-forth is due to the difference in interpretation of generators as "distributed slack" if net._options.get("distributed_slack", False): @@ -197,11 +198,6 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. lightsim_grid_model = init_ls2g(net) solver_type = SolverType.KLUSingleSlack if KLU_solver_available else SolverType.SparseLUSingleSlack - if trafo_flag: - net.trafo.tap_phase_shifter_type = tap_phase_shifter_type - net.trafo.tap_pos = tap_pos - net.trafo.shift_degree = shift_degree - n_lines = len(net.line) n_lines_cases = len(nminus1_cases.get("line", {}).get("index", [])) n_trafos = len(net.trafo) diff --git a/pandapower/control/__init__.py b/pandapower/control/__init__.py index a167ce4bd..dafac3057 100644 --- a/pandapower/control/__init__.py +++ b/pandapower/control/__init__.py @@ -21,4 +21,4 @@ from pandapower.control.util.characteristic import Characteristic, SplineCharacteristic from pandapower.control.util.auxiliary import (get_controller_index, plot_characteristic, _create_trafo_characteristics, create_trafo_characteristic_object) -from pandapower.control.util.diagnostic import control_diagnostic, trafo_characteristic_table_diagnostic +from pandapower.control.util.diagnostic import trafo_characteristic_table_diagnostic diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py index 0bc0fa665..a79a6fa94 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/staticVarCompensatorCim16.py @@ -2,7 +2,6 @@ import time import pandas as pd -import numpy as np from pandapower.converter.cim import cim_tools from pandapower.converter.cim.cim2pp import build_pp_net diff --git a/pandapower/test/converter/test_from_powerfactory.py b/pandapower/test/converter/test_from_powerfactory.py index 06bbb4b02..838785f07 100644 --- a/pandapower/test/converter/test_from_powerfactory.py +++ b/pandapower/test/converter/test_from_powerfactory.py @@ -8,6 +8,7 @@ from pandapower.converter.powerfactory.validate import validate_pf_conversion from pandapower.converter.powerfactory.export_pfd_to_pp import import_project, from_pfd +from pandapower.convert_format import _convert_trafo_pst_logic try: import pandaplan.core.pplog as logging diff --git a/pandapower/test/converter/testfiles/trafo_tap_model.json b/pandapower/test/converter/testfiles/trafo_tap_model.json index 0fefbcd52..f5a3c4fa9 100644 --- a/pandapower/test/converter/testfiles/trafo_tap_model.json +++ b/pandapower/test/converter/testfiles/trafo_tap_model.json @@ -305,7 +305,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"tap2_phase_shifter_type\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"tap2_neutral\",\"tap2_max\",\"tap2_min\",\"tap2_side\",\"tap2_step_percent\",\"tap2_step_degree\",\"tap2_pos\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20],\"data\":[[\"2-Winding Transformer(3)\",\"2-Winding Transformer Type\",94,81,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,10.0,0.0,false,1,1.0,true,false,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",2.0,30.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer\",\"2-Winding Transformer 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"pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -384,6 +384,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", + "tap_phase_shifter_type": "uint32", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" From 9c6ea9314ad9c6964ec20556ca507750d47a700e Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 13 Dec 2024 15:44:09 +0200 Subject: [PATCH 049/125] fix pandapower PR issue - remove unused import --- pandapower/control/__init__.py | 1 - 1 file changed, 1 deletion(-) diff --git a/pandapower/control/__init__.py b/pandapower/control/__init__.py index dafac3057..0f4f706b1 100644 --- a/pandapower/control/__init__.py +++ b/pandapower/control/__init__.py @@ -21,4 +21,3 @@ from pandapower.control.util.characteristic import Characteristic, SplineCharacteristic from pandapower.control.util.auxiliary import (get_controller_index, plot_characteristic, _create_trafo_characteristics, create_trafo_characteristic_object) -from pandapower.control.util.diagnostic import trafo_characteristic_table_diagnostic From 3319170ff93dc31e1eca822d99090e26eed1fdcc Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Mon, 16 Dec 2024 10:35:39 +0200 Subject: [PATCH 050/125] address Thomas comments --- pandapower/control/__init__.py | 3 ++- pandapower/control/util/auxiliary.py | 10 ++-------- .../shunts/nonLinearShuntCompensatorCim16.py | 4 ---- .../transformers/powerTransformersCim16.py | 2 -- .../converter_classes/transformers/tapController.py | 4 ---- pandapower/grid_equivalents/auxiliary.py | 3 +-- pandapower/test/loadflow/test_results.py | 4 +--- 7 files changed, 6 insertions(+), 24 deletions(-) diff --git a/pandapower/control/__init__.py b/pandapower/control/__init__.py index 0f4f706b1..51f94e865 100644 --- a/pandapower/control/__init__.py +++ b/pandapower/control/__init__.py @@ -19,5 +19,6 @@ # --- Other --- from pandapower.control.run_control import * from pandapower.control.util.characteristic import Characteristic, SplineCharacteristic -from pandapower.control.util.auxiliary import (get_controller_index, plot_characteristic, _create_trafo_characteristics, +from pandapower.control.util.auxiliary import (plot_characteristic, _create_trafo_characteristics, create_trafo_characteristic_object) +from pandapower.control.util.diagnostic import trafo_characteristic_table_diagnostic diff --git a/pandapower/control/util/auxiliary.py b/pandapower/control/util/auxiliary.py index d9c647d7d..1d82b24d9 100644 --- a/pandapower/control/util/auxiliary.py +++ b/pandapower/control/util/auxiliary.py @@ -218,7 +218,7 @@ def create_trafo_characteristic_object(net): del net["trafo_characteristic_spline"] # 2-winding transformers if (net['trafo_characteristic_table'].index.size > 0 and - net['trafo_characteristic_table']['vk_percent'].notna().any()): + net['trafo']['id_characteristic_table'].notna().any()): time_start = time.time() logger.info("Creating tap dependent characteristic objects for 2w-trafos.") characteristic_df_temp = net['trafo_characteristic_table'][ @@ -230,8 +230,6 @@ def create_trafo_characteristic_object(net): variables_filtered = [var for var in variables if var in characteristic_df.columns] x_points = [characteristic_df['step'].to_list()] y_points = {col: [characteristic_df[col].tolist()] for col in variables_filtered} - logger.info("Adding characteristic objects for 2w-trafo with trafo_id %s and variables " - "%s" % (trafo_id, variables_filtered)) _create_trafo_characteristics(net, "trafo", [trafo_id], variables_filtered, x_points, y_points) logger.info(f"Finished creating tap dependent characteristic objects for 2w-trafos in " @@ -240,7 +238,7 @@ def create_trafo_characteristic_object(net): logger.info("trafo_characteristic_table has no values for 2w-trafos - no characteristic objects created.") # 3-winding transformers if (net['trafo_characteristic_table'].index.size > 0 and - net['trafo_characteristic_table']['vkr_hv_percent'].notna().any()): + net['trafo3w']['id_characteristic_table'].notna().any()): time_start = time.time() logger.info("Creating tap dependent characteristic objects for 3w-trafos.") characteristic_df_temp = net['trafo_characteristic_table'][ @@ -254,8 +252,6 @@ def create_trafo_characteristic_object(net): variables_filtered = [var for var in variables if var in characteristic_df.columns] x_points = [characteristic_df['step'].to_list()] y_points = {col: [characteristic_df[col].tolist()] for col in variables_filtered} - logger.info("Adding characteristic objects for 3w-trafo with trafo_id %s and variables " - "%s" % (trafo_id, variables_filtered)) _create_trafo_characteristics(net, "trafo3w", [trafo_id], variables_filtered, x_points, y_points) logger.info(f"Finished creating tap dependent characteristic objects for 3w-trafos in " @@ -332,8 +328,6 @@ def create_shunt_characteristic_object(net): variables_filtered = [var for var in variables if var in characteristic_df.columns] x_points = [characteristic_df['step'].to_list()] y_points = {col: [characteristic_df[col].tolist()] for col in variables_filtered} - logger.info("Adding characteristic objects for shunt with shunt_id %s and variables " - "%s" % (shunt_id, variables_filtered)) _create_shunt_characteristics(net, [shunt_id], variables_filtered, x_points, y_points) logger.info(f"Finished creating step dependent power characteristic objects for shunts in" diff --git a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py index 2bb03cb5f..a14cdd7b5 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/shunts/nonLinearShuntCompensatorCim16.py @@ -26,7 +26,6 @@ def convert_nonlinear_shunt_compensator_cim16(self): eqssh_shunts = self._prepare_nonlinear_shunt_compensator_cim16() self._create_shunt_characteristic_table(eqssh_shunts) self.cimConverter.copy_to_pp('shunt', eqssh_shunts) - # self._create_shunt_characteristic_object(net=self.cimConverter.net) # moved out of converter else: eqssh_shunts = pd.DataFrame(None) self.logger.info("Created %s shunts in %ss." % (eqssh_shunts.index.size, time.time() - time_start)) @@ -71,9 +70,6 @@ def _prepare_nonlinear_shunt_compensator_cim16(self) -> pd.DataFrame: eqssh_shunts = eqssh_shunts.rename(columns={ 'rdfId': sc['o_id'], 'rdfId_Terminal': sc['t'], 'connected': 'in_service', 'index_bus': 'bus', 'nomU': 'vn_kv', 'p': 'p_mw', 'q': 'q_mvar', 'sections': 'step', 'maximumSections': 'max_step'}) - # commented out - this way information on current and max step is not lost - # eqssh_shunts['step'] = 1 - # eqssh_shunts['max_step'] = 1 return eqssh_shunts def _create_shunt_characteristic_table(self, eqssh_shunts): diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index 70c8fc6db..479d38609 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -354,7 +354,6 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: "in the PhaseTapChangerTablePoints!" % one_id) ptct = ptct.drop(drop_index) continue - current_step = one_df['current_step'].iloc[0] one_df = one_df.set_index('step') neutral_step = one_df['neutralStep'].iloc[0] ptct = ptct.drop(drop_index) @@ -507,7 +506,6 @@ def _prepare_trafos_cim16(self, power_trafo2w: pd.DataFrame) -> pd.DataFrame: power_trafo2w['shift_degree'] = power_trafo2w['phaseAngleClock'].astype(float).fillna( power_trafo2w['phaseAngleClock_lv'].astype(float)) * 30 power_trafo2w['parallel'] = 1 - # power_trafo2w['tap_phase_shifter'] = False # removed power_trafo2w['in_service'] = power_trafo2w.connected & power_trafo2w.connected_lv power_trafo2w['connectionKind'] = power_trafo2w['connectionKind'].fillna('') power_trafo2w['connectionKind_lv'] = power_trafo2w['connectionKind_lv'].fillna('') diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py index 89ecc150a..be6b4c3b1 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py @@ -1,10 +1,6 @@ import logging -import time -from typing import List - import pandas as pd -import pandapower.auxiliary from pandapower.control.controller.trafo.ContinuousTapControl import ContinuousTapControl from pandapower.control.controller.trafo.DiscreteTapControl import DiscreteTapControl from pandapower.converter.cim import cim_tools diff --git a/pandapower/grid_equivalents/auxiliary.py b/pandapower/grid_equivalents/auxiliary.py index 1ea48a8e5..83a413f01 100644 --- a/pandapower/grid_equivalents/auxiliary.py +++ b/pandapower/grid_equivalents/auxiliary.py @@ -498,7 +498,6 @@ def adaptation_phase_shifter(net, v_boundary, p_boundary): pfe_kw=.0, i0_percent=.0, # shift_degree=-phase_errors[idx], tap_step_degree=-phase_errors[idx], - # tap_phase_shifter_type=2, name="phase_shifter_adapter_"+str(lb)) # pp.create_load(net, lb, -p_errors[idx], -q_errors[idx], # name="phase_shifter_adapter_"+str(lb)) @@ -509,7 +508,7 @@ def adaptation_phase_shifter(net, v_boundary, p_boundary): def replace_motor_by_load(net, all_external_buses): """ replace the 'external' motors by loads. The name is modified. - e.g., "equivalent_MotorName_3" ("equivalent"+"orignial name"+"original index") + e.g., "equivalent_MotorName_3" ("equivalent"+"original name"+"original index") """ motors = net.motor.index[net.motor.bus.isin(all_external_buses)] for mi, m in net.motor.loc[motors].iterrows(): diff --git a/pandapower/test/loadflow/test_results.py b/pandapower/test/loadflow/test_results.py index da5904bc8..78f17c594 100644 --- a/pandapower/test/loadflow/test_results.py +++ b/pandapower/test/loadflow/test_results.py @@ -6,14 +6,12 @@ import pandas as pd import pytest import numpy as np -from numpy import isin, isnan, isclose, allclose +from numpy import isin, isnan, isclose import pandapower as pp -import pandapower.control from pandapower.test.consistency_checks import runpp_with_consistency_checks from pandapower.test.loadflow.result_test_network_generator import add_test_enforce_qlims, \ add_test_gen -from pandapower.test.helper_functions import assert_res_equal from pandapower.test.conftest import result_test_network # simple example grid for tap dependent impedance tests: From 05fc525ad5278269306262f3623e7ac724fccf49 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Mon, 16 Dec 2024 11:35:10 +0200 Subject: [PATCH 051/125] resolve codacy issue - move import to test lib --- pandapower/control/__init__.py | 1 - pandapower/test/control/test_tap_dependent_impedance.py | 4 ++-- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/pandapower/control/__init__.py b/pandapower/control/__init__.py index 51f94e865..2e1de6b59 100644 --- a/pandapower/control/__init__.py +++ b/pandapower/control/__init__.py @@ -21,4 +21,3 @@ from pandapower.control.util.characteristic import Characteristic, SplineCharacteristic from pandapower.control.util.auxiliary import (plot_characteristic, _create_trafo_characteristics, create_trafo_characteristic_object) -from pandapower.control.util.diagnostic import trafo_characteristic_table_diagnostic diff --git a/pandapower/test/control/test_tap_dependent_impedance.py b/pandapower/test/control/test_tap_dependent_impedance.py index c228171da..6c66445d0 100644 --- a/pandapower/test/control/test_tap_dependent_impedance.py +++ b/pandapower/test/control/test_tap_dependent_impedance.py @@ -8,8 +8,8 @@ import logging import pandapower as pp -from pandapower.control import Characteristic, SplineCharacteristic, TapDependentImpedance, \ - trafo_characteristic_table_diagnostic +from pandapower.control import Characteristic, SplineCharacteristic, TapDependentImpedance +from pandapower.control.util.diagnostic import trafo_characteristic_table_diagnostic def test_tap_dependent_impedance_control(): From eb3e62db21a8e97caa82bb7c204aa6f8f36be757 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Mon, 16 Dec 2024 12:04:23 +0200 Subject: [PATCH 052/125] removed creation of empty characteristic table in json files --- pandapower/networks/IEEE_European_LV_Off_Peak_1.json | 11 ----------- .../networks/IEEE_European_LV_Off_Peak_1440.json | 11 ----------- pandapower/networks/IEEE_European_LV_On_Peak_566.json | 11 ----------- pandapower/networks/lv_schutterwald.json | 11 ----------- .../power_system_test_case_jsons/GBnetwork.json | 11 ----------- .../GBreducednetwork.json | 11 ----------- .../power_system_test_case_jsons/case118.json | 11 ----------- .../power_system_test_case_jsons/case11_iwamoto.json | 11 ----------- .../power_system_test_case_jsons/case1354pegase.json | 11 ----------- .../networks/power_system_test_case_jsons/case14.json | 11 ----------- .../power_system_test_case_jsons/case145.json | 11 ----------- .../power_system_test_case_jsons/case1888rte.json | 11 ----------- .../power_system_test_case_jsons/case24_ieee_rts.json | 11 ----------- .../power_system_test_case_jsons/case2848rte.json | 11 ----------- .../power_system_test_case_jsons/case2869pegase.json | 11 ----------- .../networks/power_system_test_case_jsons/case30.json | 11 ----------- .../power_system_test_case_jsons/case300.json | 11 ----------- .../power_system_test_case_jsons/case3120sp.json | 11 ----------- .../power_system_test_case_jsons/case33bw.json | 11 ----------- .../networks/power_system_test_case_jsons/case39.json | 11 ----------- .../power_system_test_case_jsons/case4gs.json | 11 ----------- .../networks/power_system_test_case_jsons/case5.json | 11 ----------- .../networks/power_system_test_case_jsons/case57.json | 11 ----------- .../case5_demo_gridcal.json | 11 ----------- .../power_system_test_case_jsons/case6470rte.json | 11 ----------- .../power_system_test_case_jsons/case6495rte.json | 11 ----------- .../power_system_test_case_jsons/case6515rte.json | 11 ----------- .../power_system_test_case_jsons/case6ww.json | 11 ----------- .../power_system_test_case_jsons/case89pegase.json | 11 ----------- .../networks/power_system_test_case_jsons/case9.json | 11 ----------- .../power_system_test_case_jsons/case9241pegase.json | 11 ----------- .../power_system_test_case_jsons/case_ieee30.json | 11 ----------- .../case_illinois200.json | 11 ----------- .../power_system_test_case_jsons/iceland.json | 11 ----------- pandapower/test/control/testfiles/stactrl_test.json | 11 ----------- pandapower/test/converter/case2_2_by_code.json | 11 ----------- .../test/converter/testfiles/trafo_tap_model.json | 11 ----------- pandapower/test/loadflow/runpp_3ph Validation.json | 9 --------- pandapower/test/test_files/test_ac_dc.json | 11 ----------- pandapower/test/test_files/test_trafo3w_tap.json | 11 ----------- 40 files changed, 438 deletions(-) diff --git a/pandapower/networks/IEEE_European_LV_Off_Peak_1.json b/pandapower/networks/IEEE_European_LV_Off_Peak_1.json index baf88455d..db9d40302 100644 --- a/pandapower/networks/IEEE_European_LV_Off_Peak_1.json +++ b/pandapower/networks/IEEE_European_LV_Off_Peak_1.json @@ -546,17 +546,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json b/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json index 832d0d859..edec0ac0e 100644 --- a/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json +++ b/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json @@ -546,17 +546,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/IEEE_European_LV_On_Peak_566.json b/pandapower/networks/IEEE_European_LV_On_Peak_566.json index af2a3fdc8..cd8a049f5 100644 --- a/pandapower/networks/IEEE_European_LV_On_Peak_566.json +++ b/pandapower/networks/IEEE_European_LV_On_Peak_566.json @@ -546,17 +546,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/lv_schutterwald.json b/pandapower/networks/lv_schutterwald.json index 1badb2cd5..fdabe4999 100644 --- a/pandapower/networks/lv_schutterwald.json +++ b/pandapower/networks/lv_schutterwald.json @@ -509,17 +509,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/GBnetwork.json b/pandapower/networks/power_system_test_case_jsons/GBnetwork.json index 70f492749..d178eb09f 100644 --- a/pandapower/networks/power_system_test_case_jsons/GBnetwork.json +++ b/pandapower/networks/power_system_test_case_jsons/GBnetwork.json @@ -516,17 +516,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json b/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json index 4c9863077..f2ec458b4 100644 --- a/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json +++ b/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json @@ -522,17 +522,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case118.json b/pandapower/networks/power_system_test_case_jsons/case118.json index 56bd2e43d..10737c6ce 100644 --- a/pandapower/networks/power_system_test_case_jsons/case118.json +++ b/pandapower/networks/power_system_test_case_jsons/case118.json @@ -519,17 +519,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json b/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json index e836218d3..1948ac10a 100644 --- a/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json +++ b/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json @@ -507,17 +507,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case1354pegase.json b/pandapower/networks/power_system_test_case_jsons/case1354pegase.json index 93e584079..3b9339ea7 100644 --- a/pandapower/networks/power_system_test_case_jsons/case1354pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case1354pegase.json @@ -520,17 +520,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case14.json b/pandapower/networks/power_system_test_case_jsons/case14.json index fe668249f..583a943ad 100644 --- a/pandapower/networks/power_system_test_case_jsons/case14.json +++ b/pandapower/networks/power_system_test_case_jsons/case14.json @@ -519,17 +519,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case145.json b/pandapower/networks/power_system_test_case_jsons/case145.json index bf0417720..aeeab821f 100644 --- a/pandapower/networks/power_system_test_case_jsons/case145.json +++ b/pandapower/networks/power_system_test_case_jsons/case145.json @@ -520,17 +520,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case1888rte.json b/pandapower/networks/power_system_test_case_jsons/case1888rte.json index 009af257f..ef58fda29 100644 --- a/pandapower/networks/power_system_test_case_jsons/case1888rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case1888rte.json @@ -524,17 +524,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json b/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json index 00fd00c25..17e8b88f9 100644 --- a/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json +++ b/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json @@ -524,17 +524,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case2848rte.json b/pandapower/networks/power_system_test_case_jsons/case2848rte.json index 0da9e77f2..7450b634f 100644 --- a/pandapower/networks/power_system_test_case_jsons/case2848rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case2848rte.json @@ -524,17 +524,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case2869pegase.json b/pandapower/networks/power_system_test_case_jsons/case2869pegase.json index 8ed783375..f8964f297 100644 --- a/pandapower/networks/power_system_test_case_jsons/case2869pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case2869pegase.json @@ -520,17 +520,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case30.json b/pandapower/networks/power_system_test_case_jsons/case30.json index ed0f5304f..cf53adcdf 100644 --- a/pandapower/networks/power_system_test_case_jsons/case30.json +++ b/pandapower/networks/power_system_test_case_jsons/case30.json @@ -518,17 +518,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case300.json b/pandapower/networks/power_system_test_case_jsons/case300.json index bd01be095..c99bfa2a7 100644 --- a/pandapower/networks/power_system_test_case_jsons/case300.json +++ b/pandapower/networks/power_system_test_case_jsons/case300.json @@ -520,17 +520,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case3120sp.json b/pandapower/networks/power_system_test_case_jsons/case3120sp.json index fc9564e0b..be606febe 100644 --- a/pandapower/networks/power_system_test_case_jsons/case3120sp.json +++ b/pandapower/networks/power_system_test_case_jsons/case3120sp.json @@ -524,17 +524,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case33bw.json b/pandapower/networks/power_system_test_case_jsons/case33bw.json index 8f31434af..eb973ed16 100644 --- a/pandapower/networks/power_system_test_case_jsons/case33bw.json +++ b/pandapower/networks/power_system_test_case_jsons/case33bw.json @@ -515,17 +515,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case39.json b/pandapower/networks/power_system_test_case_jsons/case39.json index 85784f612..f6ed49f2b 100644 --- a/pandapower/networks/power_system_test_case_jsons/case39.json +++ b/pandapower/networks/power_system_test_case_jsons/case39.json @@ -519,17 +519,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case4gs.json b/pandapower/networks/power_system_test_case_jsons/case4gs.json index 6b2761d03..f5c178ca0 100644 --- a/pandapower/networks/power_system_test_case_jsons/case4gs.json +++ b/pandapower/networks/power_system_test_case_jsons/case4gs.json @@ -518,17 +518,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case5.json b/pandapower/networks/power_system_test_case_jsons/case5.json index c6a0374ed..03e27d14c 100644 --- a/pandapower/networks/power_system_test_case_jsons/case5.json +++ b/pandapower/networks/power_system_test_case_jsons/case5.json @@ -523,17 +523,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case57.json b/pandapower/networks/power_system_test_case_jsons/case57.json index bcfe80c86..70da8df16 100644 --- a/pandapower/networks/power_system_test_case_jsons/case57.json +++ b/pandapower/networks/power_system_test_case_jsons/case57.json @@ -519,17 +519,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json b/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json index 4c556ded6..2c1edb195 100644 --- a/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json +++ b/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json @@ -513,17 +513,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case6470rte.json b/pandapower/networks/power_system_test_case_jsons/case6470rte.json index d565bc2b7..3571276a7 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6470rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6470rte.json @@ -524,17 +524,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case6495rte.json b/pandapower/networks/power_system_test_case_jsons/case6495rte.json index 723de1b70..e6efb9e35 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6495rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6495rte.json @@ -524,17 +524,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case6515rte.json b/pandapower/networks/power_system_test_case_jsons/case6515rte.json index b9fe8a35d..bde1766bd 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6515rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6515rte.json @@ -524,17 +524,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case6ww.json b/pandapower/networks/power_system_test_case_jsons/case6ww.json index e6a9e477b..9b84bbfb6 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6ww.json +++ b/pandapower/networks/power_system_test_case_jsons/case6ww.json @@ -518,17 +518,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case89pegase.json b/pandapower/networks/power_system_test_case_jsons/case89pegase.json index 27b127eb3..f0eb9cb11 100644 --- a/pandapower/networks/power_system_test_case_jsons/case89pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case89pegase.json @@ -520,17 +520,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case9.json b/pandapower/networks/power_system_test_case_jsons/case9.json index 5dc5d798e..b6f6648ba 100644 --- a/pandapower/networks/power_system_test_case_jsons/case9.json +++ b/pandapower/networks/power_system_test_case_jsons/case9.json @@ -518,17 +518,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case9241pegase.json b/pandapower/networks/power_system_test_case_jsons/case9241pegase.json index 14fb711fa..a1801b1c9 100644 --- a/pandapower/networks/power_system_test_case_jsons/case9241pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case9241pegase.json @@ -520,17 +520,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case_ieee30.json b/pandapower/networks/power_system_test_case_jsons/case_ieee30.json index c53971866..78539a1f7 100644 --- a/pandapower/networks/power_system_test_case_jsons/case_ieee30.json +++ b/pandapower/networks/power_system_test_case_jsons/case_ieee30.json @@ -519,17 +519,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case_illinois200.json b/pandapower/networks/power_system_test_case_jsons/case_illinois200.json index 6ade53507..83bfb3484 100644 --- a/pandapower/networks/power_system_test_case_jsons/case_illinois200.json +++ b/pandapower/networks/power_system_test_case_jsons/case_illinois200.json @@ -524,17 +524,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/iceland.json b/pandapower/networks/power_system_test_case_jsons/iceland.json index 7a4d4d202..e73ab39e0 100644 --- a/pandapower/networks/power_system_test_case_jsons/iceland.json +++ b/pandapower/networks/power_system_test_case_jsons/iceland.json @@ -516,17 +516,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/test/control/testfiles/stactrl_test.json b/pandapower/test/control/testfiles/stactrl_test.json index b6e8c14e7..2bf01fa35 100644 --- a/pandapower/test/control/testfiles/stactrl_test.json +++ b/pandapower/test/control/testfiles/stactrl_test.json @@ -541,17 +541,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/test/converter/case2_2_by_code.json b/pandapower/test/converter/case2_2_by_code.json index 6eb650127..17e8845a1 100644 --- a/pandapower/test/converter/case2_2_by_code.json +++ b/pandapower/test/converter/case2_2_by_code.json @@ -519,17 +519,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/test/converter/testfiles/trafo_tap_model.json b/pandapower/test/converter/testfiles/trafo_tap_model.json index f5a3c4fa9..f9b0c4e0d 100644 --- a/pandapower/test/converter/testfiles/trafo_tap_model.json +++ b/pandapower/test/converter/testfiles/trafo_tap_model.json @@ -541,17 +541,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/test/loadflow/runpp_3ph Validation.json b/pandapower/test/loadflow/runpp_3ph Validation.json index ef86eedf2..977af8d6f 100644 --- a/pandapower/test/loadflow/runpp_3ph Validation.json +++ b/pandapower/test/loadflow/runpp_3ph Validation.json @@ -1907,15 +1907,6 @@ } }, "pf_converged": true, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - } - }, "res_asymmetric_load": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/test/test_files/test_ac_dc.json b/pandapower/test/test_files/test_ac_dc.json index 2e2521e5e..f181cafd4 100644 --- a/pandapower/test/test_files/test_ac_dc.json +++ b/pandapower/test/test_files/test_ac_dc.json @@ -615,17 +615,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/test/test_files/test_trafo3w_tap.json b/pandapower/test/test_files/test_trafo3w_tap.json index f4fd23ea2..a0c28939d 100644 --- a/pandapower/test/test_files/test_trafo3w_tap.json +++ b/pandapower/test/test_files/test_trafo3w_tap.json @@ -596,17 +596,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", From 4eae525615b48758720a2c44bacd1e332e176cc9 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Mon, 16 Dec 2024 12:27:38 +0200 Subject: [PATCH 053/125] amend test_create_trafo_characteristics test to also include a non linear characteristic --- pandapower/test/api/test_auxiliary.py | 34 +++++++++++++++++---------- 1 file changed, 22 insertions(+), 12 deletions(-) diff --git a/pandapower/test/api/test_auxiliary.py b/pandapower/test/api/test_auxiliary.py index 7ab081ece..aab868468 100644 --- a/pandapower/test/api/test_auxiliary.py +++ b/pandapower/test/api/test_auxiliary.py @@ -27,6 +27,7 @@ import pandapower.networks import pandapower.control import pandapower.timeseries +from math import isclose class MemoryLeakDemo: @@ -231,8 +232,8 @@ def test_create_trafo_characteristics(): assert isinstance(net.trafo_characteristic_spline.at[ net.trafo.id_characteristic_spline.at[1], 'vk_percent_characteristic'], pp.control.SplineCharacteristic) - assert net.trafo_characteristic_spline.at[ - net.trafo.id_characteristic_spline.at[1], 'vk_percent_characteristic'](-2) == 2 + assert isclose(net.trafo_characteristic_spline.at[ + net.trafo.id_characteristic_spline.at[1], 'vk_percent_characteristic'](-2).item(), 2, rel_tol=1e-9) assert pd.isna(net.trafo_characteristic_spline.at[ net.trafo.id_characteristic_spline.at[1], 'vkr_hv_percent_characteristic']) @@ -250,13 +251,13 @@ def test_create_trafo_characteristics(): assert isinstance(net.trafo_characteristic_spline.at[ net.trafo.id_characteristic_spline.at[0], 'vk_percent_characteristic'], pp.control.SplineCharacteristic) - assert net.trafo_characteristic_spline.at[ - net.trafo.id_characteristic_spline.at[0], 'vk_percent_characteristic'](2) == 6 + assert isclose(net.trafo_characteristic_spline.at[ + net.trafo.id_characteristic_spline.at[0], 'vk_percent_characteristic'](2).item(), 6, rel_tol=1e-9) assert isinstance(net.trafo_characteristic_spline.at[ net.trafo.id_characteristic_spline.at[1], 'vk_percent_characteristic'], pp.control.SplineCharacteristic) - assert net.trafo_characteristic_spline.at[ - net.trafo.id_characteristic_spline.at[1], 'vk_percent_characteristic'](-1) == 3 + assert isclose(net.trafo_characteristic_spline.at[ + net.trafo.id_characteristic_spline.at[1], 'vk_percent_characteristic'](-1).item(), 3, rel_tol=1e-9) assert pd.isna(net.trafo_characteristic_spline.at[ net.trafo.id_characteristic_spline.at[0], 'vkr_hv_percent_characteristic']) assert pd.isna(net.trafo_characteristic_spline.at[ @@ -265,10 +266,10 @@ def test_create_trafo_characteristics(): # test for 3w trafo new_rows = pd.DataFrame( {'id_characteristic': [2, 2, 2, 2, 2], 'step': [-8, -4, 0, 4, 8], 'voltage_ratio': [1, 1, 1, 1, 1], - 'angle_deg': [0, 0, 0, 0, 0], 'vk_hv_percent': [8.1, 9.1, 10.1, 11.1, 12.1], - 'vkr_hv_percent': [1.323, 1.324, 1.325, 1.326, 1.327], 'vk_mv_percent': [8.1, 9.1, 10.1, 11.1, 12.1], - 'vkr_mv_percent': [1.323, 1.324, 1.325, 1.326, 1.327], 'vk_lv_percent': [8.1, 9.1, 10.1, 11.1, 12.1], - 'vkr_lv_percent': [1.323, 1.324, 1.325, 1.326, 1.327]}) + 'angle_deg': [0, 0, 0, 0, 0], 'vk_hv_percent': [8.1, 9.5, 10, 11.1, 12.9], + 'vkr_hv_percent': [1.323, 1.325, 1.329, 1.331, 1.339], 'vk_mv_percent': [8.1, 9.5, 10, 11.1, 12.9], + 'vkr_mv_percent': [1.323, 1.325, 1.329, 1.331, 1.339], 'vk_lv_percent': [8.1, 9.5, 10, 11.1, 12.9], + 'vkr_lv_percent': [1.323, 1.325, 1.329, 1.331, 1.339]}) net["trafo_characteristic_table"] = pd.concat([net["trafo_characteristic_table"], new_rows], ignore_index=True) net.trafo3w['id_characteristic_table'].at[0] = 2 net.trafo3w['tap_dependency_table'].at[0] = True @@ -281,8 +282,17 @@ def test_create_trafo_characteristics(): assert isinstance(net.trafo_characteristic_spline.at[ net.trafo3w.id_characteristic_spline.at[0], 'vkr_hv_percent_characteristic'], pp.control.SplineCharacteristic) - assert net.trafo_characteristic_spline.at[ - net.trafo3w.id_characteristic_spline.at[0], 'vkr_hv_percent_characteristic'](-4) == 1.324 + assert isclose(net.trafo_characteristic_spline.at[ + net.trafo3w.id_characteristic_spline.at[0], 'vk_hv_percent_characteristic'](0).item(), 10, rel_tol=1e-9) + assert isclose(net.trafo_characteristic_spline.at[ + net.trafo3w.id_characteristic_spline.at[0], 'vk_lv_percent_characteristic'](4).item(), 11.1, + rel_tol=1e-9) + assert isclose(net.trafo_characteristic_spline.at[ + net.trafo3w.id_characteristic_spline.at[0], 'vkr_hv_percent_characteristic'](-4).item(), 1.325, + rel_tol=1e-9) + assert isclose(net.trafo_characteristic_spline.at[ + net.trafo3w.id_characteristic_spline.at[0], 'vkr_lv_percent_characteristic'](8).item(), 1.339, + rel_tol=1e-9) assert pd.isna(net.trafo_characteristic_spline.at[ net.trafo3w.id_characteristic_spline.at[0], 'vk_percent_characteristic']) From a2a538aefa4a8f2e2118156026bfb5677b3548f0 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Mon, 16 Dec 2024 12:35:57 +0200 Subject: [PATCH 054/125] re-introduce test_tap_phase_shifter_type_default function but re-purpose to check for tap_phase_shifter_type instead of tap_phase_shifter --- pandapower/test/api/test_create.py | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/pandapower/test/api/test_create.py b/pandapower/test/api/test_create.py index 93a6825cb..3bc6ed77e 100644 --- a/pandapower/test/api/test_create.py +++ b/pandapower/test/api/test_create.py @@ -229,6 +229,21 @@ def test_nonexistent_bus(): func() +def test_tap_phase_shifter_type_default(): + expected_default = pd.NA + net = pp.create_empty_network() + pp.create_bus(net, 110) + pp.create_bus(net, 20) + data = pp.load_std_type(net, "25 MVA 110/20 kV", "trafo") + if "tap_phase_shifter_type" in data: + del data["tap_phase_shifter_type"] + pp.create_std_type(net, data, "without_tap_shifter_info", "trafo") + pp.create_transformer_from_parameters(net, 0, 1, 25e3, 110, 20, 0.4, + 12, 20, 0.07) + pp.create_transformer(net, 0, 1, "without_tap_shifter_info") + assert (net.trafo.tap_phase_shifter_type == expected_default).all() + + def test_create_line_conductance(): net = pp.create_empty_network() pp.create_bus(net, 20) From 8867abd6ebd202ecaf339b2d4c3d3196de2cb407 Mon Sep 17 00:00:00 2001 From: tfabian Date: Mon, 16 Dec 2024 14:54:29 +0100 Subject: [PATCH 055/125] renaming: phase_shifter_type to tap_changer_type and 0,1,2 to "Ratio" "Symmetrical" and "Ideal" still todo: fix tests. --- pandapower/build_branch.py | 6 +- pandapower/contingency/contingency.py | 18 ++--- pandapower/convert_format.py | 16 ++-- .../transformers/powerTransformersCim16.py | 12 +-- pandapower/converter/pypower/from_ppc.py | 4 +- pandapower/create.py | 76 +++++++++---------- .../networks/IEEE_European_LV_Off_Peak_1.json | 34 ++++----- .../IEEE_European_LV_Off_Peak_1440.json | 34 ++++----- .../IEEE_European_LV_On_Peak_566.json | 34 ++++----- pandapower/networks/create_examples.py | 4 +- pandapower/networks/lv_schutterwald.json | 44 +++++------ .../GBnetwork.json | 40 +++++----- .../GBreducednetwork.json | 40 +++++----- .../power_system_test_case_jsons/case118.json | 52 ++++++------- .../case11_iwamoto.json | 52 ++++++------- .../case1354pegase.json | 52 ++++++------- .../power_system_test_case_jsons/case14.json | 52 ++++++------- .../power_system_test_case_jsons/case145.json | 52 ++++++------- .../case1888rte.json | 52 ++++++------- .../case24_ieee_rts.json | 52 ++++++------- .../case2848rte.json | 52 ++++++------- .../case2869pegase.json | 52 ++++++------- .../power_system_test_case_jsons/case30.json | 52 ++++++------- .../power_system_test_case_jsons/case300.json | 52 ++++++------- .../case3120sp.json | 52 ++++++------- .../case33bw.json | 52 ++++++------- .../power_system_test_case_jsons/case39.json | 52 ++++++------- .../power_system_test_case_jsons/case4gs.json | 52 ++++++------- .../power_system_test_case_jsons/case5.json | 52 ++++++------- .../power_system_test_case_jsons/case57.json | 52 ++++++------- .../case5_demo_gridcal.json | 40 +++++----- .../case6470rte.json | 52 ++++++------- .../case6495rte.json | 52 ++++++------- .../case6515rte.json | 52 ++++++------- .../power_system_test_case_jsons/case6ww.json | 52 ++++++------- .../case89pegase.json | 52 ++++++------- .../power_system_test_case_jsons/case9.json | 52 ++++++------- .../case9241pegase.json | 52 ++++++------- .../case_ieee30.json | 52 ++++++------- .../case_illinois200.json | 52 ++++++------- .../power_system_test_case_jsons/iceland.json | 40 +++++----- pandapower/std_types.py | 34 ++++----- pandapower/test/api/test_create.py | 16 ++-- .../test/contingency/test_contingency.py | 4 +- .../control/test_tap_dependent_impedance.py | 4 +- .../test/control/testfiles/stactrl_test.json | 34 ++++----- .../test/converter/case2_2_by_code.json | 30 ++++---- pandapower/test/converter/test_from_cim.py | 6 +- .../converter/testfiles/test_line_3ph.json | 40 +++++----- .../test_net_3ph_test_2020_10_19.json | 42 +++++----- .../converter/testfiles/test_trafo_3ph.json | 42 +++++----- .../converter/testfiles/trafo_tap_model.json | 46 +++++------ pandapower/test/estimation/3bus_wls.json | 4 +- .../test/estimation/test_wls_estimation.py | 4 +- pandapower/test/helper_functions.py | 2 +- .../loadflow/result_test_network_generator.py | 6 +- .../test/loadflow/runpp_3ph Validation.json | 40 +++++----- pandapower/test/loadflow/test_recycle.py | 2 +- pandapower/test/loadflow/test_results.py | 8 +- pandapower/test/loadflow/test_runpp.py | 2 +- pandapower/test/loadflow/test_runpp_3ph.py | 2 +- pandapower/test/loadflow/test_scenarios.py | 12 +-- pandapower/test/opf/test_basic.py | 10 +-- .../shortcircuit/sc_test_meshed_grid.json | 4 +- pandapower/test/shortcircuit/test_1ph.py | 4 +- .../test/shortcircuit/test_all_currents.py | 8 +- .../test/shortcircuit/test_iec60909_4.py | 10 +-- .../test/shortcircuit/test_transformer.py | 2 +- .../test/test_files/IEC60909-4_example.json | 48 ++++++------ .../controller_containing_NoneNan.json | 32 ++++---- pandapower/test/test_files/test_ac_dc.json | 34 ++++----- .../test/test_files/test_trafo3w_tap.json | 32 ++++---- pandapower/test/timeseries/test_timeseries.py | 2 +- .../timeseries/test_timeseries_recycle.py | 4 +- tutorials/create_advanced.ipynb | 4 +- tutorials/tap_dependent_impedance.ipynb | 2 +- ...three_phase_loadflow_tutorial_simple.ipynb | 2 +- 77 files changed, 1186 insertions(+), 1186 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index c75390b8c..18949af0e 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -601,9 +601,9 @@ def _calc_tap_from_dataframe(net, trafo_df): sin = lambda x: np.sin(np.deg2rad(x)) arctan = lambda x: np.rad2deg(np.arctan(x)) - if f'tap{t}_phase_shifter_type' in trafo_df: + if f'tap{t}_changer_type' in trafo_df: # tap_phase_shift_type is only in dataframe starting from pp Version 3.0, older version use different logic - phase_shifter_type = get_trafo_values(trafo_df, f"tap{t}_phase_shifter_type") + phase_shifter_type = get_trafo_values(trafo_df, f"tap{t}_changer_type") if f'tap{t}_dependency_table' in trafo_df: tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") tap_dependency = np.array( @@ -1346,7 +1346,7 @@ def _trafo_df_from_trafo3w(net, sequence=1, update_vk_values=True): trafo2["vn_lv_kv"] = {side: t3["vn_%s_kv" % side].values for side in sides} trafo2["shift_degree"] = {"hv": np.zeros(nr_trafos), "mv": t3.shift_mv_degree.values, "lv": t3.shift_lv_degree.values} - for param in ["tap_phase_shifter_type", "tap_dependency_table", "id_characteristic_table", "tap_phase_shifter"]: + for param in ["tap_changer_type", "tap_dependency_table", "id_characteristic_table", "tap_phase_shifter"]: if param in t3: trafo2[param] = {side: t3[param] for side in sides} trafo2["parallel"] = {side: np.ones(nr_trafos) for side in sides} diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index d593fad9c..105808e02 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -176,10 +176,10 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. raise UserWarning("bus index must be continuous and start with 0 (use pandapower.create_continuous_bus_index)") contingency_evaluation_function(net, **kwargs) - if "tap_phase_shifter_type" in net.trafo.columns: - if np.any(net.trafo.tap_phase_shifter_type == 2): - tap_phase_shifter_type, tap_pos, shift_degree = _convert_trafo_phase_shifter(net) - net.trafo.tap_phase_shifter_type = tap_phase_shifter_type + if "tap_changer_type" in net.trafo.columns: + if np.any(net.trafo.tap_changer_type == "Ideal"): + tap_changer_type, tap_pos, shift_degree = _convert_trafo_phase_shifter(net) + net.trafo.tap_changer_type = tap_changer_type net.trafo.tap_pos = tap_pos net.trafo.shift_degree = shift_degree @@ -290,7 +290,7 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. def _convert_trafo_phase_shifter(net): - tap_phase_shifter_type = net.trafo.tap_phase_shifter_type.values.copy() + tap_changer_type = net.trafo.tap_changer_type.values.copy() # vn_hv_kv = net.trafo.vn_hv_kv.values.copy() shift_degree = net.trafo.shift_degree.values.copy() @@ -299,12 +299,12 @@ def _convert_trafo_phase_shifter(net): tap_diff = tap_pos - tap_neutral tap_step_degree = net.trafo.tap_step_degree.values.copy() - net.trafo.loc[tap_phase_shifter_type == 2, 'shift_degree'] += (tap_diff[tap_phase_shifter_type == 2] * - tap_step_degree[tap_phase_shifter_type == 2]) + net.trafo.loc[tap_changer_type == "Ideal", 'shift_degree'] += (tap_diff[tap_changer_type == "Ideal"] * + tap_step_degree[tap_changer_type == "Ideal"]) net.trafo["tap_pos"] = 0 - net.trafo["tap_phase_shifter_type"] = pd.NA + net.trafo["tap_changer_type"] = pd.NA - return tap_phase_shifter_type, tap_pos, shift_degree + return tap_changer_type, tap_pos, shift_degree def _update_contingency_results(net, contingency_results, result_variables, nminus1, cause_element=None, diff --git a/pandapower/convert_format.py b/pandapower/convert_format.py index c4cfa7508..1cfcaaf06 100644 --- a/pandapower/convert_format.py +++ b/pandapower/convert_format.py @@ -96,8 +96,8 @@ def correct_dtypes(net, error): raised. """ empty_net = create_empty_network() - empty_net.trafo['tap_phase_shifter_type'] = empty_net.trafo['tap_phase_shifter_type'].astype("Int64") - empty_net.trafo3w['tap_phase_shifter_type'] = empty_net.trafo3w['tap_phase_shifter_type'].astype("Int64") + empty_net.trafo['tap_changer_type'] = empty_net.trafo['tap_changer_type'] + empty_net.trafo3w['tap_changer_type'] = empty_net.trafo3w['tap_changer_type'] not_corrected = list() failed = dict() for key, table in empty_net.items(): @@ -363,8 +363,8 @@ def _add_missing_columns(net, elements_to_deserialize): net.gen["slack"] = False if _check_elements_to_deserialize('trafo', elements_to_deserialize) and \ - "tap_phase_shifter_type" not in net.trafo: - net.trafo["tap_phase_shifter_type"] = pd.NA + "tap_changer_type" not in net.trafo: + net.trafo["tap_changer_type"] = pd.NA # asymmetric impedance if _check_elements_to_deserialize('impedance', elements_to_deserialize): @@ -565,20 +565,20 @@ def _convert_trafo_pst_logic(net): (net[trafotable][f"tap{t}_step_degree"] == 0)) & ((net[trafotable][f"tap{t}_step_percent"].isna()) | (net[trafotable][f"tap{t}_step_percent"] == 0))) - net[trafotable].loc[mask_na, f"tap{t}_phase_shifter_type"] = pd.NA + net[trafotable].loc[mask_na, f"tap{t}_changer_type"] = "None" # ratio/asymmetrical phase shifters mask_ratio_asym = ((net[trafotable][f"tap{t}_step_degree"] != 90) & ((net[trafotable][f"tap{t}_step_percent"].notna()) & (net[trafotable][f"tap{t}_step_percent"] != 0))) - net[trafotable].loc[mask_ratio_asym, f"tap{t}_phase_shifter_type"] = 0 + net[trafotable].loc[mask_ratio_asym, f"tap{t}_changer_type"] = "Ratio" # symmetrical phase shifters mask_sym = ((net[trafotable][f"tap{t}_step_degree"] == 90) & ((net[trafotable][f"tap{t}_step_percent"].notna()) & (net[trafotable][f"tap{t}_step_percent"] != 0))) - net[trafotable].loc[mask_sym, f"tap{t}_phase_shifter_type"] = 1 + net[trafotable].loc[mask_sym, f"tap{t}_changer_type"] = "Symmetrical" # ideal phase shifters mask_ideal = (((net[trafotable][f"tap{t}_step_degree"].notna()) & (net[trafotable][f"tap{t}_step_degree"] != 0)) & ((net[trafotable][f"tap{t}_step_percent"].isna()) | (net[trafotable][f"tap{t}_step_percent"] == 0))) - net[trafotable].loc[mask_ideal, f"tap{t}_phase_shifter_type"] = 2 + net[trafotable].loc[mask_ideal, f"tap{t}_changer_type"] = "Ideal" diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index 479d38609..b9b6aed5a 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -307,14 +307,14 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: self.cimConverter.cim['ssh']['RatioTapChanger'][['rdfId', 'step']], how='left', on='rdfId') eqssh_tap_changers[sc['tc']] = 'RatioTapChanger' - eqssh_tap_changers['tap_phase_shifter_type'] = 0 # Ratio/Asymmetrical phase shifter + eqssh_tap_changers['tap_changer_type'] = "Ratio" # Ratio/Asymmetrical phase shifter eqssh_tap_changers[sc['tc_id']] = eqssh_tap_changers['rdfId'].copy() eqssh_tap_changers_linear = pd.merge(self.cimConverter.cim['eq']['PhaseTapChangerLinear'], self.cimConverter.cim['ssh']['PhaseTapChangerLinear'], how='left', on='rdfId') eqssh_tap_changers_linear['stepVoltageIncrement'] = .001 eqssh_tap_changers_linear[sc['tc']] = 'PhaseTapChangerLinear' - eqssh_tap_changers_linear['tap_phase_shifter_type'] = 2 # Ideal phase shifter + eqssh_tap_changers_linear['tap_changer_type'] = "Ideal" # Ideal phase shifter eqssh_tap_changers_linear[sc['tc_id']] = eqssh_tap_changers_linear['rdfId'].copy() eqssh_tap_changers = pd.concat([eqssh_tap_changers, eqssh_tap_changers_linear], ignore_index=True, sort=False) eqssh_tap_changers_async = pd.merge(self.cimConverter.cim['eq']['PhaseTapChangerAsymmetrical'], @@ -323,7 +323,7 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: eqssh_tap_changers_async['stepVoltageIncrement'] = eqssh_tap_changers_async['voltageStepIncrement'][:] eqssh_tap_changers_async = eqssh_tap_changers_async.drop(columns=['voltageStepIncrement']) eqssh_tap_changers_async[sc['tc']] = 'PhaseTapChangerAsymmetrical' - eqssh_tap_changers_async['tap_phase_shifter_type'] = 0 # Ratio/Asymmetrical phase shifter + eqssh_tap_changers_async['tap_changer_type'] = "Ratio" # Ratio/Asymmetrical phase shifter eqssh_tap_changers_async[sc['tc_id']] = eqssh_tap_changers_async['rdfId'].copy() eqssh_tap_changers = pd.concat([eqssh_tap_changers, eqssh_tap_changers_async], ignore_index=True, sort=False) eqssh_ratio_tap_changers_sync = pd.merge(self.cimConverter.cim['eq']['PhaseTapChangerSymmetrical'], @@ -332,7 +332,7 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: eqssh_ratio_tap_changers_sync['stepVoltageIncrement'] = eqssh_ratio_tap_changers_sync['voltageStepIncrement'] eqssh_ratio_tap_changers_sync = eqssh_ratio_tap_changers_sync.drop(columns=['voltageStepIncrement']) eqssh_ratio_tap_changers_sync[sc['tc']] = 'PhaseTapChangerSymmetrical' - eqssh_ratio_tap_changers_sync['tap_phase_shifter_type'] = 1 # Symmetrical phase shifter + eqssh_ratio_tap_changers_sync['tap_changer_type'] = "Symmetrical" # Symmetrical phase shifter eqssh_ratio_tap_changers_sync[sc['tc_id']] = eqssh_ratio_tap_changers_sync['rdfId'].copy() eqssh_tap_changers = \ pd.concat([eqssh_tap_changers, eqssh_ratio_tap_changers_sync], ignore_index=True, sort=False) @@ -364,7 +364,7 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: ptct = ptct.rename(columns={'current_step': 'step'}) ptct['stepPhaseShiftIncrement'] = ptct['angle'][:] ptct['stepVoltageIncrement'] = ptct['ratio'][:] - ptct['tap_phase_shifter_type'] = 0 # Ratio/Asymmetrical phase shifter + ptct['tap_changer_type'] = "Ratio" # Ratio/Asymmetrical phase shifter eqssh_tap_changers = pd.concat([eqssh_tap_changers, ptct], ignore_index=True, sort=False) del eqssh_tap_changers_linear, eqssh_tap_changers_async, eqssh_ratio_tap_changers_sync @@ -435,7 +435,7 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: how='left', left_on='Terminal', right_on='rdfId_Terminal') # add the TapChangers power_transformers = pd.merge(power_transformers, eqssh_tap_changers, how='left', on=sc['pte_id']) - power_transformers['tap_phase_shifter_type'] = power_transformers['tap_phase_shifter_type'].astype('Int64') + power_transformers['tap_changer_type'] = power_transformers['tap_changer_type'] return power_transformers def _prepare_trafos_cim16(self, power_trafo2w: pd.DataFrame) -> pd.DataFrame: diff --git a/pandapower/converter/pypower/from_ppc.py b/pandapower/converter/pypower/from_ppc.py index f25a0bef9..c69f8282a 100644 --- a/pandapower/converter/pypower/from_ppc.py +++ b/pandapower/converter/pypower/from_ppc.py @@ -287,7 +287,7 @@ def _from_ppc_branch(net, ppc, f_hz, **kwargs): vkr_percent[~tap_side_is_hv] /= (1+ratio_1[~tap_side_is_hv])**2 tap_step_percent = np.abs(ratio_1)*100 - tap_phase_shifter_type = np.where(tap_step_percent > 0, 0, pd.NA) + tap_changer_type = np.where(tap_step_percent > 0, 0, pd.NA) idx_trafo = create_transformers_from_parameters( net, hv_buses=net.bus.index[hv_bus], lv_buses=net.bus.index[lv_bus], sn_mva=sn, @@ -296,7 +296,7 @@ def _from_ppc_branch(net, ppc, f_hz, **kwargs): max_loading_percent=100, pfe_kw=pfe_kw, i0_percent=i0_percent, shift_degree=ppc['branch'][is_trafo, SHIFT], tap_step_percent=tap_step_percent, tap_pos=np.sign(ratio_1), - tap_side=tap_side, tap_neutral=0, tap_phase_shifter_type=tap_phase_shifter_type) + tap_side=tap_side, tap_neutral=0, tap_changer_type=tap_changer_type) else: idx_trafo = [] # unused data from ppc: rateB, rateC diff --git a/pandapower/create.py b/pandapower/create.py index d10eb2bb9..e911e2970 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -246,7 +246,7 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("tap_step_percent", "f8"), ("tap_step_degree", "f8"), ("tap_pos", "i4"), - ("tap_phase_shifter_type", "i4"), + ("tap_changer_type", dtype(object)), ('id_characteristic_table', 'u4'), ('tap_dependency_table', 'bool'), ("parallel", "u4"), @@ -281,7 +281,7 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True): ("tap_step_degree", "f8"), ("tap_pos", "i4"), ("tap_at_star_point", 'bool'), - ("tap_phase_shifter_type", 'i4'), + ("tap_changer_type", dtype(object)), ('id_characteristic_table', 'u4'), ('tap_dependency_table', 'bool'), ("in_service", 'bool')], @@ -3282,7 +3282,7 @@ def create_lines_dc_from_parameters(net, from_buses_dc, to_buses_dc, length_km, def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in_service=True, - index=None, max_loading_percent=nan, parallel=1, df=1., tap_phase_shifter_type=nan, + index=None, max_loading_percent=nan, parallel=1, df=1., tap_changer_type="None", tap_dependency_table=nan, id_characteristic_table=nan, pt_percent=nan, oltc=nan, xn_ohm=nan, tap2_pos=nan, **kwargs): """ @@ -3343,8 +3343,8 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ net.trafo_characteristic_table - **tap_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, - 1: Symmetrical, 2: Ideal)* + **tap_changer_type** (String, nan) - specifies the phase shifter type ("Ratio": Ratio/Asymmetrical, + "Symmetrical": Symmetrical, "Ideal": Ideal, "None": no tap changer)* **xn_ohm** (float) - impedance of the grounding reactor (Z_N) for short circuit calculation @@ -3391,7 +3391,7 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in v.update(updates) for s, tap_pos_var in (("", tap_pos), ("2", tap2_pos)): # to enable a second tap changer if available for tp in (f"tap{s}_neutral", f"tap{s}_max", f"tap{s}_min", f"tap{s}_side", - f"tap{s}_step_percent", f"tap{s}_step_degree", f"tap{s}_phase_shifter_type"): + f"tap{s}_step_percent", f"tap{s}_step_degree", f"tap{s}_changer_type"): if tp in ti: v[tp] = ti[tp] if (f"tap{s}_neutral" in v) and (tap_pos_var is nan): @@ -3409,8 +3409,8 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in "trafo", dtype="Int64") _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo", dtype=bool_, default_val=False) - _set_value_if_not_nan(net, index, tap_phase_shifter_type, "tap_phase_shifter_type", - "trafo", dtype="Int64") + _set_value_if_not_nan(net, index, tap_changer_type, "tap_changer_type", + "trafo", dtype=str) _set_value_if_not_nan(net, index, pt_percent, "pt_percent", "trafo") _set_value_if_not_nan(net, index, oltc, "oltc", "trafo", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, xn_ohm, "xn_ohm", "trafo") @@ -3423,7 +3423,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn shift_degree=0, tap_side=None, tap_neutral=nan, tap_max=nan, tap_min=nan, tap_step_percent=nan, tap_step_degree=nan, - tap_pos=nan, tap_phase_shifter_type=nan, id_characteristic_table=nan, + tap_pos=nan, tap_changer_type="None", id_characteristic_table=nan, in_service=True, name=None, vector_group=None, index=None, max_loading_percent=nan, parallel=1, df=1., vk0_percent=nan, vkr0_percent=nan, @@ -3432,7 +3432,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn pt_percent=nan, oltc=nan, tap_dependency_table=False, xn_ohm=nan, tap2_side=None, tap2_neutral=nan, tap2_max=nan, tap2_min=nan, tap2_step_percent=nan, tap2_step_degree=nan, - tap2_pos=nan, tap2_phase_shifter_type=nan, **kwargs): + tap2_pos=nan, tap2_changer_type="None", **kwargs): """ Creates a two-winding transformer in table net["trafo"]. The trafo parameters are defined through the standard type library. @@ -3502,7 +3502,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **tap_step_degree** (float) - tap step size for voltage angle in degree* - **tap_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + **tap_changer_type** (str, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal)* **index** (int, None) - Force a specified ID if it is available. If None, the index one \ @@ -3546,7 +3546,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **tap2_step_degree** (float) - second tap step size for voltage angle in degree* - **tap2_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + **tap2_changer_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal)* **leakage_resistance_ratio_hv** (bool) - ratio of transformer short-circuit resistance on HV side (default 0.5) @@ -3597,8 +3597,8 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo", dtype="Int64") - _set_value_if_not_nan(net, index, tap_phase_shifter_type, - "tap_phase_shifter_type", "trafo", dtype="Int64") + _set_value_if_not_nan(net, index, tap_changer_type, + "tap_changer_type", "trafo", dtype=str) _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo", dtype=bool_, default_val=False) @@ -3611,8 +3611,8 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn _set_value_if_not_nan(net, index, tap2_step_degree, "tap2_step_degree", "trafo", dtype=np.float64) _set_value_if_not_nan(net, index, tap2_pos if pd.notnull(tap2_pos) else tap2_neutral, "tap2_pos", "trafo", dtype=np.float64) - _set_value_if_not_nan(net, index, tap2_phase_shifter_type, "tap2_phase_shifter_type", - "trafo", dtype="Int64") + _set_value_if_not_nan(net, index, tap2_changer_type, "tap2_changer_type", + "trafo", dtype=object) if not (isnan(vk0_percent) and isnan(vkr0_percent) and isnan(mag0_percent) and isnan(mag0_rx) and isnan(si0_hv_partial) and vector_group is None): @@ -3634,14 +3634,14 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k vkr_percent, vk_percent, pfe_kw, i0_percent, shift_degree=0, tap_side=None, tap_neutral=nan, tap_max=nan, tap_min=nan, tap_step_percent=nan, tap_step_degree=nan, tap_pos=nan, - tap_phase_shifter_type=nan, id_characteristic_table=nan, in_service=True, + tap_changer_type=nan, id_characteristic_table=nan, in_service=True, name=None, vector_group=None, index=None, max_loading_percent=nan, parallel=1, df=1., vk0_percent=nan, vkr0_percent=nan, mag0_percent=nan, mag0_rx=nan, si0_hv_partial=nan, pt_percent=nan, oltc=nan, tap_dependency_table=False, xn_ohm=nan, tap2_side=None, tap2_neutral=nan, tap2_max=nan, tap2_min=nan, tap2_step_percent=nan, tap2_step_degree=nan, - tap2_pos=nan, tap2_phase_shifter_type=nan, + tap2_pos=nan, tap2_changer_type=nan, **kwargs): """ Creates several two-winding transformers in table net["trafo"]. @@ -3713,7 +3713,7 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k **tap_step_degree** (list of float) - tap step size for voltage angle in degree* - **tap_phase_shifter_type** (list of int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + **tap_changer_type** (list of str, nan) - specifies the tap changer type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal)* **index** (list of int, None) - Force a specified ID if it is available. If None, the index one \ @@ -3757,7 +3757,7 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k **tap2_step_degree** (list of float) - second tap step size for voltage angle in degree* - **tap2_phase_shifter_type** (list of int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + **tap2_changer_type** (list of int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal)* ** only considered in load flow if calculate_voltage_angles = True @@ -3778,7 +3778,7 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k "tap_neutral": tp_neutral, "tap_max": tap_max, "tap_min": tap_min, "shift_degree": shift_degree, "tap_pos": tp_pos, "tap_side": tap_side, "tap_step_percent": tap_step_percent, "tap_step_degree": tap_step_degree, - "tap_phase_shifter_type": tap_phase_shifter_type, "parallel": parallel, "df": df, + "tap_changer_type": tap_changer_type, "parallel": parallel, "df": df, "tap_dependency_table": tap_dependency_table} _add_to_entries_if_not_nan(net, "trafo", entries, index, "id_characteristic_table", @@ -3801,8 +3801,8 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_step_percent", tap2_step_percent) _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_step_degree", tap2_step_degree) _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_pos", tap2_pos) - _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_phase_shifter_type", - tap2_phase_shifter_type, dtype="Int64") + _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_changer_type", + tap2_changer_type, dtype="Int64") defaults_to_fill = [("tap_dependency_table", False)] _set_multiple_entries(net, "trafo", index, defaults_to_fill=defaults_to_fill, **entries, **kwargs) @@ -3811,7 +3811,7 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_pos=nan, - in_service=True, index=None, max_loading_percent=nan, tap_phase_shifter_type=nan, + in_service=True, index=None, max_loading_percent=nan, tap_changer_type=nan, tap_at_star_point=False, tap_dependency_table=nan, id_characteristic_table=nan): """ Creates a three-winding transformer in table net["trafo3w"]. @@ -3836,8 +3836,8 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p **tap_pos** (int, nan) - current tap position of the transformer. Defaults to the medium \ position (tap_neutral) - **tap_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, - 1: Symmetrical, 2: Ideal) + **tap_changer_type** (str, nan) - specifies the tap changer (0: Ratio/Asymmetrical, + 1: Symmetrical, 2: Ideal)* **tap_at_star_point** (boolean) - Whether tap changer is located at the star point of the \ 3W-transformer or at the bus @@ -3904,7 +3904,7 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p }) for tp in ( "tap_neutral", "tap_max", "tap_min", "tap_side", "tap_step_percent", "tap_step_degree", - "tap_phase_shifter_type"): + "tap_changer_type"): if tp in ti: v.update({tp: ti[tp]}) @@ -3924,8 +3924,8 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p "id_characteristic_table", "trafo3w", dtype="Int64") _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo3w", dtype=bool_, default_val=False) - _set_value_if_not_nan(net, index, tap_phase_shifter_type, - "tap_phase_shifter_type", "trafo3w", dtype="Int64") + _set_value_if_not_nan(net, index, tap_changer_type, + "tap_changer_type", "trafo3w", dtype=str) return index @@ -3937,7 +3937,7 @@ def create_transformer3w_from_parameters( vkr_mv_percent, vkr_lv_percent, pfe_kw, i0_percent, shift_mv_degree=0., shift_lv_degree=0., tap_side=None, tap_step_percent=nan, tap_step_degree=nan, tap_pos=nan, - tap_neutral=nan, tap_max=nan, tap_phase_shifter_type=nan, + tap_neutral=nan, tap_max=nan, tap_changer_type=nan, tap_min=nan, name=None, in_service=True, index=None, max_loading_percent=nan, tap_at_star_point=False, vk0_hv_percent=nan, vk0_mv_percent=nan, vk0_lv_percent=nan, @@ -4007,7 +4007,7 @@ def create_transformer3w_from_parameters( **tap_pos** (int, nan) - current tap position of the transformer. Defaults to the \ medium position (tap_neutral) - **tap_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + **tap_changer_type** (str, nan) -specifies the tap changer (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal) **tap_at_star_point** (boolean) - Whether tap changer is located at the star point of the \ @@ -4086,8 +4086,8 @@ def create_transformer3w_from_parameters( _set_value_if_not_nan(net, index, max_loading_percent, "max_loading_percent", "trafo3w") _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo3w", dtype="Int64") - _set_value_if_not_nan(net, index, tap_phase_shifter_type, - "tap_phase_shifter_type", "trafo3w", dtype="Int64") + _set_value_if_not_nan(net, index, tap_changer_type, + "tap_changer_type", "trafo3w", dtype=str) _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo3w", dtype=bool_, default_val=False) @@ -4103,7 +4103,7 @@ def create_transformers3w_from_parameters( tap_step_percent=nan, tap_step_degree=nan, tap_pos=nan, tap_neutral=nan, tap_max=nan, tap_min=nan, name=None, in_service=True, index=None, max_loading_percent=nan, - tap_at_star_point=False, tap_phase_shifter_type=nan, + tap_at_star_point=False, tap_changer_type=nan, vk0_hv_percent=nan, vk0_mv_percent=nan, vk0_lv_percent=nan, vkr0_hv_percent=nan, vkr0_mv_percent=nan, vkr0_lv_percent=nan, vector_group=None, tap_dependency_table=False, id_characteristic_table=nan, **kwargs): @@ -4173,8 +4173,8 @@ def create_transformers3w_from_parameters( **tap_pos** (list of int, nan) - current tap position of the transformer. Defaults to the \ medium position (tap_neutral) - **tap_phase_shifter_type** (list of int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, - 1: Symmetrical, 2: Ideal) + **tap_changer_type** (list of str, nan) - specifies the tap changer (0: Ratio/Asymmetrical, + 1: Symmetrical, 2: Ideal) **tap_at_star_point** (list of boolean) - Whether tap changer is located at the star point of the \ 3W-transformer or at the bus @@ -4252,8 +4252,8 @@ def create_transformers3w_from_parameters( max_loading_percent) _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "id_characteristic_table", id_characteristic_table, dtype="Int64") - _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "tap_phase_shifter_type", - tap_phase_shifter_type, dtype="Int64") + _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "tap_changer_type", + tap_changer_type, dtype=str) defaults_to_fill = [("tap_dependency_table", False)] _set_multiple_entries(net, "trafo3w", index, defaults_to_fill=defaults_to_fill, **entries, diff --git a/pandapower/networks/IEEE_European_LV_Off_Peak_1.json b/pandapower/networks/IEEE_European_LV_Off_Peak_1.json index db9d40302..91e7ba0a8 100644 --- a/pandapower/networks/IEEE_European_LV_Off_Peak_1.json +++ b/pandapower/networks/IEEE_European_LV_Off_Peak_1.json @@ -318,7 +318,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", "orient": "split", "dtype": { "name": "object", @@ -340,7 +340,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -1192,7 +1192,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1210,7 +1210,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1228,7 +1228,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1246,7 +1246,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "08 MVA 10/04 kV Dyn1 ASEA": { "sn_mva": 0.800000011920929, @@ -1266,7 +1266,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1287,7 +1287,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1305,7 +1305,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1323,7 +1323,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1341,7 +1341,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1359,7 +1359,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1377,7 +1377,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1395,7 +1395,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1413,7 +1413,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1431,7 +1431,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1449,7 +1449,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { diff --git a/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json b/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json index edec0ac0e..a8fd79c05 100644 --- a/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json +++ b/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json @@ -318,7 +318,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", "orient": "split", "dtype": { "name": "object", @@ -340,7 +340,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -1192,7 +1192,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1210,7 +1210,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1228,7 +1228,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1246,7 +1246,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "08 MVA 10/04 kV Dyn1 ASEA": { "sn_mva": 0.800000011920929, @@ -1266,7 +1266,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1287,7 +1287,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1305,7 +1305,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1323,7 +1323,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1341,7 +1341,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1359,7 +1359,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1377,7 +1377,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1395,7 +1395,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1413,7 +1413,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1431,7 +1431,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1449,7 +1449,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { diff --git a/pandapower/networks/IEEE_European_LV_On_Peak_566.json b/pandapower/networks/IEEE_European_LV_On_Peak_566.json index cd8a049f5..b56aba730 100644 --- a/pandapower/networks/IEEE_European_LV_On_Peak_566.json +++ b/pandapower/networks/IEEE_European_LV_On_Peak_566.json @@ -318,7 +318,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", "orient": "split", "dtype": { "name": "object", @@ -340,7 +340,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -1192,7 +1192,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1210,7 +1210,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1228,7 +1228,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1246,7 +1246,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "08 MVA 10/04 kV Dyn1 ASEA": { "sn_mva": 0.800000011920929, @@ -1266,7 +1266,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1287,7 +1287,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1305,7 +1305,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1323,7 +1323,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1341,7 +1341,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1359,7 +1359,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1377,7 +1377,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1395,7 +1395,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1413,7 +1413,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1431,7 +1431,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1449,7 +1449,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { diff --git a/pandapower/networks/create_examples.py b/pandapower/networks/create_examples.py index 18a3bedcf..b53f50b85 100644 --- a/pandapower/networks/create_examples.py +++ b/pandapower/networks/create_examples.py @@ -203,7 +203,7 @@ def example_multivoltage(): pfe_kw=0.95, i0_percent=0.2375, tap_side="hv", tap_neutral=0, tap_min=-2, tap_max=2, tap_step_percent=2.5, tap_pos=0, - shift_degree=150, name='MV-LV-Trafo', tap_phase_shifter_type=0) + shift_degree=150, name='MV-LV-Trafo', tap_changer_type="Ratio") # Trafo3w hv_bus = pp.get_element_index(net, "bus", "Bus HV2") @@ -218,7 +218,7 @@ def example_multivoltage(): pfe_kw=0, i0_percent=0, shift_mv_degree=30, shift_lv_degree=30, tap_side="hv", tap_neutral=0, tap_min=-8, tap_max=8, tap_step_percent=1.25, - tap_pos=0, name='HV-MV-MV-Trafo', tap_phase_shifter_type=0) + tap_pos=0, name='HV-MV-MV-Trafo', tap_changer_type="Ratio") # --- Static generators diff --git a/pandapower/networks/lv_schutterwald.json b/pandapower/networks/lv_schutterwald.json index fdabe4999..059708cd6 100644 --- a/pandapower/networks/lv_schutterwald.json +++ b/pandapower/networks/lv_schutterwald.json @@ -290,7 +290,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1,3,4,5,6,7,10,11,12,13,14,15,16],\"data\":[[\"T_idx_47\",\"0.4 MVA 20\\/0.4 kV\",2983,3000,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_45\",\"0.25 MVA 20\\/0.4 kV\",2984,3001,0.25,20.0,0.4,6.0,1.44,0.8,0.32,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_35\",\"0.4 MVA 20\\/0.4 kV\",2986,3003,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_77\",\"0.4 MVA 20\\/0.4 kV\",2987,3004,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_78\",\"0.63 MVA 20\\/0.4 kV\",2988,3005,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_119\",\"0.63 MVA 20\\/0.4 kV\",2989,3006,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_118\",\"0.63 MVA 20\\/0.4 kV\",2990,3007,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_117\",\"0.4 MVA 20\\/0.4 kV\",2993,3010,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_80\",\"0.63 MVA 20\\/0.4 kV\",2994,3011,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_73\",\"0.63 MVA 20\\/0.4 kV\",2995,3012,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_43\",\"0.63 MVA 20\\/0.4 kV\",2996,3013,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_81\",\"0.63 MVA 20\\/0.4 kV\",2997,3014,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_71\",\"0.4 MVA 20\\/0.4 kV\",2998,3015,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_ZUSATZ\",\"0.63 MVA 20\\/0.4 kV\",2999,3016,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1,3,4,5,6,7,10,11,12,13,14,15,16],\"data\":[[\"T_idx_47\",\"0.4 MVA 20\\/0.4 kV\",2983,3000,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_45\",\"0.25 MVA 20\\/0.4 kV\",2984,3001,0.25,20.0,0.4,6.0,1.44,0.8,0.32,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_35\",\"0.4 MVA 20\\/0.4 kV\",2986,3003,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_77\",\"0.4 MVA 20\\/0.4 kV\",2987,3004,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_78\",\"0.63 MVA 20\\/0.4 kV\",2988,3005,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_119\",\"0.63 MVA 20\\/0.4 kV\",2989,3006,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_118\",\"0.63 MVA 20\\/0.4 kV\",2990,3007,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_117\",\"0.4 MVA 20\\/0.4 kV\",2993,3010,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_80\",\"0.63 MVA 20\\/0.4 kV\",2994,3011,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_73\",\"0.63 MVA 20\\/0.4 kV\",2995,3012,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_43\",\"0.63 MVA 20\\/0.4 kV\",2996,3013,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_81\",\"0.63 MVA 20\\/0.4 kV\",2997,3014,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_71\",\"0.4 MVA 20\\/0.4 kV\",2998,3015,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_ZUSATZ\",\"0.63 MVA 20\\/0.4 kV\",2999,3016,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -312,7 +312,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -915,7 +915,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 160.0 }, "100 MVA 220/110 kV": { @@ -933,7 +933,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 100.0 }, "63 MVA 110/20 kV": { @@ -951,7 +951,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 63.0 }, "40 MVA 110/20 kV": { @@ -969,7 +969,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 40.0 }, "25 MVA 110/20 kV": { @@ -987,7 +987,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 25.0 }, "63 MVA 110/10 kV": { @@ -1005,7 +1005,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 63.0 }, "40 MVA 110/10 kV": { @@ -1023,7 +1023,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 40.0 }, "25 MVA 110/10 kV": { @@ -1041,7 +1041,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 25.0 }, "63 MVA 110/20 kV v1.4.3 and older": { @@ -1059,7 +1059,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 63.0 }, "40 MVA 110/20 kV v1.4.3 and older": { @@ -1077,7 +1077,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 40.0 }, "25 MVA 110/20 kV v1.4.3 and older": { @@ -1095,7 +1095,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 25.0 }, "63 MVA 110/10 kV v1.4.3 and older": { @@ -1113,7 +1113,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 63.0 }, "40 MVA 110/10 kV v1.4.3 and older": { @@ -1131,7 +1131,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 40.0 }, "25 MVA 110/10 kV v1.4.3 and older": { @@ -1149,7 +1149,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 25.0 }, "0.25 MVA 20/0.4 kV": { @@ -1167,7 +1167,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 0.25 }, "0.4 MVA 20/0.4 kV": { @@ -1185,7 +1185,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 0.4 }, "0.63 MVA 20/0.4 kV": { @@ -1203,7 +1203,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 0.63 }, "0.25 MVA 10/0.4 kV": { @@ -1221,7 +1221,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 0.25 }, "0.4 MVA 10/0.4 kV": { @@ -1239,7 +1239,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 0.4 }, "0.63 MVA 10/0.4 kV": { @@ -1257,7 +1257,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "sn_mva": 0.63 } }, diff --git a/pandapower/networks/power_system_test_case_jsons/GBnetwork.json b/pandapower/networks/power_system_test_case_jsons/GBnetwork.json index d178eb09f..fe2633406 100644 --- a/pandapower/networks/power_system_test_case_jsons/GBnetwork.json +++ b/pandapower/networks/power_system_test_case_jsons/GBnetwork.json @@ -296,7 +296,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -318,7 +318,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -329,7 +329,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -359,7 +359,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -794,7 +794,7 @@ "tap_min": -2, "vkr_percent": 1.425, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -812,7 +812,7 @@ "tap_min": -2, "vkr_percent": 1.44, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -830,7 +830,7 @@ "tap_min": -2, "vkr_percent": 1.2, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -848,7 +848,7 @@ "tap_min": -9, "vkr_percent": 0.25, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 12.2, "tap_max": 9 @@ -866,7 +866,7 @@ "tap_min": -9, "vkr_percent": 0.31, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -884,7 +884,7 @@ "tap_min": -2, "vkr_percent": 1.206, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -902,7 +902,7 @@ "tap_min": -2, "vkr_percent": 1.325, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -920,7 +920,7 @@ "tap_min": -2, "vkr_percent": 1.0794, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -938,7 +938,7 @@ "tap_min": -9, "vkr_percent": 0.322, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -956,7 +956,7 @@ "tap_min": -9, "vkr_percent": 0.26, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 12.0, "tap_max": 9 @@ -974,7 +974,7 @@ "tap_min": -9, "vkr_percent": 0.276, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -992,7 +992,7 @@ "tap_min": -9, "vkr_percent": 0.302, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1010,7 +1010,7 @@ "tap_min": -9, "vkr_percent": 0.282, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1028,7 +1028,7 @@ "tap_min": -9, "vkr_percent": 0.295, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -1056,7 +1056,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1081,7 +1081,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json b/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json index f2ec458b4..d4766c9a0 100644 --- a/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json +++ b/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json @@ -301,7 +301,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1,10,11,12,2,3,4,5,6,7,8,9],\"data\":[[null,null,0,2,132.0,275.0,132.0,19.8215482745,0.924,0.0,-3.9393939394,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,0,2,132.0,275.0,132.0,19.8215482745,0.924,0.0,-3.9393939394,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,3,2,648.0,275.0,132.0,26.639027009300001,1.944,0.0,-0.0679012346,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,3,2,648.0,275.0,132.0,26.639027009300001,1.944,0.0,-0.6790123457,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,1,2,652.0,275.0,132.0,53.889295279899997,19.586079999999999,0.0,-0.1901840491,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,6,3,1090.0,400.0,275.0,14.893648478799999,2.2999,0.0,-1.0770642202,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,5,3,1500.0,400.0,275.0,34.555064751800003,1.95,0.0,-0.9973333333,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,5,3,1120.0,400.0,275.0,25.801115014699999,1.456,0.0,-1.5696428571,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,4,3,1000.0,400.0,275.0,24.020824298899999,1.0,0.0,-1.25,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,4,3,1000.0,400.0,275.0,24.020824298899999,1.0,0.0,-1.25,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,6,3,1090.0,400.0,275.0,14.8919691781,2.289,0.0,-1.4110091743,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,11,17,2400.0,400.0,400.0,21.672890347199999,1.776,0.0,-1.2129166667,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,11,12,3100.0,400.0,400.0,33.550250371600001,2.976,0.0,-1.2419354839,2.0,null,null,null,null,null,null,null,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1,10,11,12,2,3,4,5,6,7,8,9],\"data\":[[null,null,0,2,132.0,275.0,132.0,19.8215482745,0.924,0.0,-3.9393939394,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,0,2,132.0,275.0,132.0,19.8215482745,0.924,0.0,-3.9393939394,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,3,2,648.0,275.0,132.0,26.639027009300001,1.944,0.0,-0.0679012346,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,3,2,648.0,275.0,132.0,26.639027009300001,1.944,0.0,-0.6790123457,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,1,2,652.0,275.0,132.0,53.889295279899997,19.586079999999999,0.0,-0.1901840491,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,6,3,1090.0,400.0,275.0,14.893648478799999,2.2999,0.0,-1.0770642202,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,5,3,1500.0,400.0,275.0,34.555064751800003,1.95,0.0,-0.9973333333,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,5,3,1120.0,400.0,275.0,25.801115014699999,1.456,0.0,-1.5696428571,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,4,3,1000.0,400.0,275.0,24.020824298899999,1.0,0.0,-1.25,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,4,3,1000.0,400.0,275.0,24.020824298899999,1.0,0.0,-1.25,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,6,3,1090.0,400.0,275.0,14.8919691781,2.289,0.0,-1.4110091743,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,11,17,2400.0,400.0,400.0,21.672890347199999,1.776,0.0,-1.2129166667,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,11,12,3100.0,400.0,400.0,33.550250371600001,2.976,0.0,-1.2419354839,2.0,null,null,null,null,null,null,null,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -323,7 +323,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -334,7 +334,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -364,7 +364,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -799,7 +799,7 @@ "tap_min": -2, "vkr_percent": 1.425, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -816,7 +816,7 @@ "tap_min": -2, "vkr_percent": 1.44, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -833,7 +833,7 @@ "tap_min": -2, "vkr_percent": 1.2, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -850,7 +850,7 @@ "tap_min": -9, "vkr_percent": 0.25, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 12.2, "tap_max": 9 @@ -867,7 +867,7 @@ "tap_min": -9, "vkr_percent": 0.31, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -884,7 +884,7 @@ "tap_min": -2, "vkr_percent": 1.206, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -901,7 +901,7 @@ "tap_min": -2, "vkr_percent": 1.325, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -918,7 +918,7 @@ "tap_min": -2, "vkr_percent": 1.0794, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -935,7 +935,7 @@ "tap_min": -9, "vkr_percent": 0.322, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -952,7 +952,7 @@ "tap_min": -9, "vkr_percent": 0.26, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 12.0, "tap_max": 9 @@ -969,7 +969,7 @@ "tap_min": -9, "vkr_percent": 0.276, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -986,7 +986,7 @@ "tap_min": -9, "vkr_percent": 0.302, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1003,7 +1003,7 @@ "tap_min": -9, "vkr_percent": 0.282, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1020,7 +1020,7 @@ "tap_min": -9, "vkr_percent": 0.295, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -1048,7 +1048,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1073,7 +1073,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case118.json b/pandapower/networks/power_system_test_case_jsons/case118.json index 10737c6ce..6323f7ccc 100644 --- a/pandapower/networks/power_system_test_case_jsons/case118.json +++ b/pandapower/networks/power_system_test_case_jsons/case118.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,11,12,2,3,4,5,6,7,8,9],\"data\":[[null,null,7,4,9900.0,345.0,138.0,264.329999999999984,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,1.5,null,-1.0,false,1,1.0,true,100.0],[null,null,25,24,9900.0,345.0,138.0,378.180000000000007,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,80,79,9900.0,345.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,86,85,9900.0,161.0,138.0,2072.25986507098105,279.97199999999998,0.0,-0.04494949494949,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,115,67,9900.0,345.0,161.0,40.236040821631541,3.366,0.0,-0.16565656565657,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,29,16,9900.0,345.0,138.0,384.120000000000005,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,37,36,9900.0,345.0,138.0,371.25,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,62,58,9900.0,345.0,138.0,382.139999999999986,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,63,60,9900.0,345.0,138.0,265.319999999999993,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,1.5,null,-1.0,false,1,1.0,true,100.0],[null,null,64,65,9900.0,345.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,64,67,9900.0,345.0,161.0,158.988082081645359,13.662000000000001,0.0,-0.64444444444444,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,67,68,9900.0,161.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,80,67,9900.0,345.0,161.0,200.72906123678257,17.324999999999999,0.0,-0.81616161616162,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,11,12,2,3,4,5,6,7,8,9],\"data\":[[null,null,7,4,9900.0,345.0,138.0,264.329999999999984,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,1.5,null,-1.0,false,1,1.0,true,100.0],[null,null,25,24,9900.0,345.0,138.0,378.180000000000007,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,80,79,9900.0,345.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,86,85,9900.0,161.0,138.0,2072.25986507098105,279.97199999999998,0.0,-0.04494949494949,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,115,67,9900.0,345.0,161.0,40.236040821631541,3.366,0.0,-0.16565656565657,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,29,16,9900.0,345.0,138.0,384.120000000000005,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,37,36,9900.0,345.0,138.0,371.25,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,62,58,9900.0,345.0,138.0,382.139999999999986,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,63,60,9900.0,345.0,138.0,265.319999999999993,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,1.5,null,-1.0,false,1,1.0,true,100.0],[null,null,64,65,9900.0,345.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,64,67,9900.0,345.0,161.0,158.988082081645359,13.662000000000001,0.0,-0.64444444444444,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,67,68,9900.0,161.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,80,67,9900.0,345.0,161.0,200.72906123678257,17.324999999999999,0.0,-0.81616161616162,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,7 +362,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -918,7 +918,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -936,7 +936,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -954,7 +954,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -972,7 +972,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -990,7 +990,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1008,7 +1008,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1026,7 +1026,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1044,7 +1044,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1062,7 +1062,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1080,7 +1080,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1098,7 +1098,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1116,7 +1116,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1134,7 +1134,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1152,7 +1152,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1170,7 +1170,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1188,7 +1188,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1206,7 +1206,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1224,7 +1224,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1242,7 +1242,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1260,7 +1260,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1287,7 +1287,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1312,7 +1312,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json b/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json index 1948ac10a..685df097c 100644 --- a/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json +++ b/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json @@ -287,7 +287,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -309,7 +309,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -320,7 +320,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -350,7 +350,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -908,7 +908,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -926,7 +926,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -944,7 +944,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -962,7 +962,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -980,7 +980,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "vn_hv_kv": 110, @@ -998,7 +998,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "vn_hv_kv": 110, @@ -1016,7 +1016,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "vn_hv_kv": 110, @@ -1034,7 +1034,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV v1.4.3 and older": { "i0_percent": 0.086, @@ -1052,7 +1052,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV v1.4.3 and older": { "i0_percent": 0.08, @@ -1070,7 +1070,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV v1.4.3 and older": { "i0_percent": 0.071, @@ -1088,7 +1088,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV v1.4.3 and older": { "vn_hv_kv": 110, @@ -1106,7 +1106,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV v1.4.3 and older": { "vn_hv_kv": 110, @@ -1124,7 +1124,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV v1.4.3 and older": { "vn_hv_kv": 110, @@ -1142,7 +1142,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 20/0.4 kV": { "vn_hv_kv": 20, @@ -1160,7 +1160,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "vn_hv_kv": 20, @@ -1178,7 +1178,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV": { "vn_hv_kv": 20, @@ -1196,7 +1196,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "vn_hv_kv": 10, @@ -1214,7 +1214,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "vn_hv_kv": 10, @@ -1232,7 +1232,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 10/0.4 kV": { "vn_hv_kv": 10, @@ -1250,7 +1250,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { @@ -1277,7 +1277,7 @@ "tap_min": -10, "tap_max": 10, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63/25/38 MVA 110/10/10 kV": { "vn_hv_kv": 110, @@ -1302,7 +1302,7 @@ "tap_min": -10, "tap_max": 10, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "fuse": {} diff --git a/pandapower/networks/power_system_test_case_jsons/case1354pegase.json b/pandapower/networks/power_system_test_case_jsons/case1354pegase.json index 3b9339ea7..b679c7f9d 100644 --- a/pandapower/networks/power_system_test_case_jsons/case1354pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case1354pegase.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,7 +363,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -919,7 +919,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -937,7 +937,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -955,7 +955,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -973,7 +973,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -991,7 +991,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1009,7 +1009,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1027,7 +1027,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1045,7 +1045,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1063,7 +1063,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1081,7 +1081,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1099,7 +1099,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1117,7 +1117,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1135,7 +1135,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1153,7 +1153,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1171,7 +1171,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1189,7 +1189,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1207,7 +1207,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1225,7 +1225,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1243,7 +1243,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1261,7 +1261,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1288,7 +1288,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1313,7 +1313,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case14.json b/pandapower/networks/power_system_test_case_jsons/case14.json index 583a943ad..946d9ac19 100644 --- a/pandapower/networks/power_system_test_case_jsons/case14.json +++ b/pandapower/networks/power_system_test_case_jsons/case14.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,3,6,9900.0,135.0,14.0,2070.288000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,3,8,9900.0,135.0,0.208,5506.181999999999789,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.1,null,-1.0,false,1,1.0,true,100.0],[null,null,4,5,9900.0,135.0,0.208,2494.998000000000047,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.8,null,-1.0,false,1,1.0,true,100.0],[null,null,6,7,9900.0,14.0,12.0,1743.884999999999991,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,6,8,9900.0,14.0,0.208,1089.098999999999933,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,3,6,9900.0,135.0,14.0,2070.288000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,3,8,9900.0,135.0,0.208,5506.181999999999789,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.1,null,-1.0,false,1,1.0,true,100.0],[null,null,4,5,9900.0,135.0,0.208,2494.998000000000047,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.8,null,-1.0,false,1,1.0,true,100.0],[null,null,6,7,9900.0,14.0,12.0,1743.884999999999991,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,6,8,9900.0,14.0,0.208,1089.098999999999933,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,7 +362,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -918,7 +918,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -936,7 +936,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -954,7 +954,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -972,7 +972,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -990,7 +990,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1008,7 +1008,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1026,7 +1026,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1044,7 +1044,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1062,7 +1062,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1080,7 +1080,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1098,7 +1098,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1116,7 +1116,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1134,7 +1134,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1152,7 +1152,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1170,7 +1170,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1188,7 +1188,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1206,7 +1206,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1224,7 +1224,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1242,7 +1242,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1260,7 +1260,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1287,7 +1287,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1312,7 +1312,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case145.json b/pandapower/networks/power_system_test_case_jsons/case145.json index aeeab821f..7537a9199 100644 --- a/pandapower/networks/power_system_test_case_jsons/case145.json +++ b/pandapower/networks/power_system_test_case_jsons/case145.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,7 +363,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -919,7 +919,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -937,7 +937,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -955,7 +955,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -973,7 +973,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -991,7 +991,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1009,7 +1009,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1027,7 +1027,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1045,7 +1045,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1063,7 +1063,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1081,7 +1081,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1099,7 +1099,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1117,7 +1117,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1135,7 +1135,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1153,7 +1153,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1171,7 +1171,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1189,7 +1189,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1207,7 +1207,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1225,7 +1225,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1243,7 +1243,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1261,7 +1261,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1288,7 +1288,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1313,7 +1313,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case1888rte.json b/pandapower/networks/power_system_test_case_jsons/case1888rte.json index ef58fda29..09d9ba1d8 100644 --- a/pandapower/networks/power_system_test_case_jsons/case1888rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case1888rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -923,7 +923,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +941,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +959,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +977,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +995,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1013,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1031,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1049,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1067,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1085,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1103,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1121,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1139,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1157,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1175,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1193,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1211,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1229,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1247,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1265,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1292,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1317,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json b/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json index 17e8b88f9..9986230e5 100644 --- a/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json +++ b/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,23,2,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,10,8,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,11,8,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,10,9,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,2.0,null,1,false,1,1.0,true,100.0],[null,null,11,9,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,2.0,null,1,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,23,2,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,10,8,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,11,8,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,10,9,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,2.0,null,1,false,1,1.0,true,100.0],[null,null,11,9,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,2.0,null,1,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -923,7 +923,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +941,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +959,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +977,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +995,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1013,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1031,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1049,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1067,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1085,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1103,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1121,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1139,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1157,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1175,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1193,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1211,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1229,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1247,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1265,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1292,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1317,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case2848rte.json b/pandapower/networks/power_system_test_case_jsons/case2848rte.json index 7450b634f..abf7c25a9 100644 --- a/pandapower/networks/power_system_test_case_jsons/case2848rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case2848rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -923,7 +923,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +941,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +959,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +977,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +995,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1013,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1031,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1049,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1067,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1085,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1103,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1121,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1139,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1157,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1175,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1193,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1211,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1229,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1247,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1265,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1292,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1317,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case2869pegase.json b/pandapower/networks/power_system_test_case_jsons/case2869pegase.json index f8964f297..912913b90 100644 --- a/pandapower/networks/power_system_test_case_jsons/case2869pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case2869pegase.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,7 +363,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -919,7 +919,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -937,7 +937,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -955,7 +955,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -973,7 +973,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -991,7 +991,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1009,7 +1009,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1027,7 +1027,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1045,7 +1045,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1063,7 +1063,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1081,7 +1081,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1099,7 +1099,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1117,7 +1117,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1135,7 +1135,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1153,7 +1153,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1171,7 +1171,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1189,7 +1189,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1207,7 +1207,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1225,7 +1225,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1243,7 +1243,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1261,7 +1261,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1288,7 +1288,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1313,7 +1313,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case30.json b/pandapower/networks/power_system_test_case_jsons/case30.json index cf53adcdf..767a58c91 100644 --- a/pandapower/networks/power_system_test_case_jsons/case30.json +++ b/pandapower/networks/power_system_test_case_jsons/case30.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -331,7 +331,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -361,7 +361,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -917,7 +917,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -935,7 +935,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -953,7 +953,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -971,7 +971,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -989,7 +989,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1007,7 +1007,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1025,7 +1025,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1043,7 +1043,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1061,7 +1061,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1079,7 +1079,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1097,7 +1097,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1115,7 +1115,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1133,7 +1133,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1151,7 +1151,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1169,7 +1169,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1187,7 +1187,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1205,7 +1205,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1223,7 +1223,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1241,7 +1241,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1259,7 +1259,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1286,7 +1286,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1311,7 +1311,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case300.json b/pandapower/networks/power_system_test_case_jsons/case300.json index c99bfa2a7..7b3a56b16 100644 --- a/pandapower/networks/power_system_test_case_jsons/case300.json +++ b/pandapower/networks/power_system_test_case_jsons/case300.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,7 +363,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -919,7 +919,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -937,7 +937,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -955,7 +955,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -973,7 +973,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -991,7 +991,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1009,7 +1009,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1027,7 +1027,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1045,7 +1045,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1063,7 +1063,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1081,7 +1081,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1099,7 +1099,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1117,7 +1117,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1135,7 +1135,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1153,7 +1153,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1171,7 +1171,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1189,7 +1189,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1207,7 +1207,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1225,7 +1225,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1243,7 +1243,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1261,7 +1261,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1288,7 +1288,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1313,7 +1313,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case3120sp.json b/pandapower/networks/power_system_test_case_jsons/case3120sp.json index be606febe..963e00458 100644 --- a/pandapower/networks/power_system_test_case_jsons/case3120sp.json +++ b/pandapower/networks/power_system_test_case_jsons/case3120sp.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -923,7 +923,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +941,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +959,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +977,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +995,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1013,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1031,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1049,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1067,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1085,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1103,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1121,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1139,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1157,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1175,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1193,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1211,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1229,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1247,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1265,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1292,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1317,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case33bw.json b/pandapower/networks/power_system_test_case_jsons/case33bw.json index eb973ed16..3c3f663d1 100644 --- a/pandapower/networks/power_system_test_case_jsons/case33bw.json +++ b/pandapower/networks/power_system_test_case_jsons/case33bw.json @@ -295,7 +295,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -317,7 +317,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -328,7 +328,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -358,7 +358,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -911,7 +911,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -929,7 +929,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -947,7 +947,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -965,7 +965,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -983,7 +983,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1001,7 +1001,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1019,7 +1019,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1037,7 +1037,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1055,7 +1055,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1073,7 +1073,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1091,7 +1091,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1109,7 +1109,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1127,7 +1127,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1145,7 +1145,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1163,7 +1163,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1181,7 +1181,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1199,7 +1199,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1217,7 +1217,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1235,7 +1235,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1253,7 +1253,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1279,7 +1279,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1304,7 +1304,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case39.json b/pandapower/networks/power_system_test_case_jsons/case39.json index f6ed49f2b..4b4055957 100644 --- a/pandapower/networks/power_system_test_case_jsons/case39.json +++ b/pandapower/networks/power_system_test_case_jsons/case39.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,2,3,4,5,6,7,8,9],\"data\":[[null,null,1,29,900.0,345.0,345.0,16.289999999999999,0.0,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,5,30,1800.0,345.0,345.0,45.0,0.0,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,28,37,1200.0,345.0,345.0,18.744599222175971,0.96,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,9,31,900.0,345.0,345.0,18.0,0.0,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,11,10,500.0,345.0,345.0,21.76470767090613,0.8,0.0,0.0,0.0,\"hv\",0,null,null,0.6,null,1,false,1,1.0,true,100.0],[null,null,11,12,500.0,345.0,345.0,21.76470767090613,0.8,0.0,0.0,0.0,\"hv\",0,null,null,0.6,null,1,false,1,1.0,true,100.0],[null,null,18,19,900.0,345.0,345.0,12.435967996099061,0.63,0.0,0.0,0.0,\"hv\",0,null,null,6.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,18,32,900.0,345.0,345.0,12.79551874681132,0.63,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,19,33,900.0,345.0,345.0,16.220237359545639,0.81,0.0,0.0,0.0,\"hv\",0,null,null,0.89999999999999,null,1,false,1,1.0,true,100.0],[null,null,21,34,900.0,345.0,345.0,12.869999999999999,0.0,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,24,36,900.0,345.0,345.0,20.88698159141239,0.54,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,2,3,4,5,6,7,8,9],\"data\":[[null,null,1,29,900.0,345.0,345.0,16.289999999999999,0.0,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,5,30,1800.0,345.0,345.0,45.0,0.0,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,28,37,1200.0,345.0,345.0,18.744599222175971,0.96,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,9,31,900.0,345.0,345.0,18.0,0.0,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,11,10,500.0,345.0,345.0,21.76470767090613,0.8,0.0,0.0,0.0,\"hv\",0,null,null,0.6,null,1,false,1,1.0,true,100.0],[null,null,11,12,500.0,345.0,345.0,21.76470767090613,0.8,0.0,0.0,0.0,\"hv\",0,null,null,0.6,null,1,false,1,1.0,true,100.0],[null,null,18,19,900.0,345.0,345.0,12.435967996099061,0.63,0.0,0.0,0.0,\"hv\",0,null,null,6.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,18,32,900.0,345.0,345.0,12.79551874681132,0.63,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,19,33,900.0,345.0,345.0,16.220237359545639,0.81,0.0,0.0,0.0,\"hv\",0,null,null,0.89999999999999,null,1,false,1,1.0,true,100.0],[null,null,21,34,900.0,345.0,345.0,12.869999999999999,0.0,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,24,36,900.0,345.0,345.0,20.88698159141239,0.54,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,7 +362,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -918,7 +918,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -936,7 +936,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -954,7 +954,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -972,7 +972,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -990,7 +990,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1008,7 +1008,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1026,7 +1026,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1044,7 +1044,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1062,7 +1062,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1080,7 +1080,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1098,7 +1098,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1116,7 +1116,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1134,7 +1134,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1152,7 +1152,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1170,7 +1170,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1188,7 +1188,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1206,7 +1206,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1224,7 +1224,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1242,7 +1242,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1260,7 +1260,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1287,7 +1287,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1312,7 +1312,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case4gs.json b/pandapower/networks/power_system_test_case_jsons/case4gs.json index f5c178ca0..d47f2be89 100644 --- a/pandapower/networks/power_system_test_case_jsons/case4gs.json +++ b/pandapower/networks/power_system_test_case_jsons/case4gs.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -331,7 +331,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -361,7 +361,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -914,7 +914,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -932,7 +932,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -950,7 +950,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -968,7 +968,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -986,7 +986,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1004,7 +1004,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1022,7 +1022,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1040,7 +1040,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1058,7 +1058,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1076,7 +1076,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1094,7 +1094,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1112,7 +1112,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1130,7 +1130,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1148,7 +1148,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1166,7 +1166,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1184,7 +1184,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1202,7 +1202,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1220,7 +1220,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1238,7 +1238,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1256,7 +1256,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1282,7 +1282,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1307,7 +1307,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case5.json b/pandapower/networks/power_system_test_case_jsons/case5.json index 03e27d14c..33bcbd205 100644 --- a/pandapower/networks/power_system_test_case_jsons/case5.json +++ b/pandapower/networks/power_system_test_case_jsons/case5.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -336,7 +336,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -366,7 +366,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -919,7 +919,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -937,7 +937,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -955,7 +955,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -973,7 +973,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -991,7 +991,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1009,7 +1009,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1027,7 +1027,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1045,7 +1045,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1063,7 +1063,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1081,7 +1081,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1099,7 +1099,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1117,7 +1117,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1135,7 +1135,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1153,7 +1153,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1171,7 +1171,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1189,7 +1189,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1207,7 +1207,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1225,7 +1225,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1243,7 +1243,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1261,7 +1261,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1287,7 +1287,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1312,7 +1312,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case57.json b/pandapower/networks/power_system_test_case_jsons/case57.json index 70da8df16..f76585f30 100644 --- a/pandapower/networks/power_system_test_case_jsons/case57.json +++ b/pandapower/networks/power_system_test_case_jsons/case57.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,11,12,13,14,15,16,2,3,4,5,6,7,8,9],\"data\":[[null,null,17,3,9900.0,500.0,115.0,5494.50000000000091,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.0,null,-1.0,false,1,1.0,true,100.0],[null,null,17,3,9900.0,500.0,115.0,4257.0,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,45,13,9900.0,138.0,115.0,727.649999999999977,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,10.0,null,-1.0,false,1,1.0,true,100.0],[null,null,50,9,9900.0,138.0,115.0,704.879999999999996,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.99999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,48,12,9900.0,138.0,115.0,1890.900000000000091,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,10.5,null,-1.0,false,1,1.0,true,100.0],[null,null,42,10,9900.0,230.0,115.0,1514.700000000000046,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.2,null,-1.0,false,1,1.0,true,100.0],[null,null,55,39,9900.0,230.0,138.0,11830.5,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.2,null,-1.0,false,1,1.0,true,100.0],[null,null,56,38,9900.0,230.0,138.0,13414.5,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.0,null,-1.0,false,1,1.0,true,100.0],[null,null,54,8,9900.0,161.0,115.0,1192.950000000000046,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.00000000000001,null,-1.0,false,1,1.0,true,100.0],[null,null,19,20,9900.0,500.0,138.0,7689.329999999999018,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.29999999999999,null,1.0,false,1,1.0,true,100.0],[null,null,24,23,9900.0,345.0,138.0,11701.799999999999272,0.0,0.0,0.0,0.0,\"hv\",null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,24,23,9900.0,345.0,138.0,12177.0,0.0,0.0,0.0,0.0,\"hv\",null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,25,23,9900.0,161.0,138.0,468.269999999999982,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.29999999999999,null,1.0,false,1,1.0,true,100.0],[null,null,28,6,9900.0,161.0,115.0,641.519999999999982,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.3,null,-1.0,false,1,1.0,true,100.0],[null,null,31,33,9900.0,345.0,138.0,9434.700000000000728,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.5,null,-1.0,false,1,1.0,true,100.0],[null,null,40,10,9900.0,230.0,115.0,7415.100000000000364,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.5,null,-1.0,false,1,1.0,true,100.0],[null,null,44,14,9900.0,138.0,115.0,1031.579999999999927,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.5,null,-1.0,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,11,12,13,14,15,16,2,3,4,5,6,7,8,9],\"data\":[[null,null,17,3,9900.0,500.0,115.0,5494.50000000000091,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.0,null,-1.0,false,1,1.0,true,100.0],[null,null,17,3,9900.0,500.0,115.0,4257.0,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,45,13,9900.0,138.0,115.0,727.649999999999977,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,10.0,null,-1.0,false,1,1.0,true,100.0],[null,null,50,9,9900.0,138.0,115.0,704.879999999999996,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.99999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,48,12,9900.0,138.0,115.0,1890.900000000000091,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,10.5,null,-1.0,false,1,1.0,true,100.0],[null,null,42,10,9900.0,230.0,115.0,1514.700000000000046,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.2,null,-1.0,false,1,1.0,true,100.0],[null,null,55,39,9900.0,230.0,138.0,11830.5,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.2,null,-1.0,false,1,1.0,true,100.0],[null,null,56,38,9900.0,230.0,138.0,13414.5,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.0,null,-1.0,false,1,1.0,true,100.0],[null,null,54,8,9900.0,161.0,115.0,1192.950000000000046,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.00000000000001,null,-1.0,false,1,1.0,true,100.0],[null,null,19,20,9900.0,500.0,138.0,7689.329999999999018,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.29999999999999,null,1.0,false,1,1.0,true,100.0],[null,null,24,23,9900.0,345.0,138.0,11701.799999999999272,0.0,0.0,0.0,0.0,\"hv\",null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,24,23,9900.0,345.0,138.0,12177.0,0.0,0.0,0.0,0.0,\"hv\",null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,25,23,9900.0,161.0,138.0,468.269999999999982,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.29999999999999,null,1.0,false,1,1.0,true,100.0],[null,null,28,6,9900.0,161.0,115.0,641.519999999999982,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.3,null,-1.0,false,1,1.0,true,100.0],[null,null,31,33,9900.0,345.0,138.0,9434.700000000000728,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.5,null,-1.0,false,1,1.0,true,100.0],[null,null,40,10,9900.0,230.0,115.0,7415.100000000000364,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.5,null,-1.0,false,1,1.0,true,100.0],[null,null,44,14,9900.0,138.0,115.0,1031.579999999999927,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.5,null,-1.0,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,7 +362,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -918,7 +918,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -936,7 +936,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -954,7 +954,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -972,7 +972,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -990,7 +990,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1008,7 +1008,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1026,7 +1026,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1044,7 +1044,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1062,7 +1062,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1080,7 +1080,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1098,7 +1098,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1116,7 +1116,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1134,7 +1134,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1152,7 +1152,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1170,7 +1170,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1188,7 +1188,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1206,7 +1206,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1224,7 +1224,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1242,7 +1242,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1260,7 +1260,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1287,7 +1287,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1312,7 +1312,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json b/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json index 2c1edb195..91ae4acb0 100644 --- a/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json +++ b/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json @@ -293,7 +293,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -315,7 +315,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -326,7 +326,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -356,7 +356,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -792,7 +792,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 4.0, "vkr_percent": 1.2 }, @@ -810,7 +810,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 6.0, "vkr_percent": 1.44 }, @@ -828,7 +828,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 4.0, "vkr_percent": 1.325 }, @@ -846,7 +846,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 6.0, "vkr_percent": 1.425 }, @@ -864,7 +864,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 4.0, "vkr_percent": 1.0794 }, @@ -882,7 +882,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 6.0, "vkr_percent": 1.206 }, @@ -900,7 +900,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 12.0, "vkr_percent": 0.26 }, @@ -918,7 +918,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 12.2, "vkr_percent": 0.25 }, @@ -936,7 +936,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 10.04, "vkr_percent": 0.276 }, @@ -954,7 +954,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 11.2, "vkr_percent": 0.282 }, @@ -972,7 +972,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 10.04, "vkr_percent": 0.295 }, @@ -990,7 +990,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 11.2, "vkr_percent": 0.302 }, @@ -1008,7 +1008,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 10.04, "vkr_percent": 0.31 }, @@ -1026,7 +1026,7 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_percent": 11.2, "vkr_percent": 0.322 } @@ -1049,7 +1049,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1074,7 +1074,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case6470rte.json b/pandapower/networks/power_system_test_case_jsons/case6470rte.json index 3571276a7..b2fc3a7c8 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6470rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6470rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -923,7 +923,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +941,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +959,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +977,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +995,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1013,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1031,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1049,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1067,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1085,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1103,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1121,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1139,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1157,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1175,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1193,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1211,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1229,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1247,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1265,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1292,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1317,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case6495rte.json b/pandapower/networks/power_system_test_case_jsons/case6495rte.json index e6efb9e35..05cfad5f4 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6495rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6495rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -923,7 +923,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +941,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +959,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +977,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +995,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1013,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1031,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1049,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1067,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1085,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1103,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1121,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1139,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1157,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1175,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1193,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1211,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1229,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1247,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1265,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1292,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1317,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case6515rte.json b/pandapower/networks/power_system_test_case_jsons/case6515rte.json index bde1766bd..1a4b6f45d 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6515rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6515rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -923,7 +923,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +941,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +959,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +977,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +995,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1013,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1031,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1049,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1067,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1085,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1103,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1121,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1139,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1157,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1175,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1193,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1211,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1229,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1247,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1265,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1292,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1317,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case6ww.json b/pandapower/networks/power_system_test_case_jsons/case6ww.json index 9b84bbfb6..a6cf0be7f 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6ww.json +++ b/pandapower/networks/power_system_test_case_jsons/case6ww.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -331,7 +331,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -361,7 +361,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -914,7 +914,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -932,7 +932,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -950,7 +950,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -968,7 +968,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -986,7 +986,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1004,7 +1004,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1022,7 +1022,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1040,7 +1040,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1058,7 +1058,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1076,7 +1076,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1094,7 +1094,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1112,7 +1112,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1130,7 +1130,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1148,7 +1148,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1166,7 +1166,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1184,7 +1184,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1202,7 +1202,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1220,7 +1220,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1238,7 +1238,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1256,7 +1256,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1282,7 +1282,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1307,7 +1307,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case89pegase.json b/pandapower/networks/power_system_test_case_jsons/case89pegase.json index f0eb9cb11..f8fc43d32 100644 --- a/pandapower/networks/power_system_test_case_jsons/case89pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case89pegase.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,7 +363,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -919,7 +919,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -937,7 +937,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -955,7 +955,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -973,7 +973,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -991,7 +991,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1009,7 +1009,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1027,7 +1027,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1045,7 +1045,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1063,7 +1063,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1081,7 +1081,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1099,7 +1099,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1117,7 +1117,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1135,7 +1135,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1153,7 +1153,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1171,7 +1171,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1189,7 +1189,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1207,7 +1207,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1225,7 +1225,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1243,7 +1243,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1261,7 +1261,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1288,7 +1288,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1313,7 +1313,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case9.json b/pandapower/networks/power_system_test_case_jsons/case9.json index b6f6648ba..ecc5ddc3b 100644 --- a/pandapower/networks/power_system_test_case_jsons/case9.json +++ b/pandapower/networks/power_system_test_case_jsons/case9.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -331,7 +331,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -361,7 +361,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -914,7 +914,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -932,7 +932,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -950,7 +950,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -968,7 +968,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -986,7 +986,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1004,7 +1004,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1022,7 +1022,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1040,7 +1040,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1058,7 +1058,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1076,7 +1076,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1094,7 +1094,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1112,7 +1112,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1130,7 +1130,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1148,7 +1148,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1166,7 +1166,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1184,7 +1184,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1202,7 +1202,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1220,7 +1220,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1238,7 +1238,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1256,7 +1256,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1282,7 +1282,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1307,7 +1307,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case9241pegase.json b/pandapower/networks/power_system_test_case_jsons/case9241pegase.json index a1801b1c9..40765885f 100644 --- a/pandapower/networks/power_system_test_case_jsons/case9241pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case9241pegase.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,7 +363,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -919,7 +919,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -937,7 +937,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -955,7 +955,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -973,7 +973,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -991,7 +991,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 11.2 }, @@ -1009,7 +1009,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1027,7 +1027,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1045,7 +1045,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1063,7 +1063,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.2 }, @@ -1081,7 +1081,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1099,7 +1099,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 6.0 }, @@ -1117,7 +1117,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1135,7 +1135,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "vk_percent": 4.0 }, @@ -1153,7 +1153,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 18.0 }, @@ -1171,7 +1171,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1189,7 +1189,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1207,7 +1207,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 }, @@ -1225,7 +1225,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 10.04 }, @@ -1243,7 +1243,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 12.0 }, @@ -1261,7 +1261,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 9, "vk_percent": 16.2 } @@ -1288,7 +1288,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1313,7 +1313,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case_ieee30.json b/pandapower/networks/power_system_test_case_jsons/case_ieee30.json index 78539a1f7..856bc3504 100644 --- a/pandapower/networks/power_system_test_case_jsons/case_ieee30.json +++ b/pandapower/networks/power_system_test_case_jsons/case_ieee30.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4,5,6],\"data\":[[null,null,5,8,99.998999999999995,132.0,1.0,20.799792,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,5,9,99.998999999999995,132.0,33.0,55.599444000000012,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.1,null,-1.0,false,1,1.0,true,100.0],[null,null,10,8,99.998999999999995,11.0,1.0,20.799792,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,9,8,99.998999999999995,33.0,1.0,10.999890000000001,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,3,11,99.998999999999995,132.0,33.0,25.599744000000001,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.8,null,-1.0,false,1,1.0,true,100.0],[null,null,11,12,99.998999999999995,33.0,11.0,13.99986,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,27,26,99.998999999999995,132.0,33.0,39.599603999999999,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.2,null,-1.0,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4,5,6],\"data\":[[null,null,5,8,99.998999999999995,132.0,1.0,20.799792,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,5,9,99.998999999999995,132.0,33.0,55.599444000000012,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.1,null,-1.0,false,1,1.0,true,100.0],[null,null,10,8,99.998999999999995,11.0,1.0,20.799792,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,9,8,99.998999999999995,33.0,1.0,10.999890000000001,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,3,11,99.998999999999995,132.0,33.0,25.599744000000001,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.8,null,-1.0,false,1,1.0,true,100.0],[null,null,11,12,99.998999999999995,33.0,11.0,13.99986,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,27,26,99.998999999999995,132.0,33.0,39.599603999999999,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.2,null,-1.0,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,7 +362,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -915,7 +915,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -933,7 +933,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -951,7 +951,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -969,7 +969,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -987,7 +987,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1005,7 +1005,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1023,7 +1023,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1041,7 +1041,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1059,7 +1059,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1077,7 +1077,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1095,7 +1095,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1113,7 +1113,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1131,7 +1131,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1149,7 +1149,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1167,7 +1167,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1185,7 +1185,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1203,7 +1203,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1221,7 +1221,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1239,7 +1239,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1257,7 +1257,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1283,7 +1283,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1308,7 +1308,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case_illinois200.json b/pandapower/networks/power_system_test_case_jsons/case_illinois200.json index 83bfb3484..b81d388b2 100644 --- a/pandapower/networks/power_system_test_case_jsons/case_illinois200.json +++ b/pandapower/networks/power_system_test_case_jsons/case_illinois200.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -920,7 +920,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -938,7 +938,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -956,7 +956,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -974,7 +974,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -992,7 +992,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1010,7 +1010,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1028,7 +1028,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1046,7 +1046,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1064,7 +1064,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1082,7 +1082,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1100,7 +1100,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1118,7 +1118,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1136,7 +1136,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1154,7 +1154,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1172,7 +1172,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1190,7 +1190,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1208,7 +1208,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1226,7 +1226,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1244,7 +1244,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1262,7 +1262,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1288,7 +1288,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1313,7 +1313,7 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/iceland.json b/pandapower/networks/power_system_test_case_jsons/iceland.json index e73ab39e0..c2bfebe33 100644 --- a/pandapower/networks/power_system_test_case_jsons/iceland.json +++ b/pandapower/networks/power_system_test_case_jsons/iceland.json @@ -296,7 +296,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -318,7 +318,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -329,7 +329,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -359,7 +359,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -794,7 +794,7 @@ "tap_min": -2, "vkr_percent": 1.425, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -812,7 +812,7 @@ "tap_min": -2, "vkr_percent": 1.44, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -830,7 +830,7 @@ "tap_min": -2, "vkr_percent": 1.2, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -848,7 +848,7 @@ "tap_min": -9, "vkr_percent": 0.25, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 12.2, "tap_max": 9 @@ -866,7 +866,7 @@ "tap_min": -9, "vkr_percent": 0.31, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -884,7 +884,7 @@ "tap_min": -2, "vkr_percent": 1.206, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -902,7 +902,7 @@ "tap_min": -2, "vkr_percent": 1.325, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -920,7 +920,7 @@ "tap_min": -2, "vkr_percent": 1.0794, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -938,7 +938,7 @@ "tap_min": -9, "vkr_percent": 0.322, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -956,7 +956,7 @@ "tap_min": -9, "vkr_percent": 0.26, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 12.0, "tap_max": 9 @@ -973,7 +973,7 @@ "tap_neutral": 0, "tap_min": -9, "vkr_percent": 0.276, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_step_percent": 1.5, "tap_side": "hv", "vk_percent": 10.04, @@ -992,7 +992,7 @@ "tap_min": -9, "vkr_percent": 0.302, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1010,7 +1010,7 @@ "tap_min": -9, "vkr_percent": 0.282, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1028,7 +1028,7 @@ "tap_min": -9, "vkr_percent": 0.295, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -1056,7 +1056,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1081,7 +1081,7 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/std_types.py b/pandapower/std_types.py index c4eae117e..01a319d8d 100644 --- a/pandapower/std_types.py +++ b/pandapower/std_types.py @@ -67,7 +67,7 @@ def create_std_type(net, data, name, element="line", overwrite=True, check_requi "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "vk0_percent": 6, "vkr0_percent": 0.78125, "mag0_percent": 100, @@ -984,7 +984,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, "100 MVA 220/110 kV": {"i0_percent": 0.06, @@ -1002,7 +1002,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, # compare to IFT Ingenieurbüro data and Schlabbach book @@ -1022,7 +1022,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, "40 MVA 110/20 kV": {"i0_percent": 0.05, @@ -1040,7 +1040,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, "25 MVA 110/20 kV": {"i0_percent": 0.07, @@ -1058,7 +1058,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, "63 MVA 110/10 kV": {"sn_mva": 63, @@ -1076,7 +1076,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, "40 MVA 110/10 kV": {"sn_mva": 40, @@ -1094,7 +1094,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, "25 MVA 110/10 kV": {"sn_mva": 25, @@ -1112,7 +1112,7 @@ def basic_trafo_std_types(): "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, # Trafo 20/0.4 # 0.25 MVA 20/0.4 kV 0.45 Trafo Union @@ -1132,7 +1132,7 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, # 0.4 MVA 20/0.4 kV Trafo Union "0.4 MVA 20/0.4 kV": @@ -1149,7 +1149,7 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, # 0.63 MVA 20/0.4 kV Trafo Union "0.63 MVA 20/0.4 kV": @@ -1168,7 +1168,7 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, # Trafo 10/0.4: # 0.25 MVA 10/0.4 kV 0.4 Trafo Union wnr @@ -1188,7 +1188,7 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, # 0.4 MVA 10/0.4 kV Trafo Union wnr "0.4 MVA 10/0.4 kV": @@ -1207,7 +1207,7 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, # 0.63 MVA 10/0.4 kV Trafo Union wnr "0.63 MVA 10/0.4 kV": @@ -1226,7 +1226,7 @@ def basic_trafo_std_types(): "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, } return trafotypes @@ -1258,7 +1258,7 @@ def basic_trafo3w_std_types(): "tap_min": -10, "tap_max": 10, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False}, "63/25/38 MVA 110/10/10 kV": {"sn_hv_mva": 63, @@ -1283,7 +1283,7 @@ def basic_trafo3w_std_types(): "tap_min": -10, "tap_max": 10, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "trafo_characteristic_table": False} } return trafo3wtypes diff --git a/pandapower/test/api/test_create.py b/pandapower/test/api/test_create.py index 3bc6ed77e..7ecbf5289 100644 --- a/pandapower/test/api/test_create.py +++ b/pandapower/test/api/test_create.py @@ -229,19 +229,19 @@ def test_nonexistent_bus(): func() -def test_tap_phase_shifter_type_default(): - expected_default = pd.NA +def test_tap_changer_type_default(): + expected_default = "None" net = pp.create_empty_network() pp.create_bus(net, 110) pp.create_bus(net, 20) data = pp.load_std_type(net, "25 MVA 110/20 kV", "trafo") - if "tap_phase_shifter_type" in data: - del data["tap_phase_shifter_type"] + if "tap_changer_type" in data: + del data["tap_changer_type"] pp.create_std_type(net, data, "without_tap_shifter_info", "trafo") pp.create_transformer_from_parameters(net, 0, 1, 25e3, 110, 20, 0.4, 12, 20, 0.07) pp.create_transformer(net, 0, 1, "without_tap_shifter_info") - assert (net.trafo.tap_phase_shifter_type == expected_default).all() + assert (net.trafo.tap_changer_type == expected_default).all() def test_create_line_conductance(): @@ -886,7 +886,7 @@ def test_trafo_2_tap_changers(): "tap2_min": -10, "tap2_step_percent": 1, "tap2_step_degree": 0, - "tap2_phase_shifter_type": 0} + "tap2_changer_type": "Ratio"} for c in tap2_data.keys(): assert c not in net.trafo.columns @@ -914,7 +914,7 @@ def test_trafo_2_tap_changers_parameters(): "tap2_min": -10, "tap2_step_percent": 1, "tap2_step_degree": 0, - "tap2_phase_shifter_type": 0} + "tap2_changer_type": "Ratio"} pp.create_transformer_from_parameters(net, b1, b2, **std_type) @@ -940,7 +940,7 @@ def test_trafos_2_tap_changers_parameters(): "tap2_min": -10, "tap2_step_percent": 1, "tap2_step_degree": 0, - "tap2_phase_shifter_type": 0} + "tap2_changer_type": "Ratio"} std_type_p = {k: np.array([v, v]) if not isinstance(v, str) else v for k, v in std_type.items()} diff --git a/pandapower/test/contingency/test_contingency.py b/pandapower/test/contingency/test_contingency.py index e171a2961..42868c6e7 100644 --- a/pandapower/test/contingency/test_contingency.py +++ b/pandapower/test/contingency/test_contingency.py @@ -165,7 +165,7 @@ def test_unequal_trafo_hv_lv_impedances(): pp.create_transformer_from_parameters(net, 1, 2, 150, 110, 110, 0.5, 10, 15, 0.1, 150, 'hv', 0, 10, -10, 0, - 1, 5, max_loading_percent=100, tap_phase_shifter_type=2, + 1, 5, max_loading_percent=100, tap_changer_type = "Ideal", leakage_resistance_ratio_hv=0.2, leakage_reactance_ratio_hv=0.4) pp.create_lines(net, [2, 2], [3, 3], 25, "243-AL1/39-ST1A 110.0", max_loading_percent=100) @@ -238,7 +238,7 @@ def test_lightsim2grid_phase_shifters(): assert net.trafo.shift_degree.values[0] == 150 assert net.trafo.tap_pos.values[0] == 5 - assert net.trafo.tap_phase_shifter_type.values[0] == 2 + assert net.trafo.tap_changer_type.values[0] == "Ideal" assert np.array_equal(res["line"]["causes_overloading"], net.res_line.causes_overloading.values) if len(net.trafo) > 0: diff --git a/pandapower/test/control/test_tap_dependent_impedance.py b/pandapower/test/control/test_tap_dependent_impedance.py index 6c66445d0..c06a6c0ac 100644 --- a/pandapower/test/control/test_tap_dependent_impedance.py +++ b/pandapower/test/control/test_tap_dependent_impedance.py @@ -20,7 +20,7 @@ def test_tap_dependent_impedance_control(): pp.create_transformer_from_parameters(net, b1, b2, 40, 110, 21, 0.5, 12.3, 25, 0.11, 0, 'hv', 10, 20, 0, 1.8, 180, - 10, tap_phase_shifter_type=0) + 10, tap_changer_type="Ratio") characteristic_vk = Characteristic.from_points(net, ((0, 13.5), (10, 12.3), (20, 11.1))) characteristic_vkr = Characteristic.from_points(net, ((0, 0.52), (10, 0.5), (20, 0.53))) @@ -51,7 +51,7 @@ def test_tap_dependent_impedance_restore(): pp.create_transformer_from_parameters(net, b1, b2, 40, 110, 21, 0.5, 12.3, 25, 0.11, 0, 'hv', 10, 20, 0, 1.8, 180, - 10, tap_phase_shifter_type=0) + 10, tap_changer_type="Ratio") characteristic_vk = Characteristic.from_points(net, ((0, 13.5), (10, 12.3), (20, 11.1))) characteristic_vkr = Characteristic.from_points(net, ((0, 0.52), (10, 0.5), (20, 0.53))) diff --git a/pandapower/test/control/testfiles/stactrl_test.json b/pandapower/test/control/testfiles/stactrl_test.json index 2bf01fa35..1ff2bc568 100644 --- a/pandapower/test/control/testfiles/stactrl_test.json +++ b/pandapower/test/control/testfiles/stactrl_test.json @@ -314,7 +314,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0,1,2,3],\"data\":[[\"Trafo\",\"90 MVA 132\\/33 kV\",11,49,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"],[\"Trafo(1)\",\"90 MVA 132\\/33 kV\",53,63,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"],[\"Trafo(2)\",\"90 MVA 132\\/33 kV\",75,85,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"],[\"Trafo(3)\",\"90 MVA 132\\/33 kV\",94,88,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0,1,2,3],\"data\":[[\"Trafo\",\"90 MVA 132\\/33 kV\",11,49,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"],[\"Trafo(1)\",\"90 MVA 132\\/33 kV\",53,63,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"],[\"Trafo(2)\",\"90 MVA 132\\/33 kV\",75,85,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"],[\"Trafo(3)\",\"90 MVA 132\\/33 kV\",94,88,90.0,110.0,11.0,13.180000305175781,0.277640014886856,44.907001495361328,0.068000003695488,30.0,\"hv\",0,-9,6,1.669999957084656,0.0,0,false,1,1.0,true,10.0,0.0,100.0,0.0,0.899999976158142,1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -336,7 +336,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -1121,7 +1121,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1139,7 +1139,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1157,7 +1157,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1175,7 +1175,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1193,7 +1193,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1211,7 +1211,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1229,7 +1229,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1247,7 +1247,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1265,7 +1265,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1283,7 +1283,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1301,7 +1301,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1319,7 +1319,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1337,7 +1337,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1355,7 +1355,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "90 MVA 132/33 kV": { "sn_mva": 90.0, @@ -1375,7 +1375,7 @@ "tap_side": "hv", "tap_step_percent": 1.6699999570846558, "tap_step_degree": 0.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 6, "tap_min": -9, "tap_neutral": 0 diff --git a/pandapower/test/converter/case2_2_by_code.json b/pandapower/test/converter/case2_2_by_code.json index 17e8845a1..b22600d95 100644 --- a/pandapower/test/converter/case2_2_by_code.json +++ b/pandapower/test/converter/case2_2_by_code.json @@ -318,7 +318,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -1086,7 +1086,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1104,7 +1104,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1122,7 +1122,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1140,7 +1140,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1158,7 +1158,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1176,7 +1176,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1194,7 +1194,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1212,7 +1212,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1230,7 +1230,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1248,7 +1248,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1266,7 +1266,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1284,7 +1284,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1302,7 +1302,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1320,7 +1320,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { diff --git a/pandapower/test/converter/test_from_cim.py b/pandapower/test/converter/test_from_cim.py index d2936abd1..bd65f1b80 100644 --- a/pandapower/test/converter/test_from_cim.py +++ b/pandapower/test/converter/test_from_cim.py @@ -726,7 +726,7 @@ def test_fullgrid_trafo(fullgrid_v2): assert 1.250 == element_0['tap_step_percent'].item() assert math.isnan(element_0['tap_step_degree'].item()) assert -2.0 == element_0['tap_pos'].item() - assert 0 == element_0['tap_phase_shifter_type'].item() + assert 0 == element_0['tap_changer_type'].item() assert 1.0 == element_0['parallel'].item() assert 1.0 == element_0['df'].item() assert element_0['in_service'].item() @@ -766,7 +766,7 @@ def test_fullgrid_trafo(fullgrid_v2): assert math.isnan(element_1['tap_step_percent'].item()) assert math.isnan(element_1['tap_step_degree'].item()) assert math.isnan(element_1['tap_pos'].item()) - assert pd.isna(element_1['tap_phase_shifter_type'].item()) + assert pd.isna(element_1['tap_changer_type'].item()) assert 1.0 == element_1['parallel'].item() assert 1.0 == element_1['df'].item() assert element_1['in_service'].item() @@ -789,7 +789,7 @@ def test_fullgrid_trafo(fullgrid_v2): element_2 = fullgrid_v2.trafo[fullgrid_v2.trafo['origin_id'] == '_ff3a91ec-2286-a64c-a046-d62bc0163ffe'] assert 1.990 == element_2['tap_step_degree'].item() assert 'PhaseTapChangerLinear' == element_2['tapchanger_class'].item() - assert 2 == element_2['tap_phase_shifter_type'].item() + assert "Ideal" == element_2['tap_changer_type'].item() assert pd.isna(element_2['id_characteristic_table'].item()) assert not element_2['tap_dependency_table'].item() diff --git a/pandapower/test/converter/testfiles/test_line_3ph.json b/pandapower/test/converter/testfiles/test_line_3ph.json index 8f0381568..fe432e1a6 100644 --- a/pandapower/test/converter/testfiles/test_line_3ph.json +++ b/pandapower/test/converter/testfiles/test_line_3ph.json @@ -247,7 +247,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -269,7 +269,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -278,7 +278,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -308,7 +308,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -960,7 +960,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -978,7 +978,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -996,7 +996,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1014,7 +1014,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1032,7 +1032,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1050,7 +1050,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1068,7 +1068,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1086,7 +1086,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1104,7 +1104,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1122,7 +1122,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1140,7 +1140,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1158,7 +1158,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1176,7 +1176,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1194,7 +1194,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { @@ -1221,7 +1221,7 @@ "tap_min": -10, "tap_max": 10, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63/25/38 MVA 110/10/10 kV": { "sn_hv_mva": 63, @@ -1246,7 +1246,7 @@ "tap_min": -10, "tap_max": 10, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } } }, diff --git a/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json b/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json index 09206a3c7..510ed3bc6 100644 --- a/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json +++ b/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json @@ -247,7 +247,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",null,0,1,0.629999995231628,20.0,0.400000005960464,6.0,1.095238089561462,1.649999976158142,0.261914998292923,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,1.095237970352173,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",null,0,1,0.629999995231628,20.0,0.400000005960464,6.0,1.095238089561462,1.649999976158142,0.261914998292923,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,1.095237970352173,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -269,7 +269,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -287,7 +287,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -317,7 +317,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -969,7 +969,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -987,7 +987,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1005,7 +1005,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1023,7 +1023,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1041,7 +1041,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1059,7 +1059,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1077,7 +1077,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1095,7 +1095,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1113,7 +1113,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1131,7 +1131,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV Dyn ASEA": { "sn_mva": 0.6299999952316284, @@ -1151,7 +1151,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1172,7 +1172,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1190,7 +1190,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1208,7 +1208,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1226,7 +1226,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { @@ -1253,7 +1253,7 @@ "tap_min": -10, "tap_max": 10, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63/25/38 MVA 110/20/10 kV": { "sn_hv_mva": 63, @@ -1278,7 +1278,7 @@ "tap_min": -10, "tap_max": 10, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } } }, diff --git a/pandapower/test/converter/testfiles/test_trafo_3ph.json b/pandapower/test/converter/testfiles/test_trafo_3ph.json index 27c34e419..d7e6a45d1 100644 --- a/pandapower/test/converter/testfiles/test_trafo_3ph.json +++ b/pandapower/test/converter/testfiles/test_trafo_3ph.json @@ -239,7 +239,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",null,0,1,0.629999995231628,20.0,0.400000005960464,6.0,1.095238089561462,1.649999976158142,0.261914998292923,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,1.095237970352173,100.0,0.0,0.899999976158142,\"Yzn\",1.0,\"\",\"\"]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",null,0,1,0.629999995231628,20.0,0.400000005960464,6.0,1.095238089561462,1.649999976158142,0.261914998292923,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,1.095237970352173,100.0,0.0,0.899999976158142,\"Yzn\",1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -261,7 +261,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -279,7 +279,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -309,7 +309,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -948,7 +948,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -966,7 +966,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -984,7 +984,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV Yzn ASEA": { "sn_mva": 0.6299999952316284, @@ -1004,7 +1004,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1025,7 +1025,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1043,7 +1043,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1061,7 +1061,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1079,7 +1079,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1097,7 +1097,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1115,7 +1115,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1133,7 +1133,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1151,7 +1151,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1169,7 +1169,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1187,7 +1187,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1205,7 +1205,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { @@ -1232,7 +1232,7 @@ "tap_min": -10, "tap_max": 10, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63/25/38 MVA 110/20/10 kV": { "sn_hv_mva": 63, @@ -1257,7 +1257,7 @@ "tap_min": -10, "tap_max": 10, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } } }, diff --git a/pandapower/test/converter/testfiles/trafo_tap_model.json b/pandapower/test/converter/testfiles/trafo_tap_model.json index f9b0c4e0d..296444c0f 100644 --- a/pandapower/test/converter/testfiles/trafo_tap_model.json +++ b/pandapower/test/converter/testfiles/trafo_tap_model.json @@ -305,7 +305,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"tap2_phase_shifter_type\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"tap2_neutral\",\"tap2_max\",\"tap2_min\",\"tap2_side\",\"tap2_step_percent\",\"tap2_step_degree\",\"tap2_pos\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20],\"data\":[[\"2-Winding Transformer(3)\",\"2-Winding Transformer Type\",94,81,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,10.0,0.0,0,1,1.0,true,0,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",2.0,30.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer\",\"2-Winding Transformer 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"{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"tap2_phase_shifter_type\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"tap2_neutral\",\"tap2_max\",\"tap2_min\",\"tap2_side\",\"tap2_step_percent\",\"tap2_step_degree\",\"tap2_pos\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20],\"data\":[[\"2-Winding Transformer(3)\",\"2-Winding Transformer Type\",94,81,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,10.0,0.0,0,1,1.0,true,0,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",2.0,30.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer\",\"2-Winding Transformer 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LV-d\",367,341,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,0.0,5.0,5.0,2,1,1.0,true,2,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",0.0,-10.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer(12)\",\"2-W HV-d LV-d\",354,315,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,0.0,5.0,0.0,2,1,1.0,true,2,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",0.0,-10.0,-5.0,1.0,\"\",\"\"],[\"2-Winding Transformer(15)\",\"2-W HV-d LV-d\",380,406,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,0.0,5.0,3.0,2,1,1.0,true,2,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",0.0,-10.0,-2.0,1.0,\"\",\"\"],[\"2-Winding Transformer(19)\",\"2-W HV-V HV-V\",471,484,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,0.0,0.0,0,1,1.0,true,1,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"hv\",2.0,90.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer(16)\",\"2-W HV-V HV-V\",419,447,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,0.0,5.0,0,1,1.0,true,1,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"hv\",2.0,90.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer(18)\",\"2-W HV-V HV-V\",510,458,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,0.0,0.0,0,1,1.0,true,1,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"hv\",2.0,90.0,-5.0,1.0,\"\",\"\"],[\"2-Winding Transformer(17)\",\"2-W HV-V HV-V\",497,432,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,0.0,3.0,0,1,1.0,true,1,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"hv\",2.0,90.0,-2.0,1.0,\"\",\"\"],[\"2-Winding Transformer(20)\",\"2-W no tap changer\",562,549,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,null,null,null,null,null,null,null,null,1,1.0,true,null,3.0,0.0,100.0,0.0,0.899999976158142,null,null,null,null,null,null,null,1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -327,7 +327,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -354,7 +354,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -384,7 +384,7 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -1081,7 +1081,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1099,7 +1099,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "2-W HV-V LV-d": { "sn_mva": 100.0, @@ -1119,7 +1119,7 @@ "tap_side": "hv", "tap_step_percent": 2.0, "tap_step_degree": 10.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 10, "tap_min": -10, "tap_neutral": 0, @@ -1165,7 +1165,7 @@ "tap_side": "hv", "tap_step_percent": 0, "tap_step_degree": 5.0, - "tap_phase_shifter_type": 2, + "tap_changer_type": "Ideal", "tap_max": 10, "tap_min": -10, "tap_neutral": 0, @@ -1195,7 +1195,7 @@ "tap_side": "hv", "tap_step_percent": 2.0, "tap_step_degree": 0.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 10, "tap_min": -10, "tap_neutral": 0, @@ -1223,7 +1223,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1241,7 +1241,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1259,7 +1259,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "2-W HV-d LV-V": { "sn_mva": 100.0, @@ -1279,7 +1279,7 @@ "tap_side": "hv", "tap_step_percent": 0, "tap_step_degree": 5.0, - "tap_phase_shifter_type": 2, + "tap_changer_type": "Ideal", "tap_max": 10, "tap_min": -10, "tap_neutral": 0, @@ -1307,7 +1307,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1325,7 +1325,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1343,7 +1343,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1361,7 +1361,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1379,7 +1379,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1397,7 +1397,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "2-Winding Transformer Type": { "sn_mva": 100.0, @@ -1417,7 +1417,7 @@ "tap_side": "hv", "tap_step_percent": 2.0, "tap_step_degree": 10.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 10, "tap_min": -10, "tap_neutral": 0, @@ -1445,7 +1445,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1463,7 +1463,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1481,7 +1481,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { diff --git a/pandapower/test/estimation/3bus_wls.json b/pandapower/test/estimation/3bus_wls.json index 7fe04d3d1..ec128a354 100644 --- a/pandapower/test/estimation/3bus_wls.json +++ b/pandapower/test/estimation/3bus_wls.json @@ -157,7 +157,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "dtype": { "name": "object", "std_type": "object", @@ -178,7 +178,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" diff --git a/pandapower/test/estimation/test_wls_estimation.py b/pandapower/test/estimation/test_wls_estimation.py index 3209b2812..23416c059 100644 --- a/pandapower/test/estimation/test_wls_estimation.py +++ b/pandapower/test/estimation/test_wls_estimation.py @@ -212,7 +212,7 @@ def test_3bus_with_transformer(): pp.create_std_type(net, {"sn_mva": 25, "vn_hv_kv": 110, "vn_lv_kv": 10, "vk_percent": 10.04, "vkr_percent": 0.276, "pfe_kw": 28.51, "i0_percent": 0.073, "shift_degree": 150, "tap_side": "hv", "tap_neutral": 0, "tap_min": -9, "tap_max": 9, "tap_step_degree": 0, - "tap_step_percent": 1.5, "tap_phase_shifter_type": 0}, + "tap_step_percent": 1.5, "tap_changer_type": "Ratio"}, "25 MVA 110/10 kV v1.4.3 and older", element="trafo") pp.create_transformer(net, 3, 0, std_type="25 MVA 110/10 kV v1.4.3 and older") @@ -498,7 +498,7 @@ def test_init_slack_with_multiple_transformers(angles=True): pp.create_std_type(net, {"sn_mva": 63, "vn_hv_kv": 110, "vn_lv_kv": 10, "vk_percent": 10.04, "vkr_percent": 0.31, "pfe_kw": 31.51, "i0_percent": 0.078, "shift_degree": 150, "tap_side": "hv", "tap_neutral": 0, "tap_min": -9, "tap_max": 9, "tap_step_degree": 0, - "tap_step_percent": 1.5, "tap_phase_shifter_type": 0}, + "tap_step_percent": 1.5, "tap_changer_type": "Ratio"}, "63 MVA 110/10 kV v1.4.3 and older", element="trafo") pp.create_transformer(net, 3, 7, std_type="63 MVA 110/10 kV v1.4.3 and older", in_service=False) diff --git a/pandapower/test/helper_functions.py b/pandapower/test/helper_functions.py index bd6d0e350..be5397735 100644 --- a/pandapower/test/helper_functions.py +++ b/pandapower/test/helper_functions.py @@ -47,7 +47,7 @@ def create_test_network(): tap_pos=0, tap_side="hv", tap_min=-2, tap_step_percent=2.5, i0_percent=0.68751, sn_mva=0.016, pfe_kw=0.11, name=None, - in_service=True, index=None, tap_phase_shifter_type=0) + in_service=True, index=None, tap_changer_type="Ratio") # 0.016 MVA 10/0.4 kV ET 16/23 SGB pp.create_line_from_parameters(net, b2, b3, 1, name="line1", r_ohm_per_km=0.2067, diff --git a/pandapower/test/loadflow/result_test_network_generator.py b/pandapower/test/loadflow/result_test_network_generator.py index 2e8466921..368238261 100644 --- a/pandapower/test/loadflow/result_test_network_generator.py +++ b/pandapower/test/loadflow/result_test_network_generator.py @@ -175,12 +175,12 @@ def add_test_trafo(net): pp.create_transformer_from_parameters(net, b2, b3, vk_percent=5., vkr_percent=2., i0_percent=.4, pfe_kw=2., sn_mva=0.4, vn_hv_kv=22, vn_lv_kv=0.42, tap_max=10, tap_neutral=5, tap_min=0, - tap_step_percent=1.25, tap_pos=3, tap_phase_shifter_type=0, shift_degree=150, + tap_step_percent=1.25, tap_pos=3, tap_changer_type="Ratio", shift_degree=150, tap_side="hv", parallel=2) t2 = pp.create_transformer_from_parameters(net, b2, b3, vk_percent=5., vkr_percent=2., i0_percent=.4, pfe_kw=2, sn_mva=0.4, vn_hv_kv=22, vn_lv_kv=0.42, tap_max=10, tap_neutral=5, tap_min=0, - tap_step_percent=1.25, tap_pos=3, tap_phase_shifter_type=0, tap_side="hv", + tap_step_percent=1.25, tap_pos=3, tap_changer_type="Ratio", tap_side="hv", shift_degree=150, index=pp.get_free_id(net.trafo) + 1) pp.create_switch(net, b3, t2, et="t", closed=False) pp.create_transformer_from_parameters(net, b2, b3, vk_percent=5., vkr_percent=2., @@ -325,7 +325,7 @@ def add_test_trafo3w(net): vkr_mv_percent=.02, vk_lv_percent=.25, vkr_lv_percent=.01, pfe_kw=0.5, i0_percent=0.1, name="test", index=pp.get_free_id(net.trafo3w) + 1, - tap_side="hv", tap_pos=2, tap_phase_shifter_type=0, tap_step_percent=1.25, + tap_side="hv", tap_pos=2, tap_changer_type="Ratio", tap_step_percent=1.25, tap_min=-5, tap_neutral=0, tap_max=5) # adding out of service 3w trafo should not change results pp.create_transformer3w_from_parameters(net, hv_bus=b2, mv_bus=b3, lv_bus=b4, vn_hv_kv=20, diff --git a/pandapower/test/loadflow/runpp_3ph Validation.json b/pandapower/test/loadflow/runpp_3ph Validation.json index 977af8d6f..44059a3ea 100644 --- a/pandapower/test/loadflow/runpp_3ph Validation.json +++ b/pandapower/test/loadflow/runpp_3ph Validation.json @@ -253,7 +253,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0,1],\"data\":[[\"Trafo 2\",null,0,6,1.600000023841858,10.0,0.400000005960464,6.0,0.78125,2.700000047683716,0.168750002980232,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,0.78125,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"],[\"Trafo 1\",null,1,2,1.600000023841858,10.0,0.400000005960464,6.0,0.78125,2.700000047683716,0.168750002980232,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,0.78125,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0,1],\"data\":[[\"Trafo 2\",null,0,6,1.600000023841858,10.0,0.400000005960464,6.0,0.78125,2.700000047683716,0.168750002980232,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,0.78125,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"],[\"Trafo 1\",null,1,2,1.600000023841858,10.0,0.400000005960464,6.0,0.78125,2.700000047683716,0.168750002980232,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,0.78125,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -275,7 +275,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -990,7 +990,7 @@ "tap_side": "lv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1011,7 +1011,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1029,7 +1029,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1047,7 +1047,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1065,7 +1065,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1083,7 +1083,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1101,7 +1101,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1119,7 +1119,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1137,7 +1137,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1155,7 +1155,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1173,7 +1173,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1191,7 +1191,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1209,7 +1209,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "2-Wicklungstransformatortyp": { "sn_mva": 1.600000023841858, @@ -1229,7 +1229,7 @@ "tap_side": "lv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1250,7 +1250,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1268,7 +1268,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { @@ -1295,7 +1295,7 @@ "tap_min": -10, "tap_max": 10, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63/25/38 MVA 110/10/10 kV": { "sn_hv_mva": 63, @@ -1320,7 +1320,7 @@ "tap_min": -10, "tap_max": 10, "tap_step_percent": 1.2, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } } }, diff --git a/pandapower/test/loadflow/test_recycle.py b/pandapower/test/loadflow/test_recycle.py index cd2131896..6c05617f5 100644 --- a/pandapower/test/loadflow/test_recycle.py +++ b/pandapower/test/loadflow/test_recycle.py @@ -198,7 +198,7 @@ def test_recycle_dc_trafo_ideal(recycle_net): 12, 10, 0.1, 0, tap_side='hv', tap_neutral=0, tap_max=10, tap_min=-10, tap_step_percent=0, tap_step_degree=30, tap_pos=0, - tap_phase_shifter_type=2) + tap_changer_type = "Ideal") net2 = net.deepcopy() pl = 1.2 ql = 0. diff --git a/pandapower/test/loadflow/test_results.py b/pandapower/test/loadflow/test_results.py index 78f17c594..da7e1005e 100644 --- a/pandapower/test/loadflow/test_results.py +++ b/pandapower/test/loadflow/test_results.py @@ -28,7 +28,7 @@ def add_trafo_connection(net, hv_bus, trafotype="2W"): vn_hv_kv=20., vn_mv_kv=0.9, vn_lv_kv=0.45, sn_hv_mva=0.6, sn_mv_mva=0.5, sn_lv_mva=0.4, vk_hv_percent=1., vk_mv_percent=1., vk_lv_percent=1., vkr_hv_percent=0.3, vkr_mv_percent=0.3, vkr_lv_percent=0.3, - pfe_kw=0.2, i0_percent=0.3, tap_neutral=0., tap_phase_shifter_type=0, + pfe_kw=0.2, i0_percent=0.3, tap_neutral=0., tap_changer_type="Ratio", tap_pos=2, tap_step_percent=1., tap_min=-2, tap_max=2) else: pp.create_transformer(net, hv_bus=hv_bus, lv_bus=cb, std_type="0.25 MVA 20/0.4 kV", tap_pos=2) @@ -247,10 +247,10 @@ def test_trafo_2_taps(v_tol=1e-6, i_tol=1e-6, s_tol=1e-2, l_tol=1e-3, va_tol=1e- pp.create_transformer_from_parameters(net, 0, 1, 100, 110, 20, 0.5, 12, 14, 0.5, tap_side="hv", tap_neutral=0, tap_max=10, tap_min=-10, tap_step_percent=2, tap_step_degree=0, - tap_pos=0, tap_phase_shifter_type=0, + tap_pos=0, tap_changer_type="Ratio", tap2_side="hv", tap2_neutral=0, tap2_max=10, tap2_min=-10, tap2_step_percent=2, tap2_step_degree=0, - tap2_pos=0, tap2_phase_shifter_type=0) + tap2_pos=0, tap2_changer_type="Ratio") pp.create_load(net, 1, 10) @@ -888,7 +888,7 @@ def test_trafo_unequal_r_x_hv_lv(): pp.create_transformer_from_parameters(net, 0, 1, 150, 120, 19, 1, 3, 20, 0.12, tap_side="hv", tap_neutral=0, tap_max=2, tap_min=-2, tap_step_percent=5, tap_step_degree=30, - tap_pos=-2, tap_phase_shifter_type=0, leakage_resistance_ratio_hv=0.6, leakage_reactance_ratio_hv=0.2) + tap_pos=-2, tap_changer_type="Ratio", leakage_resistance_ratio_hv=0.6, leakage_reactance_ratio_hv=0.2) pp.create_load(net, 1, 100, 20) runpp_with_consistency_checks(net) diff --git a/pandapower/test/loadflow/test_runpp.py b/pandapower/test/loadflow/test_runpp.py index 0ce7d9948..7e2eaf06d 100644 --- a/pandapower/test/loadflow/test_runpp.py +++ b/pandapower/test/loadflow/test_runpp.py @@ -1329,7 +1329,7 @@ def test_tap_dependent_impedance(): vkr_hv_percent=0.3, vkr_mv_percent=0.3, vkr_lv_percent=0.3, pfe_kw=0.2, i0_percent=0.3, tap_neutral=0., tap_side='hv', tap_pos=0, tap_step_percent=0., tap_min=-2, tap_max=2, - tap_phase_shifter_type=0) + tap_changer_type="Ratio") net_backup = net.deepcopy() diff --git a/pandapower/test/loadflow/test_runpp_3ph.py b/pandapower/test/loadflow/test_runpp_3ph.py index 0c9720aa3..45ce8a162 100644 --- a/pandapower/test/loadflow/test_runpp_3ph.py +++ b/pandapower/test/loadflow/test_runpp_3ph.py @@ -411,7 +411,7 @@ def make_nw(net, bushv, tap_ps, case, vector_group): tap_min=-2, tap_max=2, tap_step_degree=0, tap_step_percent=2.5, - tap_phase_shifter_type=0, + tap_changer_type="Ratio", vk0_percent=6, vkr0_percent=0.78125, mag0_percent=100, mag0_rx=0., si0_hv_partial=0.9, vector_group=vector_group, diff --git a/pandapower/test/loadflow/test_scenarios.py b/pandapower/test/loadflow/test_scenarios.py index c6f44c8f5..be581305e 100644 --- a/pandapower/test/loadflow/test_scenarios.py +++ b/pandapower/test/loadflow/test_scenarios.py @@ -23,7 +23,7 @@ def test_2gen_1ext_grid(): net.shunt.q_mvar *= -1 pp.create_gen(net, 2, p_mw=0.100) net.trafo.shift_degree = 150 - net.trafo.tap_phase_shifter_type = 0 + net.trafo.tap_changer_type = "Ratio" pp.runpp(net, init='dc', calculate_voltage_angles=True) assert np.allclose(net.res_gen.p_mw.values, [0.100, 0.100]) @@ -48,7 +48,7 @@ def test_0gen_2ext_grid(): pp.create_ext_grid(net, 1) net.gen = net.gen.drop(0) net.trafo.shift_degree = 150 - net.trafo.tap_phase_shifter_type = 0 + net.trafo.tap_changer_type = "Ratio" net.ext_grid.at[1, "in_service"] = False pp.create_ext_grid(net, 3) @@ -75,7 +75,7 @@ def test_0gen_2ext_grid_decoupled(): net.ext_grid.at[2, "in_service"] = False auxbus = pp.create_bus(net, name="bus1", vn_kv=10.) net.trafo.shift_degree = 150 - net.trafo.tap_phase_shifter_type = 0 + net.trafo.tap_changer_type = "Ratio" pp.create_std_type(net, {"type": "cs", "r_ohm_per_km": 0.876, "q_mm2": 35.0, "endtmp_deg": 160.0, "c_nf_per_km": 260.0, "max_i_ka": 0.123, "x_ohm_per_km": 0.1159876}, @@ -259,7 +259,7 @@ def test_transformer_phase_shift_complex(): pfe_kw=0, i0_percent=0.1, shift_degree=30, tap_side=side, tap_neutral=0, tap_max=2, tap_min=-2, tap_step_percent=2, tap_step_degree=10, tap_pos=0, - tap_phase_shifter_type=0) + tap_changer_type="Ratio") pp.runpp(net, init="dc", calculate_voltage_angles=True) assert np.isclose(net.res_bus.vm_pu.at[b2], test_ref[0], rtol=1e-4) assert np.isclose(net.res_bus.va_degree.at[b2], test_ref[1], rtol=1e-4) @@ -305,7 +305,7 @@ def test_transformer3w_phase_shift(): shift_lv_degree=60, tap_side=side, tap_step_percent=2, tap_step_degree=10, tap_pos=0, tap_neutral=0, tap_min=-2, - tap_max=2, tap_phase_shifter_type=0) + tap_max=2, tap_changer_type="Ratio") pp.runpp(net, init="dc", calculate_voltage_angles=True) assert np.isclose(net.res_bus.vm_pu.at[b2], test_ref[0][0], rtol=1e-4) assert np.isclose(net.res_bus.va_degree.at[b2], test_ref[0][1], rtol=1e-4) @@ -424,7 +424,7 @@ def network_with_trafo3ws(): vkr_lv_percent=.01, pfe_kw=.5, i0_percent=0.1, name="test", index=pp.get_free_id(net.trafo3w) + 1, tap_side="hv", tap_pos=2, tap_step_percent=1.25, - tap_min=-5, tap_neutral=0, tap_max=5, tap_phase_shifter_type=0) + tap_min=-5, tap_neutral=0, tap_max=5, tap_changer_type="Ratio") return net, t3, hv, mv, lv diff --git a/pandapower/test/opf/test_basic.py b/pandapower/test/opf/test_basic.py index eccac3620..432ee1139 100644 --- a/pandapower/test/opf/test_basic.py +++ b/pandapower/test/opf/test_basic.py @@ -253,7 +253,7 @@ def test_opf_gen_voltage(): vn_hv_kv=10.0, vkr_percent=2.8125, tap_pos=0, tap_side="hv", tap_min=-2, tap_step_percent=2.5, i0_percent=0.68751, - sn_mva=0.016, pfe_kw=0.11, name=None, tap_phase_shifter_type=0, + sn_mva=0.016, pfe_kw=0.11, name=None, tap_changer_type="Ratio", in_service=True, index=None, max_loading_percent=200) pp.create_gen(net, 3, p_mw=0.01, controllable=True, min_p_mw=0, max_p_mw=0.025, max_q_mvar=0.5, min_q_mvar=-0.5) @@ -299,7 +299,7 @@ def test_opf_sgen_voltage(): vn_hv_kv=10.0, vkr_percent=2.8125, tap_pos=0, tap_side="hv", tap_min=-2, tap_step_percent=2.5, i0_percent=0.68751, - sn_mva=0.016, pfe_kw=0.11, name=None, tap_phase_shifter_type=0, + sn_mva=0.016, pfe_kw=0.11, name=None, tap_changer_type="Ratio", in_service=True, index=None, max_loading_percent=1000000) pp.create_sgen(net, 3, p_mw=0.01, controllable=True, min_p_mw=-0.005, max_p_mw=0.015, max_q_mvar=0.025, min_q_mvar=-0.025) @@ -346,7 +346,7 @@ def test_opf_gen_loading(): vn_hv_kv=10.0, vkr_percent=2.8125, tap_pos=0, tap_side="hv", tap_min=-2, tap_step_percent=2.5, i0_percent=0.68751, - sn_mva=0.016, pfe_kw=0.11, name=None, tap_phase_shifter_type=0, + sn_mva=0.016, pfe_kw=0.11, name=None, tap_changer_type="Ratio", in_service=True, index=None, max_loading_percent=145) pp.create_gen(net, 3, p_mw=0.01, controllable=True, min_p_mw=0.005, max_p_mw=0.015, max_q_mvar=0.05, min_q_mvar=-0.05) @@ -399,7 +399,7 @@ def test_opf_sgen_loading(): vkr_percent=2.8125, tap_pos=0, tap_side="hv", tap_min=-2, tap_step_percent=2.5, i0_percent=0.68751, sn_mva=0.016, pfe_kw=0.11, name=None, in_service=True, index=None, - max_loading_percent=max_trafo_loading, tap_phase_shifter_type=0) + max_loading_percent=max_trafo_loading, tap_changer_type="Ratio") pp.create_sgen(net, 3, p_mw=0.01, controllable=True, min_p_mw=0.005, max_p_mw=.015, max_q_mvar=0.025, min_q_mvar=-0.025) pp.create_poly_cost(net, 0, "sgen", cp1_eur_per_mw=-10) @@ -569,7 +569,7 @@ def test_opf_varying_max_line_loading(): vkr_percent=2.8125, tap_pos=0, tap_side="hv", tap_min=-2, tap_step_percent=2.5, i0_percent=0.68751, sn_mva=0.016, pfe_kw=0.11, name=None, in_service=True, index=None, - max_loading_percent=max_trafo_loading, tap_phase_shifter_type=0) + max_loading_percent=max_trafo_loading, tap_changer_type="Ratio") pp.create_sgen(net, 3, p_mw=0.1, controllable=True, min_p_mw=0.005, max_p_mw=0.15, max_q_mvar=0.025, min_q_mvar=-0.025) diff --git a/pandapower/test/shortcircuit/sc_test_meshed_grid.json b/pandapower/test/shortcircuit/sc_test_meshed_grid.json index 14b20dad8..13eb57e26 100644 --- a/pandapower/test/shortcircuit/sc_test_meshed_grid.json +++ b/pandapower/test/shortcircuit/sc_test_meshed_grid.json @@ -165,7 +165,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"2-Wicklungstransformator(2)\",\"0.63 MVA 10\\/0.4 kV Yyn0 6 ASEA\",0,1,0.629999995231628,10.0,0.400000005960464,6.0,1.047619104385376,1.399999976158142,0.22223199903965,0.0,\"hv\",0,-2,2,2.5,null,0,false,1,1.0,true],[\"2-Wicklungstransformator\",\"0.4 MVA 10\\/0.4 kV Yyn6 4 ASEA\",3,4,0.400000005960464,10.0,0.400000005960464,4.0,1.075000047683716,1.149999976158142,0.287510007619858,180.0,\"hv\",0,-2,2,2.5,null,0,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1],\"data\":[[\"2-Wicklungstransformator(2)\",\"0.63 MVA 10\\/0.4 kV Yyn0 6 ASEA\",0,1,0.629999995231628,10.0,0.400000005960464,6.0,1.047619104385376,1.399999976158142,0.22223199903965,0.0,\"hv\",0,-2,2,2.5,null,0,false,1,1.0,true],[\"2-Wicklungstransformator\",\"0.4 MVA 10\\/0.4 kV Yyn6 4 ASEA\",3,4,0.400000005960464,10.0,0.400000005960464,4.0,1.075000047683716,1.149999976158142,0.287510007619858,180.0,\"hv\",0,-2,2,2.5,null,0,false,1,1.0,true]]}", "dtype": { "name": "object", "std_type": "object", @@ -186,7 +186,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" diff --git a/pandapower/test/shortcircuit/test_1ph.py b/pandapower/test/shortcircuit/test_1ph.py index 9a0846ed3..aac8fa654 100644 --- a/pandapower/test/shortcircuit/test_1ph.py +++ b/pandapower/test/shortcircuit/test_1ph.py @@ -44,7 +44,7 @@ def add_network(net, vector_group): "sn_mva": 25, "vn_lv_kv": 20.0, "vn_hv_kv": 110.0, "vk_percent": 11.2, "shift_degree": 150, "vector_group": vector_group, "tap_side": "hv", "tap_neutral": 0, "tap_min": -9, "tap_max": 9, "tap_step_degree": 0, - "tap_step_percent": 1.5, "tap_phase_shifter_type": 0, "vk0_percent": 5, + "tap_step_percent": 1.5, "tap_changer_type": "Ratio", "vk0_percent": 5, "vkr0_percent": 0.4, "mag0_percent": 10, "mag0_rx": 0.4, "si0_hv_partial": 0.9} pp.create_std_type(net, transformer_type, vector_group, "trafo") @@ -327,7 +327,7 @@ def vde_232(): si0_hv_partial=0.9, pt_percent=12, oltc=True, power_station_unit=True, - xn_ohm=22, tap_phase_shifter_type=0) + xn_ohm=22, tap_changer_type="Ratio") pp.create_gen(net, 1, 150, 1, 150, vn_kv=21, xdss_pu=0.14, rdss_ohm=0.002, cos_phi=0.85, power_station_trafo=0, pg_percent=5) diff --git a/pandapower/test/shortcircuit/test_all_currents.py b/pandapower/test/shortcircuit/test_all_currents.py index 8aaf8f546..9eb88f7ff 100644 --- a/pandapower/test/shortcircuit/test_all_currents.py +++ b/pandapower/test/shortcircuit/test_all_currents.py @@ -81,7 +81,7 @@ def net_transformer_simple(): vkr_percent=0.5, pfe_kw=14, shift_degree=0.0, tap_side="hv", tap_neutral=0, tap_min=-2, tap_max=2, tap_pos=0, tap_step_percent=2.5, parallel=1, sn_mva=0.4, i0_percent=0.5, - tap_phase_shifter_type=0) + tap_changer_type="Ratio") return net @@ -118,7 +118,7 @@ def net_transformer_simple_3(): pp.create_transformer_from_parameters(net, 4, 5, sn_mva=0.4, vn_hv_kv=10., vn_lv_kv=0.4, vk_percent=6., vkr_percent=0.5, pfe_kw=14, i0_percent=0.5, shift_degree=0.0, tap_side="hv", tap_neutral=0, tap_min=-2, tap_max=2, tap_pos=0, - tap_step_percent=2.5, parallel=1, tap_phase_shifter_type=0) + tap_step_percent=2.5, parallel=1, tap_changer_type="Ratio") pp.create_lines_from_parameters(net, [0, 3, 5], [1, 4, 6], 1, 0.099, 0.156, 400, 0.457) return net @@ -132,7 +132,7 @@ def net_transformer_simple_4(): pp.create_transformer_from_parameters(net, 7, 8, sn_mva=0.4, vn_hv_kv=10., vn_lv_kv=0.4, vk_percent=6., vkr_percent=0.5, pfe_kw=14, i0_percent=0.5, shift_degree=0.0, tap_side="hv", tap_neutral=0, tap_min=-2, tap_max=2, tap_pos=0, - tap_step_percent=2.5, parallel=1, tap_phase_shifter_type=0) + tap_step_percent=2.5, parallel=1, tap_changer_type="Ratio") pp.create_switch(net, 6, 4, "l", closed=True) pp.create_sgen(net, 3, 0, 0, 20, k=1.2, kappa=1) pp.create_load(net, 6, 0.1) @@ -148,7 +148,7 @@ def net_transformer(): pp.create_ext_grid(net, b1a, s_sc_max_mva=100., s_sc_min_mva=40., rx_min=0.1, rx_max=0.1) pp.create_switch(net, b1a, b1b, et="b") pp.create_transformer_from_parameters(net, b1b, b2, vn_hv_kv=11., vn_lv_kv=0.42, vk_percent=6., - vkr_percent=0.5, pfe_kw=14, shift_degree=0.0, tap_phase_shifter_type=0, + vkr_percent=0.5, pfe_kw=14, shift_degree=0.0, tap_changer_type="Ratio", tap_side="hv", tap_neutral=0, tap_min=-2, tap_max=2, tap_pos=2, tap_step_percent=2.5, parallel=2, sn_mva=0.4, i0_percent=0.5) pp.create_shunt(net, b2, q_mvar=0.050, p_mw=0.0500) # adding a shunt shouldn't change the result diff --git a/pandapower/test/shortcircuit/test_iec60909_4.py b/pandapower/test/shortcircuit/test_iec60909_4.py index 4f69fff75..367b6ecc7 100644 --- a/pandapower/test/shortcircuit/test_iec60909_4.py +++ b/pandapower/test/shortcircuit/test_iec60909_4.py @@ -76,7 +76,7 @@ def iec_60909_4(): vk0_hv_percent=44.1, vkr0_hv_percent=0.26, vk0_mv_percent=6.299627, vkr0_mv_percent=0.03714286, vk0_lv_percent=6.299627, vkr0_lv_percent=0.03714286, - vector_group="YNyd", tap_phase_shifter_type=0, + vector_group="YNyd", tap_changer_type="Ratio", tap_max=10, tap_min=-10, tap_pos=0, tap_neutral=0, tap_side="hv", tap_step_percent=0.1) # vk0 = sqrt(vkr0^2 + vki0^2) = sqrt(vkr^2 + (2.1 * vki)^2) = sqrt(vkr^2 + (2.1)^2 * (vk^2 - vkr^2)) pp.create_transformer3w_from_parameters(net, @@ -90,7 +90,7 @@ def iec_60909_4(): vk0_hv_percent=44.1, vkr0_hv_percent=0.26, vk0_mv_percent=6.299627, vkr0_mv_percent=0.03714286, vk0_lv_percent=6.299627, vkr0_lv_percent=0.03714286, - vector_group="Yynd", tap_phase_shifter_type=0, + vector_group="Yynd", tap_changer_type="Ratio", tap_max=10, tap_min=-10, tap_pos=0, tap_neutral=0, tap_side="hv", tap_step_percent=0.1) @@ -105,7 +105,7 @@ def iec_60909_4(): vk0_hv_percent=12, vkr0_hv_percent=0.5, vk0_mv_percent=12, vkr0_mv_percent=0.5, vk0_lv_percent=12, vkr0_lv_percent=0.5, - vector_group="Yyd", tap_phase_shifter_type=0, + vector_group="Yyd", tap_changer_type="Ratio", tap_max=10, tap_min=-10, tap_pos=0, tap_neutral=0, tap_side="hv", tap_step_percent=0.1) pp.create_transformer3w_from_parameters(net, @@ -119,7 +119,7 @@ def iec_60909_4(): vk0_hv_percent=12, vkr0_hv_percent=0.5, vk0_mv_percent=12, vkr0_mv_percent=0.5, vk0_lv_percent=12, vkr0_lv_percent=0.5, - vector_group="Yynd", tap_phase_shifter_type=0, + vector_group="Yynd", tap_changer_type="Ratio", tap_max=10, tap_min=-10, tap_pos=0, tap_neutral=0, tap_side="hv", tap_step_percent=0.1) # reactor is 100 Ohm @@ -287,7 +287,7 @@ def vde_232(): pp.create_ext_grid(net, 0, s_sc_max_mva=13.61213 * 110 * np.sqrt(3), rx_max=0.20328, x0x_max=3.47927, r0x0_max=3.03361) pp.create_transformer_from_parameters(net, 0, 1, 150, 115, 21, 0.5, 16, - pfe_kw=0, i0_percent=0, tap_step_percent=1, tap_phase_shifter_type=0, + pfe_kw=0, i0_percent=0, tap_step_percent=1, tap_changer_type="Ratio", tap_max=12, tap_min=-12, tap_neutral=0, tap_side='hv', vector_group="YNd", vk0_percent=np.sqrt(np.square(0.95*15.99219) + np.square(0.5)), diff --git a/pandapower/test/shortcircuit/test_transformer.py b/pandapower/test/shortcircuit/test_transformer.py index 4f72119c8..13737ff07 100644 --- a/pandapower/test/shortcircuit/test_transformer.py +++ b/pandapower/test/shortcircuit/test_transformer.py @@ -23,7 +23,7 @@ def net_transformer(): vkr_percent=0.5, pfe_kw=14, shift_degree=0.0, tap_side="hv", tap_neutral=0, tap_min=-2, tap_max=2, tap_pos=2, tap_step_percent=2.5, parallel=2, sn_mva=0.4, i0_percent=0.5, - tap_phase_shifter_type=0) + tap_changer_type="Ratio") # adding a shunt shouldn't change the result: pp.create_shunt(net, b2, q_mvar=0.050, p_mw=0.0500) return net diff --git a/pandapower/test/test_files/IEC60909-4_example.json b/pandapower/test/test_files/IEC60909-4_example.json index b7328cd86..17968cc43 100644 --- a/pandapower/test/test_files/IEC60909-4_example.json +++ b/pandapower/test/test_files/IEC60909-4_example.json @@ -179,7 +179,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"_ppc_idx\",\"description\",\"df\",\"equipment\",\"hv_bus\",\"i0_percent\",\"in_service\",\"lv_bus\",\"mag0_percent\",\"mag0_rx\",\"name\",\"parallel\",\"shift_degree\",\"si0_hv_partial\",\"sn_mva\",\"std_type\",\"tap_max\",\"tap_neutral\",\"tap_min\",\"tap_phase_shifter_type\",\"tap_pos\",\"tap_set_vm_pu\",\"tap_side\",\"tap_step_degree\",\"tap_step_percent\",\"vector_group\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk0_percent\",\"vk_percent\",\"vkr0_percent\",\"vkr_percent\",\"pfe_kw\"],\"index\":[0,1],\"data\":[[4,\"\",1.0,\"\",0,0.0,true,3,100,0,\"T1\",1,150.0,0.8999999762,0.6299999952316,\"20\\/0.4 kV 630 kVA\",null,null,null,false,0,1.0,null,null,null,\"YNyn\",20.0,0.4099999964,3.8136322498,4.0,1.0317460299,1.0317460299,0.0],[5,\"\",1.0,\"\",0,0.0,true,4,100,0,\"T2\",1,150.0,0.8999999762,0.4000000059605,\"20\\/0.4 kV 400 kVA\",null,null,null,false,0,1.0,null,null,null,\"Dyn\",20.0,0.4099999964,3.8169283867,4.0,1.1499999762,1.1499999762,0.0]]}", + "_object": "{\"columns\":[\"_ppc_idx\",\"description\",\"df\",\"equipment\",\"hv_bus\",\"i0_percent\",\"in_service\",\"lv_bus\",\"mag0_percent\",\"mag0_rx\",\"name\",\"parallel\",\"shift_degree\",\"si0_hv_partial\",\"sn_mva\",\"std_type\",\"tap_max\",\"tap_neutral\",\"tap_min\",\"tap_changer_type\",\"tap_pos\",\"tap_set_vm_pu\",\"tap_side\",\"tap_step_degree\",\"tap_step_percent\",\"vector_group\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk0_percent\",\"vk_percent\",\"vkr0_percent\",\"vkr_percent\",\"pfe_kw\"],\"index\":[0,1],\"data\":[[4,\"\",1.0,\"\",0,0.0,true,3,100,0,\"T1\",1,150.0,0.8999999762,0.6299999952316,\"20\\/0.4 kV 630 kVA\",null,null,null,false,0,1.0,null,null,null,\"YNyn\",20.0,0.4099999964,3.8136322498,4.0,1.0317460299,1.0317460299,0.0],[5,\"\",1.0,\"\",0,0.0,true,4,100,0,\"T2\",1,150.0,0.8999999762,0.4000000059605,\"20\\/0.4 kV 400 kVA\",null,null,null,false,0,1.0,null,null,null,\"Dyn\",20.0,0.4099999964,3.8169283867,4.0,1.1499999762,1.1499999762,0.0]]}", "dtype": { "_ppc_idx": "int32", "description": "object", @@ -200,7 +200,7 @@ "tap_max": "float64", "tap_neutral": "float64", "tap_min": "float64", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "tap_pos": "int32", "tap_set_vm_pu": "float64", "tap_side": "object", @@ -972,7 +972,7 @@ "tap_max": 2.0, "tap_neutral": 0.0, "tap_min": -2.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 2.5, @@ -995,7 +995,7 @@ "tap_max": 2.0, "tap_neutral": 0.0, "tap_min": -2.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 2.5, @@ -1018,7 +1018,7 @@ "tap_max": 2.0, "tap_neutral": 0.0, "tap_min": -2.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 2.5, @@ -1041,7 +1041,7 @@ "tap_max": 2.0, "tap_neutral": 0.0, "tap_min": -2.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 2.5, @@ -1064,7 +1064,7 @@ "tap_max": 2.0, "tap_neutral": 0.0, "tap_min": -2.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 2.5, @@ -1087,7 +1087,7 @@ "tap_max": 2.0, "tap_neutral": 0.0, "tap_min": -2.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 2.5, @@ -1110,7 +1110,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1133,7 +1133,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1156,7 +1156,7 @@ "tap_max": NaN, "tap_neutral": NaN, "tap_min": NaN, - "tap_phase_shifter_type": NaN, + "tap_changer_type": NaN, "tap_side": null, "tap_step_degree": NaN, "tap_step_percent": NaN, @@ -1179,7 +1179,7 @@ "tap_max": NaN, "tap_neutral": NaN, "tap_min": NaN, - "tap_phase_shifter_type": NaN, + "tap_changer_type": NaN, "tap_side": null, "tap_step_degree": NaN, "tap_step_percent": NaN, @@ -1202,7 +1202,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1225,7 +1225,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1248,7 +1248,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1271,7 +1271,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1294,7 +1294,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1317,7 +1317,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1340,7 +1340,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1363,7 +1363,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1386,7 +1386,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1409,7 +1409,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1432,7 +1432,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, @@ -1455,7 +1455,7 @@ "tap_max": 9.0, "tap_neutral": 0.0, "tap_min": -9.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_side": "hv", "tap_step_degree": 0.0, "tap_step_percent": 1.5, diff --git a/pandapower/test/test_files/controller_containing_NoneNan.json b/pandapower/test/test_files/controller_containing_NoneNan.json index 133e3329f..efeab51a0 100644 --- a/pandapower/test/test_files/controller_containing_NoneNan.json +++ b/pandapower/test/test_files/controller_containing_NoneNan.json @@ -198,7 +198,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -220,7 +220,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -897,7 +897,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -915,7 +915,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -933,7 +933,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -951,7 +951,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -969,7 +969,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -987,7 +987,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1005,7 +1005,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1023,7 +1023,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1041,7 +1041,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1059,7 +1059,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1077,7 +1077,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1095,7 +1095,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1113,7 +1113,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1131,7 +1131,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { diff --git a/pandapower/test/test_files/test_ac_dc.json b/pandapower/test/test_files/test_ac_dc.json index f181cafd4..5c43379f1 100644 --- a/pandapower/test/test_files/test_ac_dc.json +++ b/pandapower/test/test_files/test_ac_dc.json @@ -388,7 +388,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",\"2-Winding Transformer Type\",3,1,250.0,380.0,110.0,10.0,0.000199999994948,5.0,0.100000001490116,0.0,\"hv\",0,0,0,0.0,0.0,0,false,1,1.0,true,10.0,0.5,100.0,0.0,0.899999976158142,1.0,\"\",\"\"]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",\"2-Winding Transformer Type\",3,1,250.0,380.0,110.0,10.0,0.000199999994948,5.0,0.100000001490116,0.0,\"hv\",0,0,0,0.0,0.0,0,false,1,1.0,true,10.0,0.5,100.0,0.0,0.899999976158142,1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -410,7 +410,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -1273,7 +1273,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1291,7 +1291,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1309,7 +1309,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1327,7 +1327,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1345,7 +1345,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1363,7 +1363,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1381,7 +1381,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1399,7 +1399,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1417,7 +1417,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1435,7 +1435,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1453,7 +1453,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1471,7 +1471,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "2-Winding Transformer Type": { "sn_mva": 250.0, @@ -1491,7 +1491,7 @@ "tap_side": "hv", "tap_step_percent": 0.0, "tap_step_degree": 0.0, - "tap_phase_shifter_type": 0, + "tap_changer_type": "Ratio", "tap_max": 0, "tap_min": 0, "tap_neutral": 0 @@ -1512,7 +1512,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1530,7 +1530,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { diff --git a/pandapower/test/test_files/test_trafo3w_tap.json b/pandapower/test/test_files/test_trafo3w_tap.json index a0c28939d..04c0785d5 100644 --- a/pandapower/test/test_files/test_trafo3w_tap.json +++ b/pandapower/test/test_files/test_trafo3w_tap.json @@ -368,7 +368,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -390,7 +390,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_changer_type": "object", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -1282,7 +1282,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1300,7 +1300,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1318,7 +1318,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1336,7 +1336,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1354,7 +1354,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1372,7 +1372,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1390,7 +1390,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1408,7 +1408,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1426,7 +1426,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1444,7 +1444,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1462,7 +1462,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1480,7 +1480,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1498,7 +1498,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1516,7 +1516,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_phase_shifter_type": 0 + "tap_changer_type": "Ratio" } }, "trafo3w": { diff --git a/pandapower/test/timeseries/test_timeseries.py b/pandapower/test/timeseries/test_timeseries.py index 4af9554c6..a7da7c4c3 100644 --- a/pandapower/test/timeseries/test_timeseries.py +++ b/pandapower/test/timeseries/test_timeseries.py @@ -38,7 +38,7 @@ def simple_test_net(): pp.create_transformer3w_from_parameters(net, b1, b3, b4, 110, 20, 6, 1e2, 1e2, 1e1, 3, 2, 2, 1, 1, 1, 100, 1, 60, 30, 'hv', tap_step_percent=1.5, tap_step_degree=0, tap_pos=0, tap_neutral=0, tap_max=10, - tap_min=-10, name='tr2', tap_phase_shifter_type=0) + tap_min=-10, name='tr2', tap_changer_type="Ratio") pp.create_load(net, b2, 1.5e1, 1, name='trafo1') pp.create_load(net, b3, 3e1, 1.5, name='trafo2_mv') diff --git a/pandapower/test/timeseries/test_timeseries_recycle.py b/pandapower/test/timeseries/test_timeseries_recycle.py index a38a4476e..4ae4f3164 100644 --- a/pandapower/test/timeseries/test_timeseries_recycle.py +++ b/pandapower/test/timeseries/test_timeseries_recycle.py @@ -298,7 +298,7 @@ def test_const_pq_gen_trafo_tap_dc(simple_test_net, run_function=pp.rundcpp): def test_const_pq_gen_trafo_tap_ideal(simple_test_net, run_function): # allows to use recycle = {"bus_pq", "gen", "trafo"} net = simple_test_net - net.trafo.loc[0, ["tap_step_percent", "tap_step_degree", "tap_phase_shifter_type"]] = 0, 5, 2 + net.trafo.loc[0, ["tap_step_percent", "tap_step_degree", "tap_changer_type"]] = 0, 5, "Ideal" profiles, _ = create_data_source(n_timesteps) profiles['ext_grid'] = np.ones(n_timesteps) + np.arange(0, n_timesteps) * 1e-2 ds = DFData(profiles) @@ -326,7 +326,7 @@ def test_const_pq_gen_trafo_tap_ideal(simple_test_net, run_function): def test_const_pq_gen_trafo_tap_shifter(simple_test_net, run_function): # allows to use recycle = {"bus_pq", "gen", "trafo"} net = simple_test_net - net.trafo.loc[0, ["tap_step_percent", "tap_step_degree", "tap_phase_shifter_type"]] = 1, 10, 0 + net.trafo.loc[0, ["tap_step_percent", "tap_step_degree", "tap_changer_type"]] = 1, 10, "Ratio" profiles, _ = create_data_source(n_timesteps) profiles['ext_grid'] = np.ones(n_timesteps) + np.arange(0, n_timesteps) * 1e-2 ds = DFData(profiles) diff --git a/tutorials/create_advanced.ipynb b/tutorials/create_advanced.ipynb index 7e913e863..effaba588 100644 --- a/tutorials/create_advanced.ipynb +++ b/tutorials/create_advanced.ipynb @@ -3285,7 +3285,7 @@ " vkr_mv_percent=0.033333, vkr_lv_percent=0.04, pfe_kw=0, i0_percent=0, \n", " shift_mv_degree=30, shift_lv_degree=30, tap_side=\"hv\", tap_neutral=0, tap_min=-8, \n", " tap_max=8, tap_step_percent=1.25, tap_pos=0, name='HV-MV-MV-Trafo', \n", - " tap_phase_shifter_type=0)\n", + " tap_changer_type=0)\n", "\n", "# show transformer3w table\n", "net.trafo3w" @@ -4475,7 +4475,7 @@ "source": [ "hv_bus = pp.get_element_index(net, \"bus\", \"Bus MV4\")\n", "lv_bus = pp.get_element_index(net, \"bus\",\"Bus LV0\")\n", - "pp.create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva=.4, vn_hv_kv=10, vn_lv_kv=0.4, vkr_percent=1.325, vk_percent=4, pfe_kw=0.95, i0_percent=0.2375, tap_side=\"hv\", tap_neutral=0, tap_min=-2, tap_max=2, tap_step_percent=2.5, tap_phase_shifter_type=0, tp_pos=0, shift_degree=150, name='MV-LV-Trafo')\n", + "pp.create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva=.4, vn_hv_kv=10, vn_lv_kv=0.4, vkr_percent=1.325, vk_percent=4, pfe_kw=0.95, i0_percent=0.2375, tap_side=\"hv\", tap_neutral=0, tap_min=-2, tap_max=2, tap_step_percent=2.5, tap_changer_type=0, tp_pos=0, shift_degree=150, name='MV-LV-Trafo')\n", "\n", "#show only low voltage transformer\n", "net.trafo[net.trafo.lv_bus.isin(lv_buses.index)]" diff --git a/tutorials/tap_dependent_impedance.ipynb b/tutorials/tap_dependent_impedance.ipynb index 514ee7875..2f026a2f0 100644 --- a/tutorials/tap_dependent_impedance.ipynb +++ b/tutorials/tap_dependent_impedance.ipynb @@ -45,7 +45,7 @@ " sn_mv_mva=0.5, sn_lv_mva=0.4, vk_hv_percent=1., \n", " vk_mv_percent=1., vk_lv_percent=1., vkr_hv_percent=0.3, \n", " vkr_mv_percent=0.3, vkr_lv_percent=0.3, pfe_kw=0.2, \n", - " i0_percent=0.3, tap_neutral=0., tap_pos=2, tap_phase_shifter_type=0, \n", + " i0_percent=0.3, tap_neutral=0., tap_pos=2, tap_changer_type=0, \n", " tap_step_percent=1., tap_min=-2, tap_max=2)\n", " else:\n", " pp.create_transformer(net, hv_bus=hv_bus, lv_bus=cb, std_type=\"0.25 MVA 20/0.4 kV\", tap_pos=2)\n", diff --git a/tutorials/three_phase_loadflow_tutorial_simple.ipynb b/tutorials/three_phase_loadflow_tutorial_simple.ipynb index 1bc69efda..8301c4719 100644 --- a/tutorials/three_phase_loadflow_tutorial_simple.ipynb +++ b/tutorials/three_phase_loadflow_tutorial_simple.ipynb @@ -401,7 +401,7 @@ " tap_min= -2, tap_max= 2,\n", " tap_step_degree= 0,\n", " tap_step_percent= 2.5,\n", - " tap_phase_shifter_type=0,\n", + " tap_changer_type=0,\n", " vk0_percent= 6, vkr0_percent= 0.78125, \n", " mag0_percent= 100, mag0_rx= 0.,\n", " si0_hv_partial= 0.9,vector_group= \"Dyn\",\n", From 62512c44e72c956becc698176c593ad242cc54a6 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Mon, 16 Dec 2024 15:58:30 +0200 Subject: [PATCH 056/125] documentation typos --- doc/about/deprecating.rst | 8 ++++---- doc/about/units.rst | 2 +- doc/about/update20.rst | 2 +- doc/elements/asymmetric_load.rst | 2 +- doc/elements/asymmetric_sgen.rst | 2 +- doc/elements/ext_grid.rst | 2 +- doc/elements/impedance.rst | 2 +- doc/elements/line.rst | 2 +- doc/elements/load.rst | 2 +- doc/elements/sgen.rst | 2 +- doc/elements/storage.rst | 2 +- doc/elements/switch.rst | 2 +- doc/elements/tcsc.rst | 2 +- doc/elements/trafo3w.rst | 4 ++-- doc/estimation.rst | 4 ++-- doc/networks.rst | 2 +- doc/opf/formulation.rst | 6 +++--- doc/opf/pandamodels.rst | 6 +++--- doc/opf/pypower_run.rst | 6 +++--- doc/plotting/plotly/create_traces.rst | 3 ++- doc/powerflow/ac.rst | 4 ++-- doc/powerflow/ac_3ph.rst | 2 +- doc/powerflow/dc.rst | 2 +- doc/powerflow/diagnostic.rst | 2 +- doc/shortcircuit/branch_elements.rst | 4 ++-- doc/shortcircuit/currents.rst | 4 ++-- doc/shortcircuit/ikss.rst | 2 +- doc/topology.rst | 2 +- doc/topology/create_graph.rst | 4 ++-- doc/topology/examples.rst | 4 ++-- 30 files changed, 47 insertions(+), 46 deletions(-) diff --git a/doc/about/deprecating.rst b/doc/about/deprecating.rst index 030abfb8a..3fbb51057 100644 --- a/doc/about/deprecating.rst +++ b/doc/about/deprecating.rst @@ -13,21 +13,21 @@ This figure illustrates a time sequence of a process with deprecation warnings, :width: 500em :align: center -Proposed steps for contributers and reviewers: +Proposed steps for contributors and reviewers: #. Provide two pull requests (PR1 and PR2) including #. final code that should remain in the long-term - * if input parameter names have been changed, these can be catched and notified using :code:`raise DeprecationWarning("Notification message")` + * if input parameter names have been changed, this can be handled and a notification issued using :code:`raise DeprecationWarning("Notification message")` #. interim code to be contained in the master branch from the next to the next but one release version * to implement deprecation warnings type :code:`warnings.warn("Notification message", category=DeprecationWarning)` (:code:`category=FutureWarning` is also possible; don't forget :code:`import warnings`) - * the new functionality should be available but if the user does not pass arguments that explicitely call the new functionality, the old functionality should be evaluated plus sending DeprecationWarnings + * the new functionality should be available but if the user does not pass arguments that explicitly call the new functionality, the old functionality should be evaluated plus sending DeprecationWarnings * make sure to add new tests for the new functionality * please add :code:`assert Version(pp.__version__) < Version('2.12')` with :code:`from packaging.version import Version` to the tests of the deprecated functionality (assuming that the latest pandapower version is `v2.10.x` ; tests of the deprecated code should be removed with PR1) #. Reviewer: don't approve the PRs as long as both PRs are correct and complete #. The person merging PR2 is responsible to merge PR1 after the next release As an example, please have a look at the revision of the function `pandapower.toolbox.merge_nets()`. -It has been revised by `PR2 `_ temporarly. This state is available from pandapower version `v2.10.0` to `v2.11.1`. +It has been revised by `PR2 `_ temporarily. This state is available from pandapower version `v2.10.0` to `v2.11.1`. With `v2.12.0` the final code, merged via `PR1 `_, is available. For suggestions on revising this process, `Issue 1760 `_ can be reopened. diff --git a/doc/about/units.rst b/doc/about/units.rst index ad3470303..f4d428f6a 100644 --- a/doc/about/units.rst +++ b/doc/about/units.rst @@ -47,7 +47,7 @@ The power equation in the balanced three phase system is therefore given as :mat For unbalanced three phase systems, the following conventions apply: - voltage values are entered as phase-to-phase voltages - current values are entered as phase currents - - But, Phase power values can be entered seperately in the new element **asymmetric_load** + - But, Phase power values can be entered separately in the new element **asymmetric_load** The power equation in each phase is therefore given as :math:`S_{ph-e} = \frac{V_{ph-ph} \cdot I_{ph-ph}}{\sqrt3 }`. diff --git a/doc/about/update20.rst b/doc/about/update20.rst index 0227e5f9a..3a1f6e623 100644 --- a/doc/about/update20.rst +++ b/doc/about/update20.rst @@ -181,7 +181,7 @@ the cost parameters can be directly specified as parameters instead of passing a | **pandapower 2.x** | :code:`pp.create_poly_cost(net, 3, "gen", c_per_mw=0.1, c2_per_mw2=0.01)` | +--------------------+--------------------------------------------------------------------------------------------------------------+ -The definition of piecewise linear costs has also changed. In pandapower 1.x, the cost polyonmial is given as list of cost points: :: +The definition of piecewise linear costs has also changed. In pandapower 1.x, the cost polynomial is given as list of cost points: :: [(p1, c1), (p2, c2), (p3, c3)] diff --git a/doc/elements/asymmetric_load.rst b/doc/elements/asymmetric_load.rst index 7a738aff8..c6c9b63e7 100644 --- a/doc/elements/asymmetric_load.rst +++ b/doc/elements/asymmetric_load.rst @@ -34,7 +34,7 @@ Input Parameters .. note:: - - The apparent power value sn_mva is provided as additional information for usage in controller or other applications based on panadapower. It is not considered in the power flow! + - The apparent power value sn_mva is provided as additional information for usage in controller or other applications based on pandapower. It is not considered in the power flow! - 'wye' is the same as PH-E loads diff --git a/doc/elements/asymmetric_sgen.rst b/doc/elements/asymmetric_sgen.rst index 15d023ab5..050a0d87d 100644 --- a/doc/elements/asymmetric_sgen.rst +++ b/doc/elements/asymmetric_sgen.rst @@ -58,7 +58,7 @@ The PQ-Values are calculated from the parameter table values as: .. note:: - The apparent power value sn_mva is provided as additional information for usage in controller or other applications based on panadapower. It is not considered in the power flow! + The apparent power value sn_mva is provided as additional information for usage in controller or other applications based on pandapower. It is not considered in the power flow! Result Parameters ========================== diff --git a/doc/elements/ext_grid.rst b/doc/elements/ext_grid.rst index 1650b1126..13dd3f87c 100644 --- a/doc/elements/ext_grid.rst +++ b/doc/elements/ext_grid.rst @@ -53,7 +53,7 @@ with: \end{align*} -** Unbalanced Load Flow / Single phase short ciruit ** +** Unbalanced Load Flow / Single phase short circuit ** The external grid is modelled as a voltage source for positive sequence model, which means the node the grid is connected to is treated as a slack node. For zero sequence and negative sequence external grid impedance is calculated: diff --git a/doc/elements/impedance.rst b/doc/elements/impedance.rst index 32bf06f94..946eb8ad6 100644 --- a/doc/elements/impedance.rst +++ b/doc/elements/impedance.rst @@ -48,7 +48,7 @@ The per unit values are therefore transformed into the network per unit system: where :math:`S_{N}` is the reference power of the per unit system (see :ref:`Unit Systems and Conventions`). -The asymetric impedance results in an asymetric nodal point admittance matrix: +The asymmetric impedance results in an asymmetric nodal point admittance matrix: .. math:: :nowrap: diff --git a/doc/elements/line.rst b/doc/elements/line.rst index d1a2ffda0..4ecf560e5 100644 --- a/doc/elements/line.rst +++ b/doc/elements/line.rst @@ -95,7 +95,7 @@ The power system frequency :math:`f` is defined when creating an empty network, .. note:: - For three phase load flow, three decoupled sequence networks ( zero , positive and negtive) are considered. + For three phase load flow, three decoupled sequence networks ( zero , positive and negative) are considered. **Positive and Negative sequence impedances** are given by r_ohm_per_km, x_ohm_per_km, and c_nf_per_km diff --git a/doc/elements/load.rst b/doc/elements/load.rst index 8e718fd75..8225353ba 100644 --- a/doc/elements/load.rst +++ b/doc/elements/load.rst @@ -33,7 +33,7 @@ Input Parameters .. note:: - The apparent power value sn_mva is provided as additional information for usage in controller or other applications based on panadapower. It is not considered in the power flow! + The apparent power value sn_mva is provided as additional information for usage in controller or other applications based on pandapower. It is not considered in the power flow! Electric Model diff --git a/doc/elements/sgen.rst b/doc/elements/sgen.rst index 5502d1eb7..a3d7ca62e 100644 --- a/doc/elements/sgen.rst +++ b/doc/elements/sgen.rst @@ -59,7 +59,7 @@ The PQ-Values are calculated from the parameter table values as: .. note:: - The apparent power value sn_mva is provided as additional information for usage in controller or other applications based on panadapower. It is not considered in the power flow! + The apparent power value sn_mva is provided as additional information for usage in controller or other applications based on pandapower. It is not considered in the power flow! Result Parameters ========================== diff --git a/doc/elements/storage.rst b/doc/elements/storage.rst index 43b877a38..68b4369d1 100644 --- a/doc/elements/storage.rst +++ b/doc/elements/storage.rst @@ -54,7 +54,7 @@ The PQ-Values are calculated from the parameter table values as: .. note:: - The apparent power value sn_mva, state of charge soc and storage capacity max_e_mwh are provided as additional information for usage in controller or other applications based on panadapower. It is not considered in the power flow! + The apparent power value sn_mva, state of charge soc and storage capacity max_e_mwh are provided as additional information for usage in controller or other applications based on pandapower. It is not considered in the power flow! Result Parameters ========================== diff --git a/doc/elements/switch.rst b/doc/elements/switch.rst index d818417de..f0f4d51e9 100644 --- a/doc/elements/switch.rst +++ b/doc/elements/switch.rst @@ -43,7 +43,7 @@ This has the following advantages compared to modelling the switch as a small im *Bus-Element-Switches:* -When the power flow is calculated internally for every open bus-element switch an auxilary bus is created in the pypower case file. The pypower branch that corresponds to the element is then connected to this bus. This has the following advantages compared to modelling the switch by setting the element out of service: +When the power flow is calculated internally for every open bus-element switch an auxiliary bus is created in the pypower case file. The pypower branch that corresponds to the element is then connected to this bus. This has the following advantages compared to modelling the switch by setting the element out of service: - loading current is considered - information about switch position is preserved diff --git a/doc/elements/tcsc.rst b/doc/elements/tcsc.rst index 61f2ba52f..0de0cc605 100644 --- a/doc/elements/tcsc.rst +++ b/doc/elements/tcsc.rst @@ -9,7 +9,7 @@ We implement the FACTS devices based on the following source: A. Panosyan, "Modeling of advanced power transmission system controllers", Ph.D. dissertation, Gottfried Wilhelm Leibniz Universität Hannover, 2010. -Thyristor-Controlled Series Capacitor (TCSC) device is a series element that controles the power flowing through its +Thyristor-Controlled Series Capacitor (TCSC) device is a series element that controls the power flowing through its path by regulating its impedance. The TCSC device is very similar to the Static Var Compensator (SVC) - in fact, it is its series counterpart. Indeed, a TCSC device consists of a parallel circuit of a fixed capacitor and a reactor controlled by a pair of diff --git a/doc/elements/trafo3w.rst b/doc/elements/trafo3w.rst index e45357227..0c6ae0f94 100644 --- a/doc/elements/trafo3w.rst +++ b/doc/elements/trafo3w.rst @@ -26,7 +26,7 @@ Create Function the medium level, it is given relative to the minimum of the rated apparent power in high and medium level: min(sn_hv_mva, sn_mv_mva). This is consistent with most commercial network calculation software (e.g. PowerFactory). - Some tools (like PSS Sincal) however define all short ciruit voltages relative + Some tools (like PSS Sincal) however define all short circuit voltages relative to the overall rated apparent power of the transformer: max(sn_hv_mva, sn_mv_mva, sn_lv_mva). You might have to convert the values depending on how the short-circuit voltages are defined. @@ -81,7 +81,7 @@ values to branch based values v'_{k, lh} &= vk\_lv\_percent \cdot \frac{sn\_hv\_mva}{min(sn\_hv\_mva, sn\_lv\_mva)} \end{align*} -These transformer now represent a :math:`\Delta` connection of the equivalent transformers. A :math:`\Delta-Y` conversion is therefore applied to recieve the parameters in :math:`Y`-connection: +These transformer now represent a :math:`\Delta` connection of the equivalent transformers. A :math:`\Delta-Y` conversion is therefore applied to receive the parameters in :math:`Y`-connection: .. math:: :nowrap: diff --git a/doc/estimation.rst b/doc/estimation.rst index e328ed79d..9ad8f83c6 100644 --- a/doc/estimation.rst +++ b/doc/estimation.rst @@ -87,7 +87,7 @@ Handling of bad data The state estimation class allows additionally the removal of bad data, especially single or non-interacting false measurements. For detecting bad data the Chi-squared distribution is used to identify the presence of them. -Afterwards follows the largest normalized residual test that identifys the actual measurements which will be removed at the end. +Afterwards follows the largest normalized residual test that identifies the actual measurements which will be removed at the end. Both methods are combined in the *perform_rn_max_test* function that is part of the state estimation class. To access it, the following wrapper function *remove_bad_data* has been created. @@ -145,7 +145,7 @@ If we like to check our data for fault measurements, and exclude them in in our success_rn_max = remove_bad_data(net, init="flat") V_rn_max, delta_rn_max = net.res_bus_est.vm_pu, net.res_bus_est.va_degree -In the case that we only like to know if there is a likelihood of fault measurements (probabilty of fault can be adjusted), the Chi-squared test should be performed separatly. +In the case that we only like to know if there is a likelihood of fault measurements (probability of fault can be adjusted), the Chi-squared test should be performed separately. If the test detects the possibility of fault data, the value of the added class member variable *bad_data_present* would be *true* as well as the boolean variable *success_chi2* that is used here: :: diff --git a/doc/networks.rst b/doc/networks.rst index f3d4497f8..d9b7b19d8 100644 --- a/doc/networks.rst +++ b/doc/networks.rst @@ -9,7 +9,7 @@ benchmark grids through the networks module. The pandapower networks module contains example grids, simple test grids, randomly generated grids, CIGRE test grids, IEEE case files (including 3-phase grids) and synthetic low voltage grids from Georg Kerber, Lindner et. al. and Dickert et. al. -If you want to evaluate your algotihms on benchmark grids with corresponding full-year load, generation, and storage profiles +If you want to evaluate your algorithms on benchmark grids with corresponding full-year load, generation, and storage profiles or want to publish your results in a reproducible manner, we recommend the SimBench repository (`Homepage `_, `GitHub Repository to use SimBench with pandapower `_). diff --git a/doc/opf/formulation.rst b/doc/opf/formulation.rst index 68bb1a8f0..b6e75e112 100644 --- a/doc/opf/formulation.rst +++ b/doc/opf/formulation.rst @@ -40,7 +40,7 @@ The network constraints contain constraints for bus voltages and branch flows: :file: opf_constraints.csv :delim: ; -The defaults are unconstraint branch loadings and :math:`\pm 1.0 pu` for bus voltages. +The defaults are unconstrained branch loadings and :math:`\pm 1.0 pu` for bus voltages. Cost functions --------------- @@ -74,10 +74,10 @@ Polynomial cost functions can be specified using create_poly_cost(): .. note:: Please note, that polynomial costs for reactive power can only be quadratic, linear or constant. - Piecewise linear cost funcions for reactive power are not working at the moment with 2 segments or more. + Piecewise linear cost functions for reactive power are not working at the moment with 2 segments or more. Loads can only have 2 data points in their piecewise linear cost function for active power. -Active and reactive power costs are calculted separately. The costs of all types are summed up to determine the overall costs for a grid state. +Active and reactive power costs are calculated separately. The costs of all types are summed up to determine the overall costs for a grid state. Visualization of cost functions -------------------------------- diff --git a/doc/opf/pandamodels.rst b/doc/opf/pandamodels.rst index 380a27bc5..ca4bb2f37 100644 --- a/doc/opf/pandamodels.rst +++ b/doc/opf/pandamodels.rst @@ -31,9 +31,9 @@ If you are not yet using `Julia `_, install it :code:`ENV["PYTHON"]="/Users/%Username/opt/anaconda3/bin/python"` -3. Access the package manager by typing :code:`]`. Now install the packages: :code:`add Ipopt PowerModels PyCall`. To pass the python environment variable, running :code:`build PyCall` inside the julia package manager may be neccessary. +3. Access the package manager by typing :code:`]`. Now install the packages: :code:`add Ipopt PowerModels PyCall`. To pass the python environment variable, running :code:`build PyCall` inside the julia package manager may be necessary. -4. Inside package manager, test your `PowerModels `_ installation by executing :code:`test PowerModels`. Alternatively, you can call :code:`using Pkg` and then :code:`Pkg.test("PowerModels")` outside the package manager directly as julia expression. Then, test wether calling Python from Julia works, as described `here `__. +4. Inside package manager, test your `PowerModels `_ installation by executing :code:`test PowerModels`. Alternatively, you can call :code:`using Pkg` and then :code:`Pkg.test("PowerModels")` outside the package manager directly as julia expression. Then, test whether calling Python from Julia works, as described `here `__. .. note:: If you cannot plot using PyCall and PyPlot in Julia, see the workarounds offered `here `__. @@ -43,7 +43,7 @@ If you are not yet using `Julia `_, install it 7. Now install our interface `PandaModels.jl` by type :code:`add PandaModels` inside Julia package manager. -8. Finally, you can then test whether the PandaModels.jl interface works: Navigate to your local pandapower test folder :code:`pandapower/pandapower/test/opf` folder and run :code:`python-jl test_pandamodels_runpm.py` or :code:`pytest test_pandamodels_runpm.py` if pytest is intalled. If everything works there should be no error. +8. Finally, you can then test whether the PandaModels.jl interface works: Navigate to your local pandapower test folder :code:`pandapower/pandapower/test/opf` folder and run :code:`python-jl test_pandamodels_runpm.py` or :code:`pytest test_pandamodels_runpm.py` if pytest is installed. If everything works there should be no error. Additional Solvers diff --git a/doc/opf/pypower_run.rst b/doc/opf/pypower_run.rst index fe868f30e..e0234084b 100644 --- a/doc/opf/pypower_run.rst +++ b/doc/opf/pypower_run.rst @@ -19,7 +19,7 @@ AC OPF The internal solver uses the interior point method. By default, the initial state is the center of the operational constraints. Another option would be to initialize the optimisation with a valid loadflow solution. -For optimiation of a timeseries, this warm start possibilty could imply a significant speedup. +For optimization of a timeseries, this warm start possibility could imply a significant speedup. This is not yet provided in the actual version, but could be an useful extension in the future. @@ -44,13 +44,13 @@ To understand the usage, the `DC OPF tutorial `_. In constrast, the library lightsim2grid +cf. `link `_. In contrast, the library lightsim2grid is used as a backend for power flow simulation instead of the implementation in pandapower. It leads to a boost in performance. The library lightsim2grid is implemented in C++ and can either be installed with pip install lightsim2grid, or built from source. diff --git a/doc/powerflow/ac_3ph.rst b/doc/powerflow/ac_3ph.rst index 91cef5cf1..2e3373dd8 100644 --- a/doc/powerflow/ac_3ph.rst +++ b/doc/powerflow/ac_3ph.rst @@ -13,7 +13,7 @@ pandapower uses Sequence Frame to solve three phase power flow : .. note:: If you are interested in the pypower casefile that pandapower is using for power flow internally, you can find it in net["_ppc0"],net["_ppc1"], net["_ppc2"]. - However all necessary informations are written into the pandpower format net, so the pandapower user should not usually have to deal with pypower. + However all necessary information is written into the pandapower format net, so the pandapower user should not usually have to deal with pypower. Asymmetric Power Flow using power-grid-model diff --git a/doc/powerflow/dc.rst b/doc/powerflow/dc.rst index 9da934d54..123917734 100644 --- a/doc/powerflow/dc.rst +++ b/doc/powerflow/dc.rst @@ -17,4 +17,4 @@ pandapower uses PYPOWER to solve the DC power flow problem: .. note:: If you are interested in the pypower casefile that pandapower is using for power flow, you can find it in net["_ppc"]. - However all necessary informations are written into the pandpower format net, so the pandapower user should not usually have to deal with pypower. + However all necessary information is written into the pandapower format net, so the pandapower user should not usually have to deal with pypower. diff --git a/doc/powerflow/diagnostic.rst b/doc/powerflow/diagnostic.rst index 8ed62aed3..f2598d34b 100644 --- a/doc/powerflow/diagnostic.rst +++ b/doc/powerflow/diagnostic.rst @@ -52,7 +52,7 @@ Both reports show the same result, but on the left hand picture with detailed in Result Dictionary ------------------ -Additionally all check results are returned in a dict to allow simple access to the indeces of all element where +Additionally all check results are returned in a dict to allow simple access to the indices of all element where errors were found. .. image:: /pics/diagnostic/diag_results_dict.png diff --git a/doc/shortcircuit/branch_elements.rst b/doc/shortcircuit/branch_elements.rst index ad73bdf8a..73868de22 100644 --- a/doc/shortcircuit/branch_elements.rst +++ b/doc/shortcircuit/branch_elements.rst @@ -30,7 +30,7 @@ where the correction factor for the short-circuit resistance :math:`K_L` is def 1 + 0.04 K^{-1} (endtemp\_degree - 20°C) & \text{ for minimum short-circuit calculations} \end{array}\right. -The end temperature in degree after a fault has to be defined with the parameter endtemp\_degre in the line table. +The end temperature in degree after a fault has to be defined with the parameter endtemp\_degree in the line table. Two-Winding Transformer ------------------------- @@ -87,7 +87,7 @@ two-winding transformers. Impedance -------------------------- -The impedance element is a generic element that is not desribed in the standard. It is considered in the short-circuit calculation just as in the power flow as described :ref:`here `. +The impedance element is a generic element that is not described in the standard. It is considered in the short-circuit calculation just as in the power flow as described :ref:`here `. diff --git a/doc/shortcircuit/currents.rst b/doc/shortcircuit/currents.rst index 1e1687960..aa6d84c83 100644 --- a/doc/shortcircuit/currents.rst +++ b/doc/shortcircuit/currents.rst @@ -7,7 +7,7 @@ The short-circuit currents are calculated according to the **IEC 60909** interna 1. equivalent voltage source method (i.e. by introducing the Thevenin's voltage source) at the fault location and 2. superposition method that considers the pre-fault voltage vector. -For both methods, the possiboility to use LU factorization is implemented (option inverse_y=False). This improves the performance of the short-circuit calculation and reduces the required RAM, especially for large grid models, if the number of fault buses is low. +For both methods, the possibility to use LU factorization is implemented (option inverse_y=False). This improves the performance of the short-circuit calculation and reduces the required RAM, especially for large grid models, if the number of fault buses is low. For a detailed explanation of the theory behind short-circuit calculations according to IEC 60909 please refer to the mentioned normative document or secondary literature: @@ -38,7 +38,7 @@ The power system units can be considered by setting the parameters "power_statio Note that the short-circuit currents are calculated in the complex domain, which allows obtaining the branch-related values for current magnitude and phase angle. In the case of transformers with rated voltage values unequal to the bus rated voltage values, only the current results are available because the voltage results are not valid in this case. For such configurations, only the superposition method can be used to obtain voltage, active and reactive power results (see below). -**Ad 2)** The superposition method (per IEC 60909) considers the pre-fault voltage vector. This method is activated by passing the argument "use_pre_fault_voltage" as True to the "calc_sc" function call. The superposition method is only inplemented for three-phase symmetric fault (fault="3ph"). +**Ad 2)** The superposition method (per IEC 60909) considers the pre-fault voltage vector. This method is activated by passing the argument "use_pre_fault_voltage" as True to the "calc_sc" function call. The superposition method is only implemented for three-phase symmetric fault (fault="3ph"). Note that the user needs to explicitly carry out the power flow calculation (i.e. by invoking the "runpp" function call) on the network, before proceeding to the short-circuit calculation with the superposition method. We rely on the user to execute this step explicitly so that the user is fully aware that a power flow calculation is executed, and also has control over all the relevant options for the power flow calculation. Results provide branch currents magnitude and angle, along with active and reactive power flows, and bus voltages magnitude and angle values. diff --git a/doc/shortcircuit/ikss.rst b/doc/shortcircuit/ikss.rst index 8c294218f..5ac39ec4c 100644 --- a/doc/shortcircuit/ikss.rst +++ b/doc/shortcircuit/ikss.rst @@ -82,7 +82,7 @@ For the calculation of a short-circuit at bus :math:`j`, this yields the followi where :math:`\underline{I}''_{kIj}` is the voltage source contribution of the short-circuit current at bus :math:`j`. The voltages at all non-fault buses and the current at the fault bus are unknown. To solve for :math:`\underline{I}''_{kIj}` , -we multipliy with the inverted nodal point admittance matrix (impedance matrix): +we multiply with the inverted nodal point admittance matrix (impedance matrix): .. math:: diff --git a/doc/topology.rst b/doc/topology.rst index ef766cda5..4fa9ce736 100644 --- a/doc/topology.rst +++ b/doc/topology.rst @@ -9,7 +9,7 @@ pandapower provides a function to translate pandapower networks into networkx gr are available in networkx can be used to analyse the network. For example you can find the shortest path between two nodes, find out if two areas in a network are connected to each other or if there are cycles in a network. For a complete list of all NetworkX algorithms see https://networkx.org/documentation/stable/reference/algorithms/index.html -pandapower also provides some search algorithms specialiced for electric networks, such as finding all buses that are connected to a slack node. +pandapower also provides some search algorithms specialised for electric networks, such as finding all buses that are connected to a slack node. .. toctree:: :maxdepth: 1 diff --git a/doc/topology/create_graph.rst b/doc/topology/create_graph.rst index fe2446b04..b36a8b065 100644 --- a/doc/topology/create_graph.rst +++ b/doc/topology/create_graph.rst @@ -2,7 +2,7 @@ Create networkx graph ====================== -The basis of all topology functions is the conversion of a padapower network into a NetworkX MultiGraph. A MultiGraph is a simplified representation of a network's topology, reduced to nodes and edges. +The basis of all topology functions is the conversion of a pandapower network into a NetworkX MultiGraph. A MultiGraph is a simplified representation of a network's topology, reduced to nodes and edges. Busses are being represented by nodes (Note: only buses with in_service = 1 appear in the graph), edges represent physical connections between buses (typically lines or trafos). Multiple parallel edges between nodes are possible. @@ -13,7 +13,7 @@ This is a very simple example of a pandapower network being converted to a Multi :alt: alternate Text :align: center -Nodes have the same indicees as the buses they originate from. Edges are defined by the nodes they connect. +Nodes have the same indices as the buses they originate from. Edges are defined by the nodes they connect. Additionally nodes and edges can hold key/value attribute pairs. The following attributes get transferred into the MultiGraph: diff --git a/doc/topology/examples.rst b/doc/topology/examples.rst index a1898a967..539e9efd4 100644 --- a/doc/topology/examples.rst +++ b/doc/topology/examples.rst @@ -2,7 +2,7 @@ Examples ========== -The combination of a suitable MultiGraph and the availabe topology functions enables you to perform a wide range of topological +The combination of a suitable MultiGraph and the available topology functions enables you to perform a wide range of topological searches and analyses. Here are a few examples of what you can do: @@ -58,7 +58,7 @@ Here are a few examples of what you can do: Using NetworkX algorithms: shortest path ----------------------------------------- -For many basic network analyses the algorithms that come with the NetworkX package will work just fine and you won't need one of the spezialised topology functions. +For many basic network analyses the algorithms that come with the NetworkX package will work just fine and you won't need one of the specialised topology functions. Finding the shortest path between two buses is a good example for that. .. code:: python From a0dea888e84d0bcf3bf326360e5b6384d859868a Mon Sep 17 00:00:00 2001 From: tfabian Date: Mon, 16 Dec 2024 16:40:49 +0100 Subject: [PATCH 057/125] all but 10 tests are running after renaming. Missing is matpower and ppc testfiles adaptation, and one NaN va pd.NA assert where I do not know enough python --- pandapower/build_branch.py | 14 ++++++-------- pandapower/create.py | 18 +++++++++--------- pandapower/test/api/test_create.py | 2 +- pandapower/test/converter/test_from_cim.py | 2 +- pandapower/test/loadflow/test_scenarios.py | 2 +- 5 files changed, 18 insertions(+), 20 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 18949af0e..98d446e2f 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -603,7 +603,7 @@ def _calc_tap_from_dataframe(net, trafo_df): if f'tap{t}_changer_type' in trafo_df: # tap_phase_shift_type is only in dataframe starting from pp Version 3.0, older version use different logic - phase_shifter_type = get_trafo_values(trafo_df, f"tap{t}_changer_type") + tap_changer_type = get_trafo_values(trafo_df, f"tap{t}_changer_type") if f'tap{t}_dependency_table' in trafo_df: tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") tap_dependency = np.array( @@ -611,11 +611,9 @@ def _calc_tap_from_dataframe(net, trafo_df): else: tap_table = np.array([False]) tap_dependency = np.array([False]) - if not isinstance(trafo_df, dict) and not isinstance(phase_shifter_type, np.ndarray): - phase_shifter_type = phase_shifter_type.to_numpy() - phase_shifter_type = pd.Series(phase_shifter_type).fillna(-1).to_numpy() - tap_table = np.logical_and(tap_dependency, np.logical_not(phase_shifter_type == -1)) - tap_no_table = np.logical_and(~tap_dependency, np.logical_not(phase_shifter_type == -1)) + tap_changer_type = pd.Series(tap_changer_type) + tap_table = np.logical_and(tap_dependency, np.logical_not(tap_changer_type == "None")) + tap_no_table = np.logical_and(~tap_dependency, np.logical_not(tap_changer_type == "None")) if any(tap_table): id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: @@ -631,8 +629,8 @@ def _calc_tap_from_dataframe(net, trafo_df): vn[mask] = vn[mask] * filtered_df['voltage_ratio'] trafo_shift[mask] += filtered_df['angle_deg'] if any(tap_no_table): - tap_ideal = np.logical_and(phase_shifter_type == 2, tap_no_table) - tap_complex = np.logical_and(np.logical_or(phase_shifter_type == 0, phase_shifter_type == 1), + tap_ideal = np.logical_and(tap_changer_type == "Ideal", tap_no_table) + tap_complex = np.logical_and(np.logical_or(tap_changer_type == "Ratio", tap_changer_type == "Symmetrical"), tap_no_table) for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: mask_ideal = (tap_ideal & (tap_side == side)) diff --git a/pandapower/create.py b/pandapower/create.py index e911e2970..18aab5e4a 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -3282,7 +3282,7 @@ def create_lines_dc_from_parameters(net, from_buses_dc, to_buses_dc, length_km, def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in_service=True, - index=None, max_loading_percent=nan, parallel=1, df=1., tap_changer_type="None", + index=None, max_loading_percent=nan, parallel=1, df=1., tap_changer_type=pd.NA, tap_dependency_table=nan, id_characteristic_table=nan, pt_percent=nan, oltc=nan, xn_ohm=nan, tap2_pos=nan, **kwargs): """ @@ -3410,7 +3410,7 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, tap_changer_type, "tap_changer_type", - "trafo", dtype=str) + "trafo", dtype=object) _set_value_if_not_nan(net, index, pt_percent, "pt_percent", "trafo") _set_value_if_not_nan(net, index, oltc, "oltc", "trafo", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, xn_ohm, "xn_ohm", "trafo") @@ -3423,7 +3423,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn shift_degree=0, tap_side=None, tap_neutral=nan, tap_max=nan, tap_min=nan, tap_step_percent=nan, tap_step_degree=nan, - tap_pos=nan, tap_changer_type="None", id_characteristic_table=nan, + tap_pos=nan, tap_changer_type=pd.NA, id_characteristic_table=nan, in_service=True, name=None, vector_group=None, index=None, max_loading_percent=nan, parallel=1, df=1., vk0_percent=nan, vkr0_percent=nan, @@ -3432,7 +3432,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn pt_percent=nan, oltc=nan, tap_dependency_table=False, xn_ohm=nan, tap2_side=None, tap2_neutral=nan, tap2_max=nan, tap2_min=nan, tap2_step_percent=nan, tap2_step_degree=nan, - tap2_pos=nan, tap2_changer_type="None", **kwargs): + tap2_pos=nan, tap2_changer_type=pd.NA, **kwargs): """ Creates a two-winding transformer in table net["trafo"]. The trafo parameters are defined through the standard type library. @@ -3502,8 +3502,8 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **tap_step_degree** (float) - tap step size for voltage angle in degree* - **tap_changer_type** (str, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, - 1: Symmetrical, 2: Ideal)* + **tap_changer_type** (str, nan) - specifies the phase shifter type ("Ratio": Ratio/Asymmetrical, + "Symmetrical": Symmetrical, "Ideal": Ideal)* **index** (int, None) - Force a specified ID if it is available. If None, the index one \ higher than the highest already existing index is selected. @@ -3546,7 +3546,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **tap2_step_degree** (float) - second tap step size for voltage angle in degree* - **tap2_changer_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, + **tap2_changer_type** (str, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal)* **leakage_resistance_ratio_hv** (bool) - ratio of transformer short-circuit resistance on HV side (default 0.5) @@ -3598,7 +3598,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo", dtype="Int64") _set_value_if_not_nan(net, index, tap_changer_type, - "tap_changer_type", "trafo", dtype=str) + "tap_changer_type", "trafo", dtype=object) _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo", dtype=bool_, default_val=False) @@ -5872,7 +5872,7 @@ def _not_nan(value, all_=True): return not any(isnan(value)) else: try: - return not (value is None or isnan(value)) + return not (value is None or value is pd.NA or isnan(value)) except TypeError: return True diff --git a/pandapower/test/api/test_create.py b/pandapower/test/api/test_create.py index 7ecbf5289..fd565bc58 100644 --- a/pandapower/test/api/test_create.py +++ b/pandapower/test/api/test_create.py @@ -230,7 +230,7 @@ def test_nonexistent_bus(): def test_tap_changer_type_default(): - expected_default = "None" + expected_default = pd.NA net = pp.create_empty_network() pp.create_bus(net, 110) pp.create_bus(net, 20) diff --git a/pandapower/test/converter/test_from_cim.py b/pandapower/test/converter/test_from_cim.py index bd65f1b80..923790267 100644 --- a/pandapower/test/converter/test_from_cim.py +++ b/pandapower/test/converter/test_from_cim.py @@ -726,7 +726,7 @@ def test_fullgrid_trafo(fullgrid_v2): assert 1.250 == element_0['tap_step_percent'].item() assert math.isnan(element_0['tap_step_degree'].item()) assert -2.0 == element_0['tap_pos'].item() - assert 0 == element_0['tap_changer_type'].item() + assert "Ratio" == element_0['tap_changer_type'].item() assert 1.0 == element_0['parallel'].item() assert 1.0 == element_0['df'].item() assert element_0['in_service'].item() diff --git a/pandapower/test/loadflow/test_scenarios.py b/pandapower/test/loadflow/test_scenarios.py index be581305e..9f5d4eb0f 100644 --- a/pandapower/test/loadflow/test_scenarios.py +++ b/pandapower/test/loadflow/test_scenarios.py @@ -220,7 +220,7 @@ def test_transformer_phase_shift(): net, b1, b2, 40000, 110, 20, 0.1, 5, 0, 0.1, 30, side, # 0, 2, -2, 1.25, 10, 0) - 0, 2, -2, 0, 10, 0, 2) + 0, 2, -2, 0, 10, 0, "Ideal") pp.create_transformer_from_parameters( net, b2, b3, 630, 20, 0.4, 0.1, 5, 0, 0.1, 20) pp.runpp(net, init="dc", calculate_voltage_angles=True) From afdb27ad6ebd9272b8430dc30334c9cb11710d9f Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Tue, 17 Dec 2024 12:24:47 +0200 Subject: [PATCH 058/125] debugging updates --- pandapower/build_bus.py | 6 +++--- pandapower/convert_format.py | 10 +++++++--- .../transformers/powerTransformersCim16.py | 10 ++++++---- pandapower/test/converter/test_from_powerfactory.py | 1 - 4 files changed, 16 insertions(+), 11 deletions(-) diff --git a/pandapower/build_bus.py b/pandapower/build_bus.py index 61adb504f..13cbaa519 100644 --- a/pandapower/build_bus.py +++ b/pandapower/build_bus.py @@ -642,11 +642,11 @@ def _calc_shunts_and_add_on_ppc(net, ppc): v_ratio = (ppc["bus"][bus_lookup[s["bus"].values], BASE_KV] / s["vn_kv"].values) ** 2 * base_multiplier if "step_dependency_table" in s: - if np.any(vl & (s.step_dependency_table == True) & (s.id_characteristic_table.isna())): + if np.any(vl & (s.step_dependency_table is True) & (pd.isna(s.id_characteristic_table))): raise UserWarning("Shunts with step_dependency_table True and id_characteristic_table NA detected.\n" "Please set an id_characteristic_table or set step_dependency_table to False.") - elif (np.any(vl & s.step_dependency_table == False - & ~s.id_characteristic_table.isna())): + elif (np.any(vl & s.step_dependency_table is False + & ~pd.isna(s.id_characteristic_table))): warnings.warn("Shunts with step_dependency_table False but id_characteristic_table detected.", category=UserWarning) s.step_dependency_table.fillna(False) diff --git a/pandapower/convert_format.py b/pandapower/convert_format.py index c4cfa7508..25a795aa9 100644 --- a/pandapower/convert_format.py +++ b/pandapower/convert_format.py @@ -43,7 +43,7 @@ def convert_format(net, elements_to_deserialize=None): _convert_geo_data(net, elements_to_deserialize) _convert_group_element_index(net) _convert_trafo_controller_parameter_names(net) - _convert_trafo_pst_logic(net) + convert_trafo_pst_logic(net) if Version(str(net.format_version)) < Version("2.4.0"): _convert_bus_pq_meas_to_load_reference(net, elements_to_deserialize) if Version(str(net.format_version)) < Version("2.0.0"): @@ -68,7 +68,7 @@ def _convert_geo_data(net, elements_to_deserialize=None): if ((_check_elements_to_deserialize('bus_geodata', elements_to_deserialize) and _check_elements_to_deserialize('bus', elements_to_deserialize)) or (_check_elements_to_deserialize('line_geodata', elements_to_deserialize) - and _check_elements_to_deserialize('line', elements_to_deserialize))): + and _check_elements_to_deserialize('line', elements_to_deserialize))): if hasattr(net, 'bus_geodata') or hasattr(net, 'line_geodata'): if Version(str(net.format_version)) < Version("1.6"): net.bus_geodata = pd.DataFrame.from_dict(net.bus_geodata) @@ -155,6 +155,7 @@ def _convert_trafo_controller_parameter_names(net): if "controlled_bus" in controller.__dict__.keys(): controller.__dict__["trafobus"] = controller.__dict__.pop("controlled_bus") + def _convert_bus_pq_meas_to_load_reference(net, elements_to_deserialize): if _check_elements_to_deserialize('measurement', elements_to_deserialize): bus_pq_meas_mask = net.measurement.measurement_type.isin(["p", "q"]) & \ @@ -551,7 +552,10 @@ def _update_characteristics(net, elements_to_deserialize): c.kwargs = {"kind": c.__dict__.pop("kind"), "bounds_error": False, "fill_value": c.__dict__.pop("fill_value")} -def _convert_trafo_pst_logic(net): +def convert_trafo_pst_logic(net): + """ + Converts trafo and trafo3w phase shifter logic to version 3.0 or later + """ for trafotable in ["trafo", "trafo3w"]: if trafotable in net and isinstance(net[trafotable], pd.DataFrame): if net[trafotable].index.size > 0: diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index 479d38609..2dc1e8f73 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -444,7 +444,8 @@ def _prepare_trafos_cim16(self, power_trafo2w: pd.DataFrame) -> pd.DataFrame: # a list of transformer parameters which are used for each transformer winding copy_list = ['index_bus', 'Terminal', 'ratedU', 'r', 'x', 'b', 'g', 'r0', 'x0', 'neutralStep', 'lowStep', 'highStep', 'stepVoltageIncrement', 'stepPhaseShiftIncrement', 'step', 'connected', - 'phaseAngleClock', 'connectionKind', sc['pte_id'], sc['tc'], sc['tc_id'], 'grounded', 'angle'] + 'phaseAngleClock', 'connectionKind', sc['pte_id'], sc['tc'], sc['tc_id'], 'grounded', 'angle', + 'tap_phase_shifter_type'] for one_item in copy_list: # copy the columns which are required for each winding power_trafo2w[one_item + '_lv'] = power_trafo2w[one_item].copy() @@ -457,7 +458,7 @@ def _prepare_trafos_cim16(self, power_trafo2w: pd.DataFrame) -> pd.DataFrame: power_trafo2w.loc[power_trafo2w['step_lv'].notna(), 'tap_side'] = 'lv' power_trafo2w.loc[power_trafo2w['step'].notna(), 'tap_side'] = 'hv' fillna_list = ['neutralStep', 'lowStep', 'highStep', 'stepVoltageIncrement', 'stepPhaseShiftIncrement', 'step', - sc['tc'], sc['tc_id']] + sc['tc'], sc['tc_id'], 'tap_phase_shifter_type'] for one_item in fillna_list: power_trafo2w[one_item] = power_trafo2w[one_item].fillna(power_trafo2w[one_item + '_lv']) del fillna_list, one_item @@ -532,7 +533,8 @@ def _prepare_trafo3w_cim16(self, power_trafo3w: pd.DataFrame) -> pd.DataFrame: # a list of transformer parameters which are used for each transformer winding copy_list = ['index_bus', 'Terminal', 'ratedS', 'ratedU', 'r', 'x', 'b', 'g', 'r0', 'x0', 'neutralStep', 'lowStep', 'highStep', 'stepVoltageIncrement', 'stepPhaseShiftIncrement', 'step', 'connected', - 'angle', 'phaseAngleClock', 'connectionKind', 'grounded', sc['pte_id'], sc['tc'], sc['tc_id']] + 'angle', 'phaseAngleClock', 'connectionKind', 'grounded', sc['pte_id'], sc['tc'], sc['tc_id'], + 'tap_phase_shifter_type'] for one_item in copy_list: # copy the columns which are required for each winding power_trafo3w[one_item + '_mv'] = power_trafo3w[one_item].copy() @@ -550,7 +552,7 @@ def _prepare_trafo3w_cim16(self, power_trafo3w: pd.DataFrame) -> pd.DataFrame: power_trafo3w.loc[power_trafo3w['step_mv'].notna(), 'tap_side'] = 'mv' power_trafo3w.loc[power_trafo3w['step'].notna(), 'tap_side'] = 'hv' fillna_list = ['neutralStep', 'lowStep', 'highStep', 'stepVoltageIncrement', 'stepPhaseShiftIncrement', 'step', - sc['tc'], sc['tc_id']] + sc['tc'], sc['tc_id'], 'tap_phase_shifter_type'] for one_item in fillna_list: power_trafo3w[one_item] = power_trafo3w[one_item].fillna(power_trafo3w[one_item + '_mv']) power_trafo3w[one_item] = power_trafo3w[one_item].fillna(power_trafo3w[one_item + '_lv']) diff --git a/pandapower/test/converter/test_from_powerfactory.py b/pandapower/test/converter/test_from_powerfactory.py index 838785f07..06bbb4b02 100644 --- a/pandapower/test/converter/test_from_powerfactory.py +++ b/pandapower/test/converter/test_from_powerfactory.py @@ -8,7 +8,6 @@ from pandapower.converter.powerfactory.validate import validate_pf_conversion from pandapower.converter.powerfactory.export_pfd_to_pp import import_project, from_pfd -from pandapower.convert_format import _convert_trafo_pst_logic try: import pandaplan.core.pplog as logging From 42c05db4ca731758fd9c2f872e3b6e5204d3fec0 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Tue, 17 Dec 2024 17:11:47 +0200 Subject: [PATCH 059/125] fix bug in test_shunt_step_dependency_warning() function --- pandapower/build_bus.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pandapower/build_bus.py b/pandapower/build_bus.py index 13cbaa519..7057787d9 100644 --- a/pandapower/build_bus.py +++ b/pandapower/build_bus.py @@ -642,10 +642,10 @@ def _calc_shunts_and_add_on_ppc(net, ppc): v_ratio = (ppc["bus"][bus_lookup[s["bus"].values], BASE_KV] / s["vn_kv"].values) ** 2 * base_multiplier if "step_dependency_table" in s: - if np.any(vl & (s.step_dependency_table is True) & (pd.isna(s.id_characteristic_table))): + if np.any(vl & (s.step_dependency_table == True) & (pd.isna(s.id_characteristic_table))): raise UserWarning("Shunts with step_dependency_table True and id_characteristic_table NA detected.\n" "Please set an id_characteristic_table or set step_dependency_table to False.") - elif (np.any(vl & s.step_dependency_table is False + elif (np.any(vl & s.step_dependency_table == False & ~pd.isna(s.id_characteristic_table))): warnings.warn("Shunts with step_dependency_table False but id_characteristic_table detected.", category=UserWarning) From 462e87113b6e0a33444e618ef51eb0fd54febd54 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Tue, 17 Dec 2024 17:57:06 +0200 Subject: [PATCH 060/125] fix deprecation warnings --- pandapower/test/loadflow/test_runpp.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pandapower/test/loadflow/test_runpp.py b/pandapower/test/loadflow/test_runpp.py index 0ce7d9948..6f9207c82 100644 --- a/pandapower/test/loadflow/test_runpp.py +++ b/pandapower/test/loadflow/test_runpp.py @@ -783,7 +783,7 @@ def test_zip_loads_out_of_service(): pp.create_line(net, from_bus=bus2, to_bus=bus3, length_km=0.1, std_type="NAYY 4x50 SE", name="Line") - net1 = net.deepcopy() + net1 = copy.deepcopy(net) oos_load = pp.create_load( net1, bus=bus3, p_mw=0.100, q_mvar=0.05, in_service=False, const_i_percent=0, const_z_percent=100) @@ -1331,7 +1331,7 @@ def test_tap_dependent_impedance(): tap_pos=0, tap_step_percent=0., tap_min=-2, tap_max=2, tap_phase_shifter_type=0) - net_backup = net.deepcopy() + net_backup = copy.deepcopy(net) net["trafo_characteristic_table"] = pd.DataFrame( {'id_characteristic': [0, 0, 0, 0, 0], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [0.95, 0.975, 1, 1.025, 1.05], From 906b12156ef6651d379779f5b89c660941734a88 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Wed, 18 Dec 2024 10:36:42 +0200 Subject: [PATCH 061/125] add shunt_characteristic_table_diagnostic function --- pandapower/control/util/diagnostic.py | 72 ++++++++++++++++++++++----- 1 file changed, 60 insertions(+), 12 deletions(-) diff --git a/pandapower/control/util/diagnostic.py b/pandapower/control/util/diagnostic.py index 3603bfe1c..c8c26de75 100644 --- a/pandapower/control/util/diagnostic.py +++ b/pandapower/control/util/diagnostic.py @@ -12,6 +12,8 @@ except: import logging as pplog +import warnings + logger = pplog.getLogger(__name__) @@ -83,10 +85,9 @@ def trafo_characteristic_table_diagnostic(net): (~net[trafo_table]['tap_dependency_table'] & net[trafo_table]['id_characteristic_table'].notna()) ].shape[0] if mismatch != 0: - raise UserWarning( - f"{trafo_table}: found {mismatch} transformer(s) with not both " - f"tap_dependency_table and id_characteristic_table parameters populated. " - f"Power flow calculation will raise an error.") + warnings.warn(f"{trafo_table}: found {mismatch} transformer(s) with not both " + f"tap_dependency_table and id_characteristic_table parameters populated. " + f"Power flow calculation will raise an error.", category=UserWarning) # check if all relevant columns are populated in the trafo_characteristic_table temp = net[trafo_table].dropna(subset=["id_characteristic_table"])[ ["tap_dependency_table", "id_characteristic_table"]] @@ -94,18 +95,65 @@ def trafo_characteristic_table_diagnostic(net): right_on="id_characteristic", how="inner") unpopulated = merged_df.loc[~merged_df[cols].notna().all(axis=1)] if not unpopulated.empty: - raise UserWarning(f"There are some transformers in the {trafo_table} table with not all characteristics " - f"populated in the trafo_characteristic_table.") + warnings.warn(f"There are some transformers in the {trafo_table} table with not all " + f"characteristics populated in the trafo_characteristic_table.", category=UserWarning) # check tap_dependency_table & id_characteristic_table column types if net[trafo_table]['tap_dependency_table'].dtype != 'bool': - raise UserWarning(f"The tap_dependency_table column in the {trafo_table} table is not of bool type.") + warnings.warn(f"The tap_dependency_table column in the {trafo_table} table is not of bool type.", + category=UserWarning) if net[trafo_table]['id_characteristic_table'].dtype != 'Int64': - raise UserWarning(f"The id_characteristic_table column in the {trafo_table} table is not of Int64 type.") + warnings.warn(f"The id_characteristic_table column in the {trafo_table} table is not of Int64 type.", + category=UserWarning) # check if all id_characteristic_table values are present in id_characteristic column # of trafo_characteristic_table if not net[trafo_table]['id_characteristic_table'].isin( net["trafo_characteristic_table"]['id_characteristic']).all(): - raise UserWarning(f"Not all id_characteristic_table values in the {trafo_table} table are present" - f"in id_characteristic column of trafo_characteristic_table. " - f"Power flow calculation will raise an error.") - return True + warnings.warn(f"Not all id_characteristic_table values in the {trafo_table} table are present" + f"in id_characteristic column of trafo_characteristic_table. " + f"Power flow calculation will raise an error.", category=UserWarning) + + +def shunt_characteristic_table_diagnostic(net): + logger.info("Checking shunt characteristic table") + if "shunt_characteristic_table" not in net: + logger.info("No shunt characteristic table found") + return False + cols = ["id_characteristic", "step", "q_mvar", "p_mw"] + if len(net["shunt"]) == 0 or \ + not all(col in net["shunt"] for col in ['id_characteristic_table', 'step_dependency_table']) or \ + (not net["shunt"]['id_characteristic_table'].notna().any() and + not net["shunt"]['step_dependency_table'].any()): + logger.info("No %s with step-dependent characteristics found." % "shunt") + return False + # check if both step_dependency_table & id_characteristic_table columns are populated + mismatch = net["shunt"][ + (net["shunt"]['step_dependency_table'] & net["shunt"]['id_characteristic_table'].isna()) | + (~net["shunt"]['step_dependency_table'] & net["shunt"]['id_characteristic_table'].notna()) + ].shape[0] + if mismatch != 0: + warnings.warn(f"Found {mismatch} shunt(s) with not both " + f"step_dependency_table and id_characteristic_table parameters populated. " + f"Power flow calculation will raise an error.", category=UserWarning) + # check if all relevant columns are populated in the shunt_characteristic_table + temp = net["shunt"].dropna(subset=["id_characteristic_table"])[ + ["step_dependency_table", "id_characteristic_table"]] + merged_df = temp.merge(net["shunt_characteristic_table"], left_on="id_characteristic_table", + right_on="id_characteristic", how="inner") + unpopulated = merged_df.loc[~merged_df[cols].notna().all(axis=1)] + if not unpopulated.empty: + warnings.warn(f"There are some shunts with not all " + "characteristics populated in the shunt_characteristic_table.", category=UserWarning) + # check step_dependency_table & id_characteristic_table column types + if net["shunt"]['step_dependency_table'].dtype != 'bool': + warnings.warn("The step_dependency_table column in the shunt table is not of bool type.", + category=UserWarning) + if net["shunt"]['id_characteristic_table'].dtype != 'Int64': + warnings.warn("The id_characteristic_table column in the shunt table is not of Int64 type.", + category=UserWarning) + # check if all id_characteristic_table values are present in id_characteristic column + # of shunt_characteristic_table + if not net["shunt"]['id_characteristic_table'].isin( + net["shunt_characteristic_table"]['id_characteristic']).all(): + warnings.warn("Not all id_characteristic_table values in the shunt table are present" + "in id_characteristic column of shunt_characteristic_table. " + "Power flow calculation will raise an error.", category=UserWarning) From 6cfd2a74819944c810395a3e5f001fb22d5058c5 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Wed, 18 Dec 2024 10:38:31 +0200 Subject: [PATCH 062/125] fix bug in build_bus.py --- pandapower/build_bus.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/pandapower/build_bus.py b/pandapower/build_bus.py index 7057787d9..a1b7a2f9b 100644 --- a/pandapower/build_bus.py +++ b/pandapower/build_bus.py @@ -645,8 +645,7 @@ def _calc_shunts_and_add_on_ppc(net, ppc): if np.any(vl & (s.step_dependency_table == True) & (pd.isna(s.id_characteristic_table))): raise UserWarning("Shunts with step_dependency_table True and id_characteristic_table NA detected.\n" "Please set an id_characteristic_table or set step_dependency_table to False.") - elif (np.any(vl & s.step_dependency_table == False - & ~pd.isna(s.id_characteristic_table))): + elif np.any(vl & (s.step_dependency_table == False) & (~pd.isna(s.id_characteristic_table))): warnings.warn("Shunts with step_dependency_table False but id_characteristic_table detected.", category=UserWarning) s.step_dependency_table.fillna(False) From cb45c18e26c5448195dd24ae1a6ae0cebd6cc502 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Wed, 18 Dec 2024 12:27:04 +0200 Subject: [PATCH 063/125] fix bug in cgmes converter --- .../transformers/powerTransformersCim16.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index 2dc1e8f73..0aea9493f 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -355,11 +355,13 @@ def _prepare_power_transformers_cim16(self) -> pd.DataFrame: ptct = ptct.drop(drop_index) continue one_df = one_df.set_index('step') + current_step = one_df['current_step'].iloc[0] neutral_step = one_df['neutralStep'].iloc[0] ptct = ptct.drop(drop_index) - # keep the angle and ratio based on neutral tap position - ptct.loc[keep_index, 'angle'] = one_df.loc[neutral_step, 'angle'] - ptct.loc[keep_index, 'ratio'] = one_df.loc[neutral_step, 'ratio'] + # calculate the angle and ratio per tap based on the current tap position + ptct.loc[keep_index, 'angle'] = one_df.loc[current_step, 'angle'] / max(1, abs(current_step - neutral_step)) + ptct.loc[keep_index, 'ratio'] = \ + (one_df.loc[current_step, 'ratio'] - 1) * 100 / max(1, abs(current_step - neutral_step)) ptct = ptct.drop(columns=['rdfId', 'PhaseTapChangerTable', 'step']) ptct = ptct.rename(columns={'current_step': 'step'}) ptct['stepPhaseShiftIncrement'] = ptct['angle'][:] From 86f66f19359b8b311e94e7f2a7e4546e0af9465b Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Wed, 18 Dec 2024 11:53:02 +0100 Subject: [PATCH 064/125] WIP pf_converter --- .../powerfactory/pp_import_functions.py | 270 +++++++++++++++--- 1 file changed, 236 insertions(+), 34 deletions(-) diff --git a/pandapower/converter/powerfactory/pp_import_functions.py b/pandapower/converter/powerfactory/pp_import_functions.py index 2bda5ad4c..9278df1b4 100644 --- a/pandapower/converter/powerfactory/pp_import_functions.py +++ b/pandapower/converter/powerfactory/pp_import_functions.py @@ -29,8 +29,10 @@ bus_dict = {} grf_map = {} - # import network to pandapower: +import pandas as pd + + def from_pf( dict_net, pv_as_slack=True, @@ -639,13 +641,14 @@ def get_coords_from_buses(net, from_bus, to_bus, **kwargs): from_geo: Optional[str] = None to_geo: Optional[str] = None if from_bus in net.bus.index: - from_geo: str = net.bus.loc[from_bus, ['geo']] + from_geo: str = net.bus.loc[from_bus, 'geo'] if to_bus in net.bus.index: - to_geo: str = net.bus.loc[to_bus, ['geo']] + to_geo: str = net.bus.loc[to_bus, 'geo'] if from_geo and to_geo: coords = [geojson.utils.coords(geojson.loads(from_geo)), geojson.utils.coords(geojson.loads(to_geo))] + coords = [tuple((x, y)) for item in coords for x, y in item] logger.debug('got coords from buses: %s' % coords) else: logger.debug('no coords for line between buses %d and %d' % (from_bus, to_bus)) @@ -2290,14 +2293,18 @@ def create_trafo_type(net, item): "tap_side": ['hv', 'lv', 'ext'][item.tap_side], # 'ext' not implemented } + type_data.update({"tap_phase_shifter_type": pd.NA}) + type_data.update({"tap2_phase_shifter_type": pd.NA}) + if item.itapch: logger.debug('trafo <%s> has tap changer' % name) + type_data.update({ # see if it is an ideal phase shifter or a complex phase shifter # checking tap_step_percent because a nonzero value for ideal phase shifter can be stored in the object "tap_step_percent": item.dutap if item.tapchtype != 1 else 0, "tap_step_degree": item.dphitap if item.tapchtype == 1 else item.phitr, - "tap_phase_shifter": True if item.tapchtype == 1 else False, + "tap_phase_shifter_type": item.tapchtype, "tap_max": item.ntpmx, "tap_min": item.ntpmn, "tap_neutral": item.nntap0 @@ -2316,7 +2323,7 @@ def create_trafo_type(net, item): # checking tap_step_percent because a nonzero value for ideal phase shifter can be stored in the object "tap2_step_percent": item.dutap2 if item.tapchtype2 != 1 else 0, "tap2_step_degree": item.dphitap2 if item.tapchtype2 == 1 else item.phitr2, - "tap2_phase_shifter": True if item.tapchtype2 == 1 else False, + "tap2_phase_shifter_type": item.tapchtype2, "tap2_max": item.ntpmx2, "tap2_min": item.ntpmn2, "tap2_neutral": item.nntap02 @@ -2380,20 +2387,129 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc tap_pos2 = item.GetAttribute("c:nntap2") if std_type is not None: + use_tap_table = item.GetAttribute("iTaps") + if use_tap_table == 1: + if "trafo_characteristic_table" not in net: + net["trafo_characteristic_table"] = pd.DataFrame( + columns=['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent', + 'vk_hv_percent', 'vkr_hv_percent', 'vk_mv_percent', 'vkr_mv_percent', 'vk_lv_percent', + 'vkr_lv_percent']) + + last_index = net["trafo_characteristic_table"]['id_characteristic'].max() if not net[ + "trafo_characteristic_table"].empty else -1 + new_id_characteristic_table = last_index + 1 + tap_min = pf_type.ntpmn + tap_max = pf_type.ntpmx + meas_side = 1 if item.GetAttribute("iMeasLoc") == 1 else 2 + + steps = list(range(tap_min, tap_max + 1)) + + new_tap_table = pd.DataFrame(item.GetAttribute("mTaps"), + columns=['voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent', + 'ignore']) + new_tap_table = new_tap_table.drop(columns='ignore') + new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn_h if meas_side == 1 \ + else new_tap_table["voltage_ratio"] / pf_type.utrn_l + new_tap_table["vkr_percent"] = new_tap_table["vkr_percent"] / item.GetAttribute("Snom_a") # pf_type.strn + + if len(new_tap_table) == len(steps): + new_tap_table['step'] = steps[:len(new_tap_table)] + else: + raise ValueError("The number of steps differs from the number of rows in new_tap_table.") + new_tap_table['id_characteristic'] = new_id_characteristic_table + + missing_columns = set(net["trafo_characteristic_table"].columns) - set(new_tap_table.columns) + for col in missing_columns: + new_tap_table[col] = np.nan + + net["trafo_characteristic_table"] = pd.concat([net["trafo_characteristic_table"], new_tap_table], + ignore_index=True) + + tap_dependency_table = True + tap_phase_shifter_type = pf_type.tapchtype if pf_type.itapch else -1 + id_characteristic_table = new_id_characteristic_table + else: + id_characteristic_table = np.nan + tap_dependency_table = False + tap_phase_shifter_type = np.nan + + # tap_phase_shifter_type = tap_phase_shifter_type + tid = pp.create_transformer(net, hv_bus=bus1, lv_bus=bus2, name=name, std_type=std_type, tap_pos=tap_pos, + tap_dependency_table=tap_dependency_table, + tap_phase_shifter_type=tap_phase_shifter_type, + id_characteristic_table=id_characteristic_table, in_service=in_service, parallel=item.ntnum, df=item.ratfac, tap2_pos=tap_pos2, leakage_resistance_ratio_hv=pf_type.itrdr, leakage_reactance_ratio_hv=pf_type.itrdl) trafo_dict[item] = tid logger.debug('created trafo at index <%d>' % tid) else: logger.info("Create Trafo 3ph") + use_tap_table = item.GetAttribute("iTaps") + if use_tap_table == 1: + if "trafo_characteristic_table" not in net: + net["trafo_characteristic_table"] = pd.DataFrame( + columns=['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent', + 'vk_hv_percent', 'vkr_hv_percent', 'vk_mv_percent', 'vkr_mv_percent', 'vk_lv_percent', + 'vkr_lv_percent']) + + last_index = net["trafo_characteristic_table"]['id_characteristic'].max() if not net[ + "trafo_characteristic_table"].empty else -1 + new_id_characteristic_table = last_index + 1 + tap_min = pf_type.ntpmn + tap_max = pf_type.ntpmx + tap_side = item.GetAttribute("tap_side") + meas_side = item.GetAttribute("iMeasLoc") + + steps = list(range(tap_min, tap_max + 1)) + + new_tap_table = pd.DataFrame(item.GetAttribute("mTaps"), + columns=['voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent', + 'ignore']) + new_tap_table = new_tap_table.drop(columns='ignore') + + if meas_side == 0: + new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn_h if tap_side == 0 else new_tap_table["voltage_ratio"] / pf_type.utrn_l + elif meas_side == 1: + new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn_l if tap_side == 0 else new_tap_table["voltage_ratio"] / pf_type.utrn_h + + #0 heißt an derselben Seite + + new_tap_table["vkr_percent"] = new_tap_table["vkr_percent"] / item.GetAttribute("Snom_a") # pf_type.strn + # Sn_MVA = pf_type.strn + # new_tap_table["vkr_percent"] = (new_tap_table["vk_percent"] ** 2) / (new_tap_table["vkr_percent"] * Sn_MVA) + + if len(new_tap_table) == len(steps): + new_tap_table['step'] = steps[:len(new_tap_table)] + else: + raise ValueError("The number of steps differs from the number of rows in new_tap_table.") + new_tap_table['id_characteristic'] = new_id_characteristic_table + + missing_columns = set(net["trafo_characteristic_table"].columns) - set(new_tap_table.columns) + for col in missing_columns: + new_tap_table[col] = np.nan + + net["trafo_characteristic_table"] = pd.concat([net["trafo_characteristic_table"], new_tap_table], + ignore_index=True) + tap_dependency_table = True + tap_phase_shifter_type = pf_type.tapchtype if pf_type.itapch else -1 + id_characteristic_table = new_id_characteristic_table + else: + id_characteristic_table = np.nan + tap_dependency_table = False + tap_phase_shifter_type = np.nan + tid = pp.create_transformer_from_parameters( net, hv_bus=bus1, lv_bus=bus2, name=name, tap_pos=tap_pos, + tap_side=tap_side, + tap_phase_shifter_type=tap_phase_shifter_type, + id_characteristic_table=id_characteristic_table, + tap_dependency_table=tap_dependency_table, in_service=in_service, parallel=item.ntnum, df=item.ratfac, @@ -2465,17 +2581,17 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc add_additional_attributes(item, net, element='trafo', element_id=tid, attr_dict={'e:cpSite.loc_name': 'site', 'for_name': 'equipment', "cimRdfId": "origin_id"}) - if pf_type.itapzdep: - x_points = (net.trafo.at[tid, "tap_min"], net.trafo.at[tid, "tap_neutral"], net.trafo.at[tid, "tap_max"]) - vk_min, vk_neutral, vk_max = pf_type.uktmn, net.trafo.at[tid, "vk_percent"], pf_type.uktmx - vkr_min, vkr_neutral, vkr_max = pf_type.ukrtmn, net.trafo.at[tid, "vkr_percent"], pf_type.ukrtmx - # todo - # vk0_min, vk0_max = pf_type.uk0tmn, pf_type.uk0tmx - # vkr0_min, vkr0_max = pf_type.uk0rtmn, pf_type.uk0rtmx - pp.control._create_trafo_characteristics(net, trafotable="trafo", trafo_index=tid, variable="vk_percent", - x_points=x_points, y_points=(vk_min, vk_neutral, vk_max)) - pp.control._create_trafo_characteristics(net, trafotable="trafo", trafo_index=tid, variable="vkr_percent", - x_points=x_points, y_points=(vkr_min, vkr_neutral, vkr_max)) + # if pf_type.itapzdep: + # x_points = (net.trafo.at[tid, "tap_min"], net.trafo.at[tid, "tap_neutral"], net.trafo.at[tid, "tap_max"]) + # vk_min, vk_neutral, vk_max = pf_type.uktmn, net.trafo.at[tid, "vk_percent"], pf_type.uktmx + # vkr_min, vkr_neutral, vkr_max = pf_type.ukrtmn, net.trafo.at[tid, "vkr_percent"], pf_type.ukrtmx + # # todo + # # vk0_min, vk0_max = pf_type.uk0tmn, pf_type.uk0tmx + # # vkr0_min, vkr0_max = pf_type.uk0rtmn, pf_type.uk0rtmx + # pp.control.create_trafo_characteristics(net, trafotable="trafo", trafo_index=tid, variable="vk_percent", + # x_points=x_points, y_points=(vk_min, vk_neutral, vk_max)) + # pp.control.create_trafo_characteristics(net, trafotable="trafo", trafo_index=tid, variable="vkr_percent", + # x_points=x_points, y_points=(vkr_min, vkr_neutral, vkr_max)) def get_pf_trafo_results(net, item, tid, is_unbalanced): @@ -2562,6 +2678,75 @@ def create_trafo3w(net, item, tap_opt='nntap'): logger.warning("trafo3w %s has parallel=%d, this is not implemented. " "Calculation results will be incorrect." % (item.loc_name, item.nt3nm)) + + use_tap_table = item.GetAttribute("iTaps") + if use_tap_table == 1: + if "trafo_characteristic_table" not in net: + net["trafo_characteristic_table"] = pd.DataFrame( + columns=['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent', + 'vk_hv_percent', 'vkr_hv_percent', 'vk_mv_percent', 'vkr_mv_percent', 'vk_lv_percent', + 'vkr_lv_percent']) + + last_index = net["trafo_characteristic_table"]['id_characteristic'].max() if not net[ + "trafo_characteristic_table"].empty else -1 + new_id_characteristic_table = last_index + 1 + + new_tap_table = pd.DataFrame(item.GetAttribute("mTaps"), + columns=['voltage_ratio', 'angle_deg', 'vk_hv_percent', 'vkr_hv_percent', + 'vk_mv_percent', 'vkr_mv_percent', + 'vk_lv_percent', 'vkr_lv_percent']) + + if pf_type.itapzdep: + table_side = pf_type.itapzside + else: + table_side = item.GetAttribute("iMeasTap") + + if table_side == 0: + tap_min = pf_type.n3tmn_h + tap_max = pf_type.n3tmx_h + elif table_side == 1: + tap_min = pf_type.n3tmn_m + tap_max = pf_type.n3tmx_m + elif table_side == 2: + tap_min = pf_type.n3tmn_l + tap_max = pf_type.n3tmx_l + + steps = list(range(tap_min, tap_max + 1)) + + meas_side = item.GetAttribute("iMeasLoc") + + if meas_side == 0: + new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn3_h + elif meas_side == 1: + new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn3_m + elif meas_side == 2: + meas_side["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn3_l + + new_tap_table["vkr_hv_percent"] = new_tap_table["vkr_hv_percent"] / item.GetAttribute( + "Snom_h_a") # pf_type.strn3h + new_tap_table["vkr_mv_percent"] = new_tap_table["vkr_mv_percent"] / item.GetAttribute( + "Snom_m_a") # pf_type.strn3m + new_tap_table["vkr_lv_percent"] = new_tap_table["vkr_lv_percent"] / item.GetAttribute( + "Snom_l_a") # pf_type.strn3l + + if len(new_tap_table) == len(steps): + new_tap_table['step'] = steps[:len(new_tap_table)] + else: + raise ValueError("The number of steps differs from the number of rows in new_tap_table.") + new_tap_table['id_characteristic'] = new_id_characteristic_table + + missing_columns = set(net["trafo_characteristic_table"].columns) - set(new_tap_table.columns) + for col in missing_columns: + new_tap_table[col] = np.nan + + net["trafo_characteristic_table"] = pd.concat([net["trafo_characteristic_table"], new_tap_table], + ignore_index=True) + + params['tap_dependency_table'] = True + params['id_characteristic_table'] = new_id_characteristic_table + else: + params['tap_dependency_table'] = False + if item.HasAttribute('t:du3tp_h'): steps = [pf_type.du3tp_h, pf_type.du3tp_m, pf_type.du3tp_l] side = np.nonzero(steps)[0] @@ -2580,8 +2765,25 @@ def create_trafo3w(net, item, tap_opt='nntap'): logger.debug("got tap %f from c:n3tap" % tap_pos) else: raise ValueError('could not read current tap position: tap_opt = %s' % tap_opt) + + tap_step_percent = item.GetAttribute('t:du3tp_' + ts) + tap_step_degree = item.GetAttribute('t:ph3tr_' + ts) + + if (tap_step_degree is None or tap_step_degree == 0) and (tap_step_percent is None or tap_step_percent == 0): + tap_phase_shifter_type = pd.NA # net[trafotable].loc[mask_na, f"tap{t}_phase_shifter_type"] = pd.NA + # ratio/asymmetrical phase shifters + elif (tap_step_degree != 90 and tap_step_percent is not None and tap_step_percent != 0): + tap_phase_shifter_type = 0 # net[trafotable].loc[mask_ratio_asym, f"tap{t}_phase_shifter_type"] = 0 + # symmetrical phase shifters + elif (tap_step_degree == 90 and tap_step_percent is not None and tap_step_percent != 0): + tap_phase_shifter_type = 1 # net[trafotable].loc[mask_sym, f"tap{t}_phase_shifter_type"] = 1 + # ideal phase shifters + elif (tap_step_degree is not None and tap_step_degree != 0 and (tap_step_percent is None or tap_step_percent == 0)): + tap_phase_shifter_type = 2 # net[trafotable].loc[mask_ideal, f"tap{t}_phase_shifter_type"] = 2 + params.update({ 'tap_side': ts + 'v', # hv, mv, lv + 'tap_phase_shifter_type': tap_phase_shifter_type, 'tap_step_percent': item.GetAttribute('t:du3tp_' + ts), 'tap_step_degree': item.GetAttribute('t:ph3tr_' + ts), 'tap_min': item.GetAttribute('t:n3tmn_' + ts), @@ -2622,22 +2824,22 @@ def create_trafo3w(net, item, tap_opt='nntap'): # TODO Implement the tap changer controller for 3-winding transformer - if pf_type.itapzdep: - x_points = (net.trafo3w.at[tid, "tap_min"], net.trafo3w.at[tid, "tap_neutral"], net.trafo3w.at[tid, "tap_max"]) - for side in ("hv", "mv", "lv"): - vk_min = pf_type.GetAttribute(f"uktr3mn_{side[0]}") - vk_neutral = net.trafo3w.at[tid, f"vk_{side}_percent"] - vk_max = pf_type.GetAttribute(f"uktr3mx_{side[0]}") - vkr_min = pf_type.GetAttribute(f"uktrr3mn_{side[0]}") - vkr_neutral = net.trafo3w.at[tid, f"vkr_{side}_percent"] - vkr_max = pf_type.GetAttribute(f"uktrr3mx_{side[0]}") - # todo zero-sequence parameters (must be implemented in build_branch first) - pp.control._create_trafo_characteristics(net, trafotable="trafo3w", trafo_index=tid, - variable=f"vk_{side}_percent", x_points=x_points, - y_points=(vk_min, vk_neutral, vk_max)) - pp.control._create_trafo_characteristics(net, trafotable="trafo3w", trafo_index=tid, - variable=f"vkr_{side}_percent", x_points=x_points, - y_points=(vkr_min, vkr_neutral, vkr_max)) + # if pf_type.itapzdep: + # x_points = (net.trafo3w.at[tid, "tap_min"], net.trafo3w.at[tid, "tap_neutral"], net.trafo3w.at[tid, "tap_max"]) + # for side in ("hv", "mv", "lv"): + # vk_min = pf_type.GetAttribute(f"uktr3mn_{side[0]}") + # vk_neutral = net.trafo3w.at[tid, f"vk_{side}_percent"] + # vk_max = pf_type.GetAttribute(f"uktr3mx_{side[0]}") + # vkr_min = pf_type.GetAttribute(f"uktrr3mn_{side[0]}") + # vkr_neutral = net.trafo3w.at[tid, f"vkr_{side}_percent"] + # vkr_max = pf_type.GetAttribute(f"uktrr3mx_{side[0]}") + # # todo zero-sequence parameters (must be implemented in build_branch first) + # pp.control.create_trafo_characteristics(net, trafotable="trafo3w", trafo_index=tid, + # variable=f"vk_{side}_percent", x_points=x_points, + # y_points=(vk_min, vk_neutral, vk_max)) + # pp.control.create_trafo_characteristics(net, trafotable="trafo3w", trafo_index=tid, + # variable=f"vkr_{side}_percent", x_points=x_points, + # y_points=(vkr_min, vkr_neutral, vkr_max)) def propagate_bus_coords(net, bus1, bus2): @@ -2747,8 +2949,8 @@ def calc_p_mw_and_q_mvar(r: float, x: float) -> tuple[float, float]: x_val = item.xrea elif item.shtype == 2: # Shunt is a capacitor bank - b = item.bcap*1e-6 - g = item.gparac*1e-6 + b = item.bcap * 1e-6 + g = item.gparac * 1e-6 r_val = g / (g ** 2 + b ** 2) x_val = -b / (g ** 2 + b ** 2) From ca4a0eb37ccc3d146538c59dad6608e18f44ce90 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Wed, 18 Dec 2024 12:56:51 +0200 Subject: [PATCH 065/125] improve control/util/diagnostic.py lib --- pandapower/control/util/diagnostic.py | 28 ++++++++++++++++----------- 1 file changed, 17 insertions(+), 11 deletions(-) diff --git a/pandapower/control/util/diagnostic.py b/pandapower/control/util/diagnostic.py index c8c26de75..121f82e70 100644 --- a/pandapower/control/util/diagnostic.py +++ b/pandapower/control/util/diagnostic.py @@ -80,14 +80,22 @@ def trafo_characteristic_table_diagnostic(net): logger.info("No %s with tap-dependent characteristics found." % trafo_table) continue # check if both tap_dependency_table & id_characteristic_table columns are populated - mismatch = net[trafo_table][ + mismatch_a = net[trafo_table][ (net[trafo_table]['tap_dependency_table'] & net[trafo_table]['id_characteristic_table'].isna()) | (~net[trafo_table]['tap_dependency_table'] & net[trafo_table]['id_characteristic_table'].notna()) ].shape[0] - if mismatch != 0: - warnings.warn(f"{trafo_table}: found {mismatch} transformer(s) with not both " + if mismatch_a != 0: + warnings.warn(f"{trafo_table}: found {mismatch_a} transformer(s) with not both " f"tap_dependency_table and id_characteristic_table parameters populated. " f"Power flow calculation will raise an error.", category=UserWarning) + # check if both tap_dependency_table & tap_phase_shifter_type columns are populated + mismatch_b = net[trafo_table][ + (net[trafo_table]['tap_dependency_table'] & net[trafo_table]['tap_phase_shifter_type'].isna()) + ].shape[0] + if mismatch_b != 0: + warnings.warn(f"{trafo_table}: found {mismatch_b} transformer(s) with tap_dependency_table set to " + f"True and tap_phase_shifter_type parameter not populated. The characteristics from " + f"trafo_characteristic_table will not be considered.", category=UserWarning) # check if all relevant columns are populated in the trafo_characteristic_table temp = net[trafo_table].dropna(subset=["id_characteristic_table"])[ ["tap_dependency_table", "id_characteristic_table"]] @@ -106,11 +114,10 @@ def trafo_characteristic_table_diagnostic(net): category=UserWarning) # check if all id_characteristic_table values are present in id_characteristic column # of trafo_characteristic_table - if not net[trafo_table]['id_characteristic_table'].isin( + if not net[trafo_table]['id_characteristic_table'].dropna().isin( net["trafo_characteristic_table"]['id_characteristic']).all(): - warnings.warn(f"Not all id_characteristic_table values in the {trafo_table} table are present" - f"in id_characteristic column of trafo_characteristic_table. " - f"Power flow calculation will raise an error.", category=UserWarning) + warnings.warn(f"Not all id_characteristic_table values in the {trafo_table} table are present " + f"in id_characteristic column of trafo_characteristic_table.", category=UserWarning) def shunt_characteristic_table_diagnostic(net): @@ -152,8 +159,7 @@ def shunt_characteristic_table_diagnostic(net): category=UserWarning) # check if all id_characteristic_table values are present in id_characteristic column # of shunt_characteristic_table - if not net["shunt"]['id_characteristic_table'].isin( + if not net["shunt"]['id_characteristic_table'].dropna().isin( net["shunt_characteristic_table"]['id_characteristic']).all(): - warnings.warn("Not all id_characteristic_table values in the shunt table are present" - "in id_characteristic column of shunt_characteristic_table. " - "Power flow calculation will raise an error.", category=UserWarning) + warnings.warn("Not all id_characteristic_table values in the shunt table are present " + "in id_characteristic column of shunt_characteristic_table.", category=UserWarning) From a8a3b6371b9977b14f91cfa1bc70a59f89e44a4a Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Wed, 18 Dec 2024 15:22:53 +0200 Subject: [PATCH 066/125] update documentation for trafo characteristics --- doc/elements/trafo.rst | 38 +++++++++++++++++++++++++++- doc/elements/trafo3w.rst | 38 +++++++++++++++++++++++++++- doc/elements/trafo3w_char_spline.csv | 3 +++ doc/elements/trafo3w_char_table.csv | 19 ++++++++++++++ doc/elements/trafo3w_par.csv | 7 +++-- doc/elements/trafo_char_spline.csv | 3 +++ doc/elements/trafo_char_table.csv | 19 ++++++++++++++ doc/elements/trafo_par.csv | 11 +++++--- 8 files changed, 130 insertions(+), 8 deletions(-) create mode 100644 doc/elements/trafo3w_char_spline.csv create mode 100644 doc/elements/trafo3w_char_table.csv create mode 100644 doc/elements/trafo_char_spline.csv create mode 100644 doc/elements/trafo_char_table.csv diff --git a/doc/elements/trafo.rst b/doc/elements/trafo.rst index c1d46df78..465d3c1f3 100644 --- a/doc/elements/trafo.rst +++ b/doc/elements/trafo.rst @@ -231,12 +231,48 @@ If both values are given for an ideal phase shift transformer, the power flow wi .. seealso:: - `ENTSO-E - Phase Shift Transformers Modelling, Version 1.0.0, May 2015 `_ + `ENTSO-E - Phase Shift Transformers Modelling, Version 1.0.0, May 2014 `_ `J. Verboomen, D. Van Hertem, P. H. Schavemaker, W. L. Kling and R. Belmans, "Phase shifting transformers: principles and applications," 2005 International Conference on Future Power Systems, Amsterdam, 2005 `_ +Trafo characteristic table +---------------------------- +A transformer characteristic table (trafo_characteristic_table) can be used to adjust the transformer parameters +(voltage ratio, angle, impedance) according to the selected tap position. This lookup table is created automatically +from version 3.0 onwards through the CIM CGMES to pandapower converter (if this information is available in the EQ +profile), or the user may define this table manually. The id_characteristic_table variable in net.trafo references +the id_characteristic column in net.trafo_characteristic_table per transformer. +If the tap_dependency_table variable in net.trafo is set to True, this indicates that there is a corresponding +characteristic available in net.trafo_characteristic_table, which overwrites the default trafo parameters +tap_step_percent, tap_step_degree, vk_percent and vkr_percent. + +The below table provides an example trafo_characteristic_table table, populated for two 2-winding transformers. + +.. tabularcolumns:: |p{0.10\linewidth}|p{0.55\linewidth}|p{0.15\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth} +.. csv-table:: + :file: trafo_char_table.csv + :delim: , + :widths: 10, 55, 15, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55 + +.. note:: + - tap_dependency_table has to be set to True, and id_characteristic_table and tap_phase_shifter_type variables need to be populated in order to consider the corresponding trafo_characteristic table values. + - Only one tap_dependency_table is supported per 2-winding transformer (there is no tap2_dependency_table variable) + +The function pandapower.control.trafo_characteristic_table_diagnostic can be used for sanity checks. +The function pandapower.control.create_trafo_characteristic_object can be used to automatically create +SplineCharacteristic objects and populate the net.trafo_characteristic_spline table according to the +net.trafo_characteristic_table table. An additional column id_characteristic_spline is also created in net.trafo +to set up the reference to the spline characteristics. + +The below table provides an example trafo_characteristic_spline table, populated for two 2-winding transformers. + +.. tabularcolumns:: |p{0.10\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth} +.. csv-table:: + :file: trafo_char_spline.csv + :delim: , + :widths: 10, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55 Result Parameters ========================== diff --git a/doc/elements/trafo3w.rst b/doc/elements/trafo3w.rst index 0c6ae0f94..3b0acffc7 100644 --- a/doc/elements/trafo3w.rst +++ b/doc/elements/trafo3w.rst @@ -141,8 +141,44 @@ is located at the star point of the three winding transformer or at the terminal .. seealso:: `MVA METHOD FOR 3-WINDING TRANSFORMER `_ +Trafo characteristic table +---------------------------- - +A transformer characteristic table (trafo_characteristic_table) can be used to adjust the 3-winding transformer parameters +(voltage ratio, angle, impedance) according to the selected tap position. This lookup table is created automatically +from version 3.0 onwards through the CIM CGMES to pandapower converter (if this information is available in the EQ +profile), or the user may define this table manually. The id_characteristic_table variable in net.trafo3w references +the id_characteristic column in net.trafo_characteristic_table per 3-winding transformer. + +If the tap_dependency_table variable in net.trafo3w is set to True, this indicates that there is a corresponding +characteristic available in net.trafo_characteristic_table, which overwrites the default 3-winding transformer parameters +tap_step_percent, tap_step_degree, vkr_hv_percent, vkr_mv_percent, vkr_lv_percent, vk_hv_percent, vk_mv_percent and +vk_lv_percent. + +The below table provides an example trafo_characteristic_table table, populated for two 3-winding transformers. + +.. tabularcolumns:: |p{0.10\linewidth}|p{0.55\linewidth}|p{0.15\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth} +.. csv-table:: + :file: trafo3w_char_table.csv + :delim: , + :widths: 10, 55, 15, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55 + +.. note:: + tap_dependency_table has to be set to True, and id_characteristic_table and tap_phase_shifter_type variables need to be populated in order to consider the corresponding trafo_characteristic table values. + +The function pandapower.control.trafo_characteristic_table_diagnostic can be used for sanity checks. +The function pandapower.control.create_trafo_characteristic_object can be used to automatically create +SplineCharacteristic objects and populate the net.trafo_characteristic_spline table according to the +net.trafo_characteristic_table table. An additional column id_characteristic_spline is also created in net.trafo3w +to set up the reference to the spline characteristics. + +The below table provides an example trafo_characteristic_spline table, populated for two 3-winding transformers. + +.. tabularcolumns:: |p{0.10\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth} +.. csv-table:: + :file: trafo3w_char_spline.csv + :delim: , + :widths: 10, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55 Result Parameters ========================== diff --git a/doc/elements/trafo3w_char_spline.csv b/doc/elements/trafo3w_char_spline.csv new file mode 100644 index 000000000..882617abf --- /dev/null +++ b/doc/elements/trafo3w_char_spline.csv @@ -0,0 +1,3 @@ +,id_characteristic,voltage_ratio_characteristic,angle_deg_characteristic,vk_percent_characteristic,vkr_percent_characteristic,vk_hv_percent_characteristic,vkr_hv_percent_characteristic,vk_mv_percent_characteristic,vkr_mv_percent_characteristic,vk_lv_percent_characteristic,vkr_lv_percent_characteristic +0,0,SplineCharacteristic,SplineCharacteristic,,,SplineCharacteristic,SplineCharacteristic,SplineCharacteristic,SplineCharacteristic,SplineCharacteristic,SplineCharacteristic +1,1,SplineCharacteristic,SplineCharacteristic,,,SplineCharacteristic,SplineCharacteristic,SplineCharacteristic,SplineCharacteristic,SplineCharacteristic,SplineCharacteristic diff --git a/doc/elements/trafo3w_char_table.csv b/doc/elements/trafo3w_char_table.csv new file mode 100644 index 000000000..852826818 --- /dev/null +++ b/doc/elements/trafo3w_char_table.csv @@ -0,0 +1,19 @@ +,id_characteristic,step,voltage_ratio,angle_deg,vk_percent,vkr_percent,vkr_hv_percent,vkr_mv_percent,vkr_lv_percent,vk_hv_percent,vk_mv_percent,vk_lv_percent +0,0,10,1.049230814,0,,,0.202038469,0.151000013,0.169759643,19.50770312,7.0000001,12.62692044 +1,0,11,1.036923051,0,,,0.202278839,0.151000013,0.169819736,19.38077652,7.0000001,12.59519014 +2,0,12,1.024615407,0,,,0.20251921,0.151000013,0.169879828,19.25385386,7.0000001,12.56346081 +3,0,13,1.012307644,0,,,0.202759595,0.151000013,0.169939925,19.12692371,7.0000001,12.53172959 +4,0,14,1,0,,,0.202999996,0.151000013,0.170000025,19.00000131,7.0000001,12.50000029 +5,0,15,0.987692297,0,,,0.203740375,0.151000013,0.17018512,18.92692004,7.0000001,12.48173115 +6,0,16,0.975384593,0,,,0.204480754,0.151000013,0.170370214,18.8538408,7.0000001,12.46346251 +7,0,17,0.963076949,0,,,0.205221133,0.151000013,0.170555309,18.78076168,7.0000001,12.44519387 +8,0,18,0.950769246,0,,,0.205961527,0.151000013,0.170740408,18.7076846,7.0000001,12.42692574 +9,1,1,0.990151525,-1.002313972,,,0.396666721,0.369999989,0.369999993,15.52653181,9.499999316,15.12530373 +10,1,2,0.992585003,-0.749875605,,,0.396666739,0.369999989,0.369999996,15.61989434,9.499999316,15.14397671 +11,1,3,0.995037675,-0.498676896,,,0.396666721,0.369999989,0.369999993,15.71325949,9.499999316,15.16265016 +12,1,4,0.99750942,-0.248718262,,,0.396666739,0.369999989,0.369999996,15.80662726,9.499999316,15.18132407 +13,1,5,1,0,,,0.396666774,0.369999989,0.370000003,15.90000215,9.499999316,15.19999936 +14,1,6,1.00472033,0.463003337,,,0.396666739,0.369999989,0.369999996,15.76878837,9.499999316,15.17375616 +15,1,7,1.00950563,0.921646893,,,0.396666739,0.369999989,0.369999996,15.63757528,9.499999316,15.14751298 +16,1,8,1.014354944,1.375934005,,,0.396666739,0.369999989,0.369999996,15.5063629,9.499999316,15.12126983 +17,1,9,1.019267559,1.825870156,,,0.396666774,0.369999989,0.370000003,15.37515802,9.499999316,15.09502807 diff --git a/doc/elements/trafo3w_par.csv b/doc/elements/trafo3w_par.csv index ccd4f2067..3f4edef60 100644 --- a/doc/elements/trafo3w_par.csv +++ b/doc/elements/trafo3w_par.csv @@ -26,6 +26,9 @@ tap_min;integer;;minimum tap position tap_max;integer;;maximum tap position tap_step_percent;float;:math:`>` 0;tap step size [%] tap_step_degree;float;;tap step size for voltage angle -tap_at_star_point;bool;;whether the tap changer is modelled at terminal or at star point +tap_at_star_point;boolean;True / False;whether the tap changer is modelled at terminal or at star point tap_pos;integer;;current position of tap changer -in_service*;boolean;True/False;specifies if the transformer is in service. +tap_phase_shifter_type;integer;0, 1, 2;specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal) +tap_dependency_table;boolean;True / False;whether the transformer parameters (voltage ratio, angle, impedance) are adjusted dependent on the tap position of the transformer +id_characteristic_table;integer;references the id_characteristic index from the trafo_characteristic_table +in_service*;boolean;True / False;specifies if the transformer is in service. diff --git a/doc/elements/trafo_char_spline.csv b/doc/elements/trafo_char_spline.csv new file mode 100644 index 000000000..dff4bad23 --- /dev/null +++ b/doc/elements/trafo_char_spline.csv @@ -0,0 +1,3 @@ +,id_characteristic,voltage_ratio_characteristic,angle_deg_characteristic,vk_percent_characteristic,vkr_percent_characteristic,vk_hv_percent_characteristic,vkr_hv_percent_characteristic,vk_mv_percent_characteristic,vkr_mv_percent_characteristic,vk_lv_percent_characteristic,vkr_lv_percent_characteristic +0,0,SplineCharacteristic,SplineCharacteristic,SplineCharacteristic,SplineCharacteristic,,,,,, +1,1,SplineCharacteristic,SplineCharacteristic,SplineCharacteristic,SplineCharacteristic,,,,,, diff --git a/doc/elements/trafo_char_table.csv b/doc/elements/trafo_char_table.csv new file mode 100644 index 000000000..5c501f703 --- /dev/null +++ b/doc/elements/trafo_char_table.csv @@ -0,0 +1,19 @@ +,id_characteristic,step,voltage_ratio,angle_deg,vk_percent,vkr_percent,vkr_hv_percent,vkr_mv_percent,vkr_lv_percent,vk_hv_percent,vk_mv_percent,vk_lv_percent +0,0,1,1.056666613,0,16.5299996,0.209176484,,,,,, +1,0,2,1.037777782,0,16.43000257,0.210313729,,,,,, +2,0,3,1.018888831,0,16.32999957,0.211450973,,,,,, +3,0,4,1,0,16.23000167,0.212588267,,,,,, +4,0,5,0.99000001,0,16.22176222,0.216951523,,,,,, +5,0,6,0.980000019,0,16.21353032,0.221314877,,,,,, +6,0,7,0.970000029,0,16.20529492,0.225678207,,,,,, +7,1,-5,1.00160718,-3.246266842,19.4996906,0.181380227,,,,,, +8,1,-4,1.001028895,-2.598013878,19.27375038,0.17510416,,,,,, +9,1,-3,1.00057888,-1.949094653,19.04781394,0.168828137,,,,,, +10,1,-2,1.000257373,-1.299674988,18.82187847,0.162552115,,,,,, +11,1,-1,1.000064373,-0.649921119,18.5959397,0.15627607,,,,,, +12,1,0,1,0,18.37000339,0.150000025,,,,,, +13,1,1,1.000064373,0.649921119,17.93187445,0.146578107,,,,,, +14,1,2,1.000257373,1.299675107,17.49375268,0.143156245,,,,,, +15,1,3,1.00057888,1.949094653,17.05562518,0.139734361,,,,,, +16,1,4,1.001028895,2.598013878,16.61749911,0.1363125,,,,,, +17,1,5,1.00160718,3.246266842,16.17937448,0.132890616,,,,,, diff --git a/doc/elements/trafo_par.csv b/doc/elements/trafo_par.csv index 99f328fb7..20c18317a 100644 --- a/doc/elements/trafo_par.csv +++ b/doc/elements/trafo_par.csv @@ -26,13 +26,15 @@ tap_max;integer;;maximum tap position tap_step_percent;float;:math:`>` 0;tap step size for voltage magnitude [%] tap_step_degree;float;:math:`\geq` 0;tap step size for voltage angle tap_pos;integer;;current position of tap changer -tap_phase_shifter;bool;;defines whether the transformer is an ideal phase shifter -parallel;int;:math:`>` 0;number of parallel transformers +tap_phase_shifter_type;integer;0, 1, 2;specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal) +tap_dependency_table;boolean;True / False;whether the transformer parameters (voltage ratio, angle, impedance) are adjusted dependent on the tap position of the transformer +id_characteristic_table;integer;references the id_characteristic index from the trafo_characteristic_table +parallel;integer;:math:`>` 0;number of parallel transformers max_loading_percent**;float;:math:`>` 0;Maximum loading of the transformer with respect to sn_mva and its corresponding current at 1.0 p.u. -df;float;1 :math:`\geq` df :math:`>` 0;derating factor: maximal current of transformer in relation to nominal current of transformer (from 0 to 1) +df;float;1 :math:`\geq` df :math:`>` 0;derating factor: maximum current of transformer in relation to nominal current of transformer (from 0 to 1) in_service*;boolean;True / False;specifies if the transformer is in service oltc*;boolean;True / False; specifies if the transformer has an OLTC (short-circuit relevant) -power_station_unit*;boolean;True / False; specifies if the transformer is part of a power_station_unit (short-circuit relevant). +power_station_unit*;boolean;True / False; specifies if the transformer is part of a power_station_unit (short-circuit relevant) tap2_side****;string;"""hv"", ""lv""";defines if tap changer is at the high- or low voltage side tap2_neutral****;integer;;rated tap position tap2_min****;integer;;minimum tap position @@ -40,5 +42,6 @@ tap2_max****;integer;;maximum tap position tap2_step_percent****;float;:math:`>` 0;tap step size for voltage magnitude [%] tap2_step_degree****;float;:math:`\geq` 0;tap step size for voltage angle tap2_pos****;integer;;current position of tap changer +tap2_phase_shifter_type****;integer;0, 1, 2;specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal) leakage_resistance_ratio_hv*;float;:math:0`\leq` 1;ratio of transformer short-circuit resistance on HV side (default 0.5) leakage_reactance_ratio_hv*;float;:math:0`\leq` 1;ratio of transformer short-circuit reactance on HV side (default 0.5) From 147d41f56f4a014c596ab244fc6bd19d1937e18b Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Wed, 18 Dec 2024 15:23:37 +0200 Subject: [PATCH 067/125] update docstrings in create.py --- pandapower/create.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/pandapower/create.py b/pandapower/create.py index d10eb2bb9..c33be3076 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -3542,9 +3542,9 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **tap2_min** (int, nan): minimum allowed tap position of the second tap changer - **tap2_step_percent** (float) - second tap step size for voltage magnitude in percent + **tap2_step_percent** (float, nan) - second tap step size for voltage magnitude in percent - **tap2_step_degree** (float) - second tap step size for voltage angle in degree* + **tap2_step_degree** (float, nan) - second tap step size for voltage angle in degree* **tap2_phase_shifter_type** (int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal)* @@ -4464,6 +4464,7 @@ def create_shunt(net, bus, q_mvar, p_mw=0., vn_kv=None, step=1, max_step=1, name **step_dependency_table** (boolean, False) - True if shunt parameters (p_mw, q_mvar) must be adjusted \ dependent on the step of the shunt. Requires the additional column "id_characteristic_table". \ + The function pandapower.control.shunt_characteristic_table_diagnostic can be used for sanity checks. \ The function pandapower.control.create_shunt_characteristic_object can be used to create \ SplineCharacteristic objects in the net.shunt_characteristic_spline table and add the additional column \ "id_characteristic_spline" to set up the reference to the spline characteristics. @@ -4527,6 +4528,7 @@ def create_shunts(net, buses, q_mvar, p_mw=0., vn_kv=None, step=1, max_step=1, n **step_dependency_table** (list of booleans, False) - True if shunt parameters (p_mw, q_mvar) must be \ adjusted dependent on the step of the shunts. Requires the additional column "id_characteristic_table". \ + The function pandapower.control.shunt_characteristic_table_diagnostic can be used for sanity checks. \ The function pandapower.control.create_shunt_characteristic_object can be used to create \ SplineCharacteristic objects in the net.shunt_characteristic_spline table and add the additional column \ "id_characteristic_spline" to set up the reference to the spline characteristics. From 377d4097348244dac0ef9f956a93c07967d954d1 Mon Sep 17 00:00:00 2001 From: tfabian Date: Wed, 18 Dec 2024 15:37:25 +0100 Subject: [PATCH 068/125] all test running locally --- pandapower/contingency/contingency.py | 2 +- pandapower/convert_format.py | 2 +- pandapower/converter/pypower/from_ppc.py | 2 +- pandapower/create.py | 30 ++++++++++++------------ pandapower/test/api/test_create.py | 7 +++--- 5 files changed, 22 insertions(+), 21 deletions(-) diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index 105808e02..e70c81e84 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -302,7 +302,7 @@ def _convert_trafo_phase_shifter(net): net.trafo.loc[tap_changer_type == "Ideal", 'shift_degree'] += (tap_diff[tap_changer_type == "Ideal"] * tap_step_degree[tap_changer_type == "Ideal"]) net.trafo["tap_pos"] = 0 - net.trafo["tap_changer_type"] = pd.NA + net.trafo["tap_changer_type"] = None return tap_changer_type, tap_pos, shift_degree diff --git a/pandapower/convert_format.py b/pandapower/convert_format.py index 1cfcaaf06..c51b55cbc 100644 --- a/pandapower/convert_format.py +++ b/pandapower/convert_format.py @@ -364,7 +364,7 @@ def _add_missing_columns(net, elements_to_deserialize): if _check_elements_to_deserialize('trafo', elements_to_deserialize) and \ "tap_changer_type" not in net.trafo: - net.trafo["tap_changer_type"] = pd.NA + net.trafo["tap_changer_type"] = None # asymmetric impedance if _check_elements_to_deserialize('impedance', elements_to_deserialize): diff --git a/pandapower/converter/pypower/from_ppc.py b/pandapower/converter/pypower/from_ppc.py index c69f8282a..a257e3eda 100644 --- a/pandapower/converter/pypower/from_ppc.py +++ b/pandapower/converter/pypower/from_ppc.py @@ -287,7 +287,7 @@ def _from_ppc_branch(net, ppc, f_hz, **kwargs): vkr_percent[~tap_side_is_hv] /= (1+ratio_1[~tap_side_is_hv])**2 tap_step_percent = np.abs(ratio_1)*100 - tap_changer_type = np.where(tap_step_percent > 0, 0, pd.NA) + tap_changer_type = np.where(tap_step_percent > 0, "Ratio", None) idx_trafo = create_transformers_from_parameters( net, hv_buses=net.bus.index[hv_bus], lv_buses=net.bus.index[lv_bus], sn_mva=sn, diff --git a/pandapower/create.py b/pandapower/create.py index 18aab5e4a..8e6ddc57a 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -3282,7 +3282,7 @@ def create_lines_dc_from_parameters(net, from_buses_dc, to_buses_dc, length_km, def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in_service=True, - index=None, max_loading_percent=nan, parallel=1, df=1., tap_changer_type=pd.NA, + index=None, max_loading_percent=nan, parallel=1, df=1., tap_changer_type=None, tap_dependency_table=nan, id_characteristic_table=nan, pt_percent=nan, oltc=nan, xn_ohm=nan, tap2_pos=nan, **kwargs): """ @@ -3410,7 +3410,7 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, tap_changer_type, "tap_changer_type", - "trafo", dtype=object) + "trafo", dtype=object, default_val = None) _set_value_if_not_nan(net, index, pt_percent, "pt_percent", "trafo") _set_value_if_not_nan(net, index, oltc, "oltc", "trafo", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, xn_ohm, "xn_ohm", "trafo") @@ -3423,7 +3423,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn shift_degree=0, tap_side=None, tap_neutral=nan, tap_max=nan, tap_min=nan, tap_step_percent=nan, tap_step_degree=nan, - tap_pos=nan, tap_changer_type=pd.NA, id_characteristic_table=nan, + tap_pos=nan, tap_changer_type=None, id_characteristic_table=nan, in_service=True, name=None, vector_group=None, index=None, max_loading_percent=nan, parallel=1, df=1., vk0_percent=nan, vkr0_percent=nan, @@ -3432,7 +3432,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn pt_percent=nan, oltc=nan, tap_dependency_table=False, xn_ohm=nan, tap2_side=None, tap2_neutral=nan, tap2_max=nan, tap2_min=nan, tap2_step_percent=nan, tap2_step_degree=nan, - tap2_pos=nan, tap2_changer_type=pd.NA, **kwargs): + tap2_pos=nan, tap2_changer_type=None, **kwargs): """ Creates a two-winding transformer in table net["trafo"]. The trafo parameters are defined through the standard type library. @@ -3598,7 +3598,7 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo", dtype="Int64") _set_value_if_not_nan(net, index, tap_changer_type, - "tap_changer_type", "trafo", dtype=object) + "tap_changer_type", "trafo", dtype=object, default_val=None) _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo", dtype=bool_, default_val=False) @@ -3634,14 +3634,14 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k vkr_percent, vk_percent, pfe_kw, i0_percent, shift_degree=0, tap_side=None, tap_neutral=nan, tap_max=nan, tap_min=nan, tap_step_percent=nan, tap_step_degree=nan, tap_pos=nan, - tap_changer_type=nan, id_characteristic_table=nan, in_service=True, + tap_changer_type=None, id_characteristic_table=nan, in_service=True, name=None, vector_group=None, index=None, max_loading_percent=nan, parallel=1, df=1., vk0_percent=nan, vkr0_percent=nan, mag0_percent=nan, mag0_rx=nan, si0_hv_partial=nan, pt_percent=nan, oltc=nan, tap_dependency_table=False, xn_ohm=nan, tap2_side=None, tap2_neutral=nan, tap2_max=nan, tap2_min=nan, tap2_step_percent=nan, tap2_step_degree=nan, - tap2_pos=nan, tap2_changer_type=nan, + tap2_pos=nan, tap2_changer_type=None, **kwargs): """ Creates several two-winding transformers in table net["trafo"]. @@ -3802,7 +3802,7 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_step_degree", tap2_step_degree) _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_pos", tap2_pos) _add_to_entries_if_not_nan(net, "trafo", entries, index, "tap2_changer_type", - tap2_changer_type, dtype="Int64") + tap2_changer_type, dtype=object) defaults_to_fill = [("tap_dependency_table", False)] _set_multiple_entries(net, "trafo", index, defaults_to_fill=defaults_to_fill, **entries, **kwargs) @@ -3811,7 +3811,7 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_pos=nan, - in_service=True, index=None, max_loading_percent=nan, tap_changer_type=nan, + in_service=True, index=None, max_loading_percent=nan, tap_changer_type=None, tap_at_star_point=False, tap_dependency_table=nan, id_characteristic_table=nan): """ Creates a three-winding transformer in table net["trafo3w"]. @@ -3925,7 +3925,7 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo3w", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, tap_changer_type, - "tap_changer_type", "trafo3w", dtype=str) + "tap_changer_type", "trafo3w", dtype=str, default_val=None) return index @@ -3937,7 +3937,7 @@ def create_transformer3w_from_parameters( vkr_mv_percent, vkr_lv_percent, pfe_kw, i0_percent, shift_mv_degree=0., shift_lv_degree=0., tap_side=None, tap_step_percent=nan, tap_step_degree=nan, tap_pos=nan, - tap_neutral=nan, tap_max=nan, tap_changer_type=nan, + tap_neutral=nan, tap_max=nan, tap_changer_type=None, tap_min=nan, name=None, in_service=True, index=None, max_loading_percent=nan, tap_at_star_point=False, vk0_hv_percent=nan, vk0_mv_percent=nan, vk0_lv_percent=nan, @@ -4087,7 +4087,7 @@ def create_transformer3w_from_parameters( _set_value_if_not_nan(net, index, id_characteristic_table, "id_characteristic_table", "trafo3w", dtype="Int64") _set_value_if_not_nan(net, index, tap_changer_type, - "tap_changer_type", "trafo3w", dtype=str) + "tap_changer_type", "trafo3w", dtype=str, default_val=None) _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo3w", dtype=bool_, default_val=False) @@ -4103,7 +4103,7 @@ def create_transformers3w_from_parameters( tap_step_percent=nan, tap_step_degree=nan, tap_pos=nan, tap_neutral=nan, tap_max=nan, tap_min=nan, name=None, in_service=True, index=None, max_loading_percent=nan, - tap_at_star_point=False, tap_changer_type=nan, + tap_at_star_point=False, tap_changer_type=None, vk0_hv_percent=nan, vk0_mv_percent=nan, vk0_lv_percent=nan, vkr0_hv_percent=nan, vkr0_mv_percent=nan, vkr0_lv_percent=nan, vector_group=None, tap_dependency_table=False, id_characteristic_table=nan, **kwargs): @@ -4253,7 +4253,7 @@ def create_transformers3w_from_parameters( _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "id_characteristic_table", id_characteristic_table, dtype="Int64") _add_to_entries_if_not_nan(net, "trafo3w", entries, index, "tap_changer_type", - tap_changer_type, dtype=str) + tap_changer_type, dtype=str, default_val=None) defaults_to_fill = [("tap_dependency_table", False)] _set_multiple_entries(net, "trafo3w", index, defaults_to_fill=defaults_to_fill, **entries, @@ -5872,7 +5872,7 @@ def _not_nan(value, all_=True): return not any(isnan(value)) else: try: - return not (value is None or value is pd.NA or isnan(value)) + return not (value is None or isnan(value)) except TypeError: return True diff --git a/pandapower/test/api/test_create.py b/pandapower/test/api/test_create.py index fd565bc58..829fe2ca6 100644 --- a/pandapower/test/api/test_create.py +++ b/pandapower/test/api/test_create.py @@ -1,5 +1,5 @@ # -*- coding: utf-8 -*- - +import math # Copyright (c) 2016-2024 by University of Kassel and Fraunhofer Institute for Energy Economics # and Energy System Technology (IEE), Kassel. All rights reserved. @@ -230,7 +230,7 @@ def test_nonexistent_bus(): def test_tap_changer_type_default(): - expected_default = pd.NA + expected_default = math.nan # comment: wanted to implement "None" as default, but some test rely on that some function converts NaN to ratio tap changer. net = pp.create_empty_network() pp.create_bus(net, 110) pp.create_bus(net, 20) @@ -241,7 +241,8 @@ def test_tap_changer_type_default(): pp.create_transformer_from_parameters(net, 0, 1, 25e3, 110, 20, 0.4, 12, 20, 0.07) pp.create_transformer(net, 0, 1, "without_tap_shifter_info") - assert (net.trafo.tap_changer_type == expected_default).all() + #assert (net.trafo.tap_changer_type == expected_default).all() # comparison with NaN is always false. revert back to this + assert (net.trafo.tap_changer_type.isna()).all() def test_create_line_conductance(): From ecc85782731f3caa7f65d849d75f8521a464a7b4 Mon Sep 17 00:00:00 2001 From: tfabian Date: Wed, 18 Dec 2024 15:54:50 +0100 Subject: [PATCH 069/125] merge to latest and again fixing tests --- pandapower/control/util/diagnostic.py | 4 ++-- .../transformers/powerTransformersCim16.py | 8 ++++---- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/pandapower/control/util/diagnostic.py b/pandapower/control/util/diagnostic.py index 121f82e70..1c670d124 100644 --- a/pandapower/control/util/diagnostic.py +++ b/pandapower/control/util/diagnostic.py @@ -90,11 +90,11 @@ def trafo_characteristic_table_diagnostic(net): f"Power flow calculation will raise an error.", category=UserWarning) # check if both tap_dependency_table & tap_phase_shifter_type columns are populated mismatch_b = net[trafo_table][ - (net[trafo_table]['tap_dependency_table'] & net[trafo_table]['tap_phase_shifter_type'].isna()) + (net[trafo_table]['tap_dependency_table'] & net[trafo_table]['tap_changer_type'].isna()) ].shape[0] if mismatch_b != 0: warnings.warn(f"{trafo_table}: found {mismatch_b} transformer(s) with tap_dependency_table set to " - f"True and tap_phase_shifter_type parameter not populated. The characteristics from " + f"True and tap_changer_type parameter not populated. The characteristics from " f"trafo_characteristic_table will not be considered.", category=UserWarning) # check if all relevant columns are populated in the trafo_characteristic_table temp = net[trafo_table].dropna(subset=["id_characteristic_table"])[ diff --git a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py index ea953d9cb..090473c9d 100644 --- a/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py +++ b/pandapower/converter/cim/cim2pp/converter_classes/transformers/powerTransformersCim16.py @@ -447,7 +447,7 @@ def _prepare_trafos_cim16(self, power_trafo2w: pd.DataFrame) -> pd.DataFrame: copy_list = ['index_bus', 'Terminal', 'ratedU', 'r', 'x', 'b', 'g', 'r0', 'x0', 'neutralStep', 'lowStep', 'highStep', 'stepVoltageIncrement', 'stepPhaseShiftIncrement', 'step', 'connected', 'phaseAngleClock', 'connectionKind', sc['pte_id'], sc['tc'], sc['tc_id'], 'grounded', 'angle', - 'tap_phase_shifter_type'] + 'tap_changer_type'] for one_item in copy_list: # copy the columns which are required for each winding power_trafo2w[one_item + '_lv'] = power_trafo2w[one_item].copy() @@ -460,7 +460,7 @@ def _prepare_trafos_cim16(self, power_trafo2w: pd.DataFrame) -> pd.DataFrame: power_trafo2w.loc[power_trafo2w['step_lv'].notna(), 'tap_side'] = 'lv' power_trafo2w.loc[power_trafo2w['step'].notna(), 'tap_side'] = 'hv' fillna_list = ['neutralStep', 'lowStep', 'highStep', 'stepVoltageIncrement', 'stepPhaseShiftIncrement', 'step', - sc['tc'], sc['tc_id'], 'tap_phase_shifter_type'] + sc['tc'], sc['tc_id'], 'tap_changer_type'] for one_item in fillna_list: power_trafo2w[one_item] = power_trafo2w[one_item].fillna(power_trafo2w[one_item + '_lv']) del fillna_list, one_item @@ -536,7 +536,7 @@ def _prepare_trafo3w_cim16(self, power_trafo3w: pd.DataFrame) -> pd.DataFrame: copy_list = ['index_bus', 'Terminal', 'ratedS', 'ratedU', 'r', 'x', 'b', 'g', 'r0', 'x0', 'neutralStep', 'lowStep', 'highStep', 'stepVoltageIncrement', 'stepPhaseShiftIncrement', 'step', 'connected', 'angle', 'phaseAngleClock', 'connectionKind', 'grounded', sc['pte_id'], sc['tc'], sc['tc_id'], - 'tap_phase_shifter_type'] + 'tap_changer_type'] for one_item in copy_list: # copy the columns which are required for each winding power_trafo3w[one_item + '_mv'] = power_trafo3w[one_item].copy() @@ -554,7 +554,7 @@ def _prepare_trafo3w_cim16(self, power_trafo3w: pd.DataFrame) -> pd.DataFrame: power_trafo3w.loc[power_trafo3w['step_mv'].notna(), 'tap_side'] = 'mv' power_trafo3w.loc[power_trafo3w['step'].notna(), 'tap_side'] = 'hv' fillna_list = ['neutralStep', 'lowStep', 'highStep', 'stepVoltageIncrement', 'stepPhaseShiftIncrement', 'step', - sc['tc'], sc['tc_id'], 'tap_phase_shifter_type'] + sc['tc'], sc['tc_id'], 'tap_changer_type'] for one_item in fillna_list: power_trafo3w[one_item] = power_trafo3w[one_item].fillna(power_trafo3w[one_item + '_mv']) power_trafo3w[one_item] = power_trafo3w[one_item].fillna(power_trafo3w[one_item + '_lv']) From e8a03aa3f656e4c17c675a69dd589eb9813f3317 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Wed, 18 Dec 2024 18:58:44 +0200 Subject: [PATCH 070/125] add documentation for shunt_characteristic_table --- doc/elements/shunt.rst | 40 +++++++++++++++++++++++++++++- doc/elements/shunt_char_spline.csv | 3 +++ doc/elements/shunt_char_table.csv | 11 ++++++++ doc/elements/shunt_par.csv | 11 +++++--- doc/elements/trafo.rst | 4 +-- doc/elements/trafo3w.rst | 4 +-- doc/elements/trafo3w_par.csv | 2 +- doc/elements/trafo_par.csv | 2 +- 8 files changed, 66 insertions(+), 11 deletions(-) create mode 100644 doc/elements/shunt_char_spline.csv create mode 100644 doc/elements/shunt_char_table.csv diff --git a/doc/elements/shunt.rst b/doc/elements/shunt.rst index 7a825fbb6..f40ec6940 100644 --- a/doc/elements/shunt.rst +++ b/doc/elements/shunt.rst @@ -68,7 +68,45 @@ Converting to the per unit system results in: \end{align*} with the reference values for the per unit system as defined in :ref:`Unit Systems and Conventions`. - + +Shunt characteristic table +============================ + +A shunt characteristic table (shunt_characteristic_table) can be used to adjust the shunt parameters +(q_mvar, p_mw) according to the selected step position. This lookup table is created automatically +from version 3.0 onwards through the CIM CGMES to pandapower converter (if this information is available in the EQ +profile), or the user may define this table manually. The id_characteristic_table variable in net.shunt references +the id_characteristic column in net.shunt_characteristic_table per shunt. + +If the shunt_dependency_table variable in net.shunt is set to True, this indicates that there is a corresponding +characteristic available in net.shunt_characteristic_table, which overwrites the default shunt parameters +q_mvar and p_mw. + +The below table provides an example shunt_characteristic_table, populated for two shunt elements. + +.. tabularcolumns:: |p{0.10\linewidth}|p{0.55\linewidth}|p{0.15\linewidth}|p{0.20\linewidth}|p{0.20\linewidth} +.. csv-table:: + :file: shunt_char_table.csv + :delim: , + :widths: 10, 55, 15, 20, 20 + +.. note:: + shunt_dependency_table has to be set to True and the id_characteristic_table variable needs to be populated in order to consider the corresponding shunt_characteristic_table values. + +The function pandapower.control.shunt_characteristic_table_diagnostic can be used for sanity checks. +The function pandapower.control.create_shunt_characteristic_object can be used to automatically create +SplineCharacteristic objects and populate the net.shunt_characteristic_spline table according to the +net.shunt_characteristic_table table. An additional column id_characteristic_spline is also created in net.shunt +to set up the reference to the spline characteristics. + +The below table provides an example shunt_characteristic_spline table, populated for two shunt elements. + +.. tabularcolumns:: |p{0.10\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth} +.. csv-table:: + :file: shunt_char_spline.csv + :delim: , + :widths: 10, 55, 55, 55 + Result Parameters ========================== *net.res_shunt* diff --git a/doc/elements/shunt_char_spline.csv b/doc/elements/shunt_char_spline.csv new file mode 100644 index 000000000..c966ba883 --- /dev/null +++ b/doc/elements/shunt_char_spline.csv @@ -0,0 +1,3 @@ +,id_characteristic,q_mvar_characteristic,p_mw_characteristic +0,0,SplineCharacteristic,SplineCharacteristic +1,1,SplineCharacteristic,SplineCharacteristic diff --git a/doc/elements/shunt_char_table.csv b/doc/elements/shunt_char_table.csv new file mode 100644 index 000000000..e02c5759f --- /dev/null +++ b/doc/elements/shunt_char_table.csv @@ -0,0 +1,11 @@ +,id_characteristic,step,q_mvar,p_mw +0,0,1,176.3999987,0.223000955 +1,0,2,171.0046573,0.223000955 +2,0,3,165.6093266,0.223000955 +3,0,4,160.2139746,0.223000955 +4,0,5,155.4759927,0.223000955 +5,1,1,179.999968,0.034992 +6,1,2,174.083296,0.034992 +7,1,3,168.166624,0.034992 +8,1,4,162.249952,0.034992 +9,1,5,156.333296,0.034992 diff --git a/doc/elements/shunt_par.csv b/doc/elements/shunt_par.csv index bf58ab561..abb0701c4 100644 --- a/doc/elements/shunt_par.csv +++ b/doc/elements/shunt_par.csv @@ -1,8 +1,11 @@ **Parameter**;**Datatype**;**Value Range**;**Explanation** name;string;;name of the shunt bus*;integer;;index of bus where the impedance starts -p_mw*;float;:math:`\geq` 0;shunt active power in MW at v= 1.0 p.u. -q_mvar*;float;;shunt reactive power in kvar at v= 1.0 p.u. +p_mw*;float;:math:`\geq` 0;shunt active power in MW at v= 1.0 p.u. per step +q_mvar*;float;;shunt reactive power in MVAr at v= 1.0 p.u. per step vn_kv*;float;:math:`>` 0;rated voltage of the shunt element -step*;integer;:math:`\geq` 1;step position of the shunt -in_service*;boolean;True / False;specifies if the shunt is in service. +step*;integer;:math:`\geq` 1;step position of the shunt with which power values are multiplied +max_step*;integer;:math:`\geq` 1;maximum allowed step of shunt +in_service*;boolean;True / False;specifies if the shunt is in service +step_dependency_table;boolean;True / False;whether the shunt parameters (q_mvar, p_mw) are adjusted dependent on the step of the shunt +id_characteristic_table;integer;:math:`\geq` 0;references the id_characteristic index from the shunt_characteristic_table \ No newline at end of file diff --git a/doc/elements/trafo.rst b/doc/elements/trafo.rst index 465d3c1f3..8bc0312f6 100644 --- a/doc/elements/trafo.rst +++ b/doc/elements/trafo.rst @@ -248,7 +248,7 @@ If the tap_dependency_table variable in net.trafo is set to True, this indicates characteristic available in net.trafo_characteristic_table, which overwrites the default trafo parameters tap_step_percent, tap_step_degree, vk_percent and vkr_percent. -The below table provides an example trafo_characteristic_table table, populated for two 2-winding transformers. +The below table provides an example trafo_characteristic_table, populated for two 2-winding transformers. .. tabularcolumns:: |p{0.10\linewidth}|p{0.55\linewidth}|p{0.15\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth} .. csv-table:: @@ -257,7 +257,7 @@ The below table provides an example trafo_characteristic_table table, populated :widths: 10, 55, 15, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55 .. note:: - - tap_dependency_table has to be set to True, and id_characteristic_table and tap_phase_shifter_type variables need to be populated in order to consider the corresponding trafo_characteristic table values. + - tap_dependency_table has to be set to True, and id_characteristic_table and tap_phase_shifter_type variables need to be populated in order to consider the corresponding trafo_characteristic_table values. - Only one tap_dependency_table is supported per 2-winding transformer (there is no tap2_dependency_table variable) The function pandapower.control.trafo_characteristic_table_diagnostic can be used for sanity checks. diff --git a/doc/elements/trafo3w.rst b/doc/elements/trafo3w.rst index 3b0acffc7..126e83adb 100644 --- a/doc/elements/trafo3w.rst +++ b/doc/elements/trafo3w.rst @@ -155,7 +155,7 @@ characteristic available in net.trafo_characteristic_table, which overwrites the tap_step_percent, tap_step_degree, vkr_hv_percent, vkr_mv_percent, vkr_lv_percent, vk_hv_percent, vk_mv_percent and vk_lv_percent. -The below table provides an example trafo_characteristic_table table, populated for two 3-winding transformers. +The below table provides an example trafo_characteristic_table, populated for two 3-winding transformers. .. tabularcolumns:: |p{0.10\linewidth}|p{0.55\linewidth}|p{0.15\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth}|p{0.55\linewidth} .. csv-table:: @@ -164,7 +164,7 @@ The below table provides an example trafo_characteristic_table table, populated :widths: 10, 55, 15, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55 .. note:: - tap_dependency_table has to be set to True, and id_characteristic_table and tap_phase_shifter_type variables need to be populated in order to consider the corresponding trafo_characteristic table values. + tap_dependency_table has to be set to True, and id_characteristic_table and tap_phase_shifter_type variables need to be populated in order to consider the corresponding trafo_characteristic_table values. The function pandapower.control.trafo_characteristic_table_diagnostic can be used for sanity checks. The function pandapower.control.create_trafo_characteristic_object can be used to automatically create diff --git a/doc/elements/trafo3w_par.csv b/doc/elements/trafo3w_par.csv index 3f4edef60..26b0a9c45 100644 --- a/doc/elements/trafo3w_par.csv +++ b/doc/elements/trafo3w_par.csv @@ -30,5 +30,5 @@ tap_at_star_point;boolean;True / False;whether the tap changer is modelled at te tap_pos;integer;;current position of tap changer tap_phase_shifter_type;integer;0, 1, 2;specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal) tap_dependency_table;boolean;True / False;whether the transformer parameters (voltage ratio, angle, impedance) are adjusted dependent on the tap position of the transformer -id_characteristic_table;integer;references the id_characteristic index from the trafo_characteristic_table +id_characteristic_table;integer;:math:`\geq` 0;references the id_characteristic index from the trafo_characteristic_table in_service*;boolean;True / False;specifies if the transformer is in service. diff --git a/doc/elements/trafo_par.csv b/doc/elements/trafo_par.csv index 20c18317a..bf425ab69 100644 --- a/doc/elements/trafo_par.csv +++ b/doc/elements/trafo_par.csv @@ -28,7 +28,7 @@ tap_step_degree;float;:math:`\geq` 0;tap step size for voltage angle tap_pos;integer;;current position of tap changer tap_phase_shifter_type;integer;0, 1, 2;specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal) tap_dependency_table;boolean;True / False;whether the transformer parameters (voltage ratio, angle, impedance) are adjusted dependent on the tap position of the transformer -id_characteristic_table;integer;references the id_characteristic index from the trafo_characteristic_table +id_characteristic_table;integer;:math:`\geq` 0;references the id_characteristic index from the trafo_characteristic_table parallel;integer;:math:`>` 0;number of parallel transformers max_loading_percent**;float;:math:`>` 0;Maximum loading of the transformer with respect to sn_mva and its corresponding current at 1.0 p.u. df;float;1 :math:`\geq` df :math:`>` 0;derating factor: maximum current of transformer in relation to nominal current of transformer (from 0 to 1) From 3cc601ba2201f57964d903d9dca74e0d4f6d92a1 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Wed, 18 Dec 2024 19:05:52 +0200 Subject: [PATCH 071/125] fix codacy minor issue --- pandapower/control/util/diagnostic.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pandapower/control/util/diagnostic.py b/pandapower/control/util/diagnostic.py index 121f82e70..e2ffb57cc 100644 --- a/pandapower/control/util/diagnostic.py +++ b/pandapower/control/util/diagnostic.py @@ -148,8 +148,8 @@ def shunt_characteristic_table_diagnostic(net): right_on="id_characteristic", how="inner") unpopulated = merged_df.loc[~merged_df[cols].notna().all(axis=1)] if not unpopulated.empty: - warnings.warn(f"There are some shunts with not all " - "characteristics populated in the shunt_characteristic_table.", category=UserWarning) + warnings.warn("There are some shunts with not all characteristics " + "populated in the shunt_characteristic_table.", category=UserWarning) # check step_dependency_table & id_characteristic_table column types if net["shunt"]['step_dependency_table'].dtype != 'bool': warnings.warn("The step_dependency_table column in the shunt table is not of bool type.", From e8a6239674610c68aa8eace29f2d11247584f3fc Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 19 Dec 2024 12:39:51 +0200 Subject: [PATCH 072/125] fix contingency and tap_dependent_impedance tests --- pandapower/control/util/diagnostic.py | 12 ++++++++++++ pandapower/test/contingency/test_contingency.py | 2 +- .../test/control/test_tap_dependent_impedance.py | 8 ++++---- 3 files changed, 17 insertions(+), 5 deletions(-) diff --git a/pandapower/control/util/diagnostic.py b/pandapower/control/util/diagnostic.py index d3f1b6f08..6137f3bf0 100644 --- a/pandapower/control/util/diagnostic.py +++ b/pandapower/control/util/diagnostic.py @@ -72,6 +72,7 @@ def trafo_characteristic_table_diagnostic(net): cols2w = ["id_characteristic", "step", "voltage_ratio", "angle_deg", "vk_percent", "vkr_percent"] cols3w = ["id_characteristic", "step", "voltage_ratio", "angle_deg", "vk_hv_percent", "vkr_hv_percent", "vk_mv_percent", "vkr_mv_percent", "vk_lv_percent", "vkr_lv_percent"] + warnings_count = 0 for trafo_table, cols in zip(["trafo", "trafo3w"], [cols2w, cols3w]): if len(net[trafo_table]) == 0 or \ not all(col in net[trafo_table] for col in ['id_characteristic_table', 'tap_dependency_table']) or \ @@ -88,6 +89,7 @@ def trafo_characteristic_table_diagnostic(net): warnings.warn(f"{trafo_table}: found {mismatch_a} transformer(s) with not both " f"tap_dependency_table and id_characteristic_table parameters populated. " f"Power flow calculation will raise an error.", category=UserWarning) + warnings_count += 1 # check if both tap_dependency_table & tap_phase_shifter_type columns are populated mismatch_b = net[trafo_table][ (net[trafo_table]['tap_dependency_table'] & net[trafo_table]['tap_changer_type'].isna()) @@ -96,6 +98,7 @@ def trafo_characteristic_table_diagnostic(net): warnings.warn(f"{trafo_table}: found {mismatch_b} transformer(s) with tap_dependency_table set to " f"True and tap_changer_type parameter not populated. The characteristics from " f"trafo_characteristic_table will not be considered.", category=UserWarning) + warnings_count += 1 # check if all relevant columns are populated in the trafo_characteristic_table temp = net[trafo_table].dropna(subset=["id_characteristic_table"])[ ["tap_dependency_table", "id_characteristic_table"]] @@ -105,19 +108,28 @@ def trafo_characteristic_table_diagnostic(net): if not unpopulated.empty: warnings.warn(f"There are some transformers in the {trafo_table} table with not all " f"characteristics populated in the trafo_characteristic_table.", category=UserWarning) + warnings_count += 1 # check tap_dependency_table & id_characteristic_table column types if net[trafo_table]['tap_dependency_table'].dtype != 'bool': warnings.warn(f"The tap_dependency_table column in the {trafo_table} table is not of bool type.", category=UserWarning) + warnings_count += 1 if net[trafo_table]['id_characteristic_table'].dtype != 'Int64': warnings.warn(f"The id_characteristic_table column in the {trafo_table} table is not of Int64 type.", category=UserWarning) + warnings_count += 1 # check if all id_characteristic_table values are present in id_characteristic column # of trafo_characteristic_table if not net[trafo_table]['id_characteristic_table'].dropna().isin( net["trafo_characteristic_table"]['id_characteristic']).all(): warnings.warn(f"Not all id_characteristic_table values in the {trafo_table} table are present " f"in id_characteristic column of trafo_characteristic_table.", category=UserWarning) + warnings_count += 1 + logger.info(f"{warnings_count} warnings were issued") + if warnings_count > 0: + return False + else: + return True def shunt_characteristic_table_diagnostic(net): diff --git a/pandapower/test/contingency/test_contingency.py b/pandapower/test/contingency/test_contingency.py index 42868c6e7..2a7d2c255 100644 --- a/pandapower/test/contingency/test_contingency.py +++ b/pandapower/test/contingency/test_contingency.py @@ -225,7 +225,7 @@ def test_lightsim2grid_phase_shifters(): pp.create_lines(net, [0, 0], [1, 1], 40, "243-AL1/39-ST1A 110.0", max_loading_percent=100) pp.create_transformer_from_parameters(net, 1, 2, 150, 110, 110, 0.5, 10, 15, 0.1, 150, - 'hv', 0, 10, -10, 0, 1, 5, 2, max_loading_percent=100) + 'hv', 0, 10, -10, 0, 1, 5, "Ideal", max_loading_percent=100) pp.create_lines(net, [2, 2], [3, 3], 25, "243-AL1/39-ST1A 110.0", max_loading_percent=100) pp.create_load(net, 3, 110) diff --git a/pandapower/test/control/test_tap_dependent_impedance.py b/pandapower/test/control/test_tap_dependent_impedance.py index c06a6c0ac..ad197de99 100644 --- a/pandapower/test/control/test_tap_dependent_impedance.py +++ b/pandapower/test/control/test_tap_dependent_impedance.py @@ -140,7 +140,7 @@ def test_trafo_characteristic_table_diagnostic(): # populate id_characteristic_table parameter net.trafo['id_characteristic_table'].at[0] = 0 net.trafo['tap_dependency_table'].at[0] = False - with pytest.raises(UserWarning): + with pytest.warns(UserWarning): trafo_characteristic_table_diagnostic(net) # populate tap_dependency_table parameter net.trafo['tap_dependency_table'].at[0] = True @@ -152,16 +152,16 @@ def test_trafo_characteristic_table_diagnostic(): 'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [5, 5.2, 6, 6.8, 7], 'vkr_percent': np.nan, 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan, 'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan}) - with pytest.raises(UserWarning): + with pytest.warns(UserWarning): trafo_characteristic_table_diagnostic(net) # let's make some invalid configurations net.trafo.at[0, "tap_dependency_table"] = 0 - with pytest.raises(UserWarning): + with pytest.warns(UserWarning): trafo_characteristic_table_diagnostic(net) net.trafo.at[0, "tap_dependency_table"] = True net.trafo.at[0, "id_characteristic_table"] = int(2) - with pytest.raises(UserWarning): + with pytest.warns(UserWarning): trafo_characteristic_table_diagnostic(net) From 151c973eb1f48227e1005a436802cddb3b20681d Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 19 Dec 2024 15:31:38 +0200 Subject: [PATCH 073/125] fix run_contingency_ls2g, _convert_trafo_phase_shifter & test_lightsim2grid_phase_shifters --- pandapower/contingency/contingency.py | 69 ++++++++++++++----- .../test/contingency/test_contingency.py | 8 ++- 2 files changed, 59 insertions(+), 18 deletions(-) diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index e70c81e84..57db03bd9 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -176,12 +176,24 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. raise UserWarning("bus index must be continuous and start with 0 (use pandapower.create_continuous_bus_index)") contingency_evaluation_function(net, **kwargs) - if "tap_changer_type" in net.trafo.columns: + tps_flag = False + if "tap_phase_shifter" in net.trafo.columns: + if np.any(net.trafo.tap_phase_shifter): + tps_flag = True + tps, tps_tap_pos, tps_shift_degree = _convert_trafo_phase_shifter( + net, "trafo", "tap_phase_shifter") + + tct2w_flag = False + tct3w_flag = False + if ("tap_changer_type" in net.trafo.columns) or ("tap_changer_type" in net.trafo3w.columns): if np.any(net.trafo.tap_changer_type == "Ideal"): - tap_changer_type, tap_pos, shift_degree = _convert_trafo_phase_shifter(net) - net.trafo.tap_changer_type = tap_changer_type - net.trafo.tap_pos = tap_pos - net.trafo.shift_degree = shift_degree + tct2w_flag = True + tct2w, tct2w_tap_pos, tct2w_shift_degree = _convert_trafo_phase_shifter( + net, "trafo", "tap_changer_type") + if np.any(net.trafo3w.tap_changer_type == "Ideal"): + tct3w_flag = True + tct3w, tct3w_tap_pos, tct3w_shift_degree = _convert_trafo_phase_shifter( + net, "trafo3w", "tap_changer_type") # setting "slack" back-and-forth is due to the difference in interpretation of generators as "distributed slack" if net._options.get("distributed_slack", False): @@ -198,6 +210,19 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. lightsim_grid_model = init_ls2g(net) solver_type = SolverType.KLUSingleSlack if KLU_solver_available else SolverType.SparseLUSingleSlack + if tps_flag: + net.trafo.tap_phase_shifter = tps + net.trafo.tap_pos = tps_tap_pos + net.trafo.shift_degree = tps_shift_degree + if tct2w_flag: + net.trafo.tap_changer_type = tct2w + net.trafo.tap_pos = tct2w_tap_pos + net.trafo.shift_degree = tct2w_shift_degree + if tct3w_flag: + net.trafo3w.tap_changer_type = tct3w + net.trafo3w.tap_pos = tct3w_tap_pos + net.trafo3w.shift_degree = tct3w_shift_degree + n_lines = len(net.line) n_lines_cases = len(nminus1_cases.get("line", {}).get("index", [])) n_trafos = len(net.trafo) @@ -289,22 +314,32 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. np.sort(map_index[element])], "congestion_caused_mva"] = congestion_caused -def _convert_trafo_phase_shifter(net): - tap_changer_type = net.trafo.tap_changer_type.values.copy() - # vn_hv_kv = net.trafo.vn_hv_kv.values.copy() - shift_degree = net.trafo.shift_degree.values.copy() +def _convert_trafo_phase_shifter(net, trafotable="trafo", tap_param="tap_changer_type"): + """ + Moves tap_step_degree values for ideal phase shifters to the shift_degree values. + Works both for old implementation (tap_phase_shifter) and for new implementation (tap_changer_type). + """ + tap_changer = net[trafotable][tap_param].values.copy() + shift_degree = net[trafotable].shift_degree.values.copy() - tap_pos = net.trafo.tap_pos.values - tap_neutral = net.trafo.tap_neutral.values + tap_pos = net[trafotable].tap_pos.values + tap_neutral = net[trafotable].tap_neutral.values tap_diff = tap_pos - tap_neutral - tap_step_degree = net.trafo.tap_step_degree.values.copy() + tap_step_degree = net[trafotable].tap_step_degree.values.copy() + + if tap_param == "tap_changer_type": + net.trafo.loc[tap_changer == "Ideal", 'shift_degree'] += (tap_diff[tap_changer == "Ideal"] * + tap_step_degree[tap_changer == "Ideal"]) + net[trafotable][tap_param] = None + elif tap_param == "tap_phase_shifter": + net.trafo.loc[tap_changer, 'shift_degree'] += tap_diff[tap_changer] * tap_step_degree[tap_changer] + net[trafotable][tap_param] = False + else: + raise ValueError("tap_param argument not recognized") - net.trafo.loc[tap_changer_type == "Ideal", 'shift_degree'] += (tap_diff[tap_changer_type == "Ideal"] * - tap_step_degree[tap_changer_type == "Ideal"]) - net.trafo["tap_pos"] = 0 - net.trafo["tap_changer_type"] = None + net[trafotable]["tap_pos"] = 0 - return tap_changer_type, tap_pos, shift_degree + return tap_changer, tap_pos, shift_degree def _update_contingency_results(net, contingency_results, result_variables, nminus1, cause_element=None, diff --git a/pandapower/test/contingency/test_contingency.py b/pandapower/test/contingency/test_contingency.py index 2a7d2c255..fb7e2a304 100644 --- a/pandapower/test/contingency/test_contingency.py +++ b/pandapower/test/contingency/test_contingency.py @@ -251,7 +251,13 @@ def test_lightsim2grid_phase_shifters(): pp.runpp(net) bus_res = net.res_bus.copy() - _convert_trafo_phase_shifter(net) + if "tap_phase_shifter" in net.trafo.columns: + _convert_trafo_phase_shifter(net, "trafo", "tap_phase_shifter") + if ("tap_changer_type" in net.trafo.columns) or ("tap_changer_type" in net.trafo3w.columns): + if np.any(net.trafo.tap_changer_type == "Ideal"): + _convert_trafo_phase_shifter(net, "trafo", "tap_changer_type") + if np.any(net.trafo3w.tap_changer_type == "Ideal"): + _convert_trafo_phase_shifter(net, "trafo3w", "tap_changer_type") pp.runpp(net) assert_frame_equal(bus_res, net.res_bus) From 91fa21db0e05f4791a532b7c781d25d8b04d1d1c Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 19 Dec 2024 16:03:14 +0200 Subject: [PATCH 074/125] minor fixes --- pandapower/control/util/diagnostic.py | 2 +- pandapower/convert_format.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pandapower/control/util/diagnostic.py b/pandapower/control/util/diagnostic.py index 6137f3bf0..4e27a75e5 100644 --- a/pandapower/control/util/diagnostic.py +++ b/pandapower/control/util/diagnostic.py @@ -142,7 +142,7 @@ def shunt_characteristic_table_diagnostic(net): not all(col in net["shunt"] for col in ['id_characteristic_table', 'step_dependency_table']) or \ (not net["shunt"]['id_characteristic_table'].notna().any() and not net["shunt"]['step_dependency_table'].any()): - logger.info("No %s with step-dependent characteristics found." % "shunt") + logger.info("No shunt with step-dependent characteristics found.") return False # check if both step_dependency_table & id_characteristic_table columns are populated mismatch = net["shunt"][ diff --git a/pandapower/convert_format.py b/pandapower/convert_format.py index 51c8ffa72..5fc633d7d 100644 --- a/pandapower/convert_format.py +++ b/pandapower/convert_format.py @@ -569,7 +569,7 @@ def convert_trafo_pst_logic(net): (net[trafotable][f"tap{t}_step_degree"] == 0)) & ((net[trafotable][f"tap{t}_step_percent"].isna()) | (net[trafotable][f"tap{t}_step_percent"] == 0))) - net[trafotable].loc[mask_na, f"tap{t}_changer_type"] = "None" + net[trafotable].loc[mask_na, f"tap{t}_changer_type"] = None # ratio/asymmetrical phase shifters mask_ratio_asym = ((net[trafotable][f"tap{t}_step_degree"] != 90) & ((net[trafotable][f"tap{t}_step_percent"].notna()) & From c1a1666b5f79e883578fabedc540a7a4e8e99a4a Mon Sep 17 00:00:00 2001 From: Jakob Kirschner Date: Thu, 19 Dec 2024 15:24:30 +0100 Subject: [PATCH 075/125] add Int64 to sql bigint dtypes and convert pd.NA to None for postgres conversion --- pandapower/sql_io.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/pandapower/sql_io.py b/pandapower/sql_io.py index 1175809f7..9dac834ef 100644 --- a/pandapower/sql_io.py +++ b/pandapower/sql_io.py @@ -38,7 +38,7 @@ def match_sql_type(dtype): if dtype in ("float", "float32", "float64"): return "double precision" - elif dtype in ("int", "int32", "int64", "uint32", "uint64"): + elif dtype in ("int", "int32", "int64", "uint32", "uint64", "Int64"): return "bigint" elif dtype in ("object", "str"): return "varchar" @@ -116,6 +116,8 @@ def upload_sql_table(conn, cursor, table_name, table, index_name=None, timestamp for x in table[table_columns].itertuples(index=tuples_index)] else: tuples = [tuple(x) for x in table[table_columns].itertuples(index=tuples_index)] + # Replace pd.NA values with None for conversion to postgres NULL + tuples = [tuple(None if value is pd.NA else value for value in row) for row in tuples] # Comma-separated dataframe columns sql_columns = [index_name, *table_columns, *id_columns.keys()] From 4f44236ab7895a53aa1ec2c7340209a1c60b9871 Mon Sep 17 00:00:00 2001 From: Jakob Kirschner Date: Thu, 19 Dec 2024 17:34:10 +0100 Subject: [PATCH 076/125] add temporary tap_phase_shifter column to trafo df for lightsim2grid model --- pandapower/contingency/contingency.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index 57db03bd9..936c25c65 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -195,6 +195,9 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. tct3w, tct3w_tap_pos, tct3w_shift_degree = _convert_trafo_phase_shifter( net, "trafo3w", "tap_changer_type") + # TODO: remove next line when lightsim2grid supports checking of column 'tap_changer_type' + net.trafo["tap_phase_shifter"] = (net.trafo["tap_changer_type"] == "Ideal") + # setting "slack" back-and-forth is due to the difference in interpretation of generators as "distributed slack" if net._options.get("distributed_slack", False): slack_backup = net.gen.slack.copy() @@ -210,6 +213,9 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. lightsim_grid_model = init_ls2g(net) solver_type = SolverType.KLUSingleSlack if KLU_solver_available else SolverType.SparseLUSingleSlack + # TODO: remove next line when lightsim2grid supports checking of column 'tap_changer_type' + del net.trafo["tap_phase_shifter"] + if tps_flag: net.trafo.tap_phase_shifter = tps net.trafo.tap_pos = tps_tap_pos From 8ca7fdc1414362fe606c6b09674d35a23fe9ff29 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 19 Dec 2024 19:14:47 +0200 Subject: [PATCH 077/125] fix lightsim2grid dependency; fix codacy issues --- pandapower/contingency/contingency.py | 27 ++++++++++++++------------- 1 file changed, 14 insertions(+), 13 deletions(-) diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index 936c25c65..5bdb36447 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -195,8 +195,8 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. tct3w, tct3w_tap_pos, tct3w_shift_degree = _convert_trafo_phase_shifter( net, "trafo3w", "tap_changer_type") - # TODO: remove next line when lightsim2grid supports checking of column 'tap_changer_type' - net.trafo["tap_phase_shifter"] = (net.trafo["tap_changer_type"] == "Ideal") + # TODO: remove next line when lightsim2grid supports checking of column 'tap_changer_type' + net.trafo["tap_phase_shifter"] = False # setting "slack" back-and-forth is due to the difference in interpretation of generators as "distributed slack" if net._options.get("distributed_slack", False): @@ -213,21 +213,22 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. lightsim_grid_model = init_ls2g(net) solver_type = SolverType.KLUSingleSlack if KLU_solver_available else SolverType.SparseLUSingleSlack - # TODO: remove next line when lightsim2grid supports checking of column 'tap_changer_type' - del net.trafo["tap_phase_shifter"] + # TODO: remove next 2 lines when lightsim2grid supports checking of column 'tap_changer_type' + if ("tap_changer_type" in net.trafo.columns) or ("tap_changer_type" in net.trafo3w.columns): + del net.trafo["tap_phase_shifter"] if tps_flag: - net.trafo.tap_phase_shifter = tps - net.trafo.tap_pos = tps_tap_pos - net.trafo.shift_degree = tps_shift_degree + net.trafo.tap_phase_shifter = tps # noqa + net.trafo.tap_pos = tps_tap_pos # noqa + net.trafo.shift_degree = tps_shift_degree # noqa if tct2w_flag: - net.trafo.tap_changer_type = tct2w - net.trafo.tap_pos = tct2w_tap_pos - net.trafo.shift_degree = tct2w_shift_degree + net.trafo.tap_changer_type = tct2w # noqa + net.trafo.tap_pos = tct2w_tap_pos # noqa + net.trafo.shift_degree = tct2w_shift_degree # noqa if tct3w_flag: - net.trafo3w.tap_changer_type = tct3w - net.trafo3w.tap_pos = tct3w_tap_pos - net.trafo3w.shift_degree = tct3w_shift_degree + net.trafo3w.tap_changer_type = tct3w # noqa + net.trafo3w.tap_pos = tct3w_tap_pos # noqa + net.trafo3w.shift_degree = tct3w_shift_degree # noqa n_lines = len(net.line) n_lines_cases = len(nminus1_cases.get("line", {}).get("index", [])) From 95412fcf9bf0070e6b87b3681d17a4a7f1a32680 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 19 Dec 2024 19:36:48 +0200 Subject: [PATCH 078/125] attempt to fix codacy issues --- pandapower/contingency/contingency.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index 5bdb36447..c5137117b 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -218,17 +218,17 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. del net.trafo["tap_phase_shifter"] if tps_flag: - net.trafo.tap_phase_shifter = tps # noqa - net.trafo.tap_pos = tps_tap_pos # noqa - net.trafo.shift_degree = tps_shift_degree # noqa + net.trafo.tap_phase_shifter = tps # codacy-disable + net.trafo.tap_pos = tps_tap_pos # codacy-disable + net.trafo.shift_degree = tps_shift_degree # codacy-disable if tct2w_flag: - net.trafo.tap_changer_type = tct2w # noqa - net.trafo.tap_pos = tct2w_tap_pos # noqa - net.trafo.shift_degree = tct2w_shift_degree # noqa + net.trafo.tap_changer_type = tct2w # codacy-disable + net.trafo.tap_pos = tct2w_tap_pos # codacy-disable + net.trafo.shift_degree = tct2w_shift_degree # codacy-disable if tct3w_flag: - net.trafo3w.tap_changer_type = tct3w # noqa - net.trafo3w.tap_pos = tct3w_tap_pos # noqa - net.trafo3w.shift_degree = tct3w_shift_degree # noqa + net.trafo3w.tap_changer_type = tct3w # codacy-disable + net.trafo3w.tap_pos = tct3w_tap_pos # codacy-disable + net.trafo3w.shift_degree = tct3w_shift_degree # codacy-disable n_lines = len(net.line) n_lines_cases = len(nminus1_cases.get("line", {}).get("index", [])) From abd849d148f8a3065fcb7abae0f893dc15f0150c Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 19 Dec 2024 20:05:11 +0200 Subject: [PATCH 079/125] update documentation to reflect tap_changer_type name change --- doc/elements/trafo.rst | 2 +- doc/elements/trafo3w.rst | 2 +- doc/elements/trafo3w_par.csv | 2 +- doc/elements/trafo_par.csv | 4 ++-- pandapower/create.py | 34 +++++++++++++++++----------------- 5 files changed, 22 insertions(+), 22 deletions(-) diff --git a/doc/elements/trafo.rst b/doc/elements/trafo.rst index 8bc0312f6..269ed9e9b 100644 --- a/doc/elements/trafo.rst +++ b/doc/elements/trafo.rst @@ -257,7 +257,7 @@ The below table provides an example trafo_characteristic_table, populated for tw :widths: 10, 55, 15, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55 .. note:: - - tap_dependency_table has to be set to True, and id_characteristic_table and tap_phase_shifter_type variables need to be populated in order to consider the corresponding trafo_characteristic_table values. + - tap_dependency_table has to be set to True, and id_characteristic_table and tap_changer_type variables need to be populated in order to consider the corresponding trafo_characteristic_table values. - Only one tap_dependency_table is supported per 2-winding transformer (there is no tap2_dependency_table variable) The function pandapower.control.trafo_characteristic_table_diagnostic can be used for sanity checks. diff --git a/doc/elements/trafo3w.rst b/doc/elements/trafo3w.rst index 126e83adb..7e48b65db 100644 --- a/doc/elements/trafo3w.rst +++ b/doc/elements/trafo3w.rst @@ -164,7 +164,7 @@ The below table provides an example trafo_characteristic_table, populated for tw :widths: 10, 55, 15, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55 .. note:: - tap_dependency_table has to be set to True, and id_characteristic_table and tap_phase_shifter_type variables need to be populated in order to consider the corresponding trafo_characteristic_table values. + tap_dependency_table has to be set to True, and id_characteristic_table and tap_changer_type variables need to be populated in order to consider the corresponding trafo_characteristic_table values. The function pandapower.control.trafo_characteristic_table_diagnostic can be used for sanity checks. The function pandapower.control.create_trafo_characteristic_object can be used to automatically create diff --git a/doc/elements/trafo3w_par.csv b/doc/elements/trafo3w_par.csv index 26b0a9c45..0ef05d7b3 100644 --- a/doc/elements/trafo3w_par.csv +++ b/doc/elements/trafo3w_par.csv @@ -28,7 +28,7 @@ tap_step_percent;float;:math:`>` 0;tap step size [%] tap_step_degree;float;;tap step size for voltage angle tap_at_star_point;boolean;True / False;whether the tap changer is modelled at terminal or at star point tap_pos;integer;;current position of tap changer -tap_phase_shifter_type;integer;0, 1, 2;specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal) +tap_changer_type;string;"""Ratio"", ""Symmetrical"", ""Ideal""";specifies the tap changer type tap_dependency_table;boolean;True / False;whether the transformer parameters (voltage ratio, angle, impedance) are adjusted dependent on the tap position of the transformer id_characteristic_table;integer;:math:`\geq` 0;references the id_characteristic index from the trafo_characteristic_table in_service*;boolean;True / False;specifies if the transformer is in service. diff --git a/doc/elements/trafo_par.csv b/doc/elements/trafo_par.csv index bf425ab69..470393689 100644 --- a/doc/elements/trafo_par.csv +++ b/doc/elements/trafo_par.csv @@ -26,7 +26,7 @@ tap_max;integer;;maximum tap position tap_step_percent;float;:math:`>` 0;tap step size for voltage magnitude [%] tap_step_degree;float;:math:`\geq` 0;tap step size for voltage angle tap_pos;integer;;current position of tap changer -tap_phase_shifter_type;integer;0, 1, 2;specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal) +tap_changer_type;string;"""Ratio"", ""Symmetrical"", ""Ideal""";specifies the tap changer type tap_dependency_table;boolean;True / False;whether the transformer parameters (voltage ratio, angle, impedance) are adjusted dependent on the tap position of the transformer id_characteristic_table;integer;:math:`\geq` 0;references the id_characteristic index from the trafo_characteristic_table parallel;integer;:math:`>` 0;number of parallel transformers @@ -42,6 +42,6 @@ tap2_max****;integer;;maximum tap position tap2_step_percent****;float;:math:`>` 0;tap step size for voltage magnitude [%] tap2_step_degree****;float;:math:`\geq` 0;tap step size for voltage angle tap2_pos****;integer;;current position of tap changer -tap2_phase_shifter_type****;integer;0, 1, 2;specifies the phase shifter type (0: Ratio/Asymmetrical, 1: Symmetrical, 2: Ideal) +tap2_changer_type****;string;"""Ratio"", ""Symmetrical"", ""Ideal""";specifies the tap changer type leakage_resistance_ratio_hv*;float;:math:0`\leq` 1;ratio of transformer short-circuit resistance on HV side (default 0.5) leakage_reactance_ratio_hv*;float;:math:0`\leq` 1;ratio of transformer short-circuit reactance on HV side (default 0.5) diff --git a/pandapower/create.py b/pandapower/create.py index 8637ad92b..121efcf93 100644 --- a/pandapower/create.py +++ b/pandapower/create.py @@ -3343,8 +3343,8 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in **id_characteristic_table** (int, nan) - references the index of the characteristic from the lookup table \ net.trafo_characteristic_table - **tap_changer_type** (String, nan) - specifies the phase shifter type ("Ratio": Ratio/Asymmetrical, - "Symmetrical": Symmetrical, "Ideal": Ideal, "None": no tap changer)* + **tap_changer_type** (string, None) - specifies the phase shifter type ("Ratio", "Symmetrical", "Ideal", + None: no tap changer)* **xn_ohm** (float) - impedance of the grounding reactor (Z_N) for short circuit calculation @@ -3410,7 +3410,7 @@ def create_transformer(net, hv_bus, lv_bus, std_type, name=None, tap_pos=nan, in _set_value_if_not_nan(net, index, tap_dependency_table, "tap_dependency_table", "trafo", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, tap_changer_type, "tap_changer_type", - "trafo", dtype=object, default_val = None) + "trafo", dtype=object, default_val=None) _set_value_if_not_nan(net, index, pt_percent, "pt_percent", "trafo") _set_value_if_not_nan(net, index, oltc, "oltc", "trafo", dtype=bool_, default_val=False) _set_value_if_not_nan(net, index, xn_ohm, "xn_ohm", "trafo") @@ -3502,8 +3502,8 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **tap_step_degree** (float) - tap step size for voltage angle in degree* - **tap_changer_type** (str, nan) - specifies the phase shifter type ("Ratio": Ratio/Asymmetrical, - "Symmetrical": Symmetrical, "Ideal": Ideal)* + **tap_changer_type** (str, None) - specifies the phase shifter type ("Ratio", "Symmetrical", "Ideal", + None: no tap changer)* **index** (int, None) - Force a specified ID if it is available. If None, the index one \ higher than the highest already existing index is selected. @@ -3546,8 +3546,8 @@ def create_transformer_from_parameters(net, hv_bus, lv_bus, sn_mva, vn_hv_kv, vn **tap2_step_degree** (float, nan) - second tap step size for voltage angle in degree* - **tap2_changer_type** (str, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, - 1: Symmetrical, 2: Ideal)* + **tap2_changer_type** (str, None) - specifies the tap changer type ("Ratio", "Symmetrical", "Ideal", + None: no tap changer)* **leakage_resistance_ratio_hv** (bool) - ratio of transformer short-circuit resistance on HV side (default 0.5) @@ -3713,8 +3713,8 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k **tap_step_degree** (list of float) - tap step size for voltage angle in degree* - **tap_changer_type** (list of str, nan) - specifies the tap changer type (0: Ratio/Asymmetrical, - 1: Symmetrical, 2: Ideal)* + **tap_changer_type** (list of str, None) - specifies the tap changer type ("Ratio", "Symmetrical", "Ideal", + None: no tap changer)* **index** (list of int, None) - Force a specified ID if it is available. If None, the index one \ higher than the highest already existing index is selected. @@ -3757,8 +3757,8 @@ def create_transformers_from_parameters(net, hv_buses, lv_buses, sn_mva, vn_hv_k **tap2_step_degree** (list of float) - second tap step size for voltage angle in degree* - **tap2_changer_type** (list of int, nan) - specifies the phase shifter type (0: Ratio/Asymmetrical, - 1: Symmetrical, 2: Ideal)* + **tap2_changer_type** (list of int, None) - specifies the tap changer type ("Ratio", "Symmetrical", "Ideal", + None: no tap changer)* ** only considered in load flow if calculate_voltage_angles = True @@ -3836,8 +3836,8 @@ def create_transformer3w(net, hv_bus, mv_bus, lv_bus, std_type, name=None, tap_p **tap_pos** (int, nan) - current tap position of the transformer. Defaults to the medium \ position (tap_neutral) - **tap_changer_type** (str, nan) - specifies the tap changer (0: Ratio/Asymmetrical, - 1: Symmetrical, 2: Ideal)* + **tap_changer_type** (str, None) - specifies the tap changer type ("Ratio", "Symmetrical", "Ideal", + None: no tap changer)* **tap_at_star_point** (boolean) - Whether tap changer is located at the star point of the \ 3W-transformer or at the bus @@ -4007,8 +4007,8 @@ def create_transformer3w_from_parameters( **tap_pos** (int, nan) - current tap position of the transformer. Defaults to the \ medium position (tap_neutral) - **tap_changer_type** (str, nan) -specifies the tap changer (0: Ratio/Asymmetrical, - 1: Symmetrical, 2: Ideal) + **tap_changer_type** (str, None) - specifies the tap changer type ("Ratio", "Symmetrical", "Ideal", + None: no tap changer) **tap_at_star_point** (boolean) - Whether tap changer is located at the star point of the \ 3W-transformer or at the bus @@ -4173,8 +4173,8 @@ def create_transformers3w_from_parameters( **tap_pos** (list of int, nan) - current tap position of the transformer. Defaults to the \ medium position (tap_neutral) - **tap_changer_type** (list of str, nan) - specifies the tap changer (0: Ratio/Asymmetrical, - 1: Symmetrical, 2: Ideal) + **tap_changer_type** (list of str, None) - specifies the tap changer type ("Ratio", "Symmetrical", "Ideal", + None: no tap changer) **tap_at_star_point** (list of boolean) - Whether tap changer is located at the star point of the \ 3W-transformer or at the bus From 762158a3e533e1f3e13c0bec0ee0817ffbbd7f90 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 19 Dec 2024 20:17:10 +0200 Subject: [PATCH 080/125] 2nd attempt to resolve codacy issue --- pandapower/contingency/contingency.py | 27 ++++++++++++++++++--------- 1 file changed, 18 insertions(+), 9 deletions(-) diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index c5137117b..17db28aff 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -218,17 +218,26 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. del net.trafo["tap_phase_shifter"] if tps_flag: - net.trafo.tap_phase_shifter = tps # codacy-disable - net.trafo.tap_pos = tps_tap_pos # codacy-disable - net.trafo.shift_degree = tps_shift_degree # codacy-disable + # codacy-disable-next-line + net.trafo.tap_phase_shifter = tps + # codacy-disable-next-line + net.trafo.tap_pos = tps_tap_pos + # codacy-disable-next-line + net.trafo.shift_degree = tps_shift_degree if tct2w_flag: - net.trafo.tap_changer_type = tct2w # codacy-disable - net.trafo.tap_pos = tct2w_tap_pos # codacy-disable - net.trafo.shift_degree = tct2w_shift_degree # codacy-disable + # codacy-disable-next-line + net.trafo.tap_changer_type = tct2w + # codacy-disable-next-line + net.trafo.tap_pos = tct2w_tap_pos + # codacy-disable-next-line + net.trafo.shift_degree = tct2w_shift_degree if tct3w_flag: - net.trafo3w.tap_changer_type = tct3w # codacy-disable - net.trafo3w.tap_pos = tct3w_tap_pos # codacy-disable - net.trafo3w.shift_degree = tct3w_shift_degree # codacy-disable + # codacy-disable-next-line + net.trafo3w.tap_changer_type = tct3w + # codacy-disable-next-line + net.trafo3w.tap_pos = tct3w_tap_pos + # codacy-disable-next-line + net.trafo3w.shift_degree = tct3w_shift_degree n_lines = len(net.line) n_lines_cases = len(nminus1_cases.get("line", {}).get("index", [])) From 3b622f4e4add4c870c4576c0cc9d05aff23977f7 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Thu, 19 Dec 2024 20:46:13 +0200 Subject: [PATCH 081/125] 3rd attempt to resolve codacy issue --- pandapower/contingency/contingency.py | 12 +++--------- 1 file changed, 3 insertions(+), 9 deletions(-) diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index 17db28aff..5bbd0c170 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -177,6 +177,7 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. contingency_evaluation_function(net, **kwargs) tps_flag = False + tps, tps_tap_pos, tps_shift_degree = None, None, None if "tap_phase_shifter" in net.trafo.columns: if np.any(net.trafo.tap_phase_shifter): tps_flag = True @@ -184,7 +185,9 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. net, "trafo", "tap_phase_shifter") tct2w_flag = False + tct2w, tct2w_tap_pos, tct2w_shift_degree = None, None, None tct3w_flag = False + tct3w, tct3w_tap_pos, tct3w_shift_degree = None, None, None if ("tap_changer_type" in net.trafo.columns) or ("tap_changer_type" in net.trafo3w.columns): if np.any(net.trafo.tap_changer_type == "Ideal"): tct2w_flag = True @@ -218,25 +221,16 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. del net.trafo["tap_phase_shifter"] if tps_flag: - # codacy-disable-next-line net.trafo.tap_phase_shifter = tps - # codacy-disable-next-line net.trafo.tap_pos = tps_tap_pos - # codacy-disable-next-line net.trafo.shift_degree = tps_shift_degree if tct2w_flag: - # codacy-disable-next-line net.trafo.tap_changer_type = tct2w - # codacy-disable-next-line net.trafo.tap_pos = tct2w_tap_pos - # codacy-disable-next-line net.trafo.shift_degree = tct2w_shift_degree if tct3w_flag: - # codacy-disable-next-line net.trafo3w.tap_changer_type = tct3w - # codacy-disable-next-line net.trafo3w.tap_pos = tct3w_tap_pos - # codacy-disable-next-line net.trafo3w.shift_degree = tct3w_shift_degree n_lines = len(net.line) From bf57ba2921c15041fa64b097002c9d3702caf6f6 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 20 Dec 2024 09:53:43 +0200 Subject: [PATCH 082/125] add test_shunt_characteristic_table_diagnostic test function --- pandapower/control/util/diagnostic.py | 11 +++++ .../control/test_tap_dependent_impedance.py | 49 ++++++++++++++++++- 2 files changed, 59 insertions(+), 1 deletion(-) diff --git a/pandapower/control/util/diagnostic.py b/pandapower/control/util/diagnostic.py index 4e27a75e5..5e3aa8f42 100644 --- a/pandapower/control/util/diagnostic.py +++ b/pandapower/control/util/diagnostic.py @@ -138,6 +138,7 @@ def shunt_characteristic_table_diagnostic(net): logger.info("No shunt characteristic table found") return False cols = ["id_characteristic", "step", "q_mvar", "p_mw"] + warnings_count = 0 if len(net["shunt"]) == 0 or \ not all(col in net["shunt"] for col in ['id_characteristic_table', 'step_dependency_table']) or \ (not net["shunt"]['id_characteristic_table'].notna().any() and @@ -153,6 +154,7 @@ def shunt_characteristic_table_diagnostic(net): warnings.warn(f"Found {mismatch} shunt(s) with not both " f"step_dependency_table and id_characteristic_table parameters populated. " f"Power flow calculation will raise an error.", category=UserWarning) + warnings_count += 1 # check if all relevant columns are populated in the shunt_characteristic_table temp = net["shunt"].dropna(subset=["id_characteristic_table"])[ ["step_dependency_table", "id_characteristic_table"]] @@ -162,16 +164,25 @@ def shunt_characteristic_table_diagnostic(net): if not unpopulated.empty: warnings.warn("There are some shunts with not all characteristics " "populated in the shunt_characteristic_table.", category=UserWarning) + warnings_count += 1 # check step_dependency_table & id_characteristic_table column types if net["shunt"]['step_dependency_table'].dtype != 'bool': warnings.warn("The step_dependency_table column in the shunt table is not of bool type.", category=UserWarning) + warnings_count += 1 if net["shunt"]['id_characteristic_table'].dtype != 'Int64': warnings.warn("The id_characteristic_table column in the shunt table is not of Int64 type.", category=UserWarning) + warnings_count += 1 # check if all id_characteristic_table values are present in id_characteristic column # of shunt_characteristic_table if not net["shunt"]['id_characteristic_table'].dropna().isin( net["shunt_characteristic_table"]['id_characteristic']).all(): warnings.warn("Not all id_characteristic_table values in the shunt table are present " "in id_characteristic column of shunt_characteristic_table.", category=UserWarning) + warnings_count += 1 + logger.info(f"{warnings_count} warnings were issued") + if warnings_count > 0: + return False + else: + return True diff --git a/pandapower/test/control/test_tap_dependent_impedance.py b/pandapower/test/control/test_tap_dependent_impedance.py index ad197de99..55ff811f3 100644 --- a/pandapower/test/control/test_tap_dependent_impedance.py +++ b/pandapower/test/control/test_tap_dependent_impedance.py @@ -9,7 +9,8 @@ import pandapower as pp from pandapower.control import Characteristic, SplineCharacteristic, TapDependentImpedance -from pandapower.control.util.diagnostic import trafo_characteristic_table_diagnostic +from pandapower.control.util.diagnostic import (trafo_characteristic_table_diagnostic, + shunt_characteristic_table_diagnostic) def test_tap_dependent_impedance_control(): @@ -165,5 +166,51 @@ def test_trafo_characteristic_table_diagnostic(): trafo_characteristic_table_diagnostic(net) +def test_shunt_characteristic_table_diagnostic(): + net = pp.create_empty_network() + vn_kv = 20 + b1 = pp.create_bus(net, vn_kv=vn_kv) + pp.create_shunt(net, bus=b1, q_mvar=-50, p_mw=0, step=1, max_step=5) + pp.create_ext_grid(net, b1, vm_pu=1.01) + b2 = pp.create_bus(net, vn_kv=vn_kv) + pp.create_line_from_parameters(net, b1, b2, 12.2, r_ohm_per_km=0.08, x_ohm_per_km=0.12, + c_nf_per_km=300, max_i_ka=.2, df=.8) + cb = pp.create_bus(net, vn_kv=0.4) + pp.create_load(net, cb, 0.2, 0.05) + pp.create_transformer(net, hv_bus=b2, lv_bus=cb, std_type="0.25 MVA 20/0.4 kV", tap_pos=2) + + # initially no shunt_characteristic_table is available + assert shunt_characteristic_table_diagnostic(net) is False + + # add shunt_characteristic_table + net["shunt_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [1, 2, 3, 4, 5], 'q_mvar': [-25, -55, -75, -120, -125], + 'p_mw': [1, 1.5, 3, 4.5, 5]}) + # populate id_characteristic_table parameter + net.shunt['id_characteristic_table'].at[0] = 0 + net.shunt['step_dependency_table'].at[0] = False + with pytest.warns(UserWarning): + shunt_characteristic_table_diagnostic(net) + # populate step_dependency_table parameter + net.shunt['step_dependency_table'].at[0] = True + assert shunt_characteristic_table_diagnostic(net) is True + + # add shunt_characteristic_table with missing parameter values + net["shunt_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [1, 2, 3, 4, 5], 'q_mvar': [-25, -55, -75, -120, -125], + 'p_mw': np.nan}) + with pytest.warns(UserWarning): + shunt_characteristic_table_diagnostic(net) + + # let's make some invalid configurations + net.shunt.at[0, "step_dependency_table"] = 0 + with pytest.warns(UserWarning): + shunt_characteristic_table_diagnostic(net) + net.shunt.at[0, "step_dependency_table"] = True + net.shunt.at[0, "id_characteristic_table"] = int(2) + with pytest.warns(UserWarning): + shunt_characteristic_table_diagnostic(net) + + if __name__ == '__main__': pytest.main([__file__, "-xs"]) From 435a728209061451e443af366c543d30eefe285b Mon Sep 17 00:00:00 2001 From: tfabian Date: Fri, 20 Dec 2024 09:18:25 +0100 Subject: [PATCH 083/125] revert json files back (because current status was only half-updated and wrong) had to fix one test. /cas9 grid equivalent / build branch --- pandapower/build_branch.py | 2 +- pandapower/convert_format.py | 7 +- .../networks/IEEE_European_LV_Off_Peak_1.json | 45 ++++++++----- .../IEEE_European_LV_Off_Peak_1440.json | 45 ++++++++----- .../IEEE_European_LV_On_Peak_566.json | 45 ++++++++----- pandapower/networks/lv_schutterwald.json | 55 +++++++++------- pandapower/networks/mv_oberrhein.json | 15 ++++- .../networks/mv_oberrhein_substations.json | 15 ++++- .../GBnetwork.json | 34 ++++------ .../GBreducednetwork.json | 34 ++++------ .../power_system_test_case_jsons/case118.json | 60 +++++++++-------- .../case11_iwamoto.json | 64 +++++++++++-------- .../case1354pegase.json | 60 +++++++++-------- .../power_system_test_case_jsons/case14.json | 60 +++++++++-------- .../power_system_test_case_jsons/case145.json | 60 +++++++++-------- .../case1888rte.json | 60 +++++++++-------- .../case24_ieee_rts.json | 60 +++++++++-------- .../case2848rte.json | 60 +++++++++-------- .../case2869pegase.json | 60 +++++++++-------- .../power_system_test_case_jsons/case30.json | 60 +++++++++-------- .../power_system_test_case_jsons/case300.json | 60 +++++++++-------- .../case3120sp.json | 60 +++++++++-------- .../case33bw.json | 60 +++++++++-------- .../power_system_test_case_jsons/case39.json | 60 +++++++++-------- .../power_system_test_case_jsons/case4gs.json | 60 +++++++++-------- .../power_system_test_case_jsons/case5.json | 60 +++++++++-------- .../power_system_test_case_jsons/case57.json | 60 +++++++++-------- .../case5_demo_gridcal.json | 34 ++++------ .../case6470rte.json | 60 +++++++++-------- .../case6495rte.json | 60 +++++++++-------- .../case6515rte.json | 60 +++++++++-------- .../power_system_test_case_jsons/case6ww.json | 60 +++++++++-------- .../case89pegase.json | 60 +++++++++-------- .../power_system_test_case_jsons/case9.json | 60 +++++++++-------- .../case9241pegase.json | 60 +++++++++-------- .../case_ieee30.json | 60 +++++++++-------- .../case_illinois200.json | 60 +++++++++-------- .../power_system_test_case_jsons/iceland.json | 34 ++++------ .../test_grid_equivalents_toolbox.py | 1 + 39 files changed, 1091 insertions(+), 839 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 98d446e2f..3252a7847 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -655,7 +655,7 @@ def _calc_tap_from_dataframe(net, trafo_df): vn[mask_complex] = np.sqrt((u1 + du * cos(tap_angles)) ** 2 + (du * sin(tap_angles)) ** 2) trafo_shift[mask_complex] += (arctan(direction * du * sin(tap_angles) / (u1 + du * cos(tap_angles)))) - else: + elif f'tap{t}_phase_shifter' in trafo_df: tap_phase_shifter = get_trafo_values(trafo_df, f"tap{t}_phase_shifter") for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: tap_ideal = tap_phase_shifter & (tap_side == side) diff --git a/pandapower/convert_format.py b/pandapower/convert_format.py index 5fc633d7d..491302c81 100644 --- a/pandapower/convert_format.py +++ b/pandapower/convert_format.py @@ -558,11 +558,12 @@ def convert_trafo_pst_logic(net): """ for trafotable in ["trafo", "trafo3w"]: if trafotable in net and isinstance(net[trafotable], pd.DataFrame): + for t in ("", "2"): + # drop old tap_phase_shifter flag + if f"tap{t}_phase_shifter" in net[trafotable]: + net[trafotable] = net[trafotable].drop(columns=f"tap{t}_phase_shifter") if net[trafotable].index.size > 0: for t in ("", "2"): - # drop old tap_phase_shifter flag - if f"tap{t}_phase_shifter" in net[trafotable]: - net[trafotable] = net[trafotable].drop(columns=f"tap{t}_phase_shifter") if (f"tap{t}_step_degree" in net[trafotable]) or (f"tap{t}_step_percent" in net[trafotable]): # no phase shifters - check if both tap_step_percent & tap_step_degree are 0 or nan mask_na = (((net[trafotable][f"tap{t}_step_degree"].isna()) | diff --git a/pandapower/networks/IEEE_European_LV_Off_Peak_1.json b/pandapower/networks/IEEE_European_LV_Off_Peak_1.json index 91e7ba0a8..e91c815a8 100644 --- a/pandapower/networks/IEEE_European_LV_Off_Peak_1.json +++ b/pandapower/networks/IEEE_European_LV_Off_Peak_1.json @@ -318,7 +318,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", "orient": "split", "dtype": { "name": "object", @@ -340,7 +340,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -546,6 +546,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -1192,7 +1203,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1210,7 +1221,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1228,7 +1239,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1246,7 +1257,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "08 MVA 10/04 kV Dyn1 ASEA": { "sn_mva": 0.800000011920929, @@ -1266,7 +1277,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1287,7 +1298,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1305,7 +1316,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1323,7 +1334,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1341,7 +1352,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1359,7 +1370,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1377,7 +1388,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1395,7 +1406,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1413,7 +1424,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1431,7 +1442,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1449,7 +1460,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json b/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json index a8fd79c05..ccc96d974 100644 --- a/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json +++ b/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json @@ -318,7 +318,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", "orient": "split", "dtype": { "name": "object", @@ -340,7 +340,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -546,6 +546,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -1192,7 +1203,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1210,7 +1221,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1228,7 +1239,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1246,7 +1257,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "08 MVA 10/04 kV Dyn1 ASEA": { "sn_mva": 0.800000011920929, @@ -1266,7 +1277,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1287,7 +1298,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1305,7 +1316,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1323,7 +1334,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1341,7 +1352,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1359,7 +1370,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1377,7 +1388,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1395,7 +1406,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1413,7 +1424,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1431,7 +1442,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1449,7 +1460,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/networks/IEEE_European_LV_On_Peak_566.json b/pandapower/networks/IEEE_European_LV_On_Peak_566.json index b56aba730..870517ef1 100644 --- a/pandapower/networks/IEEE_European_LV_On_Peak_566.json +++ b/pandapower/networks/IEEE_European_LV_On_Peak_566.json @@ -318,7 +318,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"tap_set_vm_pu\",\"description\",\"equipment\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[0],\"data\":[[\"Trafo\",\"08 MVA 10\\/04 kV Dyn1 ASEA\",0,1,0.800000011920929,11.0,0.416000008583069,4.019950389862061,0.400000005960464,0.0,0.0,30.0,\"hv\",0,-2,2,2.5,0.0,0,false,1,1.0,true,1.0,\"\",\"\",\"Dyn\",4.019950389862061,0.400000005960464,1,0,0.899999976158142]]}", "orient": "split", "dtype": { "name": "object", @@ -340,7 +340,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -546,6 +546,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -1192,7 +1203,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1210,7 +1221,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1228,7 +1239,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1246,7 +1257,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "08 MVA 10/04 kV Dyn1 ASEA": { "sn_mva": 0.800000011920929, @@ -1266,7 +1277,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1287,7 +1298,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1305,7 +1316,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1323,7 +1334,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1341,7 +1352,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1359,7 +1370,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1377,7 +1388,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1395,7 +1406,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1413,7 +1424,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1431,7 +1442,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1449,7 +1460,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false } }, "trafo3w": { diff --git a/pandapower/networks/lv_schutterwald.json b/pandapower/networks/lv_schutterwald.json index 059708cd6..b33bacfb1 100644 --- a/pandapower/networks/lv_schutterwald.json +++ b/pandapower/networks/lv_schutterwald.json @@ -290,7 +290,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1,3,4,5,6,7,10,11,12,13,14,15,16],\"data\":[[\"T_idx_47\",\"0.4 MVA 20\\/0.4 kV\",2983,3000,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_45\",\"0.25 MVA 20\\/0.4 kV\",2984,3001,0.25,20.0,0.4,6.0,1.44,0.8,0.32,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_35\",\"0.4 MVA 20\\/0.4 kV\",2986,3003,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_77\",\"0.4 MVA 20\\/0.4 kV\",2987,3004,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_78\",\"0.63 MVA 20\\/0.4 kV\",2988,3005,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_119\",\"0.63 MVA 20\\/0.4 kV\",2989,3006,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_118\",\"0.63 MVA 20\\/0.4 kV\",2990,3007,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_117\",\"0.4 MVA 20\\/0.4 kV\",2993,3010,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_80\",\"0.63 MVA 20\\/0.4 kV\",2994,3011,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_73\",\"0.63 MVA 20\\/0.4 kV\",2995,3012,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_43\",\"0.63 MVA 20\\/0.4 kV\",2996,3013,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_81\",\"0.63 MVA 20\\/0.4 kV\",2997,3014,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_71\",\"0.4 MVA 20\\/0.4 kV\",2998,3015,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_ZUSATZ\",\"0.63 MVA 20\\/0.4 kV\",2999,3016,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1,3,4,5,6,7,10,11,12,13,14,15,16],\"data\":[[\"T_idx_47\",\"0.4 MVA 20\\/0.4 kV\",2983,3000,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_45\",\"0.25 MVA 20\\/0.4 kV\",2984,3001,0.25,20.0,0.4,6.0,1.44,0.8,0.32,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_35\",\"0.4 MVA 20\\/0.4 kV\",2986,3003,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_77\",\"0.4 MVA 20\\/0.4 kV\",2987,3004,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_78\",\"0.63 MVA 20\\/0.4 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kV\",2997,3014,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_71\",\"0.4 MVA 20\\/0.4 kV\",2998,3015,0.4,20.0,0.4,6.0,1.425,1.35,0.3375,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true],[\"T_idx_ZUSATZ\",\"0.63 MVA 20\\/0.4 kV\",2999,3016,0.63,20.0,0.4,6.0,1.206,1.65,0.2619,150.0,\"hv\",0,-2,2,2.5,0.0,1,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -312,7 +312,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -509,6 +509,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -915,7 +926,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 160.0 }, "100 MVA 220/110 kV": { @@ -933,7 +944,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 100.0 }, "63 MVA 110/20 kV": { @@ -951,7 +962,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 63.0 }, "40 MVA 110/20 kV": { @@ -969,7 +980,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 40.0 }, "25 MVA 110/20 kV": { @@ -987,7 +998,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 25.0 }, "63 MVA 110/10 kV": { @@ -1005,7 +1016,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 63.0 }, "40 MVA 110/10 kV": { @@ -1023,7 +1034,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 40.0 }, "25 MVA 110/10 kV": { @@ -1041,7 +1052,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 25.0 }, "63 MVA 110/20 kV v1.4.3 and older": { @@ -1059,7 +1070,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 63.0 }, "40 MVA 110/20 kV v1.4.3 and older": { @@ -1077,7 +1088,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 40.0 }, "25 MVA 110/20 kV v1.4.3 and older": { @@ -1095,7 +1106,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 25.0 }, "63 MVA 110/10 kV v1.4.3 and older": { @@ -1113,7 +1124,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 63.0 }, "40 MVA 110/10 kV v1.4.3 and older": { @@ -1131,7 +1142,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 40.0 }, "25 MVA 110/10 kV v1.4.3 and older": { @@ -1149,7 +1160,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 25.0 }, "0.25 MVA 20/0.4 kV": { @@ -1167,7 +1178,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 0.25 }, "0.4 MVA 20/0.4 kV": { @@ -1185,7 +1196,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 0.4 }, "0.63 MVA 20/0.4 kV": { @@ -1203,7 +1214,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 0.63 }, "0.25 MVA 10/0.4 kV": { @@ -1221,7 +1232,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 0.25 }, "0.4 MVA 10/0.4 kV": { @@ -1239,7 +1250,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 0.4 }, "0.63 MVA 10/0.4 kV": { @@ -1257,7 +1268,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "sn_mva": 0.63 } }, diff --git a/pandapower/networks/mv_oberrhein.json b/pandapower/networks/mv_oberrhein.json index b81d29bac..00053a005 100644 --- a/pandapower/networks/mv_oberrhein.json +++ b/pandapower/networks/mv_oberrhein.json @@ -292,7 +292,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[114,142],\"data\":[[\"HV\\/MV Transformer 0\",\"25 MVA 110\\/20 kV\",58,39,25.0,110.0,20.0,11.199999999999999,0.282,29.0,0.071,150.0,\"hv\",0,-9,9,1.5,null,-2,false,1,1.0,true],[\"HV\\/MV Transformer 1\",\"25 MVA 110\\/20 kV\",318,319,25.0,110.0,20.0,11.199999999999999,0.282,29.0,0.071,150.0,\"hv\",0,-9,9,1.5,null,-3,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[114,142],\"data\":[[\"HV\\/MV Transformer 0\",\"25 MVA 110\\/20 kV\",58,39,25.0,110.0,20.0,11.199999999999999,0.282,29.0,0.071,150.0,\"hv\",0,-9,9,1.5,null,-2,false,1,1.0,true],[\"HV\\/MV Transformer 1\",\"25 MVA 110\\/20 kV\",318,319,25.0,110.0,20.0,11.199999999999999,0.282,29.0,0.071,150.0,\"hv\",0,-9,9,1.5,null,-3,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -314,7 +314,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_phase_shifter_type": "uint32", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -514,6 +514,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/mv_oberrhein_substations.json b/pandapower/networks/mv_oberrhein_substations.json index d0b8998fb..0becaa3fd 100644 --- a/pandapower/networks/mv_oberrhein_substations.json +++ b/pandapower/networks/mv_oberrhein_substations.json @@ -292,7 +292,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"float64", "in_service": "bool" @@ -514,6 +514,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/GBnetwork.json b/pandapower/networks/power_system_test_case_jsons/GBnetwork.json index fe2633406..9e25cb852 100644 --- a/pandapower/networks/power_system_test_case_jsons/GBnetwork.json +++ b/pandapower/networks/power_system_test_case_jsons/GBnetwork.json @@ -296,7 +296,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -318,7 +318,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -329,7 +329,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -359,7 +359,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -516,6 +515,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -794,7 +804,6 @@ "tap_min": -2, "vkr_percent": 1.425, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -812,7 +821,6 @@ "tap_min": -2, "vkr_percent": 1.44, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -830,7 +838,6 @@ "tap_min": -2, "vkr_percent": 1.2, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -848,7 +855,6 @@ "tap_min": -9, "vkr_percent": 0.25, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 12.2, "tap_max": 9 @@ -866,7 +872,6 @@ "tap_min": -9, "vkr_percent": 0.31, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -884,7 +889,6 @@ "tap_min": -2, "vkr_percent": 1.206, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -902,7 +906,6 @@ "tap_min": -2, "vkr_percent": 1.325, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -920,7 +923,6 @@ "tap_min": -2, "vkr_percent": 1.0794, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -938,7 +940,6 @@ "tap_min": -9, "vkr_percent": 0.322, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -956,7 +957,6 @@ "tap_min": -9, "vkr_percent": 0.26, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 12.0, "tap_max": 9 @@ -974,7 +974,6 @@ "tap_min": -9, "vkr_percent": 0.276, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -992,7 +991,6 @@ "tap_min": -9, "vkr_percent": 0.302, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1010,7 +1008,6 @@ "tap_min": -9, "vkr_percent": 0.282, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1028,7 +1025,6 @@ "tap_min": -9, "vkr_percent": 0.295, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -1056,7 +1052,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1081,7 +1076,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json b/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json index d4766c9a0..e12a8873b 100644 --- a/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json +++ b/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json @@ -301,7 +301,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1,10,11,12,2,3,4,5,6,7,8,9],\"data\":[[null,null,0,2,132.0,275.0,132.0,19.8215482745,0.924,0.0,-3.9393939394,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,0,2,132.0,275.0,132.0,19.8215482745,0.924,0.0,-3.9393939394,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,3,2,648.0,275.0,132.0,26.639027009300001,1.944,0.0,-0.0679012346,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,3,2,648.0,275.0,132.0,26.639027009300001,1.944,0.0,-0.6790123457,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,1,2,652.0,275.0,132.0,53.889295279899997,19.586079999999999,0.0,-0.1901840491,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,6,3,1090.0,400.0,275.0,14.893648478799999,2.2999,0.0,-1.0770642202,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,5,3,1500.0,400.0,275.0,34.555064751800003,1.95,0.0,-0.9973333333,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,5,3,1120.0,400.0,275.0,25.801115014699999,1.456,0.0,-1.5696428571,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,4,3,1000.0,400.0,275.0,24.020824298899999,1.0,0.0,-1.25,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,4,3,1000.0,400.0,275.0,24.020824298899999,1.0,0.0,-1.25,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,6,3,1090.0,400.0,275.0,14.8919691781,2.289,0.0,-1.4110091743,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,11,17,2400.0,400.0,400.0,21.672890347199999,1.776,0.0,-1.2129166667,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,11,12,3100.0,400.0,400.0,33.550250371600001,2.976,0.0,-1.2419354839,2.0,null,null,null,null,null,null,null,false,1,1.0,true]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[0,1,10,11,12,2,3,4,5,6,7,8,9],\"data\":[[null,null,0,2,132.0,275.0,132.0,19.8215482745,0.924,0.0,-3.9393939394,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,0,2,132.0,275.0,132.0,19.8215482745,0.924,0.0,-3.9393939394,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,3,2,648.0,275.0,132.0,26.639027009300001,1.944,0.0,-0.0679012346,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,3,2,648.0,275.0,132.0,26.639027009300001,1.944,0.0,-0.6790123457,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,1,2,652.0,275.0,132.0,53.889295279899997,19.586079999999999,0.0,-0.1901840491,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,6,3,1090.0,400.0,275.0,14.893648478799999,2.2999,0.0,-1.0770642202,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,5,3,1500.0,400.0,275.0,34.555064751800003,1.95,0.0,-0.9973333333,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,5,3,1120.0,400.0,275.0,25.801115014699999,1.456,0.0,-1.5696428571,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,4,3,1000.0,400.0,275.0,24.020824298899999,1.0,0.0,-1.25,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,4,3,1000.0,400.0,275.0,24.020824298899999,1.0,0.0,-1.25,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,6,3,1090.0,400.0,275.0,14.8919691781,2.289,0.0,-1.4110091743,0.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,11,17,2400.0,400.0,400.0,21.672890347199999,1.776,0.0,-1.2129166667,2.0,null,null,null,null,null,null,null,false,1,1.0,true],[null,null,11,12,3100.0,400.0,400.0,33.550250371600001,2.976,0.0,-1.2419354839,2.0,null,null,null,null,null,null,null,false,1,1.0,true]]}", "orient": "split", "dtype": { "name": "object", @@ -323,7 +323,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -334,7 +334,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -364,7 +364,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -522,6 +521,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -799,7 +809,6 @@ "tap_min": -2, "vkr_percent": 1.425, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -816,7 +825,6 @@ "tap_min": -2, "vkr_percent": 1.44, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -833,7 +841,6 @@ "tap_min": -2, "vkr_percent": 1.2, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -850,7 +857,6 @@ "tap_min": -9, "vkr_percent": 0.25, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 12.2, "tap_max": 9 @@ -867,7 +873,6 @@ "tap_min": -9, "vkr_percent": 0.31, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -884,7 +889,6 @@ "tap_min": -2, "vkr_percent": 1.206, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -901,7 +905,6 @@ "tap_min": -2, "vkr_percent": 1.325, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -918,7 +921,6 @@ "tap_min": -2, "vkr_percent": 1.0794, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -935,7 +937,6 @@ "tap_min": -9, "vkr_percent": 0.322, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -952,7 +953,6 @@ "tap_min": -9, "vkr_percent": 0.26, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 12.0, "tap_max": 9 @@ -969,7 +969,6 @@ "tap_min": -9, "vkr_percent": 0.276, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -986,7 +985,6 @@ "tap_min": -9, "vkr_percent": 0.302, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1003,7 +1001,6 @@ "tap_min": -9, "vkr_percent": 0.282, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1020,7 +1017,6 @@ "tap_min": -9, "vkr_percent": 0.295, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -1048,7 +1044,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1073,7 +1068,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case118.json b/pandapower/networks/power_system_test_case_jsons/case118.json index 6323f7ccc..28efc1bdc 100644 --- a/pandapower/networks/power_system_test_case_jsons/case118.json +++ b/pandapower/networks/power_system_test_case_jsons/case118.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,11,12,2,3,4,5,6,7,8,9],\"data\":[[null,null,7,4,9900.0,345.0,138.0,264.329999999999984,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,1.5,null,-1.0,false,1,1.0,true,100.0],[null,null,25,24,9900.0,345.0,138.0,378.180000000000007,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,80,79,9900.0,345.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,86,85,9900.0,161.0,138.0,2072.25986507098105,279.97199999999998,0.0,-0.04494949494949,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,115,67,9900.0,345.0,161.0,40.236040821631541,3.366,0.0,-0.16565656565657,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,29,16,9900.0,345.0,138.0,384.120000000000005,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,37,36,9900.0,345.0,138.0,371.25,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,62,58,9900.0,345.0,138.0,382.139999999999986,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,63,60,9900.0,345.0,138.0,265.319999999999993,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,1.5,null,-1.0,false,1,1.0,true,100.0],[null,null,64,65,9900.0,345.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,64,67,9900.0,345.0,161.0,158.988082081645359,13.662000000000001,0.0,-0.64444444444444,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,67,68,9900.0,161.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,80,67,9900.0,345.0,161.0,200.72906123678257,17.324999999999999,0.0,-0.81616161616162,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,11,12,2,3,4,5,6,7,8,9],\"data\":[[null,null,7,4,9900.0,345.0,138.0,264.329999999999984,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,1.5,null,-1.0,false,1,1.0,true,100.0],[null,null,25,24,9900.0,345.0,138.0,378.180000000000007,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,80,79,9900.0,345.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,86,85,9900.0,161.0,138.0,2072.25986507098105,279.97199999999998,0.0,-0.04494949494949,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,115,67,9900.0,345.0,161.0,40.236040821631541,3.366,0.0,-0.16565656565657,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,29,16,9900.0,345.0,138.0,384.120000000000005,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,37,36,9900.0,345.0,138.0,371.25,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,62,58,9900.0,345.0,138.0,382.139999999999986,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.0,null,-1.0,false,1,1.0,true,100.0],[null,null,63,60,9900.0,345.0,138.0,265.319999999999993,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,1.5,null,-1.0,false,1,1.0,true,100.0],[null,null,64,65,9900.0,345.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,64,67,9900.0,345.0,161.0,158.988082081645359,13.662000000000001,0.0,-0.64444444444444,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,67,68,9900.0,161.0,138.0,366.300000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.49999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,80,67,9900.0,345.0,161.0,200.72906123678257,17.324999999999999,0.0,-0.81616161616162,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,7 +362,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -519,6 +518,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -918,7 +928,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -936,7 +946,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -954,7 +964,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -972,7 +982,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -990,7 +1000,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1008,7 +1018,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1026,7 +1036,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1044,7 +1054,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1062,7 +1072,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1080,7 +1090,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1098,7 +1108,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1116,7 +1126,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1134,7 +1144,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1152,7 +1162,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1170,7 +1180,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1188,7 +1198,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1206,7 +1216,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1224,7 +1234,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1242,7 +1252,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1260,7 +1270,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1287,7 +1297,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1312,7 +1321,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json b/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json index 685df097c..ab15b1e10 100644 --- a/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json +++ b/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json @@ -287,7 +287,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -309,7 +309,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -320,7 +320,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -350,7 +350,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -507,6 +506,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -908,7 +918,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -926,7 +936,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -944,7 +954,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -962,7 +972,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -980,7 +990,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "vn_hv_kv": 110, @@ -998,7 +1008,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "vn_hv_kv": 110, @@ -1016,7 +1026,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "vn_hv_kv": 110, @@ -1034,7 +1044,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/20 kV v1.4.3 and older": { "i0_percent": 0.086, @@ -1052,7 +1062,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/20 kV v1.4.3 and older": { "i0_percent": 0.08, @@ -1070,7 +1080,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/20 kV v1.4.3 and older": { "i0_percent": 0.071, @@ -1088,7 +1098,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/10 kV v1.4.3 and older": { "vn_hv_kv": 110, @@ -1106,7 +1116,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/10 kV v1.4.3 and older": { "vn_hv_kv": 110, @@ -1124,7 +1134,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/10 kV v1.4.3 and older": { "vn_hv_kv": 110, @@ -1142,7 +1152,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "vn_hv_kv": 20, @@ -1160,7 +1170,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "vn_hv_kv": 20, @@ -1178,7 +1188,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "vn_hv_kv": 20, @@ -1196,7 +1206,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "vn_hv_kv": 10, @@ -1214,7 +1224,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "vn_hv_kv": 10, @@ -1232,7 +1242,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "vn_hv_kv": 10, @@ -1250,7 +1260,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false } }, "trafo3w": { @@ -1276,8 +1286,7 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2, - "tap_changer_type": "Ratio" + "tap_step_percent": 1.2 }, "63/25/38 MVA 110/10/10 kV": { "vn_hv_kv": 110, @@ -1301,8 +1310,7 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2, - "tap_changer_type": "Ratio" + "tap_step_percent": 1.2 } }, "fuse": {} diff --git a/pandapower/networks/power_system_test_case_jsons/case1354pegase.json b/pandapower/networks/power_system_test_case_jsons/case1354pegase.json index b679c7f9d..840d7cf2f 100644 --- a/pandapower/networks/power_system_test_case_jsons/case1354pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case1354pegase.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,7 +363,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -520,6 +519,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -919,7 +929,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -937,7 +947,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -955,7 +965,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -973,7 +983,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -991,7 +1001,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1009,7 +1019,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1027,7 +1037,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1045,7 +1055,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1063,7 +1073,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1081,7 +1091,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1099,7 +1109,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1117,7 +1127,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1135,7 +1145,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1153,7 +1163,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1171,7 +1181,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1189,7 +1199,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1207,7 +1217,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1225,7 +1235,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1243,7 +1253,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1261,7 +1271,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1288,7 +1298,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1313,7 +1322,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case14.json b/pandapower/networks/power_system_test_case_jsons/case14.json index 946d9ac19..f64d58cf2 100644 --- a/pandapower/networks/power_system_test_case_jsons/case14.json +++ b/pandapower/networks/power_system_test_case_jsons/case14.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,3,6,9900.0,135.0,14.0,2070.288000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,3,8,9900.0,135.0,0.208,5506.181999999999789,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.1,null,-1.0,false,1,1.0,true,100.0],[null,null,4,5,9900.0,135.0,0.208,2494.998000000000047,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.8,null,-1.0,false,1,1.0,true,100.0],[null,null,6,7,9900.0,14.0,12.0,1743.884999999999991,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,6,8,9900.0,14.0,0.208,1089.098999999999933,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,3,6,9900.0,135.0,14.0,2070.288000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,3,8,9900.0,135.0,0.208,5506.181999999999789,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.1,null,-1.0,false,1,1.0,true,100.0],[null,null,4,5,9900.0,135.0,0.208,2494.998000000000047,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.8,null,-1.0,false,1,1.0,true,100.0],[null,null,6,7,9900.0,14.0,12.0,1743.884999999999991,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,6,8,9900.0,14.0,0.208,1089.098999999999933,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,7 +362,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -519,6 +518,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -918,7 +928,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -936,7 +946,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -954,7 +964,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -972,7 +982,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -990,7 +1000,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1008,7 +1018,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1026,7 +1036,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1044,7 +1054,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1062,7 +1072,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1080,7 +1090,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1098,7 +1108,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1116,7 +1126,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1134,7 +1144,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1152,7 +1162,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1170,7 +1180,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1188,7 +1198,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1206,7 +1216,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1224,7 +1234,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1242,7 +1252,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1260,7 +1270,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1287,7 +1297,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1312,7 +1321,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case145.json b/pandapower/networks/power_system_test_case_jsons/case145.json index 7537a9199..623f9a433 100644 --- a/pandapower/networks/power_system_test_case_jsons/case145.json +++ b/pandapower/networks/power_system_test_case_jsons/case145.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,7 +363,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -520,6 +519,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -919,7 +929,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -937,7 +947,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -955,7 +965,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -973,7 +983,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -991,7 +1001,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1009,7 +1019,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1027,7 +1037,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1045,7 +1055,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1063,7 +1073,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1081,7 +1091,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1099,7 +1109,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1117,7 +1127,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1135,7 +1145,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1153,7 +1163,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1171,7 +1181,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1189,7 +1199,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1207,7 +1217,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1225,7 +1235,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1243,7 +1253,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1261,7 +1271,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1288,7 +1298,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1313,7 +1322,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case1888rte.json b/pandapower/networks/power_system_test_case_jsons/case1888rte.json index 09d9ba1d8..ae0d70712 100644 --- a/pandapower/networks/power_system_test_case_jsons/case1888rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case1888rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -524,6 +523,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -923,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1302,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1326,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json b/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json index 9986230e5..c169eacc0 100644 --- a/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json +++ b/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,23,2,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,10,8,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,11,8,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,10,9,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,2.0,null,1,false,1,1.0,true,100.0],[null,null,11,9,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,2.0,null,1,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,23,2,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,10,8,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,11,8,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,3.0,null,1,false,1,1.0,true,100.0],[null,null,10,9,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,2.0,null,1,false,1,1.0,true,100.0],[null,null,11,9,400.0,230.0,138.0,33.572607882021913,0.92,0.0,0.0,0.0,\"hv\",0,null,null,2.0,null,1,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -524,6 +523,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -923,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1302,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1326,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case2848rte.json b/pandapower/networks/power_system_test_case_jsons/case2848rte.json index abf7c25a9..a7375b421 100644 --- a/pandapower/networks/power_system_test_case_jsons/case2848rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case2848rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -524,6 +523,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -923,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1302,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1326,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case2869pegase.json b/pandapower/networks/power_system_test_case_jsons/case2869pegase.json index 912913b90..1834b4dbf 100644 --- a/pandapower/networks/power_system_test_case_jsons/case2869pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case2869pegase.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,7 +363,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -520,6 +519,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -919,7 +929,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -937,7 +947,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -955,7 +965,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -973,7 +983,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -991,7 +1001,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1009,7 +1019,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1027,7 +1037,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1045,7 +1055,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1063,7 +1073,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1081,7 +1091,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1099,7 +1109,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1117,7 +1127,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1135,7 +1145,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1153,7 +1163,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1171,7 +1181,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1189,7 +1199,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1207,7 +1217,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1225,7 +1235,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1243,7 +1253,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1261,7 +1271,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1288,7 +1298,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1313,7 +1322,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case30.json b/pandapower/networks/power_system_test_case_jsons/case30.json index 767a58c91..68d2f55a8 100644 --- a/pandapower/networks/power_system_test_case_jsons/case30.json +++ b/pandapower/networks/power_system_test_case_jsons/case30.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -331,7 +331,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -361,7 +361,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -518,6 +517,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -917,7 +927,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -935,7 +945,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -953,7 +963,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -971,7 +981,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -989,7 +999,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1007,7 +1017,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1025,7 +1035,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1043,7 +1053,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1061,7 +1071,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1079,7 +1089,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1097,7 +1107,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1115,7 +1125,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1133,7 +1143,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1151,7 +1161,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1169,7 +1179,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1187,7 +1197,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1205,7 +1215,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1223,7 +1233,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1241,7 +1251,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1259,7 +1269,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1286,7 +1296,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1311,7 +1320,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case300.json b/pandapower/networks/power_system_test_case_jsons/case300.json index 7b3a56b16..a3af72513 100644 --- a/pandapower/networks/power_system_test_case_jsons/case300.json +++ b/pandapower/networks/power_system_test_case_jsons/case300.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,7 +363,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -520,6 +519,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -919,7 +929,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -937,7 +947,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -955,7 +965,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -973,7 +983,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -991,7 +1001,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1009,7 +1019,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1027,7 +1037,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1045,7 +1055,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1063,7 +1073,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1081,7 +1091,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1099,7 +1109,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1117,7 +1127,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1135,7 +1145,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1153,7 +1163,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1171,7 +1181,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1189,7 +1199,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1207,7 +1217,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1225,7 +1235,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1243,7 +1253,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1261,7 +1271,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1288,7 +1298,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1313,7 +1322,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case3120sp.json b/pandapower/networks/power_system_test_case_jsons/case3120sp.json index 963e00458..cf9adb5b1 100644 --- a/pandapower/networks/power_system_test_case_jsons/case3120sp.json +++ b/pandapower/networks/power_system_test_case_jsons/case3120sp.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -524,6 +523,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -923,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1302,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1326,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case33bw.json b/pandapower/networks/power_system_test_case_jsons/case33bw.json index 3c3f663d1..9ef5276c6 100644 --- a/pandapower/networks/power_system_test_case_jsons/case33bw.json +++ b/pandapower/networks/power_system_test_case_jsons/case33bw.json @@ -295,7 +295,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -317,7 +317,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -328,7 +328,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -358,7 +358,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -515,6 +514,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -911,7 +921,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -929,7 +939,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -947,7 +957,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -965,7 +975,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -983,7 +993,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1001,7 +1011,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1019,7 +1029,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1037,7 +1047,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1055,7 +1065,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1073,7 +1083,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1091,7 +1101,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1109,7 +1119,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1127,7 +1137,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1145,7 +1155,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1163,7 +1173,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1181,7 +1191,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1199,7 +1209,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1217,7 +1227,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1235,7 +1245,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1253,7 +1263,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1279,7 +1289,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1304,7 +1313,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case39.json b/pandapower/networks/power_system_test_case_jsons/case39.json index 4b4055957..abbc39f57 100644 --- a/pandapower/networks/power_system_test_case_jsons/case39.json +++ b/pandapower/networks/power_system_test_case_jsons/case39.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,2,3,4,5,6,7,8,9],\"data\":[[null,null,1,29,900.0,345.0,345.0,16.289999999999999,0.0,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,5,30,1800.0,345.0,345.0,45.0,0.0,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,28,37,1200.0,345.0,345.0,18.744599222175971,0.96,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,9,31,900.0,345.0,345.0,18.0,0.0,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,11,10,500.0,345.0,345.0,21.76470767090613,0.8,0.0,0.0,0.0,\"hv\",0,null,null,0.6,null,1,false,1,1.0,true,100.0],[null,null,11,12,500.0,345.0,345.0,21.76470767090613,0.8,0.0,0.0,0.0,\"hv\",0,null,null,0.6,null,1,false,1,1.0,true,100.0],[null,null,18,19,900.0,345.0,345.0,12.435967996099061,0.63,0.0,0.0,0.0,\"hv\",0,null,null,6.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,18,32,900.0,345.0,345.0,12.79551874681132,0.63,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,19,33,900.0,345.0,345.0,16.220237359545639,0.81,0.0,0.0,0.0,\"hv\",0,null,null,0.89999999999999,null,1,false,1,1.0,true,100.0],[null,null,21,34,900.0,345.0,345.0,12.869999999999999,0.0,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,24,36,900.0,345.0,345.0,20.88698159141239,0.54,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,2,3,4,5,6,7,8,9],\"data\":[[null,null,1,29,900.0,345.0,345.0,16.289999999999999,0.0,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,5,30,1800.0,345.0,345.0,45.0,0.0,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,28,37,1200.0,345.0,345.0,18.744599222175971,0.96,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,9,31,900.0,345.0,345.0,18.0,0.0,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,11,10,500.0,345.0,345.0,21.76470767090613,0.8,0.0,0.0,0.0,\"hv\",0,null,null,0.6,null,1,false,1,1.0,true,100.0],[null,null,11,12,500.0,345.0,345.0,21.76470767090613,0.8,0.0,0.0,0.0,\"hv\",0,null,null,0.6,null,1,false,1,1.0,true,100.0],[null,null,18,19,900.0,345.0,345.0,12.435967996099061,0.63,0.0,0.0,0.0,\"hv\",0,null,null,6.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,18,32,900.0,345.0,345.0,12.79551874681132,0.63,0.0,0.0,0.0,\"hv\",0,null,null,7.00000000000001,null,1,false,1,1.0,true,100.0],[null,null,19,33,900.0,345.0,345.0,16.220237359545639,0.81,0.0,0.0,0.0,\"hv\",0,null,null,0.89999999999999,null,1,false,1,1.0,true,100.0],[null,null,21,34,900.0,345.0,345.0,12.869999999999999,0.0,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0],[null,null,24,36,900.0,345.0,345.0,20.88698159141239,0.54,0.0,0.0,0.0,\"hv\",0,null,null,2.49999999999999,null,1,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,7 +362,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -519,6 +518,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -918,7 +928,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -936,7 +946,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -954,7 +964,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -972,7 +982,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -990,7 +1000,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1008,7 +1018,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1026,7 +1036,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1044,7 +1054,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1062,7 +1072,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1080,7 +1090,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1098,7 +1108,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1116,7 +1126,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1134,7 +1144,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1152,7 +1162,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1170,7 +1180,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1188,7 +1198,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1206,7 +1216,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1224,7 +1234,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1242,7 +1252,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1260,7 +1270,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1287,7 +1297,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1312,7 +1321,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case4gs.json b/pandapower/networks/power_system_test_case_jsons/case4gs.json index d47f2be89..001a9c68b 100644 --- a/pandapower/networks/power_system_test_case_jsons/case4gs.json +++ b/pandapower/networks/power_system_test_case_jsons/case4gs.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -331,7 +331,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -361,7 +361,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -518,6 +517,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -914,7 +924,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -932,7 +942,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -950,7 +960,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -968,7 +978,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -986,7 +996,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1004,7 +1014,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1022,7 +1032,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1040,7 +1050,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1058,7 +1068,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1076,7 +1086,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1094,7 +1104,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1112,7 +1122,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1130,7 +1140,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1148,7 +1158,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1166,7 +1176,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1184,7 +1194,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1202,7 +1212,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1220,7 +1230,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1238,7 +1248,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1256,7 +1266,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1282,7 +1292,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1307,7 +1316,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case5.json b/pandapower/networks/power_system_test_case_jsons/case5.json index 33bcbd205..65ec9fc5e 100644 --- a/pandapower/networks/power_system_test_case_jsons/case5.json +++ b/pandapower/networks/power_system_test_case_jsons/case5.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -336,7 +336,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -366,7 +366,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -523,6 +522,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -919,7 +929,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -937,7 +947,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -955,7 +965,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -973,7 +983,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -991,7 +1001,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1009,7 +1019,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1027,7 +1037,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1045,7 +1055,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1063,7 +1073,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1081,7 +1091,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1099,7 +1109,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1117,7 +1127,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1135,7 +1145,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1153,7 +1163,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1171,7 +1181,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1189,7 +1199,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1207,7 +1217,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1225,7 +1235,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1243,7 +1253,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1261,7 +1271,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1287,7 +1297,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1312,7 +1321,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case57.json b/pandapower/networks/power_system_test_case_jsons/case57.json index f76585f30..7cdbbbb4c 100644 --- a/pandapower/networks/power_system_test_case_jsons/case57.json +++ b/pandapower/networks/power_system_test_case_jsons/case57.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,11,12,13,14,15,16,2,3,4,5,6,7,8,9],\"data\":[[null,null,17,3,9900.0,500.0,115.0,5494.50000000000091,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.0,null,-1.0,false,1,1.0,true,100.0],[null,null,17,3,9900.0,500.0,115.0,4257.0,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,45,13,9900.0,138.0,115.0,727.649999999999977,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,10.0,null,-1.0,false,1,1.0,true,100.0],[null,null,50,9,9900.0,138.0,115.0,704.879999999999996,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.99999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,48,12,9900.0,138.0,115.0,1890.900000000000091,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,10.5,null,-1.0,false,1,1.0,true,100.0],[null,null,42,10,9900.0,230.0,115.0,1514.700000000000046,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.2,null,-1.0,false,1,1.0,true,100.0],[null,null,55,39,9900.0,230.0,138.0,11830.5,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.2,null,-1.0,false,1,1.0,true,100.0],[null,null,56,38,9900.0,230.0,138.0,13414.5,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.0,null,-1.0,false,1,1.0,true,100.0],[null,null,54,8,9900.0,161.0,115.0,1192.950000000000046,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.00000000000001,null,-1.0,false,1,1.0,true,100.0],[null,null,19,20,9900.0,500.0,138.0,7689.329999999999018,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.29999999999999,null,1.0,false,1,1.0,true,100.0],[null,null,24,23,9900.0,345.0,138.0,11701.799999999999272,0.0,0.0,0.0,0.0,\"hv\",null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,24,23,9900.0,345.0,138.0,12177.0,0.0,0.0,0.0,0.0,\"hv\",null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,25,23,9900.0,161.0,138.0,468.269999999999982,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.29999999999999,null,1.0,false,1,1.0,true,100.0],[null,null,28,6,9900.0,161.0,115.0,641.519999999999982,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.3,null,-1.0,false,1,1.0,true,100.0],[null,null,31,33,9900.0,345.0,138.0,9434.700000000000728,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.5,null,-1.0,false,1,1.0,true,100.0],[null,null,40,10,9900.0,230.0,115.0,7415.100000000000364,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.5,null,-1.0,false,1,1.0,true,100.0],[null,null,44,14,9900.0,138.0,115.0,1031.579999999999927,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.5,null,-1.0,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,10,11,12,13,14,15,16,2,3,4,5,6,7,8,9],\"data\":[[null,null,17,3,9900.0,500.0,115.0,5494.50000000000091,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.0,null,-1.0,false,1,1.0,true,100.0],[null,null,17,3,9900.0,500.0,115.0,4257.0,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,45,13,9900.0,138.0,115.0,727.649999999999977,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,10.0,null,-1.0,false,1,1.0,true,100.0],[null,null,50,9,9900.0,138.0,115.0,704.879999999999996,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.99999999999999,null,-1.0,false,1,1.0,true,100.0],[null,null,48,12,9900.0,138.0,115.0,1890.900000000000091,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,10.5,null,-1.0,false,1,1.0,true,100.0],[null,null,42,10,9900.0,230.0,115.0,1514.700000000000046,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.2,null,-1.0,false,1,1.0,true,100.0],[null,null,55,39,9900.0,230.0,138.0,11830.5,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.2,null,-1.0,false,1,1.0,true,100.0],[null,null,56,38,9900.0,230.0,138.0,13414.5,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.0,null,-1.0,false,1,1.0,true,100.0],[null,null,54,8,9900.0,161.0,115.0,1192.950000000000046,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.00000000000001,null,-1.0,false,1,1.0,true,100.0],[null,null,19,20,9900.0,500.0,138.0,7689.329999999999018,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.29999999999999,null,1.0,false,1,1.0,true,100.0],[null,null,24,23,9900.0,345.0,138.0,11701.799999999999272,0.0,0.0,0.0,0.0,\"hv\",null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,24,23,9900.0,345.0,138.0,12177.0,0.0,0.0,0.0,0.0,\"hv\",null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,25,23,9900.0,161.0,138.0,468.269999999999982,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.29999999999999,null,1.0,false,1,1.0,true,100.0],[null,null,28,6,9900.0,161.0,115.0,641.519999999999982,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.3,null,-1.0,false,1,1.0,true,100.0],[null,null,31,33,9900.0,345.0,138.0,9434.700000000000728,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.5,null,-1.0,false,1,1.0,true,100.0],[null,null,40,10,9900.0,230.0,115.0,7415.100000000000364,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.5,null,-1.0,false,1,1.0,true,100.0],[null,null,44,14,9900.0,138.0,115.0,1031.579999999999927,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,4.5,null,-1.0,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,7 +362,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -519,6 +518,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -918,7 +928,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -936,7 +946,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -954,7 +964,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -972,7 +982,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -990,7 +1000,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1008,7 +1018,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1026,7 +1036,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1044,7 +1054,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1062,7 +1072,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1080,7 +1090,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1098,7 +1108,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1116,7 +1126,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1134,7 +1144,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1152,7 +1162,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1170,7 +1180,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1188,7 +1198,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1206,7 +1216,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1224,7 +1234,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1242,7 +1252,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1260,7 +1270,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1287,7 +1297,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1312,7 +1321,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json b/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json index 91ae4acb0..d15720489 100644 --- a/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json +++ b/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json @@ -293,7 +293,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -315,7 +315,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -326,7 +326,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -356,7 +356,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -513,6 +512,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -792,7 +802,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "vk_percent": 4.0, "vkr_percent": 1.2 }, @@ -810,7 +819,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "vk_percent": 6.0, "vkr_percent": 1.44 }, @@ -828,7 +836,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "vk_percent": 4.0, "vkr_percent": 1.325 }, @@ -846,7 +853,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "vk_percent": 6.0, "vkr_percent": 1.425 }, @@ -864,7 +870,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "vk_percent": 4.0, "vkr_percent": 1.0794 }, @@ -882,7 +887,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "vk_percent": 6.0, "vkr_percent": 1.206 }, @@ -900,7 +904,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "vk_percent": 12.0, "vkr_percent": 0.26 }, @@ -918,7 +921,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "vk_percent": 12.2, "vkr_percent": 0.25 }, @@ -936,7 +938,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "vk_percent": 10.04, "vkr_percent": 0.276 }, @@ -954,7 +955,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "vk_percent": 11.2, "vkr_percent": 0.282 }, @@ -972,7 +972,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "vk_percent": 10.04, "vkr_percent": 0.295 }, @@ -990,7 +989,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "vk_percent": 11.2, "vkr_percent": 0.302 }, @@ -1008,7 +1006,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "vk_percent": 10.04, "vkr_percent": 0.31 }, @@ -1026,7 +1023,6 @@ "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "vk_percent": 11.2, "vkr_percent": 0.322 } @@ -1049,7 +1045,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1074,7 +1069,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case6470rte.json b/pandapower/networks/power_system_test_case_jsons/case6470rte.json index b2fc3a7c8..890907f16 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6470rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6470rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -524,6 +523,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -923,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1302,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1326,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case6495rte.json b/pandapower/networks/power_system_test_case_jsons/case6495rte.json index 05cfad5f4..51bb284df 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6495rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6495rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -524,6 +523,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -923,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1302,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1326,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case6515rte.json b/pandapower/networks/power_system_test_case_jsons/case6515rte.json index 1a4b6f45d..b56734e7c 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6515rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6515rte.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -524,6 +523,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -923,7 +933,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -941,7 +951,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -959,7 +969,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -977,7 +987,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -995,7 +1005,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1013,7 +1023,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1031,7 +1041,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1049,7 +1059,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1067,7 +1077,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1085,7 +1095,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1103,7 +1113,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1121,7 +1131,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1139,7 +1149,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1157,7 +1167,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1175,7 +1185,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1193,7 +1203,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1211,7 +1221,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1229,7 +1239,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1247,7 +1257,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1265,7 +1275,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1292,7 +1302,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1317,7 +1326,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case6ww.json b/pandapower/networks/power_system_test_case_jsons/case6ww.json index a6cf0be7f..ca355d32d 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6ww.json +++ b/pandapower/networks/power_system_test_case_jsons/case6ww.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -331,7 +331,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -361,7 +361,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -518,6 +517,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -914,7 +924,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -932,7 +942,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -950,7 +960,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -968,7 +978,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -986,7 +996,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1004,7 +1014,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1022,7 +1032,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1040,7 +1050,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1058,7 +1068,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1076,7 +1086,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1094,7 +1104,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1112,7 +1122,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1130,7 +1140,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1148,7 +1158,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1166,7 +1176,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1184,7 +1194,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1202,7 +1212,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1220,7 +1230,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1238,7 +1248,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1256,7 +1266,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1282,7 +1292,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1307,7 +1316,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case89pegase.json b/pandapower/networks/power_system_test_case_jsons/case89pegase.json index f8fc43d32..14941bbb1 100644 --- a/pandapower/networks/power_system_test_case_jsons/case89pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case89pegase.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,7 +363,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -520,6 +519,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -919,7 +929,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -937,7 +947,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -955,7 +965,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -973,7 +983,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -991,7 +1001,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1009,7 +1019,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1027,7 +1037,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1045,7 +1055,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1063,7 +1073,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1081,7 +1091,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1099,7 +1109,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1117,7 +1127,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1135,7 +1145,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1153,7 +1163,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1171,7 +1181,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1189,7 +1199,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1207,7 +1217,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1225,7 +1235,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1243,7 +1253,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1261,7 +1271,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1288,7 +1298,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1313,7 +1322,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case9.json b/pandapower/networks/power_system_test_case_jsons/case9.json index ecc5ddc3b..1a2e4ff14 100644 --- a/pandapower/networks/power_system_test_case_jsons/case9.json +++ b/pandapower/networks/power_system_test_case_jsons/case9.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -331,7 +331,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -361,7 +361,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -518,6 +517,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -914,7 +924,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -932,7 +942,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -950,7 +960,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -968,7 +978,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -986,7 +996,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1004,7 +1014,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1022,7 +1032,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1040,7 +1050,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1058,7 +1068,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1076,7 +1086,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1094,7 +1104,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1112,7 +1122,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1130,7 +1140,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1148,7 +1158,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1166,7 +1176,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1184,7 +1194,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1202,7 +1212,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1220,7 +1230,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1238,7 +1248,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1256,7 +1266,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1282,7 +1292,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1307,7 +1316,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case9241pegase.json b/pandapower/networks/power_system_test_case_jsons/case9241pegase.json index 40765885f..5697621c9 100644 --- a/pandapower/networks/power_system_test_case_jsons/case9241pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case9241pegase.json @@ -299,7 +299,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -321,7 +321,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -333,7 +333,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -363,7 +363,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -520,6 +519,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -919,7 +929,7 @@ "vkr_percent": 1.425, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -937,7 +947,7 @@ "vkr_percent": 0.322, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -955,7 +965,7 @@ "vkr_percent": 0.31, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -973,7 +983,7 @@ "vkr_percent": 0.282, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -991,7 +1001,7 @@ "vkr_percent": 0.302, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 11.2 }, @@ -1009,7 +1019,7 @@ "vkr_percent": 1.44, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1027,7 +1037,7 @@ "vkr_percent": 0.276, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1045,7 +1055,7 @@ "vkr_percent": 1.2, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1063,7 +1073,7 @@ "vkr_percent": 0.25, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.2 }, @@ -1081,7 +1091,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1099,7 +1109,7 @@ "vkr_percent": 1.206, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 6.0 }, @@ -1117,7 +1127,7 @@ "vkr_percent": 1.325, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1135,7 +1145,7 @@ "vkr_percent": 1.0794, "tap_step_percent": 2.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "vk_percent": 4.0 }, @@ -1153,7 +1163,7 @@ "vkr_percent": 0.32, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 18.0 }, @@ -1171,7 +1181,7 @@ "vkr_percent": 0.26, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1189,7 +1199,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1207,7 +1217,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 }, @@ -1225,7 +1235,7 @@ "vkr_percent": 0.295, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 10.04 }, @@ -1243,7 +1253,7 @@ "vkr_percent": 0.41, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 12.0 }, @@ -1261,7 +1271,7 @@ "vkr_percent": 0.34, "tap_step_percent": 1.5, "tap_side": "hv", - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 9, "vk_percent": 16.2 } @@ -1288,7 +1298,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1313,7 +1322,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/networks/power_system_test_case_jsons/case_ieee30.json b/pandapower/networks/power_system_test_case_jsons/case_ieee30.json index 856bc3504..bea49d968 100644 --- a/pandapower/networks/power_system_test_case_jsons/case_ieee30.json +++ b/pandapower/networks/power_system_test_case_jsons/case_ieee30.json @@ -298,7 +298,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4,5,6],\"data\":[[null,null,5,8,99.998999999999995,132.0,1.0,20.799792,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,5,9,99.998999999999995,132.0,33.0,55.599444000000012,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.1,null,-1.0,false,1,1.0,true,100.0],[null,null,10,8,99.998999999999995,11.0,1.0,20.799792,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,9,8,99.998999999999995,33.0,1.0,10.999890000000001,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,3,11,99.998999999999995,132.0,33.0,25.599744000000001,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.8,null,-1.0,false,1,1.0,true,100.0],[null,null,11,12,99.998999999999995,33.0,11.0,13.99986,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,27,26,99.998999999999995,132.0,33.0,39.599603999999999,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.2,null,-1.0,false,1,1.0,true,100.0]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4,5,6],\"data\":[[null,null,5,8,99.998999999999995,132.0,1.0,20.799792,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.2,null,-1.0,false,1,1.0,true,100.0],[null,null,5,9,99.998999999999995,132.0,33.0,55.599444000000012,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.1,null,-1.0,false,1,1.0,true,100.0],[null,null,10,8,99.998999999999995,11.0,1.0,20.799792,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,9,8,99.998999999999995,33.0,1.0,10.999890000000001,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,3,11,99.998999999999995,132.0,33.0,25.599744000000001,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.8,null,-1.0,false,1,1.0,true,100.0],[null,null,11,12,99.998999999999995,33.0,11.0,13.99986,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,27,26,99.998999999999995,132.0,33.0,39.599603999999999,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.2,null,-1.0,false,1,1.0,true,100.0]]}", "orient": "split", "dtype": { "name": "object", @@ -320,7 +320,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -332,7 +332,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -362,7 +362,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -519,6 +518,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -915,7 +925,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -933,7 +943,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -951,7 +961,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -969,7 +979,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -987,7 +997,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1005,7 +1015,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1023,7 +1033,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1041,7 +1051,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1059,7 +1069,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1077,7 +1087,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1095,7 +1105,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1113,7 +1123,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1131,7 +1141,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1149,7 +1159,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1167,7 +1177,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1185,7 +1195,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1203,7 +1213,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1221,7 +1231,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1239,7 +1249,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1257,7 +1267,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1283,7 +1293,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1308,7 +1317,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/case_illinois200.json b/pandapower/networks/power_system_test_case_jsons/case_illinois200.json index b81d388b2..7dc673b32 100644 --- a/pandapower/networks/power_system_test_case_jsons/case_illinois200.json +++ b/pandapower/networks/power_system_test_case_jsons/case_illinois200.json @@ -303,7 +303,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -325,7 +325,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -337,7 +337,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -367,7 +367,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -524,6 +523,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -920,7 +930,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -938,7 +948,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -956,7 +966,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -974,7 +984,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -992,7 +1002,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1010,7 +1020,7 @@ "tap_max": 2, "tap_neutral": 0, "tap_min": -2, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 2.5, @@ -1028,7 +1038,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1046,7 +1056,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1064,7 +1074,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1082,7 +1092,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1100,7 +1110,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1118,7 +1128,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1136,7 +1146,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1154,7 +1164,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1172,7 +1182,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1190,7 +1200,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1208,7 +1218,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1226,7 +1236,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1244,7 +1254,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1262,7 +1272,7 @@ "tap_max": 9, "tap_neutral": 0, "tap_min": -9, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_side": "hv", "tap_step_degree": 0, "tap_step_percent": 1.5, @@ -1288,7 +1298,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, @@ -1313,7 +1322,6 @@ "tap_min": -10, "tap_side": "hv", "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "vk_hv_percent": 10.4, "vk_lv_percent": 10.4, "vk_mv_percent": 10.4, diff --git a/pandapower/networks/power_system_test_case_jsons/iceland.json b/pandapower/networks/power_system_test_case_jsons/iceland.json index c2bfebe33..7a51b132c 100644 --- a/pandapower/networks/power_system_test_case_jsons/iceland.json +++ b/pandapower/networks/power_system_test_case_jsons/iceland.json @@ -296,7 +296,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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"orient": "split", "dtype": { "name": "object", @@ -318,7 +318,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -329,7 +329,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -359,7 +359,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -516,6 +515,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -794,7 +804,6 @@ "tap_min": -2, "vkr_percent": 1.425, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -812,7 +821,6 @@ "tap_min": -2, "vkr_percent": 1.44, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -830,7 +838,6 @@ "tap_min": -2, "vkr_percent": 1.2, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -848,7 +855,6 @@ "tap_min": -9, "vkr_percent": 0.25, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 12.2, "tap_max": 9 @@ -866,7 +872,6 @@ "tap_min": -9, "vkr_percent": 0.31, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -884,7 +889,6 @@ "tap_min": -2, "vkr_percent": 1.206, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 6.0, "tap_max": 2 @@ -902,7 +906,6 @@ "tap_min": -2, "vkr_percent": 1.325, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -920,7 +923,6 @@ "tap_min": -2, "vkr_percent": 1.0794, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 4.0, "tap_max": 2 @@ -938,7 +940,6 @@ "tap_min": -9, "vkr_percent": 0.322, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -956,7 +957,6 @@ "tap_min": -9, "vkr_percent": 0.26, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 12.0, "tap_max": 9 @@ -973,7 +973,6 @@ "tap_neutral": 0, "tap_min": -9, "vkr_percent": 0.276, - "tap_changer_type": "Ratio", "tap_step_percent": 1.5, "tap_side": "hv", "vk_percent": 10.04, @@ -992,7 +991,6 @@ "tap_min": -9, "vkr_percent": 0.302, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1010,7 +1008,6 @@ "tap_min": -9, "vkr_percent": 0.282, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 11.2, "tap_max": 9 @@ -1028,7 +1025,6 @@ "tap_min": -9, "vkr_percent": 0.295, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_percent": 10.04, "tap_max": 9 @@ -1056,7 +1052,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 }, @@ -1081,7 +1076,6 @@ "tap_max": 10, "vkr_mv_percent": 0.32, "tap_step_percent": 1.2, - "tap_changer_type": "Ratio", "tap_side": "hv", "vk_hv_percent": 10.4 } diff --git a/pandapower/test/grid_equivalents/test_grid_equivalents_toolbox.py b/pandapower/test/grid_equivalents/test_grid_equivalents_toolbox.py index 005f68439..d6fab8b42 100644 --- a/pandapower/test/grid_equivalents/test_grid_equivalents_toolbox.py +++ b/pandapower/test/grid_equivalents/test_grid_equivalents_toolbox.py @@ -65,6 +65,7 @@ def boundary_testnet(which): expected_bb["b"]["internal"] = expected_bb["a"]["external"] - {18} expected_bb["b"]["external"] = expected_bb["a"]["internal"] | {18} + net = pp.convert_format(net) pp.runpp(net) return net, expected_bb, expected_bbr From 97d1836ddd1f2ba16abfcab88b4de4d1455ea4b7 Mon Sep 17 00:00:00 2001 From: tfabian Date: Fri, 20 Dec 2024 09:52:25 +0100 Subject: [PATCH 084/125] updated docu for phase shifter --- doc/elements/trafo.rst | 19 +++++++++++++------ 1 file changed, 13 insertions(+), 6 deletions(-) diff --git a/doc/elements/trafo.rst b/doc/elements/trafo.rst index 269ed9e9b..d72e81a31 100644 --- a/doc/elements/trafo.rst +++ b/doc/elements/trafo.rst @@ -166,9 +166,9 @@ Where the reference voltage :math:`V_{N}` is the nominal voltage at the low volt Tap Changer --------------- -**Longitudinal regulator** +**Longitudinal regulator (Ratio Tap Changer)** -A longitudinal regulator can be modeled by setting tap_phase_shifter to False and defining the tap changer voltage step with tap_step_percent. +A longitudinal regulator can be modeled by setting tap_changer_type to "Ratio" and defining the tap changer voltage step with tap_step_percent. The reference voltage is then multiplied with the tap factor: @@ -190,15 +190,22 @@ On which side the reference voltage is adapted depends on the :math:`tap\_side` .. note:: The variables tap_min and tap_max are not considered in the power flow. The user is responsible to ensure that tap_min < tap_pos < tap_max! -**Cross regulator** +**Cross regulator (Ratio Tap Changer / Symmetrical Tap Changer)** In addition to tap_step_percent a value for tap_step_degree can be defined to model an angle shift for each tap, resulting in a cross -regulator that affects the magnitude as well as the angle of the transformer ratio. +regulator that affects the magnitude as well as the angle of the transformer ratio. Use tap_changer_type "Ratio", +or if the angle shift is :math:'\pm 90' degrees, you can use tap_changer_type "Symmetrical" (and tap_step_percent cen be left empty). +.. math:: + :nowrap: + + \begin{align*} + n_{tap} = 1 + (tap\_pos - tap\_neutral) \cdot \frac{tap\_st\_percent}{100} \exp(\mathrm j \phi) + \end{align*} **Ideal phase shifter** -If tap_phase_shifter is set to True, the tap changer is modeled as an ideal phase shifter, meaning that a constant +If tap_changer_type is set to "Ideal", the tap changer is modeled as an ideal phase shifter, meaning that a constant angle shift is added with each tap step: .. math:: @@ -209,7 +216,7 @@ angle shift is added with each tap step: \theta &= shift\_degree \end{align*} -The angle shift can be directly defined in tap_step_degree, in which case: +The angle shift can be directly defined in tap_step_degree (the same parameter as for "Ratio" tap changer is used!), in which case: .. math:: :nowrap: From 6f97e61798b9a2d831167d4a895469cda64ce9c4 Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Fri, 20 Dec 2024 09:55:13 +0100 Subject: [PATCH 085/125] Completed pf_converter for adjusted trafo tap changer working --- .../powerfactory/pp_import_functions.py | 151 ++++++++++++------ 1 file changed, 106 insertions(+), 45 deletions(-) diff --git a/pandapower/converter/powerfactory/pp_import_functions.py b/pandapower/converter/powerfactory/pp_import_functions.py index 9278df1b4..cdade4153 100644 --- a/pandapower/converter/powerfactory/pp_import_functions.py +++ b/pandapower/converter/powerfactory/pp_import_functions.py @@ -2293,18 +2293,25 @@ def create_trafo_type(net, item): "tap_side": ['hv', 'lv', 'ext'][item.tap_side], # 'ext' not implemented } - type_data.update({"tap_phase_shifter_type": pd.NA}) - type_data.update({"tap2_phase_shifter_type": pd.NA}) + type_data.update({"tap_changer_type": None}) + type_data.update({"tap2_changer_type": None}) if item.itapch: logger.debug('trafo <%s> has tap changer' % name) + if item.tapchtype == 0: + tap_changer_type = "Ratio" + elif item.tapchtype == 1: + tap_changer_type = "Symmetrical" + elif item.tapchtype == 2: + tap_changer_type = "Ideal" + type_data.update({ # see if it is an ideal phase shifter or a complex phase shifter # checking tap_step_percent because a nonzero value for ideal phase shifter can be stored in the object "tap_step_percent": item.dutap if item.tapchtype != 1 else 0, "tap_step_degree": item.dphitap if item.tapchtype == 1 else item.phitr, - "tap_phase_shifter_type": item.tapchtype, + "tap_changer_type": tap_changer_type, "tap_max": item.ntpmx, "tap_min": item.ntpmn, "tap_neutral": item.nntap0 @@ -2323,7 +2330,7 @@ def create_trafo_type(net, item): # checking tap_step_percent because a nonzero value for ideal phase shifter can be stored in the object "tap2_step_percent": item.dutap2 if item.tapchtype2 != 1 else 0, "tap2_step_degree": item.dphitap2 if item.tapchtype2 == 1 else item.phitr2, - "tap2_phase_shifter_type": item.tapchtype2, + "tap2_changer_type": item.tapchtype2, "tap2_max": item.ntpmx2, "tap2_min": item.ntpmn2, "tap2_neutral": item.nntap02 @@ -2400,7 +2407,8 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc new_id_characteristic_table = last_index + 1 tap_min = pf_type.ntpmn tap_max = pf_type.ntpmx - meas_side = 1 if item.GetAttribute("iMeasLoc") == 1 else 2 + tap_side = pf_type.tap_side + meas_side = item.GetAttribute("iMeasLoc") # 0: meas-side == tap_side steps = list(range(tap_min, tap_max + 1)) @@ -2408,8 +2416,19 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc columns=['voltage_ratio', 'angle_deg', 'vk_percent', 'vkr_percent', 'ignore']) new_tap_table = new_tap_table.drop(columns='ignore') - new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn_h if meas_side == 1 \ - else new_tap_table["voltage_ratio"] / pf_type.utrn_l + if meas_side == 0: + if tap_side == 0: + new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn_h + else: + new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn_l + elif meas_side == 1: + if tap_side == 0: + new_tap_table["voltage_ratio"] = pf_type.utrn_l / new_tap_table["voltage_ratio"] + else: + new_tap_table["voltage_ratio"] = pf_type.utrn_h / new_tap_table["voltage_ratio"] + else: + raise ValueError("Measurement location for tap table not given.") + new_tap_table["vkr_percent"] = new_tap_table["vkr_percent"] / item.GetAttribute("Snom_a") # pf_type.strn if len(new_tap_table) == len(steps): @@ -2425,20 +2444,28 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc net["trafo_characteristic_table"] = pd.concat([net["trafo_characteristic_table"], new_tap_table], ignore_index=True) + if pf_type.tapchtype == 0: + tap_changer_type = "Ratio" + elif pf_type.tapchtype == 1: + tap_changer_type = "Symmetrical" + elif pf_type.tapchtype == 2: + tap_changer_type = "Ideal" + else: + tap_changer_type = None + tap_dependency_table = True - tap_phase_shifter_type = pf_type.tapchtype if pf_type.itapch else -1 id_characteristic_table = new_id_characteristic_table else: - id_characteristic_table = np.nan + id_characteristic_table = None tap_dependency_table = False - tap_phase_shifter_type = np.nan + tap_changer_type = None - # tap_phase_shifter_type = tap_phase_shifter_type + # tap_changer_type = tap_changer_type tid = pp.create_transformer(net, hv_bus=bus1, lv_bus=bus2, name=name, std_type=std_type, tap_pos=tap_pos, tap_dependency_table=tap_dependency_table, - tap_phase_shifter_type=tap_phase_shifter_type, + tap_changer_type=tap_changer_type, id_characteristic_table=id_characteristic_table, in_service=in_service, parallel=item.ntnum, df=item.ratfac, tap2_pos=tap_pos2, leakage_resistance_ratio_hv=pf_type.itrdr, leakage_reactance_ratio_hv=pf_type.itrdl) @@ -2470,15 +2497,20 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc new_tap_table = new_tap_table.drop(columns='ignore') if meas_side == 0: - new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn_h if tap_side == 0 else new_tap_table["voltage_ratio"] / pf_type.utrn_l + if tap_side == 0: + new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn_h + else: + new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn_l elif meas_side == 1: - new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn_l if tap_side == 0 else new_tap_table["voltage_ratio"] / pf_type.utrn_h - - #0 heißt an derselben Seite + new_tap_table["angle_deg"] = -new_tap_table["angle_deg"] + if tap_side == 0: + new_tap_table["voltage_ratio"] = pf_type.utrn_l / new_tap_table["voltage_ratio"] + else: + new_tap_table["voltage_ratio"] = pf_type.utrn_h / new_tap_table["voltage_ratio"] + else: + raise ValueError("Measurement location for tap table not given.") new_tap_table["vkr_percent"] = new_tap_table["vkr_percent"] / item.GetAttribute("Snom_a") # pf_type.strn - # Sn_MVA = pf_type.strn - # new_tap_table["vkr_percent"] = (new_tap_table["vk_percent"] ** 2) / (new_tap_table["vkr_percent"] * Sn_MVA) if len(new_tap_table) == len(steps): new_tap_table['step'] = steps[:len(new_tap_table)] @@ -2492,13 +2524,22 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc net["trafo_characteristic_table"] = pd.concat([net["trafo_characteristic_table"], new_tap_table], ignore_index=True) + + if pf_type.tapchtype == 0: + tap_changer_type = "Ratio" + elif pf_type.tapchtype == 1: + tap_changer_type = "Symmetrical" + elif pf_type.tapchtype == 2: + tap_changer_type = "Ideal" + else: + tap_changer_type = None + tap_dependency_table = True - tap_phase_shifter_type = pf_type.tapchtype if pf_type.itapch else -1 id_characteristic_table = new_id_characteristic_table else: - id_characteristic_table = np.nan + id_characteristic_table = None tap_dependency_table = False - tap_phase_shifter_type = np.nan + tap_changer_type = None tid = pp.create_transformer_from_parameters( net, @@ -2507,7 +2548,7 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc name=name, tap_pos=tap_pos, tap_side=tap_side, - tap_phase_shifter_type=tap_phase_shifter_type, + tap_changer_type=tap_changer_type, id_characteristic_table=id_characteristic_table, tap_dependency_table=tap_dependency_table, in_service=in_service, @@ -2692,42 +2733,62 @@ def create_trafo3w(net, item, tap_opt='nntap'): new_id_characteristic_table = last_index + 1 new_tap_table = pd.DataFrame(item.GetAttribute("mTaps"), - columns=['voltage_ratio', 'angle_deg', 'vk_hv_percent', 'vkr_hv_percent', - 'vk_mv_percent', 'vkr_mv_percent', - 'vk_lv_percent', 'vkr_lv_percent']) + columns=['voltage_ratio', 'angle_deg', 'vk_hv_percent', 'vk_mv_percent', + 'vk_lv_percent', 'vkr_hv_percent', 'vkr_mv_percent', 'vkr_lv_percent']) if pf_type.itapzdep: table_side = pf_type.itapzside else: table_side = item.GetAttribute("iMeasTap") + meas_side = item.GetAttribute("iMeasLoc") if table_side == 0: tap_min = pf_type.n3tmn_h tap_max = pf_type.n3tmx_h + if meas_side == 0: + new_tap_table["voltage_ratio"] = pf_type.utrn3_h / new_tap_table["voltage_ratio"] + elif meas_side == 1: + new_tap_table["voltage_ratio"] = pf_type.utrn3_m / new_tap_table["voltage_ratio"] + elif meas_side == 2: + new_tap_table["voltage_ratio"] = pf_type.utrn3_l / new_tap_table["voltage_ratio"] elif table_side == 1: tap_min = pf_type.n3tmn_m tap_max = pf_type.n3tmx_m + new_tap_table["angle_deg"] = -new_tap_table["angle_deg"] + if meas_side == 0: + new_tap_table["voltage_ratio"] = pf_type.utrn3_h / new_tap_table["voltage_ratio"] + elif meas_side == 1: + new_tap_table["voltage_ratio"] = pf_type.utrn3_m / new_tap_table["voltage_ratio"] + elif meas_side == 2: + new_tap_table["voltage_ratio"] = pf_type.utrn3_l / new_tap_table["voltage_ratio"] elif table_side == 2: tap_min = pf_type.n3tmn_l tap_max = pf_type.n3tmx_l + new_tap_table["angle_deg"] = -new_tap_table["angle_deg"] + if meas_side == 0: + new_tap_table["voltage_ratio"] = pf_type.utrn3_h / new_tap_table["voltage_ratio"] + elif meas_side == 1: + new_tap_table["voltage_ratio"] = pf_type.utrn3_m / new_tap_table["voltage_ratio"] + elif meas_side == 2: + new_tap_table["voltage_ratio"] = pf_type.utrn3_l / new_tap_table["voltage_ratio"] + + snom_h_a = item.GetAttribute("Snom_h_a") + snom_m_a = item.GetAttribute("Snom_m_a") + snom_l_a = item.GetAttribute("Snom_l_a") + new_tap_table["vkr_hv_percent"] = new_tap_table["vkr_hv_percent"] / ( + np.min([float(snom_h_a), float(snom_m_a)]) * 1000) * 100 + new_tap_table["vkr_mv_percent"] = new_tap_table["vkr_mv_percent"] / ( + np.min([float(snom_m_a), float(snom_l_a)]) * 1000) * 100 + new_tap_table["vkr_lv_percent"] = new_tap_table["vkr_lv_percent"] / ( + np.min([float(snom_h_a), float(snom_m_a)]) * 1000) * 100 steps = list(range(tap_min, tap_max + 1)) - meas_side = item.GetAttribute("iMeasLoc") - - if meas_side == 0: - new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn3_h - elif meas_side == 1: - new_tap_table["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn3_m - elif meas_side == 2: - meas_side["voltage_ratio"] = new_tap_table["voltage_ratio"] / pf_type.utrn3_l - - new_tap_table["vkr_hv_percent"] = new_tap_table["vkr_hv_percent"] / item.GetAttribute( - "Snom_h_a") # pf_type.strn3h - new_tap_table["vkr_mv_percent"] = new_tap_table["vkr_mv_percent"] / item.GetAttribute( - "Snom_m_a") # pf_type.strn3m - new_tap_table["vkr_lv_percent"] = new_tap_table["vkr_lv_percent"] / item.GetAttribute( - "Snom_l_a") # pf_type.strn3l + #new_tap_table["vkr_hv_percent"] = new_tap_table["vkr_hv_percent"] / item.GetAttribute( + # "Snom_h_a") # pf_type.strn3h + # # pf_type.strn3m + #new_tap_table["vkr_lv_percent"] = new_tap_table["vkr_lv_percent"] / item.GetAttribute( + # "Snom_l_a") # pf_type.strn3l if len(new_tap_table) == len(steps): new_tap_table['step'] = steps[:len(new_tap_table)] @@ -2770,20 +2831,20 @@ def create_trafo3w(net, item, tap_opt='nntap'): tap_step_degree = item.GetAttribute('t:ph3tr_' + ts) if (tap_step_degree is None or tap_step_degree == 0) and (tap_step_percent is None or tap_step_percent == 0): - tap_phase_shifter_type = pd.NA # net[trafotable].loc[mask_na, f"tap{t}_phase_shifter_type"] = pd.NA + tap_changer_type = None # ratio/asymmetrical phase shifters elif (tap_step_degree != 90 and tap_step_percent is not None and tap_step_percent != 0): - tap_phase_shifter_type = 0 # net[trafotable].loc[mask_ratio_asym, f"tap{t}_phase_shifter_type"] = 0 + tap_changer_type = "Ratio" # symmetrical phase shifters elif (tap_step_degree == 90 and tap_step_percent is not None and tap_step_percent != 0): - tap_phase_shifter_type = 1 # net[trafotable].loc[mask_sym, f"tap{t}_phase_shifter_type"] = 1 + tap_changer_type = "Symmetrical" # ideal phase shifters elif (tap_step_degree is not None and tap_step_degree != 0 and (tap_step_percent is None or tap_step_percent == 0)): - tap_phase_shifter_type = 2 # net[trafotable].loc[mask_ideal, f"tap{t}_phase_shifter_type"] = 2 + tap_changer_type = "Ideal" params.update({ 'tap_side': ts + 'v', # hv, mv, lv - 'tap_phase_shifter_type': tap_phase_shifter_type, + 'tap_changer_type': tap_changer_type, 'tap_step_percent': item.GetAttribute('t:du3tp_' + ts), 'tap_step_degree': item.GetAttribute('t:ph3tr_' + ts), 'tap_min': item.GetAttribute('t:n3tmn_' + ts), From 85bf778ecb96398b4869b84424e00e9113d20377 Mon Sep 17 00:00:00 2001 From: tfabian Date: Fri, 20 Dec 2024 10:03:45 +0100 Subject: [PATCH 086/125] revert json in converter --- .../converter/testfiles/test_line_3ph.json | 41 ++++++----- .../test_net_3ph_test_2020_10_19.json | 43 ++++++------ .../converter/testfiles/test_trafo_3ph.json | 43 ++++++------ .../converter/testfiles/trafo_tap_model.json | 68 +++++++++++-------- 4 files changed, 98 insertions(+), 97 deletions(-) diff --git a/pandapower/test/converter/testfiles/test_line_3ph.json b/pandapower/test/converter/testfiles/test_line_3ph.json index fe432e1a6..ee01cd8c2 100644 --- a/pandapower/test/converter/testfiles/test_line_3ph.json +++ b/pandapower/test/converter/testfiles/test_line_3ph.json @@ -247,7 +247,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -269,7 +269,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool" @@ -278,7 +278,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -308,7 +308,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -960,7 +959,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -978,7 +977,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -996,7 +995,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1014,7 +1013,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1032,7 +1031,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1050,7 +1049,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1068,7 +1067,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1086,7 +1085,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1104,7 +1103,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1122,7 +1121,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1140,7 +1139,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1158,7 +1157,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1176,7 +1175,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1194,7 +1193,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false } }, "trafo3w": { @@ -1220,8 +1219,7 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2, - "tap_changer_type": "Ratio" + "tap_step_percent": 1.2 }, "63/25/38 MVA 110/10/10 kV": { "sn_hv_mva": 63, @@ -1245,8 +1243,7 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2, - "tap_changer_type": "Ratio" + "tap_step_percent": 1.2 } } }, diff --git a/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json b/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json index 510ed3bc6..3b76cde0e 100644 --- a/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json +++ b/pandapower/test/converter/testfiles/test_net_3ph_test_2020_10_19.json @@ -247,7 +247,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",null,0,1,0.629999995231628,20.0,0.400000005960464,6.0,1.095238089561462,1.649999976158142,0.261914998292923,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,1.095237970352173,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",null,0,1,0.629999995231628,20.0,0.400000005960464,6.0,1.095238089561462,1.649999976158142,0.261914998292923,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,1.095237970352173,100.0,0.0,0.899999976158142,\"Dyn\",1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -269,7 +269,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -287,7 +287,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -317,7 +317,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -969,7 +968,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -987,7 +986,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1005,7 +1004,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1023,7 +1022,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1041,7 +1040,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1059,7 +1058,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1077,7 +1076,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1095,7 +1094,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1113,7 +1112,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1131,7 +1130,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV Dyn ASEA": { "sn_mva": 0.6299999952316284, @@ -1151,7 +1150,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1172,7 +1171,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1190,7 +1189,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1208,7 +1207,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1226,7 +1225,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false } }, "trafo3w": { @@ -1252,8 +1251,7 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2, - "tap_changer_type": "Ratio" + "tap_step_percent": 1.2 }, "63/25/38 MVA 110/20/10 kV": { "sn_hv_mva": 63, @@ -1277,8 +1275,7 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2, - "tap_changer_type": "Ratio" + "tap_step_percent": 1.2 } } }, diff --git a/pandapower/test/converter/testfiles/test_trafo_3ph.json b/pandapower/test/converter/testfiles/test_trafo_3ph.json index d7e6a45d1..64c5eefe2 100644 --- a/pandapower/test/converter/testfiles/test_trafo_3ph.json +++ b/pandapower/test/converter/testfiles/test_trafo_3ph.json @@ -239,7 +239,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",null,0,1,0.629999995231628,20.0,0.400000005960464,6.0,1.095238089561462,1.649999976158142,0.261914998292923,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,1.095237970352173,100.0,0.0,0.899999976158142,\"Yzn\",1.0,\"\",\"\"]]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"vector_group\",\"tap_set_vm_pu\",\"description\",\"equipment\"],\"index\":[0],\"data\":[[\"2-Winding Transformer\",null,0,1,0.629999995231628,20.0,0.400000005960464,6.0,1.095238089561462,1.649999976158142,0.261914998292923,0.0,null,null,null,null,null,null,0,false,1,1.0,true,6.0,1.095237970352173,100.0,0.0,0.899999976158142,\"Yzn\",1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -261,7 +261,7 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "int32", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", @@ -279,7 +279,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -309,7 +309,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -948,7 +947,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -966,7 +965,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -984,7 +983,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV Yzn ASEA": { "sn_mva": 0.6299999952316284, @@ -1004,7 +1003,7 @@ "tap_side": "hv", "tap_step_percent": 2.5, "tap_step_degree": 0.0, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 2, "tap_min": -2, "tap_neutral": 0 @@ -1025,7 +1024,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1043,7 +1042,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1061,7 +1060,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1079,7 +1078,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1097,7 +1096,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.63 MVA 10/0.4 kV": { "sn_mva": 0.63, @@ -1115,7 +1114,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/10 kV": { "sn_mva": 63, @@ -1133,7 +1132,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1151,7 +1150,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/20 kV": { "i0_percent": 0.07, @@ -1169,7 +1168,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1187,7 +1186,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "63 MVA 110/20 kV": { "i0_percent": 0.04, @@ -1205,7 +1204,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false } }, "trafo3w": { @@ -1231,8 +1230,7 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2, - "tap_changer_type": "Ratio" + "tap_step_percent": 1.2 }, "63/25/38 MVA 110/20/10 kV": { "sn_hv_mva": 63, @@ -1256,8 +1254,7 @@ "tap_neutral": 0, "tap_min": -10, "tap_max": 10, - "tap_step_percent": 1.2, - "tap_changer_type": "Ratio" + "tap_step_percent": 1.2 } } }, diff --git a/pandapower/test/converter/testfiles/trafo_tap_model.json b/pandapower/test/converter/testfiles/trafo_tap_model.json index 296444c0f..428711c08 100644 --- a/pandapower/test/converter/testfiles/trafo_tap_model.json +++ b/pandapower/test/converter/testfiles/trafo_tap_model.json @@ -305,7 +305,7 @@ "trafo": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": 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LV-d\",367,341,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,0.0,5.0,5.0,true,1,1.0,true,true,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",0.0,-10.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer(12)\",\"2-W HV-d LV-d\",354,315,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,0.0,5.0,0.0,true,1,1.0,true,true,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",0.0,-10.0,-5.0,1.0,\"\",\"\"],[\"2-Winding Transformer(15)\",\"2-W HV-d LV-d\",380,406,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,0.0,5.0,3.0,true,1,1.0,true,true,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"lv\",0.0,-10.0,-2.0,1.0,\"\",\"\"],[\"2-Winding Transformer(19)\",\"2-W HV-V HV-V\",471,484,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,0.0,0.0,false,1,1.0,true,false,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"hv\",2.0,90.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer(16)\",\"2-W HV-V HV-V\",419,447,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,0.0,5.0,false,1,1.0,true,false,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"hv\",2.0,90.0,0.0,1.0,\"\",\"\"],[\"2-Winding Transformer(18)\",\"2-W HV-V HV-V\",510,458,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,0.0,0.0,false,1,1.0,true,false,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"hv\",2.0,90.0,-5.0,1.0,\"\",\"\"],[\"2-Winding Transformer(17)\",\"2-W HV-V HV-V\",497,432,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,\"hv\",0.0,-10.0,10.0,2.0,0.0,3.0,false,1,1.0,true,false,3.0,0.0,100.0,0.0,0.899999976158142,0.0,10.0,-10.0,\"hv\",2.0,90.0,-2.0,1.0,\"\",\"\"],[\"2-Winding Transformer(20)\",\"2-W no tap changer\",562,549,100.0,110.0,20.0,12.0,0.5,14.0,0.5,0.0,null,null,null,null,null,null,null,false,1,1.0,true,false,3.0,0.0,100.0,0.0,0.899999976158142,null,null,null,null,null,null,null,1.0,\"\",\"\"]]}", "orient": "split", "dtype": { "name": "object", @@ -327,11 +327,11 @@ "tap_step_percent": "float64", "tap_step_degree": "float64", "tap_pos": "float64", - "tap_changer_type": "object", + "tap_phase_shifter": "bool", "parallel": "uint32", "df": "float64", "in_service": "bool", - "tap2_phase_shifter_type": "uint32", + "tap2_phase_shifter": "bool", "vk0_percent": "float64", "vkr0_percent": "float64", "mag0_percent": "float64", @@ -354,7 +354,7 @@ "trafo3w": { "_module": "pandas.core.frame", "_class": "DataFrame", - "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_changer_type\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", "orient": "split", "dtype": { "name": "object", @@ -384,7 +384,6 @@ "tap_max": "int32", "tap_step_percent": "float64", "tap_step_degree": "float64", - "tap_changer_type": "object", "tap_pos": "int32", "tap_at_star_point": "bool", "in_service": "bool" @@ -541,6 +540,17 @@ "is_multiindex": false, "is_multicolumn": false }, + "characteristic": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object" + }, + "is_multiindex": false, + "is_multicolumn": false + }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", @@ -1081,7 +1091,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/10 kV": { "sn_mva": 40, @@ -1099,7 +1109,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "2-W HV-V LV-d": { "sn_mva": 100.0, @@ -1119,14 +1129,14 @@ "tap_side": "hv", "tap_step_percent": 2.0, "tap_step_degree": 10.0, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 10, "tap_min": -10, "tap_neutral": 0, "tap2_side": "lv", "tap2_step_percent": 0, "tap2_step_degree": 5.0, - "tap2_phase_shifter_type": 2, + "tap2_phase_shifter": true, "tap2_max": 10, "tap2_min": -10, "tap2_neutral": 0 @@ -1165,14 +1175,14 @@ "tap_side": "hv", "tap_step_percent": 0, "tap_step_degree": 5.0, - "tap_changer_type": "Ideal", + "tap_phase_shifter": true, "tap_max": 10, "tap_min": -10, "tap_neutral": 0, "tap2_side": "lv", "tap2_step_percent": 0, "tap2_step_degree": -10.0, - "tap2_phase_shifter_type": 2, + "tap2_phase_shifter": true, "tap2_max": 10, "tap2_min": -10, "tap2_neutral": 0 @@ -1195,14 +1205,14 @@ "tap_side": "hv", "tap_step_percent": 2.0, "tap_step_degree": 0.0, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 10, "tap_min": -10, "tap_neutral": 0, "tap2_side": "hv", "tap2_step_percent": 2.0, "tap2_step_degree": 90.0, - "tap2_phase_shifter_type": 1, + "tap2_phase_shifter": false, "tap2_max": 10, "tap2_min": -10, "tap2_neutral": 0 @@ -1223,7 +1233,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "160 MVA 380/110 kV": { "i0_percent": 0.06, @@ -1241,7 +1251,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 20/0.4 kV": { "sn_mva": 0.4, @@ -1259,7 +1269,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "2-W HV-d LV-V": { "sn_mva": 100.0, @@ -1279,14 +1289,14 @@ "tap_side": "hv", "tap_step_percent": 0, "tap_step_degree": 5.0, - "tap_changer_type": "Ideal", + "tap_phase_shifter": true, "tap_max": 10, "tap_min": -10, "tap_neutral": 0, "tap2_side": "lv", "tap2_step_percent": 2.0, "tap2_step_degree": 30.0, - "tap2_phase_shifter_type": 0, + "tap2_phase_shifter": false, "tap2_max": 10, "tap2_min": -10, "tap2_neutral": 0 @@ -1307,7 +1317,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 10/0.4 kV": { "sn_mva": 0.25, @@ -1325,7 +1335,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "40 MVA 110/20 kV": { "i0_percent": 0.05, @@ -1343,7 +1353,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "100 MVA 220/110 kV": { "i0_percent": 0.06, @@ -1361,7 +1371,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.4 MVA 10/0.4 kV": { "sn_mva": 0.4, @@ -1379,7 +1389,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "25 MVA 110/10 kV": { "sn_mva": 25, @@ -1397,7 +1407,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "2-Winding Transformer Type": { "sn_mva": 100.0, @@ -1417,14 +1427,14 @@ "tap_side": "hv", "tap_step_percent": 2.0, "tap_step_degree": 10.0, - "tap_changer_type": "Ratio", + "tap_phase_shifter": false, "tap_max": 10, "tap_min": -10, "tap_neutral": 0, "tap2_side": "lv", "tap2_step_percent": 2.0, "tap2_step_degree": 30.0, - "tap2_phase_shifter_type": 0, + "tap2_phase_shifter": false, "tap2_max": 10, "tap2_min": -10, "tap2_neutral": 0 @@ -1445,7 +1455,7 @@ "tap_max": 9, "tap_step_degree": 0, "tap_step_percent": 1.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.25 MVA 20/0.4 kV": { "sn_mva": 0.25, @@ -1463,7 +1473,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false }, "0.63 MVA 20/0.4 kV": { "sn_mva": 0.63, @@ -1481,7 +1491,7 @@ "tap_max": 2, "tap_step_degree": 0, "tap_step_percent": 2.5, - "tap_changer_type": "Ratio" + "tap_phase_shifter": false } }, "trafo3w": { From 92e78c0a810792a46734dc5bddc1b36963726e1f Mon Sep 17 00:00:00 2001 From: tfabian Date: Fri, 20 Dec 2024 10:25:55 +0100 Subject: [PATCH 087/125] panos comment, change not necessary --- pandapower/convert_format.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/pandapower/convert_format.py b/pandapower/convert_format.py index 491302c81..5fc633d7d 100644 --- a/pandapower/convert_format.py +++ b/pandapower/convert_format.py @@ -558,12 +558,11 @@ def convert_trafo_pst_logic(net): """ for trafotable in ["trafo", "trafo3w"]: if trafotable in net and isinstance(net[trafotable], pd.DataFrame): - for t in ("", "2"): - # drop old tap_phase_shifter flag - if f"tap{t}_phase_shifter" in net[trafotable]: - net[trafotable] = net[trafotable].drop(columns=f"tap{t}_phase_shifter") if net[trafotable].index.size > 0: for t in ("", "2"): + # drop old tap_phase_shifter flag + if f"tap{t}_phase_shifter" in net[trafotable]: + net[trafotable] = net[trafotable].drop(columns=f"tap{t}_phase_shifter") if (f"tap{t}_step_degree" in net[trafotable]) or (f"tap{t}_step_percent" in net[trafotable]): # no phase shifters - check if both tap_step_percent & tap_step_degree are 0 or nan mask_na = (((net[trafotable][f"tap{t}_step_degree"].isna()) | From 08c4ac728a4a66c8765cfbd17ebe02028b6111ec Mon Sep 17 00:00:00 2001 From: tfabian Date: Fri, 20 Dec 2024 10:27:20 +0100 Subject: [PATCH 088/125] panos comment, change not necessary --- pandapower/control/util/diagnostic.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pandapower/control/util/diagnostic.py b/pandapower/control/util/diagnostic.py index 5e3aa8f42..440b49c29 100644 --- a/pandapower/control/util/diagnostic.py +++ b/pandapower/control/util/diagnostic.py @@ -90,7 +90,7 @@ def trafo_characteristic_table_diagnostic(net): f"tap_dependency_table and id_characteristic_table parameters populated. " f"Power flow calculation will raise an error.", category=UserWarning) warnings_count += 1 - # check if both tap_dependency_table & tap_phase_shifter_type columns are populated + # check if both tap_dependency_table & tap_changer_type columns are populated mismatch_b = net[trafo_table][ (net[trafo_table]['tap_dependency_table'] & net[trafo_table]['tap_changer_type'].isna()) ].shape[0] From a4104050325c093c6b1eb068bf3babfe6f146472 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 20 Dec 2024 11:31:40 +0200 Subject: [PATCH 089/125] update std_types documentation --- doc/std_types/basic.rst | 8 ++++---- doc/std_types/trafo3wtypes.csv | 6 +++--- doc/std_types/trafotypes.csv | 30 +++++++++++++++--------------- 3 files changed, 22 insertions(+), 22 deletions(-) diff --git a/doc/std_types/basic.rst b/doc/std_types/basic.rst index 51c5a0971..5133cf2d0 100644 --- a/doc/std_types/basic.rst +++ b/doc/std_types/basic.rst @@ -34,18 +34,18 @@ DC Lines Transformers ----------------- -.. tabularcolumns:: |l|l|l|l|l|l|l|l|l|l|l|l|l|l|l|l| +.. tabularcolumns:: |l|l|l|l|l|l|l|l|l|l|l|l|l|l|l|l|l| .. csv-table:: :file: trafotypes.csv :delim: ; - :widths: 60, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15 + :widths: 60, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15 Three Winding Transformers -------------------------------- -.. tabularcolumns:: |l|l|l|l|l|l|l|l|l|l|l||l|l|l|l|l|l|l|l|l|l|l| +.. tabularcolumns:: |l|l|l|l|l|l|l|l|l|l|l||l|l|l|l|l|l|l|l|l|l|l|l| .. csv-table:: :file: trafo3wtypes.csv :delim: ; - :widths: 60, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15 + :widths: 60, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15 diff --git a/doc/std_types/trafo3wtypes.csv b/doc/std_types/trafo3wtypes.csv index d2ca6ffce..9dafc0d8f 100644 --- a/doc/std_types/trafo3wtypes.csv +++ b/doc/std_types/trafo3wtypes.csv @@ -1,3 +1,3 @@ -;sn_hv_mva;sn_mv_mva;sn_lv_mva;vn_hv_kv;vn_mv_kv;vn_lv_kv;vk_hv_percent;vk_mv_percent;vk_lv_percent;vkr_hv_percent;vkr_mv_percent;vkr_lv_percent;pfe_kw;i0_percent;shift_mv_degree;shift_lv_degree;tap_side;tap_neutral;tap_min;tap_max;tap_step_percent -63/25/38 MVA 110/20/10 kV;63;25;38;110;20;10;10.4;10.4;10.4;0.28;0.32;0.35;35;0.89;0;0;hv;0;-10;10;1.2 -63/25/38 MVA 110/10/10 kV;63;25;38;110;10;10;10.4;10.4;10.4;0.28;0.32;0.35;35;0.89;0;0;hv;0;-10;10;1.2 +;sn_hv_mva;sn_mv_mva;sn_lv_mva;vn_hv_kv;vn_mv_kv;vn_lv_kv;vk_hv_percent;vk_mv_percent;vk_lv_percent;vkr_hv_percent;vkr_mv_percent;vkr_lv_percent;pfe_kw;i0_percent;shift_mv_degree;shift_lv_degree;tap_side;tap_neutral;tap_min;tap_max;tap_step_percent;tap_changer_type +63/25/38 MVA 110/20/10 kV;63;25;38;110;20;10;10.4;10.4;10.4;0.28;0.32;0.35;35;0.89;0;0;hv;0;-10;10;1.2;Ratio +63/25/38 MVA 110/10/10 kV;63;25;38;110;10;10;10.4;10.4;10.4;0.28;0.32;0.35;35;0.89;0;0;hv;0;-10;10;1.2;Ratio diff --git a/doc/std_types/trafotypes.csv b/doc/std_types/trafotypes.csv index b6012c9b6..daa387658 100644 --- a/doc/std_types/trafotypes.csv +++ b/doc/std_types/trafotypes.csv @@ -1,15 +1,15 @@ -;sn_mva;vn_hv_kv;vn_lv_kv;vk_percent;vkr_percent;pfe_kw;i0_percent;shift_degree;tap_side;tap_neutral;tap_min;tap_max;tap_step_percent;tap_step_degree;tap_phase_shifter -160 MVA 380/110 kV;160.0;380.0;110.0;12.2;0.25;60.0;0.06;0;hv;0;-9;9;1.5;0;False -100 MVA 220/110 kV;100.0;220.0;110.0;12.0;0.26;55.0;0.06;0;hv;0;-9;9;1.5;0;False -63 MVA 110/20 kV;63.0;110.0;20.0;18.0;0.32;22.0;0.04;150;hv;0;-9;9;1.5;0;False -40 MVA 110/20 kV;40.0;110.0;20.0;16.2;0.34;18.0;0.05;150;hv;0;-9;9;1.5;0;False -25 MVA 110/20 kV;25.0;110.0;20.0;12.0;0.41;14.0;0.07;150;hv;0;-9;9;1.5;0;False -63 MVA 110/10 kV;63.0;110.0;10.0;18.0;0.32;22.0;0.04;150;hv;0;-9;9;1.5;0;False -40 MVA 110/10 kV;40.0;110.0;10.0;16.2;0.34;18.0;0.05;150;hv;0;-9;9;1.5;0;False -25 MVA 110/10 kV;25.0;110.0;10.0;12.0;0.41;14.0;0.07;150;hv;0;-9;9;1.5;0;False -0.25 MVA 20/0.4 kV;0.25;20.0;0.4;6.0;1.44;0.8;0.32;150;hv;0;-2;2;2.5;0;False -0.4 MVA 20/0.4 kV;0.4;20.0;0.4;6.0;1.425;1.35;0.3375;150;hv;0;-2;2;2.5;0;False -0.63 MVA 20/0.4 kV;0.63;20.0;0.4;6.0;1.206;1.65;0.2619;150;hv;0;-2;2;2.5;0;False -0.25 MVA 10/0.4 kV;0.25;10.0;0.4;4.0;1.2;0.6;0.24;150;hv;0;-2;2;2.5;0;False -0.4 MVA 10/0.4 kV;0.4;10.0;0.4;4.0;1.325;0.95;0.2375;150;hv;0;-2;2;2.5;0;False -0.63 MVA 10/0.4 kV;0.63;10.0;0.4;4.0;1.0794;1.18;0.1873;150;hv;0;-2;2;2.5;0;False +;sn_mva;vn_hv_kv;vn_lv_kv;vk_percent;vkr_percent;pfe_kw;i0_percent;shift_degree;tap_side;tap_neutral;tap_min;tap_max;tap_step_percent;tap_step_degree;tap_changer_type +160 MVA 380/110 kV;160.0;380.0;110.0;12.2;0.25;60.0;0.06;0;hv;0;-9;9;1.5;0;Ratio +100 MVA 220/110 kV;100.0;220.0;110.0;12.0;0.26;55.0;0.06;0;hv;0;-9;9;1.5;0;Ratio +63 MVA 110/20 kV;63.0;110.0;20.0;18.0;0.32;22.0;0.04;150;hv;0;-9;9;1.5;0;Ratio +40 MVA 110/20 kV;40.0;110.0;20.0;16.2;0.34;18.0;0.05;150;hv;0;-9;9;1.5;0;Ratio +25 MVA 110/20 kV;25.0;110.0;20.0;12.0;0.41;14.0;0.07;150;hv;0;-9;9;1.5;0;Ratio +63 MVA 110/10 kV;63.0;110.0;10.0;18.0;0.32;22.0;0.04;150;hv;0;-9;9;1.5;0;Ratio +40 MVA 110/10 kV;40.0;110.0;10.0;16.2;0.34;18.0;0.05;150;hv;0;-9;9;1.5;0;Ratio +25 MVA 110/10 kV;25.0;110.0;10.0;12.0;0.41;14.0;0.07;150;hv;0;-9;9;1.5;0;Ratio +0.25 MVA 20/0.4 kV;0.25;20.0;0.4;6.0;1.44;0.8;0.32;150;hv;0;-2;2;2.5;0;Ratio +0.4 MVA 20/0.4 kV;0.4;20.0;0.4;6.0;1.425;1.35;0.3375;150;hv;0;-2;2;2.5;0;Ratio +0.63 MVA 20/0.4 kV;0.63;20.0;0.4;6.0;1.206;1.65;0.2619;150;hv;0;-2;2;2.5;0;Ratio +0.25 MVA 10/0.4 kV;0.25;10.0;0.4;4.0;1.2;0.6;0.24;150;hv;0;-2;2;2.5;0;Ratio +0.4 MVA 10/0.4 kV;0.4;10.0;0.4;4.0;1.325;0.95;0.2375;150;hv;0;-2;2;2.5;0;Ratio +0.63 MVA 10/0.4 kV;0.63;10.0;0.4;4.0;1.0794;1.18;0.1873;150;hv;0;-2;2;2.5;0;Ratio From 21fc04de3e3dcd07b60c4dbd5db322c7c84225d6 Mon Sep 17 00:00:00 2001 From: tfabian Date: Fri, 20 Dec 2024 10:46:50 +0100 Subject: [PATCH 090/125] docu for tap_changer_type --- doc/about/update30.rst | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/doc/about/update30.rst b/doc/about/update30.rst index f82695000..05599ca4d 100644 --- a/doc/about/update30.rst +++ b/doc/about/update30.rst @@ -28,7 +28,13 @@ This is established by multiple functions/codings in the pandapower package. The columns in :code:`net.group` are also changed: To :code:`element_type` and :code:`element_index` to avoid misunderstandings. A major rework could include the names :code:`element_type` and :code:`element_index` at any place in the package but has not been implemented (yet?) since it would break large parts of package usage. +Transformers +========== +Different types of tap changers are now explicitly accessible via :code:`tap_changer_type` (string) "Ratio", "Symmetrical" or "Ideal". + + To sum up, the following changes were made: - TrafoController parameters: :code:`trafotable, trafotype` ➔ :code:`element_type`; :code:`tid` ➔ :code:`element_index` - Group column: :code:`net.groups.element` ➔ :code:`net.groups.element_index` + - the tap changer variables :code:`tap_phase_shifter` ➔ :code:`tap_changer_type` bool true/fals to string "Ratio","Symmetrical","Ideal". \ No newline at end of file From 4ac812ab2085a9b880f519077cf758504de3f649 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 20 Dec 2024 11:51:19 +0200 Subject: [PATCH 091/125] update std_types documentation v2 --- doc/std_types/basic.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/doc/std_types/basic.rst b/doc/std_types/basic.rst index 5133cf2d0..ccf2a5d40 100644 --- a/doc/std_types/basic.rst +++ b/doc/std_types/basic.rst @@ -34,11 +34,11 @@ DC Lines Transformers ----------------- -.. tabularcolumns:: |l|l|l|l|l|l|l|l|l|l|l|l|l|l|l|l|l| +.. tabularcolumns:: |l|l|l|l|l|l|l|l|l|l|l|l|l|l|l|l| .. csv-table:: :file: trafotypes.csv :delim: ; - :widths: 60, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15 + :widths: 60, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15 Three Winding Transformers -------------------------------- From a1fb8102fbaee137a2efcc0cea5c62dc417d6ad6 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 20 Dec 2024 12:10:32 +0200 Subject: [PATCH 092/125] update update30.rst --- doc/about/update30.rst | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/doc/about/update30.rst b/doc/about/update30.rst index 05599ca4d..b81c96691 100644 --- a/doc/about/update30.rst +++ b/doc/about/update30.rst @@ -29,12 +29,12 @@ The columns in :code:`net.group` are also changed: To :code:`element_type` and : A major rework could include the names :code:`element_type` and :code:`element_index` at any place in the package but has not been implemented (yet?) since it would break large parts of package usage. Transformers -========== -Different types of tap changers are now explicitly accessible via :code:`tap_changer_type` (string) "Ratio", "Symmetrical" or "Ideal". +============= +Different types of tap changers for 2-winding and 3-winding transformers are now explicitly accessible via :code:`tap_changer_type` (string) "Ratio", "Symmetrical" or "Ideal". To sum up, the following changes were made: - TrafoController parameters: :code:`trafotable, trafotype` ➔ :code:`element_type`; :code:`tid` ➔ :code:`element_index` - Group column: :code:`net.groups.element` ➔ :code:`net.groups.element_index` - - the tap changer variables :code:`tap_phase_shifter` ➔ :code:`tap_changer_type` bool true/fals to string "Ratio","Symmetrical","Ideal". \ No newline at end of file + - the tap changer variables :code:`tap_phase_shifter` ➔ :code:`tap_changer_type` bool True/False to string "Ratio","Symmetrical","Ideal". \ No newline at end of file From 246efc2b26ba2d77adfc21df4291a9084aebec52 Mon Sep 17 00:00:00 2001 From: tfabian Date: Fri, 20 Dec 2024 11:23:06 +0100 Subject: [PATCH 093/125] delete "characteristic" from json file --- pandapower/networks/IEEE_European_LV_Off_Peak_1.json | 11 ----------- .../networks/IEEE_European_LV_Off_Peak_1440.json | 11 ----------- pandapower/networks/IEEE_European_LV_On_Peak_566.json | 11 ----------- pandapower/networks/lv_schutterwald.json | 11 ----------- pandapower/networks/mv_oberrhein.json | 11 ----------- pandapower/networks/mv_oberrhein_substations.json | 11 ----------- .../power_system_test_case_jsons/GBnetwork.json | 11 ----------- .../GBreducednetwork.json | 11 ----------- .../power_system_test_case_jsons/case118.json | 11 ----------- .../power_system_test_case_jsons/case11_iwamoto.json | 11 ----------- .../power_system_test_case_jsons/case1354pegase.json | 11 ----------- .../networks/power_system_test_case_jsons/case14.json | 11 ----------- .../power_system_test_case_jsons/case145.json | 11 ----------- .../power_system_test_case_jsons/case1888rte.json | 11 ----------- .../power_system_test_case_jsons/case24_ieee_rts.json | 11 ----------- .../power_system_test_case_jsons/case2848rte.json | 11 ----------- .../power_system_test_case_jsons/case2869pegase.json | 11 ----------- .../networks/power_system_test_case_jsons/case30.json | 11 ----------- .../power_system_test_case_jsons/case300.json | 11 ----------- .../power_system_test_case_jsons/case3120sp.json | 11 ----------- .../power_system_test_case_jsons/case33bw.json | 11 ----------- .../networks/power_system_test_case_jsons/case39.json | 11 ----------- .../power_system_test_case_jsons/case4gs.json | 11 ----------- .../networks/power_system_test_case_jsons/case5.json | 11 ----------- .../networks/power_system_test_case_jsons/case57.json | 11 ----------- .../case5_demo_gridcal.json | 11 ----------- .../power_system_test_case_jsons/case6470rte.json | 11 ----------- .../power_system_test_case_jsons/case6495rte.json | 11 ----------- .../power_system_test_case_jsons/case6515rte.json | 11 ----------- .../power_system_test_case_jsons/case6ww.json | 11 ----------- .../power_system_test_case_jsons/case89pegase.json | 11 ----------- .../networks/power_system_test_case_jsons/case9.json | 11 ----------- .../power_system_test_case_jsons/case9241pegase.json | 11 ----------- .../power_system_test_case_jsons/case_ieee30.json | 11 ----------- .../case_illinois200.json | 11 ----------- .../power_system_test_case_jsons/iceland.json | 11 ----------- .../test/converter/testfiles/trafo_tap_model.json | 11 ----------- .../test/test_files/old_versions/example_2.12.0.json | 11 ----------- .../test/test_files/old_versions/example_2.12.1.json | 11 ----------- .../test/test_files/old_versions/example_2.13.0.json | 11 ----------- 40 files changed, 440 deletions(-) diff --git a/pandapower/networks/IEEE_European_LV_Off_Peak_1.json b/pandapower/networks/IEEE_European_LV_Off_Peak_1.json index e91c815a8..460faf14b 100644 --- a/pandapower/networks/IEEE_European_LV_Off_Peak_1.json +++ b/pandapower/networks/IEEE_European_LV_Off_Peak_1.json @@ -546,17 +546,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json b/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json index ccc96d974..9ded48606 100644 --- a/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json +++ b/pandapower/networks/IEEE_European_LV_Off_Peak_1440.json @@ -546,17 +546,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/IEEE_European_LV_On_Peak_566.json b/pandapower/networks/IEEE_European_LV_On_Peak_566.json index 870517ef1..7c2dafeb8 100644 --- a/pandapower/networks/IEEE_European_LV_On_Peak_566.json +++ b/pandapower/networks/IEEE_European_LV_On_Peak_566.json @@ -546,17 +546,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/lv_schutterwald.json b/pandapower/networks/lv_schutterwald.json index b33bacfb1..e2ae47a34 100644 --- a/pandapower/networks/lv_schutterwald.json +++ b/pandapower/networks/lv_schutterwald.json @@ -509,17 +509,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/mv_oberrhein.json b/pandapower/networks/mv_oberrhein.json index 00053a005..2f9bb6224 100644 --- a/pandapower/networks/mv_oberrhein.json +++ b/pandapower/networks/mv_oberrhein.json @@ -514,17 +514,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/mv_oberrhein_substations.json b/pandapower/networks/mv_oberrhein_substations.json index 0becaa3fd..b3fe2498e 100644 --- a/pandapower/networks/mv_oberrhein_substations.json +++ b/pandapower/networks/mv_oberrhein_substations.json @@ -514,17 +514,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/GBnetwork.json b/pandapower/networks/power_system_test_case_jsons/GBnetwork.json index 9e25cb852..946765109 100644 --- a/pandapower/networks/power_system_test_case_jsons/GBnetwork.json +++ b/pandapower/networks/power_system_test_case_jsons/GBnetwork.json @@ -515,17 +515,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json b/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json index e12a8873b..40ea014c6 100644 --- a/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json +++ b/pandapower/networks/power_system_test_case_jsons/GBreducednetwork.json @@ -521,17 +521,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case118.json b/pandapower/networks/power_system_test_case_jsons/case118.json index 28efc1bdc..d730524b7 100644 --- a/pandapower/networks/power_system_test_case_jsons/case118.json +++ b/pandapower/networks/power_system_test_case_jsons/case118.json @@ -518,17 +518,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json b/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json index ab15b1e10..b84284501 100644 --- a/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json +++ b/pandapower/networks/power_system_test_case_jsons/case11_iwamoto.json @@ -506,17 +506,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case1354pegase.json b/pandapower/networks/power_system_test_case_jsons/case1354pegase.json index 840d7cf2f..2b72e5609 100644 --- a/pandapower/networks/power_system_test_case_jsons/case1354pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case1354pegase.json @@ -519,17 +519,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case14.json b/pandapower/networks/power_system_test_case_jsons/case14.json index f64d58cf2..b668b52d1 100644 --- a/pandapower/networks/power_system_test_case_jsons/case14.json +++ b/pandapower/networks/power_system_test_case_jsons/case14.json @@ -518,17 +518,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case145.json b/pandapower/networks/power_system_test_case_jsons/case145.json index 623f9a433..b0c34e996 100644 --- a/pandapower/networks/power_system_test_case_jsons/case145.json +++ b/pandapower/networks/power_system_test_case_jsons/case145.json @@ -519,17 +519,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case1888rte.json b/pandapower/networks/power_system_test_case_jsons/case1888rte.json index ae0d70712..a09fa560f 100644 --- a/pandapower/networks/power_system_test_case_jsons/case1888rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case1888rte.json @@ -523,17 +523,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json b/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json index c169eacc0..eed8bb234 100644 --- a/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json +++ b/pandapower/networks/power_system_test_case_jsons/case24_ieee_rts.json @@ -523,17 +523,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case2848rte.json b/pandapower/networks/power_system_test_case_jsons/case2848rte.json index a7375b421..6d089ba68 100644 --- a/pandapower/networks/power_system_test_case_jsons/case2848rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case2848rte.json @@ -523,17 +523,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case2869pegase.json b/pandapower/networks/power_system_test_case_jsons/case2869pegase.json index 1834b4dbf..92a8a4b17 100644 --- a/pandapower/networks/power_system_test_case_jsons/case2869pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case2869pegase.json @@ -519,17 +519,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case30.json b/pandapower/networks/power_system_test_case_jsons/case30.json index 68d2f55a8..76204c52f 100644 --- a/pandapower/networks/power_system_test_case_jsons/case30.json +++ b/pandapower/networks/power_system_test_case_jsons/case30.json @@ -517,17 +517,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case300.json b/pandapower/networks/power_system_test_case_jsons/case300.json index a3af72513..f871aa975 100644 --- a/pandapower/networks/power_system_test_case_jsons/case300.json +++ b/pandapower/networks/power_system_test_case_jsons/case300.json @@ -519,17 +519,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case3120sp.json b/pandapower/networks/power_system_test_case_jsons/case3120sp.json index cf9adb5b1..9a213d405 100644 --- a/pandapower/networks/power_system_test_case_jsons/case3120sp.json +++ b/pandapower/networks/power_system_test_case_jsons/case3120sp.json @@ -523,17 +523,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case33bw.json b/pandapower/networks/power_system_test_case_jsons/case33bw.json index 9ef5276c6..a2150f73b 100644 --- a/pandapower/networks/power_system_test_case_jsons/case33bw.json +++ b/pandapower/networks/power_system_test_case_jsons/case33bw.json @@ -514,17 +514,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case39.json b/pandapower/networks/power_system_test_case_jsons/case39.json index abbc39f57..a56dcdc04 100644 --- a/pandapower/networks/power_system_test_case_jsons/case39.json +++ b/pandapower/networks/power_system_test_case_jsons/case39.json @@ -518,17 +518,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case4gs.json b/pandapower/networks/power_system_test_case_jsons/case4gs.json index 001a9c68b..f71de00d7 100644 --- a/pandapower/networks/power_system_test_case_jsons/case4gs.json +++ b/pandapower/networks/power_system_test_case_jsons/case4gs.json @@ -517,17 +517,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case5.json b/pandapower/networks/power_system_test_case_jsons/case5.json index 65ec9fc5e..c435e6664 100644 --- a/pandapower/networks/power_system_test_case_jsons/case5.json +++ b/pandapower/networks/power_system_test_case_jsons/case5.json @@ -522,17 +522,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case57.json b/pandapower/networks/power_system_test_case_jsons/case57.json index 7cdbbbb4c..e6ae0c093 100644 --- a/pandapower/networks/power_system_test_case_jsons/case57.json +++ b/pandapower/networks/power_system_test_case_jsons/case57.json @@ -518,17 +518,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json b/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json index d15720489..7ffe6dcdc 100644 --- a/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json +++ b/pandapower/networks/power_system_test_case_jsons/case5_demo_gridcal.json @@ -512,17 +512,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case6470rte.json b/pandapower/networks/power_system_test_case_jsons/case6470rte.json index 890907f16..209dd03c3 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6470rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6470rte.json @@ -523,17 +523,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case6495rte.json b/pandapower/networks/power_system_test_case_jsons/case6495rte.json index 51bb284df..8bd85ee0b 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6495rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6495rte.json @@ -523,17 +523,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case6515rte.json b/pandapower/networks/power_system_test_case_jsons/case6515rte.json index b56734e7c..a0feb23ef 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6515rte.json +++ b/pandapower/networks/power_system_test_case_jsons/case6515rte.json @@ -523,17 +523,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case6ww.json b/pandapower/networks/power_system_test_case_jsons/case6ww.json index ca355d32d..e19dadb4a 100644 --- a/pandapower/networks/power_system_test_case_jsons/case6ww.json +++ b/pandapower/networks/power_system_test_case_jsons/case6ww.json @@ -517,17 +517,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case89pegase.json b/pandapower/networks/power_system_test_case_jsons/case89pegase.json index 14941bbb1..4b686706d 100644 --- a/pandapower/networks/power_system_test_case_jsons/case89pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case89pegase.json @@ -519,17 +519,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case9.json b/pandapower/networks/power_system_test_case_jsons/case9.json index 1a2e4ff14..dcc53703c 100644 --- a/pandapower/networks/power_system_test_case_jsons/case9.json +++ b/pandapower/networks/power_system_test_case_jsons/case9.json @@ -517,17 +517,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case9241pegase.json b/pandapower/networks/power_system_test_case_jsons/case9241pegase.json index 5697621c9..9a07315c1 100644 --- a/pandapower/networks/power_system_test_case_jsons/case9241pegase.json +++ b/pandapower/networks/power_system_test_case_jsons/case9241pegase.json @@ -519,17 +519,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case_ieee30.json b/pandapower/networks/power_system_test_case_jsons/case_ieee30.json index bea49d968..e7328cfc3 100644 --- a/pandapower/networks/power_system_test_case_jsons/case_ieee30.json +++ b/pandapower/networks/power_system_test_case_jsons/case_ieee30.json @@ -518,17 +518,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/case_illinois200.json b/pandapower/networks/power_system_test_case_jsons/case_illinois200.json index 7dc673b32..893ff2fc9 100644 --- a/pandapower/networks/power_system_test_case_jsons/case_illinois200.json +++ b/pandapower/networks/power_system_test_case_jsons/case_illinois200.json @@ -523,17 +523,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/networks/power_system_test_case_jsons/iceland.json b/pandapower/networks/power_system_test_case_jsons/iceland.json index 7a51b132c..481781aeb 100644 --- a/pandapower/networks/power_system_test_case_jsons/iceland.json +++ b/pandapower/networks/power_system_test_case_jsons/iceland.json @@ -515,17 +515,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/test/converter/testfiles/trafo_tap_model.json b/pandapower/test/converter/testfiles/trafo_tap_model.json index 428711c08..cf9575f03 100644 --- a/pandapower/test/converter/testfiles/trafo_tap_model.json +++ b/pandapower/test/converter/testfiles/trafo_tap_model.json @@ -540,17 +540,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/test/test_files/old_versions/example_2.12.0.json b/pandapower/test/test_files/old_versions/example_2.12.0.json index b41af38b3..52fad6c51 100644 --- a/pandapower/test/test_files/old_versions/example_2.12.0.json +++ b/pandapower/test/test_files/old_versions/example_2.12.0.json @@ -495,17 +495,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/test/test_files/old_versions/example_2.12.1.json b/pandapower/test/test_files/old_versions/example_2.12.1.json index 13d627693..5cf112b30 100644 --- a/pandapower/test/test_files/old_versions/example_2.12.1.json +++ b/pandapower/test/test_files/old_versions/example_2.12.1.json @@ -495,17 +495,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", diff --git a/pandapower/test/test_files/old_versions/example_2.13.0.json b/pandapower/test/test_files/old_versions/example_2.13.0.json index ac0f0c9d7..14e9fc2ee 100644 --- a/pandapower/test/test_files/old_versions/example_2.13.0.json +++ b/pandapower/test/test_files/old_versions/example_2.13.0.json @@ -495,17 +495,6 @@ "is_multiindex": false, "is_multicolumn": false }, - "characteristic": { - "_module": "pandas.core.frame", - "_class": "DataFrame", - "_object": "{\"columns\":[\"object\"],\"index\":[],\"data\":[]}", - "orient": "split", - "dtype": { - "object": "object" - }, - "is_multiindex": false, - "is_multicolumn": false - }, "controller": { "_module": "pandas.core.frame", "_class": "DataFrame", From c1a0aafa6345648a23517c59c3b0d22a2572edaa Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Fri, 20 Dec 2024 11:34:28 +0100 Subject: [PATCH 094/125] test pf_converter for adjusted trafo tap changer working and small bug_fix in converter --- pandapower/build_branch.py | 3 +- .../powerfactory/pp_import_functions.py | 10 ++--- .../test/converter/test_from_powerfactory.py | 36 +++++++++++++++++- .../converter/testfiles/test_tap_changer.pfd | Bin 0 -> 157816 bytes 4 files changed, 41 insertions(+), 8 deletions(-) create mode 100644 pandapower/test/converter/testfiles/test_tap_changer.pfd diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 98d446e2f..3c2683f47 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -611,7 +611,7 @@ def _calc_tap_from_dataframe(net, trafo_df): else: tap_table = np.array([False]) tap_dependency = np.array([False]) - tap_changer_type = pd.Series(tap_changer_type) + #tap_changer_type = pd.Series(tap_changer_type) tap_table = np.logical_and(tap_dependency, np.logical_not(tap_changer_type == "None")) tap_no_table = np.logical_and(~tap_dependency, np.logical_not(tap_changer_type == "None")) if any(tap_table): @@ -822,6 +822,7 @@ def _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, sn_mva, sequenc [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency_table]) if any(tap_dependency_table) and not isinstance(trafo_df, dict): vk_percent, vkr_percent = _get_vk_values_from_table(trafo_df, net.trafo_characteristic_table) + # update for 3W already in _calc_sc_voltages_of_equivalent_transformers else: vk_percent = get_trafo_values(trafo_df, "vk_percent") vkr_percent = get_trafo_values(trafo_df, "vkr_percent") diff --git a/pandapower/converter/powerfactory/pp_import_functions.py b/pandapower/converter/powerfactory/pp_import_functions.py index cdade4153..b2cfb1bf7 100644 --- a/pandapower/converter/powerfactory/pp_import_functions.py +++ b/pandapower/converter/powerfactory/pp_import_functions.py @@ -2293,8 +2293,8 @@ def create_trafo_type(net, item): "tap_side": ['hv', 'lv', 'ext'][item.tap_side], # 'ext' not implemented } - type_data.update({"tap_changer_type": None}) - type_data.update({"tap2_changer_type": None}) + type_data.update({"tap_changer_type": "None"}) + type_data.update({"tap2_changer_type": "None"}) if item.itapch: logger.debug('trafo <%s> has tap changer' % name) @@ -2451,7 +2451,7 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc elif pf_type.tapchtype == 2: tap_changer_type = "Ideal" else: - tap_changer_type = None + tap_changer_type = "None" tap_dependency_table = True id_characteristic_table = new_id_characteristic_table @@ -2532,7 +2532,7 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc elif pf_type.tapchtype == 2: tap_changer_type = "Ideal" else: - tap_changer_type = None + tap_changer_type = "None" tap_dependency_table = True id_characteristic_table = new_id_characteristic_table @@ -2831,7 +2831,7 @@ def create_trafo3w(net, item, tap_opt='nntap'): tap_step_degree = item.GetAttribute('t:ph3tr_' + ts) if (tap_step_degree is None or tap_step_degree == 0) and (tap_step_percent is None or tap_step_percent == 0): - tap_changer_type = None + tap_changer_type = "None" # ratio/asymmetrical phase shifters elif (tap_step_degree != 90 and tap_step_percent is not None and tap_step_percent != 0): tap_changer_type = "Ratio" diff --git a/pandapower/test/converter/test_from_powerfactory.py b/pandapower/test/converter/test_from_powerfactory.py index 06bbb4b02..02e3ca7b5 100644 --- a/pandapower/test/converter/test_from_powerfactory.py +++ b/pandapower/test/converter/test_from_powerfactory.py @@ -18,6 +18,7 @@ try: import powerfactory as pf + PF_INSTALLED = True except ImportError: PF_INSTALLED = False @@ -65,7 +66,12 @@ def test_pf_export(): tol = get_tol() for key, diff in all_diffs.items(): - delta = diff.abs().max() + if isinstance(diff, pd.DataFrame): + delta = diff["diff"].abs().max() + elif isinstance(diff, pd.Series): + delta = diff.abs().max() + else: + raise (UserWarning, "Diff variable has wrong type!") assert delta < tol[key], "%s has too high difference: %f > %f" % (key, delta, tol[key]) @@ -87,9 +93,15 @@ def test_pf_export_trafo3w(): # doesn't pass yet due to trafo3w implementation # trafo3w implementation is not very accurate for key, diff in all_diffs.items(): - delta = diff.abs().max() + if isinstance(diff, pd.DataFrame): + delta = diff["diff"].abs().max() + elif isinstance(diff, pd.Series): + delta = diff.abs().max() + else: + raise (UserWarning, "Diff variable has wrong type!") assert delta < tol[key], "%s has too high difference: %f > %f" % (key, delta, tol[key]) + def test_trafo_tap2_results(): path = os.path.join(pp.pp_dir, 'test', 'converter', 'testfiles', 'trafo_tap_model.json') net = pp.from_json(path) @@ -102,5 +114,25 @@ def test_trafo_tap2_results(): delta = diff['diff'].abs().max() assert delta < tol, "%s has too high difference: %f > %f" % (key, delta, tol) +@pytest.mark.skipif(not PF_INSTALLED, reason='powerfactory must be installed') +def test_pf_export_tap_changer(): + app = pf.GetApplication() + # import the tap changer test grid to powerfactory + path = os.path.join(pp.pp_dir, 'test', 'converter', 'testfiles', 'test_tap_changer.pfd') + prj = import_project(path, app, 'TEST_PF_CONVERTER', import_folder='TEST_IMPORT', clear_import_folder=True) + prj_name = prj.GetFullName() + + net = from_pfd(app, prj_name=prj_name) + + all_diffs = validate_pf_conversion(net, tolerance_mva=1e-9) + tol = get_tol() + + for key, diff in all_diffs.items(): + if type(diff) == pd.Series: + delta = diff.abs().max() + else: + delta = diff['diff'].abs().max() + assert delta < tol[key], "%s has too high difference: %f > %f" % (key, delta, tol[key]) + if __name__ == '__main__': pytest.main([__file__, "-xs"]) diff --git a/pandapower/test/converter/testfiles/test_tap_changer.pfd b/pandapower/test/converter/testfiles/test_tap_changer.pfd new file mode 100644 index 0000000000000000000000000000000000000000..b9444a36da00232bfaba77baa811fb77f153b652 GIT 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zKD4o8!8Y=aaTq}UfC)?Jp`QmTu)(xGB~Vv}`LbQvcRD&B!*6lR=VNkE7TJ2gAFc2L zc3VrkTa*!~ZY(ss3VKrZjg+hT{4-4xQmz%3G1HQiy@5n-PT@-^Ebdg#4+ql+ohDY8 ziumdiYA}pF&>ZB+d4cI`MXb`Y-Ip1UyFpuGMJ2On{w(0SrJ^#Kw>GQv$4K~Q5kB41X*^S8V+lRg=Q^fOQnrN zYHBq*=hbE&mt~FFCp*C8?|u_D+ui-8igS|wFq*ORevPn;>klB)U_*4jHXZnRyU#?7IUyH<2}EryiuvNzDimrI`qBfJl;?+tb;XQfzsCf{`0s z?S6qwQ16>dA|ss0Htuv`^*_q5xe-G>wUR>lw`dy4VGgygKrTc{|OzT3!jWX*QhL7C_hFvfPB+u;18vZFu<8I zBpqh05Fq%!m!nN3v+vL5uYh#!uND)Ss6ae~$T{=Ph~97~YjAA*l3wlr*St5KV+(V_ z)AX=v=NXRsM_O!X8y^kda>qjfd{8B z--CP<7*zbPb9Qrefi_2unZH>NupMJ_3**ef+`cNUo5}%H#&p;7PCMa0;JH11Y1#?e zzMJ!@Ms~w~p-jh;+TUzzLLmMdOudCwiUoAGG3rPbkRAbU82nYc&_!jjdY5K{<;zd5 zh-$hCDpNQj%q%@As1>UyJcxHi{x@Jcu4djkdSzBAS-{5&(zI9t6%-K@{lLy8XT2mf zEs7@!6(YX+=7N`ZpinRlkt&R^E2M+{fr~+!b%NnjwMBC!c6&hpyX!^)^GqMC4GoF$ zR0rjftMPHJX(63S20UGAl193DD3%XI-u=?m=fS;ZnIxPT%#b$z!S?tc@jF4=bPc}u z-_~ws@?5N~z3~WX1o3sk1g8vw6p4~nxEb!Wnd#!pM`+;RWikPK Date: Fri, 20 Dec 2024 11:59:32 +0100 Subject: [PATCH 095/125] if ("tap_changer_type" in net.trafo3w.columns) --- pandapower/contingency/contingency.py | 2 +- pandapower/test/contingency/test_contingency.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index 5bbd0c170..52fe54696 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -193,7 +193,7 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. tct2w_flag = True tct2w, tct2w_tap_pos, tct2w_shift_degree = _convert_trafo_phase_shifter( net, "trafo", "tap_changer_type") - if np.any(net.trafo3w.tap_changer_type == "Ideal"): + if ("tap_changer_type" in net.trafo3w.columns) and np.any(net.trafo3w.tap_changer_type == "Ideal"): tct3w_flag = True tct3w, tct3w_tap_pos, tct3w_shift_degree = _convert_trafo_phase_shifter( net, "trafo3w", "tap_changer_type") diff --git a/pandapower/test/contingency/test_contingency.py b/pandapower/test/contingency/test_contingency.py index fb7e2a304..24ef1d81c 100644 --- a/pandapower/test/contingency/test_contingency.py +++ b/pandapower/test/contingency/test_contingency.py @@ -412,7 +412,7 @@ def _randomize_indices(net): def test_reminder_bring_back_case118(): from packaging.version import Version - if lightsim2grid_installed and Version(lightsim2grid.__version__) > Version("0.9.0"): + if lightsim2grid_installed and Version(lightsim2grid.__version__) > Version("0.10.0"): raise UserWarning("bring back case 118 and remove xfail for test_unequal_trafo_impedances and test_case118") From 18ba569c639aaf137d6a08adaa827b187dbdbb3e Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 20 Dec 2024 13:28:05 +0200 Subject: [PATCH 096/125] fix bug in contingency.py --- pandapower/contingency/contingency.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/pandapower/contingency/contingency.py b/pandapower/contingency/contingency.py index 5bbd0c170..ac24f65d5 100644 --- a/pandapower/contingency/contingency.py +++ b/pandapower/contingency/contingency.py @@ -188,17 +188,19 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=pp. tct2w, tct2w_tap_pos, tct2w_shift_degree = None, None, None tct3w_flag = False tct3w, tct3w_tap_pos, tct3w_shift_degree = None, None, None - if ("tap_changer_type" in net.trafo.columns) or ("tap_changer_type" in net.trafo3w.columns): + if "tap_changer_type" in net.trafo.columns: if np.any(net.trafo.tap_changer_type == "Ideal"): tct2w_flag = True tct2w, tct2w_tap_pos, tct2w_shift_degree = _convert_trafo_phase_shifter( net, "trafo", "tap_changer_type") + if "tap_changer_type" in net.trafo3w.columns: if np.any(net.trafo3w.tap_changer_type == "Ideal"): tct3w_flag = True tct3w, tct3w_tap_pos, tct3w_shift_degree = _convert_trafo_phase_shifter( net, "trafo3w", "tap_changer_type") - # TODO: remove next line when lightsim2grid supports checking of column 'tap_changer_type' + # TODO: remove next 2 lines when lightsim2grid supports checking of column 'tap_changer_type' + if ("tap_changer_type" in net.trafo.columns) or ("tap_changer_type" in net.trafo3w.columns): net.trafo["tap_phase_shifter"] = False # setting "slack" back-and-forth is due to the difference in interpretation of generators as "distributed slack" From aada180b83c3edd78e1bc6362bd638a3c71e912e Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 20 Dec 2024 13:59:42 +0200 Subject: [PATCH 097/125] updated CHANGELOG.rst --- CHANGELOG.rst | 24 ++++++++++++++++++++++-- 1 file changed, 22 insertions(+), 2 deletions(-) diff --git a/CHANGELOG.rst b/CHANGELOG.rst index 0b29abe0e..481f48bde 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -3,6 +3,26 @@ Change Log [upcoming release] - 2024-..-.. ------------------------------- +- [CHANGED] updated PowerFactory to pandapower converter to export measurement reports and reflect changes in trafo/trafo3w tap changer logic +- [ADDED] shunt_characteristic_spline table +- [CHANGED] renamed characteristic table to trafo_characteristic_spline table and changed its structure so that there is one row with all spline characteristic objects per trafo/trafo3w +- [ADDED] step_dependency_table flag for shunt elements +- [CHANGED] renamed tap_dependent_impedance flag to tap_dependency_table for trafo and trafo3w elements +- [ADDED] id_characteristic_spline optional variable for shunt elements +- [REMOVED] vk_hv_percent_characteristic, vk_mv_percent_characteristic, vk_lv_percent_characteristic, vkr_hv_percent_characteristic, vkr_mv_percent_characteristic and vkr_lv_percent_characteristic variables from trafo3w table +- [REMOVED] vk_percent_characteristic and vkr_percent_characteristic variables from trafo table +- [ADDED] id_characteristic_spline optional variable for trafo and trafo3w elements +- [ADDED] id_characteristic_table variable for shunt elements +- [CHANGED] renamed id_characteristic variable to id_characteristic_table for trafo and trafo3w elements +- [ADDED] shunt_characteristic_table lookup table for step dependent values for shunt elements +- [CHANGED] renamed characteristic_temp lookup table to trafo_characteristic_table for trafo and trafo3w elements +- [CHANGED] cim2pp converter - removed default creation of trafo spline characteristics +- [ADDED] cim2pp converter - export NonlinearShuntCompensatorPoint values for shunt elements +- [FIXED] cim2pp converter - correctly populate step, max_step and q_mvar / p_mw values per step for shunt elements +- [ADDED] cim2pp converter - added tap changer type classification for trafo and trafo3w elements +- [FIXED] cim2pp converter - correctly populate tap_step_degree and shift_degree variables for trafo and trafo3w elements +- [ADDED] tap_changer_type variable for net.trafo and net.trafo3w tables (supporting "Ratio", "Symmetrical" and "Ideal" tap changer types) +- [REMOVED] tap_phase_shifter bool variable from net.trafo table - [ADDED] Implementation of Allocation Factor WLS (AF-WLS) for non observable distribution grids - [FIXED] Deletion of multiple measurements at the same bus or branch - [FIXED] Creation of zero injection measurements in WLS estimator @@ -20,7 +40,7 @@ Change Log - [CHANGED] Capitalize first letter of columns busbar_id, busbar_name and substation_id in bus df for cim converter - [FIXED] Do not modify pandas options when importing pandapower - [FIXED] fixed copy-paste error in contingency results "max_limit_nminus1" and "min_limit_nminus1" -- [ADDED] improved lightsim2grid documentation including compatibitliy issues +- [ADDED] improved lightsim2grid documentation including compatibility issues - [FIXED] cim2pp: set default xml encoding to None to avoid error after changing to lxml - [FIXED] PandaModels OPF with 'bus_dc' key errors - [FIXED] julia tests @@ -53,7 +73,7 @@ Change Log - [CHANGED] plotting for voltage profile considers also gens that are slacks and only ext_grids and slack gens that are in service - [CHANGED] switched from setup.py to pyproject.toml - [CHANGED] updated upload_release.py to not call setup.py anymore (see https://packaging.python.org/en/latest/discussions/setup-py-deprecated/) -- [CHANGED] updated upload_release.py to install the uploadad package and print the version +- [CHANGED] updated upload_release.py to install the uploaded package and print the version - [CHANGED] updated MANIFEST.in to exclude the ci files from the wheel distribution - [CHANGED] cim data structure method in cim converter changed to blueprint approach - [CHANGED] cim converter: Avoid huge logging output when ignore_errors = True From d02ee5b7183d2fee53fd8b5ee380bb785ecc3a51 Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Fri, 20 Dec 2024 15:02:18 +0100 Subject: [PATCH 098/125] Bugfix in pf import and pf import test for tap changer finalisation --- .../powerfactory/pp_import_functions.py | 8 +++++--- .../test/converter/test_from_powerfactory.py | 18 ++++++++++++++---- 2 files changed, 19 insertions(+), 7 deletions(-) diff --git a/pandapower/converter/powerfactory/pp_import_functions.py b/pandapower/converter/powerfactory/pp_import_functions.py index b2cfb1bf7..d5ff2419e 100644 --- a/pandapower/converter/powerfactory/pp_import_functions.py +++ b/pandapower/converter/powerfactory/pp_import_functions.py @@ -2429,7 +2429,8 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc else: raise ValueError("Measurement location for tap table not given.") - new_tap_table["vkr_percent"] = new_tap_table["vkr_percent"] / item.GetAttribute("Snom_a") # pf_type.strn + new_tap_table["vkr_percent"] = new_tap_table["vkr_percent"] / item.GetAttribute("Snom_a") / 1000 * 100 + # * 1000 / 100 for conversion from MVA to kVA and from decimal to % if len(new_tap_table) == len(steps): new_tap_table['step'] = steps[:len(new_tap_table)] @@ -2510,7 +2511,8 @@ def create_trafo(net, item, export_controller=True, tap_opt="nntap", is_unbalanc else: raise ValueError("Measurement location for tap table not given.") - new_tap_table["vkr_percent"] = new_tap_table["vkr_percent"] / item.GetAttribute("Snom_a") # pf_type.strn + new_tap_table["vkr_percent"] = new_tap_table["vkr_percent"] / item.GetAttribute("Snom_a") / 1000 * 100 + # * 1000 / 100 for conversion from MVA to kVA and from decimal to % if len(new_tap_table) == len(steps): new_tap_table['step'] = steps[:len(new_tap_table)] @@ -2780,7 +2782,7 @@ def create_trafo3w(net, item, tap_opt='nntap'): new_tap_table["vkr_mv_percent"] = new_tap_table["vkr_mv_percent"] / ( np.min([float(snom_m_a), float(snom_l_a)]) * 1000) * 100 new_tap_table["vkr_lv_percent"] = new_tap_table["vkr_lv_percent"] / ( - np.min([float(snom_h_a), float(snom_m_a)]) * 1000) * 100 + np.min([float(snom_h_a), float(snom_l_a)]) * 1000) * 100 steps = list(range(tap_min, tap_max + 1)) diff --git a/pandapower/test/converter/test_from_powerfactory.py b/pandapower/test/converter/test_from_powerfactory.py index 02e3ca7b5..76c09c6ea 100644 --- a/pandapower/test/converter/test_from_powerfactory.py +++ b/pandapower/test/converter/test_from_powerfactory.py @@ -119,13 +119,23 @@ def test_pf_export_tap_changer(): app = pf.GetApplication() # import the tap changer test grid to powerfactory path = os.path.join(pp.pp_dir, 'test', 'converter', 'testfiles', 'test_tap_changer.pfd') - prj = import_project(path, app, 'TEST_PF_CONVERTER', import_folder='TEST_IMPORT', clear_import_folder=True) - prj_name = prj.GetFullName() + #prj = import_project(path, app, 'TEST_PF_CONVERTER', import_folder='TEST_IMPORT', clear_import_folder=True) + #prj_name = prj.GetFullName() - net = from_pfd(app, prj_name=prj_name) + #net = from_pfd(app, prj_name=prj_name) + net = from_pfd(app, prj_name="TEST_IMPORT\\test_tap_changer") all_diffs = validate_pf_conversion(net, tolerance_mva=1e-9) - tol = get_tol() + + tol = { + 'diff_vm': 5e-3, + 'diff_va': 0.1, + 'trafo_diff': 1e-2, + 'load_p_diff_is': 1e-5, + 'load_q_diff_is': 1e-5, + 'ext_grid_p_diff': 0.1, + 'ext_grid_q_diff': 0.1 + } for key, diff in all_diffs.items(): if type(diff) == pd.Series: From 80499f206d40fe88c53e13402717a9bc7f678a34 Mon Sep 17 00:00:00 2001 From: tfabian Date: Fri, 20 Dec 2024 15:14:20 +0100 Subject: [PATCH 099/125] test merge charactersitc --- .../test/toolbox/test_grid_modification.py | 50 +++++++++++-------- pandapower/toolbox/data_modification.py | 4 ++ 2 files changed, 32 insertions(+), 22 deletions(-) diff --git a/pandapower/test/toolbox/test_grid_modification.py b/pandapower/test/toolbox/test_grid_modification.py index ad6199aa7..ee094b0be 100644 --- a/pandapower/test/toolbox/test_grid_modification.py +++ b/pandapower/test/toolbox/test_grid_modification.py @@ -190,28 +190,34 @@ def test_merge_with_groups(): assert list(pp.group_element_index(net, 4, "line")) == list(np.array([1, 3], dtype=np.int64) + \ net1.line.shape[0]) -# commented out due to change in logic of characteristics -# def test_merge_with_characteristics(): -# from pandapower.networks.simple_pandapower_test_networks import simple_four_bus_system -# from pandapower.control.util.characteristic import Characteristic -# -# # create two networks -# net1 = simple_four_bus_system() -# net2 = simple_four_bus_system() -# -# # create two characteristic -# Characteristic(net1, x_values=[0.85, 1.15], y_values=[5, 15]) -# Characteristic(net2, x_values=[0.95, 1.05], y_values=[10, 20]) -# -# # assign the characteristic ids to the trafos -# net1.trafo.loc[:, "vk_percent_characteristic"] = 0 -# net2.trafo.loc[:, "vk_percent_characteristic"] = 0 -# -# # merge networks -# merged, lookup = pp.merge_nets(net1, net2, validate=False, return_net2_reindex_lookup=True) -# -# # The second transformer should have the second characteristic -# assert merged.trafo.loc[1, "vk_percent_characteristic"] == 1 +def test_merge_with_characteristics(): + from pandapower.networks.simple_pandapower_test_networks import simple_four_bus_system + from pandapower.control.util.characteristic import Characteristic + + # create two networks + net1 = simple_four_bus_system() + net2 = simple_four_bus_system() + + net1["trafo_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [1, 1, 1, 1, 1], + 'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [2, 3, 4, 5, 6], + 'vkr_percent': [1.323, 1.324, 1.325, 1.326, 1.327], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan, + 'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan}) + net2["trafo_characteristic_table"] = pd.DataFrame( + {'id_characteristic': [0, 0, 0, 0, 0], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [1, 1, 1, 1, 1], + 'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [2.1, 3.1, 4.1, 5.1, 6.1], + 'vkr_percent': [1.3, 1.4, 1.5, 1.6, 1.7], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan, + 'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan}) + + # merge networks + merged, lookup = pp.merge_nets(net1, net2, validate=False, return_net2_reindex_lookup=True) + + # The second transformer should have the second characteristic + result = merged.trafo_characteristic_table[ + (merged.trafo_characteristic_table["id_characteristic"] == 1) & + (merged.trafo_characteristic_table["step"] == 2) + ] + assert result["vkr_percent"].values[0] == 1.7 def test_merge_nets_with_custom_elements(): diff --git a/pandapower/toolbox/data_modification.py b/pandapower/toolbox/data_modification.py index b377a2bd7..f6013154a 100644 --- a/pandapower/toolbox/data_modification.py +++ b/pandapower/toolbox/data_modification.py @@ -331,6 +331,10 @@ def reindex_elements(net, element_type, new_indices=None, old_indices=None, look net[cost_df].loc[element_in_cost_df, "element"] = get_indices(net[cost_df].element[ element_in_cost_df], lookup) + # --- adapt tap_characteristic + if element_type == "trafo": + if "trafo_characteristic_table" in net and "id_characteristic" in net["trafo_characteristic_table"]: + net["trafo_characteristic_table"]["id_characteristic"] = net["trafo_characteristic_table"]["id_characteristic"].map(lookup) def create_continuous_elements_index(net, start=0, add_df_to_reindex=set()): """ From 77a775c3cf12590283210cd5f8aaaa56e498c120 Mon Sep 17 00:00:00 2001 From: Dominik Hilbrich Date: Fri, 20 Dec 2024 16:52:59 +0100 Subject: [PATCH 100/125] Added some warnings and improvements in build branch --- pandapower/build_branch.py | 44 +++++++++++++++++++++++++------------- 1 file changed, 29 insertions(+), 15 deletions(-) diff --git a/pandapower/build_branch.py b/pandapower/build_branch.py index 011d6417a..deb4b0ef6 100644 --- a/pandapower/build_branch.py +++ b/pandapower/build_branch.py @@ -453,9 +453,14 @@ def _calc_r_x_y_from_dataframe(net, trafo_df, vn_trafo_lv, vn_lv, ppc, sequence= mode = net["_options"]["mode"] trafo_model = net["_options"]["trafo_model"] if 'tap_dependency_table' in trafo_df: - r, x = _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net.sn_mva, + if 'trafo_characteristic_table' in net: + r, x = _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net.sn_mva, sequence=sequence, characteristic=net.get("characteristic"), - update_vk_values=update_vk_values, net=net) + update_vk_values=update_vk_values, trafo_characteristic_table=net.trafo_characteristic_table) + else: + r, x = _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net.sn_mva, + sequence=sequence, characteristic=net.get("characteristic"), + update_vk_values=update_vk_values) else: r, x = _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, net.sn_mva, sequence=sequence, characteristic=net.get("characteristic"), @@ -605,17 +610,21 @@ def _calc_tap_from_dataframe(net, trafo_df): # tap_phase_shift_type is only in dataframe starting from pp Version 3.0, older version use different logic tap_changer_type = get_trafo_values(trafo_df, f"tap{t}_changer_type") if f'tap{t}_dependency_table' in trafo_df: - tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") - tap_dependency = np.array( - [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency]) + tap_dependency_table = get_trafo_values(trafo_df, "tap_dependency_table") + tap_dependency_table = np.array( + [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency_table]) else: tap_table = np.array([False]) - tap_dependency = np.array([False]) + tap_dependency_table = np.array([False]) #tap_changer_type = pd.Series(tap_changer_type) - tap_table = np.logical_and(tap_dependency, np.logical_not(tap_changer_type == "None")) - tap_no_table = np.logical_and(~tap_dependency, np.logical_not(tap_changer_type == "None")) + tap_table = np.logical_and(tap_dependency_table, np.logical_not(tap_changer_type == "None")) + tap_no_table = np.logical_and(~tap_dependency_table, np.logical_not(tap_changer_type == "None")) if any(tap_table): id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") + if np.any(tap_dependency_table & pd.isna(id_characteristic_table)): + raise UserWarning( + "Trafo with tap_dependency_table True and id_characteristic_table NA detected.\n" + "Please set an id_characteristic_table or set tap_dependency_table to False.") for side, vn, direction in [("hv", vnh, 1), ("lv", vnl, -1)]: mask = tap_table & (side == tap_side) filter_df = pd.DataFrame({ @@ -713,7 +722,10 @@ def _get_vk_values_from_table(trafo_df, trafo_characteristic_table, trafotype="2 vk_value = get_trafo_values(trafo_df, vk_var) if any(tap_dependency_table): id_characteristic_table = get_trafo_values(trafo_df, "id_characteristic_table") - + if np.any(tap_dependency_table & pd.isna(id_characteristic_table)): + raise UserWarning( + "Trafo with tap_dependency_table True and id_characteristic_table NA detected.\n" + "Please set an id_characteristic_table or set tap_dependency_table to False.") mask = tap_dependency_table filter_df = pd.DataFrame({ 'id_characteristic': id_characteristic_table, @@ -809,7 +821,7 @@ def custom_func(f, t, c): def _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, sn_mva, sequence=1, characteristic=None, - update_vk_values=True, net=None): + update_vk_values=True, trafo_characteristic_table=None): """ Calculates (Vectorized) the resistance and reactance according to the transformer values @@ -817,11 +829,13 @@ def _calc_r_x_from_dataframe(mode, trafo_df, vn_lv, vn_trafo_lv, sn_mva, sequenc parallel = get_trafo_values(trafo_df, "parallel") if sequence == 1: if "tap_dependency_table" in trafo_df: - tap_dependency_table = get_trafo_values(trafo_df, "tap_dependency_table") - tap_dependency_table = np.array( - [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency_table]) - if any(tap_dependency_table) and not isinstance(trafo_df, dict): - vk_percent, vkr_percent = _get_vk_values_from_table(trafo_df, net.trafo_characteristic_table) + tap_dependency = get_trafo_values(trafo_df, "tap_dependency_table") + tap_dependency = np.array( + [False if isinstance(x, float) and np.isnan(x) else x for x in tap_dependency]) + if any(tap_dependency) and not isinstance(trafo_df, dict): + if np.any(tap_dependency) and trafo_characteristic_table is None: + raise UserWarning("Trafo with tap_dependency_table True, but no trafo_characteristic_table found.") + vk_percent, vkr_percent = _get_vk_values_from_table(trafo_df, trafo_characteristic_table) # update for 3W already in _calc_sc_voltages_of_equivalent_transformers else: vk_percent = get_trafo_values(trafo_df, "vk_percent") From f5722974c27693e7171b83a575ae2d5d9efac8e6 Mon Sep 17 00:00:00 2001 From: Panos Xenos Date: Fri, 20 Dec 2024 18:15:58 +0200 Subject: [PATCH 101/125] remove n/a tests --- pandapower/test/loadflow/test_results.py | 161 +---------------------- 1 file changed, 1 insertion(+), 160 deletions(-) diff --git a/pandapower/test/loadflow/test_results.py b/pandapower/test/loadflow/test_results.py index da7e1005e..5becddcd8 100644 --- a/pandapower/test/loadflow/test_results.py +++ b/pandapower/test/loadflow/test_results.py @@ -9,6 +9,7 @@ from numpy import isin, isnan, isclose import pandapower as pp +from pandapower.test import assert_res_equal from pandapower.test.consistency_checks import runpp_with_consistency_checks from pandapower.test.loadflow.result_test_network_generator import add_test_enforce_qlims, \ add_test_gen @@ -258,166 +259,6 @@ def test_trafo_2_taps(v_tol=1e-6, i_tol=1e-6, s_tol=1e-2, l_tol=1e-3, va_tol=1e- net.res_bus -# todo create new test for new tap_characteristic_table logic -# commented out due to new logic on characteristics -# def test_tap_dependent_impedance(result_test_network): -# net = result_test_network -# -# # first, basic example with piecewise linear characteristic -# characteristic_vk = pp.control.Characteristic.from_points( -# net, ((net.trafo.at[0, 'tap_min'], 0.9 * net.trafo.at[0, 'vk_percent']), -# (net.trafo.at[0, 'tap_neutral'], net.trafo.at[0, 'vk_percent']), -# (net.trafo.at[0, 'tap_max'], 1.1 * net.trafo.at[0, 'vk_percent']))) -# characteristic_vkr = pp.control.Characteristic.from_points( -# net, ((net.trafo.at[0, 'tap_min'], 0.9 * net.trafo.at[0, 'vkr_percent']), -# (net.trafo.at[0, 'tap_neutral'], net.trafo.at[0, 'vkr_percent']), -# (net.trafo.at[0, 'tap_max'], 1.1 * net.trafo.at[0, 'vkr_percent']))) -# idx_vk = characteristic_vk.index -# idx_vkr = characteristic_vkr.index -# -# # we use for reference -# net0 = net.deepcopy() -# -# net.trafo["tap_dependent_impedance"] = pd.Series(index=net.trafo.index, dtype=bool, data=False) -# net.trafo.loc[0, 'tap_dependent_impedance'] = True -# net.trafo.loc[0, ['vk_percent_characteristic', 'vkr_percent_characteristic']] = idx_vk, idx_vkr -# -# # first, make sure there is no change for neutral -# net.trafo.at[0, "tap_pos"] = net.trafo.tap_neutral.at[0] -# net0.trafo.at[0, "tap_pos"] = net.trafo.tap_neutral.at[0] -# pp.runpp(net) -# pp.runpp(net0) -# assert_res_equal(net, net0) -# -# -# # now check the min and max positions -# for pos, factor in (("tap_min", 0.9), ("tap_max", 1.1)): -# assert isclose(characteristic_vk(net.trafo[pos].at[0]), net.trafo.vk_percent.at[0]*factor, rtol=0, atol=1e-12) -# assert isclose(characteristic_vkr(net.trafo[pos].at[0]), net.trafo.vkr_percent.at[0]*factor, rtol=0, atol=1e-12) -# net0.trafo.at[0, "vk_percent"] = net.trafo.vk_percent.at[0]*factor -# net0.trafo.at[0, "vkr_percent"] = net.trafo.vkr_percent.at[0]*factor -# net0.trafo.at[0, "tap_pos"] = net.trafo[pos].at[0] -# pp.runpp(net0) -# net.trafo.at[0, "tap_pos"] = net.trafo[pos].at[0] -# pp.runpp(net) -# assert_res_equal(net, net0) -# -# -# commented out due to new logic on characteristics -# def test_tap_dependent_impedance_controller_comparison(): -# net1 = create_net() -# net2 = create_net() -# -# pp.control.create_trafo_characteristics(net1, 'trafo', [0], 'vk_percent', [[-2, -1, 0, 1, 2]], [[5, 5.2, 6, 6.8, 7]]) -# pp.control.create_trafo_characteristics(net1, 'trafo', [0], 'vkr_percent', [[-2, -1, 0, 1, 2]], [[1.3, 1.4, 1.44, 1.5, 1.6]]) -# -# pp.control.SplineCharacteristic(net2, [-2, -1, 0, 1, 2], [5, 5.2, 6, 6.8, 7]) -# pp.control.SplineCharacteristic(net2, [-2, -1, 0, 1, 2], [1.3, 1.4, 1.44, 1.5, 1.6]) -# pp.control.TapDependentImpedance(net2, [0], 0, output_variable="vk_percent") -# pp.control.TapDependentImpedance(net2, [0], 1, output_variable="vkr_percent") -# -# pp.runpp(net1) -# pp.runpp(net2, run_control=True) -# -# assert_res_equal(net1, net2) -# -# -# commented out due to new logic on characteristics -# def test_tap_dependent_impedance_controller_comparison_3w(): -# net1 = create_net() -# net2 = create_net() -# for i in range(2): -# add_trafo_connection(net1, net1.trafo.at[0, 'hv_bus'], "3W") -# add_trafo_connection(net2, net2.trafo.at[0, 'hv_bus'], "3W") -# -# pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vk_hv_percent', [[-2, -1, 0, 1, 2]], [[0.85, 0.9, 1, 1.1, 1.15]]) -# pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vkr_hv_percent', [[-2, -1, 0, 1, 2]], [[0.27, 0.28, 0.3, 0.32, 0.33]]) -# pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vk_mv_percent', [[-2, -1, 0, 1, 2]], [[0.85, 0.9, 1, 1.1, 1.15]]) -# pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vkr_mv_percent', [[-2, -1, 0, 1, 2]], [[0.27, 0.28, 0.3, 0.32, 0.33]]) -# pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vk_lv_percent', [[-2, -1, 0, 1, 2]], [[0.85, 0.9, 1, 1.1, 1.15]]) -# pp.control.create_trafo_characteristics(net1, 'trafo3w', [0], 'vkr_lv_percent', [[-2, -1, 0, 1, 2]], [[0.27, 0.28, 0.3, 0.32, 0.33]]) -# -# pp.control.SplineCharacteristic(net2, [-2, -1, 0, 1, 2], [0.85, 0.9, 1, 1.1, 1.15]) -# pp.control.SplineCharacteristic(net2, [-2, -1, 0, 1, 2], [0.27, 0.28, 0.3, 0.32, 0.33]) -# -# pp.control.TapDependentImpedance(net2, [0], 0, element="trafo3w", output_variable="vk_hv_percent") -# pp.control.TapDependentImpedance(net2, [0], 1, element="trafo3w", output_variable="vkr_hv_percent") -# pp.control.TapDependentImpedance(net2, [0], 0, element="trafo3w", output_variable="vk_mv_percent") -# pp.control.TapDependentImpedance(net2, [0], 1, element="trafo3w", output_variable="vkr_mv_percent") -# pp.control.TapDependentImpedance(net2, [0], 0, element="trafo3w", output_variable="vk_lv_percent") -# pp.control.TapDependentImpedance(net2, [0], 1, element="trafo3w", output_variable="vkr_lv_percent") -# -# pp.runpp(net1) -# pp.runpp(net2, run_control=True) -# -# assert_res_equal(net1, net2) - - -# commented out due to new logic on characteristics -# def test_undefined_tap_dependent_impedance_characteristics(): -# # if some characteristic per 1 trafo are undefined, but at least 1 is defined -> OK -# # if all characteristic per 1 trafo are undefined -> raise error -# net = create_net() -# pp.control.create_trafo_characteristics(net, 'trafo', [0], 'vk_percent', [[-2, -1, 0, 1, 2]], [[5, 5.2, 6, 6.8, 7]]) -# pp.control.create_trafo_characteristics(net, 'trafo', [0], 'vkr_percent', [[-2, -1, 0, 1, 2]], [[1.3, 1.4, 1.44, 1.5, 1.6]]) -# pp.control.create_trafo_characteristics(net, 'trafo', [1], 'vk_percent', [[-2, -1, 0, 1, 2]], [[5, 5.2, 6, 6.8, 7]]) -# -# # does not raise error -# pp.runpp(net) -# -# # this will raise error -# net.trafo.at[1, "vk_percent_characteristic"] = None -# with pytest.raises(UserWarning): -# pp.runpp(net) - - -# commented out due to new logic on characteristics -# def test_undefined_tap_dependent_impedance_characteristics_trafo3w(): -# # if some characteristic per 1 trafo are undefined, but at least 1 is defined -> OK -# # if all characteristic per 1 trafo are undefined -> raise error -# net = create_net() -# add_trafo_connection(net, 1, "3W") -# add_trafo_connection(net, 1, "3W") -# net2 = create_net() -# add_trafo_connection(net2, 1, "3W") -# add_trafo_connection(net2, 1, "3W") -# -# pp.control.create_trafo_characteristics( -# net, 'trafo3w', [0, 1], 'vk_mv_percent', [[-2, -1, 0, 1, 2], [-2, -1, 0, 1, 2]], -# [[0.7, 0.9, 1, 1.1, 1.3], [0.7, 0.9, 1, 1.1, 1.3]]) -# pp.control.create_trafo_characteristics( -# net, 'trafo3w', [0, 1], 'vkr_mv_percent', [[-2, -1, 0, 1, 2], [-2, -1, 0, 1, 2]], -# [[0.3, 0.45, 0.5, 0.55, 0.7], [0.3, 0.45, 0.5, 0.55, 0.7]]) -# -# pp.control.Characteristic(net2, [-2, -1, 0, 1, 2], [0.7, 0.9, 1, 1.1, 1.3]) -# pp.control.Characteristic(net2, [-2, -1, 0, 1, 2], [0.3, 0.45, 0.5, 0.55, 0.7]) -# -# pp.control.TapDependentImpedance(net2, [0], 0, element="trafo3w", output_variable="vk_mv_percent") -# pp.control.TapDependentImpedance(net2, [0], 1, element="trafo3w", output_variable="vkr_mv_percent") -# pp.control.TapDependentImpedance(net2, [1], 0, element="trafo3w", output_variable="vk_mv_percent") -# pp.control.TapDependentImpedance(net2, [1], 1, element="trafo3w", output_variable="vkr_mv_percent") -# -# pp.runpp(net) -# pp.runpp(net2, run_control=True) -# assert_res_equal(net, net2) -# -# net.trafo3w.at[0, "vk_mv_percent_characteristic"] = None -# pp.runpp(net) -# net2.controller.at[0, "in_service"] = False -# pp.runpp(net2, run_control=True) -# assert_res_equal(net, net2) -# -# net.trafo3w.at[0, "vkr_mv_percent_characteristic"] = None -# net2.controller.at[1, "in_service"] = False -# with pytest.raises(UserWarning): -# pp.runpp(net) -# -# net.trafo3w.at[0, "tap_dependent_impedance"] = False -# pp.runpp(net) -# pp.runpp(net2, run_control=True) -# assert_res_equal(net, net2) - - def test_ext_grid(result_test_network, v_tol=1e-6, va_tol=1e-2, i_tol=1e-6, s_tol=5e-3, l_tol=1e-3): net = result_test_network runpp_with_consistency_checks(net, calculate_voltage_angles=True) From 4d07b7c4af83723b0b074747c696d87a5591722c Mon Sep 17 00:00:00 2001 From: Ghanshyam Malaviya Date: Fri, 20 Dec 2024 18:04:30 +0100 Subject: [PATCH 102/125] FIX: Tap dependent impedance of transformers tutorial test --- tutorials/tap_dependent_impedance.ipynb | 1717 +++++++++++------------ 1 file changed, 800 insertions(+), 917 deletions(-) diff --git a/tutorials/tap_dependent_impedance.ipynb b/tutorials/tap_dependent_impedance.ipynb index 2f026a2f0..44a8a3e1c 100644 --- a/tutorials/tap_dependent_impedance.ipynb +++ b/tutorials/tap_dependent_impedance.ipynb @@ -16,22 +16,30 @@ }, { "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T16:55:18.742894Z", + "start_time": "2024-12-20T16:55:17.109029Z" + } + }, "source": [ "import numpy as np\n", "import pandas as pd\n", "import pandapower as pp\n", "import pandapower.control\n", "import json" - ] + ], + "outputs": [], + "execution_count": 1 }, { "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T16:55:30.591839Z", + "start_time": "2024-12-20T16:55:30.580595Z" + } + }, "source": [ "def add_trafo_connection(net, hv_bus, element_type=\"trafo\"):\n", " cb = pp.create_bus(net, vn_kv=0.4)\n", @@ -49,7 +57,6 @@ " tap_step_percent=1., tap_min=-2, tap_max=2)\n", " else:\n", " pp.create_transformer(net, hv_bus=hv_bus, lv_bus=cb, std_type=\"0.25 MVA 20/0.4 kV\", tap_pos=2)\n", - " \n", "\n", "def create_net():\n", " net = pp.create_empty_network()\n", @@ -61,18 +68,65 @@ " c_nf_per_km=300, max_i_ka=.2, df=.8)\n", " for i in range(2):\n", " add_trafo_connection(net, b2)\n", - " \n", + " net.trafo.loc[i, \"id_characteristic_table\"] = i\n", + " net.trafo.loc[i,\"tap_dependency_table\"] = True\n", + "\n", + " net['trafo_characteristic_table'] = pd.DataFrame(\n", + " columns=['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent',\n", + " 'vkr_percent', 'vkr_hv_percent', 'vkr_mv_percent',\n", + " 'vkr_lv_percent', 'vk_hv_percent', 'vk_mv_percent',\n", + " 'vk_lv_percent'])\n", + " trafo_data = {\n", + " 'id_characteristic': [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n", + " 'step': [-2, -1, 0, 1, 2, -2, -1, 0, 1, 2],\n", + " 'voltage_ratio': [0.95, 0.97, 1.0, 1.03, 1.05, 0.95, 0.97, 1.0, 1.03, 1.05],\n", + " 'angle_deg': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n", + " 'vk_percent': [5, 5.2, 6, 6.8, 7, 5, 5.2, 6, 6.8, 7],\n", + " 'vkr_percent': [1.3, 1.4, 1.44, 1.5, 1.6, 1.3, 1.4, 1.44, 1.5, 1.6],\n", + " 'vkr_hv_percent': np.nan,\n", + " 'vkr_mv_percent': np.nan,\n", + " 'vkr_lv_percent': np.nan,\n", + " 'vk_hv_percent': np.nan,\n", + " 'vk_mv_percent': np.nan,\n", + " 'vk_lv_percent': np.nan\n", + " }\n", + "\n", + " net['trafo_characteristic_table'] = pd.DataFrame(trafo_data)\n", + "\n", + " trafo3w_data = {\n", + " 'id_characteristic': [2, 2, 2, 2, 2, 3, 3, 3, 3, 3],\n", + " 'step': [-2, -1, 0, 1, 2, -2, -1, 0, 1, 2],\n", + " 'voltage_ratio': [0.95, 0.97, 1.0, 1.03, 1.05, 0.95, 0.97, 1.0, 1.03, 1.05],\n", + " 'angle_deg': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n", + " 'vk_percent': [5, 5.2, 6, 6.8, 7, 5, 5.2, 6, 6.8, 7],\n", + " 'vkr_percent': [1.3, 1.4, 1.44, 1.5, 1.6, 1.3, 1.4, 1.44, 1.5, 1.6],\n", + " 'vkr_hv_percent': [0.27, 0.28, 0.3, 0.32, 0.33, 0.27, 0.28, 0.3, 0.32, 0.33],\n", + " 'vkr_mv_percent': [0.27, 0.28, 0.3, 0.32, 0.33, 0.27, 0.28, 0.3, 0.32, 0.33],\n", + " 'vkr_lv_percent': [0.27, 0.28, 0.3, 0.32, 0.33, 0.27, 0.28, 0.3, 0.32, 0.33],\n", + " 'vk_hv_percent': [0.85, 0.9, 1, 1.1, 1.15, 0.85, 0.9, 1, 1.1, 1.15],\n", + " 'vk_mv_percent': [0.85, 0.9, 1, 1.1, 1.15, 0.85, 0.9, 1, 1.1, 1.15],\n", + " 'vk_lv_percent': [0.85, 0.9, 1, 1.1, 1.15, 0.85, 0.9, 1, 1.1, 1.15],\n", + " }\n", + " data_frame = pd.DataFrame(trafo3w_data)\n", + " net['trafo_characteristic_table'] = pd.concat([net['trafo_characteristic_table'], data_frame], sort=False)\n", " return net" - ] + ], + "outputs": [], + "execution_count": 2 }, { "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T16:55:35.201848Z", + "start_time": "2024-12-20T16:55:35.158775Z" + } + }, "source": [ "net = create_net()" - ] + ], + "outputs": [], + "execution_count": 3 }, { "cell_type": "markdown", @@ -81,18 +135,6 @@ "We can either create the characteristics by creating the objects for characteristics and setting their index to the respective columns. Alternatively, we can use a convenience function to create set up the characteristics for vk_percent and vkr_percent. The function can be applied to a single index or for multiple transformers at a time. The imput parameters must have a correct shape:" ] }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "pp.control.create_trafo_characteristics(net, 'trafo', 0, 'vk_percent', \n", - " [-2, -1, 0, 1, 2], [5, 5.2, 6, 6.8, 7]) # single mode\n", - "pp.control.create_trafo_characteristics(net, 'trafo', [0], 'vkr_percent', \n", - " [[-2, -1, 0, 1, 2]], [[1.3, 1.4, 1.44, 1.5, 1.6]]) # multiple indices" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -102,54 +144,90 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T16:55:38.923570Z", + "start_time": "2024-12-20T16:55:38.910478Z" + } + }, + "source": "pp.control.create_trafo_characteristic_object(net)", + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\gjmal\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\control\\util\\auxiliary.py:263: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n", + " net[\"trafo_characteristic_spline\"] = net[\"trafo_characteristic_spline_temp\"].applymap(\n" + ] + } + ], + "execution_count": 4 + }, + { + "cell_type": "code", + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T16:55:41.018233Z", + "start_time": "2024-12-20T16:55:40.926357Z" + } + }, + "source": [ + "pp.control.plot_characteristic(net[\"trafo_characteristic_spline\"][\"vk_percent_characteristic\"].loc[0], -2, 2,\n", + " xlabel='Tap position \"tap_pos\"', ylabel='Value of \"vk_percent\"')" + ], "outputs": [ { "data": { - "image/png": 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", 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" }, "metadata": {}, "output_type": "display_data" } ], - "source": [ - "pp.control.plot_characteristic(net.characteristic.object.at[0], -2, 2, \n", - " xlabel='Tap position \"tap_pos\"', ylabel='Value of \"vk_percent\"')" - ] + "execution_count": 5 }, { "cell_type": "code", - "execution_count": 6, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T16:55:44.014472Z", + "start_time": "2024-12-20T16:55:43.946364Z" + } + }, + "source": [ + "pp.control.plot_characteristic(net[\"trafo_characteristic_spline\"][\"vkr_percent_characteristic\"].loc[0], -2, 2,\n", + " xlabel='Tap position \"tap_pos\"', ylabel='Value of \"vkr_percent\"')" + ], "outputs": [ { "data": { - "image/png": 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", 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Use DataFrame.map instead.\n", + " net[\"trafo_characteristic_spline\"] = net[\"trafo_characteristic_spline_temp\"].applymap(\n" + ] } ], - "source": [ - "pp.control.create_trafo_characteristics(net4, 'trafo3w', [0], 'vk_hv_percent', \n", - " [[-2, -1, 0, 1, 2]], [[0.85, 0.9, 1, 1.1, 1.15]])\n", - "\n", - "pp.control.create_trafo_characteristics(net4, 'trafo3w', [0], 'vkr_hv_percent', \n", - " [[-2, -1, 0, 1, 2]], [[0.27, 0.28, 0.3, 0.32, 0.33]])\n", - "\n", - "pp.control.create_trafo_characteristics(net4, 'trafo3w', [0], 'vk_mv_percent', \n", - " [[-2, -1, 0, 1, 2]], [[0.85, 0.9, 1, 1.1, 1.15]])\n", - "\n", - "pp.control.create_trafo_characteristics(net4, 'trafo3w', [0], 'vkr_mv_percent', \n", - " [[-2, -1, 0, 1, 2]], [[0.27, 0.28, 0.3, 0.32, 0.33]])\n", - "\n", - "pp.control.create_trafo_characteristics(net4, 'trafo3w', [0], 'vk_lv_percent', \n", - " [[-2, -1, 0, 1, 2]], [[0.85, 0.9, 1, 1.1, 1.15]])\n", - "\n", - "pp.control.create_trafo_characteristics(net4, 'trafo3w', [0], 'vkr_lv_percent', \n", - " [[-2, -1, 0, 1, 2]], [[0.27, 0.28, 0.3, 0.32, 0.33]])\n", - "\n", - "net4.characteristic" - ] + "execution_count": 17 }, { "cell_type": "code", - "execution_count": 18, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T16:57:28.333289Z", + "start_time": "2024-12-20T16:57:28.322506Z" + } + }, + "source": [ + "pp.control.SplineCharacteristic(net5, [-2, -1, 0, 1, 2], [0.85, 0.9, 1, 1.1, 1.15])\n", + "pp.control.SplineCharacteristic(net5, [-2, -1, 0, 1, 2], [0.27, 0.28, 0.3, 0.32, 0.33])" + ], "outputs": [ { "data": { @@ -553,15 +614,24 @@ "output_type": "execute_result" } ], - "source": [ - "pp.control.SplineCharacteristic(net5, [-2, -1, 0, 1, 2], [0.85, 0.9, 1, 1.1, 1.15])\n", - "pp.control.SplineCharacteristic(net5, [-2, -1, 0, 1, 2], [0.27, 0.28, 0.3, 0.32, 0.33])" - ] + "execution_count": 18 }, { "cell_type": "code", - "execution_count": 19, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T16:57:31.288425Z", + "start_time": "2024-12-20T16:57:31.271529Z" + } + }, + "source": [ + "pp.control.TapDependentImpedance(net5, [0], 0, output_variable=\"vk_hv_percent\", element=\"trafo3w\")\n", + "pp.control.TapDependentImpedance(net5, [0], 1, output_variable=\"vkr_hv_percent\", element=\"trafo3w\")\n", + "pp.control.TapDependentImpedance(net5, [0], 0, output_variable=\"vk_mv_percent\", element=\"trafo3w\")\n", + "pp.control.TapDependentImpedance(net5, [0], 1, output_variable=\"vkr_mv_percent\", element=\"trafo3w\")\n", + "pp.control.TapDependentImpedance(net5, [0], 0, output_variable=\"vk_lv_percent\", element=\"trafo3w\")\n", + "pp.control.TapDependentImpedance(net5, [0], 1, output_variable=\"vkr_lv_percent\", element=\"trafo3w\")" + ], "outputs": [ { "data": { @@ -577,56 +647,80 @@ "output_type": "execute_result" } ], - "source": [ - "pp.control.TapDependentImpedance(net5, [0], 0, output_variable=\"vk_hv_percent\", element=\"trafo3w\")\n", - "pp.control.TapDependentImpedance(net5, [0], 1, output_variable=\"vkr_hv_percent\", element=\"trafo3w\")\n", - "pp.control.TapDependentImpedance(net5, [0], 0, output_variable=\"vk_mv_percent\", element=\"trafo3w\")\n", - "pp.control.TapDependentImpedance(net5, [0], 1, output_variable=\"vkr_mv_percent\", element=\"trafo3w\")\n", - "pp.control.TapDependentImpedance(net5, [0], 0, output_variable=\"vk_lv_percent\", element=\"trafo3w\")\n", - "pp.control.TapDependentImpedance(net5, [0], 1, output_variable=\"vkr_lv_percent\", element=\"trafo3w\")" - ] + "execution_count": 19 }, { "cell_type": "code", - "execution_count": 20, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T16:57:36.623419Z", + "start_time": "2024-12-20T16:57:34.396418Z" + } + }, + "source": [ + "%timeit pp.runpp(net4)" + ], "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "14.2 ms ± 81 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" + "27.1 ms ± 849 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] } ], - "source": [ - "%timeit pp.runpp(net4)" - ] + "execution_count": 20 }, { "cell_type": "code", - "execution_count": 21, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T16:57:42.071823Z", + "start_time": "2024-12-20T16:57:38.363387Z" + } + }, + "source": [ + "%timeit pp.runpp(net5, run_control=True)" + ], "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "46.2 ms ± 497 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + "45.3 ms ± 653 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] } ], - "source": [ - "%timeit pp.runpp(net5, run_control=True)" - ] + "execution_count": 21 }, { "cell_type": "code", - "execution_count": 22, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T16:57:45.897147Z", + "start_time": "2024-12-20T16:57:45.884994Z" + } + }, + "source": [ + "assert np.allclose(net4.res_bus.vm_pu, net5.res_bus.vm_pu, atol=1e-6, rtol=0)\n", + "assert np.allclose(net4.res_bus.va_degree, net5.res_bus.va_degree, atol=1e-6, rtol=0)\n", + "pd.merge(net4.res_bus[[\"vm_pu\", \"va_degree\"]], net5.res_bus[[\"vm_pu\", \"va_degree\"]], \n", + " left_index=True, right_index=True)" + ], "outputs": [ { "data": { + "text/plain": [ + " vm_pu_x va_degree_x vm_pu_y va_degree_y\n", + "0 1.010000 0.000000 1.010000 0.000000\n", + "1 1.007329 -0.199678 1.007329 -0.199678\n", + "2 0.929303 -153.505686 0.929303 -153.505686\n", + "3 0.929303 -153.505686 0.929303 -153.505686\n", + "4 1.129082 -0.545199 1.129082 -0.545199\n", + "5 1.004785 -0.428464 1.004785 -0.428464\n", + "6 1.129548 -0.497491 1.129548 -0.497491\n", + "7 1.005072 -0.396841 1.005072 -0.396841" + ], "text/html": [ "
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namestd_typehv_buslv_bussn_mvavn_hv_kvvn_lv_kvvk_percentvkr_percentpfe_kwi0_percentshift_degreetap_sidetap_neutraltap_mintap_maxtap_step_percenttap_step_degreetap_postap_phase_shifterparalleldfin_servicetap_dependent_impedancevk_percent_characteristicvkr_percent_characteristic
0None0.25 MVA 20/0.4 kV120.2520.00.46.0000011.440.80.32150.0hv0-222.50.02False11.0TrueTrue01
1None0.25 MVA 20/0.4 kV130.2520.00.46.0000001.440.80.32150.0hv0-222.50.02False11.0TrueFalse<NA><NA>
2None0.25 MVA 20/0.4 kV120.2520.00.46.0000001.440.80.32150.0hv0-222.50.02False11.0TrueTrue<NA><NA>
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" - ], - "text/plain": [ - " name std_type hv_bus lv_bus sn_mva vn_hv_kv vn_lv_kv \\\n", - "0 None 0.25 MVA 20/0.4 kV 1 2 0.25 20.0 0.4 \n", - "1 None 0.25 MVA 20/0.4 kV 1 3 0.25 20.0 0.4 \n", - "2 None 0.25 MVA 20/0.4 kV 1 2 0.25 20.0 0.4 \n", - "\n", - " vk_percent vkr_percent pfe_kw i0_percent shift_degree tap_side \\\n", - "0 6.000001 1.44 0.8 0.32 150.0 hv \n", - "1 6.000000 1.44 0.8 0.32 150.0 hv \n", - "2 6.000000 1.44 0.8 0.32 150.0 hv \n", - "\n", - " tap_neutral tap_min tap_max tap_step_percent tap_step_degree tap_pos \\\n", - "0 0 -2 2 2.5 0.0 2 \n", - "1 0 -2 2 2.5 0.0 2 \n", - "2 0 -2 2 2.5 0.0 2 \n", - "\n", - " tap_phase_shifter parallel df in_service tap_dependent_impedance \\\n", - "0 False 1 1.0 True True \n", - "1 False 1 1.0 True False \n", - "2 False 1 1.0 True True \n", - "\n", - " vk_percent_characteristic vkr_percent_characteristic \n", - "0 0 1 \n", - "1 \n", - "2 " - ] - }, - "metadata": {}, - "output_type": "display_data" + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\gjmal\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\control\\util\\diagnostic.py:89: UserWarning: trafo: found 1 transformer(s) with not both tap_dependency_table and id_characteristic_table parameters populated. Power flow calculation will raise an error.\n", + " warnings.warn(f\"{trafo_table}: found {mismatch_a} transformer(s) with not both \"\n" + ] }, { "data": { - "text/html": [ - "
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namestd_typehv_busmv_buslv_bussn_hv_mvasn_mv_mvasn_lv_mvavn_hv_kvvn_mv_kvvn_lv_kvvk_hv_percentvk_mv_percentvk_lv_percentvkr_hv_percentvkr_mv_percentvkr_lv_percentpfe_kwi0_percentshift_mv_degreeshift_lv_degreetap_sidetap_neutraltap_mintap_maxtap_step_percenttap_step_degreetap_postap_at_star_pointin_servicevk0_hv_percentvk0_mv_percentvk0_lv_percentvkr0_hv_percentvkr0_mv_percentvkr0_lv_percentvector_grouptap_dependent_impedance
0NoneNone1540.60.50.420.00.90.451.01.01.00.30.30.30.20.30.00.0None0-221.0NaN2FalseTrueNaNNaNNaNNaNNaNNaNNoneTrue
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" - ], "text/plain": [ - " name std_type hv_bus mv_bus lv_bus sn_hv_mva sn_mv_mva sn_lv_mva \\\n", - "0 None None 1 5 4 0.6 0.5 0.4 \n", - "\n", - " vn_hv_kv vn_mv_kv vn_lv_kv vk_hv_percent vk_mv_percent vk_lv_percent \\\n", - "0 20.0 0.9 0.45 1.0 1.0 1.0 \n", - "\n", - " vkr_hv_percent vkr_mv_percent vkr_lv_percent pfe_kw i0_percent \\\n", - "0 0.3 0.3 0.3 0.2 0.3 \n", - "\n", - " shift_mv_degree shift_lv_degree tap_side tap_neutral tap_min tap_max \\\n", - "0 0.0 0.0 None 0 -2 2 \n", - "\n", - " tap_step_percent tap_step_degree tap_pos tap_at_star_point in_service \\\n", - "0 1.0 NaN 2 False True \n", - "\n", - " vk0_hv_percent vk0_mv_percent vk0_lv_percent vkr0_hv_percent \\\n", - "0 NaN NaN NaN NaN \n", - "\n", - " vkr0_mv_percent vkr0_lv_percent vector_group tap_dependent_impedance \n", - "0 NaN NaN None True " + "False" ] }, + "execution_count": 37, "metadata": {}, - "output_type": "display_data" - }, + "output_type": "execute_result" + } + ], + "execution_count": 37 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T16:58:47.875913Z", + "start_time": "2024-12-20T16:58:47.864883Z" + } + }, + "cell_type": "code", + "source": [ + "net_diagnostics.trafo.loc[0, \"id_characteristic_table\"] = 0\n", + "net_diagnostics.trafo.loc[0, \"tap_changer_type\"] = None\n", + "pp.control.util.diagnostic.trafo_characteristic_table_diagnostic(net_diagnostics)\n", + "#UserWarning: trafo: found 1 transformer(s) with tap_dependency_table set to True and tap_changer_type parameter not populated. The characteristics from trafo_characteristic_table will not be considered.\n", + " # warnings.warn(f\"{trafo_table}: found {mismatch_b} transformer(s) with tap_dependency_table set to \"" + ], + "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "hp.pandapower.control.util.diagnostic - INFO: Checking transformer characteristics\n", - "hp.pandapower.control.util.diagnostic - INFO: trafo: found 2 transformer(s) with tap-dependent impedance\n", - "hp.pandapower.control.util.diagnostic - WARNING: Some transformers in trafo table have tap_dependent_impedance set to True, but no defined characteristics. Power flow calculation will raise an error.\n", - "hp.pandapower.control.util.diagnostic - INFO: trafo: vk_percent_characteristic is missing for some transformers\n", - "hp.pandapower.control.util.diagnostic - WARNING: The characteristic value of 6.0 at the neutral tap position 0 does not match the value 6.000001 of vk_percent for the trafo with index 0 (deviation of -1.000000000139778e-06)\n", - "hp.pandapower.control.util.diagnostic - INFO: trafo: vkr_percent_characteristic is missing for some transformers\n", - "hp.pandapower.control.util.diagnostic - INFO: trafo3w: found 1 transformer(s) with tap-dependent impedance\n", - "hp.pandapower.control.util.diagnostic - WARNING: No columns defined for transformer tap characteristics in trafo3w. Power flow calculation will raise an error.\n", - "hp.pandapower.control.util.diagnostic - INFO: trafo3w: vk_hv_percent_characteristic is missing\n", - "hp.pandapower.control.util.diagnostic - INFO: trafo3w: vkr_hv_percent_characteristic is missing\n", - "hp.pandapower.control.util.diagnostic - INFO: trafo3w: vk_mv_percent_characteristic is missing\n", - "hp.pandapower.control.util.diagnostic - INFO: trafo3w: vkr_mv_percent_characteristic is missing\n", - "hp.pandapower.control.util.diagnostic - INFO: trafo3w: vk_lv_percent_characteristic is missing\n", - "hp.pandapower.control.util.diagnostic - INFO: trafo3w: vkr_lv_percent_characteristic is missing\n" + "C:\\Users\\gjmal\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\control\\util\\diagnostic.py:98: UserWarning: trafo: found 1 transformer(s) with tap_dependency_table set to True and tap_changer_type parameter not populated. The characteristics from trafo_characteristic_table will not be considered.\n", + " warnings.warn(f\"{trafo_table}: found {mismatch_b} transformer(s) with tap_dependency_table set to \"\n" ] + }, + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" } ], - "source": [ - "# let's make some invalid configurations\n", - "# missing any characteristic\n", - "pp.create_transformer(net, hv_bus=net.trafo.at[0, 'hv_bus'], \n", - " lv_bus=net.trafo.at[0, 'lv_bus'], std_type=\"0.25 MVA 20/0.4 kV\", tap_pos=2, \n", - " tap_dependent_impedance=True)\n", - "net.trafo.at[0, \"vk_percent\"] += 1e-6\n", - "add_trafo_connection(net, net.trafo.at[0, 'hv_bus'], \"trafo3w\")\n", - "# missing columns for characteristics\n", - "net.trafo3w['tap_dependent_impedance'] = True\n", - "\n", - "display(net.trafo)\n", - "display(net.trafo3w)\n", - "\n", - "# diagnostic\n", - "pp.control.trafo_characteristics_diagnostic(net)" - ] + "execution_count": 38 } ], "metadata": { "kernelspec": { - "display_name": "Python 3.10.11 ('base')", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1985,7 +1868,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.11" + "version": "3.11.8" }, "vscode": { "interpreter": { From b3864df5ea48cac4452f0b1f6d128cb30dde39d4 Mon Sep 17 00:00:00 2001 From: Ghanshyam Malaviya Date: Fri, 20 Dec 2024 19:00:09 +0100 Subject: [PATCH 103/125] FIX: Tap dependent impedance of transformers tutorial test --- tutorials/tap_dependent_impedance.ipynb | 843 ++++++++++++++++++------ 1 file changed, 653 insertions(+), 190 deletions(-) diff --git a/tutorials/tap_dependent_impedance.ipynb b/tutorials/tap_dependent_impedance.ipynb index 44a8a3e1c..d8c3fc62a 100644 --- a/tutorials/tap_dependent_impedance.ipynb +++ b/tutorials/tap_dependent_impedance.ipynb @@ -18,8 +18,8 @@ "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:55:18.742894Z", - "start_time": "2024-12-20T16:55:17.109029Z" + "end_time": "2024-12-20T17:26:30.555390Z", + "start_time": "2024-12-20T17:26:30.549364Z" } }, "source": [ @@ -30,14 +30,14 @@ "import json" ], "outputs": [], - "execution_count": 1 + "execution_count": 3 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:55:30.591839Z", - "start_time": "2024-12-20T16:55:30.580595Z" + "end_time": "2024-12-20T17:27:16.655445Z", + "start_time": "2024-12-20T17:27:16.629600Z" } }, "source": [ @@ -98,8 +98,8 @@ " 'step': [-2, -1, 0, 1, 2, -2, -1, 0, 1, 2],\n", " 'voltage_ratio': [0.95, 0.97, 1.0, 1.03, 1.05, 0.95, 0.97, 1.0, 1.03, 1.05],\n", " 'angle_deg': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n", - " 'vk_percent': [5, 5.2, 6, 6.8, 7, 5, 5.2, 6, 6.8, 7],\n", - " 'vkr_percent': [1.3, 1.4, 1.44, 1.5, 1.6, 1.3, 1.4, 1.44, 1.5, 1.6],\n", + " 'vk_percent': np.nan,\n", + " 'vkr_percent': np.nan,\n", " 'vkr_hv_percent': [0.27, 0.28, 0.3, 0.32, 0.33, 0.27, 0.28, 0.3, 0.32, 0.33],\n", " 'vkr_mv_percent': [0.27, 0.28, 0.3, 0.32, 0.33, 0.27, 0.28, 0.3, 0.32, 0.33],\n", " 'vkr_lv_percent': [0.27, 0.28, 0.3, 0.32, 0.33, 0.27, 0.28, 0.3, 0.32, 0.33],\n", @@ -112,21 +112,432 @@ " return net" ], "outputs": [], - "execution_count": 2 + "execution_count": 4 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:55:35.201848Z", - "start_time": "2024-12-20T16:55:35.158775Z" + "end_time": "2024-12-20T17:28:09.231909Z", + "start_time": "2024-12-20T17:28:09.117435Z" } }, - "source": [ - "net = create_net()" + "source": "net = create_net()", + "outputs": [ + { + "data": { + "text/plain": [ + " id_characteristic step voltage_ratio angle_deg vk_percent vkr_percent \\\n", + "0 0 -2 0.95 0 5.0 1.30 \n", + "1 0 -1 0.97 0 5.2 1.40 \n", + "2 0 0 1.00 0 6.0 1.44 \n", + "3 0 1 1.03 0 6.8 1.50 \n", + "4 0 2 1.05 0 7.0 1.60 \n", + "5 1 -2 0.95 0 5.0 1.30 \n", + "6 1 -1 0.97 0 5.2 1.40 \n", + "7 1 0 1.00 0 6.0 1.44 \n", + "8 1 1 1.03 0 6.8 1.50 \n", + "9 1 2 1.05 0 7.0 1.60 \n", + "0 2 -2 0.95 0 NaN NaN \n", + "1 2 -1 0.97 0 NaN NaN \n", + "2 2 0 1.00 0 NaN NaN \n", + "3 2 1 1.03 0 NaN NaN \n", + "4 2 2 1.05 0 NaN NaN \n", + "5 3 -2 0.95 0 NaN NaN \n", + "6 3 -1 0.97 0 NaN NaN \n", + "7 3 0 1.00 0 NaN NaN \n", + "8 3 1 1.03 0 NaN NaN \n", + "9 3 2 1.05 0 NaN NaN \n", + "\n", + " vkr_hv_percent vkr_mv_percent vkr_lv_percent vk_hv_percent \\\n", + "0 NaN NaN NaN NaN \n", + "1 NaN NaN NaN NaN \n", + "2 NaN NaN NaN NaN \n", + "3 NaN NaN NaN NaN \n", + "4 NaN NaN NaN NaN \n", + "5 NaN NaN NaN NaN \n", + "6 NaN NaN NaN NaN \n", + "7 NaN NaN NaN NaN \n", + "8 NaN NaN NaN NaN \n", + "9 NaN NaN NaN NaN \n", + "0 0.27 0.27 0.27 0.85 \n", + "1 0.28 0.28 0.28 0.90 \n", + "2 0.30 0.30 0.30 1.00 \n", + "3 0.32 0.32 0.32 1.10 \n", + "4 0.33 0.33 0.33 1.15 \n", + "5 0.27 0.27 0.27 0.85 \n", + "6 0.28 0.28 0.28 0.90 \n", + "7 0.30 0.30 0.30 1.00 \n", + "8 0.32 0.32 0.32 1.10 \n", + "9 0.33 0.33 0.33 1.15 \n", + "\n", + " vk_mv_percent vk_lv_percent \n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN NaN \n", + "4 NaN NaN \n", + "5 NaN NaN \n", + "6 NaN NaN \n", + "7 NaN NaN \n", + "8 NaN NaN \n", + "9 NaN NaN \n", + "0 0.85 0.85 \n", + "1 0.90 0.90 \n", + "2 1.00 1.00 \n", + "3 1.10 1.10 \n", + "4 1.15 1.15 \n", + "5 0.85 0.85 \n", + "6 0.90 0.90 \n", + "7 1.00 1.00 \n", + "8 1.10 1.10 \n", + "9 1.15 1.15 " + ], + "text/html": [ + "
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7101.0006.01.44NaNNaNNaNNaNNaNNaN
8111.0306.81.50NaNNaNNaNNaNNaNNaN
9121.0507.01.60NaNNaNNaNNaNNaNNaN
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7301.000NaNNaN0.300.300.301.001.001.00
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" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } ], - "outputs": [], - "execution_count": 3 + "execution_count": 6 }, { "cell_type": "markdown", @@ -146,8 +557,8 @@ "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:55:38.923570Z", - "start_time": "2024-12-20T16:55:38.910478Z" + "end_time": "2024-12-20T17:29:13.526881Z", + "start_time": "2024-12-20T17:29:13.498719Z" } }, "source": "pp.control.create_trafo_characteristic_object(net)", @@ -161,14 +572,14 @@ ] } ], - "execution_count": 4 + "execution_count": 7 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:55:41.018233Z", - "start_time": "2024-12-20T16:55:40.926357Z" + "end_time": "2024-12-20T17:29:35.761103Z", + "start_time": "2024-12-20T17:29:35.483198Z" } }, "source": [ @@ -187,14 +598,14 @@ "output_type": "display_data" } ], - "execution_count": 5 + "execution_count": 8 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:55:44.014472Z", - "start_time": "2024-12-20T16:55:43.946364Z" + "end_time": "2024-12-20T17:29:37.848492Z", + "start_time": "2024-12-20T17:29:37.641291Z" } }, "source": [ @@ -213,21 +624,21 @@ "output_type": "display_data" } ], - "execution_count": 6 + "execution_count": 9 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:55:48.056392Z", - "start_time": "2024-12-20T16:55:46.604814Z" + "end_time": "2024-12-20T17:29:45.262102Z", + "start_time": "2024-12-20T17:29:41.334183Z" } }, "source": [ "pp.runpp(net)" ], "outputs": [], - "execution_count": 7 + "execution_count": 10 }, { "cell_type": "markdown", @@ -240,8 +651,8 @@ "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:55:51.630158Z", - "start_time": "2024-12-20T16:55:51.609957Z" + "end_time": "2024-12-20T17:29:47.616492Z", + "start_time": "2024-12-20T17:29:47.599917Z" } }, "source": [ @@ -300,12 +711,12 @@ "" ] }, - "execution_count": 8, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 8 + "execution_count": 11 }, { "cell_type": "markdown", @@ -318,22 +729,22 @@ "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:55:54.072570Z", - "start_time": "2024-12-20T16:55:54.041088Z" + "end_time": "2024-12-20T17:29:54.306031Z", + "start_time": "2024-12-20T17:29:54.219226Z" } }, "source": [ "net2 = create_net()" ], "outputs": [], - "execution_count": 9 + "execution_count": 12 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:56:08.665811Z", - "start_time": "2024-12-20T16:55:55.670134Z" + "end_time": "2024-12-20T17:30:00.461234Z", + "start_time": "2024-12-20T17:29:56.511605Z" } }, "source": [ @@ -344,18 +755,18 @@ "name": "stdout", "output_type": "stream", "text": [ - "15.9 ms ± 309 μs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" + "45.3 ms ± 4.17 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] } ], - "execution_count": 10 + "execution_count": 13 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:56:24.601537Z", - "start_time": "2024-12-20T16:56:11.339655Z" + "end_time": "2024-12-20T17:30:07.173616Z", + "start_time": "2024-12-20T17:30:03.179493Z" } }, "source": [ @@ -366,11 +777,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "16.1 ms ± 230 μs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" + "49.2 ms ± 2.44 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] } ], - "execution_count": 11 + "execution_count": 14 }, { "cell_type": "markdown", @@ -390,8 +801,8 @@ "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:56:53.168919Z", - "start_time": "2024-12-20T16:56:53.131301Z" + "end_time": "2024-12-20T17:30:23.513432Z", + "start_time": "2024-12-20T17:30:23.408871Z" } }, "source": [ @@ -411,19 +822,19 @@ "json_excludes: ['self', '__class__']" ] }, - "execution_count": 12, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 12 + "execution_count": 15 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:57:10.510248Z", - "start_time": "2024-12-20T16:56:55.589600Z" + "end_time": "2024-12-20T17:30:30.982781Z", + "start_time": "2024-12-20T17:30:26.395868Z" } }, "source": [ @@ -434,11 +845,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "18.2 ms ± 213 μs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" + "56.4 ms ± 2.18 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] } ], - "execution_count": 13 + "execution_count": 16 }, { "cell_type": "markdown", @@ -458,8 +869,8 @@ "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:57:11.988060Z", - "start_time": "2024-12-20T16:57:11.982093Z" + "end_time": "2024-12-20T17:30:36.660922Z", + "start_time": "2024-12-20T17:30:36.643839Z" } }, "source": [ @@ -518,19 +929,19 @@ "" ] }, - "execution_count": 14, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 14 + "execution_count": 17 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:57:13.874119Z", - "start_time": "2024-12-20T16:57:13.860296Z" + "end_time": "2024-12-20T17:30:44.855228Z", + "start_time": "2024-12-20T17:30:44.843777Z" } }, "source": [ @@ -538,7 +949,7 @@ "assert np.allclose(net.res_bus.va_degree, net3.res_bus.va_degree, atol=1e-6, rtol=0)" ], "outputs": [], - "execution_count": 15 + "execution_count": 18 }, { "cell_type": "markdown", @@ -551,8 +962,8 @@ "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:57:15.864898Z", - "start_time": "2024-12-20T16:57:15.761774Z" + "end_time": "2024-12-20T17:31:03.737979Z", + "start_time": "2024-12-20T17:31:03.507153Z" } }, "source": [ @@ -563,14 +974,14 @@ " add_trafo_connection(net5, net5.trafo.at[0, 'hv_bus'], \"trafo3w\")" ], "outputs": [], - "execution_count": 16 + "execution_count": 19 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:57:26.509235Z", - "start_time": "2024-12-20T16:57:26.491052Z" + "end_time": "2024-12-20T17:33:05.038454Z", + "start_time": "2024-12-20T17:33:04.987694Z" } }, "source": [ @@ -588,14 +999,14 @@ ] } ], - "execution_count": 17 + "execution_count": 21 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:57:28.333289Z", - "start_time": "2024-12-20T16:57:28.322506Z" + "end_time": "2024-12-20T17:36:19.373524Z", + "start_time": "2024-12-20T17:36:19.355224Z" } }, "source": [ @@ -609,19 +1020,19 @@ "SplineCharacteristic" ] }, - "execution_count": 18, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 18 + "execution_count": 25 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:57:31.288425Z", - "start_time": "2024-12-20T16:57:31.271529Z" + "end_time": "2024-12-20T17:36:21.435889Z", + "start_time": "2024-12-20T17:36:21.395257Z" } }, "source": [ @@ -642,19 +1053,19 @@ "json_excludes: ['self', '__class__']" ] }, - "execution_count": 19, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 19 + "execution_count": 26 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:57:36.623419Z", - "start_time": "2024-12-20T16:57:34.396418Z" + "end_time": "2024-12-20T17:36:24.561437Z", + "start_time": "2024-12-20T17:36:23.680997Z" } }, "source": [ @@ -665,18 +1076,18 @@ "name": "stdout", "output_type": "stream", "text": [ - "27.1 ms ± 849 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + "69.3 ms ± 23.8 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] } ], - "execution_count": 20 + "execution_count": 27 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:57:42.071823Z", - "start_time": "2024-12-20T16:57:38.363387Z" + "end_time": "2024-12-20T17:36:37.049284Z", + "start_time": "2024-12-20T17:36:26.722895Z" } }, "source": [ @@ -687,18 +1098,18 @@ "name": "stdout", "output_type": "stream", "text": [ - "45.3 ms ± 653 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + "127 ms ± 1.89 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] } ], - "execution_count": 21 + "execution_count": 28 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:57:45.897147Z", - "start_time": "2024-12-20T16:57:45.884994Z" + "end_time": "2024-12-20T17:36:45.277624Z", + "start_time": "2024-12-20T17:36:45.257063Z" } }, "source": [ @@ -808,12 +1219,12 @@ "" ] }, - "execution_count": 22, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 22 + "execution_count": 29 }, { "cell_type": "markdown", @@ -840,20 +1251,20 @@ "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:57:59.484679Z", - "start_time": "2024-12-20T16:57:59.444995Z" + "end_time": "2024-12-20T17:37:14.422748Z", + "start_time": "2024-12-20T17:37:14.356399Z" } }, "source": "net6 = create_net()", "outputs": [], - "execution_count": 23 + "execution_count": 30 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:03.262021Z", - "start_time": "2024-12-20T16:58:03.239343Z" + "end_time": "2024-12-20T17:37:19.399723Z", + "start_time": "2024-12-20T17:37:19.357132Z" } }, "source": [ @@ -990,12 +1401,12 @@ "" ] }, - "execution_count": 24, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 24 + "execution_count": 31 }, { "cell_type": "code", @@ -1013,23 +1424,75 @@ "execution_count": 25 }, { - "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:11.977443Z", - "start_time": "2024-12-20T16:58:11.964661Z" + "end_time": "2024-12-20T17:43:17.642926Z", + "start_time": "2024-12-20T17:43:17.612158Z" } }, + "cell_type": "code", "source": [ - "# this would raise an error:\n", + "#this would raise a warning:\n", "#net6.trafo.loc[1,\"tap_dependency_table\"] = True\n", - "#net6[\"trafo_characteristic_table\"].loc[net[\"trafo_characteristic_table\"][\"id_characteristic\"]==1, \"vk_percent\"] = np.nan\n", - "#pp.control.create_trafo_characteristic_object(net6)\n", - "# net6.trafo.at[1, \"vk_percent_characteristic\"] = None\n", + "#pp.control.util.diagnostic.trafo_characteristic_table_diagnostic(net6)" + ], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\gjmal\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\control\\util\\diagnostic.py:109: UserWarning: There are some transformers in the trafo table with not all characteristics populated in the trafo_characteristic_table.\n", + " warnings.warn(f\"There are some transformers in the {trafo_table} table with not all \"\n" + ] + }, + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "execution_count": 34 + }, + { + "cell_type": "code", + "metadata": { + "ExecuteTime": { + "end_time": "2024-12-20T17:43:46.478925Z", + "start_time": "2024-12-20T17:43:45.929423Z" + } + }, + "source": [ + "#this would raise an error:\n", "#pp.runpp(net6)" ], - "outputs": [], - "execution_count": 26 + "outputs": [ + { + "ename": "FloatingPointError", + "evalue": "invalid value encountered in divide", + "output_type": "error", + "traceback": [ + "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[1;31mFloatingPointError\u001B[0m Traceback (most recent call last)", + "Cell \u001B[1;32mIn[35], line 1\u001B[0m\n\u001B[1;32m----> 1\u001B[0m \u001B[43mpp\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mrunpp\u001B[49m\u001B[43m(\u001B[49m\u001B[43mnet6\u001B[49m\u001B[43m)\u001B[49m\n", + "File \u001B[1;32m~\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\run.py:254\u001B[0m, in \u001B[0;36mrunpp\u001B[1;34m(net, algorithm, calculate_voltage_angles, init, max_iteration, tolerance_mva, trafo_model, trafo_loading, enforce_q_lims, check_connectivity, voltage_depend_loads, consider_line_temperature, run_control, distributed_slack, tdpf, tdpf_delay_s, **kwargs)\u001B[0m\n\u001B[0;32m 252\u001B[0m _check_bus_index_and_print_warning_if_high(net)\n\u001B[0;32m 253\u001B[0m _check_gen_index_and_print_warning_if_high(net)\n\u001B[1;32m--> 254\u001B[0m \u001B[43m_powerflow\u001B[49m\u001B[43m(\u001B[49m\u001B[43mnet\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n", + "File \u001B[1;32m~\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\powerflow.py:62\u001B[0m, in \u001B[0;36m_powerflow\u001B[1;34m(net, **kwargs)\u001B[0m\n\u001B[0;32m 57\u001B[0m net\u001B[38;5;241m.\u001B[39m_pd2ppc_lookups \u001B[38;5;241m=\u001B[39m {\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mbus\u001B[39m\u001B[38;5;124m\"\u001B[39m: array([], dtype\u001B[38;5;241m=\u001B[39mint64), \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mbus_dc\u001B[39m\u001B[38;5;124m\"\u001B[39m: array([], dtype\u001B[38;5;241m=\u001B[39mint64),\n\u001B[0;32m 58\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mext_grid\u001B[39m\u001B[38;5;124m\"\u001B[39m: array([], dtype\u001B[38;5;241m=\u001B[39mint64), \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mgen\u001B[39m\u001B[38;5;124m\"\u001B[39m: array([], dtype\u001B[38;5;241m=\u001B[39mint64),\n\u001B[0;32m 59\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mbranch\u001B[39m\u001B[38;5;124m\"\u001B[39m: array([], dtype\u001B[38;5;241m=\u001B[39mint64), \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mbranch_dc\u001B[39m\u001B[38;5;124m\"\u001B[39m: array([], dtype\u001B[38;5;241m=\u001B[39mint64)}\n\u001B[0;32m 61\u001B[0m \u001B[38;5;66;03m# convert pandapower net to ppc\u001B[39;00m\n\u001B[1;32m---> 62\u001B[0m ppc, ppci \u001B[38;5;241m=\u001B[39m \u001B[43m_pd2ppc\u001B[49m\u001B[43m(\u001B[49m\u001B[43mnet\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 64\u001B[0m \u001B[38;5;66;03m# store variables\u001B[39;00m\n\u001B[0;32m 65\u001B[0m net[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124m_ppc\u001B[39m\u001B[38;5;124m\"\u001B[39m] \u001B[38;5;241m=\u001B[39m ppc\n", + "File \u001B[1;32m~\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\pd2ppc.py:159\u001B[0m, in \u001B[0;36m_pd2ppc\u001B[1;34m(net, sequence, **kwargs)\u001B[0m\n\u001B[0;32m 157\u001B[0m update_vk_values \u001B[38;5;241m=\u001B[39m kwargs\u001B[38;5;241m.\u001B[39mget(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mupdate_vk_values\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;28;01mTrue\u001B[39;00m)\n\u001B[0;32m 158\u001B[0m \u001B[38;5;66;03m# Calculates ppc1/ppc2 branch impedances from branch elements\u001B[39;00m\n\u001B[1;32m--> 159\u001B[0m \u001B[43m_build_branch_ppc\u001B[49m\u001B[43m(\u001B[49m\u001B[43mnet\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mppc\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mupdate_vk_values\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 160\u001B[0m _build_branch_dc_ppc(net, ppc)\n\u001B[0;32m 162\u001B[0m _build_tcsc_ppc(net, ppc, mode)\n", + "File \u001B[1;32m~\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\build_branch.py:67\u001B[0m, in \u001B[0;36m_build_branch_ppc\u001B[1;34m(net, ppc, update_vk_values)\u001B[0m\n\u001B[0;32m 65\u001B[0m _calc_line_parameter(net, ppc)\n\u001B[0;32m 66\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mtrafo\u001B[39m\u001B[38;5;124m\"\u001B[39m \u001B[38;5;129;01min\u001B[39;00m lookup:\n\u001B[1;32m---> 67\u001B[0m \u001B[43m_calc_trafo_parameter\u001B[49m\u001B[43m(\u001B[49m\u001B[43mnet\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mppc\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mupdate_vk_values\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mupdate_vk_values\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 68\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mtrafo3w\u001B[39m\u001B[38;5;124m\"\u001B[39m \u001B[38;5;129;01min\u001B[39;00m lookup:\n\u001B[0;32m 69\u001B[0m _calc_trafo3w_parameter(net, ppc, update_vk_values\u001B[38;5;241m=\u001B[39mupdate_vk_values)\n", + "File \u001B[1;32m~\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\build_branch.py:370\u001B[0m, in \u001B[0;36m_calc_trafo_parameter\u001B[1;34m(net, ppc, update_vk_values)\u001B[0m\n\u001B[0;32m 368\u001B[0m branch[f:t, F_BUS] \u001B[38;5;241m=\u001B[39m bus_lookup[trafo[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mhv_bus\u001B[39m\u001B[38;5;124m\"\u001B[39m]\u001B[38;5;241m.\u001B[39mvalues]\n\u001B[0;32m 369\u001B[0m branch[f:t, T_BUS] \u001B[38;5;241m=\u001B[39m bus_lookup[trafo[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mlv_bus\u001B[39m\u001B[38;5;124m\"\u001B[39m]\u001B[38;5;241m.\u001B[39mvalues]\n\u001B[1;32m--> 370\u001B[0m r, x, g, b, g_asym, b_asym, ratio, shift \u001B[38;5;241m=\u001B[39m \u001B[43m_calc_branch_values_from_trafo_df\u001B[49m\u001B[43m(\u001B[49m\n\u001B[0;32m 371\u001B[0m \u001B[43m \u001B[49m\u001B[43mnet\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mppc\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mupdate_vk_values\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mupdate_vk_values\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 372\u001B[0m branch[f:t, BR_R] \u001B[38;5;241m=\u001B[39m r\n\u001B[0;32m 373\u001B[0m branch[f:t, BR_X] \u001B[38;5;241m=\u001B[39m x\n", + "File \u001B[1;32m~\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\build_branch.py:447\u001B[0m, in \u001B[0;36m_calc_branch_values_from_trafo_df\u001B[1;34m(net, ppc, trafo_df, sequence, update_vk_values)\u001B[0m\n\u001B[0;32m 444\u001B[0m vn_trafo_hv, vn_trafo_lv, shift \u001B[38;5;241m=\u001B[39m _calc_tap_from_dataframe(net, trafo_df)\n\u001B[0;32m 445\u001B[0m ratio \u001B[38;5;241m=\u001B[39m _calc_nominal_ratio_from_dataframe(ppc, trafo_df, vn_trafo_hv, vn_trafo_lv,\n\u001B[0;32m 446\u001B[0m bus_lookup)\n\u001B[1;32m--> 447\u001B[0m r, x, g, b, g_asym, b_asym \u001B[38;5;241m=\u001B[39m \u001B[43m_calc_r_x_y_from_dataframe\u001B[49m\u001B[43m(\u001B[49m\u001B[43mnet\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mtrafo_df\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mvn_trafo_lv\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mvn_lv\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mppc\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43msequence\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43msequence\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 448\u001B[0m \u001B[43m \u001B[49m\u001B[43mupdate_vk_values\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mupdate_vk_values\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 449\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m r, x, g, b, g_asym, b_asym, ratio, shift\n", + "File \u001B[1;32m~\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\build_branch.py:494\u001B[0m, in \u001B[0;36m_calc_r_x_y_from_dataframe\u001B[1;34m(net, trafo_df, vn_trafo_lv, vn_lv, ppc, sequence, update_vk_values)\u001B[0m\n\u001B[0;32m 490\u001B[0m r_ratio \u001B[38;5;241m=\u001B[39m get_trafo_values(trafo_df, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mleakage_resistance_ratio_hv\u001B[39m\u001B[38;5;124m\"\u001B[39m) \\\n\u001B[0;32m 491\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mleakage_resistance_ratio_hv\u001B[39m\u001B[38;5;124m\"\u001B[39m \u001B[38;5;129;01min\u001B[39;00m trafo_df \u001B[38;5;28;01melse\u001B[39;00m np\u001B[38;5;241m.\u001B[39mfull_like(r, fill_value\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m0.5\u001B[39m, dtype\u001B[38;5;241m=\u001B[39mnp\u001B[38;5;241m.\u001B[39mfloat64)\n\u001B[0;32m 492\u001B[0m x_ratio \u001B[38;5;241m=\u001B[39m get_trafo_values(trafo_df, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mleakage_reactance_ratio_hv\u001B[39m\u001B[38;5;124m\"\u001B[39m) \\\n\u001B[0;32m 493\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mleakage_reactance_ratio_hv\u001B[39m\u001B[38;5;124m\"\u001B[39m \u001B[38;5;129;01min\u001B[39;00m trafo_df \u001B[38;5;28;01melse\u001B[39;00m np\u001B[38;5;241m.\u001B[39mfull_like(r, fill_value\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m0.5\u001B[39m, dtype\u001B[38;5;241m=\u001B[39mnp\u001B[38;5;241m.\u001B[39mfloat64)\n\u001B[1;32m--> 494\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43m_wye_delta\u001B[49m\u001B[43m(\u001B[49m\u001B[43mr\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mx\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mg\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mb\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mr_ratio\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mx_ratio\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 495\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m 496\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mUnknown Transformer Model \u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m - valid values ar \u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mpi\u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124m or \u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mt\u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124m\"\u001B[39m \u001B[38;5;241m%\u001B[39m trafo_model)\n", + "File \u001B[1;32m~\\AppData\\Local\\pypoetry\\Cache\\virtualenvs\\pandapower-develop-2xtPOedL-py3.11\\Lib\\site-packages\\numpy\\_core\\_ufunc_config.py:449\u001B[0m, in \u001B[0;36merrstate.__call__..inner\u001B[1;34m(*args, **kwargs)\u001B[0m\n\u001B[0;32m 446\u001B[0m _token \u001B[38;5;241m=\u001B[39m _extobj_contextvar\u001B[38;5;241m.\u001B[39mset(extobj)\n\u001B[0;32m 447\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[0;32m 448\u001B[0m \u001B[38;5;66;03m# Call the original, decorated, function:\u001B[39;00m\n\u001B[1;32m--> 449\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mfunc\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 450\u001B[0m \u001B[38;5;28;01mfinally\u001B[39;00m:\n\u001B[0;32m 451\u001B[0m _extobj_contextvar\u001B[38;5;241m.\u001B[39mreset(_token)\n", + "File \u001B[1;32m~\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\build_branch.py:513\u001B[0m, in \u001B[0;36m_wye_delta\u001B[1;34m(r, x, g, b, r_ratio, x_ratio)\u001B[0m\n\u001B[0;32m 511\u001B[0m zSum_triangle \u001B[38;5;241m=\u001B[39m za_star \u001B[38;5;241m*\u001B[39m zb_star \u001B[38;5;241m+\u001B[39m za_star \u001B[38;5;241m*\u001B[39m zc_star \u001B[38;5;241m+\u001B[39m zb_star \u001B[38;5;241m*\u001B[39m zc_star\n\u001B[0;32m 512\u001B[0m zab_triangle \u001B[38;5;241m=\u001B[39m zSum_triangle \u001B[38;5;241m/\u001B[39m zc_star\n\u001B[1;32m--> 513\u001B[0m zac_triangle \u001B[38;5;241m=\u001B[39m \u001B[43mzSum_triangle\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m/\u001B[39;49m\u001B[43m \u001B[49m\u001B[43mzb_star\u001B[49m\n\u001B[0;32m 514\u001B[0m zbc_triangle \u001B[38;5;241m=\u001B[39m zSum_triangle \u001B[38;5;241m/\u001B[39m za_star\n\u001B[0;32m 515\u001B[0m r[tidx] \u001B[38;5;241m=\u001B[39m zab_triangle\u001B[38;5;241m.\u001B[39mreal\n", + "\u001B[1;31mFloatingPointError\u001B[0m: invalid value encountered in divide" + ] + } + ], + "execution_count": 35 }, { "cell_type": "markdown", @@ -1049,20 +1512,20 @@ "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:14.451966Z", - "start_time": "2024-12-20T16:58:14.413198Z" + "end_time": "2024-12-20T17:44:19.510715Z", + "start_time": "2024-12-20T17:44:19.432374Z" } }, "source": "net_create = create_net()", "outputs": [], - "execution_count": 27 + "execution_count": 36 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:15.783744Z", - "start_time": "2024-12-20T16:58:15.766811Z" + "end_time": "2024-12-20T17:44:21.886472Z", + "start_time": "2024-12-20T17:44:21.856974Z" } }, "source": [ @@ -1187,19 +1650,19 @@ "" ] }, - "execution_count": 28, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 28 + "execution_count": 37 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:17.668098Z", - "start_time": "2024-12-20T16:58:17.652722Z" + "end_time": "2024-12-20T17:44:24.855664Z", + "start_time": "2024-12-20T17:44:24.815328Z" } }, "source": [ @@ -1218,14 +1681,14 @@ ] } ], - "execution_count": 29 + "execution_count": 38 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:19.650434Z", - "start_time": "2024-12-20T16:58:19.636602Z" + "end_time": "2024-12-20T17:44:28.708038Z", + "start_time": "2024-12-20T17:44:28.678060Z" } }, "source": [ @@ -1378,26 +1841,26 @@ "" ] }, - "execution_count": 30, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 30 + "execution_count": 39 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:22.151846Z", - "start_time": "2024-12-20T16:58:22.127358Z" + "end_time": "2024-12-20T17:45:01.700203Z", + "start_time": "2024-12-20T17:45:01.637071Z" } }, "source": [ "pp.runpp(net_create)" ], "outputs": [], - "execution_count": 31 + "execution_count": 40 }, { "cell_type": "markdown", @@ -1414,48 +1877,44 @@ ] }, { - "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:25.413991Z", - "start_time": "2024-12-20T16:58:25.271533Z" + "end_time": "2024-12-20T17:55:39.913632Z", + "start_time": "2024-12-20T17:55:39.576372Z" } }, - "source": [ - "net2 = pp.from_json_string(pp.to_json(net))\n", - "net2[\"trafo_characteristic_spline\"]" - ], + "cell_type": "code", "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\gjmal\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\control\\util\\auxiliary.py:263: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n", + " net[\"trafo_characteristic_spline\"] = net[\"trafo_characteristic_spline_temp\"].applymap(\n" + ] + }, { "data": { "text/plain": [ - " id_characteristic voltage_ratio_characteristic \\\n", - "0 0 {'_module': 'pandapower.control.util.character... \n", - "1 1 {'_module': 'pandapower.control.util.character... \n", - "\n", - " angle_deg_characteristic \\\n", - "0 {'_module': 'pandapower.control.util.character... \n", - "1 {'_module': 'pandapower.control.util.character... \n", + " id_characteristic voltage_ratio_characteristic angle_deg_characteristic \\\n", + "0 0 SplineCharacteristic SplineCharacteristic \n", + "1 1 SplineCharacteristic SplineCharacteristic \n", "\n", - " vk_percent_characteristic \\\n", - "0 {'_module': 'pandapower.control.util.character... \n", - "1 {'_module': 'pandapower.control.util.character... \n", - "\n", - " vkr_percent_characteristic \\\n", - "0 {'_module': 'pandapower.control.util.character... \n", - "1 {'_module': 'pandapower.control.util.character... \n", + " vk_percent_characteristic vkr_percent_characteristic \\\n", + "0 SplineCharacteristic SplineCharacteristic \n", + "1 SplineCharacteristic SplineCharacteristic \n", "\n", " vk_hv_percent_characteristic vkr_hv_percent_characteristic \\\n", - "0 None None \n", - "1 None None \n", + "0 \n", + "1 \n", "\n", " vk_mv_percent_characteristic vkr_mv_percent_characteristic \\\n", - "0 None None \n", - "1 None None \n", + "0 \n", + "1 \n", "\n", " vk_lv_percent_characteristic vkr_lv_percent_characteristic \n", - "0 None None \n", - "1 None None " + "0 \n", + "1 " ], "text/html": [ "
\n", @@ -1493,42 +1952,48 @@ " \n", " 0\n", " 0\n", - " {'_module': 'pandapower.control.util.character...\n", - " {'_module': 'pandapower.control.util.character...\n", - " {'_module': 'pandapower.control.util.character...\n", - " {'_module': 'pandapower.control.util.character...\n", - " None\n", - " None\n", - " None\n", - " None\n", - " None\n", - " None\n", + " SplineCharacteristic\n", + " SplineCharacteristic\n", + " SplineCharacteristic\n", + " SplineCharacteristic\n", + " <NA>\n", + " <NA>\n", + " <NA>\n", + " <NA>\n", + " <NA>\n", + " <NA>\n", " \n", " \n", " 1\n", " 1\n", - " {'_module': 'pandapower.control.util.character...\n", - " {'_module': 'pandapower.control.util.character...\n", - " {'_module': 'pandapower.control.util.character...\n", - " {'_module': 'pandapower.control.util.character...\n", - " None\n", - " None\n", - " None\n", - " None\n", - " None\n", - " None\n", + " SplineCharacteristic\n", + " SplineCharacteristic\n", + " SplineCharacteristic\n", + " SplineCharacteristic\n", + " <NA>\n", + " <NA>\n", + " <NA>\n", + " <NA>\n", + " <NA>\n", + " <NA>\n", " \n", " \n", "\n", "
" ] }, - "execution_count": 32, + "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 32 + "execution_count": 49, + "source": [ + "net2 = pp.from_json_string(pp.to_json(net))\n", + "pp.control.create_trafo_characteristic_object(net2)\n", + "\n", + "net2[\"trafo_characteristic_spline\"]" + ] }, { "cell_type": "markdown", @@ -1541,12 +2006,12 @@ "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:27.266243Z", - "start_time": "2024-12-20T16:58:27.185674Z" + "end_time": "2024-12-20T17:56:29.525917Z", + "start_time": "2024-12-20T17:56:29.324462Z" } }, "source": [ - "pp.control.plot_characteristic(net[\"trafo_characteristic_spline\"][\"vk_percent_characteristic\"].loc[0], -2, 2,\n", + "pp.control.plot_characteristic(net2[\"trafo_characteristic_spline\"][\"vk_percent_characteristic\"].loc[0], -2, 2,\n", " xlabel='Tap position \"tap_pos\"', ylabel='Value of \"vk_percent\"')" ], "outputs": [ @@ -1561,7 +2026,7 @@ "output_type": "display_data" } ], - "execution_count": 33 + "execution_count": 51 }, { "cell_type": "markdown", @@ -1588,8 +2053,8 @@ "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:30.986578Z", - "start_time": "2024-12-20T16:58:30.971527Z" + "end_time": "2024-12-20T17:56:33.968743Z", + "start_time": "2024-12-20T17:56:33.939315Z" } }, "source": [ @@ -1714,19 +2179,19 @@ "" ] }, - "execution_count": 34, + "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 34 + "execution_count": 52 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:34.161404Z", - "start_time": "2024-12-20T16:58:34.148661Z" + "end_time": "2024-12-20T17:56:50.699233Z", + "start_time": "2024-12-20T17:56:50.675600Z" } }, "source": "pp.control.util.diagnostic.trafo_characteristic_table_diagnostic(net)", @@ -1737,19 +2202,19 @@ "True" ] }, - "execution_count": 35, + "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 35 + "execution_count": 53 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:37.426739Z", - "start_time": "2024-12-20T16:58:37.416019Z" + "end_time": "2024-12-20T17:56:52.614616Z", + "start_time": "2024-12-20T17:56:52.589803Z" } }, "source": "pp.control.util.diagnostic.trafo_characteristic_table_diagnostic(net6)", @@ -1758,8 +2223,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\gjmal\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\control\\util\\diagnostic.py:89: UserWarning: trafo: found 1 transformer(s) with not both tap_dependency_table and id_characteristic_table parameters populated. Power flow calculation will raise an error.\n", - " warnings.warn(f\"{trafo_table}: found {mismatch_a} transformer(s) with not both \"\n", "C:\\Users\\gjmal\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\control\\util\\diagnostic.py:109: UserWarning: There are some transformers in the trafo table with not all characteristics populated in the trafo_characteristic_table.\n", " warnings.warn(f\"There are some transformers in the {trafo_table} table with not all \"\n" ] @@ -1770,19 +2233,19 @@ "False" ] }, - "execution_count": 36, + "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 36 + "execution_count": 54 }, { "cell_type": "code", "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:44.095527Z", - "start_time": "2024-12-20T16:58:44.081532Z" + "end_time": "2024-12-20T17:57:14.900419Z", + "start_time": "2024-12-20T17:57:14.875212Z" } }, "source": [ @@ -1807,18 +2270,18 @@ "False" ] }, - "execution_count": 37, + "execution_count": 55, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 37 + "execution_count": 55 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-12-20T16:58:47.875913Z", - "start_time": "2024-12-20T16:58:47.864883Z" + "end_time": "2024-12-20T17:57:32.606404Z", + "start_time": "2024-12-20T17:57:32.577878Z" } }, "cell_type": "code", @@ -1844,12 +2307,12 @@ "False" ] }, - "execution_count": 38, + "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 38 + "execution_count": 56 } ], "metadata": { From d882ebf56ffc45073746dc5b2d603e103a01b984 Mon Sep 17 00:00:00 2001 From: Ghanshyam Malaviya Date: Thu, 2 Jan 2025 18:54:25 +0100 Subject: [PATCH 104/125] CHG: Description of tap dependent impedance of transformers tutorial test --- tutorials/tap_dependent_impedance.ipynb | 1276 +++++++++-------------- 1 file changed, 477 insertions(+), 799 deletions(-) diff --git a/tutorials/tap_dependent_impedance.ipynb b/tutorials/tap_dependent_impedance.ipynb index d8c3fc62a..4857f18c5 100644 --- a/tutorials/tap_dependent_impedance.ipynb +++ b/tutorials/tap_dependent_impedance.ipynb @@ -11,35 +11,37 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "With an adjustment of a tap position of a transformer, the number of windings is adjusted, which influences the impedence. The user can provide characteristics of the dependance of the variables vk_percent and vkr_percent on the tap position. A helper function in pandapower control module converts the provided points in a characteristic object with quadratic spline interpolation (or a user-defined characteristic object with a custom interpolation approach) and writes it in the trafo table. Finally, a diagnostic function checks for inconsistensies and provides information to the user." + "With an adjustment of a tap position of a transformer, the number of windings is adjusted, which influences the impedence. The user can provide **trafo_characteristic_table** of the dependance of the variables **voltage ratio**, **angle in degree**, **vk_percent** and **vkr_percent** on the tap position. A helper function in pandapower control module converts the provided points in a characteristic object with quadratic spline interpolation (or a user-defined characteristic object with a custom interpolation approach) and writes it in the **trafo_characteristic_spline** table. Finally, a diagnostic function checks for inconsistensies and provides information to the user." ] }, { "cell_type": "code", + "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2024-12-20T17:26:30.555390Z", "start_time": "2024-12-20T17:26:30.549364Z" } }, + "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import pandapower as pp\n", "import pandapower.control\n", "import json" - ], - "outputs": [], - "execution_count": 3 + ] }, { "cell_type": "code", + "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2024-12-20T17:27:16.655445Z", "start_time": "2024-12-20T17:27:16.629600Z" } }, + "outputs": [], "source": [ "def add_trafo_connection(net, hv_bus, element_type=\"trafo\"):\n", " cb = pp.create_bus(net, vn_kv=0.4)\n", @@ -71,6 +73,7 @@ " net.trafo.loc[i, \"id_characteristic_table\"] = i\n", " net.trafo.loc[i,\"tap_dependency_table\"] = True\n", "\n", + " # Adding the characteristics data for two- and three-winding transformers into the trafo_characteristic_table\n", " net['trafo_characteristic_table'] = pd.DataFrame(\n", " columns=['id_characteristic', 'step', 'voltage_ratio', 'angle_deg', 'vk_percent',\n", " 'vkr_percent', 'vkr_hv_percent', 'vkr_mv_percent',\n", @@ -110,89 +113,44 @@ " data_frame = pd.DataFrame(trafo3w_data)\n", " net['trafo_characteristic_table'] = pd.concat([net['trafo_characteristic_table'], data_frame], sort=False)\n", " return net" - ], - "outputs": [], - "execution_count": 4 + ] }, { "cell_type": "code", + "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2024-12-20T17:28:09.231909Z", "start_time": "2024-12-20T17:28:09.117435Z" } }, - "source": "net = create_net()", + "outputs": [], + "source": [ + "net = create_net()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can create the characteristics by generating characteristic objects and assigning them to the respective columns in the **trafo_characteristic_spline table**. To create these characteristics, a convenience function can be used to initialize and configure the characteristic objects for **voltage ratio**, **angle in degree**, **vk_percent** and **vkr_percent**. This function creates the characteristics for all transfomers within the specified network. It is essential that the input parameters are provided in the correct order to ensure proper functionality." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\gjmal\\PycharmProjects\\pandapower-develop\\pandapower\\pandapower\\control\\util\\auxiliary.py:263: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n", + " net[\"trafo_characteristic_spline\"] = net[\"trafo_characteristic_spline_temp\"].applymap(\n" + ] + }, { "data": { - "text/plain": [ - " id_characteristic step voltage_ratio angle_deg vk_percent vkr_percent \\\n", - "0 0 -2 0.95 0 5.0 1.30 \n", - "1 0 -1 0.97 0 5.2 1.40 \n", - "2 0 0 1.00 0 6.0 1.44 \n", - "3 0 1 1.03 0 6.8 1.50 \n", - "4 0 2 1.05 0 7.0 1.60 \n", - "5 1 -2 0.95 0 5.0 1.30 \n", - "6 1 -1 0.97 0 5.2 1.40 \n", - "7 1 0 1.00 0 6.0 1.44 \n", - "8 1 1 1.03 0 6.8 1.50 \n", - "9 1 2 1.05 0 7.0 1.60 \n", - "0 2 -2 0.95 0 NaN NaN \n", - "1 2 -1 0.97 0 NaN NaN \n", - "2 2 0 1.00 0 NaN NaN \n", - "3 2 1 1.03 0 NaN NaN \n", - "4 2 2 1.05 0 NaN NaN \n", - "5 3 -2 0.95 0 NaN NaN \n", - "6 3 -1 0.97 0 NaN NaN \n", - "7 3 0 1.00 0 NaN NaN \n", - "8 3 1 1.03 0 NaN NaN \n", - "9 3 2 1.05 0 NaN NaN \n", - "\n", - " vkr_hv_percent vkr_mv_percent vkr_lv_percent vk_hv_percent \\\n", - "0 NaN NaN NaN NaN \n", - "1 NaN NaN NaN NaN \n", - "2 NaN NaN NaN NaN \n", - "3 NaN NaN NaN NaN \n", - "4 NaN NaN NaN NaN \n", - "5 NaN NaN NaN NaN \n", - "6 NaN NaN NaN NaN \n", - "7 NaN NaN NaN NaN \n", - "8 NaN NaN NaN NaN \n", - "9 NaN NaN NaN NaN \n", - "0 0.27 0.27 0.27 0.85 \n", - "1 0.28 0.28 0.28 0.90 \n", - "2 0.30 0.30 0.30 1.00 \n", - "3 0.32 0.32 0.32 1.10 \n", - "4 0.33 0.33 0.33 1.15 \n", - "5 0.27 0.27 0.27 0.85 \n", - "6 0.28 0.28 0.28 0.90 \n", - "7 0.30 0.30 0.30 1.00 \n", - "8 0.32 0.32 0.32 1.10 \n", - "9 0.33 0.33 0.33 1.15 \n", - "\n", - " vk_mv_percent vk_lv_percent \n", - "0 NaN NaN \n", - "1 NaN NaN \n", - "2 NaN NaN \n", - "3 NaN NaN \n", - "4 NaN NaN \n", - "5 NaN NaN \n", - "6 NaN NaN \n", - "7 NaN NaN \n", - "8 NaN NaN \n", - "9 NaN NaN \n", - "0 0.85 0.85 \n", - "1 0.90 0.90 \n", - "2 1.00 1.00 \n", - "3 1.10 1.10 \n", - "4 1.15 1.15 \n", - "5 0.85 0.85 \n", - "6 0.90 0.90 \n", - "7 1.00 1.00 \n", - "8 1.10 1.10 \n", - "9 1.15 1.15 " - ], "text/html": [ "
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