pypowsybl.dynamic.ModelMapping.add_tap_changer_blocking_automation_system#

ModelMapping.add_tap_changer_blocking_automation_system(df, tfo_df, mp1_df, mp2_df=None, mp3_df=None, mp5_df=None, mp4_df=None)[source]#

Add a dynamic tap changer blocking automation system (not link to a network element)

Args:

df: Primary attributes as a dataframe. tfo_df: Dataframe for transformer data. mpN_df: Dataframes for a measurement point data, the automation system can handle up to 5 measurement points, at least 1 measurement point is expected. For each measurement point dataframe, alternative points can be input (for example bus or busbar section) the first energized element found in the network will be used

Parameters:
Return type:

None

Notes

Valid attributes for the primary dataframes are:

  • dynamic_model_id: id of the tap changer blocking automation system

  • parameter_set_id: id of the parameter for this model given in the dynawo configuration

  • model_name: name of the model used for the mapping (if none the default model will be used)

Valid attributes for the transformer dataframes are:

  • dynamic_model_id: id of the tap changer blocking automation system

  • transformer_id: id of a transformer controlled by the automation system

Valid attributes for the measurement point dataframes are:

  • dynamic_model_id: id of the tap changer blocking automation system

  • measurement_point_id: id of the bus or busbar section used for the voltage measurement

Examples

We need to provide 2 dataframes, 1 for tap changer blocking automation system basic data, and one for transformer data:

df = pd.DataFrame.from_records(
    index='dynamic_model_id',
    columns=['dynamic_model_id', 'parameter_set_id', 'u_measurements', 'model_name'],
    data=[('DM_TCB', 'tcb', 'BUS', 'TapChangerBlockingAutomaton')])
tfo_df = pd.DataFrame.from_records(
    index='dynamic_model_id',
    columns=['dynamic_model_id', 'transformer_id'],
    data=[('DM_TCB', 'TFO1'),
          ('DM_TCB', 'TFO2'),
          ('DM_TCB', 'TFO3')])
measurement1_df = pd.DataFrame.from_records(
    index='dynamic_model_id',
    columns=['dynamic_model_id', 'measurement_point_id'],
    data=[('DM_TCB', 'B1'),
          ('DM_TCB', 'BS1')])
measurement2_df = pd.DataFrame.from_records(
    index='dynamic_model_id',
    columns=['dynamic_model_id', 'measurement_point_id'],
    data=[('DM_TCB', 'B4')])
model_mapping.add_tap_changer_blocking_automation_system(df, tfo_df, measurement1_df, measurement2_df)