edisgo.network.heat

Module Contents

Classes

HeatPump

Data container for all heat pump data.
class edisgo.network.heat.HeatPump(**kwargs)[source]

Data container for all heat pump data.

This class holds data on heat pump COP, heat demand time series, thermal storage data…

property cop_df

DataFrame with COP time series of heat pumps.

Parameters

df (pandas.DataFrame) – DataFrame with COP time series of heat pumps in p.u.. Index of the dataframe is a time index and should contain all time steps given in timeindex. Column names are names of heat pumps as in loads_df.

Returns

DataFrame with COP time series of heat pumps in p.u.. For more information on the dataframe see input parameter df.

Return type

pandas.DataFrame

property heat_demand_df

DataFrame with heat demand time series of heat pumps.

Parameters

df (pandas.DataFrame) – DataFrame with heat demand time series of heat pumps in MW. Index of the dataframe is a time index and should contain all time steps given in timeindex. Column names are names of heat pumps as in loads_df.

Returns

DataFrame with heat demand time series of heat pumps in MW. For more information on the dataframe see input parameter df.

Return type

pandas.DataFrame

property thermal_storage_units_df

DataFrame with heat pump’s thermal storage information.

Parameters

df (pandas.DataFrame) –

DataFrame with thermal storage information. Index of the dataframe are names of heat pumps as in loads_df. Columns of the dataframe are:

capacityfloat

Thermal storage capacity in MWh.

efficiencyfloat

Charging and discharging efficiency in p.u..

state_of_charge_initialfloat

Initial state of charge in p.u..

Returns

DataFrame with thermal storage information. For more information on the dataframe see input parameter df.

Return type

pandas.DataFrame

property building_ids_df

DataFrame with buildings served by each heat pump.

Parameters

df (pandas.DataFrame) –

DataFrame with building IDs of buildings served by each heat pump. Index of the dataframe are names of heat pumps as in loads_df. Columns of the dataframe are:

building_idslist(int)

List of building IDs.

Returns

DataFrame with building IDs of buildings served by each heat pump. For more information on the dataframe see input parameter df.

Return type

pandas.DataFrame

set_cop(edisgo_object, ts_cop, heat_pump_names=None)[source]

Get COP time series for heat pumps.

Heat pumps need to already be integrated into the grid.

Parameters

  • edisgo_object (EDisGo) –

  • ts_cop (str or pandas.DataFrame) –

    Defines option used to set COP time series. Possible options are:

    • ’oedb’

      Not yet implemented! Weather cell specific hourly COP time series are obtained from the OpenEnergy DataBase for the weather year 2011. See edisgo.io.timeseries_import.cop_oedb() for more information. Using information on which weather cell each heat pump is in, the weather cell specific time series are mapped to each heat pump.

    • pandas.DataFrame

      DataFrame with self-provided COP time series per heat pump. See cop_df on information on the required dataframe format.

  • heat_pump_names (list(str) or None) – Defines for which heat pumps to get COP time series for in case ts_cop is ‘oedb’. If None, all heat pumps in loads_df (type is ‘heat_pump’) are used. Default: None.

set_heat_demand(edisgo_object, ts_heat_demand, heat_pump_names=None)[source]

Get heat demand time series for buildings with heat pumps.

Heat pumps need to already be integrated into the grid.

Parameters

  • edisgo_object (EDisGo) –

  • ts_heat_demand (str or pandas.DataFrame) –

    Defines option used to set heat demand time series. Possible options are:

  • heat_pump_names (list(str) or None) – Defines for which heat pumps to get heat demand time series for in case ts_heat_demand is ‘oedb’. If None, all heat pumps in loads_df (type is ‘heat_pump’) are used. Default: None.

reduce_memory(attr_to_reduce=None, to_type='float32')[source]

Reduces size of dataframes to save memory.

See reduce_memory for more information.

Parameters

  • attr_to_reduce (list(str), optional) – List of attributes to reduce size for. Per default, the following attributes are reduced if they exist: cop_df, heat_demand_df.

  • to_type (str, optional) – Data type to convert time series data to. This is a tradeoff between precision and memory. Default: “float32”.

to_csv(directory, reduce_memory=False, **kwargs)[source]

Exports heat pump data to csv files.

The following attributes are exported:

  • ‘cop_df’

    Attribute cop_df is saved to cop.csv.

  • ‘heat_demand_df’

    Attribute heat_demand_df is saved to heat_demand.csv.

  • ‘thermal_storage_units_df’

    Attribute thermal_storage_units_df is saved to thermal_storage_units.csv.

  • ‘building_ids_df’

    Attribute building_ids_df is saved to building_ids.csv.

Parameters

  • directory (str) – Path to save data to.

  • reduce_memory (bool, optional) – If True, size of dataframes is reduced using reduce_memory. Optional parameters of reduce_memory can be passed as kwargs to this function. Default: False.

  • kwargs – Kwargs may contain arguments of reduce_memory.

from_csv(data_path, from_zip_archive=False)[source]

Restores heat pump data from csv files.

Parameters

  • data_path (str) – Path to heat pump csv files.

  • from_zip_archive (bool, optional) – Set True if data is archived in a zip archive. Default: False