electricity_demand_etrago

The central module containing code to merge data on electricity demand and feed this data into the corresponding etraGo tables.

class ElectricalLoadEtrago(dependencies)[source]

Bases: Dataset

Aggregate annual and hourly electricity demands per substation and export to eTraGo tables

All loads including time series are aggregated per corresponding substation and inserted into the existing eTraGo tables. Additionally the aggregated national time series are stored to function as an input for pypsa-eur-sec.

Dependencies
Resulting tables
name: str = 'Electrical_load_etrago'
sources: DatasetSources = DatasetSources(tables={'cts_curves': 'demand.egon_etrago_electricity_cts', 'osm_curves': 'demand.egon_osm_ind_load_curves', 'sites_curves': 'demand.egon_sites_ind_load_curves', 'household_curves': 'demand.egon_etrago_electricity_households', 'etrago_buses': 'grid.egon_etrago_bus'}, files={}, urls={})

The sources used by the datasets. Could be tables, files and urls

targets: DatasetTargets = DatasetTargets(tables={'etrago_load': 'grid.egon_etrago_load', 'etrago_load_curves': 'grid.egon_etrago_load_timeseries'}, files={})

The targets created by the datasets. Could be tables and files

version: str = '0.0.10'
demands_per_bus(scenario)[source]

Sum all electricity demand curves up per bus

Parameters:

scenario (str) – Scenario name.

Returns:

pandas.DataFrame – Aggregated electrical demand timeseries per bus

export_to_db()[source]

Prepare and export eTraGo-ready information of loads per bus and their time series to the database

Returns:

None.

store_national_profiles(ind_curves_sites, ind_curves_osm, cts_curves, hh_curves, scenario)[source]

Store electrical load timeseries aggregated for national level as an input for pypsa-eur-sec

Parameters:

  • ind_curves_sites (pd.DataFrame) – Industrial load timeseries for industrial sites per bus

  • ind_curves_osm (pd.DataFrame) – Industrial load timeseries for industrial osm areas per bus

  • cts_curves (pd.DataFrame) – CTS load curves per bus

  • hh_curves (pd.DataFrame) – Household load curves per bus

  • scenario (str) – Scenario name

Returns:

None.