temporal

The central module containing all code dealing with processing timeseries data using demandregio

calc_load_curves_ind_osm(scenario)

Temporal disaggregate electrical demand per osm industrial landuse area.

Parameters:

scenario (str) – Scenario name.

Returns:

pandas.DataFrame – Demand timeseries of industry allocated to osm landuse areas and aggregated per substation id

calc_load_curves_ind_sites(scenario)

Temporal disaggregation of load curves per industrial site and industrial subsector.

Parameters:

scenario (str) – Scenario name.

Returns:

pandas.DataFrame – Demand timeseries of industry allocated to industrial sites and aggregated per substation id and industrial subsector

identify_bus(load_curves, demand_area)

Identify the grid connection point for a consumer by determining its grid level based on the time series’ peak load and the spatial intersection to mv grid districts or ehv voronoi cells.

Parameters:

• load_curves (pandas.DataFrame) – Demand timeseries per demand area (e.g. osm landuse area, industrial site)

• demand_area (pandas.DataFrame) – Dataframe with id and geometry of areas where an industrial demand is assigned to, such as osm landuse areas or industrial sites.

Returns:

pandas.DataFrame – Aggregated industrial demand timeseries per bus

identify_voltage_level(df)

Identify the voltage_level of a grid component based on its peak load and defined thresholds.

Parameters:

df (pandas.DataFrame) – Data frame containing information about peak loads

Returns:

pandas.DataFrame – Data frame with an additional column with voltage level

insert_osm_ind_load()

Inserts electrical industry loads assigned to osm landuse areas to the database.

Returns:

None.

insert_sites_ind_load()

Inserts electrical industry loads assigned to osm landuse areas to the database.

Returns:

None.