temporal

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

calc_load_curves_ind_osm(scenario)[source]

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)[source]

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)[source]

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)[source]

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()[source]

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

Returns:None.
insert_sites_ind_load()[source]

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

Returns:None.