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