edisgo.io.timeseries_import

Module Contents

Functions

feedin_oedb(config_data, weather_cell_ids, timeindex)

Import feed-in time series data for wind and solar power plants from the

load_time_series_demandlib(config_data, timeindex)

Get normalized sectoral electricity load time series using the

cop_oedb(config_data[, weather_cell_ids, timeindex])

Get COP (coefficient of performance) time series data from the

heat_demand_oedb(config_data, building_ids[, timeindex])

Get heat demand time series data from the
edisgo.io.timeseries_import.feedin_oedb(config_data, weather_cell_ids, timeindex)[source]

Import feed-in time series data for wind and solar power plants from the OpenEnergy DataBase.

Parameters

  • config_data (Config) – Configuration data from config files, relevant for information of which data base table to retrieve feed-in data from.

  • weather_cell_ids (list(int)) – List of weather cell id’s (integers) to obtain feed-in data for.

  • timeindex (pandas.DatetimeIndex) – Feed-in data is currently only provided for weather year 2011. If timeindex contains a different year, the data is reindexed.

Returns

DataFrame with hourly time series for active power feed-in per generator type (wind or solar, in column level 0) and weather cell (in column level 1), normalized to a capacity of 1 MW.

Return type

pandas.DataFrame

edisgo.io.timeseries_import.load_time_series_demandlib(config_data, timeindex)[source]

Get normalized sectoral electricity load time series using the demandlib.

Resulting electricity load profiles hold time series of hourly conventional electricity demand for the sectors residential, retail, agricultural and industrial. Time series are normalized to a consumption of 1 MWh per year.

Parameters

  • config_data (Config) – Configuration data from config files, relevant for industrial load profiles.

  • timeindex (pandas.DatetimeIndex) – Timesteps for which to generate load time series.

Returns

DataFrame with conventional electricity load time series for sectors residential, retail, agricultural and industrial. Index is a pandas.DatetimeIndex. Columns hold the sector type.

Return type

pandas.DataFrame

edisgo.io.timeseries_import.cop_oedb(config_data, weather_cell_ids=None, timeindex=None)[source]

Get COP (coefficient of performance) time series data from the OpenEnergy DataBase.

Parameters

  • config_data (Config) – Configuration data from config files, relevant for information of which data base table to retrieve COP data from.

  • weather_cell_ids (list(int)) – List of weather cell id’s (integers) to obtain COP data for.

  • timeindex (pandas.DatetimeIndex) – COP data is only provided for the weather year 2011. If timeindex contains a different year, the data is reindexed.

Returns

DataFrame with hourly COP time series in p.u. per weather cell.

Return type

pandas.DataFrame

edisgo.io.timeseries_import.heat_demand_oedb(config_data, building_ids, timeindex=None)[source]

Get heat demand time series data from the OpenEnergy DataBase.

Parameters

  • config_data (Config) – Configuration data from config files, relevant for information of which data base table to retrieve data from.

  • building_ids (list(int)) – List of building IDs to obtain heat demand for.

  • timeindex (pandas.DatetimeIndex) – Heat demand data is only provided for the weather year 2011. If timeindex contains a different year, the data is reindexed.

Returns

DataFrame with hourly heat demand time series in MW per building ID.

Return type

pandas.DataFrame