pvcompare.demand.calculate_load_profiles

pvcompare.demand.calculate_load_profiles(country, lat, lon, storeys, year, weather, static_inputs_directory=None, user_inputs_pvcompare_directory=None, user_inputs_mvs_directory=None)[source]

Calculates electricity and heat load profiles for country, storeys, and year.

The electricity and heat load profiles are generated with the help of oemof.demandlib. For these calculations the electricity demand is calculated with the calculate_power_demand() functionality and the heat demand with the calculate_heat_demand() functionality.

Parameters

  • country (str) – The country’s name has to be in English and with capital first letter.

  • lat (float) – Latitude of country location in ‘country’.

  • lon (float) – Longitude of country location in ‘country’.

  • storeys (int) – The number of storeys of a building.

  • year (int) – Year for which power demand time series is calculated. Year can be chosen between 2008 and 2018.

  • weather (pandas.DataFrame) – hourly weather data frame with the columns: time, latitude, longitude, wind_speed, temp_air, ghi, dhi, dni, precipitable_water.

  • static_inputs_directory (str or None) – Path to pvcompare static inputs. If None, constants.DEFAULT_STATIC_INPUTS_DIRECTORY is used. Default: None.

  • user_inputs_pvcompare_directory (str or None) – Path to user input directory. If None, constants.DEFAULT_USER_INPUTS_PVCOMPARE_DIRECTORY is used. Default: None.

  • user_inputs_mvs_directory (str or None) – Path to MVS specific input directory. If None, constants.DEFAULT_USER_INPUTS_MVS_DIRECTORY is used. Default: None.

Returns

Return type

None