pvcompare.demand.calculate_heat_demand¶
- pvcompare.demand.calculate_heat_demand(country, lat, lon, storeys, year, weather, column, static_inputs_directory=None, user_inputs_pvcompare_directory=None, user_inputs_mvs_directory=None)[source]¶
Calculates heat demand profile for storeys, country, year.
The heat demand of either space heating or space heating and warm water is calculated for a given number of houses with a given number of storeys in a certain country and year. In order to take heat demand from warm water into account the parameter include warm water in pvcompare’s input file ‘building_parameters.csv’ is set to True.
For further information regarding the calculation of the heat demand profile see Heat demand.
- Parameters
country (str) – The country’s name has to be in English and with capital first letter.
storeys (int) – Number of storeys of the houses.
year (int) – Year for which heat demand time series is calculated. Year can be chosen between 2008 and 2018.
column (str) – name of the demand
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) – Directory of the 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 input directory containing files that describe the energy system and that are an input to MVS. If None, constants.DEFAULT_USER_INPUTS_MVS_DIRECTORY is used. Default: None.
- Returns
shifted_heat_demand – Hourly heat demand time series.
- Return type