Build solar thermal profiles

Build solar thermal profiles for heating demand modeling.

This module generates solar thermal collector profiles and heat demand time series for residential and commercial sectors in the PyPSA-China energy system model.

build_solar_thermal_profiles(pop_map, cutout, outp_path)

Build per unit solar thermal time availability profiles and save them to a file

Parameters:

Name	Type	Description	Default
pop_map	DataFrame	DataFrame with the population map	required
cutout	Cutout	atlite cutout object with the weather data	required
outp_path	PathLike	Path to the output file	required

Source code in workflow/scripts/build_solar_thermal_profiles.py

def build_solar_thermal_profiles(
    pop_map: pd.DataFrame, cutout: atlite.Cutout, outp_path: os.PathLike
) -> None:
    """Build per unit solar thermal time availability profiles and save them to a file

    Args:
        pop_map (pd.DataFrame): DataFrame with the population map
        cutout (atlite.Cutout): atlite cutout object with the weather data
        outp_path (os.PathLike): Path to the output file
    """
    pop_matrix = sp.sparse.csr_matrix(pop_map.T)
    index = pop_map.columns
    index.name = "provinces"

    st = cutout.solar_thermal(
        orientation={
            "slope": float(snakemake.config["solar_thermal_angle"]),
            "azimuth": 180.0,
        },
        matrix=pop_matrix,
        index=index,
    )

    st["time"] = (
        pd.DatetimeIndex(st["time"], tz="UTC").tz_convert(TIMEZONE).tz_localize(None).values
    )

    with pd.HDFStore(outp_path, mode="w", complevel=4) as store:
        store["solar_thermal_profiles"] = st.to_pandas().divide(pop_map.sum())