data.datasets.storages.allocate_pumped_hydro_eGon2035()

Complexity

Conditions

4

Size

Total Lines	180
Code Lines	98

Duplication

Lines	0
Ratio	0 %

Importance

Changes

0

"""The central module containing all code dealing with power plant data.
        f"""DROP TABLE IF EXISTS
        {cfg['target']['schema']}.{cfg['target']['table']}"""
    )

    db.execute_sql("""DROP SEQUENCE IF EXISTS pp_seq""")
    EgonStorages.__table__.create(bind=engine, checkfirst=True)


def allocate_pumped_hydro(scn, export=True):
    """Allocates pumped_hydro plants for eGon2035 and scenario2019 scenarios
    and either exports results to data base or returns as a dataframe

    Parameters
    ----------
    export : bool
        Choose if allocated pumped hydro plants should be exported to the data
        base. The default is True.
        If export=False a data frame will be returned

    Returns
    -------
    power_plants : pandas.DataFrame
        List of pumped hydro plants in 'eGon2035' and 'scenario2019' scenarios
    """

    carrier = "pumped_hydro"

    cfg = config.datasets()["power_plants"]

    nep = select_nep_pumped_hydro(scn=scn)
    mastr = select_mastr_pumped_hydro()

    # Assign voltage level to MaStR
    mastr["voltage_level"] = assign_voltage_level(
        mastr.rename({"el_capacity": "Nettonennleistung"}, axis=1),
        cfg,
        WORKING_DIR_MASTR_OLD,
    )

    # Initalize DataFrame for matching power plants
    matched = gpd.GeoDataFrame(
        columns=[
            "carrier",
            "el_capacity",
            "scenario",
            "geometry",
            "MaStRNummer",
            "source",
            "voltage_level",
        ]
    )

    # Match pumped_hydro units from NEP list
    # using PLZ and capacity
    matched, mastr, nep = match_storage_units(
        nep,
        mastr,
        matched,
        buffer_capacity=0.1,
        consider_carrier=False,
        scn=scn,
    )

    # Match plants from NEP list using plz,
    # neglecting the capacity
    matched, mastr, nep = match_storage_units(
        nep,
        mastr,
        matched,
        consider_location="plz",
        consider_carrier=False,
        consider_capacity=False,
        scn=scn,
    )

    # Match plants from NEP list using city,
    # neglecting the capacity
    matched, mastr, nep = match_storage_units(
        nep,
        mastr,
        matched,
        consider_location="city",
        consider_carrier=False,
        consider_capacity=False,
        scn=scn,
    )

    # Match remaining plants from NEP using the federal state
    matched, mastr, nep = match_storage_units(
        nep,
        mastr,
        matched,
        buffer_capacity=0.1,
        consider_location="federal_state",
        consider_carrier=False,
        scn=scn,
    )

    # Match remaining plants from NEP using the federal state
    matched, mastr, nep = match_storage_units(
        nep,
        mastr,
        matched,
        buffer_capacity=0.7,
        consider_location="federal_state",
        consider_carrier=False,
        scn=scn,
    )

    print(f"{matched.el_capacity.sum()} MW of {carrier} matched")
    print(f"{nep.elec_capacity.sum()} MW of {carrier} not matched")

    if nep.elec_capacity.sum() > 0:
        # Get location using geolocator and city information
        located, unmatched = get_location(nep)

        # Bring both dataframes together
        matched = pd.concat(
            [
                matched,
                located[
                    [
                        "carrier",
                        "el_capacity",
                        "scenario",
                        "geometry",
                        "source",
                        "MaStRNummer",
                    ]
                ],
            ],
            ignore_index=True,
        )

    # Set CRS
    matched.crs = "EPSG:4326"

    # Assign voltage level
    matched = apply_voltage_level_thresholds(matched)

    # Assign bus_id
    # Load grid district polygons
    mv_grid_districts = db.select_geodataframe(
        f"""
    SELECT * FROM {cfg['sources']['egon_mv_grid_district']}
    """,
        epsg=4326,
    )

    ehv_grid_districts = db.select_geodataframe(
        f"""
    SELECT * FROM {cfg['sources']['ehv_voronoi']}
    """,
        epsg=4326,
    )

    # Perform spatial joins for plants in ehv and hv level seperately
    power_plants_hv = gpd.sjoin(
        matched[matched.voltage_level >= 3],
        mv_grid_districts[["bus_id", "geom"]],
        how="left",
    ).drop(columns=["index_right"])
    power_plants_ehv = gpd.sjoin(
        matched[matched.voltage_level < 3],
        ehv_grid_districts[["bus_id", "geom"]],
        how="left",
    ).drop(columns=["index_right"])

    # Combine both dataframes
    power_plants = pd.concat([power_plants_hv, power_plants_ehv])

    # Delete existing units in the target table
    db.execute_sql(
        f""" DELETE FROM {cfg ['sources']['storages']}
        WHERE carrier IN ('pumped_hydro')
        AND scenario='{scn}';"""
    )

    # If export = True export pumped_hydro plants to data base

    if export: