data.datasets.hydrogen_etrago.h2_grid.connect_h2_grid_to_neighbour_countries()

Complexity

Conditions

6

Size

Total Lines	169
Code Lines	102

Duplication

Lines	0
Ratio	0 %

Importance

Changes

0

"""
def connect_h2_grid_to_neighbour_countries(scn_name):
    """
    Connect germand H2_grid with neighbour countries. All german H2-Buses wich were planned as connection
    points for Import/Export of Hydrogen to corresponding neighbours country, are based on Publication
    of FNB-GAS (https://fnb-gas.de/wasserstoffnetz-wasserstoff-kernnetz/).

    Returns
    -------
    None

    """
    engine = db.engine()
    targets = config.datasets()["etrago_hydrogen"]["targets"]
    sources = config.datasets()["etrago_hydrogen"]["sources"]

    h2_buses_df = gpd.read_postgis(
        f"""
    SELECT bus_id, x, y, geom  
    FROM {sources["buses"]["schema"]}.{sources["buses"]["table"]}
    WHERE carrier in ('H2_grid')
    AND scn_name = '{scn_name}'

    """,
        engine,
    )

    h2_links_df = pd.read_sql(
        f"""
    SELECT link_id, bus0, bus1, p_nom 
    FROM {sources["links"]["schema"]}.{sources["links"]["table"]}
    WHERE carrier in ('H2_grid')
    AND scn_name = '{scn_name}'

    """,
        engine,
    )

    abroad_buses_df = gpd.read_postgis(
        f"""
        SELECT bus_id, x, y, geom, country 
        FROM {sources["buses"]["schema"]}.{sources["buses"]["table"]}
        WHERE carrier = 'H2' AND scn_name = '{scn_name}' AND country != 'DE'
        """,
        engine,
    )

    abroad_con_buses = [
        ("Greifenhagen", "PL"),
        ("Fürstenberg (PL)", "PL"),
        ("Eynatten", "BE"),
        ("Überackern", "AT"),
        ("Vlieghuis", "NL"),
        ("Oude", "NL"),
        ("Oude Statenzijl", "NL"),
        ("Vreden", "NL"),
        ("Elten", "NL"),
        ("Leidingen", "FR"),
        ("Carling", "FR"),
        ("Medelsheim", "FR"),
        ("Waidhaus", "CZ"),
        ("Deutschneudorf", "CZ"),
        ("Grenzach", "CH"),
        ("AWZ", "DK"),
        ("AWZ", "SE"),
        ("AQD Offshore SEN 1", "GB"),
        ("AQD Offshore SEN 1", "NO"),
        ("AQD Offshore SEN 1", "DK"),
        ("AQD Offshore SEN 1", "NL"),
        ("Fessenheim", "FR"),
        ("Ellund", "DK"),
    ]

    h2_bus_location = pd.read_csv(
        Path(".")
        / "data_bundle_egon_data"
        / "hydrogen_network"
        / "h2_grid_nodes.csv"
    )

    ### prepare data for connecting abroad_buses
    matched_locations = h2_bus_location[
        h2_bus_location["Ort"].isin([name for name, _ in abroad_con_buses])
    ]
    matched_buses = matched_locations.merge(
        h2_buses_df, left_on=["x", "y"], right_on=["x", "y"], how="inner"
    )

    final_matched_buses = matched_buses[
        ["bus_id", "Ort", "x", "y", "geom_y"]
    ].rename(columns={"geom_y": "geom"})

    abroad_links = h2_links_df[
        (h2_links_df["bus0"].isin(final_matched_buses["bus_id"]))
        | (h2_links_df["bus1"].isin(final_matched_buses["bus_id"]))
    ]
    abroad_links_bus0 = abroad_links.merge(
        final_matched_buses, left_on="bus0", right_on="bus_id", how="inner"
    )
    abroad_links_bus1 = abroad_links.merge(
        final_matched_buses, left_on="bus1", right_on="bus_id", how="inner"
    )
    abroad_con_df = pd.concat([abroad_links_bus1, abroad_links_bus0])

    connection_links = []

    for inland_name, country_code in abroad_con_buses:
        # filter out germand h2_buses for connecting neighbour-countries
        inland_bus = abroad_con_df[abroad_con_df["Ort"] == inland_name]
        if inland_bus.empty:
            print(f"Warning: No Inland-Bus found for {inland_name}.")
            continue

        # filter out corresponding abroad_bus for connecting neighbour countries
        abroad_bus = abroad_buses_df[
            abroad_buses_df["country"] == country_code
        ]
        if abroad_bus.empty:
            print(f"Warning: No Abroad-Bus found for {country_code}.")
            continue

        for _, i_bus in inland_bus.iterrows():
            abroad_bus["distance"] = abroad_bus["geom"].apply(
                lambda g: i_bus["geom"].distance(g)

The variable i_bus does not seem to be defined for all execution paths.

            )

            nearest_abroad_bus = abroad_bus.loc[
                abroad_bus["distance"].idxmin()
            ]
            relevant_buses = inland_bus[
                inland_bus["bus_id"] == i_bus["bus_id"]
            ]
            p_nom_value = relevant_buses["p_nom"].sum()

        connection_links.append(
            {
                "scn_name": scn_name,
                "carrier": "H2_grid",
                "link_id": db.next_etrago_id("link"),
                "bus0": i_bus["bus_id"],

The variable i_bus does not seem to be defined for all execution paths.

                "bus1": nearest_abroad_bus["bus_id"],

The variable nearest_abroad_bus does not seem to be defined for all execution paths.

                "p_nom": p_nom_value,

The variable p_nom_value does not seem to be defined for all execution paths.

                "p_min_pu": -1,
                "geom": MultiLineString(
                    [
                        LineString(
                            [
                                (i_bus["geom"].x, i_bus["geom"].y),
                                (
                                    nearest_abroad_bus["geom"].x,
                                    nearest_abroad_bus["geom"].y,
                                ),
                            ]
                        )
                    ]
                ),
            }
        )
    connection_links_df = gpd.GeoDataFrame(
        connection_links, geometry="geom", crs="EPSG:4326"
    )

    connection_links_df.to_postgis(
        name=targets["hydrogen_links"]["table"],
        con=engine,
        schema=targets["hydrogen_links"]["schema"],
        if_exists="append",
        index=False,
    )
    print("Neighbour countries are succesfully connected to H2-grid")