data.datasets.heat_etrago.power_to_heat.assign_electrical_bus() - Code Metrics - Inspection of "Release v2.0.0" - openego/eGon-data - Measure and Improve Code Quality continuously with Scrutinizer

Passed

Pull Request — dev (#1348)

unknown

created 2025-08-20 07:20 UTC

assign_electrical_bus() C

↳ Parent: data.datasets.heat_etrago.power_to_heat

Complexity

Conditions

Size

Total Lines	197
Code Lines	86

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
eloc	86
dl	0
loc	197
rs	6.9915
c	0
b	0
f	0
cc	5
nop	4

How to fix Long Method

"""The central module containing all code dealing with power to heat
"""

from shapely.geometry import LineString
import geopandas as gpd
import pandas as pd

from egon.data import config, db
from egon.data.datasets.scenario_parameters import get_sector_parameters


def insert_individual_power_to_heat(scenario):
    """Insert power to heat into database

    Parameters
    ----------
    scenario : str, optional
        Name of the scenario.

    Returns
    -------
    None.

    """

    sources = config.datasets()["etrago_heat"]["sources"]
    targets = config.datasets()["etrago_heat"]["targets"]

    # Delete existing entries
    db.execute_sql(
        f"""
        DELETE FROM {targets['heat_link_timeseries']['schema']}.
        {targets['heat_link_timeseries']['table']}
        WHERE link_id IN (
            SELECT link_id FROM {targets['heat_links']['schema']}.
        {targets['heat_links']['table']}
        WHERE carrier IN ('individual_heat_pump', 'rural_heat_pump',
                          'rural_resisitive_heater')
        AND scn_name = '{scenario}')
        AND scn_name = '{scenario}'
        """
    )
    db.execute_sql(
        f"""
        DELETE FROM {targets['heat_links']['schema']}.
        {targets['heat_links']['table']}
        WHERE carrier IN ('individual_heat_pump', 'rural_heat_pump',
                          'rural_resisitive_heater')
        AND bus0 IN 
        (SELECT bus_id 
         FROM {targets['heat_buses']['schema']}.
         {targets['heat_buses']['table']}
         WHERE scn_name = '{scenario}'
         AND country = 'DE')
        AND bus1 IN 
        (SELECT bus_id 
         FROM {targets['heat_buses']['schema']}.
         {targets['heat_buses']['table']}
         WHERE scn_name = '{scenario}'
         AND country = 'DE')
        """
    )

    # Select heat pumps for individual heating
    heat_pumps = db.select_dataframe(
        f"""
        SELECT mv_grid_id as power_bus,
        a.carrier, capacity, b.bus_id as heat_bus, d.feedin as cop
        FROM {sources['individual_heating_supply']['schema']}.
            {sources['individual_heating_supply']['table']} a
        JOIN {targets['heat_buses']['schema']}.
        {targets['heat_buses']['table']} b
        ON ST_Intersects(
            ST_Buffer(ST_Transform(ST_Centroid(a.geometry), 4326), 0.00000001),
            geom)
        JOIN {sources['weather_cells']['schema']}.
            {sources['weather_cells']['table']} c
        ON ST_Intersects(
            b.geom, c.geom)
        JOIN {sources['feedin_timeseries']['schema']}.
            {sources['feedin_timeseries']['table']} d
        ON c.w_id = d.w_id
        WHERE scenario = '{scenario}'
        AND scn_name  = '{scenario}'
        AND a.carrier = 'heat_pump'
        AND b.carrier = 'rural_heat'
        AND d.carrier = 'heat_pump_cop'
        """
    )

    # Assign voltage level
    heat_pumps["voltage_level"] = 7

    # Set marginal_cost
    heat_pumps["marginal_cost"] = get_sector_parameters("heat", scenario)[
        "marginal_cost"
    ]["rural_heat_pump"]

    # Insert heatpumps
    insert_power_to_heat_per_level(
        heat_pumps,
        carrier="rural_heat_pump",
        multiple_per_mv_grid=False,
        scenario=scenario,
    )

    # Deal with rural resistive heaters
    # Select resisitve heaters for individual heating
    resistive_heaters = db.select_dataframe(
        f"""
        SELECT mv_grid_id as power_bus,
        a.carrier, capacity, b.bus_id as heat_bus
        FROM {sources['individual_heating_supply']['schema']}.
            {sources['individual_heating_supply']['table']} a
        JOIN {targets['heat_buses']['schema']}.
        {targets['heat_buses']['table']} b
        ON ST_Intersects(
            ST_Buffer(ST_Transform(ST_Centroid(a.geometry), 4326), 0.00000001),
            geom)
        WHERE scenario = '{scenario}'
        AND scn_name  = '{scenario}'
        AND a.carrier = 'resistive_heater'
        AND b.carrier = 'rural_heat'
        """
    )

    if resistive_heaters.empty:
        print(f"No rural resistive heaters in scenario {scenario}.")
    else:
        # Assign voltage level
        resistive_heaters["voltage_level"] = 7

        # Set marginal_cost
        resistive_heaters["marginal_cost"] = 0

        # Insert heatpumps
        insert_power_to_heat_per_level(
            resistive_heaters,
            carrier="rural_resistive_heater",
            multiple_per_mv_grid=False,
            scenario=scenario,
        )


def insert_central_power_to_heat(scenario):
    """Insert power to heat in district heating areas into database

    Parameters
    ----------
    scenario : str
        Name of the scenario.

    Returns
    -------
    None.

    """

    sources = config.datasets()["etrago_heat"]["sources"]
    targets = config.datasets()["etrago_heat"]["targets"]

    # Delete existing entries
    db.execute_sql(
        f"""
        DELETE FROM {targets['heat_link_timeseries']['schema']}.
        {targets['heat_link_timeseries']['table']}
        WHERE link_id IN (
            SELECT link_id FROM {targets['heat_links']['schema']}.
        {targets['heat_links']['table']}
        WHERE carrier = 'central_heat_pump'
        AND scn_name = '{scenario}')
        AND scn_name = '{scenario}'
        """
    )

    db.execute_sql(
        f"""
        DELETE FROM {targets['heat_links']['schema']}.
        {targets['heat_links']['table']}
        WHERE carrier = 'central_heat_pump'
        AND bus0 IN 
        (SELECT bus_id 
         FROM {targets['heat_buses']['schema']}.
         {targets['heat_buses']['table']}
         WHERE scn_name = '{scenario}'
         AND country = 'DE')
        AND bus1 IN 
        (SELECT bus_id 
         FROM {targets['heat_buses']['schema']}.
         {targets['heat_buses']['table']}
         WHERE scn_name = '{scenario}'
         AND country = 'DE')
        """
    )

    # Select heat pumps in district heating
    central_heat_pumps = db.select_geodataframe(
        f"""
        SELECT a.index, a.district_heating_id, a.carrier, a.category, a.capacity, a.geometry, a.scenario, d.feedin as cop 
        FROM {sources['district_heating_supply']['schema']}.
            {sources['district_heating_supply']['table']} a
        JOIN {sources['weather_cells']['schema']}.
            {sources['weather_cells']['table']} c
        ON ST_Intersects(
            ST_Transform(a.geometry, 4326), c.geom)
        JOIN {sources['feedin_timeseries']['schema']}.
            {sources['feedin_timeseries']['table']} d
        ON c.w_id = d.w_id
        WHERE scenario = '{scenario}'
        AND a.carrier = 'heat_pump'
        AND d.carrier = 'heat_pump_cop'
        """,
        geom_col="geometry",
        epsg=4326,
    )

    # Assign voltage level
    central_heat_pumps = assign_voltage_level(
        central_heat_pumps, carrier="heat_pump"
    )

    # Set marginal_cost
    central_heat_pumps["marginal_cost"] = get_sector_parameters(
        "heat", scenario
    )["marginal_cost"]["central_heat_pump"]

    # Insert heatpumps in mv and below
    # (one hvmv substation per district heating grid)
    insert_power_to_heat_per_level(
        central_heat_pumps[central_heat_pumps.voltage_level > 3],
        multiple_per_mv_grid=False,
        carrier="central_heat_pump",
        scenario=scenario,
    )
    # Insert heat pumps in hv grid
    # (as many hvmv substations as intersect with district heating grid)
    insert_power_to_heat_per_level(
        central_heat_pumps[central_heat_pumps.voltage_level < 3],
        multiple_per_mv_grid=True,
        carrier="central_heat_pump",
        scenario=scenario,
    )

    # Delete existing entries
    db.execute_sql(
        f"""
        DELETE FROM {targets['heat_links']['schema']}.
        {targets['heat_links']['table']}
        WHERE carrier = 'central_resistive_heater'
        AND bus0 IN 
        (SELECT bus_id 
         FROM {targets['heat_buses']['schema']}.
         {targets['heat_buses']['table']}
         WHERE scn_name = '{scenario}'
         AND country = 'DE')
        AND bus1 IN 
        (SELECT bus_id 
         FROM {targets['heat_buses']['schema']}.
         {targets['heat_buses']['table']}
         WHERE scn_name = '{scenario}'
         AND country = 'DE')
        """
    )
    # Select heat pumps in district heating
    central_resistive_heater = db.select_geodataframe(
        f"""
        SELECT district_heating_id, carrier, category, SUM(capacity) as capacity, 
               geometry, scenario
        FROM {sources['district_heating_supply']['schema']}.
            {sources['district_heating_supply']['table']}
        WHERE scenario = '{scenario}'
        AND carrier = 'resistive_heater'
        GROUP BY (district_heating_id, carrier, category, geometry, scenario)
        """,
        geom_col="geometry",
        epsg=4326,
    )

    # Assign voltage level
    central_resistive_heater = assign_voltage_level(
        central_resistive_heater, carrier="resistive_heater"
    )

    # Set efficiency
    central_resistive_heater["efficiency"] = get_sector_parameters(
        "heat", scenario
    )["efficiency"]["central_resistive_heater"]

    # Insert heatpumps in mv and below
    # (one hvmv substation per district heating grid)
    if (
        len(
            central_resistive_heater[
                central_resistive_heater.voltage_level > 3
            ]
        )
        > 0
    ):
        insert_power_to_heat_per_level(
            central_resistive_heater[
                central_resistive_heater.voltage_level > 3
            ],
            multiple_per_mv_grid=False,
            carrier="central_resistive_heater",
            scenario=scenario,
        )
    # Insert heat pumps in hv grid
    # (as many hvmv substations as intersect with district heating grid)
    insert_power_to_heat_per_level(
        central_resistive_heater[central_resistive_heater.voltage_level < 3],
        multiple_per_mv_grid=True,
        carrier="central_resistive_heater",
        scenario=scenario,
    )


def insert_power_to_heat_per_level(
    heat_pumps,
    multiple_per_mv_grid,
    carrier,
    scenario,
):
    """Insert power to heat plants per grid level

    Parameters
    ----------
    heat_pumps : pandas.DataFrame
        Heat pumps in selected grid level
    multiple_per_mv_grid : boolean
        Choose if one district heating areas is supplied by one hvmv substation
    scenario : str
        Name of the scenario.

    Returns
    -------
    None.

    """
    sources = config.datasets()["etrago_heat"]["sources"]
    targets = config.datasets()["etrago_heat"]["targets"]

    if "central" in carrier:
        # Calculate heat pumps per electrical bus
        gdf = assign_electrical_bus(
            heat_pumps, carrier, scenario, multiple_per_mv_grid
        )

    else:
        gdf = heat_pumps.copy()

    # Select geometry of buses
    geom_buses = db.select_geodataframe(
        f"""
        SELECT bus_id, geom FROM {targets['heat_buses']['schema']}.
        {targets['heat_buses']['table']}
        WHERE scn_name = '{scenario}'
        """,
        index_col="bus_id",
        epsg=4326,
    )

    # Create topology of heat pumps
    gdf["geom_power"] = geom_buses.geom[gdf.power_bus].values
    gdf["geom_heat"] = geom_buses.loc[gdf.heat_bus, "geom"].reset_index().geom
    gdf["geometry"] = gdf.apply(
        lambda x: LineString([x["geom_power"], x["geom_heat"]]), axis=1
    )

    # Choose next unused link id
    next_link_id = db.next_etrago_id("link")

    # Initilize dataframe of links
    links = (
        gpd.GeoDataFrame(
            index=range(len(gdf)),
            columns=[
                "scn_name",
                "bus0",
                "bus1",
                "carrier",
                "link_id",
                "p_nom",
                "topo",
            ],
            data={"scn_name": scenario, "carrier": carrier},
        )
        .set_geometry("topo")
        .set_crs(epsg=4326)
    )

    # Insert values into dataframe
    links.bus0 = gdf.power_bus.values.astype(int)
    links.bus1 = gdf.heat_bus.values
    links.p_nom = gdf.capacity.values
    links.topo = gdf.geometry.values
    links.link_id = range(next_link_id, next_link_id + len(links))

    # Insert data into database
    links.to_postgis(
        targets["heat_links"]["table"],
        schema=targets["heat_links"]["schema"],
        if_exists="append",
        con=db.engine(),
    )

    if "cop" in gdf.columns:

        # Create dataframe for time-dependent data
        links_timeseries = pd.DataFrame(
            index=links.index,
            data={
                "link_id": links.link_id,
                "efficiency": gdf.cop,
                "scn_name": scenario,
                "temp_id": 1,
            },
        )

        # Insert time-dependent data to database
        links_timeseries.to_sql(
            targets["heat_link_timeseries"]["table"],
            schema=targets["heat_link_timeseries"]["schema"],
            if_exists="append",
            con=db.engine(),
            index=False,
        )


def assign_voltage_level(heat_pumps, carrier="heat_pump"):
    """Assign voltage level to heat pumps

    Parameters
    ----------
    heat_pumps : pandas.DataFrame
        Heat pumps without voltage level

    Returns
    -------
    heat_pumps : pandas.DataFrame
        Heat pumps including voltage level

    """

    # set voltage level for heat pumps according to category
    heat_pumps["voltage_level"] = 0

    heat_pumps.loc[
        heat_pumps[
            (heat_pumps.carrier == carrier) & (heat_pumps.category == "small")
        ].index,
        "voltage_level",
    ] = 7

    heat_pumps.loc[
        heat_pumps[
            (heat_pumps.carrier == carrier) & (heat_pumps.category == "medium")
        ].index,
        "voltage_level",
    ] = 5

    heat_pumps.loc[
        heat_pumps[
            (heat_pumps.carrier == carrier) & (heat_pumps.category == "large")
        ].index,
        "voltage_level",
    ] = 1

    # if capacity > 5.5 MW, heatpump is installed in HV
    heat_pumps.loc[
        heat_pumps[
            (heat_pumps.carrier == carrier) & (heat_pumps.capacity > 5.5)
        ].index,
        "voltage_level",
    ] = 1

    return heat_pumps


def assign_electrical_bus(
    heat_pumps, carrier, scenario, multiple_per_mv_grid=False
):
    """Calculates heat pumps per electrical bus

    Parameters
    ----------
    heat_pumps : pandas.DataFrame
        Heat pumps including voltage level
    multiple_per_mv_grid : boolean, optional
        Choose if a district heating area can by supplied by multiple
        hvmv substaions/mv grids. The default is False.

    Returns
    -------
    gdf : pandas.DataFrame
        Heat pumps per electrical bus

    """

    sources = config.datasets()["etrago_heat"]["sources"]
    targets = config.datasets()["etrago_heat"]["targets"]

    # Map heat buses to district heating id and area_id
    heat_buses = db.select_dataframe(
        f"""
        SELECT bus_id, area_id, id FROM
        {targets['heat_buses']['schema']}.
        {targets['heat_buses']['table']}
        JOIN {sources['district_heating_areas']['schema']}.
            {sources['district_heating_areas']['table']}
        ON ST_Intersects(
        ST_Transform(ST_Buffer(
        ST_Centroid(geom_polygon), 0.0000001), 4326), geom)
        WHERE carrier = 'central_heat'
        AND scenario='{scenario}'
        AND scn_name = '{scenario}'
        """,
        index_col="id",
    )

    heat_pumps["power_bus"] = ""

    # Select mv grid distrcits
    mv_grid_district = db.select_geodataframe(
        f"""
        SELECT bus_id, geom FROM
        {sources['egon_mv_grid_district']['schema']}.
        {sources['egon_mv_grid_district']['table']}
        """,
        epsg=4326,
    )

    # Map zensus cells to district heating areas
    map_zensus_dh = db.select_geodataframe(
        f"""
        SELECT area_id, a.zensus_population_id,
        geom_point as geom, sum(a.demand) as demand
        FROM {sources['map_district_heating_areas']['schema']}.
            {sources['map_district_heating_areas']['table']} b
        JOIN {sources['heat_demand']['schema']}.
            {sources['heat_demand']['table']} a
        ON b.zensus_population_id = a.zensus_population_id
        JOIN society.destatis_zensus_population_per_ha
        ON society.destatis_zensus_population_per_ha.id =
        a.zensus_population_id
        WHERE a.scenario = '{scenario}'
        AND b.scenario = '{scenario}'
        GROUP BY (area_id, a.zensus_population_id, geom_point)
        """,
        epsg=4326,
    )

    # Select area_id per heat pump
    heat_pumps["area_id"] = heat_buses.area_id[
        heat_pumps.district_heating_id.values
    ].values

    heat_buses.set_index("area_id", inplace=True)

    # Select only cells in choosen district heating areas
    cells = map_zensus_dh[map_zensus_dh.area_id.isin(heat_pumps.area_id)]

    # Assign power bus per zensus cell
    cells["power_bus"] = gpd.sjoin(
        cells, mv_grid_district, how="inner", op="intersects"
    ).bus_id

    # Calclate district heating demand per substaion
    demand_per_substation = pd.DataFrame(
        cells.groupby(["area_id", "power_bus"]).demand.sum()
    )

    heat_pumps.set_index("area_id", inplace=True)

    # If district heating areas are supplied by multiple hvmv-substations,
    # create one heatpump per electrical bus.
    # The installed capacity is assigned regarding the share of heat demand.
    if multiple_per_mv_grid:

        power_to_heat = demand_per_substation.reset_index()

        power_to_heat["carrier"] = carrier

        power_to_heat.loc[:, "voltage_level"] = heat_pumps.voltage_level[
            power_to_heat.area_id
        ].values

        if "heat_pump" in carrier:

            power_to_heat.loc[:, "cop"] = heat_pumps.cop[
                power_to_heat.area_id
            ].values

        power_to_heat["share_demand"] = (
            power_to_heat.groupby("area_id")
            .demand.apply(lambda grp: grp / grp.sum())
            .values
        )

        power_to_heat["capacity"] = power_to_heat["share_demand"].mul(
            heat_pumps.capacity[power_to_heat.area_id].values
        )

        power_to_heat = power_to_heat[power_to_heat.voltage_level.notnull()]

        gdf = gpd.GeoDataFrame(
            power_to_heat,
            index=power_to_heat.index,
            geometry=heat_pumps.geometry[power_to_heat.area_id].values,
        )

    # If district heating areas are supplied by one hvmv-substations,
    # the hvmv substation which has the most heat demand is choosen.
    else:

        substation_max_demand = (
            demand_per_substation.reset_index()
            .set_index("power_bus")
            .groupby("area_id")
            .demand.max()
        )

        selected_substations = (
            demand_per_substation[
                demand_per_substation.demand.isin(substation_max_demand)
            ]
            .reset_index()
            .set_index("area_id")
        )

        selected_substations.rename(
            {"demand": "demand_selected_substation"}, axis=1, inplace=True
        )

        selected_substations["share_demand"] = (
            cells.groupby(["area_id", "power_bus"])
            .demand.sum()
            .reset_index()
            .groupby("area_id")
            .demand.max()
            / cells.groupby(["area_id", "power_bus"])
            .demand.sum()
            .reset_index()
            .groupby("area_id")
            .demand.sum()
        )

        power_to_heat = selected_substations

        power_to_heat["carrier"] = carrier

        power_to_heat.loc[:, "voltage_level"] = heat_pumps.voltage_level

        if "heat_pump" in carrier:

            power_to_heat.loc[:, "cop"] = heat_pumps.cop

        power_to_heat["capacity"] = heat_pumps.capacity[
            power_to_heat.index
        ].values

        power_to_heat = power_to_heat[power_to_heat.voltage_level.notnull()]

        gdf = gpd.GeoDataFrame(
            power_to_heat,
            index=power_to_heat.index,
            geometry=heat_pumps.geometry,
        )

    gdf.reset_index(inplace=True)

    gdf["heat_bus"] = (
        heat_buses.loc[gdf.area_id, "bus_id"].reset_index().bus_id
    )

    return gdf


1			"""The central module containing all code dealing with power to heat
2			"""
3
4			from shapely.geometry import LineString
5			import geopandas as gpd
6			import pandas as pd
7
8			from egon.data import config, db
9			from egon.data.datasets.scenario_parameters import get_sector_parameters
10
11
12			def insert_individual_power_to_heat(scenario):
13			"""Insert power to heat into database
14
15			Parameters
16			----------
17			scenario : str, optional
18			Name of the scenario.
19
20			Returns
21			-------
22			None.
23
24			"""
25
26			sources = config.datasets()["etrago_heat"]["sources"]
27			targets = config.datasets()["etrago_heat"]["targets"]
28
29			# Delete existing entries
30			db.execute_sql(
31			f"""
32			DELETE FROM {targets['heat_link_timeseries']['schema']}.
33			{targets['heat_link_timeseries']['table']}
34			WHERE link_id IN (
35			SELECT link_id FROM {targets['heat_links']['schema']}.
36			{targets['heat_links']['table']}
37			WHERE carrier IN ('individual_heat_pump', 'rural_heat_pump',
38			'rural_resisitive_heater')
39			AND scn_name = '{scenario}')
40			AND scn_name = '{scenario}'
41			"""
42			)
43			db.execute_sql(
44			f"""
45			DELETE FROM {targets['heat_links']['schema']}.
46			{targets['heat_links']['table']}
47			WHERE carrier IN ('individual_heat_pump', 'rural_heat_pump',
48			'rural_resisitive_heater')
49			AND bus0 IN
50			(SELECT bus_id
51			FROM {targets['heat_buses']['schema']}.
52			{targets['heat_buses']['table']}
53			WHERE scn_name = '{scenario}'
54			AND country = 'DE')
55			AND bus1 IN
56			(SELECT bus_id
57			FROM {targets['heat_buses']['schema']}.
58			{targets['heat_buses']['table']}
59			WHERE scn_name = '{scenario}'
60			AND country = 'DE')
61			"""
62			)
63
64			# Select heat pumps for individual heating
65			heat_pumps = db.select_dataframe(
66			f"""
67			SELECT mv_grid_id as power_bus,
68			a.carrier, capacity, b.bus_id as heat_bus, d.feedin as cop
69			FROM {sources['individual_heating_supply']['schema']}.
70			{sources['individual_heating_supply']['table']} a
71			JOIN {targets['heat_buses']['schema']}.
72			{targets['heat_buses']['table']} b
73			ON ST_Intersects(
74			ST_Buffer(ST_Transform(ST_Centroid(a.geometry), 4326), 0.00000001),
75			geom)
76			JOIN {sources['weather_cells']['schema']}.
77			{sources['weather_cells']['table']} c
78			ON ST_Intersects(
79			b.geom, c.geom)
80			JOIN {sources['feedin_timeseries']['schema']}.
81			{sources['feedin_timeseries']['table']} d
82			ON c.w_id = d.w_id
83			WHERE scenario = '{scenario}'
84			AND scn_name = '{scenario}'
85			AND a.carrier = 'heat_pump'
86			AND b.carrier = 'rural_heat'
87			AND d.carrier = 'heat_pump_cop'
88			"""
89			)
90
91			# Assign voltage level
92			heat_pumps["voltage_level"] = 7
93
94			# Set marginal_cost
95			heat_pumps["marginal_cost"] = get_sector_parameters("heat", scenario)[
96			"marginal_cost"
97			]["rural_heat_pump"]
98
99			# Insert heatpumps
100			insert_power_to_heat_per_level(
101			heat_pumps,
102			carrier="rural_heat_pump",
103			multiple_per_mv_grid=False,
104			scenario=scenario,
105			)
106
107			# Deal with rural resistive heaters
108			# Select resisitve heaters for individual heating
109			resistive_heaters = db.select_dataframe(
110			f"""
111			SELECT mv_grid_id as power_bus,
112			a.carrier, capacity, b.bus_id as heat_bus
113			FROM {sources['individual_heating_supply']['schema']}.
114			{sources['individual_heating_supply']['table']} a
115			JOIN {targets['heat_buses']['schema']}.
116			{targets['heat_buses']['table']} b
117			ON ST_Intersects(
118			ST_Buffer(ST_Transform(ST_Centroid(a.geometry), 4326), 0.00000001),
119			geom)
120			WHERE scenario = '{scenario}'
121			AND scn_name = '{scenario}'
122			AND a.carrier = 'resistive_heater'
123			AND b.carrier = 'rural_heat'
124			"""
125			)
126
127			if resistive_heaters.empty:
128			print(f"No rural resistive heaters in scenario {scenario}.")
129			else:
130			# Assign voltage level
131			resistive_heaters["voltage_level"] = 7
132
133			# Set marginal_cost
134			resistive_heaters["marginal_cost"] = 0
135
136			# Insert heatpumps
137			insert_power_to_heat_per_level(
138			resistive_heaters,
139			carrier="rural_resistive_heater",
140			multiple_per_mv_grid=False,
141			scenario=scenario,
142			)
143
144
145			def insert_central_power_to_heat(scenario):
146			"""Insert power to heat in district heating areas into database
147
148			Parameters
149			----------
150			scenario : str
151			Name of the scenario.
152
153			Returns
154			-------
155			None.
156
157			"""
158
159			sources = config.datasets()["etrago_heat"]["sources"]
160			targets = config.datasets()["etrago_heat"]["targets"]
161
162			# Delete existing entries
163			db.execute_sql(
164			f"""
165			DELETE FROM {targets['heat_link_timeseries']['schema']}.
166			{targets['heat_link_timeseries']['table']}
167			WHERE link_id IN (
168			SELECT link_id FROM {targets['heat_links']['schema']}.
169			{targets['heat_links']['table']}
170			WHERE carrier = 'central_heat_pump'
171			AND scn_name = '{scenario}')
172			AND scn_name = '{scenario}'
173			"""
174			)
175
176			db.execute_sql(
177			f"""
178			DELETE FROM {targets['heat_links']['schema']}.
179			{targets['heat_links']['table']}
180			WHERE carrier = 'central_heat_pump'
181			AND bus0 IN
182			(SELECT bus_id
183			FROM {targets['heat_buses']['schema']}.
184			{targets['heat_buses']['table']}
185			WHERE scn_name = '{scenario}'
186			AND country = 'DE')
187			AND bus1 IN
188			(SELECT bus_id
189			FROM {targets['heat_buses']['schema']}.
190			{targets['heat_buses']['table']}
191			WHERE scn_name = '{scenario}'
192			AND country = 'DE')
193			"""
194			)
195
196			# Select heat pumps in district heating
197			central_heat_pumps = db.select_geodataframe(
198			f"""
199			SELECT a.index, a.district_heating_id, a.carrier, a.category, a.capacity, a.geometry, a.scenario, d.feedin as cop
200			FROM {sources['district_heating_supply']['schema']}.
201			{sources['district_heating_supply']['table']} a
202			JOIN {sources['weather_cells']['schema']}.
203			{sources['weather_cells']['table']} c
204			ON ST_Intersects(
205			ST_Transform(a.geometry, 4326), c.geom)
206			JOIN {sources['feedin_timeseries']['schema']}.
207			{sources['feedin_timeseries']['table']} d
208			ON c.w_id = d.w_id
209			WHERE scenario = '{scenario}'
210			AND a.carrier = 'heat_pump'
211			AND d.carrier = 'heat_pump_cop'
212			""",
213			geom_col="geometry",
214			epsg=4326,
215			)
216
217			# Assign voltage level
218			central_heat_pumps = assign_voltage_level(
219			central_heat_pumps, carrier="heat_pump"
220			)
221
222			# Set marginal_cost
223			central_heat_pumps["marginal_cost"] = get_sector_parameters(
224			"heat", scenario
225			)["marginal_cost"]["central_heat_pump"]
226
227			# Insert heatpumps in mv and below
228			# (one hvmv substation per district heating grid)
229			insert_power_to_heat_per_level(
230			central_heat_pumps[central_heat_pumps.voltage_level > 3],
231			multiple_per_mv_grid=False,
232			carrier="central_heat_pump",
233			scenario=scenario,
234			)
235			# Insert heat pumps in hv grid
236			# (as many hvmv substations as intersect with district heating grid)
237			insert_power_to_heat_per_level(
238			central_heat_pumps[central_heat_pumps.voltage_level < 3],
239			multiple_per_mv_grid=True,
240			carrier="central_heat_pump",
241			scenario=scenario,
242			)
243
244			# Delete existing entries
245			db.execute_sql(
246			f"""
247			DELETE FROM {targets['heat_links']['schema']}.
248			{targets['heat_links']['table']}
249			WHERE carrier = 'central_resistive_heater'
250			AND bus0 IN
251			(SELECT bus_id
252			FROM {targets['heat_buses']['schema']}.
253			{targets['heat_buses']['table']}
254			WHERE scn_name = '{scenario}'
255			AND country = 'DE')
256			AND bus1 IN
257			(SELECT bus_id
258			FROM {targets['heat_buses']['schema']}.
259			{targets['heat_buses']['table']}
260			WHERE scn_name = '{scenario}'
261			AND country = 'DE')
262			"""
263			)
264			# Select heat pumps in district heating
265			central_resistive_heater = db.select_geodataframe(
266			f"""
267			SELECT district_heating_id, carrier, category, SUM(capacity) as capacity,
268			geometry, scenario
269			FROM {sources['district_heating_supply']['schema']}.
270			{sources['district_heating_supply']['table']}
271			WHERE scenario = '{scenario}'
272			AND carrier = 'resistive_heater'
273			GROUP BY (district_heating_id, carrier, category, geometry, scenario)
274			""",
275			geom_col="geometry",
276			epsg=4326,
277			)
278
279			# Assign voltage level
280			central_resistive_heater = assign_voltage_level(
281			central_resistive_heater, carrier="resistive_heater"
282			)
283
284			# Set efficiency
285			central_resistive_heater["efficiency"] = get_sector_parameters(
286			"heat", scenario
287			)["efficiency"]["central_resistive_heater"]
288
289			# Insert heatpumps in mv and below
290			# (one hvmv substation per district heating grid)
291			if (
292			len(
293			central_resistive_heater[
294			central_resistive_heater.voltage_level > 3
295			]
296			)
297			> 0
298			):
299			insert_power_to_heat_per_level(
300			central_resistive_heater[
301			central_resistive_heater.voltage_level > 3
302			],
303			multiple_per_mv_grid=False,
304			carrier="central_resistive_heater",
305			scenario=scenario,
306			)
307			# Insert heat pumps in hv grid
308			# (as many hvmv substations as intersect with district heating grid)
309			insert_power_to_heat_per_level(
310			central_resistive_heater[central_resistive_heater.voltage_level < 3],
311			multiple_per_mv_grid=True,
312			carrier="central_resistive_heater",
313			scenario=scenario,
314			)
315
316
317			def insert_power_to_heat_per_level(
318			heat_pumps,
319			multiple_per_mv_grid,
320			carrier,
321			scenario,
322			):
323			"""Insert power to heat plants per grid level
324
325			Parameters
326			----------
327			heat_pumps : pandas.DataFrame
328			Heat pumps in selected grid level
329			multiple_per_mv_grid : boolean
330			Choose if one district heating areas is supplied by one hvmv substation
331			scenario : str
332			Name of the scenario.
333
334			Returns
335			-------
336			None.
337
338			"""
339			sources = config.datasets()["etrago_heat"]["sources"]
340			targets = config.datasets()["etrago_heat"]["targets"]
341
342			if "central" in carrier:
343			# Calculate heat pumps per electrical bus
344			gdf = assign_electrical_bus(
345			heat_pumps, carrier, scenario, multiple_per_mv_grid
346			)
347
348			else:
349			gdf = heat_pumps.copy()
350
351			# Select geometry of buses
352			geom_buses = db.select_geodataframe(
353			f"""
354			SELECT bus_id, geom FROM {targets['heat_buses']['schema']}.
355			{targets['heat_buses']['table']}
356			WHERE scn_name = '{scenario}'
357			""",
358			index_col="bus_id",
359			epsg=4326,
360			)
361
362			# Create topology of heat pumps
363			gdf["geom_power"] = geom_buses.geom[gdf.power_bus].values
364			gdf["geom_heat"] = geom_buses.loc[gdf.heat_bus, "geom"].reset_index().geom
365			gdf["geometry"] = gdf.apply(
366			lambda x: LineString([x["geom_power"], x["geom_heat"]]), axis=1
367			)
368
369			# Choose next unused link id
370			next_link_id = db.next_etrago_id("link")
371
372			# Initilize dataframe of links
373			links = (
374			gpd.GeoDataFrame(
375			index=range(len(gdf)),
376			columns=[
377			"scn_name",
378			"bus0",
379			"bus1",
380			"carrier",
381			"link_id",
382			"p_nom",
383			"topo",
384			],
385			data={"scn_name": scenario, "carrier": carrier},
386			)
387			.set_geometry("topo")
388			.set_crs(epsg=4326)
389			)
390
391			# Insert values into dataframe
392			links.bus0 = gdf.power_bus.values.astype(int)
393			links.bus1 = gdf.heat_bus.values
394			links.p_nom = gdf.capacity.values
395			links.topo = gdf.geometry.values
396			links.link_id = range(next_link_id, next_link_id + len(links))
397
398			# Insert data into database
399			links.to_postgis(
400			targets["heat_links"]["table"],
401			schema=targets["heat_links"]["schema"],
402			if_exists="append",
403			con=db.engine(),
404			)
405
406			if "cop" in gdf.columns:
407
408			# Create dataframe for time-dependent data
409			links_timeseries = pd.DataFrame(
410			index=links.index,
411			data={
412			"link_id": links.link_id,
413			"efficiency": gdf.cop,
414			"scn_name": scenario,
415			"temp_id": 1,
416			},
417			)
418
419			# Insert time-dependent data to database
420			links_timeseries.to_sql(
421			targets["heat_link_timeseries"]["table"],
422			schema=targets["heat_link_timeseries"]["schema"],
423			if_exists="append",
424			con=db.engine(),
425			index=False,
426			)
427
428
429			def assign_voltage_level(heat_pumps, carrier="heat_pump"):
430			"""Assign voltage level to heat pumps
431
432			Parameters
433			----------
434			heat_pumps : pandas.DataFrame
435			Heat pumps without voltage level
436
437			Returns
438			-------
439			heat_pumps : pandas.DataFrame
440			Heat pumps including voltage level
441
442			"""
443
444			# set voltage level for heat pumps according to category
445			heat_pumps["voltage_level"] = 0
446
447			heat_pumps.loc[
448			heat_pumps[
449			(heat_pumps.carrier == carrier) & (heat_pumps.category == "small")
450			].index,
451			"voltage_level",
452			] = 7
453
454			heat_pumps.loc[
455			heat_pumps[
456			(heat_pumps.carrier == carrier) & (heat_pumps.category == "medium")
457			].index,
458			"voltage_level",
459			] = 5
460
461			heat_pumps.loc[
462			heat_pumps[
463			(heat_pumps.carrier == carrier) & (heat_pumps.category == "large")
464			].index,
465			"voltage_level",
466			] = 1
467
468			# if capacity > 5.5 MW, heatpump is installed in HV
469			heat_pumps.loc[
470			heat_pumps[
471			(heat_pumps.carrier == carrier) & (heat_pumps.capacity > 5.5)
472			].index,
473			"voltage_level",
474			] = 1
475
476			return heat_pumps
477
478
479			def assign_electrical_bus(
480			heat_pumps, carrier, scenario, multiple_per_mv_grid=False
481			):
482			"""Calculates heat pumps per electrical bus
483
484			Parameters
485			----------
486			heat_pumps : pandas.DataFrame
487			Heat pumps including voltage level
488			multiple_per_mv_grid : boolean, optional
489			Choose if a district heating area can by supplied by multiple
490			hvmv substaions/mv grids. The default is False.
491
492			Returns
493			-------
494			gdf : pandas.DataFrame
495			Heat pumps per electrical bus
496
497			"""
498
499			sources = config.datasets()["etrago_heat"]["sources"]
500			targets = config.datasets()["etrago_heat"]["targets"]
501
502			# Map heat buses to district heating id and area_id
503			heat_buses = db.select_dataframe(
504			f"""
505			SELECT bus_id, area_id, id FROM
506			{targets['heat_buses']['schema']}.
507			{targets['heat_buses']['table']}
508			JOIN {sources['district_heating_areas']['schema']}.
509			{sources['district_heating_areas']['table']}
510			ON ST_Intersects(
511			ST_Transform(ST_Buffer(
512			ST_Centroid(geom_polygon), 0.0000001), 4326), geom)
513			WHERE carrier = 'central_heat'
514			AND scenario='{scenario}'
515			AND scn_name = '{scenario}'
516			""",
517			index_col="id",
518			)
519
520			heat_pumps["power_bus"] = ""
521
522			# Select mv grid distrcits
523			mv_grid_district = db.select_geodataframe(
524			f"""
525			SELECT bus_id, geom FROM
526			{sources['egon_mv_grid_district']['schema']}.
527			{sources['egon_mv_grid_district']['table']}
528			""",
529			epsg=4326,
530			)
531
532			# Map zensus cells to district heating areas
533			map_zensus_dh = db.select_geodataframe(
534			f"""
535			SELECT area_id, a.zensus_population_id,
536			geom_point as geom, sum(a.demand) as demand
537			FROM {sources['map_district_heating_areas']['schema']}.
538			{sources['map_district_heating_areas']['table']} b
539			JOIN {sources['heat_demand']['schema']}.
540			{sources['heat_demand']['table']} a
541			ON b.zensus_population_id = a.zensus_population_id
542			JOIN society.destatis_zensus_population_per_ha
543			ON society.destatis_zensus_population_per_ha.id =
544			a.zensus_population_id
545			WHERE a.scenario = '{scenario}'
546			AND b.scenario = '{scenario}'
547			GROUP BY (area_id, a.zensus_population_id, geom_point)
548			""",
549			epsg=4326,
550			)
551
552			# Select area_id per heat pump
553			heat_pumps["area_id"] = heat_buses.area_id[
554			heat_pumps.district_heating_id.values
555			].values
556
557			heat_buses.set_index("area_id", inplace=True)
558
559			# Select only cells in choosen district heating areas
560			cells = map_zensus_dh[map_zensus_dh.area_id.isin(heat_pumps.area_id)]
561
562			# Assign power bus per zensus cell
563			cells["power_bus"] = gpd.sjoin(
564			cells, mv_grid_district, how="inner", op="intersects"
565			).bus_id
566
567			# Calclate district heating demand per substaion
568			demand_per_substation = pd.DataFrame(
569			cells.groupby(["area_id", "power_bus"]).demand.sum()
570			)
571
572			heat_pumps.set_index("area_id", inplace=True)
573
574			# If district heating areas are supplied by multiple hvmv-substations,
575			# create one heatpump per electrical bus.
576			# The installed capacity is assigned regarding the share of heat demand.
577			if multiple_per_mv_grid:
578
579			power_to_heat = demand_per_substation.reset_index()
580
581			power_to_heat["carrier"] = carrier
582
583			power_to_heat.loc[:, "voltage_level"] = heat_pumps.voltage_level[
584			power_to_heat.area_id
585			].values
586
587			if "heat_pump" in carrier:
588
589			power_to_heat.loc[:, "cop"] = heat_pumps.cop[
590			power_to_heat.area_id
591			].values
592
593			power_to_heat["share_demand"] = (
594			power_to_heat.groupby("area_id")
595			.demand.apply(lambda grp: grp / grp.sum())
596			.values
597			)
598
599			power_to_heat["capacity"] = power_to_heat["share_demand"].mul(
600			heat_pumps.capacity[power_to_heat.area_id].values
601			)
602
603			power_to_heat = power_to_heat[power_to_heat.voltage_level.notnull()]
604
605			gdf = gpd.GeoDataFrame(
606			power_to_heat,
607			index=power_to_heat.index,
608			geometry=heat_pumps.geometry[power_to_heat.area_id].values,
609			)
610
611			# If district heating areas are supplied by one hvmv-substations,
612			# the hvmv substation which has the most heat demand is choosen.
613			else:
614
615			substation_max_demand = (
616			demand_per_substation.reset_index()
617			.set_index("power_bus")
618			.groupby("area_id")
619			.demand.max()
620			)
621
622			selected_substations = (
623			demand_per_substation[
624			demand_per_substation.demand.isin(substation_max_demand)
625			]
626			.reset_index()
627			.set_index("area_id")
628			)
629
630			selected_substations.rename(
631			{"demand": "demand_selected_substation"}, axis=1, inplace=True
632			)
633
634			selected_substations["share_demand"] = (
635			cells.groupby(["area_id", "power_bus"])
636			.demand.sum()
637			.reset_index()
638			.groupby("area_id")
639			.demand.max()
640			/ cells.groupby(["area_id", "power_bus"])
641			.demand.sum()
642			.reset_index()
643			.groupby("area_id")
644			.demand.sum()
645			)
646
647			power_to_heat = selected_substations
648
649			power_to_heat["carrier"] = carrier
650
651			power_to_heat.loc[:, "voltage_level"] = heat_pumps.voltage_level
652
653			if "heat_pump" in carrier:
654
655			power_to_heat.loc[:, "cop"] = heat_pumps.cop
656
657			power_to_heat["capacity"] = heat_pumps.capacity[
658			power_to_heat.index
659			].values
660
661			power_to_heat = power_to_heat[power_to_heat.voltage_level.notnull()]
662
663			gdf = gpd.GeoDataFrame(
664			power_to_heat,
665			index=power_to_heat.index,
666			geometry=heat_pumps.geometry,
667			)
668
669			gdf.reset_index(inplace=True)
670
671			gdf["heat_bus"] = (
672			heat_buses.loc[gdf.area_id, "bus_id"].reset_index().bus_id
673			)
674
675			return gdf
676

openego / eGon-data

Pull Request — dev (#1348)

assign_electrical_bus() C

Complexity

Size

Duplication

Importance

How to fix Long Method

Long Method

Duplication Side-by-Side

Filter issues like