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"""The central module containing all code dealing with electrical neighbours |
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""" |
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import zipfile |
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from shapely.geometry import LineString |
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from sqlalchemy.orm import sessionmaker |
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import geopandas as gpd |
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import pandas as pd |
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from egon.data import config, db |
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from egon.data.datasets import Dataset |
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from egon.data.datasets.fill_etrago_gen import add_marginal_costs |
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from egon.data.datasets.scenario_parameters import get_sector_parameters |
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import egon.data.datasets.etrago_setup as etrago |
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import egon.data.datasets.scenario_parameters.parameters as scenario_parameters |
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class ElectricalNeighbours(Dataset): |
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def __init__(self, dependencies): |
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super().__init__( |
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name="ElectricalNeighbours", |
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version="0.0.7", |
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dependencies=dependencies, |
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tasks=(grid, {tyndp_generation, tyndp_demand}), |
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) |
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def get_cross_border_buses(scenario, sources): |
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"""Returns buses from osmTGmod which are outside of Germany. |
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Parameters |
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---------- |
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sources : dict |
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List of sources |
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Returns |
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------- |
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geopandas.GeoDataFrame |
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Electricity buses outside of Germany |
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""" |
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return db.select_geodataframe( |
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f""" |
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SELECT * |
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FROM {sources['electricity_buses']['schema']}. |
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{sources['electricity_buses']['table']} |
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WHERE |
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NOT ST_INTERSECTS ( |
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geom, |
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(SELECT ST_Transform(ST_Buffer(geometry, 5), 4326) FROM |
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{sources['german_borders']['schema']}. |
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{sources['german_borders']['table']})) |
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AND (bus_id IN ( |
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SELECT bus0 FROM |
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{sources['lines']['schema']}.{sources['lines']['table']}) |
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OR bus_id IN ( |
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SELECT bus1 FROM |
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{sources['lines']['schema']}.{sources['lines']['table']})) |
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AND scn_name = '{scenario}'; |
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""", |
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epsg=4326, |
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) |
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def get_cross_border_lines(scenario, sources): |
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"""Returns lines from osmTGmod which end or start outside of Germany. |
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Parameters |
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---------- |
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sources : dict |
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List of sources |
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Returns |
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------- |
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geopandas.GeoDataFrame |
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AC-lines outside of Germany |
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""" |
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return db.select_geodataframe( |
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f""" |
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SELECT * |
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FROM {sources['lines']['schema']}.{sources['lines']['table']} a |
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WHERE |
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ST_INTERSECTS ( |
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a.topo, |
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(SELECT ST_Transform(ST_boundary(geometry), 4326) |
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FROM {sources['german_borders']['schema']}. |
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{sources['german_borders']['table']})) |
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AND scn_name = '{scenario}'; |
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""", |
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epsg=4326, |
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) |
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def central_buses_egon100(sources): |
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"""Returns buses in the middle of foreign countries based on eGon100RE |
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Parameters |
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---------- |
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sources : dict |
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List of sources |
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Returns |
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------- |
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pandas.DataFrame |
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Buses in the center of foreign countries |
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""" |
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return db.select_dataframe( |
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f""" |
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SELECT * |
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FROM {sources['electricity_buses']['schema']}. |
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{sources['electricity_buses']['table']} |
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WHERE country != 'DE' |
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AND scn_name = 'eGon100RE' |
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AND bus_id NOT IN ( |
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SELECT bus_i |
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FROM {sources['osmtgmod_bus']['schema']}. |
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{sources['osmtgmod_bus']['table']}) |
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AND carrier = 'AC' |
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""" |
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) |
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def buses(scenario, sources, targets): |
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"""Insert central buses in foreign countries per scenario |
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Parameters |
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---------- |
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sources : dict |
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List of dataset sources |
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targets : dict |
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List of dataset targets |
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Returns |
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------- |
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central_buses : geoapndas.GeoDataFrame |
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Buses in the center of foreign countries |
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""" |
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sql_delete = f""" |
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DELETE FROM {sources['electricity_buses']['schema']}. |
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{sources['electricity_buses']['table']} |
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WHERE country != 'DE' AND scn_name = '{scenario}' |
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AND carrier = 'AC' |
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AND bus_id NOT IN ( |
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SELECT bus_i |
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FROM {sources['osmtgmod_bus']['schema']}. |
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{sources['osmtgmod_bus']['table']}) |
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""" |
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# Drop only buses with v_nom != 380 for eGon100RE |
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# to keep buses from pypsa-eur-sec |
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if scenario == "eGon100RE": |
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sql_delete += "AND v_nom < 380" |
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# Delete existing buses |
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db.execute_sql(sql_delete) |
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central_buses = central_buses_egon100(sources) |
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next_bus_id = db.next_etrago_id("bus") + 1 |
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# if in test mode, add bus in center of Germany |
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if config.settings()["egon-data"]["--dataset-boundary"] != "Everything": |
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central_buses = central_buses.append( |
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{ |
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"scn_name": scenario, |
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"bus_id": next_bus_id, |
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"x": 10.4234469, |
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"y": 51.0834196, |
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"country": "DE", |
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"carrier": "AC", |
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"v_nom": 380.0, |
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}, |
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ignore_index=True, |
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) |
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next_bus_id += 1 |
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# Add buses for other voltage levels |
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foreign_buses = get_cross_border_buses(scenario, sources) |
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if config.settings()["egon-data"]["--dataset-boundary"] == "Everything": |
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foreign_buses = foreign_buses[foreign_buses.country != "DE"] |
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vnom_per_country = foreign_buses.groupby("country").v_nom.unique().copy() |
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for cntr in vnom_per_country.index: |
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print(cntr) |
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View Code Duplication |
if 110.0 in vnom_per_country[cntr]: |
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central_buses = central_buses.append( |
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{ |
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"scn_name": scenario, |
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"bus_id": next_bus_id, |
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"x": central_buses[ |
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central_buses.country == cntr |
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].x.unique()[0], |
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"y": central_buses[ |
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central_buses.country == cntr |
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].y.unique()[0], |
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"country": cntr, |
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"carrier": "AC", |
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"v_nom": 110.0, |
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}, |
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ignore_index=True, |
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) |
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next_bus_id += 1 |
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View Code Duplication |
if 220.0 in vnom_per_country[cntr]: |
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central_buses = central_buses.append( |
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{ |
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"scn_name": scenario, |
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"bus_id": next_bus_id, |
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"x": central_buses[ |
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central_buses.country == cntr |
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].x.unique()[0], |
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"y": central_buses[ |
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central_buses.country == cntr |
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].y.unique()[0], |
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"country": cntr, |
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"carrier": "AC", |
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"v_nom": 220.0, |
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}, |
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ignore_index=True, |
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) |
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next_bus_id += 1 |
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# Add geometry column |
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central_buses = gpd.GeoDataFrame( |
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central_buses, |
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geometry=gpd.points_from_xy(central_buses.x, central_buses.y), |
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crs="EPSG:4326", |
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) |
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central_buses["geom"] = central_buses.geometry.copy() |
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central_buses = central_buses.set_geometry("geom").drop( |
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"geometry", axis="columns" |
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) |
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central_buses.scn_name = scenario |
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# Insert all central buses for eGon2035 |
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if scenario == "eGon2035": |
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central_buses.to_postgis( |
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targets["buses"]["table"], |
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schema=targets["buses"]["schema"], |
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if_exists="append", |
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con=db.engine(), |
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index=False, |
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) |
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# Insert only buses for eGon100RE that are not coming from pypsa-eur-sec |
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# (buses with another voltage_level or inside Germany in test mode) |
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else: |
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central_buses[ |
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(central_buses.v_nom != 380) | (central_buses.country == "DE") |
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].to_postgis( |
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targets["buses"]["table"], |
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schema=targets["buses"]["schema"], |
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if_exists="append", |
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con=db.engine(), |
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index=False, |
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) |
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return central_buses |
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def cross_border_lines(scenario, sources, targets, central_buses): |
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"""Adds lines which connect border-crossing lines from osmtgmod |
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to the central buses in the corresponding neigbouring country |
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Parameters |
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---------- |
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sources : dict |
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List of dataset sources |
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targets : dict |
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List of dataset targets |
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central_buses : geopandas.GeoDataFrame |
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Buses in the center of foreign countries |
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Returns |
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------- |
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new_lines : geopandas.GeoDataFrame |
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Lines that connect cross-border lines to central bus per country |
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""" |
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# Delete existing data |
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db.execute_sql( |
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f""" |
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DELETE FROM {targets['lines']['schema']}. |
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{targets['lines']['table']} |
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WHERE scn_name = '{scenario}' |
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AND line_id NOT IN ( |
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SELECT branch_id |
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FROM {sources['osmtgmod_branch']['schema']}. |
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{sources['osmtgmod_branch']['table']} |
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WHERE result_id = 1 and (link_type = 'line' or |
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link_type = 'cable')) |
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AND bus0 IN ( |
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SELECT bus_i |
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FROM {sources['osmtgmod_bus']['schema']}. |
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{sources['osmtgmod_bus']['table']}) |
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AND bus1 NOT IN ( |
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SELECT bus_i |
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FROM {sources['osmtgmod_bus']['schema']}. |
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{sources['osmtgmod_bus']['table']}) |
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""" |
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) |
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# Calculate cross-border busses and lines from osmtgmod |
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foreign_buses = get_cross_border_buses(scenario, sources) |
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if config.settings()["egon-data"]["--dataset-boundary"] == "Everything": |
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foreign_buses = foreign_buses[foreign_buses.country != "DE"] |
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lines = get_cross_border_lines(scenario, sources) |
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# Select bus outside of Germany from border-crossing lines |
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lines.loc[ |
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lines[lines.bus0.isin(foreign_buses.bus_id)].index, "foreign_bus" |
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] = lines.loc[lines[lines.bus0.isin(foreign_buses.bus_id)].index, "bus0"] |
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lines.loc[ |
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lines[lines.bus1.isin(foreign_buses.bus_id)].index, "foreign_bus" |
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] = lines.loc[lines[lines.bus1.isin(foreign_buses.bus_id)].index, "bus1"] |
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# Drop lines with start and endpoint in Germany |
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lines = lines[lines.foreign_bus.notnull()] |
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lines.loc[:, "foreign_bus"] = lines.loc[:, "foreign_bus"].astype(int) |
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321
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# Copy all parameters from border-crossing lines |
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new_lines = lines.copy() |
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# Set bus0 as foreign_bus from osmtgmod |
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new_lines.bus0 = new_lines.foreign_bus.copy() |
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# Add country tag and set index |
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new_lines["country"] = ( |
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foreign_buses.set_index("bus_id") |
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.loc[lines.foreign_bus, "country"] |
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.values |
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) |
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if config.settings()["egon-data"]["--dataset-boundary"] == "Everything": |
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new_lines = new_lines[~new_lines.country.isnull()] |
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new_lines.line_id = range( |
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db.next_etrago_id("line"), db.next_etrago_id("line") + len(new_lines) |
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) |
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# Set bus in center of foreogn countries as bus1 |
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for i, row in new_lines.iterrows(): |
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print(row) |
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new_lines.loc[i, "bus1"] = central_buses.bus_id[ |
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(central_buses.country == row.country) |
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& (central_buses.v_nom == row.v_nom) |
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].values[0] |
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348
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# Create geometry for new lines |
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new_lines["geom_bus0"] = ( |
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foreign_buses.set_index("bus_id").geom[new_lines.bus0].values |
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) |
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new_lines["geom_bus1"] = ( |
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central_buses.set_index("bus_id").geom[new_lines.bus1].values |
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) |
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new_lines["topo"] = new_lines.apply( |
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lambda x: LineString([x["geom_bus0"], x["geom_bus1"]]), axis=1 |
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) |
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# Set topo as geometry column |
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new_lines = new_lines.set_geometry("topo") |
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|
362
|
|
|
# Calcultae length of lines based on topology |
363
|
|
|
old_length = new_lines["length"].copy() |
364
|
|
|
new_lines["length"] = new_lines.to_crs(3035).length / 1000 |
365
|
|
|
|
366
|
|
|
# Set electrical parameters based on lines from osmtgmod |
367
|
|
|
for parameter in ["x", "r"]: |
368
|
|
|
new_lines[parameter] = ( |
369
|
|
|
new_lines[parameter] / old_length * new_lines["length"] |
370
|
|
|
) |
371
|
|
|
for parameter in ["b", "g"]: |
372
|
|
|
new_lines[parameter] = ( |
373
|
|
|
new_lines[parameter] * old_length / new_lines["length"] |
374
|
|
|
) |
375
|
|
|
|
376
|
|
|
# Drop intermediate columns |
377
|
|
|
new_lines.drop( |
378
|
|
|
["foreign_bus", "country", "geom_bus0", "geom_bus1", "geom"], |
379
|
|
|
axis="columns", |
380
|
|
|
inplace=True, |
381
|
|
|
) |
382
|
|
|
|
383
|
|
|
new_lines = new_lines[new_lines.bus0 != new_lines.bus1] |
384
|
|
|
|
385
|
|
|
# Set scn_name |
386
|
|
|
|
387
|
|
|
# Insert lines to the database |
388
|
|
|
new_lines.to_postgis( |
389
|
|
|
targets["lines"]["table"], |
390
|
|
|
schema=targets["lines"]["schema"], |
391
|
|
|
if_exists="append", |
392
|
|
|
con=db.engine(), |
393
|
|
|
index=False, |
394
|
|
|
) |
395
|
|
|
|
396
|
|
|
return new_lines |
397
|
|
|
|
398
|
|
|
|
399
|
|
|
def choose_transformer(s_nom): |
400
|
|
|
"""Select transformer and parameters from existing data in the grid model |
401
|
|
|
|
402
|
|
|
It is assumed that transformers in the foreign countries are not limiting |
403
|
|
|
the electricity flow, so the capacitiy s_nom is set to the minimum sum |
404
|
|
|
of attached AC-lines. |
405
|
|
|
The electrical parameters are set according to already inserted |
406
|
|
|
transformers in the grid model for Germany. |
407
|
|
|
|
408
|
|
|
Parameters |
409
|
|
|
---------- |
410
|
|
|
s_nom : float |
411
|
|
|
Minimal sum of nominal power of lines at one side |
412
|
|
|
|
413
|
|
|
Returns |
414
|
|
|
------- |
415
|
|
|
int |
416
|
|
|
Selected transformer nominal power |
417
|
|
|
float |
418
|
|
|
Selected transformer nominal impedance |
419
|
|
|
|
420
|
|
|
""" |
421
|
|
|
|
422
|
|
|
if s_nom <= 600: |
423
|
|
|
return 600, 0.0002 |
424
|
|
|
elif (s_nom > 600) & (s_nom <= 1200): |
425
|
|
|
return 1200, 0.0001 |
426
|
|
|
elif (s_nom > 1200) & (s_nom <= 1600): |
427
|
|
|
return 1600, 0.000075 |
428
|
|
|
elif (s_nom > 1600) & (s_nom <= 2100): |
429
|
|
|
return 2100, 0.00006667 |
430
|
|
|
elif (s_nom > 2100) & (s_nom <= 2600): |
431
|
|
|
return 2600, 0.0000461538 |
432
|
|
|
elif (s_nom > 2600) & (s_nom <= 4800): |
433
|
|
|
return 4800, 0.000025 |
434
|
|
|
elif (s_nom > 4800) & (s_nom <= 6000): |
435
|
|
|
return 6000, 0.0000225 |
436
|
|
|
elif (s_nom > 6000) & (s_nom <= 7200): |
437
|
|
|
return 7200, 0.0000194444 |
438
|
|
|
elif (s_nom > 7200) & (s_nom <= 8000): |
439
|
|
|
return 8000, 0.000016875 |
440
|
|
|
elif (s_nom > 8000) & (s_nom <= 9000): |
441
|
|
|
return 9000, 0.000015 |
442
|
|
|
elif (s_nom > 9000) & (s_nom <= 13000): |
443
|
|
|
return 13000, 0.0000103846 |
444
|
|
|
elif (s_nom > 13000) & (s_nom <= 20000): |
445
|
|
|
return 20000, 0.00000675 |
446
|
|
|
elif (s_nom > 20000) & (s_nom <= 33000): |
447
|
|
|
return 33000, 0.00000409091 |
448
|
|
|
|
449
|
|
|
|
450
|
|
|
def central_transformer(scenario, sources, targets, central_buses, new_lines): |
451
|
|
|
"""Connect central foreign buses with different voltage levels |
452
|
|
|
|
453
|
|
|
Parameters |
454
|
|
|
---------- |
455
|
|
|
sources : dict |
456
|
|
|
List of dataset sources |
457
|
|
|
targets : dict |
458
|
|
|
List of dataset targets |
459
|
|
|
central_buses : geopandas.GeoDataFrame |
460
|
|
|
Buses in the center of foreign countries |
461
|
|
|
new_lines : geopandas.GeoDataFrame |
462
|
|
|
Lines that connect cross-border lines to central bus per country |
463
|
|
|
|
464
|
|
|
Returns |
465
|
|
|
------- |
466
|
|
|
None. |
467
|
|
|
|
468
|
|
|
""" |
469
|
|
|
# Delete existing transformers in foreign countries |
470
|
|
|
db.execute_sql( |
471
|
|
|
f""" |
472
|
|
|
DELETE FROM {targets['transformers']['schema']}. |
473
|
|
|
{targets['transformers']['table']} |
474
|
|
|
WHERE scn_name = '{scenario}' |
475
|
|
|
AND trafo_id NOT IN ( |
476
|
|
|
SELECT branch_id |
477
|
|
|
FROM {sources['osmtgmod_branch']['schema']}. |
478
|
|
|
{sources['osmtgmod_branch']['table']} |
479
|
|
|
WHERE result_id = 1 and link_type = 'transformer') |
480
|
|
|
""" |
481
|
|
|
) |
482
|
|
|
|
483
|
|
|
# Initalize the dataframe for transformers |
484
|
|
|
trafo = gpd.GeoDataFrame( |
485
|
|
|
columns=["trafo_id", "bus0", "bus1", "s_nom"], dtype=int |
486
|
|
|
) |
487
|
|
|
trafo_id = db.next_etrago_id("transformer") |
488
|
|
|
|
489
|
|
|
# Add one transformer per central foreign bus with v_nom != 380 |
490
|
|
|
for i, row in central_buses[central_buses.v_nom != 380].iterrows(): |
491
|
|
|
|
492
|
|
|
s_nom_0 = new_lines[new_lines.bus0 == row.bus_id].s_nom.sum() |
493
|
|
|
s_nom_1 = new_lines[new_lines.bus1 == row.bus_id].s_nom.sum() |
494
|
|
|
if s_nom_0 == 0.0: |
495
|
|
|
s_nom = s_nom_1 |
496
|
|
|
elif s_nom_1 == 0.0: |
497
|
|
|
s_nom = s_nom_0 |
498
|
|
|
else: |
499
|
|
|
s_nom = min([s_nom_0, s_nom_1]) |
500
|
|
|
|
501
|
|
|
s_nom, x = choose_transformer(s_nom) |
502
|
|
|
|
503
|
|
|
trafo = trafo.append( |
504
|
|
|
{ |
505
|
|
|
"trafo_id": trafo_id, |
506
|
|
|
"bus0": row.bus_id, |
507
|
|
|
"bus1": central_buses[ |
508
|
|
|
(central_buses.v_nom == 380) |
509
|
|
|
& (central_buses.country == row.country) |
510
|
|
|
].bus_id.values[0], |
511
|
|
|
"s_nom": s_nom, |
512
|
|
|
"x": x, |
513
|
|
|
}, |
514
|
|
|
ignore_index=True, |
515
|
|
|
) |
516
|
|
|
trafo_id += 1 |
517
|
|
|
|
518
|
|
|
# Set data type |
519
|
|
|
trafo = trafo.astype({"trafo_id": "int", "bus0": "int", "bus1": "int"}) |
520
|
|
|
trafo["scn_name"] = scenario |
521
|
|
|
|
522
|
|
|
# Insert transformers to the database |
523
|
|
|
trafo.to_sql( |
524
|
|
|
targets["transformers"]["table"], |
525
|
|
|
schema=targets["transformers"]["schema"], |
526
|
|
|
if_exists="append", |
527
|
|
|
con=db.engine(), |
528
|
|
|
index=False, |
529
|
|
|
) |
530
|
|
|
|
531
|
|
|
|
532
|
|
|
def foreign_dc_lines(scenario, sources, targets, central_buses): |
533
|
|
|
"""Insert DC lines to foreign countries manually |
534
|
|
|
|
535
|
|
|
Parameters |
536
|
|
|
---------- |
537
|
|
|
sources : dict |
538
|
|
|
List of dataset sources |
539
|
|
|
targets : dict |
540
|
|
|
List of dataset targets |
541
|
|
|
central_buses : geopandas.GeoDataFrame |
542
|
|
|
Buses in the center of foreign countries |
543
|
|
|
|
544
|
|
|
Returns |
545
|
|
|
------- |
546
|
|
|
None. |
547
|
|
|
|
548
|
|
|
""" |
549
|
|
|
# Delete existing dc lines to foreign countries |
550
|
|
|
db.execute_sql( |
551
|
|
|
f""" |
552
|
|
|
DELETE FROM {targets['links']['schema']}. |
553
|
|
|
{targets['links']['table']} |
554
|
|
|
WHERE scn_name = '{scenario}' |
555
|
|
|
AND carrier = 'DC' |
556
|
|
|
AND bus0 IN ( |
557
|
|
|
SELECT bus_id |
558
|
|
|
FROM {sources['electricity_buses']['schema']}. |
559
|
|
|
{sources['electricity_buses']['table']} |
560
|
|
|
WHERE scn_name = '{scenario}' |
561
|
|
|
AND carrier = 'AC' |
562
|
|
|
AND country = 'DE') |
563
|
|
|
AND bus1 IN ( |
564
|
|
|
SELECT bus_id |
565
|
|
|
FROM {sources['electricity_buses']['schema']}. |
566
|
|
|
{sources['electricity_buses']['table']} |
567
|
|
|
WHERE scn_name = '{scenario}' |
568
|
|
|
AND carrier = 'AC' |
569
|
|
|
AND country != 'DE') |
570
|
|
|
""" |
571
|
|
|
) |
572
|
|
|
capital_cost = get_sector_parameters("electricity", "eGon2035")[ |
573
|
|
|
"capital_cost" |
574
|
|
|
] |
575
|
|
|
|
576
|
|
|
# Add DC line from Lübeck to Sweden |
577
|
|
|
converter_luebeck = db.select_dataframe( |
578
|
|
|
f""" |
579
|
|
|
SELECT bus_id FROM |
580
|
|
|
{sources['electricity_buses']['schema']}. |
581
|
|
|
{sources['electricity_buses']['table']} |
582
|
|
|
WHERE x = 10.802358024202768 |
583
|
|
|
AND y = 53.897547401787 |
584
|
|
|
AND v_nom = 380 |
585
|
|
|
AND scn_name = '{scenario}' |
586
|
|
|
AND carrier = 'AC' |
587
|
|
|
""" |
588
|
|
|
).squeeze() |
589
|
|
|
|
590
|
|
|
foreign_links = pd.DataFrame( |
591
|
|
|
index=[0], |
592
|
|
|
data={ |
593
|
|
|
"link_id": db.next_etrago_id("link"), |
594
|
|
|
"bus0": converter_luebeck, |
595
|
|
|
"bus1": central_buses[ |
596
|
|
|
(central_buses.country == "SE") & (central_buses.v_nom == 380) |
597
|
|
|
] |
598
|
|
|
.squeeze() |
599
|
|
|
.bus_id, |
600
|
|
|
"p_nom": 600, |
601
|
|
|
"length": 262, |
602
|
|
|
}, |
603
|
|
|
) |
604
|
|
|
|
605
|
|
|
# When not in test-mode, add DC line from Bentwisch to Denmark |
606
|
|
|
if config.settings()["egon-data"]["--dataset-boundary"] == "Everything": |
607
|
|
|
converter_bentwisch = db.select_dataframe( |
608
|
|
|
f""" |
609
|
|
|
SELECT bus_id FROM |
610
|
|
|
{sources['electricity_buses']['schema']}. |
611
|
|
|
{sources['electricity_buses']['table']} |
612
|
|
|
WHERE x = 12.213671694775988 |
613
|
|
|
AND y = 54.09974494662279 |
614
|
|
|
AND v_nom = 380 |
615
|
|
|
AND scn_name = '{scenario}' |
616
|
|
|
AND carrier = 'AC' |
617
|
|
|
""" |
618
|
|
|
).squeeze() |
619
|
|
|
|
620
|
|
|
foreign_links = foreign_links.append( |
621
|
|
|
pd.DataFrame( |
622
|
|
|
index=[1], |
623
|
|
|
data={ |
624
|
|
|
"link_id": db.next_etrago_id("link") + 1, |
625
|
|
|
"bus0": converter_bentwisch, |
626
|
|
|
"bus1": central_buses[ |
627
|
|
|
(central_buses.country == "DK") |
628
|
|
|
& (central_buses.v_nom == 380) |
629
|
|
|
& (central_buses.x > 10) |
630
|
|
|
] |
631
|
|
|
.squeeze() |
632
|
|
|
.bus_id, |
633
|
|
|
"p_nom": 600, |
634
|
|
|
"length": 170, |
635
|
|
|
}, |
636
|
|
|
) |
637
|
|
|
) |
638
|
|
|
|
639
|
|
|
# Set parameters for all DC lines |
640
|
|
|
foreign_links["capital_cost"] = ( |
641
|
|
|
capital_cost["dc_cable"] * foreign_links.length |
642
|
|
|
+ 2 * capital_cost["dc_inverter"] |
643
|
|
|
) |
644
|
|
|
foreign_links["p_min_pu"] = -1 |
645
|
|
|
foreign_links["p_nom_extendable"] = True |
646
|
|
|
foreign_links["p_nom_min"] = foreign_links["p_nom"] |
647
|
|
|
foreign_links["scn_name"] = scenario |
648
|
|
|
foreign_links["carrier"] = "DC" |
649
|
|
|
foreign_links["efficiency"] = 1 |
650
|
|
|
|
651
|
|
|
# Add topology |
652
|
|
|
foreign_links = etrago.link_geom_from_buses(foreign_links, scenario) |
653
|
|
|
|
654
|
|
|
# Insert DC lines to the database |
655
|
|
|
foreign_links.to_postgis( |
656
|
|
|
targets["links"]["table"], |
657
|
|
|
schema=targets["links"]["schema"], |
658
|
|
|
if_exists="append", |
659
|
|
|
con=db.engine(), |
660
|
|
|
index=False, |
661
|
|
|
) |
662
|
|
|
|
663
|
|
|
|
664
|
|
|
def grid(): |
665
|
|
|
"""Insert electrical grid compoenents for neighbouring countries |
666
|
|
|
|
667
|
|
|
Returns |
668
|
|
|
------- |
669
|
|
|
None. |
670
|
|
|
|
671
|
|
|
""" |
672
|
|
|
# Select sources and targets from dataset configuration |
673
|
|
|
sources = config.datasets()["electrical_neighbours"]["sources"] |
674
|
|
|
targets = config.datasets()["electrical_neighbours"]["targets"] |
675
|
|
|
|
676
|
|
|
for scenario in ["eGon2035"]: |
677
|
|
|
|
678
|
|
|
central_buses = buses(scenario, sources, targets) |
679
|
|
|
|
680
|
|
|
foreign_lines = cross_border_lines( |
681
|
|
|
scenario, sources, targets, central_buses |
682
|
|
|
) |
683
|
|
|
|
684
|
|
|
central_transformer( |
685
|
|
|
scenario, sources, targets, central_buses, foreign_lines |
686
|
|
|
) |
687
|
|
|
|
688
|
|
|
foreign_dc_lines(scenario, sources, targets, central_buses) |
689
|
|
|
|
690
|
|
|
|
691
|
|
|
def map_carriers_tyndp(): |
692
|
|
|
"""Map carriers from TYNDP-data to carriers used in eGon |
693
|
|
|
Returns |
694
|
|
|
------- |
695
|
|
|
dict |
696
|
|
|
Carrier from TYNDP and eGon |
697
|
|
|
""" |
698
|
|
|
return { |
699
|
|
|
"Battery": "battery", |
700
|
|
|
"DSR": "demand_side_response", |
701
|
|
|
"Gas CCGT new": "gas", |
702
|
|
|
"Gas CCGT old 2": "gas", |
703
|
|
|
"Gas CCGT present 1": "gas", |
704
|
|
|
"Gas CCGT present 2": "gas", |
705
|
|
|
"Gas conventional old 1": "gas", |
706
|
|
|
"Gas conventional old 2": "gas", |
707
|
|
|
"Gas OCGT new": "gas", |
708
|
|
|
"Gas OCGT old": "gas", |
709
|
|
|
"Gas CCGT old 1": "gas", |
710
|
|
|
"Gas CCGT old 2 Bio": "biogas", |
711
|
|
|
"Gas conventional old 2 Bio": "biogas", |
712
|
|
|
"Hard coal new": "coal", |
713
|
|
|
"Hard coal old 1": "coal", |
714
|
|
|
"Hard coal old 2": "coal", |
715
|
|
|
"Hard coal old 2 Bio": "coal", |
716
|
|
|
"Heavy oil old 1": "oil", |
717
|
|
|
"Heavy oil old 1 Bio": "oil", |
718
|
|
|
"Heavy oil old 2": "oil", |
719
|
|
|
"Light oil": "oil", |
720
|
|
|
"Lignite new": "lignite", |
721
|
|
|
"Lignite old 1": "lignite", |
722
|
|
|
"Lignite old 2": "lignite", |
723
|
|
|
"Lignite old 1 Bio": "lignite", |
724
|
|
|
"Lignite old 2 Bio": "lignite", |
725
|
|
|
"Nuclear": "nuclear", |
726
|
|
|
"Offshore Wind": "wind_offshore", |
727
|
|
|
"Onshore Wind": "wind_onshore", |
728
|
|
|
"Other non-RES": "others", |
729
|
|
|
"Other RES": "others", |
730
|
|
|
"P2G": "power_to_gas", |
731
|
|
|
"PS Closed": "pumped_hydro", |
732
|
|
|
"PS Open": "reservoir", |
733
|
|
|
"Reservoir": "reservoir", |
734
|
|
|
"Run-of-River": "run_of_river", |
735
|
|
|
"Solar PV": "solar", |
736
|
|
|
"Solar Thermal": "others", |
737
|
|
|
"Waste": "Other RES", |
738
|
|
|
} |
739
|
|
|
|
740
|
|
|
|
741
|
|
View Code Duplication |
def get_foreign_bus_id(): |
|
|
|
|
742
|
|
|
"""Calculte the etrago bus id from Nodes of TYNDP based on the geometry |
743
|
|
|
|
744
|
|
|
Returns |
745
|
|
|
------- |
746
|
|
|
pandas.Series |
747
|
|
|
List of mapped node_ids from TYNDP and etragos bus_id |
748
|
|
|
|
749
|
|
|
""" |
750
|
|
|
|
751
|
|
|
sources = config.datasets()["electrical_neighbours"]["sources"] |
752
|
|
|
|
753
|
|
|
bus_id = db.select_geodataframe( |
754
|
|
|
"""SELECT bus_id, ST_Buffer(geom, 1) as geom, country |
755
|
|
|
FROM grid.egon_etrago_bus |
756
|
|
|
WHERE scn_name = 'eGon2035' |
757
|
|
|
AND carrier = 'AC' |
758
|
|
|
AND v_nom = 380. |
759
|
|
|
AND country != 'DE' |
760
|
|
|
AND bus_id NOT IN ( |
761
|
|
|
SELECT bus_i |
762
|
|
|
FROM osmtgmod_results.bus_data) |
763
|
|
|
""", |
764
|
|
|
epsg=3035, |
765
|
|
|
) |
766
|
|
|
|
767
|
|
|
# insert installed capacities |
768
|
|
|
file = zipfile.ZipFile(f"tyndp/{sources['tyndp_capacities']}") |
769
|
|
|
|
770
|
|
|
# Select buses in neighbouring countries as geodataframe |
771
|
|
|
buses = pd.read_excel( |
772
|
|
|
file.open("TYNDP-2020-Scenario-Datafile.xlsx").read(), |
773
|
|
|
sheet_name="Nodes - Dict", |
774
|
|
|
).query("longitude==longitude") |
775
|
|
|
buses = gpd.GeoDataFrame( |
776
|
|
|
buses, |
777
|
|
|
crs=4326, |
778
|
|
|
geometry=gpd.points_from_xy(buses.longitude, buses.latitude), |
779
|
|
|
).to_crs(3035) |
780
|
|
|
|
781
|
|
|
buses["bus_id"] = 0 |
782
|
|
|
|
783
|
|
|
# Select bus_id from etrago with shortest distance to TYNDP node |
784
|
|
|
for i, row in buses.iterrows(): |
785
|
|
|
distance = bus_id.set_index("bus_id").geom.distance(row.geometry) |
786
|
|
|
buses.loc[i, "bus_id"] = distance[ |
787
|
|
|
distance == distance.min() |
788
|
|
|
].index.values[0] |
789
|
|
|
|
790
|
|
|
return buses.set_index("node_id").bus_id |
791
|
|
|
|
792
|
|
|
|
793
|
|
|
@db.session_scoped |
794
|
|
|
def calc_capacities(session=None): |
795
|
|
|
"""Calculates installed capacities from TYNDP data |
796
|
|
|
|
797
|
|
|
Returns |
798
|
|
|
------- |
799
|
|
|
pandas.DataFrame |
800
|
|
|
Installed capacities per foreign node and energy carrier |
801
|
|
|
|
802
|
|
|
""" |
803
|
|
|
|
804
|
|
|
sources = config.datasets()["electrical_neighbours"]["sources"] |
805
|
|
|
|
806
|
|
|
countries = [ |
807
|
|
|
"AT", |
808
|
|
|
"BE", |
809
|
|
|
"CH", |
810
|
|
|
"CZ", |
811
|
|
|
"DK", |
812
|
|
|
"FR", |
813
|
|
|
"NL", |
814
|
|
|
"NO", |
815
|
|
|
"SE", |
816
|
|
|
"PL", |
817
|
|
|
"UK", |
818
|
|
|
] |
819
|
|
|
|
820
|
|
|
# insert installed capacities |
821
|
|
|
file = zipfile.ZipFile(f"tyndp/{sources['tyndp_capacities']}") |
822
|
|
|
df = pd.read_excel( |
823
|
|
|
file.open("TYNDP-2020-Scenario-Datafile.xlsx").read(), |
824
|
|
|
sheet_name="Capacity", |
825
|
|
|
) |
826
|
|
|
|
827
|
|
|
# differneces between different climate years are very small (<1MW) |
828
|
|
|
# choose 1984 because it is the mean value |
829
|
|
|
df_2030 = ( |
830
|
|
|
df.rename({"Climate Year": "Climate_Year"}, axis="columns") |
831
|
|
|
.query( |
832
|
|
|
'Scenario == "Distributed Energy" & Year == 2030 & ' |
833
|
|
|
"Climate_Year == 1984" |
834
|
|
|
) |
835
|
|
|
.set_index(["Node/Line", "Generator_ID"]) |
836
|
|
|
) |
837
|
|
|
|
838
|
|
|
df_2040 = ( |
839
|
|
|
df.rename({"Climate Year": "Climate_Year"}, axis="columns") |
840
|
|
|
.query( |
841
|
|
|
'Scenario == "Distributed Energy" & Year == 2040 & ' |
842
|
|
|
"Climate_Year == 1984" |
843
|
|
|
) |
844
|
|
|
.set_index(["Node/Line", "Generator_ID"]) |
845
|
|
|
) |
846
|
|
|
|
847
|
|
|
# interpolate linear between 2030 and 2040 for 2035 accordning to |
848
|
|
|
# scenario report of TSO's and the approval by BNetzA |
849
|
|
|
df_2035 = pd.DataFrame(index=df_2030.index) |
850
|
|
|
df_2035["cap_2030"] = df_2030.Value |
851
|
|
|
df_2035["cap_2040"] = df_2040.Value |
852
|
|
|
df_2035.fillna(0.0, inplace=True) |
853
|
|
|
df_2035["cap_2035"] = ( |
854
|
|
|
df_2035["cap_2030"] + (df_2035["cap_2040"] - df_2035["cap_2030"]) / 2 |
855
|
|
|
) |
856
|
|
|
df_2035 = df_2035.reset_index() |
857
|
|
|
df_2035["carrier"] = df_2035.Generator_ID.map(map_carriers_tyndp()) |
858
|
|
|
|
859
|
|
|
# group capacities by new carriers |
860
|
|
|
grouped_capacities = ( |
861
|
|
|
df_2035.groupby(["carrier", "Node/Line"]).cap_2035.sum().reset_index() |
862
|
|
|
) |
863
|
|
|
|
864
|
|
|
# choose capacities for considered countries |
865
|
|
|
return grouped_capacities[ |
866
|
|
|
grouped_capacities["Node/Line"].str[:2].isin(countries) |
867
|
|
|
] |
868
|
|
|
|
869
|
|
|
|
870
|
|
|
def insert_generators(capacities): |
871
|
|
|
"""Insert generators for foreign countries based on TYNDP-data |
872
|
|
|
|
873
|
|
|
Parameters |
874
|
|
|
---------- |
875
|
|
|
capacities : pandas.DataFrame |
876
|
|
|
Installed capacities per foreign node and energy carrier |
877
|
|
|
|
878
|
|
|
Returns |
879
|
|
|
------- |
880
|
|
|
None. |
881
|
|
|
|
882
|
|
|
""" |
883
|
|
|
targets = config.datasets()["electrical_neighbours"]["targets"] |
884
|
|
|
map_buses = get_map_buses() |
885
|
|
|
|
886
|
|
|
# Delete existing data |
887
|
|
|
db.execute_sql( |
888
|
|
|
f""" |
889
|
|
|
DELETE FROM |
890
|
|
|
{targets['generators']['schema']}.{targets['generators']['table']} |
891
|
|
|
WHERE bus IN ( |
892
|
|
|
SELECT bus_id FROM |
893
|
|
|
{targets['buses']['schema']}.{targets['buses']['table']} |
894
|
|
|
WHERE country != 'DE' |
895
|
|
|
AND scn_name = 'eGon2035') |
896
|
|
|
AND scn_name = 'eGon2035' |
897
|
|
|
AND carrier != 'CH4' |
898
|
|
|
""" |
899
|
|
|
) |
900
|
|
|
|
901
|
|
|
db.execute_sql( |
902
|
|
|
f""" |
903
|
|
|
DELETE FROM |
904
|
|
|
{targets['generators_timeseries']['schema']}. |
905
|
|
|
{targets['generators_timeseries']['table']} |
906
|
|
|
WHERE generator_id NOT IN ( |
907
|
|
|
SELECT generator_id FROM |
908
|
|
|
{targets['generators']['schema']}.{targets['generators']['table']} |
909
|
|
|
) |
910
|
|
|
AND scn_name = 'eGon2035' |
911
|
|
|
""" |
912
|
|
|
) |
913
|
|
|
|
914
|
|
|
# Select generators from TYNDP capacities |
915
|
|
|
gen = capacities[ |
916
|
|
|
capacities.carrier.isin( |
917
|
|
|
[ |
918
|
|
|
"others", |
919
|
|
|
"wind_offshore", |
920
|
|
|
"wind_onshore", |
921
|
|
|
"solar", |
922
|
|
|
"reservoir", |
923
|
|
|
"run_of_river", |
924
|
|
|
"lignite", |
925
|
|
|
"coal", |
926
|
|
|
"oil", |
927
|
|
|
"nuclear", |
928
|
|
|
] |
929
|
|
|
) |
930
|
|
|
] |
931
|
|
|
|
932
|
|
|
# Set bus_id |
933
|
|
|
gen.loc[ |
934
|
|
|
gen[gen["Node/Line"].isin(map_buses.keys())].index, "Node/Line" |
935
|
|
|
] = gen.loc[ |
936
|
|
|
gen[gen["Node/Line"].isin(map_buses.keys())].index, "Node/Line" |
937
|
|
|
].map( |
938
|
|
|
map_buses |
939
|
|
|
) |
940
|
|
|
|
941
|
|
|
gen.loc[:, "bus"] = ( |
942
|
|
|
get_foreign_bus_id().loc[gen.loc[:, "Node/Line"]].values |
943
|
|
|
) |
944
|
|
|
|
945
|
|
|
# Add scenario column |
946
|
|
|
gen["scenario"] = "eGon2035" |
947
|
|
|
|
948
|
|
|
# Add marginal costs |
949
|
|
|
gen = add_marginal_costs(gen) |
950
|
|
|
|
951
|
|
|
# insert generators data |
952
|
|
|
session = sessionmaker(bind=db.engine())() |
953
|
|
|
for i, row in gen.iterrows(): |
954
|
|
|
entry = etrago.EgonPfHvGenerator( |
955
|
|
|
scn_name=row.scenario, |
956
|
|
|
generator_id=int(db.next_etrago_id("generator")), |
957
|
|
|
bus=row.bus, |
958
|
|
|
carrier=row.carrier, |
959
|
|
|
p_nom=row.cap_2035, |
960
|
|
|
marginal_cost=row.marginal_cost, |
961
|
|
|
) |
962
|
|
|
|
963
|
|
|
session.add(entry) |
964
|
|
|
session.commit() |
965
|
|
|
session.close() |
966
|
|
|
|
967
|
|
|
# assign generators time-series data |
968
|
|
|
renew_carriers_2035 = ["wind_onshore", "wind_offshore", "solar"] |
969
|
|
|
|
970
|
|
|
sql = f"""SELECT * FROM |
971
|
|
|
{targets['generators_timeseries']['schema']}. |
972
|
|
|
{targets['generators_timeseries']['table']} |
973
|
|
|
WHERE scn_name = 'eGon100RE' |
974
|
|
|
""" |
975
|
|
|
series_egon100 = pd.read_sql_query(sql, db.engine()) |
976
|
|
|
|
977
|
|
|
sql = f""" SELECT * FROM |
978
|
|
|
{targets['generators']['schema']}.{targets['generators']['table']} |
979
|
|
|
WHERE bus IN ( |
980
|
|
|
SELECT bus_id FROM |
981
|
|
|
{targets['buses']['schema']}.{targets['buses']['table']} |
982
|
|
|
WHERE country != 'DE' |
983
|
|
|
AND scn_name = 'eGon2035') |
984
|
|
|
AND scn_name = 'eGon2035' |
985
|
|
|
""" |
986
|
|
|
gen_2035 = pd.read_sql_query(sql, db.engine()) |
987
|
|
|
gen_2035 = gen_2035[gen_2035.carrier.isin(renew_carriers_2035)] |
988
|
|
|
|
989
|
|
|
sql = f""" SELECT * FROM |
990
|
|
|
{targets['generators']['schema']}.{targets['generators']['table']} |
991
|
|
|
WHERE bus IN ( |
992
|
|
|
SELECT bus_id FROM |
993
|
|
|
{targets['buses']['schema']}.{targets['buses']['table']} |
994
|
|
|
WHERE country != 'DE' |
995
|
|
|
AND scn_name = 'eGon100RE') |
996
|
|
|
AND scn_name = 'eGon100RE' |
997
|
|
|
""" |
998
|
|
|
gen_100 = pd.read_sql_query(sql, db.engine()) |
999
|
|
|
gen_100 = gen_100[gen_100["carrier"].isin(renew_carriers_2035)] |
1000
|
|
|
|
1001
|
|
|
# egon_2035_to_100 map the timeseries used in the scenario eGon100RE |
1002
|
|
|
# to the same bus and carrier for the scenario egon2035 |
1003
|
|
|
egon_2035_to_100 = {} |
1004
|
|
|
for i, gen in gen_2035.iterrows(): |
1005
|
|
|
gen_id_100 = gen_100[ |
1006
|
|
|
(gen_100["bus"] == gen["bus"]) |
1007
|
|
|
& (gen_100["carrier"] == gen["carrier"]) |
1008
|
|
|
]["generator_id"].values[0] |
1009
|
|
|
|
1010
|
|
|
egon_2035_to_100[gen["generator_id"]] = gen_id_100 |
1011
|
|
|
|
1012
|
|
|
# insert generators_timeseries data |
1013
|
|
|
session = sessionmaker(bind=db.engine())() |
1014
|
|
|
|
1015
|
|
|
for gen_id in gen_2035.generator_id: |
1016
|
|
|
serie = series_egon100[ |
1017
|
|
|
series_egon100.generator_id == egon_2035_to_100[gen_id] |
1018
|
|
|
]["p_max_pu"].values[0] |
1019
|
|
|
entry = etrago.EgonPfHvGeneratorTimeseries( |
1020
|
|
|
scn_name="eGon2035", generator_id=gen_id, temp_id=1, p_max_pu=serie |
1021
|
|
|
) |
1022
|
|
|
|
1023
|
|
|
session.add(entry) |
1024
|
|
|
session.commit() |
1025
|
|
|
session.close() |
1026
|
|
|
|
1027
|
|
|
|
1028
|
|
|
@db.session_scoped |
1029
|
|
|
def insert_storage(capacities, session=None): |
1030
|
|
|
"""Insert storage units for foreign countries based on TYNDP-data |
1031
|
|
|
|
1032
|
|
|
Parameters |
1033
|
|
|
---------- |
1034
|
|
|
capacities : pandas.DataFrame |
1035
|
|
|
Installed capacities per foreign node and energy carrier |
1036
|
|
|
|
1037
|
|
|
|
1038
|
|
|
Returns |
1039
|
|
|
------- |
1040
|
|
|
None. |
1041
|
|
|
|
1042
|
|
|
""" |
1043
|
|
|
targets = config.datasets()["electrical_neighbours"]["targets"] |
1044
|
|
|
map_buses = get_map_buses() |
1045
|
|
|
|
1046
|
|
|
# Delete existing data |
1047
|
|
|
db.execute_sql( |
1048
|
|
|
f""" |
1049
|
|
|
DELETE FROM {targets['storage']['schema']}.{targets['storage']['table']} |
1050
|
|
|
WHERE bus IN ( |
1051
|
|
|
SELECT bus_id FROM |
1052
|
|
|
{targets['buses']['schema']}.{targets['buses']['table']} |
1053
|
|
|
WHERE country != 'DE' |
1054
|
|
|
AND scn_name = 'eGon2035') |
1055
|
|
|
AND scn_name = 'eGon2035' |
1056
|
|
|
""" |
1057
|
|
|
) |
1058
|
|
|
|
1059
|
|
|
# Add missing information suitable for eTraGo selected from |
1060
|
|
|
# scenario_parameter table |
1061
|
|
|
parameters_pumped_hydro = scenario_parameters.electricity("eGon2035")[ |
1062
|
|
|
"efficiency" |
1063
|
|
|
]["pumped_hydro"] |
1064
|
|
|
|
1065
|
|
|
parameters_battery = scenario_parameters.electricity("eGon2035")[ |
1066
|
|
|
"efficiency" |
1067
|
|
|
]["battery"] |
1068
|
|
|
|
1069
|
|
|
# Select storage capacities from TYNDP-data |
1070
|
|
|
store = capacities[capacities.carrier.isin(["battery", "pumped_hydro"])] |
1071
|
|
|
|
1072
|
|
|
# Set bus_id |
1073
|
|
|
store.loc[ |
1074
|
|
|
store[store["Node/Line"].isin(map_buses.keys())].index, "Node/Line" |
1075
|
|
|
] = store.loc[ |
1076
|
|
|
store[store["Node/Line"].isin(map_buses.keys())].index, "Node/Line" |
1077
|
|
|
].map( |
1078
|
|
|
map_buses |
1079
|
|
|
) |
1080
|
|
|
|
1081
|
|
|
store.loc[:, "bus"] = ( |
1082
|
|
|
get_foreign_bus_id().loc[store.loc[:, "Node/Line"]].values |
1083
|
|
|
) |
1084
|
|
|
|
1085
|
|
|
# Add columns for additional parameters to df |
1086
|
|
|
( |
1087
|
|
|
store["dispatch"], |
1088
|
|
|
store["store"], |
1089
|
|
|
store["standing_loss"], |
1090
|
|
|
store["max_hours"], |
1091
|
|
|
) = (None, None, None, None) |
1092
|
|
|
|
1093
|
|
|
# Insert carrier specific parameters |
1094
|
|
|
|
1095
|
|
|
parameters = ["dispatch", "store", "standing_loss", "max_hours"] |
1096
|
|
|
|
1097
|
|
|
for x in parameters: |
1098
|
|
|
store.loc[store["carrier"] == "battery", x] = parameters_battery[x] |
1099
|
|
|
store.loc[ |
1100
|
|
|
store["carrier"] == "pumped_hydro", x |
1101
|
|
|
] = parameters_pumped_hydro[x] |
1102
|
|
|
|
1103
|
|
|
# insert data |
1104
|
|
|
for i, row in store.iterrows(): |
1105
|
|
|
entry = etrago.EgonPfHvStorage( |
1106
|
|
|
scn_name="eGon2035", |
1107
|
|
|
storage_id=int(db.next_etrago_id("storage")), |
1108
|
|
|
bus=row.bus, |
1109
|
|
|
max_hours=row.max_hours, |
1110
|
|
|
efficiency_store=row.store, |
1111
|
|
|
efficiency_dispatch=row.dispatch, |
1112
|
|
|
standing_loss=row.standing_loss, |
1113
|
|
|
carrier=row.carrier, |
1114
|
|
|
p_nom=row.cap_2035, |
1115
|
|
|
) |
1116
|
|
|
|
1117
|
|
|
session.add(entry) |
1118
|
|
|
session.commit() |
1119
|
|
|
|
1120
|
|
|
|
1121
|
|
|
def get_map_buses(): |
1122
|
|
|
"""Returns a dictonary of foreign regions which are aggregated to another |
1123
|
|
|
|
1124
|
|
|
Returns |
1125
|
|
|
------- |
1126
|
|
|
Combination of aggregated regions |
1127
|
|
|
|
1128
|
|
|
|
1129
|
|
|
""" |
1130
|
|
|
return { |
1131
|
|
|
"DK00": "DKW1", |
1132
|
|
|
"DKKF": "DKE1", |
1133
|
|
|
"FR15": "FR00", |
1134
|
|
|
"NON1": "NOM1", |
1135
|
|
|
"NOS0": "NOM1", |
1136
|
|
|
"NOS1": "NOM1", |
1137
|
|
|
"PLE0": "PL00", |
1138
|
|
|
"PLI0": "PL00", |
1139
|
|
|
"SE00": "SE02", |
1140
|
|
|
"SE01": "SE02", |
1141
|
|
|
"SE03": "SE02", |
1142
|
|
|
"SE04": "SE02", |
1143
|
|
|
"RU": "RU00", |
1144
|
|
|
} |
1145
|
|
|
|
1146
|
|
|
|
1147
|
|
|
def tyndp_generation(): |
1148
|
|
|
"""Insert data from TYNDP 2020 accordning to NEP 2021 |
1149
|
|
|
Scenario 'Distributed Energy', linear interpolate between 2030 and 2040 |
1150
|
|
|
|
1151
|
|
|
Returns |
1152
|
|
|
------- |
1153
|
|
|
None. |
1154
|
|
|
""" |
1155
|
|
|
|
1156
|
|
|
capacities = calc_capacities() |
1157
|
|
|
|
1158
|
|
|
insert_generators(capacities) |
1159
|
|
|
|
1160
|
|
|
insert_storage(capacities) |
1161
|
|
|
|
1162
|
|
|
|
1163
|
|
|
@db.session_scoped |
1164
|
|
|
def tyndp_demand(session=None): |
1165
|
|
|
"""Copy load timeseries data from TYNDP 2020. |
1166
|
|
|
According to NEP 2021, the data for 2030 and 2040 is interpolated linearly. |
1167
|
|
|
|
1168
|
|
|
Returns |
1169
|
|
|
------- |
1170
|
|
|
None. |
1171
|
|
|
|
1172
|
|
|
""" |
1173
|
|
|
map_buses = get_map_buses() |
1174
|
|
|
|
1175
|
|
|
sources = config.datasets()["electrical_neighbours"]["sources"] |
1176
|
|
|
targets = config.datasets()["electrical_neighbours"]["targets"] |
1177
|
|
|
|
1178
|
|
|
# Delete existing data |
1179
|
|
|
db.execute_sql( |
1180
|
|
|
f""" |
1181
|
|
|
DELETE FROM {targets['loads']['schema']}. |
1182
|
|
|
{targets['loads']['table']} |
1183
|
|
|
WHERE |
1184
|
|
|
scn_name = 'eGon2035' |
1185
|
|
|
AND carrier = 'AC' |
1186
|
|
|
AND bus NOT IN ( |
1187
|
|
|
SELECT bus_i |
1188
|
|
|
FROM {sources['osmtgmod_bus']['schema']}. |
1189
|
|
|
{sources['osmtgmod_bus']['table']}) |
1190
|
|
|
""" |
1191
|
|
|
) |
1192
|
|
|
|
1193
|
|
|
nodes = [ |
1194
|
|
|
"AT00", |
1195
|
|
|
"BE00", |
1196
|
|
|
"CH00", |
1197
|
|
|
"CZ00", |
1198
|
|
|
"DKE1", |
1199
|
|
|
"DKW1", |
1200
|
|
|
"FR00", |
1201
|
|
|
"NL00", |
1202
|
|
|
"LUB1", |
1203
|
|
|
"LUF1", |
1204
|
|
|
"LUG1", |
1205
|
|
|
"NOM1", |
1206
|
|
|
"NON1", |
1207
|
|
|
"NOS0", |
1208
|
|
|
"SE01", |
1209
|
|
|
"SE02", |
1210
|
|
|
"SE03", |
1211
|
|
|
"SE04", |
1212
|
|
|
"PL00", |
1213
|
|
|
"UK00", |
1214
|
|
|
"UKNI", |
1215
|
|
|
] |
1216
|
|
|
# Assign etrago bus_id to TYNDP nodes |
1217
|
|
|
buses = pd.DataFrame({"nodes": nodes}) |
1218
|
|
|
buses.loc[ |
1219
|
|
|
buses[buses.nodes.isin(map_buses.keys())].index, "nodes" |
1220
|
|
|
] = buses[buses.nodes.isin(map_buses.keys())].nodes.map(map_buses) |
1221
|
|
|
buses.loc[:, "bus"] = ( |
1222
|
|
|
get_foreign_bus_id().loc[buses.loc[:, "nodes"]].values |
1223
|
|
|
) |
1224
|
|
|
buses.set_index("nodes", inplace=True) |
1225
|
|
|
buses = buses[~buses.index.duplicated(keep="first")] |
1226
|
|
|
|
1227
|
|
|
# Read in data from TYNDP for 2030 and 2040 |
1228
|
|
|
dataset_2030 = pd.read_excel( |
1229
|
|
|
f"tyndp/{sources['tyndp_demand_2030']}", sheet_name=nodes, skiprows=10 |
1230
|
|
|
) |
1231
|
|
|
|
1232
|
|
|
dataset_2040 = pd.read_excel( |
1233
|
|
|
f"tyndp/{sources['tyndp_demand_2040']}", sheet_name=None, skiprows=10 |
1234
|
|
|
) |
1235
|
|
|
|
1236
|
|
|
# Transform map_buses to pandas.Series and select only used values |
1237
|
|
|
map_series = pd.Series(map_buses) |
1238
|
|
|
map_series = map_series[map_series.index.isin(nodes)] |
1239
|
|
|
|
1240
|
|
|
# Calculate and insert demand timeseries per etrago bus_id |
1241
|
|
|
for bus in buses.index: |
1242
|
|
|
nodes = [bus] |
1243
|
|
|
|
1244
|
|
|
if bus in map_series.values: |
1245
|
|
|
nodes.extend(list(map_series[map_series == bus].index.values)) |
1246
|
|
|
|
1247
|
|
|
load_id = db.next_etrago_id("load") |
1248
|
|
|
|
1249
|
|
|
# Some etrago bus_ids represent multiple TYNDP nodes, |
1250
|
|
|
# in this cases the loads are summed |
1251
|
|
|
data_2030 = pd.Series(index=range(8760), data=0.0) |
1252
|
|
|
for node in nodes: |
1253
|
|
|
data_2030 = dataset_2030[node][2011] + data_2030 |
1254
|
|
|
|
1255
|
|
|
try: |
1256
|
|
|
data_2040 = pd.Series(index=range(8760), data=0.0) |
1257
|
|
|
|
1258
|
|
|
for node in nodes: |
1259
|
|
|
data_2040 = dataset_2040[node][2011] + data_2040 |
1260
|
|
|
except: |
1261
|
|
|
data_2040 = data_2030 |
1262
|
|
|
|
1263
|
|
|
# According to the NEP, data for 2030 and 2040 is linear interpolated |
1264
|
|
|
data_2035 = ((data_2030 + data_2040) / 2)[:8760] |
1265
|
|
|
|
1266
|
|
|
entry = etrago.EgonPfHvLoad( |
1267
|
|
|
scn_name="eGon2035", |
1268
|
|
|
load_id=int(load_id), |
1269
|
|
|
carrier="AC", |
1270
|
|
|
bus=int(buses.bus[bus]), |
1271
|
|
|
) |
1272
|
|
|
|
1273
|
|
|
entry_ts = etrago.EgonPfHvLoadTimeseries( |
1274
|
|
|
scn_name="eGon2035", |
1275
|
|
|
load_id=int(load_id), |
1276
|
|
|
temp_id=1, |
1277
|
|
|
p_set=list(data_2035.values), |
1278
|
|
|
) |
1279
|
|
|
|
1280
|
|
|
session.add(entry) |
1281
|
|
|
session.add(entry_ts) |
1282
|
|
|
session.commit() |
1283
|
|
|
|