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"""Import MaStR dataset and write to DB tables |
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Data dump from Marktstammdatenregister (2022-11-17) is imported into the |
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database. Only some technologies are taken into account and written to the |
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following tables: |
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* PV: table `supply.egon_power_plants_pv` |
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* wind turbines: table `supply.egon_power_plants_wind` |
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* biomass/biogas plants: table `supply.egon_power_plants_biomass` |
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* hydro plants: table `supply.egon_power_plants_hydro` |
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Handling of empty source data in MaStr dump: |
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* `voltage_level`: inferred based on nominal power (`capacity`) using the |
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ranges from |
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https://redmine.iks.cs.ovgu.de/oe/projects/ego-n/wiki/Definition_of_thresholds_for_voltage_level_assignment |
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which results in True in column `voltage_level_inferred`. Remaining datasets |
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are set to -1 (which only occurs if `capacity` is empty). |
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* `supply.egon_power_plants_*.bus_id`: set to -1 (only if not within grid |
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districts or no geom available, e.g. for units with nom. power <30 kW) |
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* `supply.egon_power_plants_hydro.plant_type`: NaN |
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The data is used especially for the generation of status quo grids by ding0. |
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""" |
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from __future__ import annotations |
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from pathlib import Path |
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from loguru import logger |
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import geopandas as gpd |
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import numpy as np |
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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.mastr import WORKING_DIR_MASTR_NEW |
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from egon.data.datasets.power_plants.mastr_db_classes import ( |
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EgonMastrGeocoded, |
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EgonPowerPlantsBiomass, |
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EgonPowerPlantsCombustion, |
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EgonPowerPlantsGsgk, |
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EgonPowerPlantsHydro, |
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EgonPowerPlantsNuclear, |
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EgonPowerPlantsPv, |
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EgonPowerPlantsStorage, |
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EgonPowerPlantsWind, |
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) |
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from egon.data.datasets.power_plants.pv_rooftop_buildings import ( |
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federal_state_data, |
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) |
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TESTMODE_OFF = ( |
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config.settings()["egon-data"]["--dataset-boundary"] == "Everything" |
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) |
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def isfloat(num: str): |
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""" |
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Determine if string can be converted to float. |
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Parameters |
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----------- |
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num : str |
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String to parse. |
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Returns |
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------- |
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bool |
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Returns True in string can be parsed to float. |
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""" |
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try: |
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float(num) |
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return True |
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except ValueError: |
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return False |
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def zip_and_municipality_from_standort( |
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standort: str, |
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) -> tuple[str, bool]: |
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""" |
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Get zip code and municipality from Standort string split into a list. |
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Parameters |
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----------- |
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standort : str |
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Standort as given from MaStR data. |
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Returns |
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------- |
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str |
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Standort with only the zip code and municipality |
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as well a ', Germany' added. |
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""" |
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standort_list = standort.split() |
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found = False |
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count = 0 |
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for count, elem in enumerate(standort_list): |
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if len(elem) != 5: |
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continue |
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if not elem.isnumeric(): |
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continue |
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found = True |
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break |
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if found: |
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cleaned_str = " ".join(standort_list[count:]) |
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return cleaned_str, found |
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logger.warning( |
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"Couldn't identify zip code. This entry will be dropped." |
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f" Original standort: {standort}." |
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) |
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return standort, found |
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def infer_voltage_level( |
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units_gdf: gpd.GeoDataFrame, |
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) -> gpd.GeoDataFrame: |
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""" |
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Infer nan values in voltage level derived from generator capacity to |
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the power plants. |
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Parameters |
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----------- |
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units_gdf : geopandas.GeoDataFrame |
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GeoDataFrame containing units with voltage levels from MaStR |
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Returnsunits_gdf: gpd.GeoDataFrame |
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------- |
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geopandas.GeoDataFrame |
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GeoDataFrame containing units all having assigned a voltage level. |
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""" |
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def voltage_levels(p: float) -> int: |
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if p <= 100: |
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return 7 |
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elif p <= 200: |
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return 6 |
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elif p <= 5500: |
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return 5 |
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elif p <= 20000: |
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return 4 |
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elif p <= 120000: |
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return 3 |
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return 1 |
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units_gdf["voltage_level_inferred"] = False |
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mask = units_gdf.voltage_level.isna() |
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units_gdf.loc[mask, "voltage_level_inferred"] = True |
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units_gdf.loc[mask, "voltage_level"] = units_gdf.loc[ |
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mask |
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].Nettonennleistung.apply(voltage_levels) |
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return units_gdf |
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def import_mastr() -> None: |
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"""Import MaStR data into database""" |
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engine = db.engine() |
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# import geocoded data |
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cfg = config.datasets()["mastr_new"] |
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path_parts = cfg["geocoding_path"] |
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path = Path(*["."] + path_parts).resolve() |
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path = list(path.iterdir())[0] |
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deposit_id_geocoding = int(path.parts[-1].split(".")[0].split("_")[-1]) |
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deposit_id_mastr = cfg["deposit_id"] |
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if deposit_id_geocoding != deposit_id_mastr: |
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raise AssertionError( |
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f"The zenodo (sandbox) deposit ID {deposit_id_mastr} for the MaStR" |
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f" dataset is not matching with the geocoding version " |
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f"{deposit_id_geocoding}. Make sure to hermonize the data. When " |
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f"the MaStR dataset is updated also update the geocoding and " |
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f"update the egon data bundle. The geocoding can be done using: " |
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f"https://github.com/RLI-sandbox/mastr-geocoding" |
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) |
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geocoding_gdf = gpd.read_file(path) |
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# remove failed requests |
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geocoding_gdf = geocoding_gdf.loc[geocoding_gdf.geometry.is_valid] |
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EgonMastrGeocoded.__table__.drop(bind=engine, checkfirst=True) |
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EgonMastrGeocoded.__table__.create(bind=engine, checkfirst=True) |
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geocoding_gdf.to_postgis( |
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name=EgonMastrGeocoded.__tablename__, |
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con=engine, |
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if_exists="append", |
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schema=EgonMastrGeocoded.__table_args__["schema"], |
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index=True, |
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) |
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cfg = config.datasets()["power_plants"] |
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cols_mapping = { |
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"all": { |
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"EinheitMastrNummer": "gens_id", |
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"EinheitBetriebsstatus": "status", |
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"Inbetriebnahmedatum": "commissioning_date", |
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"Postleitzahl": "postcode", |
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"Ort": "city", |
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"Gemeinde": "municipality", |
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"Bundesland": "federal_state", |
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"Nettonennleistung": "capacity", |
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"Einspeisungsart": "feedin_type", |
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}, |
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"pv": { |
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"Lage": "site_type", |
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"Standort": "site", |
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"Nutzungsbereich": "usage_sector", |
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"Hauptausrichtung": "orientation_primary", |
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"HauptausrichtungNeigungswinkel": "orientation_primary_angle", |
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"Nebenausrichtung": "orientation_secondary", |
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"NebenausrichtungNeigungswinkel": "orientation_secondary_angle", |
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"EinheitlicheAusrichtungUndNeigungswinkel": "orientation_uniform", |
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"AnzahlModule": "module_count", |
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"zugeordneteWirkleistungWechselrichter": "capacity_inverter", |
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}, |
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"wind": { |
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"Lage": "site_type", |
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"Hersteller": "manufacturer_name", |
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"Typenbezeichnung": "type_name", |
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"Nabenhoehe": "hub_height", |
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"Rotordurchmesser": "rotor_diameter", |
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}, |
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"biomass": { |
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"Technologie": "technology", |
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"Hauptbrennstoff": "main_fuel", |
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"Biomasseart": "fuel_type", |
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"ThermischeNutzleistung": "th_capacity", |
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}, |
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"hydro": { |
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"ArtDerWasserkraftanlage": "plant_type", |
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"ArtDesZuflusses": "water_origin", |
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}, |
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"combustion": { |
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"Energietraeger": "carrier", |
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"Hauptbrennstoff": "main_fuel", |
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"WeitererHauptbrennstoff": "other_main_fuel", |
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"Technologie": "technology", |
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"ThermischeNutzleistung": "th_capacity", |
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}, |
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"gsgk": { |
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"Energietraeger": "carrier", |
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"Technologie": "technology", |
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}, |
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"nuclear": { |
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"Energietraeger": "carrier", |
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"Technologie": "technology", |
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}, |
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"storage": { |
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"Energietraeger": "carrier", |
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"Technologie": "technology", |
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"Batterietechnologie": "battery_type", |
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"Pumpspeichertechnologie": "pump_storage_type", |
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}, |
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} |
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source_files = { |
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"pv": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_pv"], |
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"wind": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_wind"], |
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"biomass": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_biomass"], |
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"hydro": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_hydro"], |
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"combustion": WORKING_DIR_MASTR_NEW |
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/ cfg["sources"]["mastr_combustion"], |
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"gsgk": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_gsgk"], |
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"nuclear": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_nuclear"], |
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"storage": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_storage"], |
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} |
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target_tables = { |
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"pv": EgonPowerPlantsPv, |
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"wind": EgonPowerPlantsWind, |
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"biomass": EgonPowerPlantsBiomass, |
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"hydro": EgonPowerPlantsHydro, |
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"combustion": EgonPowerPlantsCombustion, |
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"gsgk": EgonPowerPlantsGsgk, |
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"nuclear": EgonPowerPlantsNuclear, |
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"storage": EgonPowerPlantsStorage, |
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} |
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vlevel_mapping = { |
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"Höchstspannung": 1, |
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"UmspannungZurHochspannung": 2, |
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"Hochspannung": 3, |
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"UmspannungZurMittelspannung": 4, |
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"Mittelspannung": 5, |
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"UmspannungZurNiederspannung": 6, |
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"Niederspannung": 7, |
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} |
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295
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# import locations |
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296
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locations = pd.read_csv( |
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297
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WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_location"], |
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index_col=None, |
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) |
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300
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301
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# import grid districts |
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302
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mv_grid_districts = db.select_geodataframe( |
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f""" |
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304
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SELECT * FROM {cfg['sources']['egon_mv_grid_district']} |
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""", |
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306
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epsg=4326, |
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) |
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308
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309
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# import units |
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310
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technologies = [ |
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311
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"pv", |
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312
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"wind", |
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313
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"biomass", |
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314
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"hydro", |
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315
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|
|
"combustion", |
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316
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"gsgk", |
|
317
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|
|
"nuclear", |
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318
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"storage", |
|
319
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|
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] |
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320
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321
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for tech in technologies: |
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322
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# read units |
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323
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logger.info(f"===== Importing MaStR dataset: {tech} =====") |
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324
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|
|
logger.debug("Reading CSV and filtering data...") |
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325
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|
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units = pd.read_csv( |
|
326
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|
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source_files[tech], |
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327
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|
|
usecols=( |
|
328
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["LokationMastrNummer", "Laengengrad", "Breitengrad", "Land"] |
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329
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|
+ list(cols_mapping["all"].keys()) |
|
330
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|
+ list(cols_mapping[tech].keys()) |
|
331
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), |
|
332
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|
|
index_col=None, |
|
333
|
|
|
dtype={"Postleitzahl": str}, |
|
334
|
|
|
).rename(columns=cols_mapping) |
|
335
|
|
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|
|
336
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|
|
# drop units outside of Germany |
|
337
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|
|
len_old = len(units) |
|
338
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|
|
units = units.loc[units.Land == "Deutschland"] |
|
339
|
|
|
logger.debug( |
|
340
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|
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f"{len_old - len(units)} units outside of Germany dropped..." |
|
341
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|
|
) |
|
342
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|
|
|
|
343
|
|
|
# get boundary |
|
344
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|
|
boundary = ( |
|
345
|
|
|
federal_state_data(geocoding_gdf.crs).dissolve().at[0, "geom"] |
|
346
|
|
|
) |
|
347
|
|
|
|
|
348
|
|
|
# filter for SH units if in testmode |
|
349
|
|
|
if not TESTMODE_OFF: |
|
350
|
|
|
logger.info( |
|
351
|
|
|
"TESTMODE: Dropping all units outside of Schleswig-Holstein..." |
|
352
|
|
|
) |
|
353
|
|
|
units = units.loc[units.Bundesland == "SchleswigHolstein"] |
|
354
|
|
|
|
|
355
|
|
|
# merge and rename voltage level |
|
356
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|
|
logger.debug("Merging with locations and allocate voltage level...") |
|
357
|
|
|
units = units.merge( |
|
358
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|
|
locations[["MaStRNummer", "Spannungsebene"]], |
|
359
|
|
|
left_on="LokationMastrNummer", |
|
360
|
|
|
right_on="MaStRNummer", |
|
361
|
|
|
how="left", |
|
362
|
|
|
) |
|
363
|
|
|
# convert voltage levels to numbers |
|
364
|
|
|
units["voltage_level"] = units.Spannungsebene.replace(vlevel_mapping) |
|
365
|
|
|
# set voltage level for nan values |
|
366
|
|
|
units = infer_voltage_level(units) |
|
367
|
|
|
|
|
368
|
|
|
# add geometry |
|
369
|
|
|
logger.debug("Adding geometries...") |
|
370
|
|
|
units = gpd.GeoDataFrame( |
|
371
|
|
|
units, |
|
372
|
|
|
geometry=gpd.points_from_xy( |
|
373
|
|
|
units["Laengengrad"], units["Breitengrad"], crs=4326 |
|
374
|
|
|
), |
|
375
|
|
|
crs=4326, |
|
376
|
|
|
) |
|
377
|
|
|
|
|
378
|
|
|
units["geometry_geocoded"] = ( |
|
379
|
|
|
units.Laengengrad.isna() | units.Laengengrad.isna() |
|
380
|
|
|
) |
|
381
|
|
|
|
|
382
|
|
|
units.loc[~units.geometry_geocoded, "geometry_geocoded"] = ~units.loc[ |
|
383
|
|
|
~units.geometry_geocoded, "geometry" |
|
384
|
|
|
].is_valid |
|
385
|
|
|
|
|
386
|
|
|
units_wo_geom = units["geometry_geocoded"].sum() |
|
387
|
|
|
|
|
388
|
|
|
logger.debug( |
|
389
|
|
|
f"{units_wo_geom}/{len(units)} units do not have a geometry!" |
|
390
|
|
|
" Adding geocoding results." |
|
391
|
|
|
) |
|
392
|
|
|
|
|
393
|
|
|
# determine zip and municipality string |
|
394
|
|
|
mask = ( |
|
395
|
|
|
units.Postleitzahl.apply(isfloat) |
|
396
|
|
|
& ~units.Postleitzahl.isna() |
|
397
|
|
|
& ~units.Gemeinde.isna() |
|
398
|
|
|
) |
|
399
|
|
|
units["zip_and_municipality"] = np.nan |
|
400
|
|
|
ok_units = units.loc[mask] |
|
401
|
|
|
|
|
402
|
|
|
units.loc[mask, "zip_and_municipality"] = ( |
|
403
|
|
|
ok_units.Postleitzahl.astype(int).astype(str).str.zfill(5) |
|
404
|
|
|
+ " " |
|
405
|
|
|
+ ok_units.Gemeinde.astype(str).str.rstrip().str.lstrip() |
|
406
|
|
|
+ ", Deutschland" |
|
407
|
|
|
) |
|
408
|
|
|
|
|
409
|
|
|
# get zip and municipality from Standort |
|
410
|
|
|
parse_df = units.loc[~mask] |
|
411
|
|
|
|
|
412
|
|
|
if not parse_df.empty and "Standort" in parse_df.columns: |
|
413
|
|
|
init_len = len(parse_df) |
|
414
|
|
|
|
|
415
|
|
|
logger.info( |
|
416
|
|
|
f"Parsing ZIP code and municipality from Standort for " |
|
417
|
|
|
f"{init_len} values for {tech}." |
|
418
|
|
|
) |
|
419
|
|
|
|
|
420
|
|
|
parse_df[["zip_and_municipality", "drop_this"]] = ( |
|
421
|
|
|
parse_df.Standort.astype(str) |
|
422
|
|
|
.apply(zip_and_municipality_from_standort) |
|
423
|
|
|
.tolist() |
|
424
|
|
|
) |
|
425
|
|
|
|
|
426
|
|
|
parse_df = parse_df.loc[parse_df.drop_this] |
|
427
|
|
|
|
|
428
|
|
|
if not parse_df.empty: |
|
429
|
|
|
units.loc[ |
|
430
|
|
|
parse_df.index, "zip_and_municipality" |
|
431
|
|
|
] = parse_df.zip_and_municipality |
|
432
|
|
|
|
|
433
|
|
|
# add geocoding to missing |
|
434
|
|
|
units = units.merge( |
|
435
|
|
|
right=geocoding_gdf[["zip_and_municipality", "geometry"]].rename( |
|
436
|
|
|
columns={"geometry": "temp"} |
|
437
|
|
|
), |
|
438
|
|
|
how="left", |
|
439
|
|
|
on="zip_and_municipality", |
|
440
|
|
|
) |
|
441
|
|
|
|
|
442
|
|
|
units.loc[units.geometry_geocoded, "geometry"] = units.loc[ |
|
443
|
|
|
units.geometry_geocoded, "temp" |
|
444
|
|
|
] |
|
445
|
|
|
|
|
446
|
|
|
init_len = len(units) |
|
447
|
|
|
|
|
448
|
|
|
logger.info( |
|
449
|
|
|
"Dropping units outside boundary by geometry or without geometry" |
|
450
|
|
|
"..." |
|
451
|
|
|
) |
|
452
|
|
|
|
|
453
|
|
|
units.dropna(subset=["geometry"], inplace=True) |
|
454
|
|
|
|
|
455
|
|
|
units = units.loc[units.geometry.within(boundary)] |
|
456
|
|
|
|
|
457
|
|
|
logger.debug( |
|
458
|
|
|
f"{init_len - len(units)}/{init_len} " |
|
459
|
|
|
f"({((init_len - len(units)) / init_len) * 100: g} %) dropped." |
|
460
|
|
|
) |
|
461
|
|
|
|
|
462
|
|
|
# drop unnecessary and rename columns |
|
463
|
|
|
logger.debug("Reformatting...") |
|
464
|
|
|
units.drop( |
|
465
|
|
|
columns=[ |
|
466
|
|
|
"LokationMastrNummer", |
|
467
|
|
|
"MaStRNummer", |
|
468
|
|
|
"Laengengrad", |
|
469
|
|
|
"Breitengrad", |
|
470
|
|
|
"Spannungsebene", |
|
471
|
|
|
"Land", |
|
472
|
|
|
"temp", |
|
473
|
|
|
], |
|
474
|
|
|
inplace=True, |
|
475
|
|
|
) |
|
476
|
|
|
mapping = cols_mapping["all"].copy() |
|
477
|
|
|
mapping.update(cols_mapping[tech]) |
|
478
|
|
|
mapping.update({"geometry": "geom"}) |
|
479
|
|
|
units.rename(columns=mapping, inplace=True) |
|
480
|
|
|
units["voltage_level"] = units.voltage_level.fillna(-1).astype(int) |
|
481
|
|
|
|
|
482
|
|
|
units.set_geometry("geom", inplace=True) |
|
483
|
|
|
units["id"] = range(0, len(units)) |
|
484
|
|
|
|
|
485
|
|
|
# change capacity unit: kW to MW |
|
486
|
|
|
units["capacity"] = units["capacity"] / 1e3 |
|
487
|
|
|
if "capacity_inverter" in units.columns: |
|
488
|
|
|
units["capacity_inverter"] = units["capacity_inverter"] / 1e3 |
|
489
|
|
|
if "th_capacity" in units.columns: |
|
490
|
|
|
units["th_capacity"] = units["th_capacity"] / 1e3 |
|
491
|
|
|
|
|
492
|
|
|
# assign bus ids |
|
493
|
|
|
logger.debug("Assigning bus ids...") |
|
494
|
|
|
units = units.assign( |
|
495
|
|
|
bus_id=units.loc[~units.geom.x.isna()] |
|
496
|
|
|
.sjoin(mv_grid_districts[["bus_id", "geom"]], how="left") |
|
497
|
|
|
.drop(columns=["index_right"]) |
|
498
|
|
|
.bus_id |
|
499
|
|
|
) |
|
500
|
|
|
units["bus_id"] = units.bus_id.fillna(-1).astype(int) |
|
501
|
|
|
|
|
502
|
|
|
# write to DB |
|
503
|
|
|
logger.info(f"Writing {len(units)} units to DB...") |
|
504
|
|
|
|
|
505
|
|
|
units.to_postgis( |
|
506
|
|
|
name=target_tables[tech].__tablename__, |
|
507
|
|
|
con=engine, |
|
508
|
|
|
if_exists="append", |
|
509
|
|
|
schema=target_tables[tech].__table_args__["schema"], |
|
510
|
|
|
) |
|
511
|
|
|
|
openego /
eGon-data
