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"""The central module containing all code dealing with importing data from |
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Netzentwicklungsplan 2035, Version 2031, Szenario C |
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""" |
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from pathlib import Path |
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import datetime |
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import json |
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import time |
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from sqlalchemy import Column, Float, Integer, String |
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from sqlalchemy.ext.declarative import declarative_base |
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from sqlalchemy.orm import sessionmaker |
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import numpy as np |
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import pandas as pd |
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import yaml |
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from egon.data import config, db |
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from egon.data.datasets import Dataset, wrapped_partial |
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from egon.data.metadata import ( |
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context, |
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generate_resource_fields_from_sqla_model, |
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license_ccby, |
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meta_metadata, |
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sources, |
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) |
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from egon_validation import( |
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RowCountValidation, |
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DataTypeValidation, |
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NotNullAndNotNaNValidation, |
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WholeTableNotNullAndNotNaNValidation, |
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ValueSetValidation |
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) |
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Base = declarative_base() |
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class EgonScenarioCapacities(Base): |
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__tablename__ = "egon_scenario_capacities" |
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__table_args__ = {"schema": "supply"} |
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index = Column(Integer, primary_key=True) |
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component = Column(String(25)) |
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carrier = Column(String(50)) |
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capacity = Column(Float) |
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nuts = Column(String(12)) |
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scenario_name = Column(String(50)) |
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class NEP2021ConvPowerPlants(Base): |
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__tablename__ = "egon_nep_2021_conventional_powerplants" |
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__table_args__ = {"schema": "supply"} |
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index = Column(String(50), primary_key=True) |
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bnetza_id = Column(String(50)) |
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name = Column(String(100)) |
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name_unit = Column(String(50)) |
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carrier_nep = Column(String(50)) |
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carrier = Column(String(12)) |
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chp = Column(String(12)) |
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postcode = Column(String(12)) |
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city = Column(String(50)) |
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federal_state = Column(String(12)) |
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commissioned = Column(String(12)) |
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status = Column(String(50)) |
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capacity = Column(Float) |
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a2035_chp = Column(String(12)) |
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a2035_capacity = Column(Float) |
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b2035_chp = Column(String(12)) |
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b2035_capacity = Column(Float) |
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c2035_chp = Column(String(12)) |
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c2035_capacity = Column(Float) |
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b2040_chp = Column(String(12)) |
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b2040_capacity = Column(Float) |
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def create_table(): |
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"""Create input tables for scenario setup |
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Returns |
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------- |
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None. |
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""" |
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engine = db.engine() |
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db.execute_sql("CREATE SCHEMA IF NOT EXISTS supply;") |
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EgonScenarioCapacities.__table__.drop(bind=engine, checkfirst=True) |
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NEP2021ConvPowerPlants.__table__.drop(bind=engine, checkfirst=True) |
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EgonScenarioCapacities.__table__.create(bind=engine, checkfirst=True) |
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NEP2021ConvPowerPlants.__table__.create(bind=engine, checkfirst=True) |
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def nuts_mapping(): |
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nuts_mapping = { |
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"BW": "DE1", |
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"NW": "DEA", |
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"HE": "DE7", |
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"BB": "DE4", |
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"HB": "DE5", |
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"RP": "DEB", |
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"ST": "DEE", |
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"SH": "DEF", |
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"MV": "DE8", |
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"TH": "DEG", |
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"NI": "DE9", |
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"SN": "DED", |
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"HH": "DE6", |
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"SL": "DEC", |
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"BE": "DE3", |
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"BY": "DE2", |
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} |
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return nuts_mapping |
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def insert_capacities_status_quo(scenario: str) -> None: |
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"""Insert capacity of rural heat pumps for status quo |
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Returns |
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------- |
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None. |
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""" |
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targets = config.datasets()["scenario_input"]["targets"] |
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# Delete rows if already exist |
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db.execute_sql( |
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f""" |
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DELETE FROM |
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{targets['scenario_capacities']['schema']}. |
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{targets['scenario_capacities']['table']} |
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WHERE scenario_name = '{scenario}' |
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""" |
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) |
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rural_heat_capacity = { |
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# Rural heat capacity for 2019 according to NEP 2035, version 2021 |
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"status2019": 1e6 * 5e-3, |
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# Rural heat capacity for 2023 according to NEP 2037, version 2023 |
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# 1.2 Mio. for 2020 |
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# https://www.netzentwicklungsplan.de/sites/default/files/2023-07/ |
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# NEP_2037_2045_V2023_2_Entwurf_Teil1_1.pdf#page=25 |
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# and 3 kW per heat pump |
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# https://www.netzentwicklungsplan.de/sites/default/files/2022-11/ |
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# NEP_2035_V2021_2_Entwurf_Teil1.pdf#page=33 |
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# plus 0.15 Mio. 2021 and 0.24 Mio. in 2022 |
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# https://www.enercity.de/magazin/unsere-welt/waermepumpen-boom |
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# plus 0.2 Mio. in H1 2023 -> Assumption 2023: 2 * 0.2 Mio = 0.4 Mio. |
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"status2023": (1.2 + 0.15 + 0.24 + 0.4) * 1e6 * 3e-3, |
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}[scenario] |
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if config.settings()["egon-data"]["--dataset-boundary"] != "Everything": |
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rural_heat_capacity *= population_share() |
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db.execute_sql( |
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f""" |
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INSERT INTO |
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{targets['scenario_capacities']['schema']}. |
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{targets['scenario_capacities']['table']} |
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(component, carrier, capacity, nuts, scenario_name) |
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VALUES ( |
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'link', |
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'rural_heat_pump', |
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{rural_heat_capacity}, |
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'DE', |
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'{scenario}' |
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) |
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""" |
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) |
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# Include small storages for scenario2019 |
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small_storages = { |
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# MW for Germany |
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"status2019": 600, |
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# 1.3 GW in 2020/2021 |
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# https://www.netzentwicklungsplan.de/sites/default/files/2023-07/ |
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# NEP_2037_2045_V2023_2_Entwurf_Teil1_1.pdf#page=25 |
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# Installed quantity 2020: 272,000 |
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# Installed quantity 2023: 1,197,000 |
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# https://www.photovoltaik.eu/solarspeicher/ |
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# bsw-speicherkapazitaet-von-heimspeichern-2023-verdoppelt |
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"status2023": 1300 * 1197 / 272, |
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}[scenario] |
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db.execute_sql( |
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f""" |
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INSERT INTO |
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{targets['scenario_capacities']['schema']}. |
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{targets['scenario_capacities']['table']} |
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(component, carrier, capacity, nuts, scenario_name) |
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VALUES ( |
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'storage_units', |
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'battery', |
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{small_storages}, |
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'DE', |
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'{scenario}' |
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) |
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""" |
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) |
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def insert_capacities_per_federal_state_nep(): |
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"""Inserts installed capacities per federal state accordning to |
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NEP 2035 (version 2021), scenario 2035 C |
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Returns |
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------- |
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None. |
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""" |
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sources = config.datasets()["scenario_input"]["sources"] |
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targets = config.datasets()["scenario_input"]["targets"] |
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# Connect to local database |
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engine = db.engine() |
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# Delete rows if already exist |
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db.execute_sql( |
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f""" |
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DELETE FROM |
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{targets['scenario_capacities']['schema']}. |
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{targets['scenario_capacities']['table']} |
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WHERE scenario_name = 'eGon2035' |
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AND nuts != 'DE' |
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""" |
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) |
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# read-in installed capacities per federal state of germany |
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target_file = ( |
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Path(".") |
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/ "data_bundle_egon_data" |
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/ "nep2035_version2021" |
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/ sources["eGon2035"]["capacities"] |
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) |
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df = pd.read_excel( |
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target_file, |
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sheet_name="1.Entwurf_NEP2035_V2021", |
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index_col="Unnamed: 0", |
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) |
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df_draft = pd.read_excel( |
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target_file, |
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sheet_name="Entwurf_des_Szenariorahmens", |
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index_col="Unnamed: 0", |
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) |
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# Import data on wind offshore capacities |
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df_windoff = pd.read_excel( |
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target_file, |
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sheet_name="WInd_Offshore_NEP", |
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).dropna(subset=["Bundesland", "Netzverknuepfungspunkt"]) |
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# Remove trailing whitespace from column Bundesland |
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df_windoff["Bundesland"] = df_windoff["Bundesland"].str.strip() |
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# Group and sum capacities per federal state |
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df_windoff_fs = ( |
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df_windoff[["Bundesland", "C 2035"]].groupby(["Bundesland"]).sum() |
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) |
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# List federal state with an assigned wind offshore capacity |
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index_list = list(df_windoff_fs.index.values) |
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# Overwrite capacities in df_windoff with more accurate values from |
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# df_windoff_fs |
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for state in index_list: |
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df.at["Wind offshore", state] = ( |
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df_windoff_fs.at[state, "C 2035"] / 1000 |
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) |
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# sort NEP-carriers: |
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rename_carrier = { |
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"Wind onshore": "wind_onshore", |
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"Wind offshore": "wind_offshore", |
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"sonstige Konventionelle": "others", |
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"Speicherwasser": "reservoir", |
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"Laufwasser": "run_of_river", |
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"Biomasse": "biomass", |
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"Erdgas": "gas", |
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"Kuppelgas": "gas", |
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"PV (Aufdach)": "solar_rooftop", |
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"PV (Freiflaeche)": "solar", |
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"Pumpspeicher": "pumped_hydro", |
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"sonstige EE": "others", |
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"Oel": "oil", |
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"Haushaltswaermepumpen": "residential_rural_heat_pump", |
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"KWK < 10 MW": "small_chp", |
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} |
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# 'Elektromobilitaet gesamt': 'transport', |
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# 'Elektromobilitaet privat': 'transport'} |
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# nuts1 to federal state in Germany |
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map_nuts = pd.read_sql( |
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f""" |
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SELECT DISTINCT ON (nuts) gen, nuts |
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FROM {sources['boundaries']['schema']}.{sources['boundaries']['table']} |
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""", |
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engine, |
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index_col="gen", |
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) |
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insert_data = pd.DataFrame() |
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scaled_carriers = [ |
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"Haushaltswaermepumpen", |
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"PV (Aufdach)", |
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"PV (Freiflaeche)", |
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] |
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for bl in map_nuts.index: |
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data = pd.DataFrame(df[bl]) |
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316
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# if distribution to federal states is not provided, |
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# use data from draft of scenario report |
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for c in scaled_carriers: |
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319
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|
|
data.loc[c, bl] = ( |
|
320
|
|
|
df_draft.loc[c, bl] |
|
321
|
|
|
/ df_draft.loc[c, "Summe"] |
|
322
|
|
|
* df.loc[c, "Summe"] |
|
323
|
|
|
) |
|
324
|
|
|
|
|
325
|
|
|
# split hydro into run of river and reservoir |
|
326
|
|
|
# according to draft of scenario report |
|
327
|
|
|
if data.loc["Lauf- und Speicherwasser", bl] > 0: |
|
328
|
|
|
for c in ["Speicherwasser", "Laufwasser"]: |
|
329
|
|
|
data.loc[c, bl] = ( |
|
330
|
|
|
data.loc["Lauf- und Speicherwasser", bl] |
|
331
|
|
|
* df_draft.loc[c, bl] |
|
332
|
|
|
/ df_draft.loc[["Speicherwasser", "Laufwasser"], bl].sum() |
|
333
|
|
|
) |
|
334
|
|
|
|
|
335
|
|
|
data["carrier"] = data.index.map(rename_carrier) |
|
336
|
|
|
data = data.groupby(data.carrier)[bl].sum().reset_index() |
|
337
|
|
|
data["component"] = "generator" |
|
338
|
|
|
data["nuts"] = map_nuts.nuts[bl] |
|
339
|
|
|
data["scenario_name"] = "eGon2035" |
|
340
|
|
|
|
|
341
|
|
|
# According to NEP, each heatpump has 5kW_el installed capacity |
|
342
|
|
|
# source: Entwurf des Szenariorahmens NEP 2035, version 2021, page 47 |
|
343
|
|
|
data.loc[data.carrier == "residential_rural_heat_pump", bl] *= 5e-6 |
|
344
|
|
|
data.loc[ |
|
345
|
|
|
data.carrier == "residential_rural_heat_pump", "component" |
|
346
|
|
|
] = "link" |
|
347
|
|
|
|
|
348
|
|
|
data = data.rename(columns={bl: "capacity"}) |
|
349
|
|
|
|
|
350
|
|
|
# convert GW to MW |
|
351
|
|
|
data.capacity *= 1e3 |
|
352
|
|
|
|
|
353
|
|
|
insert_data = pd.concat([insert_data, data]) |
|
354
|
|
|
|
|
355
|
|
|
# Get aggregated capacities from nep's power plant list for certain carrier |
|
356
|
|
|
|
|
357
|
|
|
carriers = ["oil", "other_non_renewable", "pumped_hydro"] |
|
358
|
|
|
|
|
359
|
|
|
capacities_list = aggr_nep_capacities(carriers) |
|
360
|
|
|
|
|
361
|
|
|
# Filter by carrier |
|
362
|
|
|
updated = insert_data[insert_data["carrier"].isin(carriers)] |
|
363
|
|
|
|
|
364
|
|
|
# Merge to replace capacities for carriers "oil", "other_non_renewable" and |
|
365
|
|
|
# "pumped_hydro" |
|
366
|
|
|
updated = ( |
|
367
|
|
|
updated.merge(capacities_list, on=["carrier", "nuts"], how="left") |
|
368
|
|
|
.fillna(0) |
|
369
|
|
|
.drop(["capacity"], axis=1) |
|
370
|
|
|
.rename(columns={"c2035_capacity": "capacity"}) |
|
371
|
|
|
) |
|
372
|
|
|
|
|
373
|
|
|
# Remove updated entries from df |
|
374
|
|
|
original = insert_data[~insert_data["carrier"].isin(carriers)] |
|
375
|
|
|
|
|
376
|
|
|
# Join dfs |
|
377
|
|
|
insert_data = pd.concat([original, updated]) |
|
378
|
|
|
|
|
379
|
|
|
# Insert data to db |
|
380
|
|
|
insert_data.to_sql( |
|
381
|
|
|
targets["scenario_capacities"]["table"], |
|
382
|
|
|
engine, |
|
383
|
|
|
schema=targets["scenario_capacities"]["schema"], |
|
384
|
|
|
if_exists="append", |
|
385
|
|
|
index=insert_data.index, |
|
386
|
|
|
) |
|
387
|
|
|
|
|
388
|
|
|
# Add district heating data accordning to energy and full load hours |
|
389
|
|
|
district_heating_input() |
|
390
|
|
|
|
|
391
|
|
|
|
|
392
|
|
|
def population_share(): |
|
393
|
|
|
"""Calulate share of population in testmode |
|
394
|
|
|
|
|
395
|
|
|
Returns |
|
396
|
|
|
------- |
|
397
|
|
|
float |
|
398
|
|
|
Share of population in testmode |
|
399
|
|
|
|
|
400
|
|
|
""" |
|
401
|
|
|
|
|
402
|
|
|
sources = config.datasets()["scenario_input"]["sources"] |
|
403
|
|
|
|
|
404
|
|
|
return ( |
|
405
|
|
|
pd.read_sql( |
|
406
|
|
|
f""" |
|
407
|
|
|
SELECT SUM(population) |
|
408
|
|
|
FROM {sources['zensus_population']['schema']}. |
|
409
|
|
|
{sources['zensus_population']['table']} |
|
410
|
|
|
WHERE population>0 |
|
411
|
|
|
""", |
|
412
|
|
|
con=db.engine(), |
|
413
|
|
|
)["sum"][0] |
|
414
|
|
|
/ 80324282 |
|
415
|
|
|
) |
|
416
|
|
|
|
|
417
|
|
|
|
|
418
|
|
|
def aggr_nep_capacities(carriers): |
|
419
|
|
|
"""Aggregates capacities from NEP power plants list by carrier and federal |
|
420
|
|
|
state |
|
421
|
|
|
|
|
422
|
|
|
Returns |
|
423
|
|
|
------- |
|
424
|
|
|
pandas.Dataframe |
|
425
|
|
|
Dataframe with capacities per federal state and carrier |
|
426
|
|
|
|
|
427
|
|
|
""" |
|
428
|
|
|
# Get list of power plants from nep |
|
429
|
|
|
nep_capacities = insert_nep_list_powerplants(export=False)[ |
|
430
|
|
|
["federal_state", "carrier", "c2035_capacity"] |
|
431
|
|
|
] |
|
432
|
|
|
|
|
433
|
|
|
# Sum up capacities per federal state and carrier |
|
434
|
|
|
capacities_list = ( |
|
435
|
|
|
nep_capacities.groupby(["federal_state", "carrier"])["c2035_capacity"] |
|
436
|
|
|
.sum() |
|
437
|
|
|
.to_frame() |
|
438
|
|
|
.reset_index() |
|
439
|
|
|
) |
|
440
|
|
|
|
|
441
|
|
|
# Neglect entries with carriers not in argument |
|
442
|
|
|
capacities_list = capacities_list[capacities_list.carrier.isin(carriers)] |
|
443
|
|
|
|
|
444
|
|
|
# Include NUTS code |
|
445
|
|
|
capacities_list["nuts"] = capacities_list.federal_state.map(nuts_mapping()) |
|
446
|
|
|
|
|
447
|
|
|
# Drop entries for foreign plants with nan values and federal_state column |
|
448
|
|
|
capacities_list = capacities_list.dropna(subset=["nuts"]).drop( |
|
449
|
|
|
columns=["federal_state"] |
|
450
|
|
|
) |
|
451
|
|
|
|
|
452
|
|
|
return capacities_list |
|
453
|
|
|
|
|
454
|
|
|
|
|
455
|
|
|
def map_carrier(): |
|
456
|
|
|
"""Map carriers from NEP and Marktstammdatenregister to carriers from eGon |
|
457
|
|
|
|
|
458
|
|
|
Returns |
|
459
|
|
|
------- |
|
460
|
|
|
pandas.Series |
|
461
|
|
|
List of mapped carriers |
|
462
|
|
|
|
|
463
|
|
|
""" |
|
464
|
|
|
return pd.Series( |
|
465
|
|
|
data={ |
|
466
|
|
|
"Abfall": "others", |
|
467
|
|
|
"Erdgas": "gas", |
|
468
|
|
|
"Sonstige\nEnergieträger": "others", |
|
469
|
|
|
"Steinkohle": "coal", |
|
470
|
|
|
"Kuppelgase": "gas", |
|
471
|
|
|
"Mineralöl-\nprodukte": "oil", |
|
472
|
|
|
"Braunkohle": "lignite", |
|
473
|
|
|
"Waerme": "others", |
|
474
|
|
|
"Mineraloelprodukte": "oil", |
|
475
|
|
|
"Mineralölprodukte": "oil", |
|
476
|
|
|
"NichtBiogenerAbfall": "others", |
|
477
|
|
|
"nicht biogener Abfall": "others", |
|
478
|
|
|
"AndereGase": "gas", |
|
479
|
|
|
"andere Gase": "gas", |
|
480
|
|
|
"Sonstige_Energietraeger": "others", |
|
481
|
|
|
"Kernenergie": "nuclear", |
|
482
|
|
|
"Pumpspeicher": "pumped_hydro", |
|
483
|
|
|
"Mineralöl-\nProdukte": "oil", |
|
484
|
|
|
"Biomasse": "biomass", |
|
485
|
|
|
} |
|
486
|
|
|
) |
|
487
|
|
|
|
|
488
|
|
|
|
|
489
|
|
|
def insert_nep_list_powerplants(export=True): |
|
490
|
|
|
"""Insert list of conventional powerplants attached to the approval |
|
491
|
|
|
of the scenario report by BNetzA |
|
492
|
|
|
|
|
493
|
|
|
Parameters |
|
494
|
|
|
---------- |
|
495
|
|
|
export : bool |
|
496
|
|
|
Choose if nep list should be exported to the data |
|
497
|
|
|
base. The default is True. |
|
498
|
|
|
If export=False a data frame will be returned |
|
499
|
|
|
|
|
500
|
|
|
Returns |
|
501
|
|
|
------- |
|
502
|
|
|
kw_liste_nep : pandas.DataFrame |
|
503
|
|
|
List of conventional power plants from nep if export=False |
|
504
|
|
|
""" |
|
505
|
|
|
|
|
506
|
|
|
sources = config.datasets()["scenario_input"]["sources"] |
|
507
|
|
|
targets = config.datasets()["scenario_input"]["targets"] |
|
508
|
|
|
|
|
509
|
|
|
# Connect to local database |
|
510
|
|
|
engine = db.engine() |
|
511
|
|
|
|
|
512
|
|
|
# Read-in data from csv-file |
|
513
|
|
|
target_file = ( |
|
514
|
|
|
Path(".") |
|
515
|
|
|
/ "data_bundle_egon_data" |
|
516
|
|
|
/ "nep2035_version2021" |
|
517
|
|
|
/ sources["eGon2035"]["list_conv_pp"] |
|
518
|
|
|
) |
|
519
|
|
|
|
|
520
|
|
|
kw_liste_nep = pd.read_csv(target_file, delimiter=";", decimal=",") |
|
521
|
|
|
|
|
522
|
|
|
# Adjust column names |
|
523
|
|
|
kw_liste_nep = kw_liste_nep.rename( |
|
524
|
|
|
columns={ |
|
525
|
|
|
"BNetzA-ID": "bnetza_id", |
|
526
|
|
|
"Kraftwerksname": "name", |
|
527
|
|
|
"Blockname": "name_unit", |
|
528
|
|
|
"Energieträger": "carrier_nep", |
|
529
|
|
|
"KWK\nJa/Nein": "chp", |
|
530
|
|
|
"PLZ": "postcode", |
|
531
|
|
|
"Ort": "city", |
|
532
|
|
|
"Bundesland/\nLand": "federal_state", |
|
533
|
|
|
"Inbetrieb-\nnahmejahr": "commissioned", |
|
534
|
|
|
"Status": "status", |
|
535
|
|
|
"el. Leistung\n06.02.2020": "capacity", |
|
536
|
|
|
"A 2035:\nKWK-Ersatz": "a2035_chp", |
|
537
|
|
|
"A 2035:\nLeistung": "a2035_capacity", |
|
538
|
|
|
"B 2035\nKWK-Ersatz": "b2035_chp", |
|
539
|
|
|
"B 2035:\nLeistung": "b2035_capacity", |
|
540
|
|
|
"C 2035:\nKWK-Ersatz": "c2035_chp", |
|
541
|
|
|
"C 2035:\nLeistung": "c2035_capacity", |
|
542
|
|
|
"B 2040:\nKWK-Ersatz": "b2040_chp", |
|
543
|
|
|
"B 2040:\nLeistung": "b2040_capacity", |
|
544
|
|
|
} |
|
545
|
|
|
) |
|
546
|
|
|
|
|
547
|
|
|
# Cut data to federal state if in testmode |
|
548
|
|
|
boundary = config.settings()["egon-data"]["--dataset-boundary"] |
|
549
|
|
|
if boundary != "Everything": |
|
550
|
|
|
map_states = { |
|
551
|
|
|
"Baden-Württemberg": "BW", |
|
552
|
|
|
"Nordrhein-Westfalen": "NW", |
|
553
|
|
|
"Hessen": "HE", |
|
554
|
|
|
"Brandenburg": "BB", |
|
555
|
|
|
"Bremen": "HB", |
|
556
|
|
|
"Rheinland-Pfalz": "RP", |
|
557
|
|
|
"Sachsen-Anhalt": "ST", |
|
558
|
|
|
"Schleswig-Holstein": "SH", |
|
559
|
|
|
"Mecklenburg-Vorpommern": "MV", |
|
560
|
|
|
"Thüringen": "TH", |
|
561
|
|
|
"Niedersachsen": "NI", |
|
562
|
|
|
"Sachsen": "SN", |
|
563
|
|
|
"Hamburg": "HH", |
|
564
|
|
|
"Saarland": "SL", |
|
565
|
|
|
"Berlin": "BE", |
|
566
|
|
|
"Bayern": "BY", |
|
567
|
|
|
} |
|
568
|
|
|
|
|
569
|
|
|
kw_liste_nep = kw_liste_nep[ |
|
570
|
|
|
kw_liste_nep.federal_state.isin([map_states[boundary], np.nan]) |
|
571
|
|
|
] |
|
572
|
|
|
|
|
573
|
|
|
for col in [ |
|
574
|
|
|
"capacity", |
|
575
|
|
|
"a2035_capacity", |
|
576
|
|
|
"b2035_capacity", |
|
577
|
|
|
"c2035_capacity", |
|
578
|
|
|
"b2040_capacity", |
|
579
|
|
|
]: |
|
580
|
|
|
kw_liste_nep.loc[ |
|
581
|
|
|
kw_liste_nep[kw_liste_nep.federal_state.isnull()].index, col |
|
582
|
|
|
] *= population_share() |
|
583
|
|
|
|
|
584
|
|
|
kw_liste_nep["carrier"] = map_carrier()[kw_liste_nep.carrier_nep].values |
|
585
|
|
|
|
|
586
|
|
|
if export is True: |
|
587
|
|
|
# Insert data to db |
|
588
|
|
|
kw_liste_nep.to_sql( |
|
589
|
|
|
targets["nep_conventional_powerplants"]["table"], |
|
590
|
|
|
engine, |
|
591
|
|
|
schema=targets["nep_conventional_powerplants"]["schema"], |
|
592
|
|
|
if_exists="replace", |
|
593
|
|
|
) |
|
594
|
|
|
else: |
|
595
|
|
|
return kw_liste_nep |
|
596
|
|
|
|
|
597
|
|
|
|
|
598
|
|
|
def district_heating_input(): |
|
599
|
|
|
"""Imports data for district heating networks in Germany |
|
600
|
|
|
|
|
601
|
|
|
Returns |
|
602
|
|
|
------- |
|
603
|
|
|
None. |
|
604
|
|
|
|
|
605
|
|
|
""" |
|
606
|
|
|
|
|
607
|
|
|
sources = config.datasets()["scenario_input"]["sources"] |
|
608
|
|
|
|
|
609
|
|
|
# import data to dataframe |
|
610
|
|
|
file = ( |
|
611
|
|
|
Path(".") |
|
612
|
|
|
/ "data_bundle_egon_data" |
|
613
|
|
|
/ "nep2035_version2021" |
|
614
|
|
|
/ sources["eGon2035"]["capacities"] |
|
615
|
|
|
) |
|
616
|
|
|
df = pd.read_excel( |
|
617
|
|
|
file, sheet_name="Kurzstudie_KWK", dtype={"Wert": float} |
|
618
|
|
|
) |
|
619
|
|
|
df.set_index(["Energietraeger", "Name"], inplace=True) |
|
620
|
|
|
|
|
621
|
|
|
# Scale values to population share in testmode |
|
622
|
|
|
if config.settings()["egon-data"]["--dataset-boundary"] != "Everything": |
|
623
|
|
|
df.loc[ |
|
624
|
|
|
pd.IndexSlice[:, "Fernwaermeerzeugung"], "Wert" |
|
625
|
|
|
] *= population_share() |
|
626
|
|
|
|
|
627
|
|
|
# Connect to database |
|
628
|
|
|
engine = db.engine() |
|
629
|
|
|
session = sessionmaker(bind=engine)() |
|
630
|
|
|
|
|
631
|
|
|
# insert heatpumps and resistive heater as link |
|
632
|
|
|
for c in ["Grosswaermepumpe", "Elektrodenheizkessel"]: |
|
633
|
|
|
entry = EgonScenarioCapacities( |
|
634
|
|
|
component="link", |
|
635
|
|
|
scenario_name="eGon2035", |
|
636
|
|
|
nuts="DE", |
|
637
|
|
|
carrier="urban_central_" |
|
638
|
|
|
+ ("heat_pump" if c == "Grosswaermepumpe" else "resistive_heater"), |
|
639
|
|
|
capacity=df.loc[(c, "Fernwaermeerzeugung"), "Wert"] |
|
640
|
|
|
* 1e6 |
|
641
|
|
|
/ df.loc[(c, "Volllaststunden"), "Wert"] |
|
642
|
|
|
/ df.loc[(c, "Wirkungsgrad"), "Wert"], |
|
643
|
|
|
) |
|
644
|
|
|
|
|
645
|
|
|
session.add(entry) |
|
646
|
|
|
|
|
647
|
|
|
# insert solar- and geothermal as generator |
|
648
|
|
|
for c in ["Geothermie", "Solarthermie"]: |
|
649
|
|
|
entry = EgonScenarioCapacities( |
|
650
|
|
|
component="generator", |
|
651
|
|
|
scenario_name="eGon2035", |
|
652
|
|
|
nuts="DE", |
|
653
|
|
|
carrier="urban_central_" |
|
654
|
|
|
+ ( |
|
655
|
|
|
"solar_thermal_collector" |
|
656
|
|
|
if c == "Solarthermie" |
|
657
|
|
|
else "geo_thermal" |
|
658
|
|
|
), |
|
659
|
|
|
capacity=df.loc[(c, "Fernwaermeerzeugung"), "Wert"] |
|
660
|
|
|
* 1e6 |
|
661
|
|
|
/ df.loc[(c, "Volllaststunden"), "Wert"], |
|
662
|
|
|
) |
|
663
|
|
|
|
|
664
|
|
|
session.add(entry) |
|
665
|
|
|
|
|
666
|
|
|
session.commit() |
|
667
|
|
|
|
|
668
|
|
|
|
|
669
|
|
|
def insert_data_nep(): |
|
670
|
|
|
"""Overall function for importing scenario input data for eGon2035 scenario |
|
671
|
|
|
|
|
672
|
|
|
Returns |
|
673
|
|
|
------- |
|
674
|
|
|
None. |
|
675
|
|
|
|
|
676
|
|
|
""" |
|
677
|
|
|
|
|
678
|
|
|
insert_nep_list_powerplants(export=True) |
|
679
|
|
|
|
|
680
|
|
|
insert_capacities_per_federal_state_nep() |
|
681
|
|
|
|
|
682
|
|
|
|
|
683
|
|
|
def eGon100_capacities(): |
|
684
|
|
|
"""Inserts installed capacities for the eGon100 scenario |
|
685
|
|
|
|
|
686
|
|
|
Returns |
|
687
|
|
|
------- |
|
688
|
|
|
None. |
|
689
|
|
|
|
|
690
|
|
|
""" |
|
691
|
|
|
|
|
692
|
|
|
sources = config.datasets()["scenario_input"]["sources"] |
|
693
|
|
|
targets = config.datasets()["scenario_input"]["targets"] |
|
694
|
|
|
|
|
695
|
|
|
# read-in installed capacities |
|
696
|
|
|
cwd = Path(".") |
|
697
|
|
|
|
|
698
|
|
|
if config.settings()["egon-data"]["--run-pypsa-eur"]: |
|
699
|
|
|
filepath = cwd / "run-pypsa-eur" |
|
700
|
|
|
pypsa_eur_repos = filepath / "pypsa-eur" |
|
701
|
|
|
# Read YAML file |
|
702
|
|
|
pes_egonconfig = pypsa_eur_repos / "config" / "config.yaml" |
|
703
|
|
|
with open(pes_egonconfig, "r") as stream: |
|
704
|
|
|
data_config = yaml.safe_load(stream) |
|
705
|
|
|
|
|
706
|
|
|
target_file = ( |
|
707
|
|
|
pypsa_eur_repos |
|
708
|
|
|
/ "results" |
|
709
|
|
|
/ data_config["run"]["name"] |
|
710
|
|
|
/ "csvs" |
|
711
|
|
|
/ sources["eGon100RE"]["capacities"] |
|
712
|
|
|
) |
|
713
|
|
|
|
|
714
|
|
|
else: |
|
715
|
|
|
target_file = ( |
|
716
|
|
|
cwd |
|
717
|
|
|
/ "data_bundle_egon_data" |
|
718
|
|
|
/ "pypsa_eur" |
|
719
|
|
|
/ "csvs" |
|
720
|
|
|
/ sources["eGon100RE"]["capacities"] |
|
721
|
|
|
) |
|
722
|
|
|
|
|
723
|
|
|
df = pd.read_csv(target_file, delimiter=",", skiprows=3) |
|
724
|
|
|
df.columns = [ |
|
725
|
|
|
"component", |
|
726
|
|
|
"country", |
|
727
|
|
|
"carrier", |
|
728
|
|
|
"p_nom_2025", |
|
729
|
|
|
"p_nom_2030", |
|
730
|
|
|
"p_nom_2035", |
|
731
|
|
|
"p_nom_2045", |
|
732
|
|
|
] |
|
733
|
|
|
|
|
734
|
|
|
df.set_index("carrier", inplace=True) |
|
735
|
|
|
|
|
736
|
|
|
df = df[df.country.str[:2] == "DE"] |
|
737
|
|
|
|
|
738
|
|
|
# Drop country column |
|
739
|
|
|
df.drop("country", axis=1, inplace=True) |
|
740
|
|
|
|
|
741
|
|
|
# Drop copmponents which will be optimized in eGo |
|
742
|
|
|
unused_carrier = [ |
|
743
|
|
|
"BEV charger", |
|
744
|
|
|
"DAC", |
|
745
|
|
|
"H2 Electrolysis", |
|
746
|
|
|
"electricity distribution grid", |
|
747
|
|
|
"home battery charger", |
|
748
|
|
|
"home battery discharger", |
|
749
|
|
|
"H2", |
|
750
|
|
|
"Li ion", |
|
751
|
|
|
"rural water tanks charger", |
|
752
|
|
|
"rural water tanks discharger", |
|
753
|
|
|
"urban decentral water tanks charger", |
|
754
|
|
|
"urban decentral water tanks discharger", |
|
755
|
|
|
"rural water tanks", |
|
756
|
|
|
"urban decentral water tanks", |
|
757
|
|
|
"urban central water tanks", |
|
758
|
|
|
"urban central water tanks charger", |
|
759
|
|
|
"urban central water tanks discharger", |
|
760
|
|
|
"H2 Fuel Cell", |
|
761
|
|
|
"gas", |
|
762
|
|
|
"SMR", |
|
763
|
|
|
"SMR CC", |
|
764
|
|
|
"Sabatier", |
|
765
|
|
|
"biogas to gas", |
|
766
|
|
|
"biogas to gas CC", |
|
767
|
|
|
"gas for industry", |
|
768
|
|
|
"gas for industry CC", |
|
769
|
|
|
"methanolisation", |
|
770
|
|
|
"EV battery", |
|
771
|
|
|
"H2 Store", |
|
772
|
|
|
"battery", |
|
773
|
|
|
"battery charger", |
|
774
|
|
|
"battery discharger", |
|
775
|
|
|
"unsustainable biogas", |
|
776
|
|
|
"biogas", |
|
777
|
|
|
"Fischer-Tropsch", |
|
778
|
|
|
] |
|
779
|
|
|
|
|
780
|
|
|
df = df[~df.index.isin(unused_carrier)] |
|
781
|
|
|
|
|
782
|
|
|
df.index = df.index.str.replace(" ", "_") |
|
783
|
|
|
|
|
784
|
|
|
# Aggregate offshore wind |
|
785
|
|
|
df.loc["wind_offshore"] = df[df.index.str.startswith("offwind")].sum( |
|
786
|
|
|
numeric_only=True |
|
787
|
|
|
) |
|
788
|
|
|
df.loc["wind_offshore", "component"] = "generators" |
|
789
|
|
|
df = df.drop(df.index[df.index.str.startswith("offwind")]) |
|
790
|
|
|
|
|
791
|
|
|
# Aggregate OCGT and CCGT |
|
792
|
|
|
df.loc["OCGT", df.columns != "component"] = ( |
|
793
|
|
|
df.loc["OCGT", df.columns != "component"] * 0.425 |
|
794
|
|
|
) |
|
795
|
|
|
df.loc["CCGT", df.columns != "component"] = ( |
|
796
|
|
|
df.loc["CCGT", df.columns != "component"] * 0.570 |
|
797
|
|
|
) |
|
798
|
|
|
df.loc["gas"] = df[df.index.str.endswith("CGT")].sum(numeric_only=True) |
|
799
|
|
|
df.loc["gas", "component"] = "links" |
|
800
|
|
|
df = df.drop(df.index[df.index.str.endswith("CGT")]) |
|
801
|
|
|
|
|
802
|
|
|
# Aggregate hydro and pumped_hydro |
|
803
|
|
|
df.loc["pumped_hydro"] = df.loc["PHS"] + df.loc["hydro"] |
|
804
|
|
|
df.loc["pumped_hydro", "component"] = "storage_units" |
|
805
|
|
|
df = df.drop(["PHS", "hydro"]) |
|
806
|
|
|
|
|
807
|
|
|
# Aggregate solar and solar-hsat |
|
808
|
|
|
df.loc["solar"] = df.loc["solar"] + df.loc["solar-hsat"] |
|
809
|
|
|
df.loc["solar", "component"] = "generators" |
|
810
|
|
|
df = df.drop(["solar-hsat"]) |
|
811
|
|
|
|
|
812
|
|
|
# Aggregate technologies with and without carbon_capture (CC) |
|
813
|
|
|
for carrier in [ |
|
814
|
|
|
"urban_central_gas_CHP", |
|
815
|
|
|
"urban_central_solid_biomass_CHP", |
|
816
|
|
|
]: |
|
817
|
|
|
df.loc[ |
|
818
|
|
|
carrier, ["p_nom_2025", "p_nom_2030", "p_nom_2035", "p_nom_2045"] |
|
819
|
|
|
] += df.loc[ |
|
820
|
|
|
f"{carrier}_CC", |
|
821
|
|
|
["p_nom_2025", "p_nom_2030", "p_nom_2035", "p_nom_2045"], |
|
822
|
|
|
] |
|
823
|
|
|
df = df.drop([f"{carrier}_CC"]) |
|
824
|
|
|
|
|
825
|
|
|
# Aggregate urban decentral and rural heat supply |
|
826
|
|
|
for merge_carrier in df.index[df.index.str.startswith("urban_decentral")]: |
|
827
|
|
|
|
|
828
|
|
|
# Add capacity of urban decentral to coresponding rural technology |
|
829
|
|
|
df.loc[merge_carrier.replace("urban_decentral", "rural")] += df.loc[ |
|
830
|
|
|
merge_carrier |
|
831
|
|
|
] |
|
832
|
|
|
|
|
833
|
|
|
# Avoid summing up of component names |
|
834
|
|
|
df.loc[ |
|
835
|
|
|
merge_carrier.replace("urban_decentral", "rural"), "component" |
|
836
|
|
|
] = df.loc[merge_carrier, "component"] |
|
837
|
|
|
|
|
838
|
|
|
# Drop urban decentral technology |
|
839
|
|
|
df = df.drop(merge_carrier) |
|
840
|
|
|
|
|
841
|
|
|
# Aggregate rural air and rural ground heat pump |
|
842
|
|
|
df.loc["rural_heat_pump"] = ( |
|
843
|
|
|
df.loc["rural_air_heat_pump"] + df.loc["rural_ground_heat_pump"] |
|
844
|
|
|
) |
|
845
|
|
|
df.loc["rural_heat_pump", "component"] = "links" |
|
846
|
|
|
df = df.drop(["rural_air_heat_pump", "rural_ground_heat_pump"]) |
|
847
|
|
|
|
|
848
|
|
|
# Rename carriers |
|
849
|
|
|
df.rename( |
|
850
|
|
|
{ |
|
851
|
|
|
"onwind": "wind_onshore", |
|
852
|
|
|
"ror": "run_of_river", |
|
853
|
|
|
"urban_central_air_heat_pump": "urban_central_heat_pump", |
|
854
|
|
|
"urban_central_solar_thermal": ( |
|
855
|
|
|
"urban_central_solar_thermal_collector" |
|
856
|
|
|
), |
|
857
|
|
|
"home_battery": "battery", |
|
858
|
|
|
}, |
|
859
|
|
|
inplace=True, |
|
860
|
|
|
) |
|
861
|
|
|
|
|
862
|
|
|
# Reset index |
|
863
|
|
|
df = df.reset_index() |
|
864
|
|
|
|
|
865
|
|
|
# Insert target capacities for all years |
|
866
|
|
|
for year in ["2025", "2030", "2035", "2045"]: |
|
867
|
|
|
df_year = df.rename( |
|
868
|
|
|
{f"p_nom_{year}": "capacity", "index": "carrier"}, axis="columns" |
|
869
|
|
|
) |
|
870
|
|
|
df_year.drop( |
|
871
|
|
|
df_year.columns[ |
|
872
|
|
|
~df_year.columns.isin(["carrier", "component", "capacity"]) |
|
873
|
|
|
], |
|
874
|
|
|
axis="columns", |
|
875
|
|
|
inplace=True, |
|
876
|
|
|
) |
|
877
|
|
|
|
|
878
|
|
|
if year == "2045": |
|
879
|
|
|
df_year["scenario_name"] = "eGon100RE" |
|
880
|
|
|
else: |
|
881
|
|
|
df_year["scenario_name"] = f"powerd{year}" |
|
882
|
|
|
|
|
883
|
|
|
df_year["nuts"] = "DE" |
|
884
|
|
|
|
|
885
|
|
|
db.execute_sql( |
|
886
|
|
|
f""" |
|
887
|
|
|
DELETE FROM |
|
888
|
|
|
{targets['scenario_capacities']['schema']}.{targets['scenario_capacities']['table']} |
|
889
|
|
|
WHERE scenario_name='{df_year["scenario_name"].unique()[0]}' |
|
890
|
|
|
""" |
|
891
|
|
|
) |
|
892
|
|
|
|
|
893
|
|
|
df_year.to_sql( |
|
894
|
|
|
targets["scenario_capacities"]["table"], |
|
895
|
|
|
schema=targets["scenario_capacities"]["schema"], |
|
896
|
|
|
con=db.engine(), |
|
897
|
|
|
if_exists="append", |
|
898
|
|
|
index=False, |
|
899
|
|
|
) |
|
900
|
|
|
|
|
901
|
|
|
|
|
902
|
|
|
def add_metadata(): |
|
903
|
|
|
"""Add metdata to supply.egon_scenario_capacities |
|
904
|
|
|
|
|
905
|
|
|
Returns |
|
906
|
|
|
------- |
|
907
|
|
|
None. |
|
908
|
|
|
|
|
909
|
|
|
""" |
|
910
|
|
|
|
|
911
|
|
|
# Import column names and datatypes |
|
912
|
|
|
fields = pd.DataFrame( |
|
913
|
|
|
generate_resource_fields_from_sqla_model(EgonScenarioCapacities) |
|
914
|
|
|
).set_index("name") |
|
915
|
|
|
|
|
916
|
|
|
# Set descriptions and units |
|
917
|
|
|
fields.loc["index", "description"] = "Index" |
|
918
|
|
|
fields.loc["component", "description"] = ( |
|
919
|
|
|
"Name of representative PyPSA component" |
|
920
|
|
|
) |
|
921
|
|
|
fields.loc["carrier", "description"] = "Name of carrier" |
|
922
|
|
|
fields.loc["capacity", "description"] = "Installed capacity" |
|
923
|
|
|
fields.loc["capacity", "unit"] = "MW" |
|
924
|
|
|
fields.loc["nuts", "description"] = ( |
|
925
|
|
|
"NUTS region, either federal state or Germany" |
|
926
|
|
|
) |
|
927
|
|
|
fields.loc["scenario_name", "description"] = ( |
|
928
|
|
|
"Name of corresponding eGon scenario" |
|
929
|
|
|
) |
|
930
|
|
|
|
|
931
|
|
|
# Reformat pandas.DataFrame to dict |
|
932
|
|
|
fields = fields.reset_index().to_dict(orient="records") |
|
933
|
|
|
|
|
934
|
|
|
meta = { |
|
935
|
|
|
"name": "supply.egon_scenario_capacities", |
|
936
|
|
|
"title": "eGon scenario capacities", |
|
937
|
|
|
"id": "WILL_BE_SET_AT_PUBLICATION", |
|
938
|
|
|
"description": ( |
|
939
|
|
|
"Installed capacities of scenarios used in the eGon project" |
|
940
|
|
|
), |
|
941
|
|
|
"language": ["de-DE"], |
|
942
|
|
|
"publicationDate": datetime.date.today().isoformat(), |
|
943
|
|
|
"context": context(), |
|
944
|
|
|
"spatial": { |
|
945
|
|
|
"location": None, |
|
946
|
|
|
"extent": "Germany", |
|
947
|
|
|
"resolution": None, |
|
948
|
|
|
}, |
|
949
|
|
|
"sources": [ |
|
950
|
|
|
sources()["nep2021"], |
|
951
|
|
|
sources()["vg250"], |
|
952
|
|
|
sources()["zensus"], |
|
953
|
|
|
sources()["egon-data"], |
|
954
|
|
|
], |
|
955
|
|
|
"licenses": [ |
|
956
|
|
|
license_ccby( |
|
957
|
|
|
"© Übertragungsnetzbetreiber; " |
|
958
|
|
|
"© Bundesamt für Kartographie und Geodäsie 2020 (Daten verändert); " |
|
959
|
|
|
"© Statistische Ämter des Bundes und der Länder 2014; " |
|
960
|
|
|
"© Jonathan Amme, Clara Büttner, Ilka Cußmann, Julian Endres, Carlos Epia, Stephan Günther, Ulf Müller, Amélia Nadal, Guido Pleßmann, Francesco Witte", |
|
961
|
|
|
) |
|
962
|
|
|
], |
|
963
|
|
|
"contributors": [ |
|
964
|
|
|
{ |
|
965
|
|
|
"title": "Clara Büttner", |
|
966
|
|
|
"email": "http://github.com/ClaraBuettner", |
|
967
|
|
|
"date": time.strftime("%Y-%m-%d"), |
|
968
|
|
|
"object": None, |
|
969
|
|
|
"comment": "Imported data", |
|
970
|
|
|
}, |
|
971
|
|
|
], |
|
972
|
|
|
"resources": [ |
|
973
|
|
|
{ |
|
974
|
|
|
"profile": "tabular-data-resource", |
|
975
|
|
|
"name": "supply.egon_scenario_capacities", |
|
976
|
|
|
"path": None, |
|
977
|
|
|
"format": "PostgreSQL", |
|
978
|
|
|
"encoding": "UTF-8", |
|
979
|
|
|
"schema": { |
|
980
|
|
|
"fields": fields, |
|
981
|
|
|
"primaryKey": ["index"], |
|
982
|
|
|
"foreignKeys": [], |
|
983
|
|
|
}, |
|
984
|
|
|
"dialect": {"delimiter": None, "decimalSeparator": "."}, |
|
985
|
|
|
} |
|
986
|
|
|
], |
|
987
|
|
|
"metaMetadata": meta_metadata(), |
|
988
|
|
|
} |
|
989
|
|
|
|
|
990
|
|
|
# Create json dump |
|
991
|
|
|
meta_json = "'" + json.dumps(meta) + "'" |
|
992
|
|
|
|
|
993
|
|
|
# Add metadata as a comment to the table |
|
994
|
|
|
db.submit_comment( |
|
995
|
|
|
meta_json, |
|
996
|
|
|
EgonScenarioCapacities.__table__.schema, |
|
997
|
|
|
EgonScenarioCapacities.__table__.name, |
|
998
|
|
|
) |
|
999
|
|
|
|
|
1000
|
|
|
|
|
1001
|
|
|
tasks = (create_table,) |
|
1002
|
|
|
|
|
1003
|
|
|
scenarios = config.settings()["egon-data"]["--scenarios"] |
|
1004
|
|
|
|
|
1005
|
|
|
status_quo = False |
|
1006
|
|
|
|
|
1007
|
|
|
for scenario in scenarios: |
|
1008
|
|
|
if "status" in scenario: |
|
1009
|
|
|
tasks += ( |
|
1010
|
|
|
wrapped_partial( |
|
1011
|
|
|
insert_capacities_status_quo, |
|
1012
|
|
|
scenario=scenario, |
|
1013
|
|
|
postfix=f"_{scenario[-2:]}", |
|
1014
|
|
|
), |
|
1015
|
|
|
) |
|
1016
|
|
|
status_quo = True |
|
1017
|
|
|
|
|
1018
|
|
|
if status_quo or ("eGon2035" in scenarios): |
|
1019
|
|
|
tasks += (insert_data_nep,) |
|
1020
|
|
|
|
|
1021
|
|
|
if "eGon100RE" in scenarios: |
|
1022
|
|
|
tasks += (eGon100_capacities,) |
|
1023
|
|
|
|
|
1024
|
|
|
tasks += (add_metadata,) |
|
1025
|
|
|
|
|
1026
|
|
|
|
|
1027
|
|
|
class ScenarioCapacities(Dataset): |
|
1028
|
|
|
""" |
|
1029
|
|
|
Create and fill table with installed generation capacities in Germany |
|
1030
|
|
|
|
|
1031
|
|
|
This dataset creates and fills a table with the installed generation capacities in |
|
1032
|
|
|
Germany in a lower spatial resolution (either per federal state or on national level). |
|
1033
|
|
|
This data is coming from external sources (e.g. German grid developement plan for scenario eGon2035). |
|
1034
|
|
|
The table is in downstream datasets used to define target values for the installed capacities. |
|
1035
|
|
|
|
|
1036
|
|
|
|
|
1037
|
|
|
*Dependencies* |
|
1038
|
|
|
* :py:func:`Setup <egon.data.datasets.database.setup>` |
|
1039
|
|
|
* :py:class:`PypsaEurSec <egon.data.datasets.pypsaeursec.PypsaEurSec>` |
|
1040
|
|
|
* :py:class:`Vg250 <egon.data.datasets.vg250.Vg250>` |
|
1041
|
|
|
* :py:class:`DataBundle <egon.data.datasets.data_bundle.DataBundle>` |
|
1042
|
|
|
* :py:class:`ZensusPopulation <egon.data.datasets.zensus.ZensusPopulation>` |
|
1043
|
|
|
|
|
1044
|
|
|
|
|
1045
|
|
|
*Resulting tables* |
|
1046
|
|
|
* :py:class:`supply.egon_scenario_capacities <egon.data.datasets.scenario_capacities.EgonScenarioCapacities>` is created and filled |
|
1047
|
|
|
* :py:class:`supply.egon_nep_2021_conventional_powerplants <egon.data.datasets.scenario_capacities.NEP2021ConvPowerPlants>` is created and filled |
|
1048
|
|
|
|
|
1049
|
|
|
""" |
|
1050
|
|
|
|
|
1051
|
|
|
#: |
|
1052
|
|
|
name: str = "ScenarioCapacities" |
|
1053
|
|
|
#: |
|
1054
|
|
|
version: str = "0.0.19" |
|
1055
|
|
|
|
|
1056
|
|
|
def __init__(self, dependencies): |
|
1057
|
|
|
super().__init__( |
|
1058
|
|
|
name=self.name, |
|
1059
|
|
|
version=self.version, |
|
1060
|
|
|
dependencies=dependencies, |
|
1061
|
|
|
tasks=tasks, |
|
1062
|
|
|
validation={ |
|
1063
|
|
|
"data-quality": [ |
|
1064
|
|
|
RowCountValidation( |
|
1065
|
|
|
table="supply.egon_nep_2021_conventional_powerplants", |
|
1066
|
|
|
rule_id="TEST_ROW_COUNT.egon_nep_2021_conventional_powerplants", |
|
1067
|
|
|
expected_count={"Schleswig-Holstein": 40, "Everything": 737} |
|
1068
|
|
|
), |
|
1069
|
|
|
DataTypeValidation( |
|
1070
|
|
|
table="supply.egon_nep_2021_conventional_powerplants", |
|
1071
|
|
|
rule_id="TEST_DATA_MULTIPLE_TYPES.egon_nep_2021_conventional_powerplants", |
|
1072
|
|
|
column_types={ |
|
1073
|
|
|
"index": "bigint", |
|
1074
|
|
|
"bnetza_id": "text", |
|
1075
|
|
|
"name": "text", |
|
1076
|
|
|
"name_unit": "text", |
|
1077
|
|
|
"carrier_nep": "text", |
|
1078
|
|
|
"chp": "text", |
|
1079
|
|
|
"postcode": "text", |
|
1080
|
|
|
"city": "text", |
|
1081
|
|
|
"federal_state": "text", |
|
1082
|
|
|
"commissioned": "double precision", |
|
1083
|
|
|
"status": "text", |
|
1084
|
|
|
"capacity": "double precision", |
|
1085
|
|
|
"a2035_chp": "text", |
|
1086
|
|
|
"a2035_capacity": "double precision", |
|
1087
|
|
|
"b2035_chp": "text", |
|
1088
|
|
|
"b2035_capacity": "double precision", |
|
1089
|
|
|
"c2035_chp": "text", |
|
1090
|
|
|
"c2035_capacity": "double precision", |
|
1091
|
|
|
"b2040_chp": "text", |
|
1092
|
|
|
"b2040_capacity": "double precision", |
|
1093
|
|
|
"carrier": "text" |
|
1094
|
|
|
} |
|
1095
|
|
|
), |
|
1096
|
|
|
NotNullAndNotNaNValidation( |
|
1097
|
|
|
table="supply.egon_nep_2021_conventional_powerplants", |
|
1098
|
|
|
rule_id="TEST_NOT_NAN.egon_nep_2021_conventional_powerplants", |
|
1099
|
|
|
columns=[ |
|
1100
|
|
|
"index", |
|
1101
|
|
|
"bnetza_id", |
|
1102
|
|
|
"name", |
|
1103
|
|
|
"name_unit", |
|
1104
|
|
|
"carrier_nep", |
|
1105
|
|
|
"chp", |
|
1106
|
|
|
"postcode", |
|
1107
|
|
|
"city", |
|
1108
|
|
|
"federal_state", |
|
1109
|
|
|
"commissioned", |
|
1110
|
|
|
"status", |
|
1111
|
|
|
"capacity", |
|
1112
|
|
|
"a2035_chp", |
|
1113
|
|
|
"a2035_capacity", |
|
1114
|
|
|
"b2035_chp", |
|
1115
|
|
|
"b2035_capacity", |
|
1116
|
|
|
"c2035_chp", |
|
1117
|
|
|
"c2035_capacity", |
|
1118
|
|
|
"b2040_chp", |
|
1119
|
|
|
"b2040_capacity", |
|
1120
|
|
|
"carrier" |
|
1121
|
|
|
] |
|
1122
|
|
|
), |
|
1123
|
|
|
WholeTableNotNullAndNotNaNValidation( |
|
1124
|
|
|
table="supply.egon_nep_2021_conventional_powerplants", |
|
1125
|
|
|
rule_id="TEST_WHOLE_TABLE_NOT_NAN.egon_nep_2021_conventional_powerplants" |
|
1126
|
|
|
), |
|
1127
|
|
|
RowCountValidation( |
|
1128
|
|
|
table="supply.egon_scenario_capacities", |
|
1129
|
|
|
rule_id="TEST_ROW_COUNT.egon_scenario_capacities", |
|
1130
|
|
|
expected_count={"Schleswig-Holstein": 17, "Everything": 236} |
|
1131
|
|
|
), |
|
1132
|
|
|
DataTypeValidation( |
|
1133
|
|
|
table="supply.egon_scenario_capacities", |
|
1134
|
|
|
rule_id="TEST_DATA_MULTIPLE_TYPES.egon_scenario_capacities", |
|
1135
|
|
|
column_types={ |
|
1136
|
|
|
"index": "integer", |
|
1137
|
|
|
"component": "character varying", |
|
1138
|
|
|
"carrier": "character varying", |
|
1139
|
|
|
"capacity": "double precision", |
|
1140
|
|
|
"nuts": "character varying", |
|
1141
|
|
|
"scenario_name": "character varying" |
|
1142
|
|
|
} |
|
1143
|
|
|
), |
|
1144
|
|
|
NotNullAndNotNaNValidation( |
|
1145
|
|
|
table="supply.egon_scenario_capacities", |
|
1146
|
|
|
rule_id="TEST_NOT_NAN.egon_scenario_capacities", |
|
1147
|
|
|
columns=[ |
|
1148
|
|
|
"index", |
|
1149
|
|
|
"component", |
|
1150
|
|
|
"carrier", |
|
1151
|
|
|
"capacity", |
|
1152
|
|
|
"nuts", |
|
1153
|
|
|
"scenario_name" |
|
1154
|
|
|
] |
|
1155
|
|
|
), |
|
1156
|
|
|
WholeTableNotNullAndNotNaNValidation( |
|
1157
|
|
|
table="supply.egon_scenario_capacities", |
|
1158
|
|
|
rule_id="TEST_WHOLE_TABLE_NOT_NAN.egon_scenario_capacities" |
|
1159
|
|
|
), |
|
1160
|
|
|
ValueSetValidation( |
|
1161
|
|
|
table="supply.egon_scenario_capacities", |
|
1162
|
|
|
rule_id="VALUE_SET_VALIDATION_CARRIER.egon_scenario_capacities", |
|
1163
|
|
|
column="carrier", |
|
1164
|
|
|
expected_values=["pumped_hydro", |
|
1165
|
|
|
"gas_for_industry", |
|
1166
|
|
|
"gas_for_industry_CC", |
|
1167
|
|
|
"biogas_to_gas", |
|
1168
|
|
|
"Sabatier", |
|
1169
|
|
|
"urban_central_gas_CHP", |
|
1170
|
|
|
"solar", |
|
1171
|
|
|
"reservoir", |
|
1172
|
|
|
"biogas", |
|
1173
|
|
|
"residential_rural_heat_pump", |
|
1174
|
|
|
"urban_central_solar_thermal_collector", |
|
1175
|
|
|
"oil", |
|
1176
|
|
|
"urban_central_resistive_heater", |
|
1177
|
|
|
"wind_offshore", |
|
1178
|
|
|
"battery", |
|
1179
|
|
|
"others", |
|
1180
|
|
|
"gas", |
|
1181
|
|
|
"wind_onshore", |
|
1182
|
|
|
"small_chp", |
|
1183
|
|
|
"Li_ion", |
|
1184
|
|
|
"urban_central_heat_pump", |
|
1185
|
|
|
"urban_central_geo_thermal", |
|
1186
|
|
|
"SMR", |
|
1187
|
|
|
"biomass", |
|
1188
|
|
|
"hydro", |
|
1189
|
|
|
"run_of_river", |
|
1190
|
|
|
"rural_solar_thermal", |
|
1191
|
|
|
"solar_rooftop", |
|
1192
|
|
|
"BEV_charger"] |
|
1193
|
|
|
), |
|
1194
|
|
|
ValueSetValidation( |
|
1195
|
|
|
table="supply.egon_scenario_capacities", |
|
1196
|
|
|
rule_id="VALUE_SET_VALIDATION_SCENARIO_NAME.egon_scenario_capacities", |
|
1197
|
|
|
column="scenario_name", |
|
1198
|
|
|
expected_values=["eGon2035", "eGon100RE"] |
|
1199
|
|
|
), |
|
1200
|
|
|
|
|
1201
|
|
|
] |
|
1202
|
|
|
}, |
|
1203
|
|
|
on_validation_failure="continue" |
|
1204
|
|
|
) |
|
1205
|
|
|
|
openego /
eGon-data
