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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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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 db |
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from egon.data.config import settings |
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from egon.data.datasets import Dataset |
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import egon.data.config |
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### will be later imported from another file ### |
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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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class ScenarioCapacities(Dataset): |
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def __init__(self, dependencies): |
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super().__init__( |
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name="ScenarioCapacities", |
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version="0.0.11", |
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dependencies=dependencies, |
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tasks=(create_table, insert_data_nep, eGon100_capacities), |
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) |
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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_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 = egon.data.config.datasets()["scenario_input"]["sources"] |
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targets = egon.data.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']}.{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 = df_windoff[['Bundesland', 'C 2035']].groupby(['Bundesland']).sum() |
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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 df_windoff_fs |
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for state in index_list: |
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df.at['Wind offshore', state] = df_windoff_fs.at[state, 'C 2035']/1000 |
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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": "other_non_renewable", |
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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": "other_renewable", |
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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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# 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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data.loc[c, bl] = ( |
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df_draft.loc[c, bl] |
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/ df_draft.loc[c, "Summe"] |
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* df.loc[c, "Summe"] |
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) |
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# split hydro into run of river and reservoir |
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# according to draft of scenario report |
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if data.loc["Lauf- und Speicherwasser", bl] > 0: |
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for c in ["Speicherwasser", "Laufwasser"]: |
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data.loc[c, bl] = ( |
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data.loc["Lauf- und Speicherwasser", bl] |
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* df_draft.loc[c, bl] |
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/ df_draft.loc[["Speicherwasser", "Laufwasser"], bl].sum() |
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) |
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data["carrier"] = data.index.map(rename_carrier) |
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data = data.groupby(data.carrier)[bl].sum().reset_index() |
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data["component"] = "generator" |
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data["nuts"] = map_nuts.nuts[bl] |
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data["scenario_name"] = "eGon2035" |
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# According to NEP, each heatpump has 3kW_el installed capacity |
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data.loc[data.carrier == "residential_rural_heat_pump", bl] *= 3e-6 |
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data.loc[ |
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data.carrier == "residential_rural_heat_pump", "component" |
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] = "link" |
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data = data.rename(columns={bl: "capacity"}) |
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# convert GW to MW |
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data.capacity *= 1e3 |
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insert_data = insert_data.append(data) |
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# Get aggregated capacities from nep's power plant list for certain carrier |
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carriers = ["oil", "other_non_renewable", "pumped_hydro"] |
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capacities_list = aggr_nep_capacities(carriers) |
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# Filter by carrier |
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updated = insert_data[insert_data["carrier"].isin(carriers)] |
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# Merge to replace capacities for carriers "oil", "other_non_renewable" and "pumped_hydro" |
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updated = ( |
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updated.merge(capacities_list, on=["carrier", "nuts"], how="left") |
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.fillna(0) |
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.drop(["capacity"], axis=1) |
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.rename(columns={"c2035_capacity": "capacity"}) |
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) |
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# Remove updated entries from df |
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original = insert_data[~insert_data["carrier"].isin(carriers)] |
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# Join dfs |
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insert_data = pd.concat([original, updated]) |
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# Insert data to db |
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insert_data.to_sql( |
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targets["scenario_capacities"]["table"], |
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engine, |
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schema=targets["scenario_capacities"]["schema"], |
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if_exists="append", |
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index=insert_data.index, |
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) |
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292
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# Add district heating data accordning to energy and full load hours |
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district_heating_input() |
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295
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296
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def population_share(): |
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297
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"""Calulate share of population in testmode |
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298
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299
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Returns |
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300
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------- |
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301
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float |
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302
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Share of population in testmode |
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303
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304
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""" |
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305
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306
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sources = egon.data.config.datasets()["scenario_input"]["sources"] |
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308
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return ( |
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309
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pd.read_sql( |
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f""" |
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311
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SELECT SUM(population) |
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312
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FROM {sources['zensus_population']['schema']}.{sources['zensus_population']['table']} |
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WHERE population>0 |
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314
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""", |
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con=db.engine(), |
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)["sum"][0] |
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/ 80324282 |
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) |
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320
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|
|
321
|
|
|
def aggr_nep_capacities(carriers): |
|
322
|
|
|
"""Aggregates capacities from NEP power plants list by carrier and federal |
|
323
|
|
|
state |
|
324
|
|
|
|
|
325
|
|
|
Returns |
|
326
|
|
|
------- |
|
327
|
|
|
pandas.Dataframe |
|
328
|
|
|
Dataframe with capacities per federal state and carrier |
|
329
|
|
|
|
|
330
|
|
|
""" |
|
331
|
|
|
# Get list of power plants from nep |
|
332
|
|
|
nep_capacities = insert_nep_list_powerplants(export=False)[ |
|
333
|
|
|
["federal_state", "carrier", "c2035_capacity"] |
|
334
|
|
|
] |
|
335
|
|
|
|
|
336
|
|
|
# Sum up capacities per federal state and carrier |
|
337
|
|
|
capacities_list = ( |
|
338
|
|
|
nep_capacities.groupby(["federal_state", "carrier"])["c2035_capacity"] |
|
339
|
|
|
.sum() |
|
340
|
|
|
.to_frame() |
|
341
|
|
|
.reset_index() |
|
342
|
|
|
) |
|
343
|
|
|
|
|
344
|
|
|
# Neglect entries with carriers not in argument |
|
345
|
|
|
capacities_list = capacities_list[capacities_list.carrier.isin(carriers)] |
|
346
|
|
|
|
|
347
|
|
|
# Include NUTS code |
|
348
|
|
|
capacities_list["nuts"] = capacities_list.federal_state.map(nuts_mapping()) |
|
349
|
|
|
|
|
350
|
|
|
# Drop entries for foreign plants with nan values and federal_state column |
|
351
|
|
|
capacities_list = capacities_list.dropna(subset=["nuts"]).drop( |
|
352
|
|
|
columns=["federal_state"] |
|
353
|
|
|
) |
|
354
|
|
|
|
|
355
|
|
|
return capacities_list |
|
356
|
|
|
|
|
357
|
|
|
|
|
358
|
|
|
def map_carrier(): |
|
359
|
|
|
"""Map carriers from NEP and Marktstammdatenregister to carriers from eGon |
|
360
|
|
|
|
|
361
|
|
|
Returns |
|
362
|
|
|
------- |
|
363
|
|
|
pandas.Series |
|
364
|
|
|
List of mapped carriers |
|
365
|
|
|
|
|
366
|
|
|
""" |
|
367
|
|
|
return pd.Series( |
|
368
|
|
|
data={ |
|
369
|
|
|
"Abfall": "other_non_renewable", |
|
370
|
|
|
"Erdgas": "gas", |
|
371
|
|
|
"Sonstige\nEnergieträger": "other_non_renewable", |
|
372
|
|
|
"Steinkohle": "coal", |
|
373
|
|
|
"Kuppelgase": "gas", |
|
374
|
|
|
"Mineralöl-\nprodukte": "oil", |
|
375
|
|
|
"Braunkohle": "lignite", |
|
376
|
|
|
"Waerme": "other_non_renewable", |
|
377
|
|
|
"Mineraloelprodukte": "oil", |
|
378
|
|
|
"NichtBiogenerAbfall": "other_non_renewable", |
|
379
|
|
|
"AndereGase": "gas", |
|
380
|
|
|
"Sonstige_Energietraeger": "other_non_renewable", |
|
381
|
|
|
"Kernenergie": "nuclear", |
|
382
|
|
|
"Pumpspeicher": "pumped_hydro", |
|
383
|
|
|
"Mineralöl-\nProdukte": "oil", |
|
384
|
|
|
} |
|
385
|
|
|
) |
|
386
|
|
|
|
|
387
|
|
|
|
|
388
|
|
|
def insert_nep_list_powerplants(export=True): |
|
389
|
|
|
"""Insert list of conventional powerplants attached to the approval |
|
390
|
|
|
of the scenario report by BNetzA |
|
391
|
|
|
|
|
392
|
|
|
Parameters |
|
393
|
|
|
---------- |
|
394
|
|
|
export : bool |
|
395
|
|
|
Choose if nep list should be exported to the data |
|
396
|
|
|
base. The default is True. |
|
397
|
|
|
If export=False a data frame will be returned |
|
398
|
|
|
|
|
399
|
|
|
Returns |
|
400
|
|
|
------- |
|
401
|
|
|
kw_liste_nep : pandas.DataFrame |
|
402
|
|
|
List of conventional power plants from nep if export=False |
|
403
|
|
|
""" |
|
404
|
|
|
|
|
405
|
|
|
sources = egon.data.config.datasets()["scenario_input"]["sources"] |
|
406
|
|
|
targets = egon.data.config.datasets()["scenario_input"]["targets"] |
|
407
|
|
|
|
|
408
|
|
|
# Connect to local database |
|
409
|
|
|
engine = db.engine() |
|
410
|
|
|
|
|
411
|
|
|
# Read-in data from csv-file |
|
412
|
|
|
target_file = ( |
|
413
|
|
|
Path(".") |
|
414
|
|
|
/ "data_bundle_egon_data" |
|
415
|
|
|
/ "nep2035_version2021" |
|
416
|
|
|
/ sources["eGon2035"]["list_conv_pp"] |
|
417
|
|
|
) |
|
418
|
|
|
|
|
419
|
|
|
kw_liste_nep = pd.read_csv(target_file, delimiter=";", decimal=",") |
|
420
|
|
|
|
|
421
|
|
|
# Adjust column names |
|
422
|
|
|
kw_liste_nep = kw_liste_nep.rename( |
|
423
|
|
|
columns={ |
|
424
|
|
|
"BNetzA-ID": "bnetza_id", |
|
425
|
|
|
"Kraftwerksname": "name", |
|
426
|
|
|
"Blockname": "name_unit", |
|
427
|
|
|
"Energieträger": "carrier_nep", |
|
428
|
|
|
"KWK\nJa/Nein": "chp", |
|
429
|
|
|
"PLZ": "postcode", |
|
430
|
|
|
"Ort": "city", |
|
431
|
|
|
"Bundesland/\nLand": "federal_state", |
|
432
|
|
|
"Inbetrieb-\nnahmejahr": "commissioned", |
|
433
|
|
|
"Status": "status", |
|
434
|
|
|
"el. Leistung\n06.02.2020": "capacity", |
|
435
|
|
|
"A 2035:\nKWK-Ersatz": "a2035_chp", |
|
436
|
|
|
"A 2035:\nLeistung": "a2035_capacity", |
|
437
|
|
|
"B 2035\nKWK-Ersatz": "b2035_chp", |
|
438
|
|
|
"B 2035:\nLeistung": "b2035_capacity", |
|
439
|
|
|
"C 2035:\nKWK-Ersatz": "c2035_chp", |
|
440
|
|
|
"C 2035:\nLeistung": "c2035_capacity", |
|
441
|
|
|
"B 2040:\nKWK-Ersatz": "b2040_chp", |
|
442
|
|
|
"B 2040:\nLeistung": "b2040_capacity", |
|
443
|
|
|
} |
|
444
|
|
|
) |
|
445
|
|
|
|
|
446
|
|
|
# Cut data to federal state if in testmode |
|
447
|
|
|
boundary = settings()["egon-data"]["--dataset-boundary"] |
|
448
|
|
|
if boundary != "Everything": |
|
449
|
|
|
map_states = { |
|
450
|
|
|
"Baden-Württemberg": "BW", |
|
451
|
|
|
"Nordrhein-Westfalen": "NW", |
|
452
|
|
|
"Hessen": "HE", |
|
453
|
|
|
"Brandenburg": "BB", |
|
454
|
|
|
"Bremen": "HB", |
|
455
|
|
|
"Rheinland-Pfalz": "RP", |
|
456
|
|
|
"Sachsen-Anhalt": "ST", |
|
457
|
|
|
"Schleswig-Holstein": "SH", |
|
458
|
|
|
"Mecklenburg-Vorpommern": "MV", |
|
459
|
|
|
"Thüringen": "TH", |
|
460
|
|
|
"Niedersachsen": "NI", |
|
461
|
|
|
"Sachsen": "SN", |
|
462
|
|
|
"Hamburg": "HH", |
|
463
|
|
|
"Saarland": "SL", |
|
464
|
|
|
"Berlin": "BE", |
|
465
|
|
|
"Bayern": "BY", |
|
466
|
|
|
} |
|
467
|
|
|
|
|
468
|
|
|
kw_liste_nep = kw_liste_nep[ |
|
469
|
|
|
kw_liste_nep.federal_state.isin([map_states[boundary], np.nan]) |
|
470
|
|
|
] |
|
471
|
|
|
|
|
472
|
|
|
for col in [ |
|
473
|
|
|
"capacity", |
|
474
|
|
|
"a2035_capacity", |
|
475
|
|
|
"b2035_capacity", |
|
476
|
|
|
"c2035_capacity", |
|
477
|
|
|
"b2040_capacity", |
|
478
|
|
|
]: |
|
479
|
|
|
kw_liste_nep.loc[ |
|
480
|
|
|
kw_liste_nep[kw_liste_nep.federal_state.isnull()].index, col |
|
481
|
|
|
] *= population_share() |
|
482
|
|
|
|
|
483
|
|
|
kw_liste_nep["carrier"] = map_carrier()[kw_liste_nep.carrier_nep].values |
|
484
|
|
|
|
|
485
|
|
|
if export is True: |
|
486
|
|
|
# Insert data to db |
|
487
|
|
|
kw_liste_nep.to_sql( |
|
488
|
|
|
targets["nep_conventional_powerplants"]["table"], |
|
489
|
|
|
engine, |
|
490
|
|
|
schema=targets["nep_conventional_powerplants"]["schema"], |
|
491
|
|
|
if_exists="replace", |
|
492
|
|
|
) |
|
493
|
|
|
else: |
|
494
|
|
|
return kw_liste_nep |
|
495
|
|
|
|
|
496
|
|
|
|
|
497
|
|
|
def district_heating_input(): |
|
498
|
|
|
"""Imports data for district heating networks in Germany |
|
499
|
|
|
|
|
500
|
|
|
Returns |
|
501
|
|
|
------- |
|
502
|
|
|
None. |
|
503
|
|
|
|
|
504
|
|
|
""" |
|
505
|
|
|
|
|
506
|
|
|
sources = egon.data.config.datasets()["scenario_input"]["sources"] |
|
507
|
|
|
|
|
508
|
|
|
# import data to dataframe |
|
509
|
|
|
file = ( |
|
510
|
|
|
Path(".") |
|
511
|
|
|
/ "data_bundle_egon_data" |
|
512
|
|
|
/ "nep2035_version2021" |
|
513
|
|
|
/ sources["eGon2035"]["capacities"] |
|
514
|
|
|
) |
|
515
|
|
|
df = pd.read_excel( |
|
516
|
|
|
file, sheet_name="Kurzstudie_KWK", dtype={"Wert": float} |
|
517
|
|
|
) |
|
518
|
|
|
df.set_index(["Energietraeger", "Name"], inplace=True) |
|
519
|
|
|
|
|
520
|
|
|
# Scale values to population share in testmode |
|
521
|
|
|
if settings()["egon-data"]["--dataset-boundary"] != "Everything": |
|
522
|
|
|
df.loc[ |
|
523
|
|
|
pd.IndexSlice[:, "Fernwaermeerzeugung"], "Wert" |
|
524
|
|
|
] *= population_share() |
|
525
|
|
|
|
|
526
|
|
|
# Connect to database |
|
527
|
|
|
engine = db.engine() |
|
528
|
|
|
session = sessionmaker(bind=engine)() |
|
529
|
|
|
|
|
530
|
|
|
# insert heatpumps and resistive heater as link |
|
531
|
|
|
for c in ["Grosswaermepumpe", "Elektrodenheizkessel"]: |
|
532
|
|
|
entry = EgonScenarioCapacities( |
|
533
|
|
|
component="link", |
|
534
|
|
|
scenario_name="eGon2035", |
|
535
|
|
|
nuts="DE", |
|
536
|
|
|
carrier="urban_central_" |
|
537
|
|
|
+ ("heat_pump" if c == "Grosswaermepumpe" else "resistive_heater"), |
|
538
|
|
|
capacity=df.loc[(c, "Fernwaermeerzeugung"), "Wert"] |
|
539
|
|
|
* 1e6 |
|
540
|
|
|
/ df.loc[(c, "Volllaststunden"), "Wert"] |
|
541
|
|
|
/ df.loc[(c, "Wirkungsgrad"), "Wert"], |
|
542
|
|
|
) |
|
543
|
|
|
|
|
544
|
|
|
session.add(entry) |
|
545
|
|
|
|
|
546
|
|
|
# insert solar- and geothermal as generator |
|
547
|
|
|
for c in ["Geothermie", "Solarthermie"]: |
|
548
|
|
|
entry = EgonScenarioCapacities( |
|
549
|
|
|
component="generator", |
|
550
|
|
|
scenario_name="eGon2035", |
|
551
|
|
|
nuts="DE", |
|
552
|
|
|
carrier="urban_central_" |
|
553
|
|
|
+ ( |
|
554
|
|
|
"solar_thermal_collector" |
|
555
|
|
|
if c == "Solarthermie" |
|
556
|
|
|
else "geo_thermal" |
|
557
|
|
|
), |
|
558
|
|
|
capacity=df.loc[(c, "Fernwaermeerzeugung"), "Wert"] |
|
559
|
|
|
* 1e6 |
|
560
|
|
|
/ df.loc[(c, "Volllaststunden"), "Wert"], |
|
561
|
|
|
) |
|
562
|
|
|
|
|
563
|
|
|
session.add(entry) |
|
564
|
|
|
|
|
565
|
|
|
session.commit() |
|
566
|
|
|
|
|
567
|
|
|
|
|
568
|
|
|
def insert_data_nep(): |
|
569
|
|
|
"""Overall function for importing scenario input data for eGon2035 scenario |
|
570
|
|
|
|
|
571
|
|
|
Returns |
|
572
|
|
|
------- |
|
573
|
|
|
None. |
|
574
|
|
|
|
|
575
|
|
|
""" |
|
576
|
|
|
|
|
577
|
|
|
insert_nep_list_powerplants(export=True) |
|
578
|
|
|
|
|
579
|
|
|
insert_capacities_per_federal_state_nep() |
|
580
|
|
|
|
|
581
|
|
|
|
|
582
|
|
|
def eGon100_capacities(): |
|
583
|
|
|
"""Inserts installed capacities for the eGon100 scenario |
|
584
|
|
|
|
|
585
|
|
|
Returns |
|
586
|
|
|
------- |
|
587
|
|
|
None. |
|
588
|
|
|
|
|
589
|
|
|
""" |
|
590
|
|
|
|
|
591
|
|
|
sources = egon.data.config.datasets()["scenario_input"]["sources"] |
|
592
|
|
|
targets = egon.data.config.datasets()["scenario_input"]["targets"] |
|
593
|
|
|
|
|
594
|
|
|
# read-in installed capacities |
|
595
|
|
|
execute_pypsa_eur_sec = False |
|
596
|
|
|
cwd = Path(".") |
|
597
|
|
|
|
|
598
|
|
|
if execute_pypsa_eur_sec: |
|
599
|
|
|
filepath = cwd / "run-pypsa-eur-sec" |
|
600
|
|
|
pypsa_eur_sec_repos = filepath / "pypsa-eur-sec" |
|
601
|
|
|
# Read YAML file |
|
602
|
|
|
pes_egonconfig = pypsa_eur_sec_repos / "config_egon.yaml" |
|
603
|
|
|
with open(pes_egonconfig, "r") as stream: |
|
604
|
|
|
data_config = yaml.safe_load(stream) |
|
605
|
|
|
|
|
606
|
|
|
target_file = ( |
|
607
|
|
|
pypsa_eur_sec_repos |
|
608
|
|
|
/ "results" |
|
609
|
|
|
/ data_config["run"] |
|
610
|
|
|
/ "csvs" |
|
611
|
|
|
/ sources["eGon100RE"]["capacities"] |
|
612
|
|
|
) |
|
613
|
|
|
|
|
614
|
|
|
else: |
|
615
|
|
|
target_file = ( |
|
616
|
|
|
cwd |
|
617
|
|
|
/ "data_bundle_egon_data" |
|
618
|
|
|
/ "pypsa_eur_sec" |
|
619
|
|
|
/ "2022-07-26-egondata-integration" |
|
620
|
|
|
/ "csvs" |
|
621
|
|
|
/ sources["eGon100RE"]["capacities"] |
|
622
|
|
|
) |
|
623
|
|
|
|
|
624
|
|
|
df = pd.read_csv(target_file, skiprows=5) |
|
625
|
|
|
df.columns = ["component", "country", "carrier", "p_nom"] |
|
626
|
|
|
|
|
627
|
|
|
df.set_index("carrier", inplace=True) |
|
628
|
|
|
|
|
629
|
|
|
df = df[df.country.str[:2] == "DE"] |
|
630
|
|
|
|
|
631
|
|
|
# Drop country column |
|
632
|
|
|
df.drop("country", axis=1, inplace=True) |
|
633
|
|
|
|
|
634
|
|
|
# Drop copmponents which will be optimized in eGo |
|
635
|
|
|
unused_carrier = [ |
|
636
|
|
|
"BEV charger", |
|
637
|
|
|
"DAC", |
|
638
|
|
|
"H2 Electrolysis", |
|
639
|
|
|
"electricity distribution grid", |
|
640
|
|
|
"home battery charger", |
|
641
|
|
|
"home battery discharger", |
|
642
|
|
|
"H2", |
|
643
|
|
|
"Li ion", |
|
644
|
|
|
"home battery", |
|
645
|
|
|
"residential rural water tanks charger", |
|
646
|
|
|
"residential rural water tanks discharger", |
|
647
|
|
|
"services rural water tanks charger", |
|
648
|
|
|
"services rural water tanks discharger", |
|
649
|
|
|
"residential rural water tanks", |
|
650
|
|
|
"services rural water tanks", |
|
651
|
|
|
"urban central water tanks", |
|
652
|
|
|
"urban central water tanks charger", |
|
653
|
|
|
"urban central water tanks discharger", |
|
654
|
|
|
"H2 Fuel Cell", |
|
655
|
|
|
] |
|
656
|
|
|
|
|
657
|
|
|
df = df[~df.index.isin(unused_carrier)] |
|
658
|
|
|
|
|
659
|
|
|
df.index = df.index.str.replace(" ", "_") |
|
660
|
|
|
|
|
661
|
|
|
# Aggregate offshore wind |
|
662
|
|
|
df = df.append( |
|
663
|
|
|
pd.DataFrame( |
|
664
|
|
|
index=["wind_offshore"], |
|
665
|
|
|
data={ |
|
666
|
|
|
"p_nom": (df.p_nom["offwind-ac"] + df.p_nom["offwind-dc"]), |
|
667
|
|
|
"component": df.component["offwind-ac"], |
|
668
|
|
|
}, |
|
669
|
|
|
) |
|
670
|
|
|
) |
|
671
|
|
|
df = df.drop(["offwind-ac", "offwind-dc"]) |
|
672
|
|
|
|
|
673
|
|
|
# Aggregate technologies with and without carbon_capture (CC) |
|
674
|
|
|
for carrier in ["SMR", "urban_central_gas_CHP"]: |
|
675
|
|
|
df.p_nom[carrier] += df.p_nom[f"{carrier}_CC"] |
|
676
|
|
|
df = df.drop([f"{carrier}_CC"]) |
|
677
|
|
|
|
|
678
|
|
|
# Aggregate residential and services rural heat supply |
|
679
|
|
|
for merge_carrier in [ |
|
680
|
|
|
"rural_resistive_heater", |
|
681
|
|
|
"rural_ground_heat_pump", |
|
682
|
|
|
"rural_gas_boiler", |
|
683
|
|
|
"rural_solar_thermal", |
|
684
|
|
|
]: |
|
685
|
|
|
if f"residential_{merge_carrier}" in df.index: |
|
686
|
|
|
df = df.append( |
|
687
|
|
|
pd.DataFrame( |
|
688
|
|
|
index=[merge_carrier], |
|
689
|
|
|
data={ |
|
690
|
|
|
"p_nom": ( |
|
691
|
|
|
df.p_nom[f"residential_{merge_carrier}"] |
|
692
|
|
|
+ df.p_nom[f"services_{merge_carrier}"] |
|
693
|
|
|
), |
|
694
|
|
|
"component": df.component[f"residential_{merge_carrier}"], |
|
695
|
|
|
}, |
|
696
|
|
|
) |
|
697
|
|
|
) |
|
698
|
|
|
df = df.drop( |
|
699
|
|
|
[f"residential_{merge_carrier}", f"services_{merge_carrier}"] |
|
700
|
|
|
) |
|
701
|
|
|
|
|
702
|
|
|
# Rename carriers |
|
703
|
|
|
df.rename( |
|
704
|
|
|
{ |
|
705
|
|
|
"onwind": "wind_onshore", |
|
706
|
|
|
"ror": "run_of_river", |
|
707
|
|
|
"PHS": "pumped_hydro", |
|
708
|
|
|
"OCGT": "gas", |
|
709
|
|
|
"rural_ground_heat_pump": "residential_rural_heat_pump", |
|
710
|
|
|
"urban_central_air_heat_pump": "urban_central_heat_pump", |
|
711
|
|
|
"urban_central_solar_thermal": "urban_central_solar_thermal_collector", |
|
712
|
|
|
}, |
|
713
|
|
|
inplace=True, |
|
714
|
|
|
) |
|
715
|
|
|
|
|
716
|
|
|
# Reset index |
|
717
|
|
|
df = df.reset_index() |
|
718
|
|
|
|
|
719
|
|
|
# Rename columns |
|
720
|
|
|
df.rename( |
|
721
|
|
|
{"p_nom": "capacity", "index": "carrier"}, axis="columns", inplace=True |
|
722
|
|
|
) |
|
723
|
|
|
|
|
724
|
|
|
df["scenario_name"] = "eGon100RE" |
|
725
|
|
|
df["nuts"] = "DE" |
|
726
|
|
|
|
|
727
|
|
|
db.execute_sql( |
|
728
|
|
|
f""" |
|
729
|
|
|
DELETE FROM |
|
730
|
|
|
{targets['scenario_capacities']['schema']}.{targets['scenario_capacities']['table']} |
|
731
|
|
|
WHERE scenario_name='eGon100RE' |
|
732
|
|
|
""" |
|
733
|
|
|
) |
|
734
|
|
|
|
|
735
|
|
|
df.to_sql( |
|
736
|
|
|
targets["scenario_capacities"]["table"], |
|
737
|
|
|
schema=targets["scenario_capacities"]["schema"], |
|
738
|
|
|
con=db.engine(), |
|
739
|
|
|
if_exists="append", |
|
740
|
|
|
index=False, |
|
741
|
|
|
) |
|
742
|
|
|
|
openego /
eGon-data
