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"""The module containing all parameters for the scenario table |
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""" |
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import pandas as pd |
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import egon.data.config |
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def read_csv(year): |
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source = egon.data.config.datasets()["pypsa-technology-data"]["targets"][ |
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"data_dir" |
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] |
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return pd.read_csv(f"{source}costs_{year}.csv") |
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def read_costs(df, technology, parameter, value_only=True): |
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result = df.loc[ |
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(df.technology == technology) & (df.parameter == parameter) |
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].squeeze() |
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# Rescale costs to EUR/MW |
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if "EUR/kW" in result.unit: |
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result.value *= 1e3 |
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result.unit = result.unit.replace("kW", "MW") |
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if value_only: |
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return result.value |
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else: |
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return result |
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def annualize_capital_costs(overnight_costs, lifetime, p): |
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""" |
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Parameters |
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---------- |
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overnight_costs : float |
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Overnight investment costs in EUR/MW or EUR/MW/km |
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lifetime : int |
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Number of years in which payments will be made |
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p : float |
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Interest rate in p.u. |
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Returns |
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------- |
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float |
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Annualized capital costs in EUR/MW/a or EUR/MW/km/a |
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""" |
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# Calculate present value of an annuity (PVA) |
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PVA = (1 / p) - (1 / (p * (1 + p) ** lifetime)) |
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return overnight_costs / PVA |
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def global_settings(scenario): |
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"""Returns global paramaters for the selected scenario. |
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Parameters |
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---------- |
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scenario : str |
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Name of the scenario. |
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Returns |
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------- |
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parameters : dict |
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List of global parameters |
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""" |
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if scenario == "eGon2035": |
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parameters = { |
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"weather_year": 2011, |
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"population_year": 2035, |
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"fuel_costs": { # Netzentwicklungsplan Strom 2035, Version 2021, 1. Entwurf, p. 39, table 6 |
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"oil": 73.8, # [EUR/MWh] |
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"gas": 25.6, # [EUR/MWh] |
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80
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"coal": 20.2, # [EUR/MWh] |
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81
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"lignite": 4.0, # [EUR/MWh] |
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82
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"nuclear": 1.7, # [EUR/MWh] |
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"biomass": 40, # Dummyvalue, ToDo: Find a suitable source |
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}, |
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"co2_costs": 76.5, # [EUR/t_CO2] |
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"co2_emissions": { # Netzentwicklungsplan Strom 2035, Version 2021, 1. Entwurf, p. 40, table 8 |
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"waste": 0.165, # [t_CO2/MW_th] |
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"lignite": 0.393, # [t_CO2/MW_th] |
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"gas": 0.201, # [t_CO2/MW_th] |
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"nuclear": 0.0, # [t_CO2/MW_th] |
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"oil": 0.288, # [t_CO2/MW_th] |
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"coal": 0.335, # [t_CO2/MW_th] |
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"other_non_renewable": 0.268, # [t_CO2/MW_th] |
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}, |
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"interest_rate": 0.05, # [p.u.] |
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} |
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elif scenario == "eGon100RE": |
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parameters = { |
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"weather_year": 2011, |
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"population_year": 2050, |
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"fuel_costs": { # Netzentwicklungsplan Strom 2035, Version 2021, 1. Entwurf, p. 39, table 6 |
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"oil": 73.8, # [EUR/MWh] |
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"gas": 25.6, # [EUR/MWh] |
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"coal": 20.2, # [EUR/MWh] |
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"lignite": 4.0, # [EUR/MWh] |
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"nuclear": 1.7, # [EUR/MWh] |
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}, |
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"co2_costs": 76.5, # [EUR/t_CO2] |
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"co2_emissions": { # Netzentwicklungsplan Strom 2035, Version 2021, 1. Entwurf, p. 40, table 8 |
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"waste": 0.165, # [t_CO2/MW_th] |
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"lignite": 0.393, # [t_CO2/MW_th] |
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"gas": 0.201, # [t_CO2/MW_th] |
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"nuclear": 0.0, # [t_CO2/MW_th] |
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"oil": 0.288, # [t_CO2/MW_th] |
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"coal": 0.335, # [t_CO2/MW_th] |
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"other_non_renewable": 0.268, # [t_CO2/MW_th] |
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}, |
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"interest_rate": 0.05, # [p.u.] |
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} |
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elif scenario == "eGon2021": |
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parameters = { |
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"weather_year": 2011, |
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"population_year": 2021, |
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} |
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elif scenario == "status2023": |
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parameters = { |
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"weather_year": 2023, |
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"population_year": 2019, # TODO: check if possible for 2023 |
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"fuel_costs": { |
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# TYNDP 2020, data for 2023 (https://2020.entsos-tyndp-scenarios.eu/fuel-commodities-and-carbon-prices/) |
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"oil": 16.4 * 3.6, # [EUR/MWh] |
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"gas": 6.1 * 3.6, # [EUR/MWh] |
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"coal": 3.4 * 3.6, # [EUR/MWh] |
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"lignite": 1.1 * 3.6, # [EUR/MWh] |
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"nuclear": 0.47 * 3.6, # [EUR/MWh] |
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"biomass": read_costs(read_csv(2020), "biomass", "fuel"), |
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}, |
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"co2_costs": 83.66, # [EUR/t_CO2], source: |
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# https://www.iwr.de/news/co2-emissionshandel-deutschland-erzielt-2023-rekordeinnahmen-von-ueber-18-mrd-euro-news38528 |
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"co2_emissions": { |
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# Netzentwicklungsplan Strom 2037, Genehmigtr Scenariorahmen, p. 66, table 21 |
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# https://www.netzentwicklungsplan.de/sites/default/files/2023-01/Szenariorahmen_2037_Genehmigung.pdf |
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"waste": 0.165, # [t_CO2/MW_th] |
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"lignite": 0.393, # [t_CO2/MW_th] |
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"gas": 0.201, # [t_CO2/MW_th] |
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"nuclear": 0.0, # [t_CO2/MW_th] |
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"oil": 0.288, # [t_CO2/MW_th] |
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"coal": 0.337, # [t_CO2/MW_th] |
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"other_non_renewable": 0.268, # [t_CO2/MW_th] |
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}, |
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"interest_rate": 0.05, # [p.u.] |
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} |
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elif scenario == "status2019": |
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parameters = { |
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"weather_year": 2011, |
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"population_year": 2019, |
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"fuel_costs": { # TYNDP 2020, data for 2020 (https://2020.entsos-tyndp-scenarios.eu/fuel-commodities-and-carbon-prices/) |
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"oil": 12.9*3.6, # [EUR/MWh] |
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"gas": 5.6*3.6, # [EUR/MWh] |
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"coal": 3.0*3.6, # [EUR/MWh] |
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165
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"lignite": 1.1*3.6, # [EUR/MWh] |
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"nuclear": 0.47*3.6, # [EUR/MWh] |
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"biomass": read_costs(read_csv(2020), "biomass", "fuel"), |
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}, |
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"co2_costs": 24.7, # [EUR/t_CO2], source: |
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#https://de.statista.com/statistik/daten/studie/1304069/umfrage/preisentwicklung-von-co2-emissionsrechten-in-eu/ |
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"co2_emissions": { # Netzentwicklungsplan Strom 2035, Version 2021, 1. Entwurf, p. 40, table 8 |
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"waste": 0.165, # [t_CO2/MW_th] |
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"lignite": 0.393, # [t_CO2/MW_th] |
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"gas": 0.201, # [t_CO2/MW_th] |
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"nuclear": 0.0, # [t_CO2/MW_th] |
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"oil": 0.288, # [t_CO2/MW_th] |
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"coal": 0.335, # [t_CO2/MW_th] |
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"other_non_renewable": 0.268, # [t_CO2/MW_th] |
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}, |
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"interest_rate": 0.05, # [p.u.] |
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} |
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else: |
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print(f"Scenario name {scenario} is not valid.") |
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return parameters |
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def electricity(scenario): |
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"""Returns paramaters of the electricity sector for the selected scenario. |
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Parameters |
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---------- |
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scenario : str |
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Name of the scenario. |
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Returns |
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------- |
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parameters : dict |
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List of parameters of electricity sector |
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""" |
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if scenario == "eGon2035": |
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costs = read_csv(2035) |
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parameters = {"grid_topology": "Status Quo"} |
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# Insert effciencies in p.u. |
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parameters["efficiency"] = { |
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"oil": read_costs(costs, "oil", "efficiency"), |
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"battery": { |
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"store": read_costs(costs, "battery inverter", "efficiency") |
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** 0.5, |
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"dispatch": read_costs(costs, "battery inverter", "efficiency") |
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** 0.5, |
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"standing_loss": 0, |
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"max_hours": 6, |
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"cyclic_state_of_charge": True, |
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}, |
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"pumped_hydro": { |
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"store": read_costs(costs, "PHS", "efficiency") ** 0.5, |
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"dispatch": read_costs(costs, "PHS", "efficiency") ** 0.5, |
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"standing_loss": 0, |
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"max_hours": 6, |
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"cyclic_state_of_charge": True, |
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}, |
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} |
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# Warning: Electrical parameters are set in osmTGmod, editing these values will not change the data! |
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parameters["electrical_parameters"] = { |
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"ac_line_110kV": { |
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"s_nom": 260, # [MVA] |
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"R": 0.109, # [Ohm/km] |
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"L": 1.2, # [mH/km] |
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}, |
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"ac_cable_110kV": { |
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"s_nom": 280, # [MVA] |
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"R": 0.0177, # [Ohm/km] |
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"L": 0.3, # [mH/km] |
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}, |
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"ac_line_220kV": { |
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"s_nom": 520, # [MVA] |
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"R": 0.109, # [Ohm/km] |
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"L": 1.0, # [mH/km] |
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}, |
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"ac_cable_220kV": { |
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"s_nom": 550, # [MVA] |
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"R": 0.0176, # [Ohm/km] |
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"L": 0.3, # [mH/km] |
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}, |
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"ac_line_380kV": { |
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"s_nom": 1790, # [MVA] |
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"R": 0.028, # [Ohm/km] |
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"L": 0.8, # [mH/km] |
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}, |
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"ac_cable_380kV": { |
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"s_nom": 925, # [MVA] |
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"R": 0.0175, # [Ohm/km] |
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"L": 0.3, # [mH/km] |
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}, |
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260
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} |
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262
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# Insert overnight investment costs |
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# Source for eHV grid costs: Netzentwicklungsplan Strom 2035, Version 2021, 2. Entwurf |
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264
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# Source for HV lines and cables: Dena Verteilnetzstudie 2021, p. 146 |
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265
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parameters["overnight_cost"] = { |
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266
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"ac_ehv_overhead_line": 2.5e6 |
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/ ( |
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268
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2 |
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* parameters["electrical_parameters"]["ac_line_380kV"]["s_nom"] |
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270
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), # [EUR/km/MW] |
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"ac_ehv_cable": 11.5e6 |
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/ ( |
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273
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2 |
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274
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* parameters["electrical_parameters"]["ac_cable_380kV"][ |
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275
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"s_nom" |
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276
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] |
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277
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), # [EUR/km/MW] |
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278
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"ac_hv_overhead_line": 0.06e6 |
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279
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/ parameters["electrical_parameters"]["ac_line_110kV"][ |
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280
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"s_nom" |
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281
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], # [EUR/km/MW] |
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282
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"ac_hv_cable": 0.8e6 |
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283
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/ parameters["electrical_parameters"]["ac_cable_110kV"][ |
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284
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"s_nom" |
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285
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], # [EUR/km/MW] |
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286
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"dc_overhead_line": 0.5e3, # [EUR/km/MW] |
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287
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"dc_cable": 3.25e3, # [EUR/km/MW] |
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288
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|
|
"dc_inverter": 0.3e6, # [EUR/MW] |
|
289
|
|
|
"transformer_380_110": 17.33e3, # [EUR/MVA] |
|
290
|
|
|
"transformer_380_220": 13.33e3, # [EUR/MVA] |
|
291
|
|
|
"transformer_220_110": 17.5e3, # [EUR/MVA] |
|
292
|
|
|
"battery inverter": read_costs( |
|
293
|
|
|
costs, "battery inverter", "investment" |
|
294
|
|
|
), |
|
295
|
|
|
"battery storage": read_costs( |
|
296
|
|
|
costs, "battery storage", "investment" |
|
297
|
|
|
), |
|
298
|
|
|
} |
|
299
|
|
|
|
|
300
|
|
|
parameters["lifetime"] = { |
|
301
|
|
|
"ac_ehv_overhead_line": read_costs( |
|
302
|
|
|
costs, "HVAC overhead", "lifetime" |
|
303
|
|
|
), |
|
304
|
|
|
"ac_ehv_cable": read_costs(costs, "HVAC overhead", "lifetime"), |
|
305
|
|
|
"ac_hv_overhead_line": read_costs( |
|
306
|
|
|
costs, "HVAC overhead", "lifetime" |
|
307
|
|
|
), |
|
308
|
|
|
"ac_hv_cable": read_costs(costs, "HVAC overhead", "lifetime"), |
|
309
|
|
|
"dc_overhead_line": read_costs(costs, "HVDC overhead", "lifetime"), |
|
310
|
|
|
"dc_cable": read_costs(costs, "HVDC overhead", "lifetime"), |
|
311
|
|
|
"dc_inverter": read_costs(costs, "HVDC inverter pair", "lifetime"), |
|
312
|
|
|
"transformer_380_110": read_costs( |
|
313
|
|
|
costs, "HVAC overhead", "lifetime" |
|
314
|
|
|
), |
|
315
|
|
|
"transformer_380_220": read_costs( |
|
316
|
|
|
costs, "HVAC overhead", "lifetime" |
|
317
|
|
|
), |
|
318
|
|
|
"transformer_220_110": read_costs( |
|
319
|
|
|
costs, "HVAC overhead", "lifetime" |
|
320
|
|
|
), |
|
321
|
|
|
"battery inverter": read_costs( |
|
322
|
|
|
costs, "battery inverter", "lifetime" |
|
323
|
|
|
), |
|
324
|
|
|
"battery storage": read_costs( |
|
325
|
|
|
costs, "battery storage", "lifetime" |
|
326
|
|
|
), |
|
327
|
|
|
} |
|
328
|
|
|
# Insert annualized capital costs |
|
329
|
|
|
# lines in EUR/km/MW/a |
|
330
|
|
|
# transfermer, inverter, battery in EUR/MW/a |
|
331
|
|
|
parameters["capital_cost"] = {} |
|
332
|
|
|
|
|
333
|
|
|
for comp in parameters["overnight_cost"].keys(): |
|
334
|
|
|
parameters["capital_cost"][comp] = annualize_capital_costs( |
|
335
|
|
|
parameters["overnight_cost"][comp], |
|
336
|
|
|
parameters["lifetime"][comp], |
|
337
|
|
|
global_settings("eGon2035")["interest_rate"], |
|
338
|
|
|
) |
|
339
|
|
|
|
|
340
|
|
|
parameters["capital_cost"]["battery"] = ( |
|
341
|
|
|
parameters["capital_cost"]["battery inverter"] |
|
342
|
|
|
+ parameters["efficiency"]["battery"]["max_hours"] |
|
343
|
|
|
* parameters["capital_cost"]["battery storage"] |
|
344
|
|
|
) |
|
345
|
|
|
|
|
346
|
|
|
# Insert marginal_costs in EUR/MWh |
|
347
|
|
|
# marginal cost can include fuel, C02 and operation and maintenance costs |
|
348
|
|
|
parameters["marginal_cost"] = { |
|
349
|
|
|
"oil": global_settings(scenario)["fuel_costs"]["oil"] |
|
350
|
|
|
/ read_costs(costs, "oil", "efficiency") |
|
351
|
|
|
+ read_costs(costs, "oil", "VOM") |
|
352
|
|
|
+ global_settings(scenario)["co2_costs"] |
|
353
|
|
|
* global_settings(scenario)["co2_emissions"]["oil"] |
|
354
|
|
|
/ read_costs(costs, "oil", "efficiency"), |
|
355
|
|
|
"other_non_renewable": global_settings(scenario)["fuel_costs"][ |
|
356
|
|
|
"gas" |
|
357
|
|
|
] / read_costs(costs, "OCGT", "efficiency") |
|
358
|
|
|
+ global_settings(scenario)["co2_costs"] |
|
359
|
|
|
* global_settings(scenario)["co2_emissions"][ |
|
360
|
|
|
"other_non_renewable" |
|
361
|
|
|
] / read_costs(costs, "OCGT", "efficiency"), |
|
362
|
|
|
"lignite": global_settings(scenario)["fuel_costs"]["lignite"] |
|
363
|
|
|
/ read_costs(costs, "lignite", "efficiency") |
|
364
|
|
|
+ read_costs(costs, "lignite", "VOM") |
|
365
|
|
|
+ global_settings(scenario)["co2_costs"] |
|
366
|
|
|
* global_settings(scenario)["co2_emissions"]["lignite"] |
|
367
|
|
|
/ read_costs(costs, "lignite", "efficiency"), |
|
368
|
|
|
"coal": global_settings(scenario)["fuel_costs"]["coal"] |
|
369
|
|
|
/ read_costs(costs, "coal", "efficiency") |
|
370
|
|
|
+ read_costs(costs, "coal", "VOM") |
|
371
|
|
|
+ global_settings(scenario)["co2_costs"] |
|
372
|
|
|
* global_settings(scenario)["co2_emissions"]["coal"] |
|
373
|
|
|
/ read_costs(costs, "coal", "efficiency"), |
|
374
|
|
|
"nuclear": global_settings(scenario)["fuel_costs"]["nuclear"] |
|
375
|
|
|
/ read_costs(costs, "nuclear", "efficiency") |
|
376
|
|
|
+ read_costs(costs, "nuclear", "VOM"), |
|
377
|
|
|
"biomass": global_settings(scenario)["fuel_costs"]["biomass"] |
|
378
|
|
|
/ read_costs(costs, "biomass", "efficiency") |
|
379
|
|
|
+ read_costs(costs, "biomass CHP", "VOM"), |
|
380
|
|
|
"wind_offshore": read_costs(costs, "offwind", "VOM"), |
|
381
|
|
|
"wind_onshore": read_costs(costs, "onwind", "VOM"), |
|
382
|
|
|
"solar": read_costs(costs, "solar", "VOM"), |
|
383
|
|
|
# According to https://www.aemo.com.au/-/media/Files/Electricity/NEM/Planning_and_Forecasting/Inputs-Assumptions-Methodologies/2019/Report-Pumped-Hydro-Cost-Modelling.pdf |
|
384
|
|
|
# for hydro generation all operations and maintenance costs might |
|
385
|
|
|
# be categorized as fixed rather than variable. |
|
386
|
|
|
"run_of_river": 0, |
|
387
|
|
|
"reservoir": 0, |
|
388
|
|
|
} |
|
389
|
|
|
|
|
390
|
|
|
elif scenario == "eGon100RE": |
|
391
|
|
|
costs = read_csv(2050) |
|
392
|
|
|
|
|
393
|
|
|
parameters = {"grid_topology": "Status Quo"} |
|
394
|
|
|
|
|
395
|
|
|
# Insert effciencies in p.u. |
|
396
|
|
|
parameters["efficiency"] = { |
|
397
|
|
|
"battery": { |
|
398
|
|
|
"store": read_costs(costs, "battery inverter", "efficiency") |
|
399
|
|
|
** 0.5, |
|
400
|
|
|
"dispatch": read_costs(costs, "battery inverter", "efficiency") |
|
401
|
|
|
** 0.5, |
|
402
|
|
|
"standing_loss": 0, |
|
403
|
|
|
"max_hours": 6, |
|
404
|
|
|
"cyclic_state_of_charge": True, |
|
405
|
|
|
}, |
|
406
|
|
|
"pumped_hydro": { |
|
407
|
|
|
"store": read_costs(costs, "PHS", "efficiency") ** 0.5, |
|
408
|
|
|
"dispatch": read_costs(costs, "PHS", "efficiency") ** 0.5, |
|
409
|
|
|
"standing_loss": 0, |
|
410
|
|
|
"max_hours": 6, |
|
411
|
|
|
"cyclic_state_of_charge": True, |
|
412
|
|
|
}, |
|
413
|
|
|
} |
|
414
|
|
|
# Warning: Electrical parameters are set in osmTGmod, editing these values will not change the data! |
|
415
|
|
|
parameters["electrical_parameters"] = { |
|
416
|
|
|
"ac_line_110kV": { |
|
417
|
|
|
"s_nom": 260, # [MVA] |
|
418
|
|
|
"R": 0.109, # [Ohm/km] |
|
419
|
|
|
"L": 1.2, # [mH/km] |
|
420
|
|
|
}, |
|
421
|
|
|
"ac_cable_110kV": { |
|
422
|
|
|
"s_nom": 280, # [MVA] |
|
423
|
|
|
"R": 0.0177, # [Ohm/km] |
|
424
|
|
|
"L": 0.3, # [mH/km] |
|
425
|
|
|
}, |
|
426
|
|
|
"ac_line_220kV": { |
|
427
|
|
|
"s_nom": 520, # [MVA] |
|
428
|
|
|
"R": 0.109, # [Ohm/km] |
|
429
|
|
|
"L": 1.0, # [mH/km] |
|
430
|
|
|
}, |
|
431
|
|
|
"ac_cable_220kV": { |
|
432
|
|
|
"s_nom": 550, # [MVA] |
|
433
|
|
|
"R": 0.0176, # [Ohm/km] |
|
434
|
|
|
"L": 0.3, # [mH/km] |
|
435
|
|
|
}, |
|
436
|
|
|
"ac_line_380kV": { |
|
437
|
|
|
"s_nom": 1790, # [MVA] |
|
438
|
|
|
"R": 0.028, # [Ohm/km] |
|
439
|
|
|
"L": 0.8, # [mH/km] |
|
440
|
|
|
}, |
|
441
|
|
|
"ac_cable_380kV": { |
|
442
|
|
|
"s_nom": 925, # [MVA] |
|
443
|
|
|
"R": 0.0175, # [Ohm/km] |
|
444
|
|
|
"L": 0.3, # [mH/km] |
|
445
|
|
|
}, |
|
446
|
|
|
} |
|
447
|
|
|
|
|
448
|
|
|
# Insert overnight investment costs |
|
449
|
|
|
# Source for transformer costs: Netzentwicklungsplan Strom 2035, Version 2021, 2. Entwurf |
|
450
|
|
|
# Source for HV lines and cables: Dena Verteilnetzstudie 2021, p. 146 |
|
451
|
|
|
parameters["overnight_cost"] = { |
|
452
|
|
|
"ac_ehv_overhead_line": read_costs( |
|
453
|
|
|
costs, "HVAC overhead", "investment" |
|
454
|
|
|
), # [EUR/km/MW] |
|
455
|
|
|
"ac_hv_overhead_line": 0.06e6 |
|
456
|
|
|
/ parameters["electrical_parameters"]["ac_line_110kV"][ |
|
457
|
|
|
"s_nom" |
|
458
|
|
|
], # [EUR/km/MW] |
|
459
|
|
|
"ac_hv_cable": 0.8e6 |
|
460
|
|
|
/ parameters["electrical_parameters"]["ac_cable_110kV"][ |
|
461
|
|
|
"s_nom" |
|
462
|
|
|
], # [EUR/km/MW] |
|
463
|
|
|
"dc_overhead_line": read_costs( |
|
464
|
|
|
costs, "HVDC overhead", "investment" |
|
465
|
|
|
), |
|
466
|
|
|
"dc_cable": read_costs(costs, "HVDC overhead", "investment"), |
|
467
|
|
|
"dc_inverter": read_costs( |
|
468
|
|
|
costs, "HVDC inverter pair", "investment" |
|
469
|
|
|
), |
|
470
|
|
|
"transformer_380_110": 17.33e3, # [EUR/MVA] |
|
471
|
|
|
"transformer_380_220": 13.33e3, # [EUR/MVA] |
|
472
|
|
|
"transformer_220_110": 17.5e3, # [EUR/MVA] |
|
473
|
|
|
"battery inverter": read_costs( |
|
474
|
|
|
costs, "battery inverter", "investment" |
|
475
|
|
|
), |
|
476
|
|
|
"battery storage": read_costs( |
|
477
|
|
|
costs, "battery storage", "investment" |
|
478
|
|
|
), |
|
479
|
|
|
} |
|
480
|
|
|
|
|
481
|
|
|
parameters["lifetime"] = { |
|
482
|
|
|
"ac_ehv_overhead_line": read_costs( |
|
483
|
|
|
costs, "HVAC overhead", "lifetime" |
|
484
|
|
|
), |
|
485
|
|
|
"ac_ehv_cable": read_costs(costs, "HVAC overhead", "lifetime"), |
|
486
|
|
|
"ac_hv_overhead_line": read_costs( |
|
487
|
|
|
costs, "HVAC overhead", "lifetime" |
|
488
|
|
|
), |
|
489
|
|
|
"ac_hv_cable": read_costs(costs, "HVAC overhead", "lifetime"), |
|
490
|
|
|
"dc_overhead_line": read_costs(costs, "HVDC overhead", "lifetime"), |
|
491
|
|
|
"dc_cable": read_costs(costs, "HVDC overhead", "lifetime"), |
|
492
|
|
|
"dc_inverter": read_costs(costs, "HVDC inverter pair", "lifetime"), |
|
493
|
|
|
"transformer_380_110": read_costs( |
|
494
|
|
|
costs, "HVAC overhead", "lifetime" |
|
495
|
|
|
), |
|
496
|
|
|
"transformer_380_220": read_costs( |
|
497
|
|
|
costs, "HVAC overhead", "lifetime" |
|
498
|
|
|
), |
|
499
|
|
|
"transformer_220_110": read_costs( |
|
500
|
|
|
costs, "HVAC overhead", "lifetime" |
|
501
|
|
|
), |
|
502
|
|
|
"battery inverter": read_costs( |
|
503
|
|
|
costs, "battery inverter", "lifetime" |
|
504
|
|
|
), |
|
505
|
|
|
"battery storage": read_costs( |
|
506
|
|
|
costs, "battery storage", "lifetime" |
|
507
|
|
|
), |
|
508
|
|
|
} |
|
509
|
|
|
# Insert annualized capital costs |
|
510
|
|
|
# lines in EUR/km/MW/a |
|
511
|
|
|
# transfermer, inverter, battery in EUR/MW/a |
|
512
|
|
|
parameters["capital_cost"] = {} |
|
513
|
|
|
|
|
514
|
|
|
for comp in parameters["overnight_cost"].keys(): |
|
515
|
|
|
parameters["capital_cost"][comp] = annualize_capital_costs( |
|
516
|
|
|
parameters["overnight_cost"][comp], |
|
517
|
|
|
parameters["lifetime"][comp], |
|
518
|
|
|
global_settings("eGon2035")["interest_rate"], |
|
519
|
|
|
) |
|
520
|
|
|
|
|
521
|
|
|
parameters["capital_cost"]["battery"] = ( |
|
522
|
|
|
parameters["capital_cost"]["battery inverter"] |
|
523
|
|
|
+ parameters["efficiency"]["battery"]["max_hours"] |
|
524
|
|
|
* parameters["capital_cost"]["battery storage"] |
|
525
|
|
|
) |
|
526
|
|
|
|
|
527
|
|
|
# Insert marginal_costs in EUR/MWh |
|
528
|
|
|
# marginal cost can include fuel, C02 and operation and maintenance costs |
|
529
|
|
|
parameters["marginal_cost"] = { |
|
530
|
|
|
"wind_offshore": read_costs(costs, "offwind", "VOM"), |
|
531
|
|
|
"wind_onshore": read_costs(costs, "onwind", "VOM"), |
|
532
|
|
|
"solar": read_costs(costs, "solar", "VOM"), |
|
533
|
|
|
# According to https://www.aemo.com.au/-/media/Files/Electricity/NEM/Planning_and_Forecasting/Inputs-Assumptions-Methodologies/2019/Report-Pumped-Hydro-Cost-Modelling.pdf |
|
534
|
|
|
# for hydro generation all operations and maintenance costs might |
|
535
|
|
|
# be categorized as fixed rather than variable. |
|
536
|
|
|
"run_of_river": 0, |
|
537
|
|
|
"reservoir": 0, |
|
538
|
|
|
} |
|
539
|
|
|
|
|
540
|
|
|
elif scenario == "eGon2021": |
|
541
|
|
|
parameters = {} |
|
542
|
|
|
|
|
543
|
|
|
elif (scenario == "status2019") or (scenario == "status2023"): |
|
544
|
|
|
costs = read_csv(2020) |
|
545
|
|
|
|
|
546
|
|
|
parameters = {"grid_topology": "Status Quo"} |
|
547
|
|
|
# Insert effciencies in p.u. |
|
548
|
|
|
parameters["efficiency"] = { |
|
549
|
|
|
"oil": read_costs(costs, "oil", "efficiency"), |
|
550
|
|
|
"battery": { |
|
551
|
|
|
"store": read_costs(costs, "battery inverter", "efficiency") |
|
552
|
|
|
** 0.5, |
|
553
|
|
|
"dispatch": read_costs(costs, "battery inverter", "efficiency") |
|
554
|
|
|
** 0.5, |
|
555
|
|
|
"standing_loss": 0, |
|
556
|
|
|
"max_hours": 6, |
|
557
|
|
|
"cyclic_state_of_charge": True, |
|
558
|
|
|
}, |
|
559
|
|
|
"pumped_hydro": { |
|
560
|
|
|
"store": read_costs(costs, "PHS", "efficiency") ** 0.5, |
|
561
|
|
|
"dispatch": read_costs(costs, "PHS", "efficiency") ** 0.5, |
|
562
|
|
|
"standing_loss": 0, |
|
563
|
|
|
"max_hours": 6, |
|
564
|
|
|
"cyclic_state_of_charge": True, |
|
565
|
|
|
}, |
|
566
|
|
|
} |
|
567
|
|
|
# Warning: Electrical parameters are set in osmTGmod, editing these values will not change the data! |
|
568
|
|
|
parameters["electrical_parameters"] = { |
|
569
|
|
|
"ac_line_110kV": { |
|
570
|
|
|
"s_nom": 260, # [MVA] |
|
571
|
|
|
"R": 0.109, # [Ohm/km] |
|
572
|
|
|
"L": 1.2, # [mH/km] |
|
573
|
|
|
}, |
|
574
|
|
|
"ac_cable_110kV": { |
|
575
|
|
|
"s_nom": 280, # [MVA] |
|
576
|
|
|
"R": 0.0177, # [Ohm/km] |
|
577
|
|
|
"L": 0.3, # [mH/km] |
|
578
|
|
|
}, |
|
579
|
|
|
"ac_line_220kV": { |
|
580
|
|
|
"s_nom": 520, # [MVA] |
|
581
|
|
|
"R": 0.109, # [Ohm/km] |
|
582
|
|
|
"L": 1.0, # [mH/km] |
|
583
|
|
|
}, |
|
584
|
|
|
"ac_cable_220kV": { |
|
585
|
|
|
"s_nom": 550, # [MVA] |
|
586
|
|
|
"R": 0.0176, # [Ohm/km] |
|
587
|
|
|
"L": 0.3, # [mH/km] |
|
588
|
|
|
}, |
|
589
|
|
|
"ac_line_380kV": { |
|
590
|
|
|
"s_nom": 1790, # [MVA] |
|
591
|
|
|
"R": 0.028, # [Ohm/km] |
|
592
|
|
|
"L": 0.8, # [mH/km] |
|
593
|
|
|
}, |
|
594
|
|
|
"ac_cable_380kV": { |
|
595
|
|
|
"s_nom": 925, # [MVA] |
|
596
|
|
|
"R": 0.0175, # [Ohm/km] |
|
597
|
|
|
"L": 0.3, # [mH/km] |
|
598
|
|
|
}, |
|
599
|
|
|
} |
|
600
|
|
|
|
|
601
|
|
|
# Insert overnight investment costs |
|
602
|
|
|
# Source for eHV grid costs: Netzentwicklungsplan Strom 2035, Version 2021, 2. Entwurf |
|
603
|
|
|
# Source for HV lines and cables: Dena Verteilnetzstudie 2021, p. 146 |
|
604
|
|
|
parameters["overnight_cost"] = { |
|
605
|
|
|
"ac_ehv_overhead_line": 2.5e6 |
|
606
|
|
|
/ ( |
|
607
|
|
|
2 |
|
608
|
|
|
* parameters["electrical_parameters"]["ac_line_380kV"]["s_nom"] |
|
609
|
|
|
), # [EUR/km/MW] |
|
610
|
|
|
"ac_ehv_cable": 11.5e6 |
|
611
|
|
|
/ ( |
|
612
|
|
|
2 |
|
613
|
|
|
* parameters["electrical_parameters"]["ac_cable_380kV"][ |
|
614
|
|
|
"s_nom" |
|
615
|
|
|
] |
|
616
|
|
|
), # [EUR/km/MW] |
|
617
|
|
|
"ac_hv_overhead_line": 0.06e6 |
|
618
|
|
|
/ parameters["electrical_parameters"]["ac_line_110kV"][ |
|
619
|
|
|
"s_nom" |
|
620
|
|
|
], # [EUR/km/MW] |
|
621
|
|
|
"ac_hv_cable": 0.8e6 |
|
622
|
|
|
/ parameters["electrical_parameters"]["ac_cable_110kV"][ |
|
623
|
|
|
"s_nom" |
|
624
|
|
|
], # [EUR/km/MW] |
|
625
|
|
|
"dc_overhead_line": 0.5e3, # [EUR/km/MW] |
|
626
|
|
|
"dc_cable": 3.25e3, # [EUR/km/MW] |
|
627
|
|
|
"dc_inverter": 0.3e6, # [EUR/MW] |
|
628
|
|
|
"transformer_380_110": 17.33e3, # [EUR/MVA] |
|
629
|
|
|
"transformer_380_220": 13.33e3, # [EUR/MVA] |
|
630
|
|
|
"transformer_220_110": 17.5e3, # [EUR/MVA] |
|
631
|
|
|
"battery inverter": read_costs( |
|
632
|
|
|
costs, "battery inverter", "investment" |
|
633
|
|
|
), |
|
634
|
|
|
"battery storage": read_costs( |
|
635
|
|
|
costs, "battery storage", "investment" |
|
636
|
|
|
), |
|
637
|
|
|
} |
|
638
|
|
|
|
|
639
|
|
|
parameters["lifetime"] = { |
|
640
|
|
|
"ac_ehv_overhead_line": read_costs( |
|
641
|
|
|
costs, "HVAC overhead", "lifetime" |
|
642
|
|
|
), |
|
643
|
|
|
"ac_ehv_cable": read_costs(costs, "HVAC overhead", "lifetime"), |
|
644
|
|
|
"ac_hv_overhead_line": read_costs( |
|
645
|
|
|
costs, "HVAC overhead", "lifetime" |
|
646
|
|
|
), |
|
647
|
|
|
"ac_hv_cable": read_costs(costs, "HVAC overhead", "lifetime"), |
|
648
|
|
|
"dc_overhead_line": read_costs(costs, "HVDC overhead", "lifetime"), |
|
649
|
|
|
"dc_cable": read_costs(costs, "HVDC overhead", "lifetime"), |
|
650
|
|
|
"dc_inverter": read_costs(costs, "HVDC inverter pair", "lifetime"), |
|
651
|
|
|
"transformer_380_110": read_costs( |
|
652
|
|
|
costs, "HVAC overhead", "lifetime" |
|
653
|
|
|
), |
|
654
|
|
|
"transformer_380_220": read_costs( |
|
655
|
|
|
costs, "HVAC overhead", "lifetime" |
|
656
|
|
|
), |
|
657
|
|
|
"transformer_220_110": read_costs( |
|
658
|
|
|
costs, "HVAC overhead", "lifetime" |
|
659
|
|
|
), |
|
660
|
|
|
"battery inverter": read_costs( |
|
661
|
|
|
costs, "battery inverter", "lifetime" |
|
662
|
|
|
), |
|
663
|
|
|
"battery storage": read_costs( |
|
664
|
|
|
costs, "battery storage", "lifetime" |
|
665
|
|
|
), |
|
666
|
|
|
} |
|
667
|
|
|
# Insert annualized capital costs |
|
668
|
|
|
# lines in EUR/km/MW/a |
|
669
|
|
|
# transfermer, inverter, battery in EUR/MW/a |
|
670
|
|
|
parameters["capital_cost"] = {} |
|
671
|
|
|
|
|
672
|
|
|
for comp in parameters["overnight_cost"].keys(): |
|
673
|
|
|
parameters["capital_cost"][comp] = annualize_capital_costs( |
|
674
|
|
|
parameters["overnight_cost"][comp], |
|
675
|
|
|
parameters["lifetime"][comp], |
|
676
|
|
|
global_settings("status2019")["interest_rate"], |
|
677
|
|
|
) |
|
678
|
|
|
|
|
679
|
|
|
parameters["capital_cost"]["battery"] = ( |
|
680
|
|
|
parameters["capital_cost"]["battery inverter"] |
|
681
|
|
|
+ parameters["efficiency"]["battery"]["max_hours"] |
|
682
|
|
|
* parameters["capital_cost"]["battery storage"] |
|
683
|
|
|
) |
|
684
|
|
|
|
|
685
|
|
|
parameters["marginal_cost"] = { |
|
686
|
|
|
"oil": global_settings(scenario)["fuel_costs"]["oil"] |
|
687
|
|
|
/ read_costs(costs, "oil", "efficiency") |
|
688
|
|
|
+ read_costs(costs, "oil", "VOM") |
|
689
|
|
|
+ global_settings(scenario)["co2_costs"] |
|
690
|
|
|
* global_settings(scenario)["co2_emissions"]["oil"] |
|
691
|
|
|
/ read_costs(costs, "oil", "efficiency"), |
|
692
|
|
|
"other_non_renewable": global_settings(scenario)["fuel_costs"][ |
|
693
|
|
|
"gas" |
|
694
|
|
|
] / read_costs(costs, "OCGT", "efficiency") |
|
695
|
|
|
+ global_settings(scenario)["co2_costs"] |
|
696
|
|
|
* global_settings(scenario)["co2_emissions"][ |
|
697
|
|
|
"other_non_renewable" |
|
698
|
|
|
] / read_costs(costs, "OCGT", "efficiency"), |
|
699
|
|
|
"lignite": global_settings(scenario)["fuel_costs"]["lignite"] |
|
700
|
|
|
/ read_costs(costs, "lignite", "efficiency") |
|
701
|
|
|
+ read_costs(costs, "lignite", "VOM") |
|
702
|
|
|
+ global_settings(scenario)["co2_costs"] |
|
703
|
|
|
* global_settings(scenario)["co2_emissions"]["lignite"] |
|
704
|
|
|
/ read_costs(costs, "lignite", "efficiency"), |
|
705
|
|
|
"coal": global_settings(scenario)["fuel_costs"]["coal"] |
|
706
|
|
|
/ read_costs(costs, "coal", "efficiency") |
|
707
|
|
|
+ read_costs(costs, "coal", "VOM") |
|
708
|
|
|
+ global_settings(scenario)["co2_costs"] |
|
709
|
|
|
* global_settings(scenario)["co2_emissions"]["coal"] |
|
710
|
|
|
/ read_costs(costs, "coal", "efficiency"), |
|
711
|
|
|
"OCGT": global_settings(scenario)["fuel_costs"]["gas"] |
|
712
|
|
|
/ read_costs(costs, "OCGT", "efficiency") |
|
713
|
|
|
+ read_costs(costs, "OCGT", "VOM") |
|
714
|
|
|
+ global_settings(scenario)["co2_costs"] |
|
715
|
|
|
* global_settings(scenario)["co2_emissions"]["gas"] |
|
716
|
|
|
/ read_costs(costs, "OCGT", "efficiency"), |
|
717
|
|
|
"nuclear": global_settings(scenario)["fuel_costs"]["nuclear"] |
|
718
|
|
|
/ read_costs(costs, "nuclear", "efficiency") |
|
719
|
|
|
+ read_costs(costs, "nuclear", "VOM"), |
|
720
|
|
|
"biomass": global_settings(scenario)["fuel_costs"]["biomass"] |
|
721
|
|
|
/ read_costs(costs, "biomass CHP", "efficiency") |
|
722
|
|
|
+ read_costs(costs, "biomass CHP", "VOM"), |
|
723
|
|
|
"wind_offshore": read_costs(costs, "offwind", "VOM"), |
|
724
|
|
|
"wind_onshore": read_costs(costs, "onwind", "VOM"), |
|
725
|
|
|
"solar": read_costs(costs, "solar", "VOM"), |
|
726
|
|
|
# According to https://www.aemo.com.au/-/media/Files/Electricity/NEM/Planning_and_Forecasting/Inputs-Assumptions-Methodologies/2019/Report-Pumped-Hydro-Cost-Modelling.pdf |
|
727
|
|
|
# for hydro generation all operations and maintenance costs might |
|
728
|
|
|
# be categorized as fixed rather than variable. |
|
729
|
|
|
"run_of_river": 0, |
|
730
|
|
|
"reservoir": 0, |
|
731
|
|
|
} |
|
732
|
|
|
|
|
733
|
|
|
else: |
|
734
|
|
|
print(f"Scenario name {scenario} is not valid.") |
|
735
|
|
|
|
|
736
|
|
|
return parameters |
|
737
|
|
|
|
|
738
|
|
|
|
|
739
|
|
|
def gas(scenario): |
|
740
|
|
|
"""Returns paramaters of the gas sector for the selected scenario. |
|
741
|
|
|
|
|
742
|
|
|
Parameters |
|
743
|
|
|
---------- |
|
744
|
|
|
scenario : str |
|
745
|
|
|
Name of the scenario. |
|
746
|
|
|
|
|
747
|
|
|
Returns |
|
748
|
|
|
------- |
|
749
|
|
|
parameters : dict |
|
750
|
|
|
List of parameters of gas sector |
|
751
|
|
|
|
|
752
|
|
|
""" |
|
753
|
|
|
|
|
754
|
|
|
if scenario == "eGon2035": |
|
755
|
|
|
costs = read_csv(2035) |
|
756
|
|
|
|
|
757
|
|
|
parameters = { |
|
758
|
|
|
"main_gas_carrier": "CH4", |
|
759
|
|
|
"H2_feedin_volumetric_fraction": 0.15, |
|
760
|
|
|
} |
|
761
|
|
|
|
|
762
|
|
|
# Insert effciencies in p.u. |
|
763
|
|
|
parameters["efficiency"] = { |
|
764
|
|
|
"power_to_H2": 0.6805, #source: project internal assumption Fraunhofer ISE |
|
765
|
|
|
"H2_to_power": read_costs(costs, "fuel cell", "efficiency"), |
|
766
|
|
|
"CH4_to_H2": read_costs(costs, "SMR", "efficiency"), |
|
767
|
|
|
"H2_feedin": 1, |
|
768
|
|
|
"H2_to_CH4": read_costs(costs, "methanation", "efficiency"), |
|
769
|
|
|
"OCGT": read_costs(costs, "OCGT", "efficiency"), |
|
770
|
|
|
"power_to_Heat": 0.2, #overall efficiency (20% electrical Input converted into waste-heat); source: project internal assumption Fraunhofer ISE |
|
771
|
|
|
"power_to_O2": 0.04, #O2-transfer efficiency; source: Sayed Sadat, Modeling Regional Utilization of the electrolysers Co-Products Oxygen and Heat in Germany, 2024 |
|
772
|
|
|
} |
|
773
|
|
|
|
|
774
|
|
|
# Insert overnight investment costs |
|
775
|
|
|
parameters["overnight_cost"] = { |
|
776
|
|
|
"power_to_H2_system": 452_000, #[EUR/MW] source: project internal assumption Fraunhofer ISE |
|
777
|
|
|
"power_to_H2_stack": 0.21 * 452_000, #[EUR/MW] source: project internal assumption Fraunhofer ISE |
|
778
|
|
|
"power_to_H2_OPEX": 0.03 * 452_000, #[EUR/MW/a] 3% of CAPEX, source: project internal assumption Fraunhofer ISE |
|
779
|
|
|
"H2_to_power": read_costs(costs, "fuel cell", "investment"), |
|
780
|
|
|
"CH4_to_H2": read_costs(costs, "SMR", "investment"), |
|
781
|
|
|
"H2_to_CH4": read_costs(costs, "methanation", "investment"), |
|
782
|
|
|
"H2_feedin": 0, |
|
783
|
|
|
"H2_underground": read_costs( |
|
784
|
|
|
costs, "hydrogen storage underground", "investment" |
|
785
|
|
|
), |
|
786
|
|
|
"H2_overground": read_costs( |
|
787
|
|
|
costs, "hydrogen storage tank incl. compressor", "investment" |
|
788
|
|
|
), |
|
789
|
|
|
"H2_pipeline": read_costs(costs, "H2 (g) pipeline", "investment"), # [EUR/MW/km] |
|
790
|
|
|
"Heat_exchanger": 25_000, # [EUR/MW_th] cost assumption for one additional heat_exchanger; source: project internal cost assumption by Fraunhofer ISE |
|
791
|
|
|
"Heat_pipeline": 400_000, # [EUR/MW/km]; average value for DN100-pipeline; source: L. Zimmermann, MODELLIERUNG DER ABWÄRMENUTZUNG VON ELEKTROLYSEUREN IN DEUTSCHLAND FÜR EINE TECHNO - ÖKONOMISCHE OPTIMIERUNG EINES SEKTOR - GEKOPPELTEN ENERGIESYSTEM, 2024 |
|
792
|
|
|
"O2_components": 5000, # [EUR] ; source: Sayed Sadat, Modeling Regional Utilization of the electrolysers Co-Products Oxygen and Heat in Germany, 2024 |
|
793
|
|
|
} |
|
794
|
|
|
|
|
795
|
|
|
#overnight_costs for O2_pipeinecosts related to pipeline_diameter |
|
796
|
|
|
parameters["O2_pipeline_costs"] = { |
|
797
|
|
|
0.5: 500_000, # EUR/km |
|
798
|
|
|
0.4: 450_000, # EUR/km |
|
799
|
|
|
0.3: 400_000, # EUR/km |
|
800
|
|
|
0.2: 350_000, # EUR/km |
|
801
|
|
|
0.0: 300_000, # EUR/km (costs for any other pipeline diameter) |
|
802
|
|
|
} |
|
803
|
|
|
|
|
804
|
|
|
# Insert lifetime |
|
805
|
|
|
parameters["lifetime"] = { |
|
806
|
|
|
"power_to_H2_system": 25, # source: project internal assumption Fraunhofer ISE |
|
807
|
|
|
"power_to_H2_stack": 15, #85000 hours ~ 15 years; source: project internal assumption Fraunhofer ISE |
|
808
|
|
|
"power_to_H2_OPEX": 1, #given as OPEX/year |
|
809
|
|
|
"H2_to_power": read_costs(costs, "fuel cell", "lifetime"), |
|
810
|
|
|
"CH4_to_H2": read_costs(costs, "SMR", "lifetime"), |
|
811
|
|
|
"H2_to_CH4": read_costs(costs, "methanation", "lifetime"), |
|
812
|
|
|
"H2_feedin": read_costs(costs, "CH4 (g) pipeline", "lifetime"), |
|
813
|
|
|
"H2_underground": read_costs( |
|
814
|
|
|
costs, "hydrogen storage underground", "lifetime" |
|
815
|
|
|
), |
|
816
|
|
|
"H2_overground": read_costs( |
|
817
|
|
|
costs, "hydrogen storage tank incl. compressor", "lifetime" |
|
818
|
|
|
), |
|
819
|
|
|
"H2_pipeline": read_costs(costs, "H2 (g) pipeline", "lifetime"), |
|
820
|
|
|
"Heat_exchanger": 20, # assumption based on lifetime heat_exchanger; source: E. van der Roest, R. Bol, T. Fens und A. van Wijk, „Utilisation of waste heat from PEM electrolysers - Unlocking local optimisation, 2023 |
|
821
|
|
|
"Heat_pipeline": 20, |
|
822
|
|
|
"O2_components": 25, # source: Sayed Sadat, Modeling Regional Utilization of the electrolysers Co-Products Oxygen and Heat in Germany, 2024 |
|
823
|
|
|
} |
|
824
|
|
|
|
|
825
|
|
|
# Insert annualized capital costs |
|
826
|
|
|
parameters["capital_cost"] = {} |
|
827
|
|
|
parameters["O2_capital_cost"]= {} |
|
828
|
|
|
|
|
829
|
|
|
for comp in parameters["overnight_cost"].keys(): |
|
830
|
|
|
parameters["capital_cost"][comp] = annualize_capital_costs( |
|
831
|
|
|
parameters["overnight_cost"][comp], |
|
832
|
|
|
parameters["lifetime"][comp], |
|
833
|
|
|
global_settings("eGon2035")["interest_rate"], |
|
834
|
|
|
) |
|
835
|
|
|
|
|
836
|
|
|
for diameter in parameters["O2_pipeline_costs"].keys(): |
|
837
|
|
|
parameters["O2_capital_cost"][diameter] = annualize_capital_costs( |
|
838
|
|
|
parameters["O2_pipeline_costs"][diameter], |
|
839
|
|
|
parameters["lifetime"]["O2_components"], |
|
840
|
|
|
global_settings("eGon2035")["interest_rate"], |
|
841
|
|
|
) |
|
842
|
|
|
|
|
843
|
|
|
parameters["marginal_cost"] = { |
|
844
|
|
|
"CH4": global_settings(scenario)["fuel_costs"]["gas"] |
|
845
|
|
|
+ global_settings(scenario)["co2_costs"] |
|
846
|
|
|
* global_settings(scenario)["co2_emissions"]["gas"], |
|
847
|
|
|
"OCGT": read_costs(costs, "OCGT", "VOM"), |
|
848
|
|
|
"biogas": global_settings(scenario)["fuel_costs"]["gas"], |
|
849
|
|
|
"chp_gas": read_costs(costs, "central gas CHP", "VOM"), |
|
850
|
|
|
} |
|
851
|
|
|
|
|
852
|
|
|
# Insert max gas production (generator) over the year |
|
853
|
|
|
parameters["max_gas_generation_overtheyear"] = { |
|
854
|
|
|
"CH4": 36000000, # [MWh] Netzentwicklungsplan Gas 2020–2030 |
|
855
|
|
|
"biogas": 10000000, # [MWh] Netzentwicklungsplan Gas 2020–2030 |
|
856
|
|
|
} |
|
857
|
|
|
|
|
858
|
|
|
elif scenario == "eGon100RE": |
|
859
|
|
|
costs = read_csv(2050) |
|
860
|
|
|
interest_rate = 0.07 # [p.u.] |
|
861
|
|
|
|
|
862
|
|
|
parameters = { |
|
863
|
|
|
"main_gas_carrier": "H2", |
|
864
|
|
|
"retrofitted_CH4pipeline-to-H2pipeline_share": 0.23, |
|
865
|
|
|
# p-e-s result, this value is overwritten if p-e-s is run |
|
866
|
|
|
} |
|
867
|
|
|
# Insert effciencies in p.u. |
|
868
|
|
|
parameters["efficiency"] = { |
|
869
|
|
|
"power_to_H2": 0.709, |
|
870
|
|
|
"H2_to_power": read_costs(costs, "fuel cell", "efficiency"), |
|
871
|
|
|
"CH4_to_H2": read_costs(costs, "SMR", "efficiency"), |
|
872
|
|
|
"H2_to_CH4": read_costs(costs, "methanation", "efficiency"), |
|
873
|
|
|
"OCGT": read_costs(costs, "OCGT", "efficiency"), |
|
874
|
|
|
"power_to_Heat": 0.2, # source: project internal assumption Fraunhofer ISE |
|
875
|
|
|
"power_to_O2": 0.015, # source: Sayed Sadat, Modeling Regional Utilization of the electrolysers Co-Products Oxygen and Heat in Germany, 2024 |
|
876
|
|
|
} |
|
877
|
|
|
|
|
878
|
|
|
# Insert FOM in % |
|
879
|
|
|
parameters["FOM"] = { |
|
880
|
|
|
"H2_underground": read_costs( |
|
881
|
|
|
costs, "hydrogen storage underground", "FOM" |
|
882
|
|
|
), |
|
883
|
|
|
"H2_overground": read_costs( |
|
884
|
|
|
costs, "hydrogen storage tank incl. compressor", "FOM" |
|
885
|
|
|
), |
|
886
|
|
|
"power_to_H2_system": 3, #3% of CAPEX, source: project internal assumption Fraunhofer ISE |
|
887
|
|
|
"power_to_H2_stack": 3, #3% of CAPEX source: project internal assumption Fraunhofer ISE |
|
888
|
|
|
"H2_to_power": read_costs(costs, "fuel cell", "FOM"), |
|
889
|
|
|
"CH4_to_H2": read_costs(costs, "SMR", "FOM"), |
|
890
|
|
|
"H2_to_CH4": read_costs(costs, "methanation", "FOM"), |
|
891
|
|
|
"H2_pipeline": 3, # 3% of CAPEX |
|
892
|
|
|
"Heat_exchanger": 3, # 3% of CAPEX |
|
893
|
|
|
"Heat_pipeline": 3, # 3% of CAPEX |
|
894
|
|
|
"O2_components": 3, # 3% of CAPEX |
|
895
|
|
|
"H2_pipeline_retrofit": read_costs( |
|
896
|
|
|
costs, "H2 (g) pipeline repurposed", "FOM" |
|
897
|
|
|
), |
|
898
|
|
|
} |
|
899
|
|
|
|
|
900
|
|
|
# Insert overnight investment costs |
|
901
|
|
|
parameters["overnight_cost"] = { |
|
902
|
|
|
"power_to_H2_system": 357_000, #[EUR/MW] source: project internal assumption Fraunhofer ISE |
|
903
|
|
|
"power_to_H2_stack": 0.21 * 357_000, #[EUR/MW] source: project internal assumption Fraunhofer ISE |
|
904
|
|
|
"H2_to_power": read_costs(costs, "fuel cell", "investment"), |
|
905
|
|
|
"CH4_to_H2": read_costs(costs, "SMR", "investment"), |
|
906
|
|
|
"H2_to_CH4": read_costs(costs, "methanation", "investment"), |
|
907
|
|
|
"H2_underground": read_costs( |
|
908
|
|
|
costs, "hydrogen storage underground", "investment" |
|
909
|
|
|
), |
|
910
|
|
|
"H2_overground": read_costs( |
|
911
|
|
|
costs, "hydrogen storage tank incl. compressor", "investment" |
|
912
|
|
|
), |
|
913
|
|
|
"H2_pipeline": read_costs(costs, "H2 (g) pipeline", "investment"), # [EUR/MW/km] |
|
914
|
|
|
"H2_pipeline_retrofit": read_costs( |
|
915
|
|
|
costs, "H2 (g) pipeline repurposed", "FOM" |
|
916
|
|
|
), |
|
917
|
|
|
"Heat_exchanger": 25_000, # [EUR/MW_th] cost assumption for one additional heat_exchanger; source: project internal cost assumption by Fraunhofer ISE |
|
918
|
|
|
"Heat_pipeline": 400_000, # [EUR/MW/km]; average value for DN100-pipeline; source: L. Zimmermann, MODELLIERUNG DER ABWÄRMENUTZUNG VON ELEKTROLYSEUREN IN DEUTSCHLAND FÜR EINE TECHNO - ÖKONOMISCHE OPTIMIERUNG EINES SEKTOR - GEKOPPELTEN ENERGIESYSTEM, 2024 |
|
919
|
|
|
"O2_components": 5000, # [EUR] ; source toDO: ask sayed |
|
920
|
|
|
} |
|
921
|
|
|
|
|
922
|
|
|
#overnight_costs for O2_pipeinecosts related to pipeline_diameter |
|
923
|
|
|
parameters["O2_pipeline_costs"] = { |
|
924
|
|
|
0.5: 500_000, # EUR/km |
|
925
|
|
|
0.4: 450_000, # EUR/km |
|
926
|
|
|
0.3: 400_000, # EUR/km |
|
927
|
|
|
0.2: 350_000, # EUR/km |
|
928
|
|
|
0: 300_000, # EUR/km (costs for any other pipeline diameter) |
|
929
|
|
|
} |
|
930
|
|
|
|
|
931
|
|
|
# Insert lifetime |
|
932
|
|
|
parameters["lifetime"] = { |
|
933
|
|
|
"power_to_H2_system": 30, # source: project internal assumption Fraunhofer ISE |
|
934
|
|
|
"power_to_H2_stack": 20, #110_000 hours ~ 20 years; source: project internal assumption Fraunhofer ISE |
|
935
|
|
|
"H2_to_power": read_costs(costs, "fuel cell", "lifetime"), |
|
936
|
|
|
"CH4_to_H2": read_costs(costs, "SMR", "lifetime"), |
|
937
|
|
|
"H2_to_CH4": read_costs(costs, "methanation", "lifetime"), |
|
938
|
|
|
"H2_feedin": read_costs(costs, "CH4 (g) pipeline", "lifetime"), |
|
939
|
|
|
"H2_underground": read_costs( |
|
940
|
|
|
costs, "hydrogen storage underground", "lifetime" |
|
941
|
|
|
), |
|
942
|
|
|
"H2_overground": read_costs( |
|
943
|
|
|
costs, "hydrogen storage tank incl. compressor", "lifetime" |
|
944
|
|
|
), |
|
945
|
|
|
"H2_pipeline": read_costs(costs, "H2 (g) pipeline", "lifetime"), |
|
946
|
|
|
"H2_pipeline_retrofit": read_costs( |
|
947
|
|
|
costs, "H2 (g) pipeline repurposed", "lifetime" |
|
948
|
|
|
), |
|
949
|
|
|
"Heat_exchanger": 20, # assumption based on lifetime heat_exchanger; source: E. van der Roest, R. Bol, T. Fens und A. van Wijk, „Utilisation of waste heat from PEM electrolysers - Unlocking local optimisation, 2023 |
|
950
|
|
|
"Heat_pipeline": 20, |
|
951
|
|
|
"O2_components": 25, # source toDO: ask sayed |
|
952
|
|
|
} |
|
953
|
|
|
|
|
954
|
|
|
# Insert costs |
|
955
|
|
|
parameters["capital_cost"] = {} |
|
956
|
|
|
parameters["O2_capital_cost"] = {} |
|
957
|
|
|
|
|
958
|
|
|
for comp in parameters["overnight_cost"].keys(): |
|
959
|
|
|
parameters["capital_cost"][comp] = annualize_capital_costs( |
|
960
|
|
|
parameters["overnight_cost"][comp], |
|
961
|
|
|
parameters["lifetime"][comp], |
|
962
|
|
|
interest_rate, |
|
963
|
|
|
) + parameters["overnight_cost"][comp] * ( |
|
964
|
|
|
parameters["FOM"][comp] / 100 |
|
965
|
|
|
) |
|
966
|
|
|
|
|
967
|
|
|
for comp in ["H2_to_power", "H2_to_CH4"]: |
|
968
|
|
|
parameters["capital_cost"][comp] = ( |
|
969
|
|
|
annualize_capital_costs( |
|
970
|
|
|
parameters["overnight_cost"][comp], |
|
971
|
|
|
parameters["lifetime"][comp], |
|
972
|
|
|
interest_rate, |
|
973
|
|
|
) |
|
974
|
|
|
+ parameters["overnight_cost"][comp] |
|
975
|
|
|
* (parameters["FOM"][comp] / 100) |
|
976
|
|
|
) * parameters["efficiency"][comp] |
|
977
|
|
|
|
|
978
|
|
|
for diameter in parameters["O2_pipeline_costs"].keys(): |
|
979
|
|
|
parameters["O2_capital_cost"][diameter] = annualize_capital_costs( |
|
980
|
|
|
parameters["O2_pipeline_costs"][diameter], |
|
981
|
|
|
parameters["lifetime"]["O2_components"], |
|
982
|
|
|
interest_rate, |
|
983
|
|
|
) |
|
984
|
|
|
|
|
985
|
|
|
parameters["marginal_cost"] = { |
|
986
|
|
|
"OCGT": read_costs(costs, "OCGT", "VOM"), |
|
987
|
|
|
"biogas": read_costs(costs, "biogas", "fuel"), |
|
988
|
|
|
"chp_gas": read_costs(costs, "central gas CHP", "VOM"), |
|
989
|
|
|
} |
|
990
|
|
|
|
|
991
|
|
|
elif scenario == "eGon2021": |
|
992
|
|
|
parameters = {} |
|
993
|
|
|
|
|
994
|
|
|
elif scenario == "status2019": |
|
995
|
|
|
costs = read_csv(2020) |
|
996
|
|
|
parameters = { |
|
997
|
|
|
"main_gas_carrier": "CH4", |
|
998
|
|
|
} |
|
999
|
|
|
|
|
1000
|
|
|
parameters["marginal_cost"] = { |
|
1001
|
|
|
"CH4": global_settings(scenario)["fuel_costs"]["gas"] |
|
1002
|
|
|
+ global_settings(scenario)["co2_costs"] |
|
1003
|
|
|
* global_settings(scenario)["co2_emissions"]["gas"], |
|
1004
|
|
|
"OCGT": read_costs(costs, "OCGT", "VOM"), |
|
1005
|
|
|
"biogas": global_settings(scenario)["fuel_costs"]["gas"], |
|
1006
|
|
|
"chp_gas": read_costs(costs, "central gas CHP", "VOM"), |
|
1007
|
|
|
} |
|
1008
|
|
|
# Insert effciencies in p.u. |
|
1009
|
|
|
parameters["efficiency"] = { |
|
1010
|
|
|
"OCGT": read_costs(costs, "OCGT", "efficiency"), |
|
1011
|
|
|
} |
|
1012
|
|
|
|
|
1013
|
|
|
else: |
|
1014
|
|
|
print(f"Scenario name {scenario} is not valid.") |
|
1015
|
|
|
|
|
1016
|
|
|
return parameters |
|
1017
|
|
|
|
|
1018
|
|
|
|
|
1019
|
|
|
def mobility(scenario): |
|
1020
|
|
|
"""Returns parameters of the mobility sector for the selected scenario. |
|
1021
|
|
|
|
|
1022
|
|
|
Parameters |
|
1023
|
|
|
---------- |
|
1024
|
|
|
scenario : str |
|
1025
|
|
|
Name of the scenario. |
|
1026
|
|
|
|
|
1027
|
|
|
Returns |
|
1028
|
|
|
------- |
|
1029
|
|
|
parameters : dict |
|
1030
|
|
|
List of parameters of mobility sector |
|
1031
|
|
|
|
|
1032
|
|
|
Notes |
|
1033
|
|
|
----- |
|
1034
|
|
|
For a detailed description of the parameters see module |
|
1035
|
|
|
:mod:`egon.data.datasets.emobility.motorized_individual_travel`. |
|
1036
|
|
|
""" |
|
1037
|
|
|
|
|
1038
|
|
|
if scenario == "eGon2035": |
|
1039
|
|
|
parameters = { |
|
1040
|
|
|
"motorized_individual_travel": { |
|
1041
|
|
|
"NEP C 2035": { |
|
1042
|
|
|
"ev_count": 15100000, |
|
1043
|
|
|
"bev_mini_share": 0.1589, |
|
1044
|
|
|
"bev_medium_share": 0.3533, |
|
1045
|
|
|
"bev_luxury_share": 0.1053, |
|
1046
|
|
|
"phev_mini_share": 0.0984, |
|
1047
|
|
|
"phev_medium_share": 0.2189, |
|
1048
|
|
|
"phev_luxury_share": 0.0652, |
|
1049
|
|
|
"model_parameters": {}, |
|
1050
|
|
|
} |
|
1051
|
|
|
} |
|
1052
|
|
|
} |
|
1053
|
|
|
|
|
1054
|
|
|
elif scenario == "eGon100RE": |
|
1055
|
|
|
# eGon100RE has 3 Scenario variations |
|
1056
|
|
|
# * allocation will always be done for all scenarios |
|
1057
|
|
|
# * model data will be written to tables `egon_etrago_*` only |
|
1058
|
|
|
# for the variation as speciefied in `datasets.yml` |
|
1059
|
|
|
parameters = { |
|
1060
|
|
|
"motorized_individual_travel": { |
|
1061
|
|
|
"Reference 2050": { |
|
1062
|
|
|
"ev_count": 25065000, |
|
1063
|
|
|
"bev_mini_share": 0.1589, |
|
1064
|
|
|
"bev_medium_share": 0.3533, |
|
1065
|
|
|
"bev_luxury_share": 0.1053, |
|
1066
|
|
|
"phev_mini_share": 0.0984, |
|
1067
|
|
|
"phev_medium_share": 0.2189, |
|
1068
|
|
|
"phev_luxury_share": 0.0652, |
|
1069
|
|
|
"model_parameters": {}, |
|
1070
|
|
|
}, |
|
1071
|
|
|
"Mobility Transition 2050": { |
|
1072
|
|
|
"ev_count": 37745000, |
|
1073
|
|
|
"bev_mini_share": 0.1589, |
|
1074
|
|
|
"bev_medium_share": 0.3533, |
|
1075
|
|
|
"bev_luxury_share": 0.1053, |
|
1076
|
|
|
"phev_mini_share": 0.0984, |
|
1077
|
|
|
"phev_medium_share": 0.2189, |
|
1078
|
|
|
"phev_luxury_share": 0.0652, |
|
1079
|
|
|
"model_parameters": {}, |
|
1080
|
|
|
}, |
|
1081
|
|
|
"Electrification 2050": { |
|
1082
|
|
|
"ev_count": 47700000, |
|
1083
|
|
|
"bev_mini_share": 0.1589, |
|
1084
|
|
|
"bev_medium_share": 0.3533, |
|
1085
|
|
|
"bev_luxury_share": 0.1053, |
|
1086
|
|
|
"phev_mini_share": 0.0984, |
|
1087
|
|
|
"phev_medium_share": 0.2189, |
|
1088
|
|
|
"phev_luxury_share": 0.0652, |
|
1089
|
|
|
"model_parameters": {}, |
|
1090
|
|
|
}, |
|
1091
|
|
|
} |
|
1092
|
|
|
} |
|
1093
|
|
|
|
|
1094
|
|
|
elif scenario == "eGon2021": |
|
1095
|
|
|
parameters = {} |
|
1096
|
|
|
|
|
1097
|
|
|
elif scenario == "status2019": |
|
1098
|
|
|
parameters = { |
|
1099
|
|
|
"motorized_individual_travel": { |
|
1100
|
|
|
"status2019": { |
|
1101
|
|
|
"ev_count": 200000, |
|
1102
|
|
|
"bev_mini_share": 0.1589, |
|
1103
|
|
|
"bev_medium_share": 0.3533, |
|
1104
|
|
|
"bev_luxury_share": 0.1053, |
|
1105
|
|
|
"phev_mini_share": 0.0984, |
|
1106
|
|
|
"phev_medium_share": 0.2189, |
|
1107
|
|
|
"phev_luxury_share": 0.0652, |
|
1108
|
|
|
"model_parameters": {}, |
|
1109
|
|
|
} |
|
1110
|
|
|
} |
|
1111
|
|
|
} |
|
1112
|
|
|
|
|
1113
|
|
|
elif scenario == "status2023": |
|
1114
|
|
|
parameters = { |
|
1115
|
|
|
"motorized_individual_travel": { |
|
1116
|
|
|
"status2023": { |
|
1117
|
|
|
"ev_count": 2577664, |
|
1118
|
|
|
"bev_mini_share": 0.1535, |
|
1119
|
|
|
"bev_medium_share": 0.3412, |
|
1120
|
|
|
"bev_luxury_share": 0.1017, |
|
1121
|
|
|
"phev_mini_share": 0.1038, |
|
1122
|
|
|
"phev_medium_share": 0.2310, |
|
1123
|
|
|
"phev_luxury_share": 0.0688, |
|
1124
|
|
|
"model_parameters": {}, |
|
1125
|
|
|
} |
|
1126
|
|
|
} |
|
1127
|
|
|
} |
|
1128
|
|
|
|
|
1129
|
|
|
else: |
|
1130
|
|
|
print(f"Scenario name {scenario} is not valid.") |
|
1131
|
|
|
parameters = dict() |
|
1132
|
|
|
|
|
1133
|
|
|
return parameters |
|
1134
|
|
|
|
|
1135
|
|
|
|
|
1136
|
|
|
def heat(scenario): |
|
1137
|
|
|
"""Returns paramaters of the heat sector for the selected scenario. |
|
1138
|
|
|
|
|
1139
|
|
|
Parameters |
|
1140
|
|
|
---------- |
|
1141
|
|
|
scenario : str |
|
1142
|
|
|
Name of the scenario. |
|
1143
|
|
|
|
|
1144
|
|
|
Returns |
|
1145
|
|
|
------- |
|
1146
|
|
|
parameters : dict |
|
1147
|
|
|
List of parameters of heat sector |
|
1148
|
|
|
|
|
1149
|
|
|
""" |
|
1150
|
|
|
|
|
1151
|
|
|
if scenario == "eGon2035": |
|
1152
|
|
|
costs = read_csv(2035) |
|
1153
|
|
|
|
|
1154
|
|
|
parameters = { |
|
1155
|
|
|
"DE_demand_reduction_residential": 0.854314018923104, |
|
1156
|
|
|
"DE_demand_reduction_service": 0.498286864771128, |
|
1157
|
|
|
"DE_district_heating_share": 0.14, |
|
1158
|
|
|
} |
|
1159
|
|
|
|
|
1160
|
|
|
# Insert efficiency in p.u. |
|
1161
|
|
|
parameters["efficiency"] = { |
|
1162
|
|
|
"water_tank_charger": read_costs( |
|
1163
|
|
|
costs, "water tank charger", "efficiency" |
|
1164
|
|
|
), |
|
1165
|
|
|
"water_tank_discharger": read_costs( |
|
1166
|
|
|
costs, "water tank discharger", "efficiency" |
|
1167
|
|
|
), |
|
1168
|
|
|
"central_resistive_heater": read_costs( |
|
1169
|
|
|
costs, "central resistive heater", "efficiency" |
|
1170
|
|
|
), |
|
1171
|
|
|
"central_gas_boiler": read_costs( |
|
1172
|
|
|
costs, "central gas boiler", "efficiency" |
|
1173
|
|
|
), |
|
1174
|
|
|
"rural_resistive_heater": read_costs( |
|
1175
|
|
|
costs, "decentral resistive heater", "efficiency" |
|
1176
|
|
|
), |
|
1177
|
|
|
"rural_gas_boiler": read_costs( |
|
1178
|
|
|
costs, "decentral gas boiler", "efficiency" |
|
1179
|
|
|
), |
|
1180
|
|
|
} |
|
1181
|
|
|
|
|
1182
|
|
|
# Insert overnight investment costs, in EUR/MWh |
|
1183
|
|
|
parameters["overnight_cost"] = { |
|
1184
|
|
|
"central_water_tank": read_costs( |
|
1185
|
|
|
costs, "central water tank storage", "investment" |
|
1186
|
|
|
), |
|
1187
|
|
|
"rural_water_tank": read_costs( |
|
1188
|
|
|
costs, "decentral water tank storage", "investment" |
|
1189
|
|
|
), |
|
1190
|
|
|
} |
|
1191
|
|
|
|
|
1192
|
|
|
# Insert lifetime |
|
1193
|
|
|
parameters["lifetime"] = { |
|
1194
|
|
|
"central_water_tank": read_costs( |
|
1195
|
|
|
costs, "central water tank storage", "lifetime" |
|
1196
|
|
|
), |
|
1197
|
|
|
"rural_water_tank": read_costs( |
|
1198
|
|
|
costs, "decentral water tank storage", "lifetime" |
|
1199
|
|
|
), |
|
1200
|
|
|
} |
|
1201
|
|
|
|
|
1202
|
|
|
# Insert annualized capital costs |
|
1203
|
|
|
parameters["capital_cost"] = {} |
|
1204
|
|
|
|
|
1205
|
|
|
for comp in parameters["overnight_cost"].keys(): |
|
1206
|
|
|
parameters["capital_cost"][comp] = annualize_capital_costs( |
|
1207
|
|
|
parameters["overnight_cost"][comp], |
|
1208
|
|
|
parameters["lifetime"][comp], |
|
1209
|
|
|
global_settings("eGon2035")["interest_rate"], |
|
1210
|
|
|
) |
|
1211
|
|
|
|
|
1212
|
|
|
# Insert marginal_costs in EUR/MWh |
|
1213
|
|
|
# marginal cost can include fuel, C02 and operation and maintenance costs |
|
1214
|
|
|
parameters["marginal_cost"] = { |
|
1215
|
|
|
"central_heat_pump": read_costs( |
|
1216
|
|
|
costs, "central air-sourced heat pump", "VOM" |
|
1217
|
|
|
), |
|
1218
|
|
|
"central_gas_chp": read_costs(costs, "central gas CHP", "VOM"), |
|
1219
|
|
|
"central_gas_boiler": read_costs( |
|
1220
|
|
|
costs, "central gas boiler", "VOM" |
|
1221
|
|
|
), |
|
1222
|
|
|
"central_resistive_heater": read_costs( |
|
1223
|
|
|
costs, "central resistive heater", "VOM" |
|
1224
|
|
|
), |
|
1225
|
|
|
"geo_thermal": 2.9, # Danish Energy Agency |
|
1226
|
|
|
"water_tank_charger": 0, # Danish Energy Agency |
|
1227
|
|
|
"water_tank_discharger": 0, # Danish Energy Agency |
|
1228
|
|
|
"rural_heat_pump": 0, # Danish Energy Agency, Technology Data for Individual Heating Plants |
|
1229
|
|
|
} |
|
1230
|
|
|
|
|
1231
|
|
|
elif scenario == "eGon100RE": |
|
1232
|
|
|
costs = read_csv(2050) |
|
1233
|
|
|
|
|
1234
|
|
|
parameters = { |
|
1235
|
|
|
"DE_demand_residential_MWh": 536692489.8152325 * 0.71542, |
|
1236
|
|
|
# [MWh], source: pypsa-eur run from 2024/12/23: |
|
1237
|
|
|
# total heat demand muliplied by residential share from resources/pop_weighted_heat_totals |
|
1238
|
|
|
"DE_demand_service_MWh": 536692489.8152325 * (1-0.71542), |
|
1239
|
|
|
# [MWh], source: pypsa-eur run from 2024/12/23: |
|
1240
|
|
|
# total heat demand muliplied by service share from resources/pop_weighted_heat_totals |
|
1241
|
|
|
"DE_district_heating_share": 0.42311285313808533, |
|
1242
|
|
|
# [%], source: pypsa-eur run from 2024/12/23 |
|
1243
|
|
|
} |
|
1244
|
|
|
|
|
1245
|
|
|
|
|
1246
|
|
|
parameters["marginal_cost"] = { |
|
1247
|
|
|
"central_heat_pump": read_costs( |
|
1248
|
|
|
costs, "central air-sourced heat pump", "VOM" |
|
1249
|
|
|
), |
|
1250
|
|
|
"central_gas_chp": read_costs(costs, "central gas CHP", "VOM"), |
|
1251
|
|
|
"central_gas_boiler": read_costs( |
|
1252
|
|
|
costs, "central gas boiler", "VOM" |
|
1253
|
|
|
), |
|
1254
|
|
|
"central_resistive_heater": read_costs( |
|
1255
|
|
|
costs, "central resistive heater", "VOM" |
|
1256
|
|
|
), |
|
1257
|
|
|
"geo_thermal": 2.7, # Danish Energy Agency |
|
1258
|
|
|
"water_tank_charger": 0, # Danish Energy Agency |
|
1259
|
|
|
"water_tank_discharger": 0, # Danish Energy Agency |
|
1260
|
|
|
"rural_heat_pump": 0, # Danish Energy Agency, Technology Data for Individual Heating Plants |
|
1261
|
|
|
} |
|
1262
|
|
|
|
|
1263
|
|
|
# Insert efficiency in p.u. |
|
1264
|
|
|
parameters["efficiency"] = { |
|
1265
|
|
|
"water_tank_charger": read_costs( |
|
1266
|
|
|
costs, "water tank charger", "efficiency" |
|
1267
|
|
|
), |
|
1268
|
|
|
"water_tank_discharger": read_costs( |
|
1269
|
|
|
costs, "water tank discharger", "efficiency" |
|
1270
|
|
|
), |
|
1271
|
|
|
"central_resistive_heater": read_costs( |
|
1272
|
|
|
costs, "central resistive heater", "efficiency" |
|
1273
|
|
|
), |
|
1274
|
|
|
"central_gas_boiler": read_costs( |
|
1275
|
|
|
costs, "central gas boiler", "efficiency" |
|
1276
|
|
|
), |
|
1277
|
|
|
"rural_resistive_heater": read_costs( |
|
1278
|
|
|
costs, "decentral resistive heater", "efficiency" |
|
1279
|
|
|
), |
|
1280
|
|
|
"rural_gas_boiler": read_costs( |
|
1281
|
|
|
costs, "decentral gas boiler", "efficiency" |
|
1282
|
|
|
), |
|
1283
|
|
|
} |
|
1284
|
|
|
|
|
1285
|
|
|
# Insert overnight investment costs, in EUR/MWh |
|
1286
|
|
|
parameters["overnight_cost"] = { |
|
1287
|
|
|
"central_water_tank": read_costs( |
|
1288
|
|
|
costs, "central water tank storage", "investment" |
|
1289
|
|
|
), |
|
1290
|
|
|
"rural_water_tank": read_costs( |
|
1291
|
|
|
costs, "decentral water tank storage", "investment" |
|
1292
|
|
|
), |
|
1293
|
|
|
} |
|
1294
|
|
|
|
|
1295
|
|
|
# Insert lifetime |
|
1296
|
|
|
parameters["lifetime"] = { |
|
1297
|
|
|
"central_water_tank": read_costs( |
|
1298
|
|
|
costs, "central water tank storage", "lifetime" |
|
1299
|
|
|
), |
|
1300
|
|
|
"rural_water_tank": read_costs( |
|
1301
|
|
|
costs, "decentral water tank storage", "lifetime" |
|
1302
|
|
|
), |
|
1303
|
|
|
} |
|
1304
|
|
|
|
|
1305
|
|
|
# Insert annualized capital costs |
|
1306
|
|
|
parameters["capital_cost"] = {} |
|
1307
|
|
|
|
|
1308
|
|
|
for comp in parameters["overnight_cost"].keys(): |
|
1309
|
|
|
parameters["capital_cost"][comp] = annualize_capital_costs( |
|
1310
|
|
|
parameters["overnight_cost"][comp], |
|
1311
|
|
|
parameters["lifetime"][comp], |
|
1312
|
|
|
global_settings("eGon100RE")["interest_rate"], |
|
1313
|
|
|
) |
|
1314
|
|
|
|
|
1315
|
|
|
elif scenario == "eGon2021": |
|
1316
|
|
|
parameters = {} |
|
1317
|
|
|
|
|
1318
|
|
|
elif scenario == "status2019": |
|
1319
|
|
|
parameters = { |
|
1320
|
|
|
"DE_demand_residential_TJ": 1658400 |
|
1321
|
|
|
+ 383300, # [TJ], space heating + hot water, source: AG Energiebilanzen 2019 (https://ag-energiebilanzen.de/wp-content/uploads/2020/10/ageb_20v_v1.pdf) |
|
1322
|
|
|
"DE_demand_service_TJ": 567300 |
|
1323
|
|
|
+ 71500, # [TJ], space heating + hot water, source: AG Energiebilanzen 2019 (https://ag-energiebilanzen.de/wp-content/uploads/2020/10/ageb_20v_v1.pdf) |
|
1324
|
|
|
"DE_district_heating_share": (189760 + 38248) |
|
1325
|
|
|
/ ( |
|
1326
|
|
|
1658400 + 383300 + 567300 + 71500 |
|
1327
|
|
|
), # [TJ], source: AG Energiebilanzen 2019 (https://ag-energiebilanzen.de/wp-content/uploads/2021/11/bilanz19d.xlsx) |
|
1328
|
|
|
} |
|
1329
|
|
|
|
|
1330
|
|
|
costs = read_csv(2020) |
|
1331
|
|
|
|
|
1332
|
|
|
# Insert marginal_costs in EUR/MWh |
|
1333
|
|
|
# marginal cost can include fuel, C02 and operation and maintenance costs |
|
1334
|
|
|
parameters["marginal_cost"] = { |
|
1335
|
|
|
"central_heat_pump": read_costs( |
|
1336
|
|
|
costs, "central air-sourced heat pump", "VOM" |
|
1337
|
|
|
), |
|
1338
|
|
|
"central_gas_chp": read_costs(costs, "central gas CHP", "VOM"), |
|
1339
|
|
|
"central_gas_boiler": read_costs( |
|
1340
|
|
|
costs, "central gas boiler", "VOM" |
|
1341
|
|
|
), |
|
1342
|
|
|
"central_resistive_heater": read_costs( |
|
1343
|
|
|
costs, "central resistive heater", "VOM" |
|
1344
|
|
|
), |
|
1345
|
|
|
"rural_heat_pump": 0, # Danish Energy Agency, Technology Data for Individual Heating Plants |
|
1346
|
|
|
} |
|
1347
|
|
|
|
|
1348
|
|
|
# Insert efficiency in p.u. |
|
1349
|
|
|
parameters["efficiency"] = { |
|
1350
|
|
|
"central_gas_boiler": read_costs( |
|
1351
|
|
|
costs, "central gas boiler", "efficiency" |
|
1352
|
|
|
), |
|
1353
|
|
|
} |
|
1354
|
|
|
|
|
1355
|
|
|
# elif scenario == "status2023": |
|
1356
|
|
|
# parameters = { |
|
1357
|
|
|
# # source: AG Energiebilanzen 2022 https://ag-energiebilanzen.de/wp-content/uploads/2023/01/AGEB_22p2_rev-1.pdf |
|
1358
|
|
|
# "DE_demand_residential_TJ": 1754.2 * 1e3 |
|
1359
|
|
|
# + 407.5 * 1e3, # [TJ], Endenergieverbrauch Haushalte 2.1 Raumwärme + Warmwasser |
|
1360
|
|
|
# "DE_demand_service_TJ": 668.4 * 1e3 |
|
1361
|
|
|
# + 44.3 * 1e3 , # [TJ], Endenergieverbrauch GHD 3.1 Raumwärme + Warmwasser |
|
1362
|
|
|
# "DE_district_heating_share": (189760 + 38248) |
|
1363
|
|
|
# / ( |
|
1364
|
|
|
# 1658400 + 383300 + 567300 + 71500 |
|
1365
|
|
|
# ), # [TJ], source: AG Energiebilanzen 2019 (https://ag-energiebilanzen.de/wp-content/uploads/2021/11/bilanz19d.xlsx) |
|
1366
|
|
|
# } # TODO status2023 needs update |
|
1367
|
|
|
# |
|
1368
|
|
|
# costs = read_csv(2020) |
|
1369
|
|
|
# |
|
1370
|
|
|
# # Insert marginal_costs in EUR/MWh |
|
1371
|
|
|
# # marginal cost can include fuel, C02 and operation and maintenance costs |
|
1372
|
|
|
# parameters["marginal_cost"] = { |
|
1373
|
|
|
# "central_heat_pump": read_costs( |
|
1374
|
|
|
# costs, "central air-sourced heat pump", "VOM" |
|
1375
|
|
|
# ), |
|
1376
|
|
|
# "central_gas_chp": read_costs(costs, "central gas CHP", "VOM"), |
|
1377
|
|
|
# "central_gas_boiler": read_costs( |
|
1378
|
|
|
# costs, "central gas boiler", "VOM" |
|
1379
|
|
|
# ), |
|
1380
|
|
|
# "central_resistive_heater": read_costs( |
|
1381
|
|
|
# costs, "central resistive heater", "VOM" |
|
1382
|
|
|
# ), |
|
1383
|
|
|
# "rural_heat_pump": 0, # Danish Energy Agency, Technology Data for Individual Heating Plants |
|
1384
|
|
|
# } |
|
1385
|
|
|
# |
|
1386
|
|
|
# # Insert efficiency in p.u. |
|
1387
|
|
|
# parameters["efficiency"] = { |
|
1388
|
|
|
# "central_gas_boiler": read_costs( |
|
1389
|
|
|
# costs, "central gas boiler", "efficiency" |
|
1390
|
|
|
# ), |
|
1391
|
|
|
# } |
|
1392
|
|
|
|
|
1393
|
|
|
else: |
|
1394
|
|
|
print(f"Scenario name {scenario} is not valid.") |
|
1395
|
|
|
|
|
1396
|
|
|
return parameters |
|
1397
|
|
|
|
openego /
eGon-data
