diff --git a/doc/data.csv b/doc/data.csv index dd66b491..c8cb4b1f 100644 --- a/doc/data.csv +++ b/doc/data.csv @@ -17,3 +17,10 @@ IRENA existing VRE capacities,existing_infrastructure/{solar|onwind|offwind}_cap USGS ammonia production,myb1-2017-nitro.xls,unknown,https://www.usgs.gov/centers/nmic/nitrogen-statistics-and-information hydrogen salt cavern potentials,hydrogen_salt_cavern_potentials.csv,CC BY 4.0,https://doi.org/10.1016/j.ijhydene.2019.12.161 hotmaps industrial site database,Industrial_Database.csv,CC BY 4.0,https://gitlab.com/hotmaps/industrial_sites/industrial_sites_Industrial_Database +Hotmaps building stock data,data_building_stock.csv,CC BY 4.0,https://gitlab.com/hotmaps/building-stock +U-values Poland,u_values_poland.csv,unknown,https://data.europa.eu/euodp/de/data/dataset/building-stock-observatory +Floor area missing in hotmaps building stock data,floor_area_missing.csv,unknown,https://data.europa.eu/euodp/de/data/dataset/building-stock-observatory +Comparative level investment,comparative_level_investment.csv,Eurostat,https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Comparative_price_levels_for_investment +Electricity taxes,electricity_taxes_eu.csv,Eurostat,https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nrg_pc_204&lang=en +Average surface components,average_surface_components.csv,unknown,http://webtool.building-typology.eu/#bm +Retrofitting thermal envelope costs for Germany,retro_cost_germany.csv,unkown,https://www.iwu.de/forschung/handlungslogiken/kosten-energierelevanter-bau-und-anlagenteile-bei-modernisierung/ diff --git a/scripts/build_retro_cost.py b/scripts/build_retro_cost.py index a70ab0cc..af44c91a 100644 --- a/scripts/build_retro_cost.py +++ b/scripts/build_retro_cost.py @@ -23,7 +23,6 @@ Structure: import pandas as pd import matplotlib.pyplot as plt -pd.options.mode.chained_assignment = None #%% ************ FUCNTIONS *************************************************** @@ -175,9 +174,9 @@ def prepare_building_stock_data(): area = building_data[(building_data.type == 'Heated area [Mm²]') & (building_data.subsector != "Total")] area_tot = area.groupby(["country", "sector"]).sum() - area["weight"] = area.apply(lambda x: x.value / + area = pd.concat([area, area.apply(lambda x: x.value / area_tot.value.loc[(x.country, x.sector)], - axis=1) + axis=1).rename("weight")],axis=1) area = area.groupby(['country', 'sector', 'subsector', 'bage']).sum() area_tot.rename(index=country_iso_dic, inplace=True) @@ -192,9 +191,9 @@ def prepare_building_stock_data(): pop_layout["ct"] = pop_layout.index.str[:2] ct_total = pop_layout.total.groupby(pop_layout["ct"]).sum() - area_per_pop = area_tot.unstack().apply(lambda x: x / ct_total[x.index]) + area_per_pop = area_tot.unstack().reindex(index=ct_total.index).apply(lambda x: x / ct_total[x.index]) missing_area_ct = ct_total.index.difference(area_tot.index.levels[0]) - for ct in missing_area_ct: + for ct in (missing_area_ct & ct_total.index): averaged_data = pd.DataFrame( area_per_pop.value.reindex(map_for_missings[ct]).mean() * ct_total[ct], @@ -233,7 +232,7 @@ def prepare_building_stock_data(): # smallest possible today u values for windows 0.8 (passive house standard) # maybe the u values for the glass and not the whole window including frame # for those types assumed in the dataset - u_values[(u_values.type=="Windows") & (u_values.value<0.8)]["value"] = 0.8 + u_values.loc[(u_values.type=="Windows") & (u_values.value<0.8), "value"] = 0.8 # drop unnecessary columns u_values.drop(['topic', 'feature','detail', 'estimated','unit'], axis=1, inplace=True, errors="ignore") @@ -314,8 +313,12 @@ def calculate_cost_energy_curve(u_values, l_strength, l_weight, average_surface_ for l in l_strength: u_values[l] = calculate_new_u(u_values, l, l_weight) - energy_saved[l] = calculate_dE(u_values, l, average_surface_w) - costs[l] = calculate_costs(u_values, l, cost_retro, average_surface) + energy_saved = pd.concat([energy_saved, + calculate_dE(u_values, l, average_surface_w).rename(l)], + axis=1) + costs = pd.concat([costs, + calculate_costs(u_values, l, cost_retro, average_surface).rename(l)], + axis=1) # energy and costs per country, sector, subsector and year e_tot = energy_saved.groupby(['country', 'sector', 'subsector', 'bage']).sum() @@ -334,11 +337,13 @@ def calculate_cost_energy_curve(u_values, l_strength, l_weight, average_surface_ axis=1, keys=["dE", "cost"]) res.rename(index=country_iso_dic, inplace=True) - res = res.loc[countries] + res = res.reindex(index=countries, level=0) + # reset index because otherwise not considered countries still in index.levels[0] + res = res.reset_index().set_index(["country", "sector"]) # map missing countries - for ct in map_for_missings.keys(): - averaged_data = pd.DataFrame(res.loc[map_for_missings[ct], :].mean(level=1)) + for ct in pd.Index(map_for_missings.keys()) & countries: + averaged_data = res.reindex(index=map_for_missings[ct], level=0).mean(level=1) index = pd.MultiIndex.from_product([[ct], averaged_data.index.to_list()]) averaged_data.index = index if ct not in res.index.levels[0]: @@ -436,12 +441,14 @@ if __name__ == "__main__": # for missing weighting of surfaces of building types assume MultiFamily houses u_values["assumed_subsector"] = u_values.subsector - u_values.assumed_subsector[ - ~u_values.subsector.isin(average_surface.index)] = 'Multifamily houses' + u_values.loc[~u_values.subsector.isin(average_surface.index), + "assumed_subsector"] = 'Multifamily houses' dE_and_cost = calculate_cost_energy_curve(u_values, l_strength, l_weight, average_surface_w, average_surface, area, country_iso_dic, countries) + # reset index because otherwise not considered countries still in index.levels[0] + dE_and_cost = dE_and_cost.reset_index().set_index(["country", "sector"]) # weights costs after construction index if construction_index: diff --git a/scripts/prepare_sector_network.py b/scripts/prepare_sector_network.py index 9e3c8872..09d515da 100644 --- a/scripts/prepare_sector_network.py +++ b/scripts/prepare_sector_network.py @@ -1820,52 +1820,52 @@ def get_parameter(item): return item - +#%% if __name__ == "__main__": # Detect running outside of snakemake and mock snakemake for testing if 'snakemake' not in globals(): from vresutils.snakemake import MockSnakemake snakemake = MockSnakemake( wildcards=dict(network='elec', simpl='', clusters='37', lv='1.0', - opts='', planning_horizons='2020', - sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1'), - input=dict(network='../pypsa-eur/networks/{network}_s{simpl}_{clusters}_ec_lv{lv}_{opts}.nc', - energy_totals_name='resources/energy_totals.csv', - co2_totals_name='resources/co2_totals.csv', - transport_name='resources/transport_data.csv', - biomass_potentials='resources/biomass_potentials.csv', - biomass_transport='data/biomass/biomass_transport_costs.csv', - timezone_mappings='data/timezone_mappings.csv', - heat_profile="data/heat_load_profile_BDEW.csv", - costs="../technology-data/outputs/costs_{planning_horizons}.csv", - h2_cavern = "data/hydrogen_salt_cavern_potentials.csv", - profile_offwind_ac="../pypsa-eur/resources/profile_offwind-ac.nc", - profile_offwind_dc="../pypsa-eur/resources/profile_offwind-dc.nc", - clustermaps='../pypsa-eur/resources/clustermaps_{network}_s{simpl}_{clusters}.h5', - clustered_pop_layout="resources/pop_layout_{network}_s{simpl}_{clusters}.csv", - simplified_pop_layout="resources/pop_layout_{network}_s{simpl}.csv", - industrial_demand="resources/industrial_energy_demand_{network}_s{simpl}_{clusters}.csv", - heat_demand_urban="resources/heat_demand_urban_{network}_s{simpl}_{clusters}.nc", - heat_demand_rural="resources/heat_demand_rural_{network}_s{simpl}_{clusters}.nc", - heat_demand_total="resources/heat_demand_total_{network}_s{simpl}_{clusters}.nc", - temp_soil_total="resources/temp_soil_total_{network}_s{simpl}_{clusters}.nc", - temp_soil_rural="resources/temp_soil_rural_{network}_s{simpl}_{clusters}.nc", - temp_soil_urban="resources/temp_soil_urban_{network}_s{simpl}_{clusters}.nc", - temp_air_total="resources/temp_air_total_{network}_s{simpl}_{clusters}.nc", - temp_air_rural="resources/temp_air_rural_{network}_s{simpl}_{clusters}.nc", - temp_air_urban="resources/temp_air_urban_{network}_s{simpl}_{clusters}.nc", - cop_soil_total="resources/cop_soil_total_{network}_s{simpl}_{clusters}.nc", - cop_soil_rural="resources/cop_soil_rural_{network}_s{simpl}_{clusters}.nc", - cop_soil_urban="resources/cop_soil_urban_{network}_s{simpl}_{clusters}.nc", - cop_air_total="resources/cop_air_total_{network}_s{simpl}_{clusters}.nc", - cop_air_rural="resources/cop_air_rural_{network}_s{simpl}_{clusters}.nc", - cop_air_urban="resources/cop_air_urban_{network}_s{simpl}_{clusters}.nc", - solar_thermal_total="resources/solar_thermal_total_{network}_s{simpl}_{clusters}.nc", - solar_thermal_urban="resources/solar_thermal_urban_{network}_s{simpl}_{clusters}.nc", - traffic_data = "data/emobility/", - solar_thermal_rural="resources/solar_thermal_rural_{network}_s{simpl}_{clusters}.nc", - retro_cost_energy = "resources/retro_cost_{network}_s{simpl}_{clusters}.csv", - floor_area = "resources/floor_area_{network}_s{simpl}_{clusters}.csv" + opts='', planning_horizons='2030', co2_budget_name="go", + sector_opts='Co2L0-120H-T-H-B-I-solar3-dist1'), + input=dict( network='../pypsa-eur/networks/{network}_s{simpl}_{clusters}_ec_lv{lv}_{opts}.nc', + energy_totals_name='resources/energy_totals.csv', + co2_totals_name='resources/co2_totals.csv', + transport_name='resources/transport_data.csv', + traffic_data = "data/emobility/", + biomass_potentials='resources/biomass_potentials.csv', + timezone_mappings='data/timezone_mappings.csv', + heat_profile="data/heat_load_profile_BDEW.csv", + costs="../technology-data/outputs/costs_{planning_horizons}.csv", + h2_cavern = "data/hydrogen_salt_cavern_potentials.csv", + profile_offwind_ac="../pypsa-eur/resources/profile_offwind-ac.nc", + profile_offwind_dc="../pypsa-eur/resources/profile_offwind-dc.nc", + busmap_s="../pypsa-eur/resources/busmap_{network}_s{simpl}.csv", + busmap="../pypsa-eur/resources/busmap_{network}_s{simpl}_{clusters}.csv", + clustered_pop_layout="resources/pop_layout_{network}_s{simpl}_{clusters}.csv", + simplified_pop_layout="resources/pop_layout_{network}_s{simpl}.csv", + industrial_demand="resources/industrial_energy_demand_{network}_s{simpl}_{clusters}.csv", + heat_demand_urban="resources/heat_demand_urban_{network}_s{simpl}_{clusters}.nc", + heat_demand_rural="resources/heat_demand_rural_{network}_s{simpl}_{clusters}.nc", + heat_demand_total="resources/heat_demand_total_{network}_s{simpl}_{clusters}.nc", + temp_soil_total="resources/temp_soil_total_{network}_s{simpl}_{clusters}.nc", + temp_soil_rural="resources/temp_soil_rural_{network}_s{simpl}_{clusters}.nc", + temp_soil_urban="resources/temp_soil_urban_{network}_s{simpl}_{clusters}.nc", + temp_air_total="resources/temp_air_total_{network}_s{simpl}_{clusters}.nc", + temp_air_rural="resources/temp_air_rural_{network}_s{simpl}_{clusters}.nc", + temp_air_urban="resources/temp_air_urban_{network}_s{simpl}_{clusters}.nc", + cop_soil_total="resources/cop_soil_total_{network}_s{simpl}_{clusters}.nc", + cop_soil_rural="resources/cop_soil_rural_{network}_s{simpl}_{clusters}.nc", + cop_soil_urban="resources/cop_soil_urban_{network}_s{simpl}_{clusters}.nc", + cop_air_total="resources/cop_air_total_{network}_s{simpl}_{clusters}.nc", + cop_air_rural="resources/cop_air_rural_{network}_s{simpl}_{clusters}.nc", + cop_air_urban="resources/cop_air_urban_{network}_s{simpl}_{clusters}.nc", + solar_thermal_total="resources/solar_thermal_total_{network}_s{simpl}_{clusters}.nc", + solar_thermal_urban="resources/solar_thermal_urban_{network}_s{simpl}_{clusters}.nc", + solar_thermal_rural="resources/solar_thermal_rural_{network}_s{simpl}_{clusters}.nc", + retro_cost_energy = "resources/retro_cost_{network}_s{simpl}_{clusters}.csv", + floor_area = "resources/floor_area_{network}_s{simpl}_{clusters}.csv" ), output=['pypsa-eur-sec/results/test/prenetworks/{network}_s{simpl}_{clusters}_lv{lv}__{sector_opts}_{co2_budget_name}_{planning_horizons}.nc'] )