eliminate manual country code conversion, adjust mock_snakemake to ll wildcard

doc/data.csv

@@ -10,7 +10,6 @@ BASt emobility statistics,emobility/,unknown,http://www.bast.de/DE/Verkehrstechn
 BDEW heating profile,heat_load_profile_BDEW.csv,unknown,https://github.com/oemof/demandlib
 heating profiles for Aarhus,heat_load_profile_DK_AdamJensen.csv,unknown,Adam Jensen MA thesis at Aarhus University
 George Lavidas wind/wave costs,WindWaveWEC_GLTB.xlsx,unknown,George Lavidas
-country codes,Country_codes.csv,CC BY 4.0,Marta Victoria
 co2 budgets,co2_budget.csv,CC BY 4.0,https://arxiv.org/abs/2004.11009
 existing heating potentials,existing_infrastructure/existing_heating_raw.csv,unknown,https://ec.europa.eu/energy/studies/mapping-and-analyses-current-and-future-2020-2030-heatingcooling-fuel-deployment_en?redir=1
 IRENA existing VRE capacities,existing_infrastructure/{solar|onwind|offwind}_capcity_IRENA.csv,unknown,https://www.irena.org/Statistics/Download-Data

rules/postprocess.smk

@@ -120,7 +120,6 @@ rule plot_summary:
         energy=RESULTS + "csvs/energy.csv",
         balances=RESULTS + "csvs/supply_energy.csv",
         eurostat=input_eurostat,
-        country_codes="data/Country_codes.csv",
     output:
         costs=RESULTS + "graphs/costs.pdf",
         energy=RESULTS + "graphs/energy.pdf",

rules/solve_myopic.smk

@@ -16,7 +16,6 @@ rule add_existing_baseyear:
         cop_soil_total=RESOURCES + "cop_soil_total_elec_s{simpl}_{clusters}.nc",
         cop_air_total=RESOURCES + "cop_air_total_elec_s{simpl}_{clusters}.nc",
         existing_heating="data/existing_infrastructure/existing_heating_raw.csv",
-        country_codes="data/Country_codes.csv",
         existing_solar="data/existing_infrastructure/solar_capacity_IRENA.csv",
         existing_onwind="data/existing_infrastructure/onwind_capacity_IRENA.csv",
         existing_offwind="data/existing_infrastructure/offwind_capacity_IRENA.csv",

scripts/add_brownfield.py

@@ -131,7 +131,7 @@ if __name__ == "__main__":
             simpl="",
             clusters="37",
             opts="",
-            lv=1.0,
+            ll='v1.0',
             sector_opts="168H-T-H-B-I-solar+p3-dist1",
             planning_horizons=2030,
         )

scripts/add_existing_baseyear.py

@@ -16,9 +16,12 @@ from types import SimpleNamespace
 import numpy as np
 import pypsa
 import xarray as xr
+import country_converter as coco
 from _helpers import override_component_attrs, update_config_with_sector_opts
 from prepare_sector_network import cluster_heat_buses, define_spatial, prepare_costs
 
+cc = coco.CountryConverter()
+
 spatial = SimpleNamespace()
 
 
@@ -55,8 +58,6 @@ def add_existing_renewables(df_agg):
     power plants.
     """
 
-    cc = pd.read_csv(snakemake.input.country_codes, index_col=0)
-
     carriers = {"solar": "solar", "onwind": "onwind", "offwind": "offwind-ac"}
 
     for tech in ["solar", "onwind", "offwind"]:
@@ -64,17 +65,7 @@ def add_existing_renewables(df_agg):
 
         df = pd.read_csv(snakemake.input[f"existing_{tech}"], index_col=0).fillna(0.0)
         df.columns = df.columns.astype(int)
-
-        rename_countries = {
-            "Czechia": "Czech Republic",
-            "UK": "United Kingdom",
-            "Bosnia Herzg": "Bosnia Herzegovina",
-            "North Macedonia": "Macedonia",
-        }
-
-        df.rename(index=rename_countries, inplace=True)
-
-        df.rename(index=cc["2 letter code (ISO-3166-2)"], inplace=True)
+        df.index = cc.convert(df.index, to='iso2')
 
         # calculate yearly differences
         df.insert(loc=0, value=0.0, column="1999")
@@ -422,9 +413,7 @@ def add_heating_capacities_installed_before_baseyear(
     # convert GW to MW
     df *= 1e3
 
-    cc = pd.read_csv(snakemake.input.country_codes, index_col=0)
-
-    df.rename(index=cc["2 letter code (ISO-3166-2)"], inplace=True)
+    df.index = cc.convert(df.index, to='iso2')
 
     # coal and oil boilers are assimilated to oil boilers
     df["oil boiler"] = df["oil boiler"] + df["coal boiler"]
@@ -611,7 +600,7 @@ if __name__ == "__main__":
             "add_existing_baseyear",
             simpl="",
             clusters="45",
-            lv=1.0,
+            ll='v1.0',
             opts="",
             sector_opts="8760H-T-H-B-I-A-solar+p3-dist1",
             planning_horizons=2020,

scripts/build_retro_cost.py

@@ -1038,7 +1038,7 @@ if __name__ == "__main__":
             "build_retro_cost",
             simpl="",
             clusters=48,
-            lv=1.0,
+            ll='v1.0',
             sector_opts="Co2L0-168H-T-H-B-I-solar3-dist1",
         )
 

scripts/plot_network.py

@@ -917,7 +917,7 @@ if __name__ == "__main__":
             "plot_network",
             simpl="",
             clusters="181",
-            lv="opt",
+            ll="vopt",
             opts="",
             sector_opts="Co2L0-730H-T-H-B-I-A-solar+p3-linemaxext10",
             planning_horizons="2050",

scripts/plot_summary.py

@@ -345,7 +345,7 @@ def plot_balances():
         plt.cla()
 
 
-def historical_emissions(cts):
+def historical_emissions(countries):
     """
     Read historical emissions to add them to the carbon budget plot.
     """
@@ -380,16 +380,15 @@ def historical_emissions(cts):
     e["total woL"] = "Total (without LULUCF)"
 
     pol = ["CO2"]  # ["All greenhouse gases - (CO2 equivalent)"]
-    cts
-    if "GB" in cts:
-        cts.remove("GB")
-        cts.append("UK")
+    if "GB" in countries:
+        countries.remove("GB")
+        countries.append("UK")
 
     year = np.arange(1990, 2018).tolist()
 
     idx = pd.IndexSlice
     co2_totals = (
-        df.loc[idx[year, e.values, cts, pol], "emissions"]
+        df.loc[idx[year, e.values, countries, pol], "emissions"]
         .unstack("Year")
         .rename(index=pd.Series(e.index, e.values))
     )
@@ -457,14 +456,13 @@ def plot_carbon_budget_distribution(input_eurostat):
     ax1.set_xlim([1990, snakemake.config["scenario"]["planning_horizons"][-1] + 1])
 
     path_cb = "results/" + snakemake.params.RDIR + "/csvs/"
-    countries = pd.read_csv(snakemake.input.country_codes, index_col=1)
-    cts = countries.index.to_list()
-    e_1990 = co2_emissions_year(cts, input_eurostat, opts, year=1990)
+    countries = snakemake.confing["countries"]
+    e_1990 = co2_emissions_year(countries, input_eurostat, opts, year=1990)
     CO2_CAP = pd.read_csv(path_cb + "carbon_budget_distribution.csv", index_col=0)
 
     ax1.plot(e_1990 * CO2_CAP[o], linewidth=3, color="dodgerblue", label=None)
 
-    emissions = historical_emissions(cts)
+    emissions = historical_emissions(countries)
 
     ax1.plot(emissions, color="black", linewidth=3, label=None)
 

scripts/prepare_sector_network.py

@@ -3234,7 +3234,7 @@ if __name__ == "__main__":
             simpl="",
             opts="",
             clusters="37",
-            lv=1.5,
+            ll='v1.5',
             sector_opts="cb40ex0-365H-T-H-B-I-A-solar+p3-dist1",
             planning_horizons="2020",
         )

scripts/solve_sector_network.py

@@ -325,7 +325,7 @@ if __name__ == "__main__":
             simpl="",
             opts="",
             clusters="45",
-            lv=1.0,
+            ll='v1.0',
             sector_opts="8760H-T-H-B-I-A-solar+p3-dist1",
             planning_horizons="2020",
         )