Merge pull request #1019 from PyPSA/reform-grouping-year-logic

Reform grouping year logic

config/config.default.yaml

@@ -360,8 +360,8 @@ solar_thermal:
 
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#existing-capacities
 existing_capacities:
-  grouping_years_power: [1960, 1965, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, 2025, 2030]
-  grouping_years_heat: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019] # these should not extend 2020
+  grouping_years_power: [1895, 1920, 1950, 1955, 1960, 1965, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, 2025, 2030]
+  grouping_years_heat: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020] # heat grouping years >= baseyear will be ignored
   threshold_capacity: 10
   default_heating_lifetime: 20
   conventional_carriers:

doc/release_notes.rst

@@ -9,6 +9,9 @@ Release Notes
 
 Upcoming Release
 ================
+* Group existing capacities to the earlier grouping_year for consistency with optimized capacities.
+
+* bugfix: installed heating capacities were 5% lower than existing heating capacities
 
 * Include gas and oil fields and saline aquifers in estimation of CO2 sequestration potential.
 

scripts/add_brownfield.py

@@ -40,8 +40,8 @@ def add_brownfield(n, n_p, year):
         # CO2 or global EU values since these are already in n
         n_p.mremove(c.name, c.df.index[c.df.lifetime == np.inf])
 
-        # remove assets whose build_year + lifetime < year
-        n_p.mremove(c.name, c.df.index[c.df.build_year + c.df.lifetime < year])
+        # remove assets whose build_year + lifetime <= year
+        n_p.mremove(c.name, c.df.index[c.df.build_year + c.df.lifetime <= year])
 
         # remove assets if their optimized nominal capacity is lower than a threshold
         # since CHP heat Link is proportional to CHP electric Link, make sure threshold is compatible

scripts/add_existing_baseyear.py

@@ -189,8 +189,19 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
     phased_out = df_agg[df_agg["DateOut"] < baseyear].index
     df_agg.drop(phased_out, inplace=True)
 
+    older_assets = (df_agg.DateIn < min(grouping_years)).sum()
+    if older_assets:
+        logger.warning(
+            f"There are {older_assets} assets with build year "
+            f"before first power grouping year {min(grouping_years)}. "
+            "These assets are dropped and not considered."
+            "Consider to redefine the grouping years to keep them."
+        )
+        to_drop = df_agg[df_agg.DateIn < min(grouping_years)].index
+        df_agg.drop(to_drop, inplace=True)
+
     df_agg["grouping_year"] = np.take(
-        grouping_years, np.digitize(df_agg.DateIn, grouping_years, right=True)
+        grouping_years[::-1], np.digitize(df_agg.DateIn, grouping_years[::-1])
     )
 
     # calculate (adjusted) remaining lifetime before phase-out (+1 because assuming
@@ -444,12 +455,25 @@ def add_heating_capacities_installed_before_baseyear(
         else:
             efficiency = costs.at[costs_name, "efficiency"]
 
-        for i, grouping_year in enumerate(grouping_years):
-            if int(grouping_year) + default_lifetime <= int(baseyear):
-                continue
+        valid_grouping_years = pd.Series(
+            [
+                int(grouping_year)
+                for grouping_year in grouping_years
+                if int(grouping_year) + default_lifetime > int(baseyear)
+                and int(grouping_year) < int(baseyear)
+            ]
+        )
+
+        # get number of years of each interval
+        _years = (
+            valid_grouping_years.diff()
+            .shift(-1)
+            .fillna(baseyear - valid_grouping_years.iloc[-1])
+        )
+        # Installation is assumed to be linear for the past
+        ratios = _years / _years.sum()
 
-            # installation is assumed to be linear for the past default_lifetime years
-            ratio = (int(grouping_year) - int(grouping_years[i - 1])) / default_lifetime
+        for ratio, grouping_year in zip(ratios, valid_grouping_years):
 
             n.madd(
                 "Link",