Merge pull request #1119 from danielelerede-oet/split_hydro_inflow

Split inflow in ppl units + same hydro profile in alt. clustering

doc/release_notes.rst

@@ -38,6 +38,8 @@ E.g. if a new rule becomes available describe how to use it `make test` and in o
 
 * Drop duplicate entries in `AL_production.csv` data used in `build_industry_demand` rule `PR #1143 <https://github.com/pypsa-meets-earth/pypsa-earth/pull/1143>`_
 
+* The computation of `hydro_profile.nc` in `build_renewable_profiles.py` is not differentiated whether alternative clustering is applied or not; the indexing of the different power plants in `add_electricity.py` is performed according to the bus either in case alternative clustering is applied or not and a `hydro_inflow_factor` is computed prior to the computation of `inflow_t` to split the inflow according to the capacity of each different unit of each power plant (if more units are present). `PR #1119 <https://github.com/pypsa-meets-earth/pypsa-earth/pull/1119>`_
+
 
 PyPSA-Earth 0.4.1
 =================

scripts/add_electricity.py

@@ -488,10 +488,7 @@ def attach_hydro(n, costs, ppl):
     ror = ppl.query('technology == "Run-Of-River"')
     phs = ppl.query('technology == "Pumped Storage"')
     hydro = ppl.query('technology == "Reservoir"')
-    if snakemake.params.alternative_clustering:
-        bus_id = ppl["region_id"]
-    else:
-        bus_id = ppl["bus"]
+    bus_id = ppl["bus"]
 
     inflow_idx = ror.index.union(hydro.index)
     if not inflow_idx.empty:
@@ -530,12 +527,18 @@ def attach_hydro(n, costs, ppl):
                 network_buses_to_keep = plants_with_data.index
                 plants_to_keep = plants_with_data.to_numpy()
 
+                # hydro_inflow_factor is used to divide the inflow between the various units of each power plant
+                hydro_inflow_factor = hydro["p_nom"] / hydro.groupby("bus")[
+                    "p_nom"
+                ].transform("sum")
+
                 inflow_t = (
                     inflow.sel(plant=plants_to_keep)
                     .rename({"plant": "name"})
                     .assign_coords(name=network_buses_to_keep)
                     .transpose("time", "name")
                     .to_pandas()
+                    * hydro_inflow_factor
                 )
 
     if "ror" in carriers and not ror.empty:

scripts/build_renewable_profiles.py

@@ -356,9 +356,6 @@ def rescale_hydro(plants, runoff, normalize_using_yearly, normalization_year):
         logger.info("No bus has installed hydro plants, ignoring normalization.")
         return runoff
 
-    if snakemake.params.alternative_clustering:
-        plants = plants.set_index("shape_id")
-
     years_statistics = normalize_using_yearly.index
     if isinstance(years_statistics, pd.DatetimeIndex):
         years_statistics = years_statistics.year
@@ -533,24 +530,6 @@ def create_scaling_factor(
         # the region should be restricted for non-hydro technologies, as the hydro potential is calculated across hydrobasins which may span beyond the region of the country
         cutout = filter_cutout_region(cutout, regions)
 
-    if snakemake.params.alternative_clustering:
-        regions = gpd.GeoDataFrame(
-            regions.reset_index()
-            .groupby("shape_id")
-            .agg(
-                {
-                    "x": "mean",
-                    "y": "mean",
-                    "country": "first",
-                    "geometry": "first",
-                    "bus": "first",
-                }
-            )
-            .reset_index()
-            .set_index("bus"),
-            crs=regions.crs,
-        )
-
     buses = regions.index
 
     func = getattr(cutout, resource.pop("method"))
@@ -575,17 +554,10 @@ def create_scaling_factor(
         # select busbar whose location (p) belongs to at least one hydrobasin geometry
         # if extendable option is true, all buses are included
         # otherwise only where hydro powerplants are available are considered
-        if snakemake.params.alternative_clustering:
-            filter_bus_to_consider = regions.index.map(
-                lambda bus_id: config.get("extendable", False)
-                | (bus_id in hydro_ppls.region_id.values)
-            )
-        ### TODO: quickfix. above case and the below case should by unified
-        if snakemake.params.alternative_clustering == False:
-            filter_bus_to_consider = regions.index.map(
-                lambda bus_id: config.get("extendable", False)
-                | (bus_id in hydro_ppls.bus.values)
-            )
+        filter_bus_to_consider = regions.index.map(
+            lambda bus_id: config.get("extendable", False)
+            | (bus_id in hydro_ppls.bus.values)
+        )
         bus_to_consider = regions.index[filter_bus_to_consider]
 
         # identify subset of buses within the hydrobasins
@@ -603,17 +575,10 @@ def create_scaling_factor(
             columns={"x": "lon", "y": "lat", "country": "countries"}
         ).loc[bus_in_hydrobasins, ["lon", "lat", "countries", "shape_id"]]
 
-        # TODO: these cases shall be fixed by restructuring the alternative clustering procedure
-        if snakemake.params.alternative_clustering == False:
-            resource["plants"]["installed_hydro"] = [
-                True if (bus_id in hydro_ppls.bus.values) else False
-                for bus_id in resource["plants"].index
-            ]
-        else:
-            resource["plants"]["installed_hydro"] = [
-                True if (bus_id in hydro_ppls.region_id.values) else False
-                for bus_id in resource["plants"].shape_id.values
-            ]
+        resource["plants"]["installed_hydro"] = [
+            True if (bus_id in hydro_ppls.bus.values) else False
+            for bus_id in resource["plants"].index
+        ]
 
         # get normalization before executing runoff
         normalization = None
@@ -629,8 +594,6 @@ def create_scaling_factor(
         else:
             # otherwise perform the calculations
             inflow = correction_factor * func(capacity_factor=True, **resource)
-            if snakemake.params.alternative_clustering:
-                inflow["plant"] = regions.shape_id.loc[inflow["plant"]].values
 
             if "clip_min_inflow" in config:
                 inflow = inflow.where(inflow >= config["clip_min_inflow"], 0)