fix p_nom_min values for extendable carriers with positive p_nom

scripts/_helpers.py

@@ -125,6 +125,15 @@ def load_network_for_plots(fn, tech_costs, config, combine_hydro_ps=True):
 
     return n
 
+def update_p_nom_max(n):
+    # if extendable carriers (solar/onwind/...) have capacity >= 0,
+    # e.g. existing assets from the OPSD project are included to the network,
+    # the installed capacity might exceed the expansion limit.
+    # Hence, we update the assumptions.
+    
+    n.generators.p_nom_max = (n.generators
+                              .apply(lambda b: b[['p_nom_min','p_nom_max']].max(), axis=1))
+
 def aggregate_p_nom(n):
     return pd.concat([
         n.generators.groupby("carrier").p_nom_opt.sum(),

scripts/add_electricity.py

@@ -84,7 +84,7 @@ It further adds extendable ``generators`` with **zero** capacity for
 """
 
 import logging
-from _helpers import configure_logging
+from _helpers import configure_logging, update_p_nom_max
 
 import pypsa
 import pandas as pd
@@ -501,6 +501,7 @@ def attach_OPSD_renewables(n):
         caps = caps / gens_per_bus.reindex(caps.index, fill_value=1)
 
         n.generators.p_nom.update(gens.bus.map(caps).dropna())
+        n.generators.p_nom_min.update(gens.bus.map(caps).dropna())
 
 
 
@@ -536,6 +537,7 @@ def estimate_renewable_capacities(n, tech_map=None):
              .groupby(n.generators.bus.map(n.buses.country))
              .transform(lambda s: normed(s) * tech_capacities.at[s.name])
              .where(lambda s: s>0.1, 0.))  # only capacities above 100kW
+        n.generators.loc[tech_i, 'p_nom_min'] = n.generators.loc[tech_i, 'p_nom']
 
 
 def add_nice_carrier_names(n, config=None):
@@ -575,6 +577,7 @@ if __name__ == "__main__":
 
     estimate_renewable_capacities(n)
     attach_OPSD_renewables(n)
+    update_p_nom_max(n)
 
     add_nice_carrier_names(n)
 

scripts/cluster_network.py

@@ -122,7 +122,7 @@ Exemplary unsolved network clustered to 37 nodes:
 """
 
 import logging
-from _helpers import configure_logging
+from _helpers import configure_logging, update_p_nom_max
 
 import pypsa
 import os
@@ -282,7 +282,7 @@ def clustering_for_n_clusters(n, n_clusters, custom_busmap=False, aggregate_carr
         aggregate_generators_carriers=aggregate_carriers,
         aggregate_one_ports=["Load", "StorageUnit"],
         line_length_factor=line_length_factor,
-        generator_strategies={'p_nom_max': p_nom_max_strategy},
+        generator_strategies={'p_nom_max': p_nom_max_strategy, 'p_nom_min': np.sum},
         scale_link_capital_costs=False)
 
     if not n.links.empty:
@@ -379,6 +379,8 @@ if __name__ == "__main__":
                                                extended_link_costs=hvac_overhead_cost,
                                                focus_weights=focus_weights)
 
+    update_p_nom_max(n)
+    
     clustering.network.export_to_netcdf(snakemake.output.network)
     for attr in ('busmap', 'linemap'): #also available: linemap_positive, linemap_negative
         getattr(clustering, attr).to_csv(snakemake.output[attr])

scripts/simplify_network.py

@@ -83,7 +83,7 @@ The rule :mod:`simplify_network` does up to four things:
 """
 
 import logging
-from _helpers import configure_logging
+from _helpers import configure_logging, update_p_nom_max
 
 from cluster_network import clustering_for_n_clusters, cluster_regions
 from add_electricity import load_costs
@@ -198,7 +198,7 @@ def _aggregate_and_move_components(n, busmap, connection_costs_to_bus, aggregate
 
     _adjust_capital_costs_using_connection_costs(n, connection_costs_to_bus)
 
-    generators, generators_pnl = aggregategenerators(n, busmap)
+    generators, generators_pnl = aggregategenerators(n, busmap, custom_strategies={'p_nom_min': np.sum})
     replace_components(n, "Generator", generators, generators_pnl)
 
     for one_port in aggregate_one_ports:
@@ -364,6 +364,8 @@ if __name__ == "__main__":
         n, cluster_map = cluster(n, int(snakemake.wildcards.simpl))
         busmaps.append(cluster_map)
 
+    update_p_nom_max(n)
+
     n.export_to_netcdf(snakemake.output.network)
 
     busmap_s = reduce(lambda x, y: x.map(y), busmaps[1:], busmaps[0])