not all columns did exist in p_max_pu of pypsa network

assume/markets/clearing_algorithms/nodal_pricing.py

@@ -147,11 +147,24 @@ def clear(
         nodal_network = self.network.copy()
 
         # Update p_max_pu for generators
-        nodal_network.generators_t.p_max_pu.update(p_max_pu)
-        nodal_network.generators_t.p_min_pu.update(p_min_pu)
+        # Also add new columns which did not yet exist in nodal_network.generators_t
+        df_p_max_pu = nodal_network.generators_t.p_max_pu
+        df_p_max_pu.update(p_max_pu)
+        new_columns = p_max_pu.loc[:,~p_max_pu.columns.isin(df_p_max_pu.columns)]
+        nodal_network.generators_t.p_max_pu = pd.concat([df_p_max_pu, new_columns], axis=1)
+
+        # Update p_min_pu for generators
+        df_p_min_pu = nodal_network.generators_t.p_min_pu
+        df_p_min_pu.update(p_min_pu)
+        new_columns = p_min_pu.loc[:,~p_min_pu.columns.isin(df_p_min_pu.columns)]
+        nodal_network.generators_t.p_min_pu = pd.concat([df_p_min_pu, new_columns], axis=1)
 
         # Update marginal costs for generators
-        nodal_network.generators_t.marginal_cost.update(costs)
+        df_costs = nodal_network.generators_t.marginal_cost
+        df_costs.update(costs)
+        new_columns = costs.loc[:,~costs.columns.isin(df_costs.columns)]
+        nodal_network.generators_t.marginal_cost = pd.concat([df_costs, new_columns], axis=1)
+
 
         with suppress_output():
             status, termination_condition = nodal_network.optimize(