Merge branch 'feature/powermodels_interface' into merge/powermodels_i…

…nterface_split_grid

edisgo/edisgo.py

@@ -3237,6 +3237,8 @@ def _check_timeindex(check_df, param_name):
         if len(self.heat_pump.cop_df.columns) > len(
             self.heat_pump.heat_demand_df.columns
         ):
+            # If there are heat pumps with heat demand but no COP time series, or the
+            # other way around, a warning is raised in HeatPump.check_integrity
             pass
         else:
             hp_cop = self.heat_pump.cop_df

edisgo/io/powermodels_io.py

@@ -363,7 +363,9 @@ def from_powermodels(
         for flex in df2.columns:
             abs_error = abs(df2[flex].values - hv_flex_dict[flex])
             rel_error = [
-                abs_error[i] / hv_flex_dict[flex][i] if (abs_error > 0.01)[i] else 0
+                abs_error[i] / hv_flex_dict[flex][i]
+                if ((abs_error > 0.01)[i] & hv_flex_dict[flex][i] != 0)
+                else 0
                 for i in range(len(abs_error))
             ]
             df2[flex] = rel_error
@@ -419,6 +421,15 @@ def from_powermodels(
         s_base,
     )
     edisgo_object.opf_results.heat_storage_t.e = df
+    df = _result_df(
+        pm,
+        "heat_storage",
+        "phss",
+        timesteps,
+        edisgo_object.timeseries.timeindex,
+        s_base,
+    )
+    edisgo_object.opf_results.heat_storage_t.p_slack = df
 
     if pm["nw"]["1"]["opf_version"] in [2, 4]:
         slacks = [
@@ -427,6 +438,7 @@ def from_powermodels(
             ("load", "pds"),
             ("electromobility", "pcps"),
             ("heatpumps", "phps"),
+            ("heatpumps", "phps2"),
         ]
         for comp, var in slacks:
             # save slacks to edisgo object
@@ -442,7 +454,10 @@ def from_powermodels(
             elif comp == "electromobility":
                 edisgo_object.opf_results.grid_slacks_t.cp_load_shedding = df
             elif comp == "heatpumps":
-                edisgo_object.opf_results.grid_slacks_t.hp_load_shedding = df
+                if var == "phps":
+                    edisgo_object.opf_results.grid_slacks_t.hp_load_shedding = df
+                elif var == "phps2":
+                    edisgo_object.opf_results.grid_slacks_t.hp_operation_slack = df
 
     # save line flows and currents to edisgo object
     for variable in ["pf", "qf", "ccm"]:

edisgo/network/timeseries.py

@@ -298,32 +298,6 @@ def storage_units_reactive_power(self):
     def storage_units_reactive_power(self, df):
         self._storage_units_reactive_power = df
 
-    @property
-    def storage_units_state_of_charge(self):
-        """
-        State of charge time series of storage units in MWh.
-
-        Parameters
-        ----------
-        df : :pandas:`pandas.DataFrame<DataFrame>`
-            State of charge time series of all storage units in topology in MWh. Index
-            of the dataframe is a time index and column names are names of storage
-            units.
-
-        Returns
-        -------
-        :pandas:`pandas.DataFrame<DataFrame>`
-            Reactive power time series of all storage units in topology in MVA for time
-            steps given in :py:attr:`~timeindex`. For more information on the dataframe
-            see input parameter `df`.
-
-        """
-        return self._internal_getter("storage_units_state_of_charge")
-
-    @storage_units_state_of_charge.setter
-    def storage_units_state_of_charge(self, df):
-        self._storage_units_state_of_charge = df
-
     def reset(self):
         """
         Resets all time series.

edisgo/opf/results/opf_result_class.py

@@ -219,13 +219,15 @@ def _get_matching_dict_of_attributes_and_file_names():
         "heat_storage_t": {
             "p": "heat_storage_t_p.csv",
             "e": "heat_storage_t_e.csv",
+            "p_slack": "heat_storage_t_p_slack.csv",
         },
         "grid_slacks_t": {
             "gen_d_crt": "dispatchable_gen_crt.csv",
             "gen_nd_crt": "non_dispatchable_gen_crt.csv",
             "load_shedding": "load_shedding.csv",
             "cp_load_shedding": "cp_load_shedding.csv",
             "hp_load_shedding": "hp_load_shedding.csv",
+            "hp_operation_slack": "hp_operation_slack.csv",
         },
     }
 

edisgo/tools/tools.py

@@ -295,7 +295,6 @@ def _assign_to_busses(graph, station):
             # `neighbor`
             subgraph_neighbor = nx.dfs_tree(subgraph, source=neighbor)
             for node in subgraph_neighbor.nodes():
-
                 edisgo_obj.topology.buses_df.at[node, mode] = neighbor
 
                 # in case of an LV station, assign feeder to all nodes in that
@@ -825,21 +824,29 @@ def add_line_susceptance(
     return edisgo_obj
 
 
-def aggregate_district_heating_components(edisgo_obj):
+def aggregate_district_heating_components(edisgo_obj, feedin_district_heating):
     """
-    Aggregate components that feed into the same district heating grid.
-    Rated power of both components is added up and COP for combined
-    component is calculated from COP of all components weighed with their rated
-    power. Heat demand of district heating grid is then reduced by feedin from other
-    sources.
+    Aggregate PtH components that feed into the same district heating network.
+
+    Besides aggregating PtH components, feed-in from other heat supply sources can
+    be specified, which is subtracted from the heat demand in the district heating
+    network in order to determine the heat demand that needs to be covered by the PtH
+    units.
+
+    Concerning the aggregated components, rated power of the single components is added
+    up and COP for combined component is calculated from COP of all components weighed
+    with their rated power. If active and reactive power time series were previously
+    set for the PtH units they are overwritten.
 
     Parameters
     -----------
     edisgo_obj : :class:`~.EDisGo`
+    feedin_district_heating : :pandas:`pandas.DataFrame<DataFrame>`
+        Other thermal feed-in into district heating per district heating area (in
+        columns) and time step (in index) in MW.
 
     """
     if "district_heating_id" in edisgo_obj.topology.loads_df.columns:
-        feedin_district_heating = edisgo_obj.overlying_grid.feedin_district_heating
         for (
             district
         ) in edisgo_obj.topology.loads_df.district_heating_id.dropna().unique():
@@ -863,7 +870,7 @@ def aggregate_district_heating_components(edisgo_obj):
                     edisgo_obj.heat_pump.heat_demand_df[district_hp] = (
                         edisgo_obj.heat_pump.heat_demand_df[district_hp]
                         - feedin_district_heating[str(district)]
-                    )  # .clip(min=0)
+                    )
                 else:
                     logger.info(
                         f"There are no other heat supply sources in district heating "
@@ -934,11 +941,13 @@ def aggregate_district_heating_components(edisgo_obj):
                         index={district_rh: district_hp}, inplace=True
                     )
 
-        # calculate power timeseries of aggregated components with reduced heat
-        # demand
-        edisgo_obj.apply_heat_pump_operating_strategy()
-    else:
-        edisgo_obj.apply_heat_pump_operating_strategy()
+            # if time series was previously set, overwrite time series in case
+            # components were aggregated components or heat demand reduced by feed-in
+            # from other components
+            if district_hp in edisgo_obj.timeseries.loads_active_power.columns:
+                edisgo_obj.apply_heat_pump_operating_strategy(
+                    heat_pump_names=district_hp
+                )
 
 
 def battery_storage_reference_operation(
@@ -986,7 +995,6 @@ def battery_storage_reference_operation(
         # If the house would feed electricity into the grid, charge the storage first.
         # No electricity exchange with grid as long as charger power is not exceeded
         if (d.house_demand > 0) & (storage_charge < storage_max):
-
             # Check if energy produced exceeds charger power
             if d.house_demand < charger_power:
                 storage_charge = storage_charge + (
@@ -1012,7 +1020,6 @@ def battery_storage_reference_operation(
         # No electricity exchange with grid as long as demand does not exceed charger
         # power
         elif (d.house_demand < 0) & (storage_charge > 0):
-
             # Check if energy demand exceeds charger power
             if d.house_demand / efficiency_discharge < (charger_power * -1):
                 storage_charge = storage_charge - (charger_power * time_base)
@@ -1083,7 +1090,7 @@ def create_storage_data(edisgo_obj):
             soc_df = pd.concat([soc_df, storage_ts.storage_charge], axis=1)
 
     soc_df.columns = edisgo_obj.topology.storage_units_df.index
-    edisgo_obj.timeseries.storage_units_state_of_charge = soc_df
+    edisgo_obj.overlying_grid.storage_units_soc = soc_df
     edisgo_obj.set_time_series_reactive_power_control()