Merge pull request #402 from openego/bugfix/dingo-annual-demand-nans

Bugfix/dingo annual demand nans

edisgo/network/timeseries.py

@@ -1448,6 +1448,12 @@ def predefined_conventional_loads_by_sector(
         load_names = self._check_if_components_exist(edisgo_object, load_names, "loads")
         loads_df = edisgo_object.topology.loads_df.loc[load_names, :]
 
+        # check if loads contain annual demand
+        if not all(loads_df.annual_consumption.notnull()):
+            raise AttributeError(
+                "The annual consumption of some loads is missing. Please provide"
+            )
+
         # scale time series by annual consumption
         ts_scaled = loads_df.apply(
             lambda x: ts_loads[x.sector] * x.annual_consumption,

tests/network/test_timeseries.py

@@ -1794,6 +1794,26 @@ def test_predefined_conventional_loads_by_sector(self, caplog):
             ).values,
         ).all()
 
+        # test Error if 'annual_consumption' is missing
+        # Save the original 'annual_consumption' values
+        original_annual_consumption = self.edisgo.topology.loads_df[
+            "annual_consumption"
+        ].copy()
+        # Set 'annual_consumption' to None for the test
+        self.edisgo.topology.loads_df["annual_consumption"] = None
+        with pytest.raises(AttributeError) as exc_info:
+            self.edisgo.timeseries.predefined_conventional_loads_by_sector(
+                self.edisgo, "demandlib"
+            )
+        assert (
+            exc_info.value.args[0]
+            == "The annual consumption of some loads is missing. Please provide"
+        )
+        # Restore the original 'annual_consumption' values
+        self.edisgo.topology.loads_df[
+            "annual_consumption"
+        ] = original_annual_consumption
+
     def test_predefined_charging_points_by_use_case(self, caplog):
         index = pd.date_range("1/1/2018", periods=3, freq="H")
         self.edisgo.timeseries.timeindex = index