PandaPower_Converter: Fix Transformer Loading Calculation by current and power and updating of validation tests

Signed-off-by: furqan463 <[email protected]>

Author: furqan463

src/power_grid_model_io/converters/pandapower_converter.py

@@ -2034,23 +2034,24 @@ def _pp_trafos_output_3ph(self):  # pylint: disable=too-many-statements
                     pgm_output_transformers["s_from"][:, 0],
                     pgm_output_transformers["s_to"][:, 0],
                 )
-                / pgm_output_transformers["s_n"]
+                / (pgm_input_transformers["sn"] / 3)
             )
             loading_b_percent = (
                 np.maximum(
                     pgm_output_transformers["s_from"][:, 1],
                     pgm_output_transformers["s_to"][:, 1],
                 )
-                / pgm_output_transformers["s_n"]
+                / (pgm_input_transformers["sn"] / 3)
             )
             loading_c_percent = (
                 np.maximum(
                     pgm_output_transformers["s_from"][:, 2],
                     pgm_output_transformers["s_to"][:, 2],
                 )
-                / pgm_output_transformers["s_n"]
+                / (pgm_input_transformers["sn"] / 3)
             )
-            loading = pgm_output_transformers["loading"]
+            # To make it consistent with PandaPower, overall loading will be calculated as max of above 3.
+            loading = np.maximum(np.maximum(loading_a_percent, loading_b_percent), loading_c_percent)
         else:
             raise ValueError(f"Invalid transformer loading type: {str(self.trafo_loading)}")
 

tests/validation/converters/test_pandapower_converter_output.py

@@ -52,8 +52,11 @@ def load_and_convert_pgm_data_3ph() -> PandaPowerData:
     Load and convert the power_grid_model results
     """
     data, extra_info = load_json_single_dataset(PGM_ASYM_OUTPUT_FILE, data_type="asym_output")
-    converter = PandaPowerConverter()
-    return converter.convert(data=data, extra_info=extra_info)
+    # trafo_loading = "power", as validation data is based on power based loading
+    converter = PandaPowerConverter(trafo_loading="power")
+    # if pp_input_data is not present in converter, some convert functions may fail.
+    converter.load_input_data(load_validation_data_3ph(), make_extra_info=False)
+    return converter.convert(data=data)
 
 
 @lru_cache