update tests to cover both cases of trafo_loading options, added seperate test cases for balanced and un-balanced load for trafo_loading

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

Author: furqan463

tests/data/pandapower/pp_validation.py

@@ -9,7 +9,7 @@
 
 @lru_cache
 def pp_net() -> pp.pandapowerNet:
-    #  (ext #1)         shunt - [104]  - 3w - [105] - sym_gen
+    #  (ext #1)         shunt - [104]  - 3w - [105] - asym_gen, asym_load
     #   |                                |
     #  [101] ---OO- [102] ---------- [103]
     #   |                                |
@@ -109,7 +109,7 @@ def pp_net_3ph() -> pp.pandapowerNet:
     """
     Creates a pandapower net used for validating 3 phase calculations
 
-     (ext #1)         shunt - [104], sym_gen - [105], motor, ward, asym_load, asym_gen
+     (ext #1)                       sym_gen , asym_load, asym_gen
       |                                |
      [101] ---OO- [102] ---------- [103]
       |                                |
@@ -208,11 +208,11 @@ def pp_net_3ph_minimal_trafo():
         2,
         0.33,
         0.34,
-        0.00,
+        0.001,
         600,
         r0_ohm_per_km=0.66,
         x0_ohm_per_km=0.65,
-        c0_nf_per_km=0.00,
+        c0_nf_per_km=0.001,
         g_us_per_km=0,
         g0_us_per_km=0,
     )
@@ -235,5 +235,5 @@ def pp_net_3ph_minimal_trafo():
         mag0_rx=0,
         si0_hv_partial=0.9,
     )
-    pp.create_asymmetric_load(net, 2, 0.2, 0.2, 0.2, 0.05, 0.05, 0.05, 0, type="wye")
+    pp.create_asymmetric_load(net, 2, 0.2, 0.19, 0.21, 0.05, 0.049, 0.052, 0, type="wye")
     return net

tests/validation/converters/test_pandapower_converter_input.py

@@ -16,7 +16,7 @@
 from power_grid_model_io.data_types import ExtraInfo
 from power_grid_model_io.utils.json import JsonEncoder
 
-from ...data.pandapower.pp_validation import pp_net
+from ...data.pandapower.pp_validation import pp_net, pp_net_3ph_minimal_trafo
 from ..utils import compare_extra_info, component_attributes, component_objects, load_json_single_dataset, select_values
 
 VALIDATION_FILE = Path(__file__).parents[2] / "data" / "pandapower" / "pgm_input_data.json"
@@ -116,3 +116,8 @@ def test_extra_info__serializable(extra_info):
 
     # Assert
     json.dumps(actual, cls=JsonEncoder)  # expect no exception
+
+def test_pgm_input_lines__cnf_zero():
+    pp_net = pp_net_3ph_minimal_trafo()
+    pp_converter = PandaPowerConverter()
+    

tests/validation/converters/test_pandapower_converter_output.py

@@ -26,6 +26,7 @@
 PGM_ASYM_OUTPUT_FILE = PGM_PP_TEST_DATA / "pgm_asym_output_data.json"
 PP_V2_NET_OUTPUT_FILE = PGM_PP_TEST_DATA / "pp_v2_net_output.json"
 PP_V2_NET_3PH_OUTPUT_FILE = PGM_PP_TEST_DATA / "pp_v2_net_3ph_output.json"
+PP_V2_NET_3PH_OUTPUT_FILE_CURRENT_LOADING = PGM_PP_TEST_DATA / "pp_v2_net_3ph_output_current_loading.json"
 
 
 @contextmanager
@@ -47,12 +48,12 @@ def load_and_convert_pgm_data() -> PandaPowerData:
 
 
 @lru_cache
-def load_and_convert_pgm_data_3ph() -> PandaPowerData:
+def load_and_convert_pgm_data_3ph(trafo_loading="power") -> PandaPowerData:
     """
     Load and convert the power_grid_model results
     """
     data, _ = load_json_single_dataset(PGM_ASYM_OUTPUT_FILE, data_type="asym_output")
-    converter = PandaPowerConverter(trafo_loading="power")
+    converter = PandaPowerConverter(trafo_loading=trafo_loading)
     converter.load_input_data(load_validation_data_3ph(), make_extra_info=False)
     return converter.convert(data=data)
 
@@ -66,11 +67,14 @@ def load_validation_data() -> PandaPowerData:
 
 
 @lru_cache
-def load_validation_data_3ph() -> PandaPowerData:
+def load_validation_data_3ph(trafo_loading="power") -> PandaPowerData:
     """
     Load the validation data from the pp file
     """
-    return pp.file_io.from_json(PP_V2_NET_3PH_OUTPUT_FILE)
+    if trafo_loading == "power":
+        return pp.file_io.from_json(PP_V2_NET_3PH_OUTPUT_FILE)
+    else:
+        return pp.file_io.from_json(PP_V2_NET_3PH_OUTPUT_FILE_CURRENT_LOADING)
 
 
 @pytest.fixture
@@ -83,13 +87,13 @@ def output_data() -> Tuple[PandaPowerData, PandaPowerData]:
     return actual, expected
 
 
-@pytest.fixture
-def output_data_3ph() -> Tuple[PandaPowerData, PandaPowerData]:
+@pytest.fixture(params = ["power", "current"])
+def output_data_3ph(request) -> Tuple[PandaPowerData, PandaPowerData]:
     """
     Load the pandapower network and the json file, and return the output_data
     """
-    actual = load_and_convert_pgm_data_3ph()
-    expected = load_validation_data_3ph()
+    actual = load_and_convert_pgm_data_3ph(request.param)
+    expected = load_validation_data_3ph(request.param)
     return actual, expected
 
 
@@ -202,11 +206,23 @@ def compare_result(actual, expected, *, rtol):
 
     pgm_net = pp_net_3ph_minimal_trafo()
     pp_net = pp_net_3ph_minimal_trafo()
+    # Asymmetric Load
+    pp.runpp_pgm(pgm_net, symmetric=False)
+    pp.runpp_3ph(pp_net)
+    check_result(pgm_net)
+    check_result(pp_net)
+    compare_result(pgm_net, pp_net, rtol=0.04)
+
+    # Symmetric Load
+    pgm_net.asymmetric_load.loc[:, ['p_a_mw', 'p_b_mw', 'p_c_mw']] = 0.2
+    pgm_net.asymmetric_load.loc[:, ['q_a_mvar', 'q_b_mvar', 'q_c_mar']] = 0.05
+    pp_net.asymmetric_load.loc[:, ['p_a_mw', 'p_b_mw', 'p_c_mw']] = 0.2
+    pp_net.asymmetric_load.loc[:, ['q_a_mvar', 'q_b_mvar', 'q_c_mar']] = 0.05
     pp.runpp_pgm(pgm_net, symmetric=False)
     pp.runpp_3ph(pp_net)
     check_result(pgm_net)
     check_result(pp_net)
-    compare_result(pgm_net, pp_net, rtol=0.004)
+    compare_result(pgm_net, pp_net, rtol=0.005)
 
 
 def test_output_data(output_data: Tuple[PandaPowerData, PandaPowerData]):
@@ -247,10 +263,7 @@ def test_attributes(output_data: Tuple[PandaPowerData, PandaPowerData], componen
     pd.testing.assert_series_equal(actual_values, expected_values, atol=5e-4, rtol=1e-4)
 
 
-# The following test only works for those components where valid data is returned by
-# load_and_convert_pgm_data_3ph. since this is failing for trafo_output_3ph (returning
-# from first "if", this function's output is not being tested currently.
-@pytest.mark.parametrize(("component", "attribute"), component_attributes_df(load_and_convert_pgm_data_3ph()))
+@pytest.mark.parametrize(("component", "attribute"), component_attributes_df(load_and_convert_pgm_data_3ph())) 
 def test_attributes_3ph(output_data_3ph: Tuple[PandaPowerData, PandaPowerData], component: str, attribute: str):
     """
     For each attribute, check if the actual values are consistent with the expected values for asym