merge trafo charactersitic

pandapower/test/contingency/test_contingency.py

@@ -412,7 +412,7 @@ def _randomize_indices(net):
 
 def test_reminder_bring_back_case118():
     from packaging.version import Version
-    if lightsim2grid_installed and Version(lightsim2grid.__version__) > Version("0.9.0"):
+    if lightsim2grid_installed and Version(lightsim2grid.__version__) > Version("0.10.0"):
         raise UserWarning("bring back case 118 and remove xfail for test_unequal_trafo_impedances and test_case118")
 
 

pandapower/test/toolbox/test_grid_modification.py

@@ -190,28 +190,34 @@ def test_merge_with_groups():
     assert list(pp.group_element_index(net, 4, "line")) == list(np.array([1, 3], dtype=np.int64) + \
         net1.line.shape[0])
 
-# commented out due to change in logic of characteristics
-# def test_merge_with_characteristics():
-#     from pandapower.networks.simple_pandapower_test_networks import simple_four_bus_system
-#     from pandapower.control.util.characteristic import Characteristic
-#
-#     # create two networks
-#     net1 = simple_four_bus_system()
-#     net2 = simple_four_bus_system()
-#
-#     # create two characteristic
-#     Characteristic(net1, x_values=[0.85, 1.15], y_values=[5, 15])
-#     Characteristic(net2, x_values=[0.95, 1.05], y_values=[10, 20])
-#
-#     # assign the characteristic ids to the trafos
-#     net1.trafo.loc[:, "vk_percent_characteristic"] = 0
-#     net2.trafo.loc[:, "vk_percent_characteristic"] = 0
-#
-#     # merge networks
-#     merged, lookup = pp.merge_nets(net1, net2, validate=False, return_net2_reindex_lookup=True)
-#
-#     # The second transformer should have the second characteristic
-#     assert merged.trafo.loc[1, "vk_percent_characteristic"] == 1
+def test_merge_with_characteristics():
+    from pandapower.networks.simple_pandapower_test_networks import simple_four_bus_system
+    from pandapower.control.util.characteristic import Characteristic
+
+    # create two networks
+    net1 = simple_four_bus_system()
+    net2 = simple_four_bus_system()
+
+    net1["trafo_characteristic_table"] = pd.DataFrame(
+        {'id_characteristic': [0, 0, 0, 0, 0], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [1, 1, 1, 1, 1],
+         'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [2, 3, 4, 5, 6],
+         'vkr_percent': [1.323, 1.324, 1.325, 1.326, 1.327], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan,
+         'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan})
+    net2["trafo_characteristic_table"] = pd.DataFrame(
+        {'id_characteristic': [0, 0, 0, 0, 0], 'step': [-2, -1, 0, 1, 2], 'voltage_ratio': [1, 1, 1, 1, 1],
+         'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [2.1, 3.1, 4.1, 5.1, 6.1],
+         'vkr_percent': [1.3, 1.4, 1.5, 1.6, 1.7], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan,
+         'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan})
+
+    # merge networks
+    merged, lookup = pp.merge_nets(net1, net2, validate=False, return_net2_reindex_lookup=True)
+
+    # The second transformer should have the second characteristic
+    result = merged.trafo_characteristic_table[
+        (merged.trafo_characteristic_table["id_characteristic"] == 1) &
+        (merged.trafo_characteristic_table["step"] == 2)
+        ]
+    assert result["vkr_percent"].values[0] == 1.7
 
 
 def test_merge_nets_with_custom_elements():

pandapower/toolbox/data_modification.py

@@ -331,6 +331,10 @@ def reindex_elements(net, element_type, new_indices=None, old_indices=None, look
             net[cost_df].loc[element_in_cost_df, "element"] = get_indices(net[cost_df].element[
                 element_in_cost_df], lookup)
 
+    # --- adapt tap_characteristic
+    if element_type ==  "trafo":
+        if "trafo_characteristic_table" in net and  "id_characteristic" in net["trafo_characteristic_table"]:
+            net["trafo_characteristic_table"]["id_characteristic"] = net["trafo_characteristic_table"]["id_characteristic"].map(lookup)
 
 def create_continuous_elements_index(net, start=0, add_df_to_reindex=set()):
     """