fixed some small bugs in the CGMES converter and improved its speed

CHANGELOG.rst

@@ -40,6 +40,7 @@ Change Log
 - [ADDED] PowerFactory converter: support load types (constI, constZ) and the setting whether to consider voltage dependency of loads
 - [FIXED] deprecation of matplotlib.cm.get_cmap(name) -> matplotlib.colormaps[name]
 - [FIXED] merge_nets failing if net2 has custom DataFrame that is not present in net1
+- [FIXED] fixed some small bugs in the CGMES converter and improved its speed
 
 [2.14.7] - 2024-06-14
 -------------------------------

pandapower/converter/cim/cim2pp/build_pp_net.py

@@ -63,12 +63,9 @@ def copy_to_pp(self, pp_type: str, input_df: pd.DataFrame):
                 level=LogLevel.WARNING, code=ReportCode.WARNING_CONVERTING,
                 message="Missing pandapower type %s in the pandapower network!" % pp_type))
             return
-        start_index_pp_net = self.net[pp_type].index.size
-        self.net[pp_type] = pd.concat([self.net[pp_type], pd.DataFrame(None, index=[list(range(input_df.index.size))])],
+        self.net[pp_type] = pd.concat([self.net[pp_type],
+                                      input_df[list(set(self.net[pp_type].columns).intersection(input_df.columns))]],
                                       ignore_index=True, sort=False)
-        for one_attr in self.net[pp_type].columns:
-            if one_attr in input_df.columns:
-                self.net[pp_type][one_attr][start_index_pp_net:] = input_df[one_attr][:]
 
     # noinspection PyShadowingNames
     def convert_to_pp(self, convert_line_to_switch: bool = False, line_r_limit: float = 0.1,

pandapower/converter/cim/cim2pp/converter_classes/connectivitynodes/connectivityNodesCim16.py

@@ -210,7 +210,7 @@ def _prepare_connectivity_nodes_cim16(self) -> Tuple[pd.DataFrame, pd.DataFrame]
         eqssh_terminals = eqssh_terminals.drop_duplicates(subset=['rdfId', 'TopologicalNode'])
         eqssh_terminals_temp = eqssh_terminals[['ConnectivityNode', 'TopologicalNode']]
         eqssh_terminals_temp = eqssh_terminals_temp.dropna(subset=['TopologicalNode'])
-        eqssh_terminals_temp = eqssh_terminals_temp.drop_duplicates()
+        eqssh_terminals_temp = eqssh_terminals_temp.drop_duplicates(subset=['ConnectivityNode'])
         connectivity_nodes_size = connectivity_nodes.index.size
         if node_breaker:
             connectivity_nodes = pd.merge(connectivity_nodes, eqssh_terminals_temp, how='left', left_on='rdfId',

pandapower/converter/cim/cim2pp/converter_classes/externalnetworks/externalNetworkInjectionsCim16.py

@@ -24,7 +24,7 @@ def convert_external_network_injections_cim16(self):
         eqssh_eni = self._prepare_external_network_injections_cim16()
 
         # choose the slack
-        eni_ref_prio_min = eqssh_eni.loc[eqssh_eni['enabled'], 'slack_weight'].min()
+        eni_ref_prio_min = eqssh_eni.loc[(eqssh_eni['enabled']) & (eqssh_eni['slack_weight'] > 0), 'slack_weight'].min()
         # check if the slack is a SynchronousMachine
         sync_machines = self.cimConverter.merge_eq_ssh_profile('SynchronousMachine')
         sync_machines = self.get_voltage_from_controllers(sync_machines)
@@ -89,6 +89,7 @@ def _prepare_external_network_injections_cim16(self) -> pd.DataFrame:
 
         # convert pu generators with prio = 0 to pq generators (PowerFactory does it same)
         eni['referencePriority'].loc[eni['referencePriority'] == 0] = -1
+        eni['referencePriority'] = eni['referencePriority'].astype(float)
         eni['controlEnabled'].loc[eni['referencePriority'] == -1] = False
         eni['p'] = -eni['p']
         eni['q'] = -eni['q']

pandapower/converter/cim/cim2pp/converter_classes/generators/synchronousMachinesCim16.py

@@ -89,8 +89,7 @@ def _prepare_synchronous_machines_cim16(self) -> pd.DataFrame:
         synchronous_machines = pd.merge(
             synchronous_machines, eqssh_reg_control.rename(columns={'rdfId': 'RegulatingControl'}),
             how='left', on='RegulatingControl')
-        synchronous_machines = pd.merge(synchronous_machines, self.cimConverter.bus_merge, how='left',
-                                              on='rdfId')
+        synchronous_machines = pd.merge(synchronous_machines, self.cimConverter.bus_merge, how='left', on='rdfId')
         synchronous_machines = synchronous_machines.drop_duplicates(['rdfId'], keep='first')
         synchronous_machines['vm_pu'] = synchronous_machines.targetValue / synchronous_machines.vn_kv
         synchronous_machines['vm_pu'] = synchronous_machines['vm_pu'].fillna(1.)
@@ -137,12 +136,12 @@ def _prepare_synchronous_machines_cim16(self) -> pd.DataFrame:
         synchronous_machines['rx'] = synchronous_machines['r2'] / synchronous_machines['x2']
         synchronous_machines['scaling'] = 1.
         synchronous_machines['generator_type'] = 'current_source'
+        synchronous_machines.loc[synchronous_machines['referencePriority'] == 0, 'referencePriority'] = float('NaN')
+        synchronous_machines['referencePriority'] = synchronous_machines['referencePriority'].astype(float)
         if 'inService' in synchronous_machines.columns:
-            synchronous_machines['connected'] = (synchronous_machines['connected']
-                                                       & synchronous_machines['inService'])
-        synchronous_machines = synchronous_machines.rename(columns={'rdfId_Terminal': sc['t'], 'rdfId': sc['o_id'],
-                                                   'connected': 'in_service', 'index_bus': 'bus',
-                                                   'minOperatingP': 'min_p_mw', 'maxOperatingP': 'max_p_mw',
-                                                   'minQ': 'min_q_mvar', 'maxQ': 'max_q_mvar',
-                                                   'ratedPowerFactor': 'cos_phi'})
+            synchronous_machines['connected'] = (synchronous_machines['connected'] & synchronous_machines['inService'])
+        synchronous_machines = synchronous_machines.rename(columns={
+            'rdfId_Terminal': sc['t'], 'rdfId': sc['o_id'], 'connected': 'in_service', 'index_bus': 'bus',
+            'minOperatingP': 'min_p_mw', 'maxOperatingP': 'max_p_mw', 'minQ': 'min_q_mvar', 'maxQ': 'max_q_mvar',
+            'ratedPowerFactor': 'cos_phi', 'referencePriority': 'slack_weight'})
         return synchronous_machines

pandapower/converter/cim/cim2pp/converter_classes/transformers/tapController.py

@@ -1,4 +1,5 @@
 import logging
+import time
 from typing import List
 
 import pandas as pd
@@ -23,6 +24,8 @@ def create_tap_controller_for_power_transformers(self):
         if self.cimConverter.power_trafo2w.index.size > 0:
             # create transformer tap controller
             self._create_tap_controller(self.cimConverter.power_trafo2w, 'trafo')
+            time_start = time.time()
+            self.logger.info("Creating the tap dependent impedance characteristic objects for 2w-trafos.")
             # create the characteristic objects for transformers
             characteristic_df_temp = \
                 self.cimConverter.net['characteristic_temp'][['id_characteristic', 'step', 'vk_percent', 'vkr_percent']]
@@ -31,9 +34,13 @@ def create_tap_controller_for_power_transformers(self):
                     characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic']]
                 self._create_characteristic_object(net=self.cimConverter.net, trafo_type='trafo', trafo_id=[trafo_id],
                                                    characteristic_df=characteristic_df)
+            self.logger.info(f"Finished creating tap dependent impedance characteristic objects for 2w-trafos in "
+                             f"{time.time() - time_start}.")
         if self.cimConverter.power_trafo3w.index.size > 0:
             # create transformer tap controller
             self._create_tap_controller(self.cimConverter.power_trafo3w, 'trafo3w')
+            time_start = time.time()
+            self.logger.info("Creating the tap dependent impedance characteristic objects for 3w-trafos.")
             # create the characteristic objects for transformers
             characteristic_df_temp = \
                 self.cimConverter.net['characteristic_temp'][
@@ -44,6 +51,8 @@ def create_tap_controller_for_power_transformers(self):
                     characteristic_df_temp['id_characteristic'] == trafo_row['id_characteristic']]
                 self._create_characteristic_object(net=self.cimConverter.net, trafo_type='trafo3w', trafo_id=[trafo_id],
                                                    characteristic_df=characteristic_df)
+            self.logger.info(f"Finished creating tap dependent impedance characteristic objects for 3w-trafos in "
+                             f"{time.time() - time_start}.")
 
     def _create_characteristic_object(self, net, trafo_type: str, trafo_id: List, characteristic_df: pd.DataFrame):
         self.logger.info("Adding characteristic object for trafo_type: %s and trafo_id: %s" % (trafo_type, trafo_id))