extract Capacitance value directly from Y-matrix of System to have proper power flow value

Signed-off-by: Taeyoung Kim <taeyoung.kim@eonerc.rwth-aachen.de>

examples/quickstart/run_nv_powerflow.log

@@ -76,7 +76,7 @@ INFO:cimpy.cimimport:CIM object Line created : 11 times
 INFO:cimpy.cimimport:CIM object SubGeographicalRegion created : 2 times
 INFO:cimpy.cimimport:CIM object BusbarSection created : 13 times
 INFO:cimpy.cimimport:CIM object TopologicalIsland created : 2 times
-INFO:cimpy.cimimport:Created totally 275 CIM objects in 0.02181220054626465s
+INFO:cimpy.cimimport:Created totally 275 CIM objects in 0.0252532958984375s
 
 
 WARNING:pandapower.auxiliary:numba cannot be imported and numba functions are disabled.

pyvolt/export.py

@@ -34,6 +34,7 @@ class CIMtoDataFrame(Exporter):
         self.node = system.nodes
         self.branch = system.branches
         self.Ymatrix = np.zeros([], dtype=complex)
+        self.system = system
         
     def makeOneDict(self, save=False):
         """
@@ -43,6 +44,7 @@ class CIMtoDataFrame(Exporter):
         branch = self.parseBranch()
         loads = self.createLoads()
         gens = self.createGens()
+        cap = self.get_branch_capacitance()
 
         df_connectivity,matrix_connectivity = self.makeConnectivity(node,branch)
         sub_connectivity = self.interpretConnectivity(matrix_connectivity) #now we can make n-different connection matrix
@@ -57,6 +59,8 @@ class CIMtoDataFrame(Exporter):
         whole_thing['con']['total_con'] = df_connectivity
         whole_thing['con']['grp_con'] = sub_connectivity
         
+        whole_thing['etc']=dict()
+        whole_thing['etc']['capacitance'] =cap
         #ToDo Not working!!!!!!
         if save == True:
             with open('dict_grid.json', 'w') as f:
@@ -98,7 +102,7 @@ class CIMtoDataFrame(Exporter):
         """
         this function create dataframe of Branch
         """
-        df = pd.DataFrame(columns=["idx", "start_node", "end_node", "r","r_pu","x","x_pu","y","y_pu","z","z_pu", "base_voltage","base_apparent_power","base_current","base_impedance","uuid"])
+        df = pd.DataFrame(columns=["idx", "start_node", "end_node", "r","r_pu","x","x_pu","y","y_pu","z","z_pu","c","base_voltage","base_apparent_power","base_current","base_impedance","uuid"])
         for k, branch in enumerate(self.branch):
             baseVoltage = branch.baseVoltage#
             base_apparent_power = branch.base_apparent_power#
@@ -121,8 +125,11 @@ class CIMtoDataFrame(Exporter):
             end_node_index = end_node.index #
             index = k #
             
+            cap = self.get_branch_capacitance()
+            cap=cap[k]
+            
             df.loc[k]=[
-                int(index), int(start_node_index), int(end_node_index), r, r_pu, x, x_pu, y, y_pu, z, z_pu, baseVoltage, base_apparent_power, base_current, base_impedance, uuid
+                int(index), int(start_node_index), int(end_node_index), r, r_pu, x, x_pu, y, y_pu, z, z_pu, cap, baseVoltage, base_apparent_power, base_current, base_impedance, uuid
             ]
         return df
     
@@ -280,6 +287,26 @@ class CIMtoDataFrame(Exporter):
                 sub_connectivity[k] = df_local
         return sub_connectivity
     
+    def get_branch_capacitance(self, frequency=50):
+        sys = self.system
+        y_mat = sys.Ymatrix
+        
+        w = 2 * np.pi * frequency
+        cap = {}
+        idx = 0
+        for branch in self.branch:
+            fr = branch.start_node.index
+            to = branch.end_node.index
+            
+            y_branch = -y_mat[fr,to]
+            
+            c = np.imag(y_branch)/w
+            
+            cap[idx]=c
+            idx +=1
+        
+        return cap
+        
     
 
 class DataFrameToJson(Exporter):
@@ -470,8 +497,8 @@ class PandapowerWork(Exporter):
             elif bus_type == 2: #generation
                 # static generator with the absolute values.
                 pp.create_sgen(net, bus_id,
-                            p_mw=abs(p_kw) / 1000.0,
-                            q_mvar=abs(q_kvar) / 1000.0,
+                            p_mw=abs(p_kw) / 1000,
+                            q_mvar=abs(q_kvar) / 1000,
                             name=f"sgen_{bus['name']}")
                 
         
@@ -495,8 +522,13 @@ class PandapowerWork(Exporter):
             # getting R,X,Z value
             length = branch["lengthkm"]
             
-            r_total = branch["resistancePu"] * (V_nom ** 2) / mva_base
-            x_total = branch["reactancePu"] * (V_nom ** 2) / mva_base
+            #this is right one, but for now with current json structure, this is wrong.
+            # r_total = branch["resistancePu"] * (V_nom ** 2) / mva_base
+            # x_total = branch["reactancePu"] * (V_nom ** 2) / mva_base
+            
+            #so we use this one, which use q['branch]['base_power'] = 25
+            r_total = branch["resistancePu"] * (V_nom ** 2) / 25  
+            x_total = branch["reactancePu"] * (V_nom ** 2) / 25
 
             r_ohm_per_km = r_total / length
             x_ohm_per_km = x_total / length
@@ -510,11 +542,13 @@ class PandapowerWork(Exporter):
             # c_nf_per_km (line capacitance in nF/km). To convert a PU susceptance to an nF/km value,
             # you would need additional parameters (e.g. frequency) and conversion factors.
             # For simplicity, we set it to 0 (if you need to account for shunt capacitance, adjust accordingly).
+            w = 2* np.pi *50 
+            capacity = -1/ (w*abs(x_total))
             
             line_id = pp.create_line_from_parameters(net, bus_from, bus_to, length_km=length,
                                                     r_ohm_per_km=r_ohm_per_km,
                                                     x_ohm_per_km=x_ohm_per_km,
-                                                    c_nf_per_km=0.0,  # adjust if needed
+                                                    c_nf_per_km=capacity*(10**6)*10,  # adjust if needed
                                                     max_i_ka=max_i_ka,
                                                     name=f"line_{branch['index']}")
 

run_nv_powerflow.log

@@ -76,50 +76,6 @@ INFO:cimpy.cimimport:CIM object Line created : 11 times
 INFO:cimpy.cimimport:CIM object SubGeographicalRegion created : 2 times
 INFO:cimpy.cimimport:CIM object BusbarSection created : 13 times
 INFO:cimpy.cimimport:CIM object TopologicalIsland created : 2 times
-INFO:cimpy.cimimport:Created totally 275 CIM objects in 0.041670799255371094s
+INFO:cimpy.cimimport:Created totally 275 CIM objects in 0.03760051727294922s
 
 
-WARNING:pandapower.auxiliary:numba cannot be imported and numba functions are disabled.
-Probably the execution is slow.
-Please install numba to gain a massive speedup.
-(or if you prefer slow execution, set the flag numba=False to avoid this warning!)
-WARNING:pandapower.auxiliary:numba cannot be imported and numba functions are disabled.
-Probably the execution is slow.
-Please install numba to gain a massive speedup.
-(or if you prefer slow execution, set the flag numba=False to avoid this warning!)
-WARNING:pandapower.auxiliary:numba cannot be imported and numba functions are disabled.
-Probably the execution is slow.
-Please install numba to gain a massive speedup.
-(or if you prefer slow execution, set the flag numba=False to avoid this warning!)
-WARNING:pandapower.auxiliary:numba cannot be imported and numba functions are disabled.
-Probably the execution is slow.
-Please install numba to gain a massive speedup.
-(or if you prefer slow execution, set the flag numba=False to avoid this warning!)
-WARNING:pandapower.auxiliary:numba cannot be imported and numba functions are disabled.
-Probably the execution is slow.
-Please install numba to gain a massive speedup.
-(or if you prefer slow execution, set the flag numba=False to avoid this warning!)
-WARNING:pandapower.auxiliary:numba cannot be imported and numba functions are disabled.
-Probably the execution is slow.
-Please install numba to gain a massive speedup.
-(or if you prefer slow execution, set the flag numba=False to avoid this warning!)
-WARNING:pandapower.auxiliary:numba cannot be imported and numba functions are disabled.
-Probably the execution is slow.
-Please install numba to gain a massive speedup.
-(or if you prefer slow execution, set the flag numba=False to avoid this warning!)
-WARNING:pandapower.auxiliary:numba cannot be imported and numba functions are disabled.
-Probably the execution is slow.
-Please install numba to gain a massive speedup.
-(or if you prefer slow execution, set the flag numba=False to avoid this warning!)
-WARNING:pandapower.auxiliary:numba cannot be imported and numba functions are disabled.
-Probably the execution is slow.
-Please install numba to gain a massive speedup.
-(or if you prefer slow execution, set the flag numba=False to avoid this warning!)
-WARNING:pandapower.auxiliary:numba cannot be imported and numba functions are disabled.
-Probably the execution is slow.
-Please install numba to gain a massive speedup.
-(or if you prefer slow execution, set the flag numba=False to avoid this warning!)
-WARNING:pandapower.auxiliary:numba cannot be imported and numba functions are disabled.
-Probably the execution is slow.
-Please install numba to gain a massive speedup.
-(or if you prefer slow execution, set the flag numba=False to avoid this warning!)