def test_staticInitalize(self):
model = PSSEModel()
model.setup()
GlobalData.data['DNet']['Nodes'] = {11: {}}
targetS, Vpcc = model.staticInitialize()
self.assertIsNotNone(Vpcc[11])
self.assertIsNotNone(targetS[11])
def test_getVoltage(self):
model = PSSEModel()
model.setup()
GlobalData.data['DNet']['Nodes'] = {11: {}}
targetS, Vpcc = model.staticInitialize()
Vpcc2 = model.getVoltage()
for node in Vpcc:
self.assertEqual(Vpcc[node], Vpcc2[node])
def test_setLoad(self):
model = PSSEModel()
model.setup()
GlobalData.data['DNet']['Nodes'] = {11: {}}
S = {11: {'P': 0.0, 'Q': 0.0}}
targetS, Vpcc = model.staticInitialize()
model.setLoad(S)
model.runPFLOW()
Vpcc2 = model.getVoltage()
for node in Vpcc:
self.assertNotEqual(Vpcc[node], Vpcc2[node])
class DefaultStaticProcedure(DefaultProcedure):
def __init__(self):
self._tnet_model = PSSEModel()
self._dnet_model = OpenDSSModel()
def setup(self):
self._tnet_model.setup()
self._dnet_model.setup()
def initialize(self):
targetS, Vpcc = self._tnet_model.staticInitialize()
power = self._dnet_model.initialize(targetS, Vpcc)
self._tnet_model.shunt(targetS, Vpcc, power)
def run(self):
GlobalData.data['static'] = {}
maxIter = 20
tol=10**-4
count = 0
loadShape = GlobalData.config['simulationConfig']['staticConfig']['loadShape']
GlobalData.data['monitorData']={}
for scale in loadShape:
GlobalData.data['static'][count] = {}
f=lambda x:[x[entry] for entry in x]
iteration=0
scaleData={}
Vpcc = self._tnet_model.getVoltage()
Vcheck=np.random.random((len(Vpcc),2))
for nodeID in Vpcc:
scaleData[nodeID]=scale
self._dnet_model.scaleLoad(scaleData)# now scale distribution feeder load
while np.any(np.abs(Vcheck[:,0]-Vcheck[:,1])>tol) and iteration<maxIter:
self._tnet_model.runPFLOW()# run power flow
Vpcc = self._tnet_model.getVoltage()
self._dnet_model.setVoltage(Vpcc)#set voltage based on previous guess
S = self._dnet_model.getLoad()# get complex power injection
self._tnet_model.setLoad(S)# set complex power injection as seen from T side
Vcheck[:,0]=Vcheck[:,1]#iterate for tight coupling
Vcheck[:,1]=np.array(f(Vpcc))
iteration+=1
# collect data and store
msg={}
msg['varName']={}
for node in Vpcc:
msg['varName'][node]=['voltage']
GlobalData.data['monitorData'][count]=self._dnet_model.monitor(msg)
GlobalData.data['static'][count]['V'] = Vpcc
GlobalData.data['static'][count]['S'] = S
GlobalData.data['static'][count]['Scale'] = scale
count = count + 1
class DefaultStaticProcedure(DefaultProcedure):
#===================================================================================================
def __init__(self):
try:
self._tnet_model = PSSEModel()
self._dnet_model = OpenDSSModel()
except:
GlobalData.log()
#===================================================================================================
def setup(self):
try:
self._tnet_model.setup()
self._dnet_model.setup()
except:
GlobalData.log()
#===================================================================================================
def initialize(self):
try:
targetS, Vpcc = self._tnet_model.staticInitialize()
GlobalData.log(20,'Attaching substaion to following buses: {}'.format(Vpcc.keys()))
power = self._dnet_model.initialize(targetS, Vpcc)
except:
GlobalData.log()
#===================================================================================================
def run(self):
try:
GlobalData.data['static'] = {}
maxIter = 20
tol=10**-4
count = 0
loadShape = GlobalData.config['simulationConfig']['staticConfig']['loadShape']
GlobalData.data['monitorData']={}
updateBins=20
for scale in loadShape:
GlobalData.log(20,'Running dispatch with loadshape {}'.format(scale))
GlobalData.data['static'][count] = {}
f=lambda x:[x[entry] for entry in x]
iteration=0
scaleData={}
Vpcc = self._tnet_model.getVoltage()
Vcheck=np.random.random((len(Vpcc),2))
for nodeID in Vpcc:
scaleData[nodeID]=scale
self._dnet_model.scaleLoad(scaleData)# now scale distribution feeder load
while np.any(np.abs(Vcheck[:,0]-Vcheck[:,1])>tol) and iteration<maxIter:
self._tnet_model.runPFLOW()# run power flow
Vpcc = self._tnet_model.getVoltage()
self._dnet_model.setVoltage(Vpcc)#set voltage based on previous guess
S = self._dnet_model.getLoad()# get complex power injection
self._tnet_model.setLoad(S)# set complex power injection as seen from T side
Vcheck[:,0]=Vcheck[:,1]#iterate for tight coupling
Vcheck[:,1]=np.array(f(Vpcc))
iteration+=1
print('Simulation Progress : ='+'='*int((updateBins-1)*(count/len(loadShape)))+'>'+\
' {}%({} dispatches/{} dispatches)'.format(((count+1)/len(loadShape))*100,count+1,len(loadShape)),end='\r')
GlobalData.log(20,'Loadshape {} Converged in {} iterations with mismatch {}'.format(scale,iteration,max(abs(np.abs(Vcheck[:,0]-Vcheck[:,1])))))
# collect data and store
msg={}
msg['varName']={}
for node in Vpcc:
msg['varName'][node]=['voltage']
GlobalData.data['monitorData'][count]=self._dnet_model.monitor(msg)
GlobalData.data['static'][count]['V'] = Vpcc
GlobalData.data['static'][count]['S'] = S
GlobalData.data['static'][count]['Scale'] = scale
count+=1
# close
print('')# for newline
ack=self._dnet_model.close()
GlobalData.log(level=20,msg=json.dumps(ack))
ierr=self._tnet_model._psspy.pssehalt_2(); assert ierr==0
except:
GlobalData.log()