def runPowerflowIter(tree,scadaSubPower, iterationTimes):
'''Runs powerflow once, then iterates.'''
print "Running calibration powerflow #1."
output = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=gridlabdDir)
outRealPow = output["caliSub.csv"]["measured_real_power"]
outImagPower = output["caliSub.csv"]["measured_reactive_power"]
outAppPowerKw = [(x[0]**2 + x[1]**2)**0.5/1000 for x in zip(outRealPow, outImagPower)]
lastFile = "subScada.player"
nextFile = "subScadaCalibrated.player"
nextPower = outAppPowerKw
for i in range(1, iterationTimes+1):
SCAL_CONST = sum(scadaSubPower[1:simLength])/sum(nextPower[1:simLength])
print "Running calibration powerflow (iteration", str(i+1), "of", iterationTimes+1,") (SCAL_CONST: ", SCAL_CONST,")"
newPlayData = []
with open(pJoin(gridlabdDir, lastFile), "r") as playerFile:
for line in playerFile:
(key,val) = line.split(',')
newPlayData.append(str(key) + ',' + str(float(val)*SCAL_CONST) + "\n")
with open(pJoin(gridlabdDir, nextFile), "w") as playerFile:
for row in newPlayData:
playerFile.write(row)
tree[playerKey]["file"] = nextFile
tree[outputRecorderKey]["file"] = "caliSubCheck.csv"
nextOutput = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=gridlabdDir)
outRealPow2nd = nextOutput["caliSubCheck.csv"]["measured_real_power"]
outImagPower2nd = nextOutput["caliSubCheck.csv"]["measured_reactive_power"]
nextAppKw = [(x[0]**2 + x[1]**2)**0.5/1000
for x in zip(outRealPow2nd, outImagPower2nd)]
lastFile = nextFile
nextFile = "subScadaCalibrated"+str(i)+".player"
nextPower = outAppPowerKw
return outRealPow, outRealPow2nd, lastFile
def runPowerflowIter(tree, scadaSubPower):
'''Runs powerflow once, then iterates.'''
# Run initial powerflow to get power.
print "Running initial calibration powerflow."
output = gridlabd.runInFilesystem(tree,
keepFiles=True,
workDir=gridlabdDir)
outRealPow = output["caliSub.csv"]["measured_real_power"]
outImagPower = output["caliSub.csv"]["measured_reactive_power"]
outAppPowerKw = [(x[0]**2 + x[1]**2)**0.5 / 1000
for x in zip(outRealPow, outImagPower)]
lastFile = "subScada.player"
nextFile = "subScadaCalibrated.player"
nextPower = outAppPowerKw
error = (sum(outRealPow[1:simLength]) / 1000 - sum(
scadaSubPower[1:simLength])) / sum(scadaSubPower[1:simLength])
iteration = 1
while abs(error) > calibrateError and iteration < 5:
# Run calibration and iterate up to 5 times.
SCAL_CONST = sum(scadaSubPower[1:simLength]) / sum(
nextPower[1:simLength])
print "Calibrating loads, running powerflow again. Our SCAL_CONST is: ", SCAL_CONST
newPlayData = []
with open(pJoin(gridlabdDir, lastFile), "r") as playerFile:
for line in playerFile:
(key, val) = line.split(',')
newPlayData.append(
str(key) + ',' + str(float(val) * SCAL_CONST) + "\n")
with open(pJoin(gridlabdDir, nextFile), "w") as playerFile:
for row in newPlayData:
playerFile.write(row)
tree[playerKey]["file"] = nextFile
tree[outputRecorderKey]["file"] = "caliSubCheck.csv"
nextOutput = gridlabd.runInFilesystem(tree,
keepFiles=True,
workDir=gridlabdDir)
outRealPowIter = nextOutput["caliSubCheck.csv"][
"measured_real_power"]
outImagPowerIter = nextOutput["caliSubCheck.csv"][
"measured_reactive_power"]
nextAppKw = [(x[0]**2 + x[1]**2)**0.5 / 1000
for x in zip(outRealPowIter, outImagPowerIter)]
lastFile = nextFile
nextFile = "subScadaCalibrated" + str(iteration) + ".player"
nextPower = nextAppKw
# Compute error and iterate.
error = (sum(outRealPowIter[1:simLength]) / 1000 - sum(
scadaSubPower[1:simLength])) / sum(scadaSubPower[1:simLength])
iteration += 1
print "Error:", abs(error * 100), "% Iteration:", iteration
return outRealPow, outRealPowIter, lastFile, iteration
def runBeckGridlab():
try:
os.remove('./beckDebuggery')
except:
pass
os.mkdir('./beckDebuggery')
rawOut = gridlabd.runInFilesystem(tree,
attachments=myFeeder.get('attachments',{}), keepFiles=True,
workDir='./beckDebuggery', glmName=None)
def runPowerflowIter(tree,scadaSubPower):
'''Runs powerflow once, then iterates.'''
# Run initial powerflow to get power.
print "Starting calibration."
print "Goal of calibration: Error: %s, Iterations: <%s, trim: %s"%(calibrateError[0], calibrateError[1], trim)
output = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=pJoin(workDir,"gridlabD"))
outRealPow = output["caliSub.csv"]["measured_real_power"][trim:simLength]
outImagPower = output["caliSub.csv"]["measured_reactive_power"][trim:simLength]
outAppPowerKw = [(x[0]**2 + x[1]**2)**0.5/1000 for x in zip(outRealPow, outImagPower)]
lastFile = "subScada.player"
nextFile = "subScadaCalibrated.player"
nextPower = outAppPowerKw
error = (sum(outRealPow)/1000-sum(scadaSubPower))/sum(scadaSubPower)
iteration = 1
print "First error:", error
while abs(error)>calibrateError[0] and iteration<calibrateError[1]:
# Run calibration and iterate up to 5 times.
SCAL_CONST = sum(scadaSubPower)/sum(nextPower)
print "Calibrating & running again... Error: %s, Iteration: %s, SCAL_CONST: %s"%(str(round(abs(error*100),2)), str(iteration), round(SCAL_CONST,2))
newPlayData = []
with open(pJoin(pJoin(workDir,"gridlabD"), lastFile), "r") as playerFile:
for line in playerFile:
(key,val) = line.split(',')
newPlayData.append(str(key) + ',' + str(float(val)*SCAL_CONST) + "\n")
with open(pJoin(pJoin(workDir,"gridlabD"), nextFile), "w") as playerFile:
for row in newPlayData:
playerFile.write(row)
tree[playerKey]["file"] = nextFile
tree[outputRecorderKey]["file"] = "caliSubCheck.csv"
nextOutput = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=pJoin(workDir,"gridlabD"))
outRealPowIter = nextOutput["caliSubCheck.csv"]["measured_real_power"][trim:simLength]
outImagPowerIter = nextOutput["caliSubCheck.csv"]["measured_reactive_power"][trim:simLength]
nextAppKw = [(x[0]**2 + x[1]**2)**0.5/1000
for x in zip(outRealPowIter, outImagPowerIter)]
lastFile = nextFile
nextFile = "subScadaCalibrated"+str(iteration)+".player"
nextPower = nextAppKw
# Compute error and iterate.
error = (sum(outRealPowIter)/1000-sum(scadaSubPower))/sum(scadaSubPower)
iteration+=1
else:
if iteration==1: outRealPowIter = outRealPow
print "Calibration done: Error: %s, Iteration: %s, SCAL_CONST: %s"%(str(round(abs(error*100),2)), str(iteration), round(SCAL_CONST,2))
return outRealPow, outRealPowIter, lastFile, iteration
def runBeckGridlab():
try:
os.remove('./beckDebuggery')
except:
pass
os.mkdir('./beckDebuggery')
rawOut = gridlabd.runInFilesystem(tree,
attachments=myFeeder.get(
'attachments', {}),
keepFiles=True,
workDir='./beckDebuggery',
glmName=None)
def runPowerflowIter(tree,scadaSubPower):
'''Runs powerflow once, then iterates.'''
# Run initial powerflow to get power.
print "Running initial calibration powerflow."
output = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=gridlabdDir)
outRealPow = output["caliSub.csv"]["measured_real_power"]
outImagPower = output["caliSub.csv"]["measured_reactive_power"]
outAppPowerKw = [(x[0]**2 + x[1]**2)**0.5/1000 for x in zip(outRealPow, outImagPower)]
lastFile = "subScada.player"
nextFile = "subScadaCalibrated.player"
nextPower = outAppPowerKw
error = (sum(outRealPow[1:simLength])/1000-sum(scadaSubPower[1:simLength]))/sum(scadaSubPower[1:simLength])
iteration = 1
while abs(error)>calibrateError and iteration<5:
# Run calibration and iterate up to 5 times.
SCAL_CONST = sum(scadaSubPower[1:simLength])/sum(nextPower[1:simLength])
print "Calibrating loads, running powerflow again. Our SCAL_CONST is: ", SCAL_CONST
newPlayData = []
with open(pJoin(gridlabdDir, lastFile), "r") as playerFile:
for line in playerFile:
(key,val) = line.split(',')
newPlayData.append(str(key) + ',' + str(float(val)*SCAL_CONST) + "\n")
with open(pJoin(gridlabdDir, nextFile), "w") as playerFile:
for row in newPlayData:
playerFile.write(row)
tree[playerKey]["file"] = nextFile
tree[outputRecorderKey]["file"] = "caliSubCheck.csv"
nextOutput = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=gridlabdDir)
outRealPowIter = nextOutput["caliSubCheck.csv"]["measured_real_power"]
outImagPowerIter = nextOutput["caliSubCheck.csv"]["measured_reactive_power"]
nextAppKw = [(x[0]**2 + x[1]**2)**0.5/1000
for x in zip(outRealPowIter, outImagPowerIter)]
lastFile = nextFile
nextFile = "subScadaCalibrated"+str(iteration)+".player"
nextPower = nextAppKw
# Compute error and iterate.
error = (sum(outRealPowIter[1:simLength])/1000-sum(scadaSubPower[1:simLength]))/sum(scadaSubPower[1:simLength])
iteration+=1
print "Error:", abs(error*100), "% Iteration:", iteration
return outRealPow, outRealPowIter, lastFile, iteration
def convertTests():
''' Test convert every windmil feeder we have (in uploads). Return number of exceptions we hit. '''
exceptionCount = 0
testFiles = [('OrvilleTreePond.std', 'OrvilleTreePond.seq')]
# ,('OlinBarre.std','OlinBarre.seq'),('OlinBeckenham.std','OlinBeckenham.seq'), ('AutocliAlberich.std','AutocliAlberich.seq')
for stdString, seqString in testFiles:
try:
# Convert the std+seq.
with open(stdString, 'r') as stdFile, open(seqString,
'r') as seqFile:
outGlm, x, y = milToGridlab.convert(stdFile.read(),
seqFile.read())
with open(stdString.replace('.std', '.glm'), 'w') as outFile:
outFile.write(feeder.sortedWrite(outGlm))
print 'WROTE GLM FOR', stdString
try:
# Draw the GLM.
myGraph = feeder.treeToNxGraph(outGlm)
feeder.latLonNxGraph(myGraph, neatoLayout=False)
plt.savefig(stdString.replace('.std', '.png'))
print 'DREW GLM OF', stdString
except:
exceptionCount += 1
print 'FAILED DRAWING', stdString
try:
# Run powerflow on the GLM.
output = gridlabd.runInFilesystem(outGlm, keepFiles=False)
with open(stdString.replace('.std', '.json'), 'w') as outFile:
json.dump(output, outFile, indent=4)
print 'RAN GRIDLAB ON', stdString
except:
exceptionCount += 1
print 'POWERFLOW FAILED', stdString
except:
print 'FAILED CONVERTING', stdString
exceptionCount += 1
traceback.print_exc()
print exceptionCount
def convertTests():
''' Test convert every windmil feeder we have (in uploads). Return number of exceptions we hit. '''
exceptionCount = 0
testFiles = [('OrvilleTreePond.std','OrvilleTreePond.seq')]
# ,('OlinBarre.std','OlinBarre.seq'),('OlinBeckenham.std','OlinBeckenham.seq'), ('AutocliAlberich.std','AutocliAlberich.seq')
for stdString, seqString in testFiles:
try:
# Convert the std+seq.
with open(stdString,'r') as stdFile, open(seqString,'r') as seqFile:
outGlm,x,y = milToGridlab.convert(stdFile.read(),seqFile.read())
with open(stdString.replace('.std','.glm'),'w') as outFile:
outFile.write(feeder.sortedWrite(outGlm))
print 'WROTE GLM FOR', stdString
try:
# Draw the GLM.
myGraph = feeder.treeToNxGraph(outGlm)
feeder.latLonNxGraph(myGraph, neatoLayout=False)
plt.savefig(stdString.replace('.std','.png'))
print 'DREW GLM OF', stdString
except:
exceptionCount += 1
print 'FAILED DRAWING', stdString
try:
# Run powerflow on the GLM.
output = gridlabd.runInFilesystem(outGlm, keepFiles=False)
with open(stdString.replace('.std','.json'),'w') as outFile:
json.dump(output, outFile, indent=4)
print 'RAN GRIDLAB ON', stdString
except:
exceptionCount += 1
print 'POWERFLOW FAILED', stdString
except:
print 'FAILED CONVERTING', stdString
exceptionCount += 1
traceback.print_exc()
print exceptionCount
def runForeground(modelDir, inputDict):
''' Run the model in its directory. WARNING: GRIDLAB CAN TAKE HOURS TO COMPLETE. '''
# Check whether model exist or not
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inputDict["created"] = str(datetime.datetime.now())
print "STARTING TO RUN", modelDir
beginTime = datetime.datetime.now()
feederList = []
# Get prepare of data and clean workspace if re-run, If re-run remove all the data in the subfolders
for dirs in os.listdir(modelDir):
if os.path.isdir(pJoin(modelDir, dirs)):
shutil.rmtree(pJoin(modelDir, dirs))
# Get each feeder, prepare data in separate folders, and run there.
for key in sorted(inputDict, key=inputDict.get):
if key.startswith("feederName"):
feederDir, feederName = inputDict[key].split("___")
feederList.append(feederName)
try:
os.remove(pJoin(modelDir, feederName, "allOutputData.json"))
except Exception, e:
pass
if not os.path.isdir(pJoin(modelDir, feederName)):
os.makedirs(pJoin(modelDir, feederName)) # create subfolders for feeders
shutil.copy(pJoin(__metaModel__._omfDir, "data", "Feeder", feederDir, feederName + ".json"),
pJoin(modelDir, feederName, "feeder.json"))
inputDict["climateName"], latforpvwatts = zipCodeToClimateName(inputDict["zipCode"])
shutil.copy(pJoin(__metaModel__._omfDir, "data", "Climate", inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, feederName, "climate.tmy2"))
try:
startTime = datetime.datetime.now()
feederJson = json.load(open(pJoin(modelDir, feederName, "feeder.json")))
tree = feederJson["tree"]
# Set up GLM with correct time and recorders:
feeder.attachRecorders(tree, "Regulator", "object", "regulator")
feeder.attachRecorders(tree, "Capacitor", "object", "capacitor")
feeder.attachRecorders(tree, "Inverter", "object", "inverter")
feeder.attachRecorders(tree, "Windmill", "object", "windturb_dg")
feeder.attachRecorders(tree, "CollectorVoltage", None, None)
feeder.attachRecorders(tree, "Climate", "object", "climate")
feeder.attachRecorders(tree, "OverheadLosses", None, None)
feeder.attachRecorders(tree, "UndergroundLosses", None, None)
feeder.attachRecorders(tree, "TriplexLosses", None, None)
feeder.attachRecorders(tree, "TransformerLosses", None, None)
feeder.groupSwingKids(tree)
feeder.adjustTime(tree=tree, simLength=float(inputDict["simLength"]),
simLengthUnits=inputDict["simLengthUnits"], simStartDate=inputDict["simStartDate"])
# RUN GRIDLABD IN FILESYSTEM (EXPENSIVE!)
rawOut = gridlabd.runInFilesystem(tree, attachments=feederJson["attachments"],
keepFiles=True, workDir=pJoin(modelDir, feederName))
cleanOut = {}
# Std Err and Std Out
cleanOut['stderr'] = rawOut['stderr']
cleanOut['stdout'] = rawOut['stdout']
# Time Stamps
for key in rawOut:
if '# timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# timestamp']
break
elif '# property.. timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# property.. timestamp']
else:
cleanOut['timeStamps'] = []
# Day/Month Aggregation Setup:
stamps = cleanOut.get('timeStamps',[])
level = inputDict.get('simLengthUnits','hours')
# Climate
for key in rawOut:
if key.startswith('Climate_') and key.endswith('.csv'):
cleanOut['climate'] = {}
cleanOut['climate']['Rain Fall (in/h)'] = hdmAgg(rawOut[key].get('rainfall'), sum, level)
cleanOut['climate']['Wind Speed (m/s)'] = hdmAgg(rawOut[key].get('wind_speed'), avg, level)
cleanOut['climate']['Temperature (F)'] = hdmAgg(rawOut[key].get('temperature'), max, level)
cleanOut['climate']['Snow Depth (in)'] = hdmAgg(rawOut[key].get('snowdepth'), max, level)
cleanOut['climate']['Direct Insolation (W/m^2)'] = hdmAgg(rawOut[key].get('solar_direct'), sum, level)
# Voltage Band
if 'VoltageJiggle.csv' in rawOut:
cleanOut['allMeterVoltages'] = {}
cleanOut['allMeterVoltages']['Min'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['min(voltage_12.mag)']], min, level)
cleanOut['allMeterVoltages']['Mean'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['mean(voltage_12.mag)']], avg, level)
cleanOut['allMeterVoltages']['StdDev'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['std(voltage_12.mag)']], avg, level)
cleanOut['allMeterVoltages']['Max'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['max(voltage_12.mag)']], max, level)
cleanOut['allMeterVoltages']['stdDevPos'] = [(x+y/2) for x,y in zip(cleanOut['allMeterVoltages']['Mean'], cleanOut['allMeterVoltages']['StdDev'])]
cleanOut['allMeterVoltages']['stdDevNeg'] = [(x-y/2) for x,y in zip(cleanOut['allMeterVoltages']['Mean'], cleanOut['allMeterVoltages']['StdDev'])]
# Total # of meters
count = 0
with open(pJoin(modelDir, feederName, "feeder.json")) as f:
for line in f:
if "\"objectType\": \"triplex_meter\"" in line:
count+=1
print "count=", count
cleanOut['allMeterVoltages']['triplexMeterCount'] = float(count)
# Power Consumption
cleanOut['Consumption'] = {}
# Set default value to be 0, avoiding missing value when computing Loads
cleanOut['Consumption']['Power'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['Losses'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['DG'] = [0] * int(inputDict["simLength"])
for key in rawOut:
if key.startswith('SwingKids_') and key.endswith('.csv'):
oneSwingPower = hdmAgg(vecPyth(rawOut[key]['sum(power_in.real)'],rawOut[key]['sum(power_in.imag)']), avg, level)
if 'Power' not in cleanOut['Consumption']:
cleanOut['Consumption']['Power'] = oneSwingPower
else:
cleanOut['Consumption']['Power'] = vecSum(oneSwingPower,cleanOut['Consumption']['Power'])
elif key.startswith('Inverter_') and key.endswith('.csv'):
realA = rawOut[key]['power_A.real']
realB = rawOut[key]['power_B.real']
realC = rawOut[key]['power_C.real']
imagA = rawOut[key]['power_A.imag']
imagB = rawOut[key]['power_B.imag']
imagC = rawOut[key]['power_C.imag']
oneDgPower = hdmAgg(vecSum(vecPyth(realA,imagA),vecPyth(realB,imagB),vecPyth(realC,imagC)), avg, level)
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(oneDgPower,cleanOut['Consumption']['DG'])
elif key.startswith('Windmill_') and key.endswith('.csv'):
vrA = rawOut[key]['voltage_A.real']
vrB = rawOut[key]['voltage_B.real']
vrC = rawOut[key]['voltage_C.real']
viA = rawOut[key]['voltage_A.imag']
viB = rawOut[key]['voltage_B.imag']
viC = rawOut[key]['voltage_C.imag']
crB = rawOut[key]['current_B.real']
crA = rawOut[key]['current_A.real']
crC = rawOut[key]['current_C.real']
ciA = rawOut[key]['current_A.imag']
ciB = rawOut[key]['current_B.imag']
ciC = rawOut[key]['current_C.imag']
powerA = vecProd(vecPyth(vrA,viA),vecPyth(crA,ciA))
powerB = vecProd(vecPyth(vrB,viB),vecPyth(crB,ciB))
powerC = vecProd(vecPyth(vrC,viC),vecPyth(crC,ciC))
# HACK: multiply by negative one because turbine power sign is opposite all other DG:
oneDgPower = [-1.0 * x for x in hdmAgg(vecSum(powerA,powerB,powerC), avg, level)]
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(oneDgPower,cleanOut['Consumption']['DG'])
elif key in ['OverheadLosses.csv', 'UndergroundLosses.csv', 'TriplexLosses.csv', 'TransformerLosses.csv']:
realA = rawOut[key]['sum(power_losses_A.real)']
imagA = rawOut[key]['sum(power_losses_A.imag)']
realB = rawOut[key]['sum(power_losses_B.real)']
imagB = rawOut[key]['sum(power_losses_B.imag)']
realC = rawOut[key]['sum(power_losses_C.real)']
imagC = rawOut[key]['sum(power_losses_C.imag)']
oneLoss = hdmAgg(vecSum(vecPyth(realA,imagA),vecPyth(realB,imagB),vecPyth(realC,imagC)), avg, level)
if 'Losses' not in cleanOut['Consumption']:
cleanOut['Consumption']['Losses'] = oneLoss
else:
cleanOut['Consumption']['Losses'] = vecSum(oneLoss,cleanOut['Consumption']['Losses'])
# Aggregate up the timestamps:
if level=='days':
cleanOut['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:10], 'days')
elif level=='months':
cleanOut['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:7], 'months')
# Write the output.
with open(pJoin(modelDir, feederName, "allOutputData.json"),"w") as outFile:
json.dump(cleanOut, outFile, indent=4)
# Update the runTime in the input file.
endTime = datetime.datetime.now()
inputDict["runTime"] = str(datetime.timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir, feederName, "allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent=4)
# Clean up the PID file.
os.remove(pJoin(modelDir, feederName,"PID.txt"))
print "DONE RUNNING GRIDLABMULTI", modelDir, feederName
except Exception as e:
print "MODEL CRASHED GRIDLABMULTI", e, modelDir, feederName
cancel(pJoin(modelDir, feederName))
with open(pJoin(modelDir, feederName, "stderr.txt"), "a+") as stderrFile:
traceback.print_exc(file = stderrFile)
def attachVolts(workDir, feederPath, voltVectorA, voltVectorB, voltVectorC,
simStartDate, simLength, simLengthUnits):
'''read voltage vectors of 3 different phases, run gridlabd, and attach output to the feeder.'''
try:
timeStamp = [simStartDate['Date']]
for x in range(1, 8760):
timeStamp.append(timeStamp[x - 1] + dt.timedelta(hours=1))
firstDateTime = timeStamp[1]
with open(pJoin(pJoin(workDir, "gridlabD"), "phaseAVoltage.player"),
"w") as voltFile:
for x in range(0, 8760):
timestamp = timeStamp[x]
voltage = str("%0.2f" % float(voltVectorA[x])) + "+0j"
line = timestamp.strftime(
"%Y-%m-%d %H:%M:%S"
) + " " + simStartDate['timeZone'] + "," + str(voltage) + "\n"
voltFile.write(line)
with open(pJoin(pJoin(workDir, "gridlabD"), "phaseBVoltage.player"),
"w") as voltFile:
for x in range(0, 8760):
timestamp = timeStamp[x]
voltage = str("%0.2f" % float(voltVectorB[x])) + "-" + str(
"%0.4f" % float(random.uniform(6449, 6460))) + "j"
line = timestamp.strftime(
"%Y-%m-%d %H:%M:%S"
) + " " + simStartDate['timeZone'] + "," + str(voltage) + "\n"
voltFile.write(line)
with open(pJoin(pJoin(workDir, "gridlabD"), "phaseCVoltage.player"),
"w") as voltFile:
for x in range(0, 8760):
timestamp = timeStamp[x]
voltage = str("%0.2f" % float(voltVectorC[x])) + "+" + str(
"%0.4f" % float(random.uniform(6449, 6460))) + "j"
line = timestamp.strftime(
"%Y-%m-%d %H:%M:%S"
) + " " + simStartDate['timeZone'] + "," + str(voltage) + "\n"
voltFile.write(line)
with open(feederPath, "r") as jsonIn:
feederJson = json.load(jsonIn)
tree = feederJson.get("tree", {})
# Find swingNode name.
for key in tree:
if tree[key].get('bustype', '').lower() == 'swing':
swingName = tree[key].get('name')
# Attach player.
classOb = {'omftype': 'class player', 'argument': '{double value;}'}
voltageObA = {
"object": "player",
"property": "voltage_A",
"file": "phaseAVoltage.player",
"loop": "0",
"parent": swingName
}
voltageObB = {
"object": "player",
"property": "voltage_B",
"file": "phaseBVoltage.player",
"loop": "0",
"parent": swingName
}
voltageObC = {
"object": "player",
"property": "voltage_C",
"file": "phaseCVoltage.player",
"loop": "0",
"parent": swingName
}
maxKey = feeder.getMaxKey(tree)
voltplayerKeyA = maxKey + 2
voltplayerKeyB = maxKey + 3
voltplayerKeyC = maxKey + 4
tree[maxKey + 1] = classOb
tree[voltplayerKeyA] = voltageObA
tree[voltplayerKeyB] = voltageObB
tree[voltplayerKeyC] = voltageObC
# Adjust time and run output.
feeder.adjustTime(tree, simLength, simLengthUnits,
firstDateTime.strftime("%Y-%m-%d %H:%M:%S"))
output = gridlabd.runInFilesystem(tree,
keepFiles=True,
workDir=pJoin(workDir, "gridlabD"))
# Write the output.
with open(pJoin(workDir, "calibratedFeeder.omd"), "w") as outJson:
playerStringA = open(
pJoin(pJoin(workDir, "gridlabD"),
"phaseAVoltage.player")).read()
playerStringB = open(
pJoin(pJoin(workDir, "gridlabD"),
"phaseBVoltage.player")).read()
playerStringC = open(
pJoin(pJoin(workDir, "gridlabD"),
"phaseCVoltage.player")).read()
feederJson["attachments"]["phaseAVoltage.player"] = playerStringA
feederJson["attachments"]["phaseBVoltage.player"] = playerStringB
feederJson["attachments"]["phaseCVoltage.player"] = playerStringC
feederJson["tree"] = tree
json.dump(feederJson, outJson, indent=4)
return pJoin(workDir, "calibratedFeeder.omd"), True
except:
print "Failed to run gridlabD with voltage players."
return "", False
def runForeground(modelDir, inData):
'''This reads a glm file, changes the method of powerflow and reruns'''
print "STARTING TO RUN", modelDir
try:
startTime = datetime.now()
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inData["created"] = str(startTime)
#read pre-calibrated feeder and run cvrdynamic
feederName = inData.get('feederName1', 'feeder1')
feederPath = pJoin(modelDir, feederName + '.omd')
# Reads a pre-calibrated feeder.
allOutput = {}
with open(feederPath, "r") as jsonIn:
feederJson = json.load(jsonIn)
localTree = feederJson.get("tree", {})
attachments = feederJson.get("attachments", {})
for key in localTree:
if "solver_method" in localTree[key].keys():
# print "current solver method", localTree[key]["solver_method"]
localTree[key]["solver_method"] = 'FBS'
#find the swing bus and recorder attached to substation
try:
for key in localTree:
if localTree[key].get('bustype', '').lower() == 'swing':
swingIndex = key
swingName = localTree[key].get('name')
if localTree[key].get(
'object', '') == 'regulator' and localTree[key].get(
'from', '') == swingName:
regIndex = key
regConfName = localTree[key]['configuration']
except:
raise ValueError('Invalid feeder selected:',
str(inData["feederName1"]))
#find the regulator and capacitor names and combine to form a string for volt-var control object
regKeys = []
accum_reg = ""
for key in localTree:
if localTree[key].get("object", "") == "regulator":
accum_reg += localTree[key].get("name", "ERROR") + ","
regKeys.append(key)
regstr = accum_reg[:-1]
# print regKeys
capKeys = []
accum_cap = ""
for key in localTree:
if localTree[key].get("object", "") == "capacitor":
accum_cap += localTree[key].get("name", "ERROR") + ","
capKeys.append(key)
if localTree[key].get("control", "").lower() == "manual":
localTree[key]['control'] = "VOLT"
# print "changing capacitor control from manual to volt"
capstr = accum_cap[:-1]
# print capKeys
# Attach recorders relevant to CVR.
recorders = [{
'object':
'collector',
'file':
'ZlossesTransformer.csv',
'group':
'class=transformer',
'limit':
'0',
'property':
'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'
}, {
'object':
'collector',
'file':
'ZlossesUnderground.csv',
'group':
'class=underground_line',
'limit':
'0',
'property':
'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'
}, {
'object':
'collector',
'file':
'ZlossesOverhead.csv',
'group':
'class=overhead_line',
'limit':
'0',
'property':
'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'
}, {
'object':
'recorder',
'file':
'Zregulator.csv',
'limit':
'0',
'parent':
localTree[regIndex]['name'],
'property':
'tap_A,tap_B,tap_C,power_in.real,power_in.imag'
}, {
'object':
'collector',
'file':
'ZvoltageJiggle.csv',
'group':
'class=triplex_meter',
'limit':
'0',
'property':
'min(voltage_12.mag),mean(voltage_12.mag),max(voltage_12.mag),std(voltage_12.mag)'
}, {
'object': 'recorder',
'file': 'ZsubstationTop.csv',
'limit': '0',
'parent': localTree[swingIndex]['name'],
'property': 'voltage_A,voltage_B,voltage_C'
}, {
'object': 'recorder',
'file': 'ZsubstationBottom.csv',
'limit': '0',
'parent': localTree[regIndex]['to'],
'property': 'voltage_A,voltage_B,voltage_C'
}]
#recorder object for capacitor switching - if capacitors exist
if capKeys != []:
for key in capKeys:
recorders.append({
'object': 'recorder',
'file': 'ZcapSwitch' + str(key) + '.csv',
'limit': '0',
'parent': localTree[key]['name'],
'property': 'switchA,switchB,switchC'
})
#attach recorder process
biggest = 1 + max([int(k) for k in localTree.keys()])
for index, rec in enumerate(recorders):
localTree[biggest + index] = rec
#run a reference load flow
HOURS = float(inData['simLengthHours'])
simStartDate = inData['simStart']
feeder.adjustTime(localTree, HOURS, "hours", simStartDate)
output = gridlabd.runInFilesystem(localTree,
attachments,
keepFiles=False,
workDir=modelDir)
try:
os.remove(pJoin(modelDir, "PID.txt"))
except:
pass
p = output['Zregulator.csv']['power_in.real']
q = output['Zregulator.csv']['power_in.imag']
#calculating length of simulation because it migth be different from the simulation input HOURS
simRealLength = int(len(p))
#time delays from configuration files
time_delay_reg = '30.0'
time_delay_cap = '300.0'
for key in localTree:
if localTree[key].get('object', '') == "regulator_configuration":
time_delay_reg = localTree[key]['time_delay']
# print "time_delay_reg",time_delay_reg
# if localTree[key].get('object','') == "capacitor":
# time_delay_cap = localTree[key]['time_delay']
# print "time_delay_cap",time_delay_cap
#change the recorder names
for key in localTree:
if localTree[key].get('object',
'') == "collector" or localTree[key].get(
'object', '') == "recorder":
if localTree[key].get('file', '').startswith('Z'):
localTree[key]['file'] = localTree[key].get(
'file', '').replace('Z', 'NewZ')
#create volt-var control object
max_key = max([int(key) for key in localTree.keys()])
# print max_key
localTree[max_key + 1] = {
'object': 'volt_var_control',
'name': 'IVVC1',
'control_method': 'ACTIVE',
'capacitor_delay': str(time_delay_cap),
'regulator_delay': str(time_delay_reg),
'desired_pf': '0.99',
'd_max': '0.6',
'd_min': '0.1',
'substation_link': str(localTree[regIndex]['name']),
'regulator_list': regstr,
'capacitor_list': capstr,
'voltage_measurements': str(inData.get("voltageNodes", 0)),
}
#running powerflow analysis via gridalab after attaching a regulator
feeder.adjustTime(localTree, HOURS, "hours", simStartDate)
output1 = gridlabd.runInFilesystem(localTree,
attachments,
keepFiles=True,
workDir=modelDir)
os.remove(pJoin(modelDir, "PID.txt"))
pnew = output1['NewZregulator.csv']['power_in.real']
qnew = output1['NewZregulator.csv']['power_in.imag']
#total real and imaginary losses as a function of time
def vecSum(u, v):
''' Add vectors u and v element-wise. Return has len <= len(u) and <=len(v). '''
return map(sum, zip(u, v))
def zeroVec(length):
''' Give a zero vector of input length. '''
return [0 for x in xrange(length)]
(realLoss, imagLoss, realLossnew, imagLossnew) = (zeroVec(int(HOURS))
for x in range(4))
for device in [
'ZlossesOverhead.csv', 'ZlossesTransformer.csv',
'ZlossesUnderground.csv'
]:
for letter in ['A', 'B', 'C']:
realLoss = vecSum(
realLoss,
output[device]['sum(power_losses_' + letter + '.real)'])
imagLoss = vecSum(
imagLoss,
output[device]['sum(power_losses_' + letter + '.imag)'])
realLossnew = vecSum(
realLossnew, output1['New' + device]['sum(power_losses_' +
letter + '.real)'])
imagLossnew = vecSum(
imagLossnew, output1['New' + device]['sum(power_losses_' +
letter + '.imag)'])
#voltage calculations and tap calculations
def divby2(u):
'''divides by 2'''
return u / 2
lowVoltage = []
meanVoltage = []
highVoltage = []
lowVoltagenew = []
meanVoltagenew = []
highVoltagenew = []
tap = {'A': [], 'B': [], 'C': []}
tapnew = {'A': [], 'B': [], 'C': []}
volt = {'A': [], 'B': [], 'C': []}
voltnew = {'A': [], 'B': [], 'C': []}
switch = {'A': [], 'B': [], 'C': []}
switchnew = {'A': [], 'B': [], 'C': []}
for letter in ['A', 'B', 'C']:
tap[letter] = output['Zregulator.csv']['tap_' + letter]
tapnew[letter] = output1['NewZregulator.csv']['tap_' + letter]
if capKeys != []:
switch[letter] = output['ZcapSwitch' + str(int(capKeys[0])) +
'.csv']['switch' + letter]
switchnew[letter] = output1['NewZcapSwitch' +
str(int(capKeys[0])) +
'.csv']['switch' + letter]
volt[letter] = map(
returnMag,
output['ZsubstationBottom.csv']['voltage_' + letter])
voltnew[letter] = map(
returnMag,
output1['NewZsubstationBottom.csv']['voltage_' + letter])
lowVoltage = map(divby2,
output['ZvoltageJiggle.csv']['min(voltage_12.mag)'])
lowVoltagenew = map(
divby2, output1['NewZvoltageJiggle.csv']['min(voltage_12.mag)'])
meanVoltage = map(divby2,
output['ZvoltageJiggle.csv']['mean(voltage_12.mag)'])
meanVoltagenew = map(
divby2, output1['NewZvoltageJiggle.csv']['mean(voltage_12.mag)'])
highVoltage = map(divby2,
output['ZvoltageJiggle.csv']['max(voltage_12.mag)'])
highVoltagenew = map(
divby2, output1['NewZvoltageJiggle.csv']['max(voltage_12.mag)'])
#energy calculations
whEnergy = []
whLosses = []
whLoads = []
whEnergy.append(sum(p) / 10**6)
whLosses.append(sum(realLoss) / 10**6)
whLoads.append((sum(p) - sum(realLoss)) / 10**6)
whEnergy.append(sum(pnew) / 10**6)
whLosses.append(sum(realLossnew) / 10**6)
whLoads.append((sum(pnew) - sum(realLossnew)) / 10**6)
indices = ['No IVVC', 'With IVVC']
# energySalesRed = (whLoads[1]-whLoads[0])*(inData['wholesaleEnergyCostPerKwh'])*1000
# lossSav = (whLosses[0]-whLosses[1])*inData['wholesaleEnergyCostPerKwh']*1000
# print energySalesRed, lossSav
#plots
ticks = []
plt.clf()
plt.title("total energy")
plt.ylabel("total load and losses (MWh)")
for element in range(2):
ticks.append(element)
bar_loss = plt.bar(element, whLosses[element], 0.15, color='red')
bar_load = plt.bar(element + 0.15,
whLoads[element],
0.15,
color='orange')
plt.legend([bar_load[0], bar_loss[0]], ['total load', 'total losses'],
bbox_to_anchor=(0., 0.915, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.1)
plt.xticks([t + 0.15 for t in ticks], indices)
plt.savefig(pJoin(modelDir, "totalEnergy.png"))
#real and imaginary power
plt.figure("real power")
plt.title("Real Power at substation")
plt.ylabel("substation real power (MW)")
pMW = [element / 10**6 for element in p]
pMWn = [element / 10**6 for element in pnew]
pw = plt.plot(pMW)
npw = plt.plot(pMWn)
plt.legend([pw[0], npw[0]], ['NO IVVC', 'WITH IVVC'],
bbox_to_anchor=(0., 0.915, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.1)
plt.savefig(pJoin(modelDir, "realPower.png"))
plt.figure("Reactive power")
plt.title("Reactive Power at substation")
plt.ylabel("substation reactive power (MVAR)")
qMVAR = [element / 10**6 for element in q]
qMVARn = [element / 10**6 for element in qnew]
iw = plt.plot(qMVAR)
niw = plt.plot(qMVARn)
plt.legend([iw[0], niw[0]], ['NO IVVC', 'WITH IVVC'],
bbox_to_anchor=(0., 0.915, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.1)
plt.savefig(pJoin(modelDir, "imaginaryPower.png"))
#voltage plots
plt.figure("voltages as a function of time")
f, ax = plt.subplots(2, sharex=True)
f.suptitle("Min and Max voltages on the feeder")
lv = ax[0].plot(lowVoltage, color='cadetblue')
mv = ax[0].plot(meanVoltage, color='blue')
hv = ax[0].plot(highVoltage, color='cadetblue')
ax[0].legend([lv[0], mv[0], hv[0]],
['low voltage', 'mean voltage', 'high voltage'],
bbox_to_anchor=(0., 0.915, 1., .1),
loc=3,
ncol=3,
mode="expand",
borderaxespad=0.1)
ax[0].set_ylabel('NO IVVC')
nlv = ax[1].plot(lowVoltagenew, color='cadetblue')
nmv = ax[1].plot(meanVoltagenew, color='blue')
nhv = ax[1].plot(highVoltagenew, color='cadetblue')
ax[1].set_ylabel('WITH IVVC')
plt.savefig(pJoin(modelDir, "Voltages.png"))
#tap positions
plt.figure("TAP positions NO IVVC")
f, ax = plt.subplots(6, sharex=True)
f.set_size_inches(10, 12.0)
#f.suptitle("Regulator Tap positions")
ax[0].plot(tap['A'])
ax[0].set_title("Regulator Tap positions NO IVVC")
ax[0].set_ylabel("TAP A")
ax[1].plot(tap['B'])
ax[1].set_ylabel("TAP B")
ax[2].plot(tap['C'])
ax[2].set_ylabel("TAP C")
ax[3].plot(tapnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel("TAP A")
ax[4].plot(tapnew['B'])
ax[4].set_ylabel("TAP B")
ax[5].plot(tapnew['C'])
ax[5].set_ylabel("TAP C")
for subplot in range(6):
ax[subplot].set_ylim(-20, 20)
f.tight_layout()
plt.savefig(pJoin(modelDir, "RegulatorTAPpositions.png"))
#substation voltages
plt.figure("substation voltage as a function of time")
f, ax = plt.subplots(6, sharex=True)
f.set_size_inches(10, 12.0)
#f.suptitle("voltages at substation NO IVVC")
ax[0].plot(volt['A'])
ax[0].set_title('Substation voltages NO IVVC')
ax[0].set_ylabel('voltage A')
ax[1].plot(volt['B'])
ax[1].set_ylabel('voltage B')
ax[2].plot(volt['C'])
ax[2].set_ylabel('voltage C')
ax[3].plot(voltnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel('voltage A')
ax[4].plot(voltnew['B'])
ax[4].set_ylabel('voltage B')
ax[5].plot(voltnew['C'])
ax[5].set_ylabel('voltage C')
f.tight_layout()
plt.savefig(pJoin(modelDir, "substationVoltages.png"))
#cap switches
plt.figure("capacitor switch state as a function of time")
f, ax = plt.subplots(6, sharex=True)
f.set_size_inches(10, 12.0)
#f.suptitle("Capacitor switch state NO IVVC")
ax[0].plot(switch['A'])
ax[0].set_title("Capacitor switch state NO IVVC")
ax[0].set_ylabel("switch A")
ax[1].plot(switch['B'])
ax[1].set_ylabel("switch B")
ax[2].plot(switch['C'])
ax[2].set_ylabel("switch C")
ax[3].plot(switchnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel("switch A")
ax[4].plot(switchnew['B'])
ax[4].set_ylabel("switch B")
ax[5].plot(switchnew['C'])
ax[5].set_ylabel("switch C")
for subplot in range(6):
ax[subplot].set_ylim(-2, 2)
f.tight_layout()
plt.savefig(pJoin(modelDir, "capacitorSwitch.png"))
#plt.show()
#monetization
monthNames = [
"January", "February", "March", "April", "May", "June", "July",
"August", "September", "October", "November", "December"
]
monthToSeason = {
'January': 'Winter',
'February': 'Winter',
'March': 'Spring',
'April': 'Spring',
'May': 'Spring',
'June': 'Summer',
'July': 'Summer',
'August': 'Summer',
'September': 'Fall',
'October': 'Fall',
'November': 'Fall',
'December': 'Winter'
}
#calculate the month and hour of simulation start and month and hour of simulation end
simStartTimestamp = simStartDate + " 00:00:00"
simFormattedDate = datetime.strptime(simStartTimestamp,
"%Y-%m-%d %H:%M:%S")
simStartMonthNum = int(simFormattedDate.strftime('%m'))
simstartMonth = monthNames[simStartMonthNum - 1]
simStartDay = int(simFormattedDate.strftime('%d'))
if calendar.isleap(int(simFormattedDate.strftime('%Y'))):
febDays = 29
else:
febDays = 28
monthHours = [
int(31 * 24),
int(febDays * 24),
int(31 * 24),
int(30 * 24),
int(31 * 24),
int(30 * 24),
int(31 * 24),
int(31 * 24),
int(30 * 24),
int(31 * 24),
int(30 * 24),
int(31 * 24)
]
simStartIndex = int(
sum(monthHours[:(simStartMonthNum - 1)]) + (simStartDay - 1) * 24)
temp = 0
cumulHours = [0]
for x in range(12):
temp += monthHours[x]
cumulHours.append(temp)
for i in range((simStartMonthNum), 13):
if int(simStartIndex + simRealLength) <= cumulHours[i] and int(
simStartIndex + simRealLength) > cumulHours[i - 1]:
simEndMonthNum = i - 1
simEndMonth = monthNames[simEndMonthNum]
# print simstartMonth,simEndMonth
#calculate peaks for the number of months in simulation
previndex = 0
monthPeak = {}
monthPeakNew = {}
peakSaveDollars = {}
energyLostDollars = {}
lossRedDollars = {}
simMonthList = monthNames[monthNames.index(simstartMonth):(
monthNames.index(simEndMonth) + 1)]
# print simMonthList
for monthElement in simMonthList:
# print monthElement
month = monthNames.index(monthElement)
index1 = int(previndex)
index2 = int(min((index1 + int(monthHours[month])), simRealLength))
monthPeak[monthElement] = max(p[index1:index2]) / 1000.0
monthPeakNew[monthElement] = max(pnew[index1:index2]) / 1000.0
peakSaveDollars[monthElement] = (
monthPeak[monthElement] - monthPeakNew[monthElement]) * float(
inData['peakDemandCost' +
str(monthToSeason[monthElement]) + 'PerKw'])
lossRedDollars[monthElement] = (
sum(realLoss[index1:index2]) / 1000.0 -
sum(realLossnew[index1:index2]) / 1000.0) * (float(
inData['wholesaleEnergyCostPerKwh']))
energyLostDollars[monthElement] = (
sum(p[index1:index2]) / 1000.0 - sum(pnew[index1:index2]) /
1000.0 - sum(realLoss[index1:index2]) / 1000.0 +
sum(realLossnew[index1:index2]) / 1000.0) * (
float(inData['wholesaleEnergyCostPerKwh']) -
float(inData['retailEnergyCostPerKwh']))
previndex = index2
#money charts
fig = plt.figure("cost benefit barchart", figsize=(10, 8))
ticks = range(len(simMonthList))
ticks1 = [element + 0.15 for element in ticks]
ticks2 = [element + 0.30 for element in ticks]
# print ticks
eld = [energyLostDollars[month] for month in simMonthList]
lrd = [lossRedDollars[month] for month in simMonthList]
psd = [peakSaveDollars[month] for month in simMonthList]
bar_eld = plt.bar(ticks, eld, 0.15, color='red')
bar_psd = plt.bar(ticks1, psd, 0.15, color='blue')
bar_lrd = plt.bar(ticks2, lrd, 0.15, color='green')
plt.legend([bar_eld[0], bar_psd[0], bar_lrd[0]], [
'energyLostDollars', 'peakReductionDollars', 'lossReductionDollars'
],
bbox_to_anchor=(0., 1.015, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.1)
monShort = [element[0:3] for element in simMonthList]
plt.xticks([t + 0.15 for t in ticks], monShort)
plt.ylabel('Utility Savings ($)')
plt.savefig(pJoin(modelDir, "spendChart.png"))
#cumulative savings graphs
fig = plt.figure("cost benefit barchart", figsize=(10, 5))
annualSavings = sum(eld) + sum(lrd) + sum(psd)
annualSave = lambda x: (annualSavings - float(inData['omCost'])
) * x - float(inData['capitalCost'])
simplePayback = float(
inData['capitalCost']) / (annualSavings - float(inData['omCost']))
plt.xlabel('Year After Installation')
plt.xlim(0, 30)
plt.ylabel('Cumulative Savings ($)')
plt.plot([0 for x in range(31)], c='gray')
plt.axvline(x=simplePayback, ymin=0, ymax=1, c='gray', linestyle='--')
plt.plot([annualSave(x) for x in range(31)], c='green')
plt.savefig(pJoin(modelDir, "savingsChart.png"))
#get exact time stamps from the CSV files generated by Gridlab-D
timeWithZone = output['Zregulator.csv']['# timestamp']
timestamps = [element[:19] for element in timeWithZone]
#data for highcharts
allOutput["timeStamps"] = timestamps
allOutput["noCVRPower"] = p
allOutput["withCVRPower"] = pnew
allOutput["noCVRLoad"] = whLoads[0]
allOutput["withCVRLoad"] = whLoads[1]
allOutput["noCVRLosses"] = whLosses[0]
allOutput["withCVRLosses"] = whLosses[1]
allOutput["noCVRTaps"] = tap
allOutput["withCVRTaps"] = tapnew
allOutput["noCVRSubVolts"] = volt
allOutput["withCVRSubVolts"] = voltnew
allOutput["noCVRCapSwitch"] = switch
allOutput["withCVRCapSwitch"] = switchnew
allOutput["noCVRHighVolt"] = highVoltage
allOutput["withCVRHighVolt"] = highVoltagenew
allOutput["noCVRLowVolt"] = lowVoltage
allOutput["withCVRLowVolt"] = lowVoltagenew
allOutput["noCVRMeanVolt"] = meanVoltage
allOutput["withCVRMeanVolt"] = meanVoltagenew
#monetization
allOutput["simMonthList"] = monShort
allOutput["energyLostDollars"] = energyLostDollars
allOutput["lossRedDollars"] = lossRedDollars
allOutput["peakSaveDollars"] = peakSaveDollars
allOutput["annualSave"] = [annualSave(x) for x in range(31)]
# Generate warnings
#TODO: Timezone adjustment
try:
# Check if times for simulation and scada match.
scadaDates = []
with open(pJoin(modelDir, "subScadaCalibrated1.player"),
"r") as scadaFile:
for line in scadaFile:
(date, val) = line.split(',')
scadaDates.append(str(date))
simFormattedEndDate = simFormattedDate + timedelta(hours=HOURS)
scadaStartDate = datetime.strptime(scadaDates[0].split(' PST')[0],
"%Y-%m-%d %H:%M:%S")
scadaEndDate = datetime.strptime(
scadaDates[len(scadaDates) - 1].split(' PST')[0],
"%Y-%m-%d %H:%M:%S")
beginRange = (scadaStartDate - simFormattedDate).total_seconds()
endRange = (scadaEndDate - simFormattedEndDate).total_seconds()
# Check if houses exist.
housesExist, voltageNodeExists = False, False
for key in localTree:
if localTree[key].get('object', '') == 'house':
housesExist = True
if localTree[key].get('name',
'') == str(inData.get("voltageNodes",
0)):
voltageNodeExists = True
if (beginRange > 0.0 or endRange < 0.0) and not housesExist:
allOutput[
"warnings"] = "<strong>WARNING:</strong> The simulation dates entered are not compatible with the scada curve in the feeder."
# Check if voltage node exists.
if not voltageNodeExists:
if allOutput.get('warnings', '') != "":
previousWarning = allOutput["warnings"]
allOutput[
"warnings"] = previousWarning + " The voltage node: " + str(
inData.get("voltageNodes",
0)) + " does not exist in the feeder."
else:
allOutput[
"warnings"] = "<strong>WARNING:</strong> The voltage node <i>" + str(
inData.get(
"voltageNodes",
0)) + "</i> does not exist in the feeder."
except:
pass
# Update the runTime in the input file.
endTime = datetime.now()
inData["runTime"] = str(
timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir, "allInputData.json"), "w") as inFile:
json.dump(inData, inFile, indent=4)
with open(pJoin(modelDir, "allOutputData.json"), "w") as outFile:
json.dump(allOutput, outFile, indent=4)
# For autotest, there won't be such file.
try:
os.remove(pJoin(modelDir, "PPID.txt"))
except Exception, e:
pass
print "DONE RUNNING", modelDir
def runForeground(modelDir, inputDict):
''' Run the model in its directory. WARNING: GRIDLAB CAN TAKE HOURS TO COMPLETE. '''
# Check whether model exist or not
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inputDict["created"] = str(datetime.datetime.now())
print "STARTING TO RUN", modelDir
beginTime = datetime.datetime.now()
feederList = []
# Get prepare of data and clean workspace if re-run, If re-run remove all the data in the subfolders
for dirs in os.listdir(modelDir):
if os.path.isdir(pJoin(modelDir, dirs)):
shutil.rmtree(pJoin(modelDir, dirs))
# Get each feeder, prepare data in separate folders, and run there.
for key in sorted(inputDict, key=inputDict.get):
if key.startswith("feederName"):
feederName = inputDict[key]
feederList.append(feederName)
try:
os.remove(pJoin(modelDir, feederName, "allOutputData.json"))
except Exception, e:
pass
if not os.path.isdir(pJoin(modelDir, feederName)):
os.makedirs(pJoin(modelDir, feederName)) # create subfolders for feeders
shutil.copy(pJoin(modelDir, feederName + ".omd"),
pJoin(modelDir, feederName, "feeder.omd"))
inputDict["climateName"], latforpvwatts = zipCodeToClimateName(inputDict["zipCode"])
shutil.copy(pJoin(__metaModel__._omfDir, "data", "Climate", inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, feederName, "climate.tmy2"))
try:
startTime = datetime.datetime.now()
feederJson = json.load(open(pJoin(modelDir, feederName, "feeder.omd")))
tree = feederJson["tree"]
# Set up GLM with correct time and recorders:
feeder.attachRecorders(tree, "Regulator", "object", "regulator")
feeder.attachRecorders(tree, "Capacitor", "object", "capacitor")
feeder.attachRecorders(tree, "Inverter", "object", "inverter")
feeder.attachRecorders(tree, "Windmill", "object", "windturb_dg")
feeder.attachRecorders(tree, "CollectorVoltage", None, None)
feeder.attachRecorders(tree, "Climate", "object", "climate")
feeder.attachRecorders(tree, "OverheadLosses", None, None)
feeder.attachRecorders(tree, "UndergroundLosses", None, None)
feeder.attachRecorders(tree, "TriplexLosses", None, None)
feeder.attachRecorders(tree, "TransformerLosses", None, None)
feeder.groupSwingKids(tree)
feeder.adjustTime(tree=tree, simLength=float(inputDict["simLength"]),
simLengthUnits=inputDict["simLengthUnits"], simStartDate=inputDict["simStartDate"])
# RUN GRIDLABD IN FILESYSTEM (EXPENSIVE!)
rawOut = gridlabd.runInFilesystem(tree, attachments=feederJson["attachments"],
keepFiles=True, workDir=pJoin(modelDir, feederName))
cleanOut = {}
# Std Err and Std Out
cleanOut['stderr'] = rawOut['stderr']
cleanOut['stdout'] = rawOut['stdout']
# Time Stamps
for key in rawOut:
if '# timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# timestamp']
break
elif '# property.. timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# property.. timestamp']
else:
cleanOut['timeStamps'] = []
# Day/Month Aggregation Setup:
stamps = cleanOut.get('timeStamps',[])
level = inputDict.get('simLengthUnits','hours')
# Climate
for key in rawOut:
if key.startswith('Climate_') and key.endswith('.csv'):
cleanOut['climate'] = {}
cleanOut['climate']['Rain Fall (in/h)'] = hdmAgg(rawOut[key].get('rainfall'), sum, level)
cleanOut['climate']['Wind Speed (m/s)'] = hdmAgg(rawOut[key].get('wind_speed'), avg, level)
cleanOut['climate']['Temperature (F)'] = hdmAgg(rawOut[key].get('temperature'), max, level)
cleanOut['climate']['Snow Depth (in)'] = hdmAgg(rawOut[key].get('snowdepth'), max, level)
cleanOut['climate']['Direct Insolation (W/m^2)'] = hdmAgg(rawOut[key].get('solar_direct'), sum, level)
# Voltage Band
if 'VoltageJiggle.csv' in rawOut:
cleanOut['allMeterVoltages'] = {}
cleanOut['allMeterVoltages']['Min'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['min(voltage_12.mag)']], min, level)
cleanOut['allMeterVoltages']['Mean'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['mean(voltage_12.mag)']], avg, level)
cleanOut['allMeterVoltages']['StdDev'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['std(voltage_12.mag)']], avg, level)
cleanOut['allMeterVoltages']['Max'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['max(voltage_12.mag)']], max, level)
cleanOut['allMeterVoltages']['stdDevPos'] = [(x+y/2) for x,y in zip(cleanOut['allMeterVoltages']['Mean'], cleanOut['allMeterVoltages']['StdDev'])]
cleanOut['allMeterVoltages']['stdDevNeg'] = [(x-y/2) for x,y in zip(cleanOut['allMeterVoltages']['Mean'], cleanOut['allMeterVoltages']['StdDev'])]
# Total # of meters
count = 0
with open(pJoin(modelDir, feederName, "feeder.omd")) as f:
for line in f:
if "\"objectType\": \"triplex_meter\"" in line:
count+=1
print "count=", count
cleanOut['allMeterVoltages']['triplexMeterCount'] = float(count)
# Power Consumption
cleanOut['Consumption'] = {}
# Set default value to be 0, avoiding missing value when computing Loads
cleanOut['Consumption']['Power'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['Losses'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['DG'] = [0] * int(inputDict["simLength"])
for key in rawOut:
if key.startswith('SwingKids_') and key.endswith('.csv'):
oneSwingPower = hdmAgg(vecPyth(rawOut[key]['sum(power_in.real)'],rawOut[key]['sum(power_in.imag)']), avg, level)
if 'Power' not in cleanOut['Consumption']:
cleanOut['Consumption']['Power'] = oneSwingPower
else:
cleanOut['Consumption']['Power'] = vecSum(oneSwingPower,cleanOut['Consumption']['Power'])
elif key.startswith('Inverter_') and key.endswith('.csv'):
realA = rawOut[key]['power_A.real']
realB = rawOut[key]['power_B.real']
realC = rawOut[key]['power_C.real']
imagA = rawOut[key]['power_A.imag']
imagB = rawOut[key]['power_B.imag']
imagC = rawOut[key]['power_C.imag']
oneDgPower = hdmAgg(vecSum(vecPyth(realA,imagA),vecPyth(realB,imagB),vecPyth(realC,imagC)), avg, level)
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(oneDgPower,cleanOut['Consumption']['DG'])
elif key.startswith('Windmill_') and key.endswith('.csv'):
vrA = rawOut[key]['voltage_A.real']
vrB = rawOut[key]['voltage_B.real']
vrC = rawOut[key]['voltage_C.real']
viA = rawOut[key]['voltage_A.imag']
viB = rawOut[key]['voltage_B.imag']
viC = rawOut[key]['voltage_C.imag']
crB = rawOut[key]['current_B.real']
crA = rawOut[key]['current_A.real']
crC = rawOut[key]['current_C.real']
ciA = rawOut[key]['current_A.imag']
ciB = rawOut[key]['current_B.imag']
ciC = rawOut[key]['current_C.imag']
powerA = vecProd(vecPyth(vrA,viA),vecPyth(crA,ciA))
powerB = vecProd(vecPyth(vrB,viB),vecPyth(crB,ciB))
powerC = vecProd(vecPyth(vrC,viC),vecPyth(crC,ciC))
# HACK: multiply by negative one because turbine power sign is opposite all other DG:
oneDgPower = [-1.0 * x for x in hdmAgg(vecSum(powerA,powerB,powerC), avg, level)]
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(oneDgPower,cleanOut['Consumption']['DG'])
elif key in ['OverheadLosses.csv', 'UndergroundLosses.csv', 'TriplexLosses.csv', 'TransformerLosses.csv']:
realA = rawOut[key]['sum(power_losses_A.real)']
imagA = rawOut[key]['sum(power_losses_A.imag)']
realB = rawOut[key]['sum(power_losses_B.real)']
imagB = rawOut[key]['sum(power_losses_B.imag)']
realC = rawOut[key]['sum(power_losses_C.real)']
imagC = rawOut[key]['sum(power_losses_C.imag)']
oneLoss = hdmAgg(vecSum(vecPyth(realA,imagA),vecPyth(realB,imagB),vecPyth(realC,imagC)), avg, level)
if 'Losses' not in cleanOut['Consumption']:
cleanOut['Consumption']['Losses'] = oneLoss
else:
cleanOut['Consumption']['Losses'] = vecSum(oneLoss,cleanOut['Consumption']['Losses'])
# Aggregate up the timestamps:
if level=='days':
cleanOut['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:10], 'days')
elif level=='months':
cleanOut['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:7], 'months')
# Write the output.
with open(pJoin(modelDir, feederName, "allOutputData.json"),"w") as outFile:
json.dump(cleanOut, outFile, indent=4)
# Update the runTime in the input file.
endTime = datetime.datetime.now()
inputDict["runTime"] = str(datetime.timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir, feederName, "allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent=4)
# Clean up the PID file.
os.remove(pJoin(modelDir, feederName,"PID.txt"))
print "DONE RUNNING GRIDLABMULTI", modelDir, feederName
except Exception as e:
print "MODEL CRASHED GRIDLABMULTI", e, modelDir, feederName
cancel(pJoin(modelDir, feederName))
with open(pJoin(modelDir, feederName, "stderr.txt"), "a+") as stderrFile:
traceback.print_exc(file = stderrFile)
def attachVolts(workDir, feederPath, voltVectorA, voltVectorB, voltVectorC, simStartDate, simLength, simLengthUnits):
'''read voltage vectors of 3 different phases, run gridlabd, and attach output to the feeder.'''
try:
timeStamp = [simStartDate['Date']]
for x in range (1, 8760):
timeStamp.append(timeStamp[x-1] + dt.timedelta(hours=1))
firstDateTime = timeStamp[1]
with open(pJoin(pJoin(workDir,"gridlabD"),"phaseAVoltage.player"),"w") as voltFile:
for x in range(0, 8760):
timestamp = timeStamp[x]
voltage = str("%0.2f"%float(voltVectorA[x]))+"+0j"
line = timestamp.strftime("%Y-%m-%d %H:%M:%S") + " " + simStartDate['timeZone'] + "," + str(voltage) + "\n"
voltFile.write(line)
with open(pJoin(pJoin(workDir,"gridlabD"),"phaseBVoltage.player"),"w") as voltFile:
for x in range(0, 8760):
timestamp = timeStamp[x]
voltage = str("%0.2f"%float(voltVectorB[x]))+"-"+str("%0.4f"%float(random.uniform(6449,6460)))+"j"
line = timestamp.strftime("%Y-%m-%d %H:%M:%S") + " " + simStartDate['timeZone'] + "," + str(voltage) + "\n"
voltFile.write(line)
with open(pJoin(pJoin(workDir,"gridlabD"),"phaseCVoltage.player"),"w") as voltFile:
for x in range(0, 8760):
timestamp = timeStamp[x]
voltage = str("%0.2f"%float(voltVectorC[x]))+"+"+str("%0.4f"%float(random.uniform(6449,6460)))+"j"
line = timestamp.strftime("%Y-%m-%d %H:%M:%S") + " " + simStartDate['timeZone'] + "," + str(voltage) + "\n"
voltFile.write(line)
with open(feederPath, "r") as jsonIn:
feederJson = json.load(jsonIn)
tree = feederJson.get("tree", {})
# Find swingNode name.
for key in tree:
if tree[key].get('bustype','').lower() == 'swing':
swingName = tree[key].get('name')
# Attach player.
classOb = {'omftype':'class player','argument':'{double value;}'}
voltageObA = {"object":"player", "property":"voltage_A", "file":"phaseAVoltage.player", "loop":"0", "parent":swingName}
voltageObB = {"object":"player", "property":"voltage_B", "file":"phaseBVoltage.player", "loop":"0", "parent":swingName}
voltageObC = {"object":"player", "property":"voltage_C", "file":"phaseCVoltage.player", "loop":"0", "parent":swingName}
maxKey = feeder.getMaxKey(tree)
voltplayerKeyA = maxKey + 2
voltplayerKeyB = maxKey + 3
voltplayerKeyC = maxKey + 4
tree[maxKey+1] = classOb
tree[voltplayerKeyA] = voltageObA
tree[voltplayerKeyB] = voltageObB
tree[voltplayerKeyC] = voltageObC
# Adjust time and run output.
feeder.adjustTime(tree, simLength, simLengthUnits, firstDateTime.strftime("%Y-%m-%d %H:%M:%S"))
output = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=pJoin(workDir,"gridlabD"))
# Write the output.
with open(pJoin(workDir,"calibratedFeeder.omd"),"w") as outJson:
playerStringA = open(pJoin(pJoin(workDir,"gridlabD"),"phaseAVoltage.player")).read()
playerStringB = open(pJoin(pJoin(workDir,"gridlabD"),"phaseBVoltage.player")).read()
playerStringC = open(pJoin(pJoin(workDir,"gridlabD"),"phaseCVoltage.player")).read()
feederJson["attachments"]["phaseAVoltage.player"] = playerStringA
feederJson["attachments"]["phaseBVoltage.player"] = playerStringB
feederJson["attachments"]["phaseCVoltage.player"] = playerStringC
feederJson["tree"] = tree
json.dump(feederJson, outJson, indent=4)
return pJoin(workDir,"calibratedFeeder.omd"), True
except:
print "Failed to run gridlabD with voltage players."
return "", False
def runForeground(modelDir, inputDict):
''' Run the model in the foreground. WARNING: can take about a minute. '''
# Global vars, and load data from the model directory.
print "STARTING TO RUN", modelDir
try:
startTime = datetime.datetime.now()
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inputDict["created"] = str(startTime)
feederName = inputDict.get('feederName1','feeder1')
feederPath = pJoin(modelDir,feederName+'.omd')
feederJson = json.load(open(feederPath))
tree = feederJson.get("tree",{})
attachments = feederJson.get("attachments",{})
allOutput = {}
''' Run CVR analysis. '''
# Reformate monthData and rates.
rates = {k:float(inputDict[k]) for k in ["capitalCost", "omCost", "wholesaleEnergyCostPerKwh",
"retailEnergyCostPerKwh", "peakDemandCostSpringPerKw", "peakDemandCostSummerPerKw",
"peakDemandCostFallPerKw", "peakDemandCostWinterPerKw"]}
# print "RATES", rates
monthNames = ["January", "February", "March", "April", "May", "June", "July", "August",
"September", "October", "November", "December"]
monthToSeason = {'January':'Winter','February':'Winter','March':'Spring','April':'Spring',
'May':'Spring','June':'Summer','July':'Summer','August':'Summer',
'September':'Fall','October':'Fall','November':'Fall','December':'Winter'}
monthData = []
for i, x in enumerate(monthNames):
monShort = x[0:3].lower()
season = monthToSeason[x]
histAvg = float(inputDict.get(monShort + "Avg", 0))
histPeak = float(inputDict.get(monShort + "Peak", 0))
monthData.append({"monthId":i, "monthName":x, "histAverage":histAvg,
"histPeak":histPeak, "season":season})
# for row in monthData:
# print row
# Graph the SCADA data.
fig = plt.figure(figsize=(10,6))
indices = [r['monthName'] for r in monthData]
d1 = [r['histPeak']/(10**3) for r in monthData]
d2 = [r['histAverage']/(10**3) for r in monthData]
ticks = range(len(d1))
bar_peak = plt.bar(ticks,d1,color='gray')
bar_avg = plt.bar(ticks,d2,color='dimgray')
plt.legend([bar_peak[0],bar_avg[0]],['histPeak','histAverage'],bbox_to_anchor=(0., 1.015, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
plt.xticks([t+0.5 for t in ticks],indices)
plt.ylabel('Mean and peak historical power consumptions (kW)')
fig.autofmt_xdate()
plt.savefig(pJoin(modelDir,"scadaChart.png"))
allOutput["histPeak"] = d1
allOutput["histAverage"] = d2
allOutput["monthName"] = [name[0:3] for name in monthNames]
# Graph feeder.
fig = plt.figure(figsize=(10,10))
myGraph = feeder.treeToNxGraph(tree)
feeder.latLonNxGraph(myGraph, neatoLayout=False)
plt.savefig(pJoin(modelDir,"feederChart.png"))
with open(pJoin(modelDir,"feederChart.png"),"rb") as inFile:
allOutput["feederChart"] = inFile.read().encode("base64")
# Get the load levels we need to test.
allLoadLevels = [x.get('histPeak',0) for x in monthData] + [y.get('histAverage',0) for y in monthData]
maxLev = _roundOne(max(allLoadLevels),'up')
minLev = _roundOne(min(allLoadLevels),'down')
tenLoadLevels = range(int(minLev),int(maxLev),int((maxLev-minLev)/10))
# Gather variables from the feeder.
for key in tree.keys():
# Set clock to single timestep.
if tree[key].get('clock','') == 'clock':
tree[key] = {"timezone":"PST+8PDT",
"stoptime":"'2013-01-01 00:00:00'",
"starttime":"'2013-01-01 00:00:00'",
"clock":"clock"}
# Save swing node index.
if tree[key].get('bustype','').lower() == 'swing':
swingIndex = key
swingName = tree[key].get('name')
# Remove all includes.
if tree[key].get('omftype','') == '#include':
del key
# Find the substation regulator and config.
for key in tree:
if tree[key].get('object','') == 'regulator' and tree[key].get('from','') == swingName:
regIndex = key
regConfName = tree[key]['configuration']
if not regConfName: regConfName = False
for key in tree:
if tree[key].get('name','') == regConfName:
regConfIndex = key
# Set substation regulator to manual operation.
baselineTap = int(inputDict.get("baselineTap")) # GLOBAL VARIABLE FOR DEFAULT TAP POSITION
tree[regConfIndex] = {
'name':tree[regConfIndex]['name'],
'object':'regulator_configuration',
'connect_type':'1',
'raise_taps':'10',
'lower_taps':'10',
'CT_phase':'ABC',
'PT_phase':'ABC',
'regulation':'0.10', #Yo, 0.10 means at tap_pos 10 we're 10% above 120V.
'Control':'MANUAL',
'control_level':'INDIVIDUAL',
'Type':'A',
'tap_pos_A':str(baselineTap),
'tap_pos_B':str(baselineTap),
'tap_pos_C':str(baselineTap) }
# Attach recorders relevant to CVR.
recorders = [
{'object': 'collector',
'file': 'ZlossesTransformer.csv',
'group': 'class=transformer',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesUnderground.csv',
'group': 'class=underground_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesOverhead.csv',
'group': 'class=overhead_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'recorder',
'file': 'Zregulator.csv',
'limit': '0',
'parent': tree[regIndex]['name'],
'property': 'tap_A,tap_B,tap_C,power_in.real,power_in.imag'},
{'object': 'collector',
'file': 'ZvoltageJiggle.csv',
'group': 'class=triplex_meter',
'limit': '0',
'property': 'min(voltage_12.mag),mean(voltage_12.mag),max(voltage_12.mag),std(voltage_12.mag)'},
{'object': 'recorder',
'file': 'ZsubstationTop.csv',
'limit': '0',
'parent': tree[swingIndex]['name'],
'property': 'voltage_A,voltage_B,voltage_C'},
{'object': 'recorder',
'file': 'ZsubstationBottom.csv',
'limit': '0',
'parent': tree[regIndex]['to'],
'property': 'voltage_A,voltage_B,voltage_C'} ]
biggest = 1 + max([int(k) for k in tree.keys()])
for index, rec in enumerate(recorders):
tree[biggest + index] = rec
# Change constant PF loads to ZIP loads. (See evernote for rationale about 50/50 power/impedance mix.)
blankZipModel = {'object':'triplex_load',
'name':'NAMEVARIABLE',
'base_power_12':'POWERVARIABLE',
'power_fraction_12': str(inputDict.get("p_percent")),
'impedance_fraction_12': str(inputDict.get("z_percent")),
'current_fraction_12': str(inputDict.get("i_percent")),
'power_pf_12': str(inputDict.get("power_factor")), #MAYBEFIX: we can probably get this PF data from the Milsoft loads.
'impedance_pf_12':str(inputDict.get("power_factor")),
'current_pf_12':str(inputDict.get("power_factor")),
'nominal_voltage':'120',
'phases':'PHASESVARIABLE',
'parent':'PARENTVARIABLE' }
def powerClean(powerStr):
''' take 3339.39+1052.29j to 3339.39 '''
return powerStr[0:powerStr.find('+')]
for key in tree:
if tree[key].get('object','') == 'triplex_node':
# Get existing variables.
name = tree[key].get('name','')
power = tree[key].get('power_12','')
parent = tree[key].get('parent','')
phases = tree[key].get('phases','')
# Replace object and reintroduce variables.
tree[key] = copy(blankZipModel)
tree[key]['name'] = name
tree[key]['base_power_12'] = powerClean(power)
tree[key]['parent'] = parent
tree[key]['phases'] = phases
# Function to determine how low we can tap down in the CVR case:
def loweringPotential(baseLine):
''' Given a baseline end of line voltage, how many more percent can we shave off the substation voltage? '''
''' testsWePass = [122.0,118.0,200.0,110.0] '''
lower = int(math.floor((baseLine/114.0-1)*100)) - 1
# If lower is negative, we can't return it because we'd be undervolting beyond what baseline already was!
if lower < 0:
return baselineTap
else:
return baselineTap - lower
# Run all the powerflows.
powerflows = []
for doingCvr in [False, True]:
# For each load level in the tenLoadLevels, run a powerflow with the load objects scaled to the level.
for desiredLoad in tenLoadLevels:
# Find the total load that was defined in Milsoft:
loadList = []
for key in tree:
if tree[key].get('object','') == 'triplex_load':
loadList.append(tree[key].get('base_power_12',''))
totalLoad = sum([float(x) for x in loadList])
# Rescale each triplex load:
for key in tree:
if tree[key].get('object','') == 'triplex_load':
currentPow = float(tree[key]['base_power_12'])
ratio = desiredLoad/totalLoad
tree[key]['base_power_12'] = str(currentPow*ratio)
# If we're doing CVR then lower the voltage.
if doingCvr:
# Find the minimum voltage we can tap down to:
newTapPos = baselineTap
for row in powerflows:
if row.get('loadLevel','') == desiredLoad:
newTapPos = loweringPotential(row.get('lowVoltage',114))
# Tap it down to there.
# MAYBEFIX: do each phase separately because that's how it's done in the field... Oof.
tree[regConfIndex]['tap_pos_A'] = str(newTapPos)
tree[regConfIndex]['tap_pos_B'] = str(newTapPos)
tree[regConfIndex]['tap_pos_C'] = str(newTapPos)
# Run the model through gridlab and put outputs in the table.
output = gridlabd.runInFilesystem(tree, attachments=attachments,
keepFiles=True, workDir=modelDir)
os.remove(pJoin(modelDir,"PID.txt"))
p = output['Zregulator.csv']['power_in.real'][0]
q = output['Zregulator.csv']['power_in.imag'][0]
s = math.sqrt(p**2+q**2)
lossTotal = 0.0
for device in ['ZlossesOverhead.csv','ZlossesTransformer.csv','ZlossesUnderground.csv']:
for letter in ['A','B','C']:
r = output[device]['sum(power_losses_' + letter + '.real)'][0]
i = output[device]['sum(power_losses_' + letter + '.imag)'][0]
lossTotal += math.sqrt(r**2 + i**2)
## Entire output:
powerflows.append({
'doingCvr':doingCvr,
'loadLevel':desiredLoad,
'realPower':p,
'powerFactor':p/s,
'losses':lossTotal,
'subVoltage': (
output['ZsubstationBottom.csv']['voltage_A'][0] +
output['ZsubstationBottom.csv']['voltage_B'][0] +
output['ZsubstationBottom.csv']['voltage_C'][0] )/3/60,
'lowVoltage':output['ZvoltageJiggle.csv']['min(voltage_12.mag)'][0]/2,
'highVoltage':output['ZvoltageJiggle.csv']['max(voltage_12.mag)'][0]/2 })
# For a given load level, find two points to interpolate on.
def getInterpPoints(t):
''' Find the two points we can interpolate from. '''
''' tests pass on [tenLoadLevels[0],tenLoadLevels[5]+499,tenLoadLevels[-1]-988] '''
loc = sorted(tenLoadLevels + [t]).index(t)
if loc==0:
return (tenLoadLevels[0],tenLoadLevels[1])
elif loc>len(tenLoadLevels)-2:
return (tenLoadLevels[-2],tenLoadLevels[-1])
else:
return (tenLoadLevels[loc-1],tenLoadLevels[loc+1])
# Calculate peak reduction.
for row in monthData:
peak = row['histPeak']
peakPoints = getInterpPoints(peak)
peakTopBase = [x for x in powerflows if x.get('loadLevel','') == peakPoints[-1] and x.get('doingCvr','') == False][0]
peakTopCvr = [x for x in powerflows if x.get('loadLevel','') == peakPoints[-1] and x.get('doingCvr','') == True][0]
peakBottomBase = [x for x in powerflows if x.get('loadLevel','') == peakPoints[0] and x.get('doingCvr','') == False][0]
peakBottomCvr = [x for x in powerflows if x.get('loadLevel','') == peakPoints[0] and x.get('doingCvr','') == True][0]
# Linear interpolation so we aren't running umpteen million loadflows.
x = (peakPoints[0],peakPoints[1])
y = (peakTopBase['realPower'] - peakTopCvr['realPower'],
peakBottomBase['realPower'] - peakBottomCvr['realPower'])
peakRed = y[0] + (y[1] - y[0]) * (peak - x[0]) / (x[1] - x[0])
row['peakReduction'] = peakRed
# Calculate energy reduction and loss reduction based on average load.
for row in monthData:
avgEnergy = row['histAverage']
energyPoints = getInterpPoints(avgEnergy)
avgTopBase = [x for x in powerflows if x.get('loadLevel','') == energyPoints[-1] and x.get('doingCvr','') == False][0]
avgTopCvr = [x for x in powerflows if x.get('loadLevel','') == energyPoints[-1] and x.get('doingCvr','') == True][0]
avgBottomBase = [x for x in powerflows if x.get('loadLevel','') == energyPoints[0] and x.get('doingCvr','') == False][0]
avgBottomCvr = [x for x in powerflows if x.get('loadLevel','') == energyPoints[0] and x.get('doingCvr','') == True][0]
# Linear interpolation so we aren't running umpteen million loadflows.
x = (energyPoints[0], energyPoints[1])
y = (avgTopBase['realPower'] - avgTopCvr['realPower'],
avgBottomBase['realPower'] - avgBottomCvr['realPower'])
energyRed = y[0] + (y[1] - y[0]) * (avgEnergy - x[0]) / (x[1] - x[0])
row['energyReduction'] = energyRed
lossY = (avgTopBase['losses'] - avgTopCvr['losses'],
avgBottomBase['losses'] - avgBottomCvr['losses'])
lossRed = lossY[0] + (lossY[1] - lossY[0]) * (avgEnergy - x[0]) / (x[1] - x[0])
row['lossReduction'] = lossRed
# Multiply by dollars.
for row in monthData:
row['energyReductionDollars'] = row['energyReduction']/1000 * (rates['wholesaleEnergyCostPerKwh'] - rates['retailEnergyCostPerKwh'])
row['peakReductionDollars'] = row['peakReduction']/1000 * rates['peakDemandCost' + row['season'] + 'PerKw']
row['lossReductionDollars'] = row['lossReduction']/1000 * rates['wholesaleEnergyCostPerKwh']
# Pretty output
def plotTable(inData):
fig = plt.figure(figsize=(10,5))
plt.axis('off')
plt.tight_layout()
plt.table(cellText=[row for row in inData[1:]],
loc = 'center',
rowLabels = range(len(inData)-1),
colLabels = inData[0])
def dictalToMatrix(dictList):
''' Take our dictal format to a matrix. '''
matrix = [dictList[0].keys()]
for row in dictList:
matrix.append(row.values())
return matrix
# Powerflow results.
plotTable(dictalToMatrix(powerflows))
plt.savefig(pJoin(modelDir,"powerflowTable.png"))
# Monetary results.
## To print partial money table
monthDataMat = dictalToMatrix(monthData)
dimX = len(monthDataMat)
dimY = len(monthDataMat[0])
monthDataPart = []
for k in range (0,dimX):
monthDatatemp = []
for m in range (4,dimY):
monthDatatemp.append(monthDataMat[k][m])
monthDataPart.append(monthDatatemp)
plotTable(monthDataPart)
plt.savefig(pJoin(modelDir,"moneyTable.png"))
allOutput["monthDataMat"] = dictalToMatrix(monthData)
allOutput["monthDataPart"] = monthDataPart
# Graph the money data.
fig = plt.figure(figsize=(10,8))
indices = [r['monthName'] for r in monthData]
d1 = [r['energyReductionDollars'] for r in monthData]
d2 = [r['lossReductionDollars'] for r in monthData]
d3 = [r['peakReductionDollars'] for r in monthData]
ticks = range(len(d1))
bar_erd = plt.bar(ticks,d1,color='red')
bar_lrd = plt.bar(ticks,d2,color='green')
bar_prd = plt.bar(ticks,d3,color='blue',yerr=d2)
plt.legend([bar_prd[0], bar_lrd[0], bar_erd[0]], ['peakReductionDollars','lossReductionDollars','energyReductionDollars'],bbox_to_anchor=(0., 1.015, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
plt.xticks([t+0.5 for t in ticks],indices)
plt.ylabel('Utility Savings ($)')
plt.tight_layout(5.5,1.3,1.2)
fig.autofmt_xdate()
plt.savefig(pJoin(modelDir,"spendChart.png"))
allOutput["energyReductionDollars"] = d1
allOutput["lossReductionDollars"] = d2
allOutput["peakReductionDollars"] = d3
# Graph the cumulative savings.
fig = plt.figure(figsize=(10,5))
annualSavings = sum(d1) + sum(d2) + sum(d3)
annualSave = lambda x:(annualSavings - rates['omCost']) * x - rates['capitalCost']
simplePayback = rates['capitalCost']/(annualSavings - rates['omCost'])
plt.xlabel('Year After Installation')
plt.xlim(0,30)
plt.ylabel('Cumulative Savings ($)')
plt.plot([0 for x in range(31)],c='gray')
plt.axvline(x=simplePayback, ymin=0, ymax=1, c='gray', linestyle='--')
plt.plot([annualSave(x) for x in range(31)], c='green')
plt.savefig(pJoin(modelDir,"savingsChart.png"))
allOutput["annualSave"] = [annualSave(x) for x in range(31)]
# Update the runTime in the input file.
endTime = datetime.datetime.now()
inputDict["runTime"] = str(datetime.timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir,"allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent=4)
# Write output file.
with open(pJoin(modelDir,"allOutputData.json"),"w") as outFile:
json.dump(allOutput, outFile, indent=4)
# For autotest, there won't be such file.
try:
os.remove(pJoin(modelDir, "PPID.txt"))
except:
pass
print "DONE RUNNING", modelDir
except Exception as e:
# If input range wasn't valid delete output, write error to disk.
cancel(modelDir)
thisErr = traceback.format_exc()
print 'ERROR IN MODEL', modelDir, thisErr
inputDict['stderr'] = thisErr
with open(os.path.join(modelDir,'stderr.txt'),'w') as errorFile:
errorFile.write(thisErr)
with open(pJoin(modelDir,"allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent=4)
def runModel(modelDir,localTree,inData):
'''This reads a glm file, changes the method of powerflow and reruns'''
try:
os.remove(pJoin(modelDir,"allOutputData.json"))
except:
pass
allOutput = {}
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inData["created"] = str(datetime.now())
with open(pJoin(modelDir,"allInputData.json"),"w") as inputFile:
json.dump(inData, inputFile, indent=4)
binaryName = "gridlabd"
for key in localTree:
if "solver_method" in localTree[key].keys():
print "current solver method", localTree[key]["solver_method"]
localTree[key]["solver_method"] = 'FBS'
#find the swing bus and recorder attached to substation
for key in localTree:
if localTree[key].get('bustype','').lower() == 'swing':
swingIndex = key
swingName = localTree[key].get('name')
if localTree[key].get('object','') == 'regulator' and localTree[key].get('from','') == swingName:
regIndex = key
regConfName = localTree[key]['configuration']
#find the regulator and capacitor names and combine to form a string for volt-var control object
regKeys = []
accum_reg = ""
for key in localTree:
if localTree[key].get("object","") == "regulator":
accum_reg += localTree[key].get("name","ERROR") + ","
regKeys.append(key)
regstr = accum_reg[:-1]
print regKeys
capKeys = []
accum_cap = ""
for key in localTree:
if localTree[key].get("object","") == "capacitor":
accum_cap += localTree[key].get("name","ERROR") + ","
capKeys.append(key)
if localTree[key].get("control","").lower() == "manual":
localTree[key]['control'] = "VOLT"
print "changing capacitor control from manual to volt"
capstr = accum_cap[:-1]
print capKeys
# Attach recorders relevant to CVR.
recorders = [
{'object': 'collector',
'file': 'ZlossesTransformer.csv',
'group': 'class=transformer',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesUnderground.csv',
'group': 'class=underground_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesOverhead.csv',
'group': 'class=overhead_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'recorder',
'file': 'Zregulator.csv',
'limit': '0',
'parent': localTree[regIndex]['name'],
'property': 'tap_A,tap_B,tap_C,power_in.real,power_in.imag'},
{'object': 'collector',
'file': 'ZvoltageJiggle.csv',
'group': 'class=triplex_meter',
'limit': '0',
'property': 'min(voltage_12.mag),mean(voltage_12.mag),max(voltage_12.mag),std(voltage_12.mag)'},
{'object': 'recorder',
'file': 'ZsubstationTop.csv',
'limit': '0',
'parent': localTree[swingIndex]['name'],
'property': 'voltage_A,voltage_B,voltage_C'},
{'object': 'recorder',
'file': 'ZsubstationBottom.csv',
'limit': '0',
'parent': localTree[regIndex]['to'],
'property': 'voltage_A,voltage_B,voltage_C'}]
#recorder object for capacitor switching - if capacitors exist
if capKeys != []:
for key in capKeys:
recorders.append({'object': 'recorder',
'file': 'ZcapSwitch' + str(key) + '.csv',
'limit': '0',
'parent': localTree[key]['name'],
'property': 'switchA,switchB,switchC'})
#attach recorder process
biggest = 1 + max([int(k) for k in localTree.keys()])
for index, rec in enumerate(recorders):
localTree[biggest + index] = rec
#run a reference load flow
HOURS = float(100)
year_lp = False #leap year
feeder.adjustTime(localTree,HOURS,"hours","2011-01-01")
output = gridlabd.runInFilesystem(localTree,keepFiles=False,workDir=modelDir)
os.remove(pJoin(modelDir,"PID.txt"))
p = output['Zregulator.csv']['power_in.real']
q = output['Zregulator.csv']['power_in.imag']
#time delays from configuration files
time_delay_reg = '30.0'
time_delay_cap = '300.0'
for key in localTree:
if localTree[key].get('object','') == "regulator_configuration":
time_delay_reg = localTree[key]['time_delay']
print "time_delay_reg",time_delay_reg
# if localTree[key].get('object','') == "capacitor":
# time_delay_cap = localTree[key]['time_delay']
# print "time_delay_cap",time_delay_cap
#change the recorder names
for key in localTree:
if localTree[key].get('object','') == "collector" or localTree[key].get('object','') == "recorder":
if localTree[key].get('file','').startswith('Z'):
localTree[key]['file'] = localTree[key].get('file','').replace('Z','NewZ')
#create volt-var control object
max_key = max([int(key) for key in localTree.keys()])
print max_key
localTree[max_key+1] = {'object' : 'volt_var_control',
'name' : 'IVVC1',
'control_method' : 'ACTIVE',
'capacitor_delay' : str(time_delay_cap),
'regulator_delay' : str(time_delay_reg),
'desired_pf' : '0.99',
'd_max' : '0.6',
'd_min' : '0.1',
'substation_link' : str(localTree[regIndex]['name']),
'regulator_list' : regstr,
'capacitor_list': capstr}
#running powerflow analysis via gridalab after attaching a regulator
feeder.adjustTime(localTree,HOURS,"hours","2011-01-01")
output1 = gridlabd.runInFilesystem(localTree,keepFiles=True,workDir=modelDir)
os.remove(pJoin(modelDir,"PID.txt"))
pnew = output1['NewZregulator.csv']['power_in.real']
qnew = output1['NewZregulator.csv']['power_in.imag']
#total real and imaginary losses as a function of time
realLoss = []
imagLoss = []
realLossnew = []
imagLossnew = []
for element in range(int(HOURS)):
r = 0.0
i = 0.0
rnew = 0.0
inew = 0.0
for device in ['ZlossesOverhead.csv','ZlossesTransformer.csv','ZlossesUnderground.csv']:
for letter in ['A','B','C']:
r += output[device]['sum(power_losses_' + letter + '.real)'][element]
i += output[device]['sum(power_losses_' + letter + '.imag)'][element]
rnew += output1['New'+device]['sum(power_losses_' + letter + '.real)'][element]
inew += output1['New'+device]['sum(power_losses_' + letter + '.imag)'][element]
realLoss.append(r)
imagLoss.append(i)
realLossnew.append(rnew)
imagLossnew.append(inew)
#voltage calculations and tap calculations
lowVoltage = []
meanVoltage = []
highVoltage = []
lowVoltagenew = []
meanVoltagenew = []
highVoltagenew = []
tap = {'A':[],'B':[],'C':[]}
tapnew = {'A':[],'B':[],'C':[]}
volt = {'A':[],'B':[],'C':[]}
voltnew = {'A':[],'B':[],'C':[]}
switch = {'A':[],'B':[],'C':[]}
switchnew = {'A':[],'B':[],'C':[]}
for element in range(int(HOURS)):
for letter in ['A','B','C']:
tap[letter].append(output['Zregulator.csv']['tap_' + letter][element])
tapnew[letter].append(output1['NewZregulator.csv']['tap_' + letter][element])
#voltage real, imag
vr, vi = sepRealImag(output['ZsubstationBottom.csv']['voltage_'+letter][element])
volt[letter].append(math.sqrt(vr**2+vi**2)/60)
vrnew, vinew = sepRealImag(output1['NewZsubstationBottom.csv']['voltage_'+letter][element])
voltnew[letter].append(math.sqrt(vrnew**2+vinew**2)/60)
if capKeys != []:
switch[letter].append(output['ZcapSwitch' + str(int(capKeys[0])) + '.csv']['switch'+ letter][element])
switchnew[letter].append(output1['NewZcapSwitch' + str(int(capKeys[0])) + '.csv']['switch'+ letter][element])
lowVoltage.append(float(output['ZvoltageJiggle.csv']['min(voltage_12.mag)'][element])/2.0)
meanVoltage.append(float(output['ZvoltageJiggle.csv']['mean(voltage_12.mag)'][element])/2.0)
highVoltage.append(float(output['ZvoltageJiggle.csv']['max(voltage_12.mag)'][element])/2.0)
lowVoltagenew.append(float(output1['NewZvoltageJiggle.csv']['min(voltage_12.mag)'][element])/2.0)
meanVoltagenew.append(float(output1['NewZvoltageJiggle.csv']['mean(voltage_12.mag)'][element])/2.0)
highVoltagenew.append(float(output1['NewZvoltageJiggle.csv']['max(voltage_12.mag)'][element])/2.0)
#energy calculations
whEnergy = []
whLosses = []
whLoads = []
whEnergy.append(sum(p)/10**6)
whLosses.append(sum(realLoss)/10**6)
whLoads.append((sum(p)-sum(realLoss))/10**6)
whEnergy.append(sum(pnew)/10**6)
whLosses.append(sum(realLossnew)/10**6)
whLoads.append((sum(pnew)-sum(realLossnew))/10**6)
indices = ['No IVVC', 'With IVVC']
# energySalesRed = (whLoads[1]-whLoads[0])*(inData['wholesaleEnergyCostPerKwh'])*1000
# lossSav = (whLosses[0]-whLosses[1])*inData['wholesaleEnergyCostPerKwh']*1000
# print energySalesRed, lossSav
#plots
ticks = []
plt.clf()
plt.title("total energy")
plt.ylabel("total load and losses (MWh)")
for element in range(2):
ticks.append(element)
bar_loss = plt.bar(element, whLosses[element], 0.15, color= 'red')
bar_load = plt.bar(element+0.15, whLoads[element], 0.15, color= 'orange')
plt.legend([bar_load[0],bar_loss[0]],['total load', 'total losses'],bbox_to_anchor=(0., 0.915, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
plt.xticks([t+0.15 for t in ticks],indices)
plt.savefig(pJoin(modelDir,"total energy.png"))
#real and imaginary power
plt.figure("real power")
plt.title("Real Power at substation")
plt.ylabel("substation real power (MW)")
pMW = [element/10**6 for element in p]
pMWn = [element/10**6 for element in pnew]
pw = plt.plot(pMW)
npw = plt.plot(pMWn)
plt.legend([pw[0], npw[0]], ['NO IVVC','WITH IVVC'],bbox_to_anchor=(0., 0.915, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
plt.savefig(pJoin(modelDir,"real power.png"))
plt.figure("Reactive power")
plt.title("Reactive Power at substation")
plt.ylabel("substation reactive power (MVAR)")
qMVAR = [element/10**6 for element in q]
qMVARn = [element/10**6 for element in qnew]
iw = plt.plot(qMVAR)
niw = plt.plot(qMVARn)
plt.legend([iw[0], niw[0]], ['NO IVVC','WITH IVVC'],bbox_to_anchor=(0., 0.915, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
plt.savefig(pJoin(modelDir,"imaginary power.png"))
#voltage plots
plt.figure("voltages as a function of time")
f,ax = plt.subplots(2,sharex=True)
f.suptitle("Voltages high and low")
lv = ax[0].plot(lowVoltage,color = 'cadetblue')
mv = ax[0].plot(meanVoltage,color = 'blue')
hv = ax[0].plot(highVoltage, color = 'cadetblue')
ax[0].legend([lv[0], mv[0], hv[0]], ['low voltage','mean voltage','high voltage'],bbox_to_anchor=(0., 0.915, 1., .1), loc=3,
ncol=3, mode="expand", borderaxespad=0.1)
ax[0].set_ylabel('NO IVVC')
nlv = ax[1].plot(lowVoltagenew,color = 'cadetblue')
nmv = ax[1].plot(meanVoltagenew,color = 'blue')
nhv = ax[1].plot(highVoltagenew, color = 'cadetblue')
ax[1].set_ylabel('WITH IVVC')
plt.savefig(pJoin(modelDir,"Voltages.png"))
#tap positions
plt.figure("TAP positions NO IVVC")
f,ax = plt.subplots(6,sharex=True)
f.set_size_inches(18.5,12.0)
#f.suptitle("Regulator Tap positions")
ax[0].plot(tap['A'])
ax[0].set_title("Regulator Tap positions NO IVVC")
ax[0].set_ylabel("TAP A")
ax[1].plot(tap['B'])
ax[1].set_ylabel("TAP B")
ax[2].plot(tap['C'])
ax[2].set_ylabel("TAP C")
ax[3].plot(tapnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel("TAP A")
ax[4].plot(tapnew['B'])
ax[4].set_ylabel("TAP B")
ax[5].plot(tapnew['C'])
ax[5].set_ylabel("TAP C")
for subplot in range(6):
ax[subplot].set_ylim(-20,20)
f.tight_layout()
plt.savefig(pJoin(modelDir,"Regulator TAP positions.png"))
#substation voltages
plt.figure("substation voltage as a function of time")
f,ax = plt.subplots(6,sharex=True)
f.set_size_inches(18.5,12.0)
#f.suptitle("voltages at substation NO IVVC")
ax[0].plot(volt['A'])
ax[0].set_title('Substation voltages NO IVVC')
ax[0].set_ylabel('voltage A')
ax[1].plot(volt['B'])
ax[1].set_ylabel('voltage B')
ax[2].plot(volt['C'])
ax[2].set_ylabel('voltage C')
ax[3].plot(voltnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel('voltage A')
ax[4].plot(voltnew['B'])
ax[4].set_ylabel('voltage B')
ax[5].plot(voltnew['C'])
ax[5].set_ylabel('voltage C')
f.tight_layout()
plt.savefig(pJoin(modelDir,"substation voltages.png"))
#cap switches - plotted if capacitors are present
if capKeys != []:
plt.figure("capacitor switch state as a function of time")
f,ax = plt.subplots(6,sharex=True)
f.set_size_inches(18.5,12.0)
#f.suptitle("Capacitor switch state NO IVVC")
ax[0].plot(switch['A'])
ax[0].set_title("Capacitor switch state NO IVVC")
ax[0].set_ylabel("switch A")
ax[1].plot(switch['B'])
ax[1].set_ylabel("switch B")
ax[2].plot(switch['C'])
ax[2].set_ylabel("switch C")
ax[3].plot(switchnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel("switch A")
ax[4].plot(switchnew['B'])
ax[4].set_ylabel("switch B")
ax[5].plot(switchnew['C'])
ax[5].set_ylabel("switch C")
for subplot in range(6):
ax[subplot].set_ylim(-2,2)
f.tight_layout()
plt.savefig(pJoin(modelDir,"capacitor switch.png"))
#plt.show()
#monetization
monthNames = ["January", "February", "March", "April", "May", "June", "July", "August",
"September", "October", "November", "December"]
monthToSeason = {'January':'Winter','February':'Winter','March':'Spring','April':'Spring',
'May':'Spring','June':'Summer','July':'Summer','August':'Summer',
'September':'Fall','October':'Fall','November':'Fall','December':'Winter'}
if year_lp == True:
febDays = 29
else:
febDays = 28
monthHours = [int(31*24),int(febDays*24),int(31*24),int(30*24),int(31*24),int(30*24),int(31*24),int(31*24),int(30*24),int(31*24),int(30*24),int(31*24)]
#find simulation months
temp = 0
cumulHours = []
for x in range(12):
temp += monthHours[x]
cumulHours.append(temp)
for i in range(12):
if i == 0:
lowval = 0
else:
lowval = cumulHours[i-1]
if HOURS<=cumulHours[i] and HOURS>=lowval:
hourMonth = monthNames[i]
hourIndex = i
#calculate peaks for the number of months in simulation
previndex = 0
monthPeak = {}
monthPeakNew = {}
peakSaveDollars = {}
energyLostDollars = {}
lossRedDollars = {}
for month in range(hourIndex+1):
index1 = int(previndex)
index2 = int(min((index1 + int(monthHours[month])), HOURS))
monthPeak[monthNames[month]] = max(p[index1:index2])/1000.0
monthPeakNew[monthNames[month]] = max(pnew[index1:index2])/1000.0
peakSaveDollars[monthNames[month]] = (monthPeak[monthNames[month]]-monthPeakNew[monthNames[month]])*inData['peakDemandCost'+str(monthToSeason[monthNames[month]])+'PerKw']
lossRedDollars[monthNames[month]] = (sum(realLoss[index1:index2])/1000.0 - sum(realLossnew[index1:index2])/1000.0)*(inData['wholesaleEnergyCostPerKwh'])
energyLostDollars[monthNames[month]] = (sum(p[index1:index2])/1000.0 - sum(pnew[index1:index2])/1000.0 - sum(realLoss[index1:index2])/1000.0
+ sum(realLossnew[index1:index2])/1000.0 )*(inData['wholesaleEnergyCostPerKwh'] - inData['retailEnergyCostPerKwh'])
previndex = index2
#money charts
simMonths = monthNames[:hourIndex+1]
fig = plt.figure("cost benefit barchart",figsize=(10,8))
ticks = range(len(simMonths))
ticks1 = [element+0.15 for element in ticks]
ticks2 = [element+0.30 for element in ticks]
print ticks
eld = [energyLostDollars[month] for month in simMonths]
lrd = [lossRedDollars[month] for month in simMonths]
psd = [peakSaveDollars[month] for month in simMonths]
bar_eld = plt.bar(ticks,eld,0.15,color='red')
bar_psd = plt.bar(ticks1,psd,0.15,color='blue')
bar_lrd = plt.bar(ticks2,lrd,0.15,color='green')
plt.legend([bar_eld[0], bar_psd[0], bar_lrd[0]], ['energyLostDollars','peakReductionDollars','lossReductionDollars'],bbox_to_anchor=(0., 1.015, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
monShort = [element[0:3] for element in simMonths]
plt.xticks([t+0.15 for t in ticks],monShort)
plt.ylabel('Utility Savings ($)')
plt.savefig(pJoin(modelDir,"spendChart.png"))
with open(pJoin(modelDir,"spendChart.png"),"rb") as inFile:
allOutput["spendChart"] = inFile.read().encode("base64")
#cumulative savings graphs
fig = plt.figure("cost benefit barchart",figsize=(10,5))
annualSavings = sum(eld) + sum(lrd) + sum(psd)
annualSave = lambda x:(annualSavings - inData['omCost']) * x - inData['capitalCost']
simplePayback = inData['capitalCost']/(annualSavings - inData['omCost'])
plt.xlabel('Year After Installation')
plt.xlim(0,30)
plt.ylabel('Cumulative Savings ($)')
plt.plot([0 for x in range(31)],c='gray')
plt.axvline(x=simplePayback, ymin=0, ymax=1, c='gray', linestyle='--')
plt.plot([annualSave(x) for x in range(31)], c='green')
plt.savefig(pJoin(modelDir,"savingsChart.png"))
with open(pJoin(modelDir,"savingsChart.png"),"rb") as inFile:
allOutput["savingsChart"] = inFile.read().encode("base64")
# Update the runTime in the input file.
# endTime = datetime.now()
# inDat["runTime"] = str(timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir,"allInputData.json"),"w") as inFile:
json.dump(inData, inFile, indent=4)
with open(pJoin(modelDir,"allOutputData.json"),"w") as outFile:
json.dump(allOutput, outFile, indent=4)
print "DONE RUNNING", modelDir
def heavyProcessing(modelDir, inputDict):
''' Run the model in its directory. WARNING: GRIDLAB CAN TAKE HOURS TO COMPLETE. '''
print "STARTING TO RUN", modelDir
beginTime = datetime.datetime.now()
# Get feeder name and data in.
try:
os.mkdir(pJoin(modelDir, 'gldContainer'))
except:
pass
feederDir, feederName = inputDict["feederName"].split("___")
shutil.copy(
pJoin(__metaModel__._omfDir, "data", "Feeder", feederDir,
feederName + ".json"), pJoin(modelDir, "feeder.json"))
shutil.copy(
pJoin(__metaModel__._omfDir, "data", "Climate",
inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, "gldContainer", "climate.tmy2"))
try:
startTime = datetime.datetime.now()
feederJson = json.load(open(pJoin(modelDir, "feeder.json")))
tree = feederJson["tree"]
# Set up GLM with correct time and recorders:
feeder.attachRecorders(tree, "Regulator", "object", "regulator")
feeder.attachRecorders(tree, "Capacitor", "object", "capacitor")
feeder.attachRecorders(tree, "Inverter", "object", "inverter")
feeder.attachRecorders(tree, "Windmill", "object", "windturb_dg")
feeder.attachRecorders(tree, "CollectorVoltage", None, None)
feeder.attachRecorders(tree, "Climate", "object", "climate")
feeder.attachRecorders(tree, "OverheadLosses", None, None)
feeder.attachRecorders(tree, "UndergroundLosses", None, None)
feeder.attachRecorders(tree, "TriplexLosses", None, None)
feeder.attachRecorders(tree, "TransformerLosses", None, None)
feeder.groupSwingKids(tree)
# Attach recorders for system voltage map:
stub = {
'object': 'group_recorder',
'group': '"class=node"',
'property': 'voltage_A',
'interval': 3600,
'file': 'aVoltDump.csv'
}
for phase in ['A', 'B', 'C']:
copyStub = dict(stub)
copyStub['property'] = 'voltage_' + phase
copyStub['file'] = phase.lower() + 'VoltDump.csv'
tree[feeder.getMaxKey(tree) + 1] = copyStub
feeder.adjustTime(tree=tree,
simLength=float(inputDict["simLength"]),
simLengthUnits=inputDict["simLengthUnits"],
simStartDate=inputDict["simStartDate"])
# RUN GRIDLABD IN FILESYSTEM (EXPENSIVE!)
rawOut = gridlabd.runInFilesystem(
tree,
attachments=feederJson["attachments"],
keepFiles=True,
workDir=pJoin(modelDir, 'gldContainer'))
cleanOut = {}
# Std Err and Std Out
cleanOut['stderr'] = rawOut['stderr']
cleanOut['stdout'] = rawOut['stdout']
# Time Stamps
for key in rawOut:
if '# timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# timestamp']
break
elif '# property.. timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# property.. timestamp']
else:
cleanOut['timeStamps'] = []
# Day/Month Aggregation Setup:
stamps = cleanOut.get('timeStamps', [])
level = inputDict.get('simLengthUnits', 'hours')
# Climate
for key in rawOut:
if key.startswith('Climate_') and key.endswith('.csv'):
cleanOut['climate'] = {}
cleanOut['climate']['Rain Fall (in/h)'] = hdmAgg(
rawOut[key].get('rainfall'), sum, level)
cleanOut['climate']['Wind Speed (m/s)'] = hdmAgg(
rawOut[key].get('wind_speed'), avg, level)
cleanOut['climate']['Temperature (F)'] = hdmAgg(
rawOut[key].get('temperature'), max, level)
cleanOut['climate']['Snow Depth (in)'] = hdmAgg(
rawOut[key].get('snowdepth'), max, level)
cleanOut['climate']['Direct Normal (W/sf)'] = hdmAgg(
rawOut[key].get('solar_direct'), sum, level)
#cleanOut['climate']['Global Horizontal (W/sf)'] = hdmAgg(rawOut[key].get('solar_global'), sum, level)
climateWbySFList = hdmAgg(rawOut[key].get('solar_global'), sum,
level)
#converting W/sf to W/sm
climateWbySMList = [x * 10.76392 for x in climateWbySFList]
cleanOut['climate'][
'Global Horizontal (W/sm)'] = climateWbySMList
# Voltage Band
if 'VoltageJiggle.csv' in rawOut:
cleanOut['allMeterVoltages'] = {}
cleanOut['allMeterVoltages']['Min'] = hdmAgg([
float(i / 2)
for i in rawOut['VoltageJiggle.csv']['min(voltage_12.mag)']
], min, level)
cleanOut['allMeterVoltages']['Mean'] = hdmAgg([
float(i / 2)
for i in rawOut['VoltageJiggle.csv']['mean(voltage_12.mag)']
], avg, level)
cleanOut['allMeterVoltages']['StdDev'] = hdmAgg([
float(i / 2)
for i in rawOut['VoltageJiggle.csv']['std(voltage_12.mag)']
], avg, level)
cleanOut['allMeterVoltages']['Max'] = hdmAgg([
float(i / 2)
for i in rawOut['VoltageJiggle.csv']['max(voltage_12.mag)']
], max, level)
# Power Consumption
cleanOut['Consumption'] = {}
# Set default value to be 0, avoiding missing value when computing Loads
cleanOut['Consumption']['Power'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['Losses'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['DG'] = [0] * int(inputDict["simLength"])
for key in rawOut:
if key.startswith('SwingKids_') and key.endswith('.csv'):
oneSwingPower = hdmAgg(
vecPyth(rawOut[key]['sum(power_in.real)'],
rawOut[key]['sum(power_in.imag)']), avg, level)
if 'Power' not in cleanOut['Consumption']:
cleanOut['Consumption']['Power'] = oneSwingPower
else:
cleanOut['Consumption']['Power'] = vecSum(
oneSwingPower, cleanOut['Consumption']['Power'])
elif key.startswith('Inverter_') and key.endswith('.csv'):
realA = rawOut[key]['power_A.real']
realB = rawOut[key]['power_B.real']
realC = rawOut[key]['power_C.real']
imagA = rawOut[key]['power_A.imag']
imagB = rawOut[key]['power_B.imag']
imagC = rawOut[key]['power_C.imag']
oneDgPower = hdmAgg(
vecSum(vecPyth(realA, imagA), vecPyth(realB, imagB),
vecPyth(realC, imagC)), avg, level)
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(
oneDgPower, cleanOut['Consumption']['DG'])
elif key.startswith('Windmill_') and key.endswith('.csv'):
vrA = rawOut[key]['voltage_A.real']
vrB = rawOut[key]['voltage_B.real']
vrC = rawOut[key]['voltage_C.real']
viA = rawOut[key]['voltage_A.imag']
viB = rawOut[key]['voltage_B.imag']
viC = rawOut[key]['voltage_C.imag']
crB = rawOut[key]['current_B.real']
crA = rawOut[key]['current_A.real']
crC = rawOut[key]['current_C.real']
ciA = rawOut[key]['current_A.imag']
ciB = rawOut[key]['current_B.imag']
ciC = rawOut[key]['current_C.imag']
powerA = vecProd(vecPyth(vrA, viA), vecPyth(crA, ciA))
powerB = vecProd(vecPyth(vrB, viB), vecPyth(crB, ciB))
powerC = vecProd(vecPyth(vrC, viC), vecPyth(crC, ciC))
oneDgPower = hdmAgg(vecSum(powerA, powerB, powerC), avg, level)
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(
oneDgPower, cleanOut['Consumption']['DG'])
elif key in [
'OverheadLosses.csv', 'UndergroundLosses.csv',
'TriplexLosses.csv', 'TransformerLosses.csv'
]:
realA = rawOut[key]['sum(power_losses_A.real)']
imagA = rawOut[key]['sum(power_losses_A.imag)']
realB = rawOut[key]['sum(power_losses_B.real)']
imagB = rawOut[key]['sum(power_losses_B.imag)']
realC = rawOut[key]['sum(power_losses_C.real)']
imagC = rawOut[key]['sum(power_losses_C.imag)']
oneLoss = hdmAgg(
vecSum(vecPyth(realA, imagA), vecPyth(realB, imagB),
vecPyth(realC, imagC)), avg, level)
if 'Losses' not in cleanOut['Consumption']:
cleanOut['Consumption']['Losses'] = oneLoss
else:
cleanOut['Consumption']['Losses'] = vecSum(
oneLoss, cleanOut['Consumption']['Losses'])
elif key.startswith('Regulator_') and key.endswith('.csv'):
#split function to strip off .csv from filename and user rest of the file name as key. for example- Regulator_VR10.csv -> key would be Regulator_VR10
regName = ""
regName = key
newkey = regName.split(".")[0]
cleanOut[newkey] = {}
cleanOut[newkey]['RegTapA'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['RegTapB'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['RegTapC'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['RegTapA'] = rawOut[key]['tap_A']
cleanOut[newkey]['RegTapB'] = rawOut[key]['tap_B']
cleanOut[newkey]['RegTapC'] = rawOut[key]['tap_C']
cleanOut[newkey]['RegPhases'] = rawOut[key]['phases'][0]
elif key.startswith('Capacitor_') and key.endswith('.csv'):
capName = ""
capName = key
newkey = capName.split(".")[0]
cleanOut[newkey] = {}
cleanOut[newkey]['Cap1A'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['Cap1B'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['Cap1C'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['Cap1A'] = rawOut[key]['switchA']
cleanOut[newkey]['Cap1B'] = rawOut[key]['switchB']
cleanOut[newkey]['Cap1C'] = rawOut[key]['switchC']
cleanOut[newkey]['CapPhases'] = rawOut[key]['phases'][0]
# What percentage of our keys have lat lon data?
latKeys = [
tree[key]['latitude'] for key in tree if 'latitude' in tree[key]
]
latPerc = 1.0 * len(latKeys) / len(tree)
if latPerc < 0.25: doNeato = True
else: doNeato = False
# Generate the frames for the system voltage map time traveling chart.
genTime = generateVoltChart(tree,
rawOut,
modelDir,
neatoLayout=doNeato)
cleanOut['genTime'] = genTime
# Aggregate up the timestamps:
if level == 'days':
cleanOut['timeStamps'] = aggSeries(stamps, stamps,
lambda x: x[0][0:10], 'days')
elif level == 'months':
cleanOut['timeStamps'] = aggSeries(stamps, stamps,
lambda x: x[0][0:7], 'months')
# Write the output.
with open(pJoin(modelDir, "allOutputData.json"), "w") as outFile:
json.dump(cleanOut, outFile, indent=4)
# Update the runTime in the input file.
endTime = datetime.datetime.now()
inputDict["runTime"] = str(
datetime.timedelta(seconds=int((endTime -
startTime).total_seconds())))
with open(pJoin(modelDir, "allInputData.json"), "w") as inFile:
json.dump(inputDict, inFile, indent=4)
# Clean up the PID file.
os.remove(pJoin(modelDir, "gldContainer", "PID.txt"))
print "DONE RUNNING", modelDir
except Exception as e:
print "MODEL CRASHED", e
# Cancel to get rid of extra background processes.
try:
os.remove(pJoin(modelDir, 'PPID.txt'))
except:
pass
thisErr = traceback.format_exc()
inputDict['stderr'] = thisErr
with open(os.path.join(modelDir, 'stderr.txt'), 'w') as errorFile:
errorFile.write(thisErr)
# Dump input with error included.
with open(pJoin(modelDir, "allInputData.json"), "w") as inFile:
json.dump(inputDict, inFile, indent=4)
finishTime = datetime.datetime.now()
inputDict["runTime"] = str(
datetime.timedelta(seconds=int((finishTime -
beginTime).total_seconds())))
with open(pJoin(modelDir, "allInputData.json"), "w") as inFile:
json.dump(inputDict, inFile, indent=4)
try:
os.remove(pJoin(modelDir, "PPID.txt"))
except:
pass
def _tests(Network, Equipment, keepFiles=True):
import os, json, traceback, shutil
from solvers import gridlabd
from matplotlib import pyplot as plt
import feeder
exceptionCount = 0
try:
#db_network = os.path.abspath('./uploads/IEEE13.mdb')
#db_equipment = os.path.abspath('./uploads/IEEE13.mdb')
prefix = str(Path("testPEC.py").resolve()).strip('scratch\cymeToGridlabTests\testPEC.py') + "\uploads\\"
db_network = "C" + prefix + Network
db_equipment = "C" + prefix + Equipment
id_feeder = '650'
conductors = prefix + "conductor_data.csv"
#print "dbnet", db_network
#print "eqnet", db_equipment
#print "conductors", conductors
#cyme_base, x, y = convertCymeModel(db_network, db_equipment, id_feeder, conductors)
cyme_base, x, y = convertCymeModel(str(db_network), str(db_equipment), test=True, type=2, feeder_id='CV160')
feeder.attachRecorders(cyme_base, "TriplexLosses", None, None)
feeder.attachRecorders(cyme_base, "TransformerLosses", None, None)
glmString = feeder.sortedWrite(cyme_base)
feederglm = "C:\Users\Asus\Documents\GitHub\omf\omf\uploads\PEC.glm"
#print "feeederglm", feederglm
gfile = open(feederglm, 'w')
gfile.write(glmString)
gfile.close()
#print 'WROTE GLM FOR'
outPrefix = "C:\Users\Asus\Documents\GitHub\omf\omf\scratch\cymeToGridlabTests\\"
try:
os.mkdir(outPrefix)
except:
pass # Directory already there.
'''Attempt to graph'''
try:
# Draw the GLM.
print "trying to graph"
myGraph = feeder.treeToNxGraph(cyme_base)
feeder.latLonNxGraph(myGraph, neatoLayout=False)
plt.savefig(outPrefix + "PEC.png")
print "outprefix", outPrefix + "PEC.png"
print 'DREW GLM OF'
except:
exceptionCount += 1
print 'FAILED DRAWING'
try:
# Run powerflow on the GLM.
output = gridlabd.runInFilesystem(glmString, keepFiles=False)
with open(outPrefix + "PEC.JSON",'w') as outFile:
json.dump(output, outFile, indent=4)
print 'RAN GRIDLAB ON\n'
except:
exceptionCount += 1
print 'POWERFLOW FAILED'
except:
print 'FAILED CONVERTING'
exceptionCount += 1
traceback.print_exc()
if not keepFiles:
shutil.rmtree(outPrefix)
return exceptionCount
'''db_network = os.path.abspath('./uploads/PasoRobles11cymsectiondevice[device]['phases']08.mdb')
def voltPlot(tree, workDir=None, neatoLayout=False):
''' Draw a color-coded map of the voltage drop on a feeder.
Returns a matplotlib object. '''
# Get rid of schedules and climate:
for key in tree.keys():
if tree[key].get("argument",
"") == "\"schedules.glm\"" or tree[key].get(
"tmyfile", "") != "":
del tree[key]
# Make sure we have a voltDump:
def safeInt(x):
try:
return int(x)
except:
return 0
biggestKey = max([safeInt(x) for x in tree.keys()])
tree[str(biggestKey * 10)] = {
"object": "voltdump",
"filename": "voltDump.csv"
}
# Run Gridlab.
if not workDir:
workDir = tempfile.mkdtemp()
print "gridlabD runInFilesystem with no specified workDir. Working in", workDir
gridlabOut = gridlabd.runInFilesystem(tree,
attachments=[],
workDir=workDir)
with open(pJoin(workDir, 'voltDump.csv'), 'r') as dumpFile:
reader = csv.reader(dumpFile)
reader.next() # Burn the header.
keys = reader.next()
voltTable = []
for row in reader:
rowDict = {}
for pos, key in enumerate(keys):
rowDict[key] = row[pos]
voltTable.append(rowDict)
# Calculate average node voltage deviation. First, helper functions.
def pythag(x, y):
''' For right triangle with sides a and b, return the hypotenuse. '''
return math.sqrt(x**2 + y**2)
def digits(x):
''' Returns number of digits before the decimal in the float x. '''
return math.ceil(math.log10(x + 1))
def avg(l):
''' Average of a list of ints or floats. '''
return sum(l) / len(l)
# Detect the feeder nominal voltage:
for key in tree:
ob = tree[key]
if type(ob) == dict and ob.get('bustype', '') == 'SWING':
feedVoltage = float(ob.get('nominal_voltage', 1))
# Tot it all up.
nodeVolts = {}
for row in voltTable:
allVolts = []
for phase in ['A', 'B', 'C']:
phaseVolt = pythag(float(row['volt' + phase + '_real']),
float(row['volt' + phase + '_imag']))
if phaseVolt != 0.0:
if digits(phaseVolt) > 3:
# Normalize to 120 V standard
phaseVolt = phaseVolt * (120 / feedVoltage)
allVolts.append(phaseVolt)
nodeVolts[row.get('node_name', '')] = avg(allVolts)
# Color nodes by VOLTAGE.
fGraph = feeder.treeToNxGraph(tree)
voltChart = plt.figure(figsize=(10, 10))
plt.axes(frameon=0)
plt.axis('off')
if neatoLayout:
# HACK: work on a new graph without attributes because graphViz tries to read attrs.
cleanG = nx.Graph(fGraph.edges())
cleanG.add_nodes_from(fGraph)
positions = nx.graphviz_layout(cleanG, prog='neato')
else:
positions = {n: fGraph.node[n].get('pos', (0, 0)) for n in fGraph}
edgeIm = nx.draw_networkx_edges(fGraph, positions)
nodeIm = nx.draw_networkx_nodes(
fGraph,
pos=positions,
node_color=[nodeVolts.get(n, 0) for n in fGraph.nodes()],
linewidths=0,
node_size=30,
cmap=plt.cm.jet)
plt.sci(nodeIm)
plt.clim(110, 130)
plt.colorbar()
return voltChart
def _tests(makeKey=False, runGridlabD=True, showGDLABResults=False, cleanUp=True):
'''Get and encrypt a .std/.seq files to a .json. cleanUp removes the unencrypted .glm and .json.
'''
# Inputs.
user = "******"
workDir = pJoin(os.getcwd())
try: os.mkdir(pJoin(os.getcwd(),'encryptedFiles'))
except: pass
if makeKey:
genKey(workDir, user)
print "Made a new key for user:"******"Read key for user:"******"Working on:", stdString+",",seqString
with open(pJoin("inFiles",stdString),'r') as stdFile, open(pJoin("inFiles",seqString),'r') as seqFile:
stdContents, seqContents = stdFile.read(), seqFile.read()
# print "First few lines before encryption:\n", stdContents[:100]
encData = encryptData(stdContents, key)
with open(pJoin(workDir, "encryptedFiles", "Encrypted_"+stdString),"w+") as encFile:
encFile.write(encData)
encData = encryptData(seqContents, key)
with open(pJoin(workDir, "encryptedFiles", "Encrypted_"+seqString),"w+") as encFile:
encFile.write(encData)
# print "First few lines after enc:\n", encData[:100]
# Read and decrypt to convert to a .glm.
with open(pJoin(workDir, "encryptedFiles", "Encrypted_"+stdString),'r') as inFile:
encStdContents = inFile.read()
with open(pJoin(workDir, "encryptedFiles", "Encrypted_"+seqString),'r') as inFile2:
encSeqContents = inFile2.read()
print "\nCreated encrypted files:", "Encrypted_"+stdString+",", "Encrypted_"+seqString
# Decrypt.
decStdContents = decryptData(encStdContents,key)
decSeqContents = decryptData(encSeqContents,key)
# print "First few lines after dec:\n", decStdContents[:100]
# Convert to .glm.
def runMilConvert(stdContents, seqContents):
myFeed, xScale, yScale = omf.milToGridlab.convert(stdContents,seqContents)
with open(pJoin(workDir,stdString.replace('.std','.glm')),'w') as outFile:
outFile.write(omf.feeder.sortedWrite(myFeed))
myGraph = omf.feeder.treeToNxGraph(myFeed)
omf.feeder.latLonNxGraph(myGraph, neatoLayout=False)
plt.savefig(pJoin(workDir,stdString.replace('.std','.png')))
plt.close()
if not os.path.isfile(pJoin(workDir,stdString.replace('.std','.glm'))):
runMilConvert(decStdContents, decSeqContents)
print "Converted std/seq to glm."
# Convert converted .glm to encrypted glm.
with open(pJoin(workDir,stdString.replace('.std','.glm')),'r') as inGLM:
glmContents = inGLM.read()
encData = encryptData(glmContents, key)
with open(pJoin(workDir, "encryptedFiles","Encrypted_"+stdString.replace('.std','.glm')),'w') as encFile:
encFile.write(encData)
print "Encrypted glm file:", stdString.replace('.std','.glm')
# Decrypt .glm, convert to .json.
with open(pJoin(workDir, "encryptedFiles", "Encrypted_"+stdString.replace('.std','.glm')),'r') as encFile:
encOutGlm = encFile.read()
outGlm = decryptData(encOutGlm,key)
newFeeder = gridlabImport(workDir, stdString.strip('.std'), outGlm)
# Run gridlabD on decrypted GLM.
if runGridlabD:
output = gridlabd.runInFilesystem(newFeeder['tree'], attachments=testAttachments, keepFiles=False)
if showGDLABResults:
print "[STDERR]\n", (output['stderr'])
print "[STDOUT]\n", (output['stdout'])
print 'RAN GRIDLAB ON', stdString
# Convert JSON to encrypted json.
with open(pJoin(workDir,stdString.replace('.std','.json')),'r') as encFile:
decJSON = encFile.read()
encData = encryptData(decJSON, key)
with open(pJoin(workDir,"encryptedFiles","Encrypted_"+stdString.replace('.std','.json')),'w') as encFile:
encFile.write(encData)
print "Encrypted JSON file:", stdString.replace('.std','.json')
# Clean up unencrypted .glm and .json.
if cleanUp:
try:
os.remove(pJoin(workDir,stdString.replace('.std','.glm')))
print "Removed unencrypted file:", stdString.replace('.std','.glm')
except: pass
try:
os.remove(pJoin(workDir,stdString.replace('.std','.json')))
print "Removed unencrypted file:", stdString.replace('.std','.json')
except: pass
print "\nDone with encrypting all test files."
except:
print "Failed to encrypt", stdString, seqString
exceptionCount += 1
traceback.print_exc()
return exceptionCount
def runModel(modelDir, localTree, inData):
'''This reads a glm file, changes the method of powerflow and reruns'''
try:
os.remove(pJoin(modelDir, "allOutputData.json"))
except:
pass
allOutput = {}
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inData["created"] = str(datetime.now())
with open(pJoin(modelDir, "allInputData.json"), "w") as inputFile:
json.dump(inData, inputFile, indent=4)
binaryName = "gridlabd"
for key in localTree:
if "solver_method" in localTree[key].keys():
print "current solver method", localTree[key]["solver_method"]
localTree[key]["solver_method"] = 'FBS'
#find the swing bus and recorder attached to substation
for key in localTree:
if localTree[key].get('bustype', '').lower() == 'swing':
swingIndex = key
swingName = localTree[key].get('name')
if localTree[key].get('object',
'') == 'regulator' and localTree[key].get(
'from', '') == swingName:
regIndex = key
regConfName = localTree[key]['configuration']
#find the regulator and capacitor names and combine to form a string for volt-var control object
regKeys = []
accum_reg = ""
for key in localTree:
if localTree[key].get("object", "") == "regulator":
accum_reg += localTree[key].get("name", "ERROR") + ","
regKeys.append(key)
regstr = accum_reg[:-1]
print regKeys
capKeys = []
accum_cap = ""
for key in localTree:
if localTree[key].get("object", "") == "capacitor":
accum_cap += localTree[key].get("name", "ERROR") + ","
capKeys.append(key)
if localTree[key].get("control", "").lower() == "manual":
localTree[key]['control'] = "VOLT"
print "changing capacitor control from manual to volt"
capstr = accum_cap[:-1]
print capKeys
# Attach recorders relevant to CVR.
recorders = [{
'object':
'collector',
'file':
'ZlossesTransformer.csv',
'group':
'class=transformer',
'limit':
'0',
'property':
'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'
}, {
'object':
'collector',
'file':
'ZlossesUnderground.csv',
'group':
'class=underground_line',
'limit':
'0',
'property':
'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'
}, {
'object':
'collector',
'file':
'ZlossesOverhead.csv',
'group':
'class=overhead_line',
'limit':
'0',
'property':
'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'
}, {
'object': 'recorder',
'file': 'Zregulator.csv',
'limit': '0',
'parent': localTree[regIndex]['name'],
'property': 'tap_A,tap_B,tap_C,power_in.real,power_in.imag'
}, {
'object':
'collector',
'file':
'ZvoltageJiggle.csv',
'group':
'class=triplex_meter',
'limit':
'0',
'property':
'min(voltage_12.mag),mean(voltage_12.mag),max(voltage_12.mag),std(voltage_12.mag)'
}, {
'object': 'recorder',
'file': 'ZsubstationTop.csv',
'limit': '0',
'parent': localTree[swingIndex]['name'],
'property': 'voltage_A,voltage_B,voltage_C'
}, {
'object': 'recorder',
'file': 'ZsubstationBottom.csv',
'limit': '0',
'parent': localTree[regIndex]['to'],
'property': 'voltage_A,voltage_B,voltage_C'
}]
#recorder object for capacitor switching - if capacitors exist
if capKeys != []:
for key in capKeys:
recorders.append({
'object': 'recorder',
'file': 'ZcapSwitch' + str(key) + '.csv',
'limit': '0',
'parent': localTree[key]['name'],
'property': 'switchA,switchB,switchC'
})
#attach recorder process
biggest = 1 + max([int(k) for k in localTree.keys()])
for index, rec in enumerate(recorders):
localTree[biggest + index] = rec
#run a reference load flow
HOURS = float(100)
year_lp = False #leap year
feeder.adjustTime(localTree, HOURS, "hours", "2011-01-01")
output = gridlabd.runInFilesystem(localTree,
keepFiles=False,
workDir=modelDir)
os.remove(pJoin(modelDir, "PID.txt"))
p = output['Zregulator.csv']['power_in.real']
q = output['Zregulator.csv']['power_in.imag']
#time delays from configuration files
time_delay_reg = '30.0'
time_delay_cap = '300.0'
for key in localTree:
if localTree[key].get('object', '') == "regulator_configuration":
time_delay_reg = localTree[key]['time_delay']
print "time_delay_reg", time_delay_reg
# if localTree[key].get('object','') == "capacitor":
# time_delay_cap = localTree[key]['time_delay']
# print "time_delay_cap",time_delay_cap
#change the recorder names
for key in localTree:
if localTree[key].get('object',
'') == "collector" or localTree[key].get(
'object', '') == "recorder":
if localTree[key].get('file', '').startswith('Z'):
localTree[key]['file'] = localTree[key].get('file',
'').replace(
'Z', 'NewZ')
#create volt-var control object
max_key = max([int(key) for key in localTree.keys()])
print max_key
localTree[max_key + 1] = {
'object': 'volt_var_control',
'name': 'IVVC1',
'control_method': 'ACTIVE',
'capacitor_delay': str(time_delay_cap),
'regulator_delay': str(time_delay_reg),
'desired_pf': '0.99',
'd_max': '0.6',
'd_min': '0.1',
'substation_link': str(localTree[regIndex]['name']),
'regulator_list': regstr,
'capacitor_list': capstr
}
#running powerflow analysis via gridalab after attaching a regulator
feeder.adjustTime(localTree, HOURS, "hours", "2011-01-01")
output1 = gridlabd.runInFilesystem(localTree,
keepFiles=True,
workDir=modelDir)
os.remove(pJoin(modelDir, "PID.txt"))
pnew = output1['NewZregulator.csv']['power_in.real']
qnew = output1['NewZregulator.csv']['power_in.imag']
#total real and imaginary losses as a function of time
realLoss = []
imagLoss = []
realLossnew = []
imagLossnew = []
for element in range(int(HOURS)):
r = 0.0
i = 0.0
rnew = 0.0
inew = 0.0
for device in [
'ZlossesOverhead.csv', 'ZlossesTransformer.csv',
'ZlossesUnderground.csv'
]:
for letter in ['A', 'B', 'C']:
r += output[device]['sum(power_losses_' + letter +
'.real)'][element]
i += output[device]['sum(power_losses_' + letter +
'.imag)'][element]
rnew += output1['New' + device]['sum(power_losses_' + letter +
'.real)'][element]
inew += output1['New' + device]['sum(power_losses_' + letter +
'.imag)'][element]
realLoss.append(r)
imagLoss.append(i)
realLossnew.append(rnew)
imagLossnew.append(inew)
#voltage calculations and tap calculations
lowVoltage = []
meanVoltage = []
highVoltage = []
lowVoltagenew = []
meanVoltagenew = []
highVoltagenew = []
tap = {'A': [], 'B': [], 'C': []}
tapnew = {'A': [], 'B': [], 'C': []}
volt = {'A': [], 'B': [], 'C': []}
voltnew = {'A': [], 'B': [], 'C': []}
switch = {'A': [], 'B': [], 'C': []}
switchnew = {'A': [], 'B': [], 'C': []}
for element in range(int(HOURS)):
for letter in ['A', 'B', 'C']:
tap[letter].append(output['Zregulator.csv']['tap_' +
letter][element])
tapnew[letter].append(
output1['NewZregulator.csv']['tap_' + letter][element])
#voltage real, imag
vr, vi = sepRealImag(
output['ZsubstationBottom.csv']['voltage_' + letter][element])
volt[letter].append(math.sqrt(vr**2 + vi**2) / 60)
vrnew, vinew = sepRealImag(
output1['NewZsubstationBottom.csv']['voltage_' +
letter][element])
voltnew[letter].append(math.sqrt(vrnew**2 + vinew**2) / 60)
if capKeys != []:
switch[letter].append(
output['ZcapSwitch' + str(int(capKeys[0])) +
'.csv']['switch' + letter][element])
switchnew[letter].append(
output1['NewZcapSwitch' + str(int(capKeys[0])) +
'.csv']['switch' + letter][element])
lowVoltage.append(
float(output['ZvoltageJiggle.csv']['min(voltage_12.mag)'][element])
/ 2.0)
meanVoltage.append(
float(
output['ZvoltageJiggle.csv']['mean(voltage_12.mag)'][element])
/ 2.0)
highVoltage.append(
float(output['ZvoltageJiggle.csv']['max(voltage_12.mag)'][element])
/ 2.0)
lowVoltagenew.append(
float(output1['NewZvoltageJiggle.csv']['min(voltage_12.mag)']
[element]) / 2.0)
meanVoltagenew.append(
float(output1['NewZvoltageJiggle.csv']['mean(voltage_12.mag)']
[element]) / 2.0)
highVoltagenew.append(
float(output1['NewZvoltageJiggle.csv']['max(voltage_12.mag)']
[element]) / 2.0)
#energy calculations
whEnergy = []
whLosses = []
whLoads = []
whEnergy.append(sum(p) / 10**6)
whLosses.append(sum(realLoss) / 10**6)
whLoads.append((sum(p) - sum(realLoss)) / 10**6)
whEnergy.append(sum(pnew) / 10**6)
whLosses.append(sum(realLossnew) / 10**6)
whLoads.append((sum(pnew) - sum(realLossnew)) / 10**6)
indices = ['No IVVC', 'With IVVC']
# energySalesRed = (whLoads[1]-whLoads[0])*(inData['wholesaleEnergyCostPerKwh'])*1000
# lossSav = (whLosses[0]-whLosses[1])*inData['wholesaleEnergyCostPerKwh']*1000
# print energySalesRed, lossSav
#plots
ticks = []
plt.clf()
plt.title("total energy")
plt.ylabel("total load and losses (MWh)")
for element in range(2):
ticks.append(element)
bar_loss = plt.bar(element, whLosses[element], 0.15, color='red')
bar_load = plt.bar(element + 0.15,
whLoads[element],
0.15,
color='orange')
plt.legend([bar_load[0], bar_loss[0]], ['total load', 'total losses'],
bbox_to_anchor=(0., 0.915, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.1)
plt.xticks([t + 0.15 for t in ticks], indices)
plt.savefig(pJoin(modelDir, "total energy.png"))
#real and imaginary power
plt.figure("real power")
plt.title("Real Power at substation")
plt.ylabel("substation real power (MW)")
pMW = [element / 10**6 for element in p]
pMWn = [element / 10**6 for element in pnew]
pw = plt.plot(pMW)
npw = plt.plot(pMWn)
plt.legend([pw[0], npw[0]], ['NO IVVC', 'WITH IVVC'],
bbox_to_anchor=(0., 0.915, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.1)
plt.savefig(pJoin(modelDir, "real power.png"))
plt.figure("Reactive power")
plt.title("Reactive Power at substation")
plt.ylabel("substation reactive power (MVAR)")
qMVAR = [element / 10**6 for element in q]
qMVARn = [element / 10**6 for element in qnew]
iw = plt.plot(qMVAR)
niw = plt.plot(qMVARn)
plt.legend([iw[0], niw[0]], ['NO IVVC', 'WITH IVVC'],
bbox_to_anchor=(0., 0.915, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.1)
plt.savefig(pJoin(modelDir, "imaginary power.png"))
#voltage plots
plt.figure("voltages as a function of time")
f, ax = plt.subplots(2, sharex=True)
f.suptitle("Voltages high and low")
lv = ax[0].plot(lowVoltage, color='cadetblue')
mv = ax[0].plot(meanVoltage, color='blue')
hv = ax[0].plot(highVoltage, color='cadetblue')
ax[0].legend([lv[0], mv[0], hv[0]],
['low voltage', 'mean voltage', 'high voltage'],
bbox_to_anchor=(0., 0.915, 1., .1),
loc=3,
ncol=3,
mode="expand",
borderaxespad=0.1)
ax[0].set_ylabel('NO IVVC')
nlv = ax[1].plot(lowVoltagenew, color='cadetblue')
nmv = ax[1].plot(meanVoltagenew, color='blue')
nhv = ax[1].plot(highVoltagenew, color='cadetblue')
ax[1].set_ylabel('WITH IVVC')
plt.savefig(pJoin(modelDir, "Voltages.png"))
#tap positions
plt.figure("TAP positions NO IVVC")
f, ax = plt.subplots(6, sharex=True)
f.set_size_inches(18.5, 12.0)
#f.suptitle("Regulator Tap positions")
ax[0].plot(tap['A'])
ax[0].set_title("Regulator Tap positions NO IVVC")
ax[0].set_ylabel("TAP A")
ax[1].plot(tap['B'])
ax[1].set_ylabel("TAP B")
ax[2].plot(tap['C'])
ax[2].set_ylabel("TAP C")
ax[3].plot(tapnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel("TAP A")
ax[4].plot(tapnew['B'])
ax[4].set_ylabel("TAP B")
ax[5].plot(tapnew['C'])
ax[5].set_ylabel("TAP C")
for subplot in range(6):
ax[subplot].set_ylim(-20, 20)
f.tight_layout()
plt.savefig(pJoin(modelDir, "Regulator TAP positions.png"))
#substation voltages
plt.figure("substation voltage as a function of time")
f, ax = plt.subplots(6, sharex=True)
f.set_size_inches(18.5, 12.0)
#f.suptitle("voltages at substation NO IVVC")
ax[0].plot(volt['A'])
ax[0].set_title('Substation voltages NO IVVC')
ax[0].set_ylabel('voltage A')
ax[1].plot(volt['B'])
ax[1].set_ylabel('voltage B')
ax[2].plot(volt['C'])
ax[2].set_ylabel('voltage C')
ax[3].plot(voltnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel('voltage A')
ax[4].plot(voltnew['B'])
ax[4].set_ylabel('voltage B')
ax[5].plot(voltnew['C'])
ax[5].set_ylabel('voltage C')
f.tight_layout()
plt.savefig(pJoin(modelDir, "substation voltages.png"))
#cap switches - plotted if capacitors are present
if capKeys != []:
plt.figure("capacitor switch state as a function of time")
f, ax = plt.subplots(6, sharex=True)
f.set_size_inches(18.5, 12.0)
#f.suptitle("Capacitor switch state NO IVVC")
ax[0].plot(switch['A'])
ax[0].set_title("Capacitor switch state NO IVVC")
ax[0].set_ylabel("switch A")
ax[1].plot(switch['B'])
ax[1].set_ylabel("switch B")
ax[2].plot(switch['C'])
ax[2].set_ylabel("switch C")
ax[3].plot(switchnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel("switch A")
ax[4].plot(switchnew['B'])
ax[4].set_ylabel("switch B")
ax[5].plot(switchnew['C'])
ax[5].set_ylabel("switch C")
for subplot in range(6):
ax[subplot].set_ylim(-2, 2)
f.tight_layout()
plt.savefig(pJoin(modelDir, "capacitor switch.png"))
#plt.show()
#monetization
monthNames = [
"January", "February", "March", "April", "May", "June", "July",
"August", "September", "October", "November", "December"
]
monthToSeason = {
'January': 'Winter',
'February': 'Winter',
'March': 'Spring',
'April': 'Spring',
'May': 'Spring',
'June': 'Summer',
'July': 'Summer',
'August': 'Summer',
'September': 'Fall',
'October': 'Fall',
'November': 'Fall',
'December': 'Winter'
}
if year_lp == True:
febDays = 29
else:
febDays = 28
monthHours = [
int(31 * 24),
int(febDays * 24),
int(31 * 24),
int(30 * 24),
int(31 * 24),
int(30 * 24),
int(31 * 24),
int(31 * 24),
int(30 * 24),
int(31 * 24),
int(30 * 24),
int(31 * 24)
]
#find simulation months
temp = 0
cumulHours = []
for x in range(12):
temp += monthHours[x]
cumulHours.append(temp)
for i in range(12):
if i == 0:
lowval = 0
else:
lowval = cumulHours[i - 1]
if HOURS <= cumulHours[i] and HOURS >= lowval:
hourMonth = monthNames[i]
hourIndex = i
#calculate peaks for the number of months in simulation
previndex = 0
monthPeak = {}
monthPeakNew = {}
peakSaveDollars = {}
energyLostDollars = {}
lossRedDollars = {}
for month in range(hourIndex + 1):
index1 = int(previndex)
index2 = int(min((index1 + int(monthHours[month])), HOURS))
monthPeak[monthNames[month]] = max(p[index1:index2]) / 1000.0
monthPeakNew[monthNames[month]] = max(pnew[index1:index2]) / 1000.0
peakSaveDollars[monthNames[month]] = (
monthPeak[monthNames[month]] - monthPeakNew[monthNames[month]]
) * inData['peakDemandCost' + str(monthToSeason[monthNames[month]]) +
'PerKw']
lossRedDollars[
monthNames[month]] = (sum(realLoss[index1:index2]) / 1000.0 -
sum(realLossnew[index1:index2]) / 1000.0) * (
inData['wholesaleEnergyCostPerKwh'])
energyLostDollars[monthNames[month]] = (
sum(p[index1:index2]) / 1000.0 - sum(pnew[index1:index2]) / 1000.0
- sum(realLoss[index1:index2]) / 1000.0 +
sum(realLossnew[index1:index2]) / 1000.0) * (
inData['wholesaleEnergyCostPerKwh'] -
inData['retailEnergyCostPerKwh'])
previndex = index2
#money charts
simMonths = monthNames[:hourIndex + 1]
fig = plt.figure("cost benefit barchart", figsize=(10, 8))
ticks = range(len(simMonths))
ticks1 = [element + 0.15 for element in ticks]
ticks2 = [element + 0.30 for element in ticks]
print ticks
eld = [energyLostDollars[month] for month in simMonths]
lrd = [lossRedDollars[month] for month in simMonths]
psd = [peakSaveDollars[month] for month in simMonths]
bar_eld = plt.bar(ticks, eld, 0.15, color='red')
bar_psd = plt.bar(ticks1, psd, 0.15, color='blue')
bar_lrd = plt.bar(ticks2, lrd, 0.15, color='green')
plt.legend(
[bar_eld[0], bar_psd[0], bar_lrd[0]],
['energyLostDollars', 'peakReductionDollars', 'lossReductionDollars'],
bbox_to_anchor=(0., 1.015, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.1)
monShort = [element[0:3] for element in simMonths]
plt.xticks([t + 0.15 for t in ticks], monShort)
plt.ylabel('Utility Savings ($)')
plt.savefig(pJoin(modelDir, "spendChart.png"))
with open(pJoin(modelDir, "spendChart.png"), "rb") as inFile:
allOutput["spendChart"] = inFile.read().encode("base64")
#cumulative savings graphs
fig = plt.figure("cost benefit barchart", figsize=(10, 5))
annualSavings = sum(eld) + sum(lrd) + sum(psd)
annualSave = lambda x: (annualSavings - inData['omCost']) * x - inData[
'capitalCost']
simplePayback = inData['capitalCost'] / (annualSavings - inData['omCost'])
plt.xlabel('Year After Installation')
plt.xlim(0, 30)
plt.ylabel('Cumulative Savings ($)')
plt.plot([0 for x in range(31)], c='gray')
plt.axvline(x=simplePayback, ymin=0, ymax=1, c='gray', linestyle='--')
plt.plot([annualSave(x) for x in range(31)], c='green')
plt.savefig(pJoin(modelDir, "savingsChart.png"))
with open(pJoin(modelDir, "savingsChart.png"), "rb") as inFile:
allOutput["savingsChart"] = inFile.read().encode("base64")
# Update the runTime in the input file.
# endTime = datetime.now()
# inDat["runTime"] = str(timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir, "allInputData.json"), "w") as inFile:
json.dump(inData, inFile, indent=4)
with open(pJoin(modelDir, "allOutputData.json"), "w") as outFile:
json.dump(allOutput, outFile, indent=4)
print "DONE RUNNING", modelDir
def _tests(Network, Equipment, keepFiles=True):
import os, json, traceback, shutil
from solvers import gridlabd
from matplotlib import pyplot as plt
import feeder
exceptionCount = 0
try:
#db_network = os.path.abspath('./uploads/IEEE13.mdb')
#db_equipment = os.path.abspath('./uploads/IEEE13.mdb')
prefix = str(Path("testPEC.py").resolve()).strip(
'scratch\cymeToGridlabTests\testPEC.py') + "\uploads\\"
db_network = "C" + prefix + Network
db_equipment = "C" + prefix + Equipment
id_feeder = '650'
conductors = prefix + "conductor_data.csv"
#print "dbnet", db_network
#print "eqnet", db_equipment
#print "conductors", conductors
#cyme_base, x, y = convertCymeModel(db_network, db_equipment, id_feeder, conductors)
cyme_base, x, y = convertCymeModel(str(db_network),
str(db_equipment),
test=True,
type=2,
feeder_id='CV160')
feeder.attachRecorders(cyme_base, "TriplexLosses", None, None)
feeder.attachRecorders(cyme_base, "TransformerLosses", None, None)
glmString = feeder.sortedWrite(cyme_base)
feederglm = "C:\Users\Asus\Documents\GitHub\omf\omf\uploads\PEC.glm"
#print "feeederglm", feederglm
gfile = open(feederglm, 'w')
gfile.write(glmString)
gfile.close()
#print 'WROTE GLM FOR'
outPrefix = "C:\Users\Asus\Documents\GitHub\omf\omf\scratch\cymeToGridlabTests\\"
try:
os.mkdir(outPrefix)
except:
pass # Directory already there.
'''Attempt to graph'''
try:
# Draw the GLM.
print "trying to graph"
myGraph = feeder.treeToNxGraph(cyme_base)
feeder.latLonNxGraph(myGraph, neatoLayout=False)
plt.savefig(outPrefix + "PEC.png")
print "outprefix", outPrefix + "PEC.png"
print 'DREW GLM OF'
except:
exceptionCount += 1
print 'FAILED DRAWING'
try:
# Run powerflow on the GLM.
output = gridlabd.runInFilesystem(glmString, keepFiles=False)
with open(outPrefix + "PEC.JSON", 'w') as outFile:
json.dump(output, outFile, indent=4)
print 'RAN GRIDLAB ON\n'
except:
exceptionCount += 1
print 'POWERFLOW FAILED'
except:
print 'FAILED CONVERTING'
exceptionCount += 1
traceback.print_exc()
if not keepFiles:
shutil.rmtree(outPrefix)
return exceptionCount
'''db_network = os.path.abspath('./uploads/PasoRobles11cymsectiondevice[device]['phases']08.mdb')
'parent':'solEngInverter',
'area':'30000 sf',
'generator_status':'ONLINE',
'object':'solar',
'efficiency':'0.14',
'panel_type':'SINGLE_CRYSTAL_SILICON' }
# myTree[oldMax + 7] = { 'interval':'3600',
# 'parent':'solEngInverter',
# 'limit':'0',
# 'file':'Inverter_solEngInverter.csv',
# 'property':'power_A,power_B,power_C',
# 'object': 'recorder'}
feeder.adjustTime(myTree, 240, 'hours', '2014-01-01')
# Run here to test.
rawOut = runInFilesystem(myTree, attachments=myFeed['attachments'], keepFiles=True, workDir='.', glmName='Orville Tree Pond Calibrated.glm')
# # Show some output.
# print 'Output Keys:', rawOut.keys()
# plt.plot([abs(complex(x)) for x in rawOut['Inverter_solEngInverter.csv']['power_A']])
# plt.show()
# Write back the full feeder.
outJson = dict(myFeed)
with open('mspWeather.csv','r') as weatherFile:
weatherString = weatherFile.read()
outJson['attachments']['mspWeather.csv'] = weatherString
outJson['tree'] = myTree
try: os.remove('./Orville Tree Pond Calibrated With Weather.json')
except: pass
with open('./Orville Tree Pond Calibrated With Weather.json', 'w') as outFile:
def voltPlot(tree, workDir=None, neatoLayout=False):
''' Draw a color-coded map of the voltage drop on a feeder.
Returns a matplotlib object. '''
# Get rid of schedules and climate:
for key in tree.keys():
if tree[key].get("argument","") == "\"schedules.glm\"" or tree[key].get("tmyfile","") != "":
del tree[key]
# Make sure we have a voltDump:
def safeInt(x):
try: return int(x)
except: return 0
biggestKey = max([safeInt(x) for x in tree.keys()])
tree[str(biggestKey*10)] = {"object":"voltdump","filename":"voltDump.csv"}
# Run Gridlab.
if not workDir:
workDir = tempfile.mkdtemp()
print "gridlabD runInFilesystem with no specified workDir. Working in", workDir
gridlabOut = gridlabd.runInFilesystem(tree, attachments=[], workDir=workDir)
with open(pJoin(workDir,'voltDump.csv'),'r') as dumpFile:
reader = csv.reader(dumpFile)
reader.next() # Burn the header.
keys = reader.next()
voltTable = []
for row in reader:
rowDict = {}
for pos,key in enumerate(keys):
rowDict[key] = row[pos]
voltTable.append(rowDict)
# Calculate average node voltage deviation. First, helper functions.
def pythag(x,y):
''' For right triangle with sides a and b, return the hypotenuse. '''
return math.sqrt(x**2+y**2)
def digits(x):
''' Returns number of digits before the decimal in the float x. '''
return math.ceil(math.log10(x+1))
def avg(l):
''' Average of a list of ints or floats. '''
return sum(l)/len(l)
# Detect the feeder nominal voltage:
for key in tree:
ob = tree[key]
if type(ob)==dict and ob.get('bustype','')=='SWING':
feedVoltage = float(ob.get('nominal_voltage',1))
# Tot it all up.
nodeVolts = {}
for row in voltTable:
allVolts = []
for phase in ['A','B','C']:
phaseVolt = pythag(float(row['volt'+phase+'_real']),
float(row['volt'+phase+'_imag']))
if phaseVolt != 0.0:
if digits(phaseVolt)>3:
# Normalize to 120 V standard
phaseVolt = phaseVolt*(120/feedVoltage)
allVolts.append(phaseVolt)
nodeVolts[row.get('node_name','')] = avg(allVolts)
# Color nodes by VOLTAGE.
fGraph = feeder.treeToNxGraph(tree)
voltChart = plt.figure(figsize=(10,10))
plt.axes(frameon = 0)
plt.axis('off')
if neatoLayout:
# HACK: work on a new graph without attributes because graphViz tries to read attrs.
cleanG = nx.Graph(fGraph.edges())
cleanG.add_nodes_from(fGraph)
positions = nx.graphviz_layout(cleanG, prog='neato')
else:
positions = {n:fGraph.node[n].get('pos',(0,0)) for n in fGraph}
edgeIm = nx.draw_networkx_edges(fGraph, positions)
nodeIm = nx.draw_networkx_nodes(fGraph,
pos = positions,
node_color = [nodeVolts.get(n,0) for n in fGraph.nodes()],
linewidths = 0,
node_size = 30,
cmap = plt.cm.jet)
plt.sci(nodeIm)
plt.clim(110,130)
plt.colorbar()
return voltChart
def runForeground(modelDir, inputDict):
''' Run the model in the foreground. WARNING: can take about a minute. '''
# Global vars, and load data from the model directory.
print "STARTING TO RUN", modelDir
try:
startTime = datetime.datetime.now()
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inputDict["created"] = str(startTime)
feederPath = pJoin(__metaModel__._omfDir,"data", "Feeder", inputDict["feederName"].split("___")[0], inputDict["feederName"].split("___")[1]+'.json')
feederJson = json.load(open(feederPath))
tree = feederJson.get("tree",{})
attachments = feederJson.get("attachments",{})
allOutput = {}
''' Run CVR analysis. '''
# Reformate monthData and rates.
rates = {k:float(inputDict[k]) for k in ["capitalCost", "omCost", "wholesaleEnergyCostPerKwh",
"retailEnergyCostPerKwh", "peakDemandCostSpringPerKw", "peakDemandCostSummerPerKw",
"peakDemandCostFallPerKw", "peakDemandCostWinterPerKw"]}
# print "RATES", rates
monthNames = ["January", "February", "March", "April", "May", "June", "July", "August",
"September", "October", "November", "December"]
monthToSeason = {'January':'Winter','February':'Winter','March':'Spring','April':'Spring',
'May':'Spring','June':'Summer','July':'Summer','August':'Summer',
'September':'Fall','October':'Fall','November':'Fall','December':'Winter'}
monthData = []
for i, x in enumerate(monthNames):
monShort = x[0:3].lower()
season = monthToSeason[x]
histAvg = float(inputDict.get(monShort + "Avg", 0))
histPeak = float(inputDict.get(monShort + "Peak", 0))
monthData.append({"monthId":i, "monthName":x, "histAverage":histAvg,
"histPeak":histPeak, "season":season})
# for row in monthData:
# print row
# Graph the SCADA data.
fig = plt.figure(figsize=(10,6))
indices = [r['monthName'] for r in monthData]
d1 = [r['histPeak']/(10**3) for r in monthData]
d2 = [r['histAverage']/(10**3) for r in monthData]
ticks = range(len(d1))
bar_peak = plt.bar(ticks,d1,color='gray')
bar_avg = plt.bar(ticks,d2,color='dimgray')
plt.legend([bar_peak[0],bar_avg[0]],['histPeak','histAverage'],bbox_to_anchor=(0., 1.015, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
plt.xticks([t+0.5 for t in ticks],indices)
plt.ylabel('Mean and peak historical power consumptions (kW)')
fig.autofmt_xdate()
plt.savefig(pJoin(modelDir,"scadaChart.png"))
allOutput["histPeak"] = d1
allOutput["histAverage"] = d2
allOutput["monthName"] = [name[0:3] for name in monthNames]
# Graph feeder.
fig = plt.figure(figsize=(10,10))
myGraph = feeder.treeToNxGraph(tree)
feeder.latLonNxGraph(myGraph, neatoLayout=False)
plt.savefig(pJoin(modelDir,"feederChart.png"))
with open(pJoin(modelDir,"feederChart.png"),"rb") as inFile:
allOutput["feederChart"] = inFile.read().encode("base64")
# Get the load levels we need to test.
allLoadLevels = [x.get('histPeak',0) for x in monthData] + [y.get('histAverage',0) for y in monthData]
maxLev = _roundOne(max(allLoadLevels),'up')
minLev = _roundOne(min(allLoadLevels),'down')
tenLoadLevels = range(int(minLev),int(maxLev),int((maxLev-minLev)/10))
# Gather variables from the feeder.
for key in tree.keys():
# Set clock to single timestep.
if tree[key].get('clock','') == 'clock':
tree[key] = {"timezone":"PST+8PDT",
"stoptime":"'2013-01-01 00:00:00'",
"starttime":"'2013-01-01 00:00:00'",
"clock":"clock"}
# Save swing node index.
if tree[key].get('bustype','').lower() == 'swing':
swingIndex = key
swingName = tree[key].get('name')
# Remove all includes.
if tree[key].get('omftype','') == '#include':
del key
# Find the substation regulator and config.
for key in tree:
if tree[key].get('object','') == 'regulator' and tree[key].get('from','') == swingName:
regIndex = key
regConfName = tree[key]['configuration']
if not regConfName: regConfName = False
for key in tree:
if tree[key].get('name','') == regConfName:
regConfIndex = key
# Set substation regulator to manual operation.
baselineTap = int(inputDict.get("baselineTap")) # GLOBAL VARIABLE FOR DEFAULT TAP POSITION
tree[regConfIndex] = {
'name':tree[regConfIndex]['name'],
'object':'regulator_configuration',
'connect_type':'1',
'raise_taps':'10',
'lower_taps':'10',
'CT_phase':'ABC',
'PT_phase':'ABC',
'regulation':'0.10', #Yo, 0.10 means at tap_pos 10 we're 10% above 120V.
'Control':'MANUAL',
'control_level':'INDIVIDUAL',
'Type':'A',
'tap_pos_A':str(baselineTap),
'tap_pos_B':str(baselineTap),
'tap_pos_C':str(baselineTap) }
# Attach recorders relevant to CVR.
recorders = [
{'object': 'collector',
'file': 'ZlossesTransformer.csv',
'group': 'class=transformer',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesUnderground.csv',
'group': 'class=underground_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesOverhead.csv',
'group': 'class=overhead_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'recorder',
'file': 'Zregulator.csv',
'limit': '0',
'parent': tree[regIndex]['name'],
'property': 'tap_A,tap_B,tap_C,power_in.real,power_in.imag'},
{'object': 'collector',
'file': 'ZvoltageJiggle.csv',
'group': 'class=triplex_meter',
'limit': '0',
'property': 'min(voltage_12.mag),mean(voltage_12.mag),max(voltage_12.mag),std(voltage_12.mag)'},
{'object': 'recorder',
'file': 'ZsubstationTop.csv',
'limit': '0',
'parent': tree[swingIndex]['name'],
'property': 'voltage_A,voltage_B,voltage_C'},
{'object': 'recorder',
'file': 'ZsubstationBottom.csv',
'limit': '0',
'parent': tree[regIndex]['to'],
'property': 'voltage_A,voltage_B,voltage_C'} ]
biggest = 1 + max([int(k) for k in tree.keys()])
for index, rec in enumerate(recorders):
tree[biggest + index] = rec
# Change constant PF loads to ZIP loads. (See evernote for rationale about 50/50 power/impedance mix.)
blankZipModel = {'object':'triplex_load',
'name':'NAMEVARIABLE',
'base_power_12':'POWERVARIABLE',
'power_fraction_12': str(inputDict.get("p_percent")),
'impedance_fraction_12': str(inputDict.get("z_percent")),
'current_fraction_12': str(inputDict.get("i_percent")),
'power_pf_12': str(inputDict.get("power_factor")), #MAYBEFIX: we can probably get this PF data from the Milsoft loads.
'impedance_pf_12':str(inputDict.get("power_factor")),
'current_pf_12':str(inputDict.get("power_factor")),
'nominal_voltage':'120',
'phases':'PHASESVARIABLE',
'parent':'PARENTVARIABLE' }
def powerClean(powerStr):
''' take 3339.39+1052.29j to 3339.39 '''
return powerStr[0:powerStr.find('+')]
for key in tree:
if tree[key].get('object','') == 'triplex_node':
# Get existing variables.
name = tree[key].get('name','')
power = tree[key].get('power_12','')
parent = tree[key].get('parent','')
phases = tree[key].get('phases','')
# Replace object and reintroduce variables.
tree[key] = copy(blankZipModel)
tree[key]['name'] = name
tree[key]['base_power_12'] = powerClean(power)
tree[key]['parent'] = parent
tree[key]['phases'] = phases
# Function to determine how low we can tap down in the CVR case:
def loweringPotential(baseLine):
''' Given a baseline end of line voltage, how many more percent can we shave off the substation voltage? '''
''' testsWePass = [122.0,118.0,200.0,110.0] '''
lower = int(math.floor((baseLine/114.0-1)*100)) - 1
# If lower is negative, we can't return it because we'd be undervolting beyond what baseline already was!
if lower < 0:
return baselineTap
else:
return baselineTap - lower
# Run all the powerflows.
powerflows = []
for doingCvr in [False, True]:
# For each load level in the tenLoadLevels, run a powerflow with the load objects scaled to the level.
for desiredLoad in tenLoadLevels:
# Find the total load that was defined in Milsoft:
loadList = []
for key in tree:
if tree[key].get('object','') == 'triplex_load':
loadList.append(tree[key].get('base_power_12',''))
totalLoad = sum([float(x) for x in loadList])
# Rescale each triplex load:
for key in tree:
if tree[key].get('object','') == 'triplex_load':
currentPow = float(tree[key]['base_power_12'])
ratio = desiredLoad/totalLoad
tree[key]['base_power_12'] = str(currentPow*ratio)
# If we're doing CVR then lower the voltage.
if doingCvr:
# Find the minimum voltage we can tap down to:
newTapPos = baselineTap
for row in powerflows:
if row.get('loadLevel','') == desiredLoad:
newTapPos = loweringPotential(row.get('lowVoltage',114))
# Tap it down to there.
# MAYBEFIX: do each phase separately because that's how it's done in the field... Oof.
tree[regConfIndex]['tap_pos_A'] = str(newTapPos)
tree[regConfIndex]['tap_pos_B'] = str(newTapPos)
tree[regConfIndex]['tap_pos_C'] = str(newTapPos)
# Run the model through gridlab and put outputs in the table.
output = gridlabd.runInFilesystem(tree, attachments=attachments,
keepFiles=True, workDir=modelDir)
os.remove(pJoin(modelDir,"PID.txt"))
p = output['Zregulator.csv']['power_in.real'][0]
q = output['Zregulator.csv']['power_in.imag'][0]
s = math.sqrt(p**2+q**2)
lossTotal = 0.0
for device in ['ZlossesOverhead.csv','ZlossesTransformer.csv','ZlossesUnderground.csv']:
for letter in ['A','B','C']:
r = output[device]['sum(power_losses_' + letter + '.real)'][0]
i = output[device]['sum(power_losses_' + letter + '.imag)'][0]
lossTotal += math.sqrt(r**2 + i**2)
## Entire output:
powerflows.append({
'doingCvr':doingCvr,
'loadLevel':desiredLoad,
'realPower':p,
'powerFactor':p/s,
'losses':lossTotal,
'subVoltage': (
output['ZsubstationBottom.csv']['voltage_A'][0] +
output['ZsubstationBottom.csv']['voltage_B'][0] +
output['ZsubstationBottom.csv']['voltage_C'][0] )/3/60,
'lowVoltage':output['ZvoltageJiggle.csv']['min(voltage_12.mag)'][0]/2,
'highVoltage':output['ZvoltageJiggle.csv']['max(voltage_12.mag)'][0]/2 })
# For a given load level, find two points to interpolate on.
def getInterpPoints(t):
''' Find the two points we can interpolate from. '''
''' tests pass on [tenLoadLevels[0],tenLoadLevels[5]+499,tenLoadLevels[-1]-988] '''
loc = sorted(tenLoadLevels + [t]).index(t)
if loc==0:
return (tenLoadLevels[0],tenLoadLevels[1])
elif loc>len(tenLoadLevels)-2:
return (tenLoadLevels[-2],tenLoadLevels[-1])
else:
return (tenLoadLevels[loc-1],tenLoadLevels[loc+1])
# Calculate peak reduction.
for row in monthData:
peak = row['histPeak']
peakPoints = getInterpPoints(peak)
peakTopBase = [x for x in powerflows if x.get('loadLevel','') == peakPoints[-1] and x.get('doingCvr','') == False][0]
peakTopCvr = [x for x in powerflows if x.get('loadLevel','') == peakPoints[-1] and x.get('doingCvr','') == True][0]
peakBottomBase = [x for x in powerflows if x.get('loadLevel','') == peakPoints[0] and x.get('doingCvr','') == False][0]
peakBottomCvr = [x for x in powerflows if x.get('loadLevel','') == peakPoints[0] and x.get('doingCvr','') == True][0]
# Linear interpolation so we aren't running umpteen million loadflows.
x = (peakPoints[0],peakPoints[1])
y = (peakTopBase['realPower'] - peakTopCvr['realPower'],
peakBottomBase['realPower'] - peakBottomCvr['realPower'])
peakRed = y[0] + (y[1] - y[0]) * (peak - x[0]) / (x[1] - x[0])
row['peakReduction'] = peakRed
# Calculate energy reduction and loss reduction based on average load.
for row in monthData:
avgEnergy = row['histAverage']
energyPoints = getInterpPoints(avgEnergy)
avgTopBase = [x for x in powerflows if x.get('loadLevel','') == energyPoints[-1] and x.get('doingCvr','') == False][0]
avgTopCvr = [x for x in powerflows if x.get('loadLevel','') == energyPoints[-1] and x.get('doingCvr','') == True][0]
avgBottomBase = [x for x in powerflows if x.get('loadLevel','') == energyPoints[0] and x.get('doingCvr','') == False][0]
avgBottomCvr = [x for x in powerflows if x.get('loadLevel','') == energyPoints[0] and x.get('doingCvr','') == True][0]
# Linear interpolation so we aren't running umpteen million loadflows.
x = (energyPoints[0], energyPoints[1])
y = (avgTopBase['realPower'] - avgTopCvr['realPower'],
avgBottomBase['realPower'] - avgBottomCvr['realPower'])
energyRed = y[0] + (y[1] - y[0]) * (avgEnergy - x[0]) / (x[1] - x[0])
row['energyReduction'] = energyRed
lossY = (avgTopBase['losses'] - avgTopCvr['losses'],
avgBottomBase['losses'] - avgBottomCvr['losses'])
lossRed = lossY[0] + (lossY[1] - lossY[0]) * (avgEnergy - x[0]) / (x[1] - x[0])
row['lossReduction'] = lossRed
# Multiply by dollars.
for row in monthData:
row['energyReductionDollars'] = row['energyReduction']/1000 * (rates['wholesaleEnergyCostPerKwh'] - rates['retailEnergyCostPerKwh'])
row['peakReductionDollars'] = row['peakReduction']/1000 * rates['peakDemandCost' + row['season'] + 'PerKw']
row['lossReductionDollars'] = row['lossReduction']/1000 * rates['wholesaleEnergyCostPerKwh']
# Pretty output
def plotTable(inData):
fig = plt.figure(figsize=(10,5))
plt.axis('off')
plt.tight_layout()
plt.table(cellText=[row for row in inData[1:]],
loc = 'center',
rowLabels = range(len(inData)-1),
colLabels = inData[0])
def dictalToMatrix(dictList):
''' Take our dictal format to a matrix. '''
matrix = [dictList[0].keys()]
for row in dictList:
matrix.append(row.values())
return matrix
# Powerflow results.
plotTable(dictalToMatrix(powerflows))
plt.savefig(pJoin(modelDir,"powerflowTable.png"))
# Monetary results.
## To print partial money table
monthDataMat = dictalToMatrix(monthData)
dimX = len(monthDataMat)
dimY = len(monthDataMat[0])
monthDataPart = []
for k in range (0,dimX):
monthDatatemp = []
for m in range (4,dimY):
monthDatatemp.append(monthDataMat[k][m])
monthDataPart.append(monthDatatemp)
plotTable(monthDataPart)
plt.savefig(pJoin(modelDir,"moneyTable.png"))
allOutput["monthDataMat"] = dictalToMatrix(monthData)
allOutput["monthDataPart"] = monthDataPart
# Graph the money data.
fig = plt.figure(figsize=(10,8))
indices = [r['monthName'] for r in monthData]
d1 = [r['energyReductionDollars'] for r in monthData]
d2 = [r['lossReductionDollars'] for r in monthData]
d3 = [r['peakReductionDollars'] for r in monthData]
ticks = range(len(d1))
bar_erd = plt.bar(ticks,d1,color='red')
bar_lrd = plt.bar(ticks,d2,color='green')
bar_prd = plt.bar(ticks,d3,color='blue',yerr=d2)
plt.legend([bar_prd[0], bar_lrd[0], bar_erd[0]], ['peakReductionDollars','lossReductionDollars','energyReductionDollars'],bbox_to_anchor=(0., 1.015, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
plt.xticks([t+0.5 for t in ticks],indices)
plt.ylabel('Utility Savings ($)')
plt.tight_layout(5.5,1.3,1.2)
fig.autofmt_xdate()
plt.savefig(pJoin(modelDir,"spendChart.png"))
allOutput["energyReductionDollars"] = d1
allOutput["lossReductionDollars"] = d2
allOutput["peakReductionDollars"] = d3
# Graph the cumulative savings.
fig = plt.figure(figsize=(10,5))
annualSavings = sum(d1) + sum(d2) + sum(d3)
annualSave = lambda x:(annualSavings - rates['omCost']) * x - rates['capitalCost']
simplePayback = rates['capitalCost']/(annualSavings - rates['omCost'])
plt.xlabel('Year After Installation')
plt.xlim(0,30)
plt.ylabel('Cumulative Savings ($)')
plt.plot([0 for x in range(31)],c='gray')
plt.axvline(x=simplePayback, ymin=0, ymax=1, c='gray', linestyle='--')
plt.plot([annualSave(x) for x in range(31)], c='green')
plt.savefig(pJoin(modelDir,"savingsChart.png"))
allOutput["annualSave"] = [annualSave(x) for x in range(31)]
# Update the runTime in the input file.
endTime = datetime.datetime.now()
inputDict["runTime"] = str(datetime.timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir,"allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent=4)
# Write output file.
with open(pJoin(modelDir,"allOutputData.json"),"w") as outFile:
json.dump(allOutput, outFile, indent=4)
# For autotest, there won't be such file.
try:
os.remove(pJoin(modelDir, "PPID.txt"))
except:
pass
print "DONE RUNNING", modelDir
except Exception as e:
# If input range wasn't valid delete output, write error to disk.
cancel(modelDir)
thisErr = traceback.format_exc()
print 'ERROR IN MODEL', modelDir, thisErr
inputDict['stderr'] = thisErr
with open(os.path.join(modelDir,'stderr.txt'),'w') as errorFile:
errorFile.write(thisErr)
with open(pJoin(modelDir,"allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent=4)
def _tests(makeKey=False, runGridlabD=True, showGDLABResults=False, cleanUp=True):
'''Get and encrypt a .std/.seq files to a .json. cleanUp removes the unencrypted .glm and .json.
'''
# Inputs.
user = "******"
workDir = pJoin(os.getcwd())
try: os.mkdir(pJoin(os.getcwd(),'encryptedFiles'))
except: pass
if makeKey:
genKey(workDir, user)
print "Made a new key for user:"******"Read key for user:"******"Working on:", stdString+",",seqString
with open(pJoin("../../","uploads",stdString),'r') as stdFile, open(pJoin("../../","uploads",seqString),'r') as seqFile:
stdContents, seqContents = stdFile.read(), seqFile.read()
# print "First few lines before encryption:\n", stdContents[:100]
encData = encryptData(stdContents, key)
with open(pJoin(workDir, "encryptedFiles", "Encrypted_"+stdString),"w+") as encFile:
encFile.write(encData)
encData = encryptData(seqContents, key)
with open(pJoin(workDir, "encryptedFiles", "Encrypted_"+seqString),"w+") as encFile:
encFile.write(encData)
# print "First few lines after enc:\n", encData[:100]
# Read and decrypt to convert to a .glm.
with open(pJoin(workDir, "encryptedFiles", "Encrypted_"+stdString),'r') as inFile:
encStdContents = inFile.read()
with open(pJoin(workDir, "encryptedFiles", "Encrypted_"+seqString),'r') as inFile2:
encSeqContents = inFile2.read()
print "\nCreated encrypted files:", "Encrypted_"+stdString+",", "Encrypted_"+seqString
# Decrypt.
decStdContents = decryptData(encStdContents,key)
decSeqContents = decryptData(encSeqContents,key)
# print "First few lines after dec:\n", decStdContents[:100]
# Convert to .glm.
def runMilConvert(stdContents, seqContents):
myFeed, xScale, yScale = omf.milToGridlab.convert(stdContents,seqContents)
with open(pJoin(workDir,stdString.replace('.std','.glm')),'w') as outFile:
outFile.write(omf.feeder.sortedWrite(myFeed))
myGraph = omf.feeder.treeToNxGraph(myFeed)
omf.feeder.latLonNxGraph(myGraph, neatoLayout=False)
plt.savefig(pJoin(workDir,stdString.replace('.std','.png')))
plt.close()
if not os.path.isfile(pJoin(workDir,stdString.replace('.std','.glm'))):
runMilConvert(decStdContents, decSeqContents)
print "Converted std/seq to glm."
# Convert converted .glm to encrypted glm.
with open(pJoin(workDir,stdString.replace('.std','.glm')),'r') as inGLM:
glmContents = inGLM.read()
encData = encryptData(glmContents, key)
with open(pJoin(workDir, "encryptedFiles","Encrypted_"+stdString.replace('.std','.glm')),'w') as encFile:
encFile.write(encData)
print "Encrypted glm file:", stdString.replace('.std','.glm')
# Decrypt .glm, convert to .json.
with open(pJoin(workDir, "encryptedFiles", "Encrypted_"+stdString.replace('.std','.glm')),'r') as encFile:
encOutGlm = encFile.read()
outGlm = decryptData(encOutGlm,key)
newFeeder = gridlabImport(workDir, stdString.strip('.std'), outGlm)
# Run gridlabD on decrypted GLM.
if runGridlabD:
output = gridlabd.runInFilesystem(newFeeder['tree'], attachments=testAttachments, keepFiles=False)
if showGDLABResults:
print "[STDERR]\n", (output['stderr'])
print "[STDOUT]\n", (output['stdout'])
print 'RAN GRIDLAB ON', stdString
# Convert JSON to encrypted json.
with open(pJoin(workDir,stdString.replace('.std','.json')),'r') as encFile:
decJSON = encFile.read()
encData = encryptData(decJSON, key)
with open(pJoin(workDir,"encryptedFiles","Encrypted_"+stdString.replace('.std','.json')),'w') as encFile:
encFile.write(encData)
print "Encrypted JSON file:", stdString.replace('.std','.json')
# Clean up unencrypted .glm and .json.
if cleanUp:
try:
os.remove(pJoin(workDir,stdString.replace('.std','.glm')))
print "Removed unencrypted file:", stdString.replace('.std','.glm')
except: pass
try:
os.remove(pJoin(workDir,stdString.replace('.std','.json')))
print "Removed unencrypted file:", stdString.replace('.std','.json')
except: pass
print "\nDone with encrypting all test files."
except:
print "Failed to encrypt", stdString, seqString
exceptionCount += 1
traceback.print_exc()
return exceptionCount
'object': 'solar',
'efficiency': '0.14',
'panel_type': 'SINGLE_CRYSTAL_SILICON'
}
# myTree[oldMax + 7] = { 'interval':'3600',
# 'parent':'solEngInverter',
# 'limit':'0',
# 'file':'Inverter_solEngInverter.csv',
# 'property':'power_A,power_B,power_C',
# 'object': 'recorder'}
feeder.adjustTime(myTree, 240, 'hours', '2014-01-01')
# Run here to test.
rawOut = runInFilesystem(myTree,
attachments=myFeed['attachments'],
keepFiles=True,
workDir='.',
glmName='Orville Tree Pond Calibrated.glm')
# # Show some output.
# print 'Output Keys:', rawOut.keys()
# plt.plot([abs(complex(x)) for x in rawOut['Inverter_solEngInverter.csv']['power_A']])
# plt.show()
# Write back the full feeder.
outJson = dict(myFeed)
with open('mspWeather.csv', 'r') as weatherFile:
weatherString = weatherFile.read()
outJson['attachments']['mspWeather.csv'] = weatherString
outJson['tree'] = myTree
try:
def runForeground(modelDir,inData):
'''This reads a glm file, changes the method of powerflow and reruns'''
try:
startTime = datetime.now()
#calibrate and run cvrdynamic
feederPath = pJoin(__metaModel__._omfDir,"data", "Feeder", inData["feederName"].split("___")[0], inData["feederName"].split("___")[1]+'.json')
scadaPath = pJoin(__metaModel__._omfDir,"uploads",(inData["scadaFile"]+'.tsv'))
calibrate.omfCalibrate(modelDir,feederPath,scadaPath)
allOutput = {}
print "here"
with open(pJoin(modelDir,"calibratedFeeder.json"), "r") as jsonIn:
feederJson = json.load(jsonIn)
localTree = feederJson.get("tree", {})
for key in localTree:
if "solver_method" in localTree[key].keys():
print "current solver method", localTree[key]["solver_method"]
localTree[key]["solver_method"] = 'FBS'
#find the swing bus and recorder attached to substation
for key in localTree:
if localTree[key].get('bustype','').lower() == 'swing':
swingIndex = key
swingName = localTree[key].get('name')
if localTree[key].get('object','') == 'regulator' and localTree[key].get('from','') == swingName:
regIndex = key
regConfName = localTree[key]['configuration']
#find the regulator and capacitor names and combine to form a string for volt-var control object
regKeys = []
accum_reg = ""
for key in localTree:
if localTree[key].get("object","") == "regulator":
accum_reg += localTree[key].get("name","ERROR") + ","
regKeys.append(key)
regstr = accum_reg[:-1]
print regKeys
capKeys = []
accum_cap = ""
for key in localTree:
if localTree[key].get("object","") == "capacitor":
accum_cap += localTree[key].get("name","ERROR") + ","
capKeys.append(key)
if localTree[key].get("control","").lower() == "manual":
localTree[key]['control'] = "VOLT"
print "changing capacitor control from manual to volt"
capstr = accum_cap[:-1]
print capKeys
# Attach recorders relevant to CVR.
recorders = [
{'object': 'collector',
'file': 'ZlossesTransformer.csv',
'group': 'class=transformer',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesUnderground.csv',
'group': 'class=underground_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesOverhead.csv',
'group': 'class=overhead_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'recorder',
'file': 'Zregulator.csv',
'limit': '0',
'parent': localTree[regIndex]['name'],
'property': 'tap_A,tap_B,tap_C,power_in.real,power_in.imag'},
{'object': 'collector',
'file': 'ZvoltageJiggle.csv',
'group': 'class=triplex_meter',
'limit': '0',
'property': 'min(voltage_12.mag),mean(voltage_12.mag),max(voltage_12.mag),std(voltage_12.mag)'},
{'object': 'recorder',
'file': 'ZsubstationTop.csv',
'limit': '0',
'parent': localTree[swingIndex]['name'],
'property': 'voltage_A,voltage_B,voltage_C'},
{'object': 'recorder',
'file': 'ZsubstationBottom.csv',
'limit': '0',
'parent': localTree[regIndex]['to'],
'property': 'voltage_A,voltage_B,voltage_C'}]
#recorder object for capacitor switching - if capacitors exist
if capKeys != []:
for key in capKeys:
recorders.append({'object': 'recorder',
'file': 'ZcapSwitch' + str(key) + '.csv',
'limit': '0',
'parent': localTree[key]['name'],
'property': 'switchA,switchB,switchC'})
#attach recorder process
biggest = 1 + max([int(k) for k in localTree.keys()])
for index, rec in enumerate(recorders):
localTree[biggest + index] = rec
#run a reference load flow
HOURS = float(inData['simLengthHours'])
simStartDate = inData['simStart']
feeder.adjustTime(localTree,HOURS,"hours",simStartDate)
output = gridlabd.runInFilesystem(localTree,keepFiles=False,workDir=modelDir)
os.remove(pJoin(modelDir,"PID.txt"))
p = output['Zregulator.csv']['power_in.real']
q = output['Zregulator.csv']['power_in.imag']
#calculating length of simulation because it migth be different from the simulation input HOURS
simRealLength = int(len(p))
#time delays from configuration files
time_delay_reg = '30.0'
time_delay_cap = '300.0'
for key in localTree:
if localTree[key].get('object','') == "regulator_configuration":
time_delay_reg = localTree[key]['time_delay']
print "time_delay_reg",time_delay_reg
# if localTree[key].get('object','') == "capacitor":
# time_delay_cap = localTree[key]['time_delay']
# print "time_delay_cap",time_delay_cap
#change the recorder names
for key in localTree:
if localTree[key].get('object','') == "collector" or localTree[key].get('object','') == "recorder":
if localTree[key].get('file','').startswith('Z'):
localTree[key]['file'] = localTree[key].get('file','').replace('Z','NewZ')
#create volt-var control object
max_key = max([int(key) for key in localTree.keys()])
print max_key
localTree[max_key+1] = {'object' : 'volt_var_control',
'name' : 'IVVC1',
'control_method' : 'ACTIVE',
'capacitor_delay' : str(time_delay_cap),
'regulator_delay' : str(time_delay_reg),
'desired_pf' : '0.99',
'd_max' : '0.6',
'd_min' : '0.1',
'substation_link' : str(localTree[regIndex]['name']),
'regulator_list' : regstr,
'capacitor_list': capstr}
#running powerflow analysis via gridalab after attaching a regulator
feeder.adjustTime(localTree,HOURS,"hours",simStartDate)
output1 = gridlabd.runInFilesystem(localTree,keepFiles=True,workDir=modelDir)
os.remove(pJoin(modelDir,"PID.txt"))
pnew = output1['NewZregulator.csv']['power_in.real']
qnew = output1['NewZregulator.csv']['power_in.imag']
#total real and imaginary losses as a function of time
def vecSum(u,v):
''' Add vectors u and v element-wise. Return has len <= len(u) and <=len(v). '''
return map(sum, zip(u,v))
def zeroVec(length):
''' Give a zero vector of input length. '''
return [0 for x in xrange(length)]
(realLoss, imagLoss, realLossnew, imagLossnew) = (zeroVec(int(HOURS)) for x in range(4))
for device in ['ZlossesOverhead.csv','ZlossesTransformer.csv','ZlossesUnderground.csv']:
for letter in ['A','B','C']:
realLoss = vecSum(realLoss, output[device]['sum(power_losses_' + letter + '.real)'])
imagLoss = vecSum(imagLoss, output[device]['sum(power_losses_' + letter + '.imag)'])
realLossnew = vecSum(realLossnew, output1['New'+device]['sum(power_losses_' + letter + '.real)'])
imagLossnew = vecSum(imagLossnew, output1['New'+device]['sum(power_losses_' + letter + '.imag)'])
#voltage calculations and tap calculations
def divby2(u):
'''divides by 2'''
return u/2
lowVoltage = []
meanVoltage = []
highVoltage = []
lowVoltagenew = []
meanVoltagenew = []
highVoltagenew = []
tap = {'A':[],'B':[],'C':[]}
tapnew = {'A':[],'B':[],'C':[]}
volt = {'A':[],'B':[],'C':[]}
voltnew = {'A':[],'B':[],'C':[]}
switch = {'A':[],'B':[],'C':[]}
switchnew = {'A':[],'B':[],'C':[]}
for letter in ['A','B','C']:
tap[letter] = output['Zregulator.csv']['tap_' + letter]
tapnew[letter] = output1['NewZregulator.csv']['tap_' + letter]
if capKeys != []:
switch[letter] = output['ZcapSwitch' + str(int(capKeys[0])) + '.csv']['switch'+ letter]
switchnew[letter] = output1['NewZcapSwitch' + str(int(capKeys[0])) + '.csv']['switch'+ letter]
volt[letter] = map(returnMag,output['ZsubstationBottom.csv']['voltage_'+letter])
voltnew[letter] = map(returnMag,output1['NewZsubstationBottom.csv']['voltage_'+letter])
lowVoltage = map(divby2,output['ZvoltageJiggle.csv']['min(voltage_12.mag)'])
lowVoltagenew = map(divby2,output1['NewZvoltageJiggle.csv']['min(voltage_12.mag)'])
meanVoltage = map(divby2,output['ZvoltageJiggle.csv']['mean(voltage_12.mag)'])
meanVoltagenew = map(divby2,output1['NewZvoltageJiggle.csv']['mean(voltage_12.mag)'])
highVoltage = map(divby2,output['ZvoltageJiggle.csv']['max(voltage_12.mag)'])
highVoltagenew = map(divby2,output1['NewZvoltageJiggle.csv']['max(voltage_12.mag)'])
#energy calculations
whEnergy = []
whLosses = []
whLoads = []
whEnergy.append(sum(p)/10**6)
whLosses.append(sum(realLoss)/10**6)
whLoads.append((sum(p)-sum(realLoss))/10**6)
whEnergy.append(sum(pnew)/10**6)
whLosses.append(sum(realLossnew)/10**6)
whLoads.append((sum(pnew)-sum(realLossnew))/10**6)
indices = ['No IVVC', 'With IVVC']
# energySalesRed = (whLoads[1]-whLoads[0])*(inData['wholesaleEnergyCostPerKwh'])*1000
# lossSav = (whLosses[0]-whLosses[1])*inData['wholesaleEnergyCostPerKwh']*1000
# print energySalesRed, lossSav
#plots
ticks = []
plt.clf()
plt.title("total energy")
plt.ylabel("total load and losses (MWh)")
for element in range(2):
ticks.append(element)
bar_loss = plt.bar(element, whLosses[element], 0.15, color= 'red')
bar_load = plt.bar(element+0.15, whLoads[element], 0.15, color= 'orange')
plt.legend([bar_load[0],bar_loss[0]],['total load', 'total losses'],bbox_to_anchor=(0., 0.915, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
plt.xticks([t+0.15 for t in ticks],indices)
plt.savefig(pJoin(modelDir,"totalEnergy.png"))
#real and imaginary power
plt.figure("real power")
plt.title("Real Power at substation")
plt.ylabel("substation real power (MW)")
pMW = [element/10**6 for element in p]
pMWn = [element/10**6 for element in pnew]
pw = plt.plot(pMW)
npw = plt.plot(pMWn)
plt.legend([pw[0], npw[0]], ['NO IVVC','WITH IVVC'],bbox_to_anchor=(0., 0.915, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
plt.savefig(pJoin(modelDir,"realPower.png"))
plt.figure("Reactive power")
plt.title("Reactive Power at substation")
plt.ylabel("substation reactive power (MVAR)")
qMVAR = [element/10**6 for element in q]
qMVARn = [element/10**6 for element in qnew]
iw = plt.plot(qMVAR)
niw = plt.plot(qMVARn)
plt.legend([iw[0], niw[0]], ['NO IVVC','WITH IVVC'],bbox_to_anchor=(0., 0.915, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
plt.savefig(pJoin(modelDir,"imaginaryPower.png"))
#voltage plots
plt.figure("voltages as a function of time")
f,ax = plt.subplots(2,sharex=True)
f.suptitle("Min and Max voltages on the feeder")
lv = ax[0].plot(lowVoltage,color = 'cadetblue')
mv = ax[0].plot(meanVoltage,color = 'blue')
hv = ax[0].plot(highVoltage, color = 'cadetblue')
ax[0].legend([lv[0], mv[0], hv[0]], ['low voltage','mean voltage','high voltage'],bbox_to_anchor=(0., 0.915, 1., .1), loc=3,
ncol=3, mode="expand", borderaxespad=0.1)
ax[0].set_ylabel('NO IVVC')
nlv = ax[1].plot(lowVoltagenew,color = 'cadetblue')
nmv = ax[1].plot(meanVoltagenew,color = 'blue')
nhv = ax[1].plot(highVoltagenew, color = 'cadetblue')
ax[1].set_ylabel('WITH IVVC')
plt.savefig(pJoin(modelDir,"Voltages.png"))
#tap positions
plt.figure("TAP positions NO IVVC")
f,ax = plt.subplots(6,sharex=True)
f.set_size_inches(10,12.0)
#f.suptitle("Regulator Tap positions")
ax[0].plot(tap['A'])
ax[0].set_title("Regulator Tap positions NO IVVC")
ax[0].set_ylabel("TAP A")
ax[1].plot(tap['B'])
ax[1].set_ylabel("TAP B")
ax[2].plot(tap['C'])
ax[2].set_ylabel("TAP C")
ax[3].plot(tapnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel("TAP A")
ax[4].plot(tapnew['B'])
ax[4].set_ylabel("TAP B")
ax[5].plot(tapnew['C'])
ax[5].set_ylabel("TAP C")
for subplot in range(6):
ax[subplot].set_ylim(-20,20)
f.tight_layout()
plt.savefig(pJoin(modelDir,"RegulatorTAPpositions.png"))
#substation voltages
plt.figure("substation voltage as a function of time")
f,ax = plt.subplots(6,sharex=True)
f.set_size_inches(10,12.0)
#f.suptitle("voltages at substation NO IVVC")
ax[0].plot(volt['A'])
ax[0].set_title('Substation voltages NO IVVC')
ax[0].set_ylabel('voltage A')
ax[1].plot(volt['B'])
ax[1].set_ylabel('voltage B')
ax[2].plot(volt['C'])
ax[2].set_ylabel('voltage C')
ax[3].plot(voltnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel('voltage A')
ax[4].plot(voltnew['B'])
ax[4].set_ylabel('voltage B')
ax[5].plot(voltnew['C'])
ax[5].set_ylabel('voltage C')
f.tight_layout()
plt.savefig(pJoin(modelDir,"substationVoltages.png"))
#cap switches
plt.figure("capacitor switch state as a function of time")
f,ax = plt.subplots(6,sharex=True)
f.set_size_inches(10,12.0)
#f.suptitle("Capacitor switch state NO IVVC")
ax[0].plot(switch['A'])
ax[0].set_title("Capacitor switch state NO IVVC")
ax[0].set_ylabel("switch A")
ax[1].plot(switch['B'])
ax[1].set_ylabel("switch B")
ax[2].plot(switch['C'])
ax[2].set_ylabel("switch C")
ax[3].plot(switchnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel("switch A")
ax[4].plot(switchnew['B'])
ax[4].set_ylabel("switch B")
ax[5].plot(switchnew['C'])
ax[5].set_ylabel("switch C")
for subplot in range(6):
ax[subplot].set_ylim(-2,2)
f.tight_layout()
plt.savefig(pJoin(modelDir,"capacitorSwitch.png"))
#plt.show()
#monetization
monthNames = ["January", "February", "March", "April", "May", "June", "July", "August",
"September", "October", "November", "December"]
monthToSeason = {'January':'Winter','February':'Winter','March':'Spring','April':'Spring',
'May':'Spring','June':'Summer','July':'Summer','August':'Summer',
'September':'Fall','October':'Fall','November':'Fall','December':'Winter'}
#calculate the month and hour of simulation start and month and hour of simulation end
simStartTimestamp = simStartDate + " 00:00:00"
simFormattedDate = datetime.strptime(simStartTimestamp,"%Y-%m-%d %H:%M:%S")
simStartMonthNum = int(simFormattedDate.strftime('%m'))
simstartMonth = monthNames[simStartMonthNum-1]
simStartDay = int(simFormattedDate.strftime('%d'))
if calendar.isleap(int(simFormattedDate.strftime('%Y'))):
febDays = 29
else:
febDays = 28
monthHours = [int(31*24),int(febDays*24),int(31*24),int(30*24),int(31*24),int(30*24),int(31*24),int(31*24),int(30*24),int(31*24),int(30*24),int(31*24)]
simStartIndex = int(sum(monthHours[:(simStartMonthNum-1)])+(simStartDay-1)*24)
temp = 0
cumulHours = [0]
for x in range(12):
temp += monthHours[x]
cumulHours.append(temp)
for i in range((simStartMonthNum),13):
if int(simStartIndex+simRealLength)<=cumulHours[i] and int(simStartIndex+simRealLength)>cumulHours[i-1]:
simEndMonthNum = i-1
simEndMonth = monthNames[simEndMonthNum]
print simstartMonth,simEndMonth
#calculate peaks for the number of months in simulation
previndex = 0
monthPeak = {}
monthPeakNew = {}
peakSaveDollars = {}
energyLostDollars = {}
lossRedDollars = {}
simMonthList = monthNames[monthNames.index(simstartMonth):(monthNames.index(simEndMonth)+1)]
print simMonthList
for monthElement in simMonthList:
print monthElement
month = monthNames.index(monthElement)
index1 = int(previndex)
index2 = int(min((index1 + int(monthHours[month])), simRealLength))
monthPeak[monthElement] = max(p[index1:index2])/1000.0
monthPeakNew[monthElement] = max(pnew[index1:index2])/1000.0
peakSaveDollars[monthElement] = (monthPeak[monthElement]-monthPeakNew[monthElement])*float(inData['peakDemandCost'+str(monthToSeason[monthElement])+'PerKw'])
lossRedDollars[monthElement] = (sum(realLoss[index1:index2])/1000.0 - sum(realLossnew[index1:index2])/1000.0)*(float(inData['wholesaleEnergyCostPerKwh']))
energyLostDollars[monthElement] = (sum(p[index1:index2])/1000.0 - sum(pnew[index1:index2])/1000.0 - sum(realLoss[index1:index2])/1000.0
+ sum(realLossnew[index1:index2])/1000.0 )*(float(inData['wholesaleEnergyCostPerKwh']) - float(inData['retailEnergyCostPerKwh']))
previndex = index2
#money charts
fig = plt.figure("cost benefit barchart",figsize=(10,8))
ticks = range(len(simMonthList))
ticks1 = [element+0.15 for element in ticks]
ticks2 = [element+0.30 for element in ticks]
print ticks
eld = [energyLostDollars[month] for month in simMonthList]
lrd = [lossRedDollars[month] for month in simMonthList]
psd = [peakSaveDollars[month] for month in simMonthList]
bar_eld = plt.bar(ticks,eld,0.15,color='red')
bar_psd = plt.bar(ticks1,psd,0.15,color='blue')
bar_lrd = plt.bar(ticks2,lrd,0.15,color='green')
plt.legend([bar_eld[0], bar_psd[0], bar_lrd[0]], ['energyLostDollars','peakReductionDollars','lossReductionDollars'],bbox_to_anchor=(0., 1.015, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
monShort = [element[0:3] for element in simMonthList]
plt.xticks([t+0.15 for t in ticks],monShort)
plt.ylabel('Utility Savings ($)')
plt.savefig(pJoin(modelDir,"spendChart.png"))
#cumulative savings graphs
fig = plt.figure("cost benefit barchart",figsize=(10,5))
annualSavings = sum(eld) + sum(lrd) + sum(psd)
annualSave = lambda x:(annualSavings - float(inData['omCost'])) * x - float(inData['capitalCost'])
simplePayback = float(inData['capitalCost'])/(annualSavings - float(inData['omCost']))
plt.xlabel('Year After Installation')
plt.xlim(0,30)
plt.ylabel('Cumulative Savings ($)')
plt.plot([0 for x in range(31)],c='gray')
plt.axvline(x=simplePayback, ymin=0, ymax=1, c='gray', linestyle='--')
plt.plot([annualSave(x) for x in range(31)], c='green')
plt.savefig(pJoin(modelDir,"savingsChart.png"))
#get exact time stamps from the CSV files generated by Gridlab-D
timeWithZone = output['Zregulator.csv']['# timestamp']
timestamps = [element[:19] for element in timeWithZone]
#data for highcharts
allOutput["timeStamps"] = timestamps
allOutput["noCVRPower"] = p
allOutput["withCVRPower"] = pnew
allOutput["noCVRLoad"] = whLoads[0]
allOutput["withCVRLoad"] = whLoads[1]
allOutput["noCVRLosses"] = whLosses[0]
allOutput["withCVRLosses"] = whLosses[1]
allOutput["noCVRTaps"] = tap
allOutput["withCVRTaps"] = tapnew
allOutput["noCVRSubVolts"] = volt
allOutput["withCVRSubVolts"] = voltnew
allOutput["noCVRCapSwitch"] = switch
allOutput["withCVRCapSwitch"] = switchnew
allOutput["noCVRHighVolt"] = highVoltage
allOutput["withCVRHighVolt"] = highVoltagenew
allOutput["noCVRLowVolt"] = lowVoltage
allOutput["withCVRLowVolt"] = lowVoltagenew
allOutput["noCVRMeanVolt"] = meanVoltage
allOutput["withCVRMeanVolt"] = meanVoltagenew
#monetization
allOutput["simMonthList"] = monShort
allOutput["energyLostDollars"] = energyLostDollars
allOutput["lossRedDollars"] = lossRedDollars
allOutput["peakSaveDollars"] = peakSaveDollars
allOutput["annualSave"] = [annualSave(x) for x in range(31)]
# Update the runTime in the input file.
endTime = datetime.now()
inData["runTime"] = str(timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir,"allInputData.json"),"w") as inFile:
json.dump(inData, inFile, indent=4)
with open(pJoin(modelDir,"allOutputData.json"),"w") as outFile:
json.dump(allOutput, outFile, indent=4)
# For autotest, there won't be such file.
try:
os.remove(pJoin(modelDir, "PPID.txt"))
except:
pass
print "DONE RUNNING", modelDir
except Exception as e:
print "Oops, Model Crashed!!!"
cancel(modelDir)
print e
def comparesol(modelDir,localTree):
'''This reads a glm file, changes the method of powerflow and reruns'''
print "Testing GridlabD solver."
startTime = datetime.now()
binaryName = "gridlabd"
for key in localTree:
if "solver_method" in localTree[key].keys():
solvmeth = localTree[key]["solver_method"]
print "success", solvmeth
if solvmeth == 'NR':
localTree[key]["solver_method"] = 'FBS'
else:
localTree[key]["solver_method"] = 'NR'
# feeder.attachRecorders(localTree, "Regulator", "object", "regulator")
# feeder.attachRecorders(localTree, "CollectorVoltage", None, None)
# last_key = len(localTree)
# print last_key
for key in localTree:
if localTree[key].get('bustype','').lower() == 'swing':
swingIndex = key
swingName = localTree[key].get('name')
print swingIndex, swingName
for key in localTree:
if localTree[key].get('object','') == 'regulator' and localTree[key].get('from','') == swingName:
regIndex = key
regConfName = localTree[key]['configuration']
print regIndex
# Attach recorders relevant to CVR.
recorders = [
{'object': 'collector',
'file': 'ZlossesTransformer.csv',
'group': 'class=transformer',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesUnderground.csv',
'group': 'class=underground_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesOverhead.csv',
'group': 'class=overhead_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'recorder',
'file': 'Zregulator.csv',
'limit': '0',
'parent': localTree[regIndex]['name'],
'property': 'tap_A,tap_B,tap_C,power_in.real,power_in.imag'},
{'object': 'collector',
'file': 'ZvoltageJiggle.csv',
'group': 'class=triplex_meter',
'limit': '0',
'property': 'min(voltage_12.mag),mean(voltage_12.mag),max(voltage_12.mag),std(voltage_12.mag)'},
{'object': 'recorder',
'file': 'ZsubstationTop.csv',
'limit': '0',
'parent': localTree[swingIndex]['name'],
'property': 'voltage_A,voltage_B,voltage_C'},
{'object': 'recorder',
'file': 'ZsubstationBottom.csv',
'limit': '0',
'parent': localTree[regIndex]['to'],
'property': 'voltage_A,voltage_B,voltage_C'} ]
biggest = 1 + max([int(k) for k in localTree.keys()])
for index, rec in enumerate(recorders):
localTree[biggest + index] = rec
max_key = max([int(key) for key in localTree.keys()])
print max_key
regKeys = []
accum = ""
for key in localTree:
if localTree[key].get("object","") == "regulator":
accum += localTree[key].get("name","ERROR") + ","
regKeys.append(key)
regstr = accum[:-1]
print regKeys
print regstr, type(regstr)
localTree[max_key+1] = {'object' : 'volt_var_control',
'name' : 'volt_var_control',
'control_method' : 'ACTIVE',
'capacitor_delay' : '30.0',
'regulator_delay' : '30.0',
'desired_pf' : '0.99',
'd_max' : '0.6',
'd_min' : '0.1',
'substation_link' : 'substation_transformer',
'regulator_list' : regstr }
feeder.adjustTime(tree=localTree, simLength=float("8760"),
simLengthUnits="hours", simStartDate="2012-01-01")
output = gridlabd.runInFilesystem(localTree,keepFiles=True,workDir=modelDir)
os.remove(pJoin(modelDir,"PID.txt"))
p = output['Zregulator.csv']['power_in.real']
q = output['Zregulator.csv']['power_in.imag']
xtime = {}
for key in output:
if '# timestamp' in output[key]:
xtime['timeStamps'] = output[key]['# timestamp']
#print type(xtime['timeStamps'][0])
#print len(p)
#xaxtick = str(xtime['timeStamps'])
# plt.plot(range(8760),p)
# plt.show()
# print "p=" , p
# print "q=" , q
print "DONE RUNNING", modelDir
def comparesol(modelDir, localTree):
'''This reads a glm file, changes the method of powerflow and reruns'''
print "Testing GridlabD solver."
startTime = datetime.now()
binaryName = "gridlabd"
for key in localTree:
if "solver_method" in localTree[key].keys():
solvmeth = localTree[key]["solver_method"]
print "success", solvmeth
if solvmeth == 'NR':
localTree[key]["solver_method"] = 'FBS'
else:
localTree[key]["solver_method"] = 'NR'
# feeder.attachRecorders(localTree, "Regulator", "object", "regulator")
# feeder.attachRecorders(localTree, "CollectorVoltage", None, None)
# last_key = len(localTree)
# print last_key
for key in localTree:
if localTree[key].get('bustype', '').lower() == 'swing':
swingIndex = key
swingName = localTree[key].get('name')
print swingIndex, swingName
for key in localTree:
if localTree[key].get('object',
'') == 'regulator' and localTree[key].get(
'from', '') == swingName:
regIndex = key
regConfName = localTree[key]['configuration']
print regIndex
# Attach recorders relevant to CVR.
recorders = [{
'object':
'collector',
'file':
'ZlossesTransformer.csv',
'group':
'class=transformer',
'limit':
'0',
'property':
'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'
}, {
'object':
'collector',
'file':
'ZlossesUnderground.csv',
'group':
'class=underground_line',
'limit':
'0',
'property':
'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'
}, {
'object':
'collector',
'file':
'ZlossesOverhead.csv',
'group':
'class=overhead_line',
'limit':
'0',
'property':
'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'
}, {
'object': 'recorder',
'file': 'Zregulator.csv',
'limit': '0',
'parent': localTree[regIndex]['name'],
'property': 'tap_A,tap_B,tap_C,power_in.real,power_in.imag'
}, {
'object':
'collector',
'file':
'ZvoltageJiggle.csv',
'group':
'class=triplex_meter',
'limit':
'0',
'property':
'min(voltage_12.mag),mean(voltage_12.mag),max(voltage_12.mag),std(voltage_12.mag)'
}, {
'object': 'recorder',
'file': 'ZsubstationTop.csv',
'limit': '0',
'parent': localTree[swingIndex]['name'],
'property': 'voltage_A,voltage_B,voltage_C'
}, {
'object': 'recorder',
'file': 'ZsubstationBottom.csv',
'limit': '0',
'parent': localTree[regIndex]['to'],
'property': 'voltage_A,voltage_B,voltage_C'
}]
biggest = 1 + max([int(k) for k in localTree.keys()])
for index, rec in enumerate(recorders):
localTree[biggest + index] = rec
max_key = max([int(key) for key in localTree.keys()])
print max_key
regKeys = []
accum = ""
for key in localTree:
if localTree[key].get("object", "") == "regulator":
accum += localTree[key].get("name", "ERROR") + ","
regKeys.append(key)
regstr = accum[:-1]
print regKeys
print regstr, type(regstr)
localTree[max_key + 1] = {
'object': 'volt_var_control',
'name': 'volt_var_control',
'control_method': 'ACTIVE',
'capacitor_delay': '30.0',
'regulator_delay': '30.0',
'desired_pf': '0.99',
'd_max': '0.6',
'd_min': '0.1',
'substation_link': 'substation_transformer',
'regulator_list': regstr
}
feeder.adjustTime(tree=localTree,
simLength=float("8760"),
simLengthUnits="hours",
simStartDate="2012-01-01")
output = gridlabd.runInFilesystem(localTree,
keepFiles=True,
workDir=modelDir)
os.remove(pJoin(modelDir, "PID.txt"))
p = output['Zregulator.csv']['power_in.real']
q = output['Zregulator.csv']['power_in.imag']
xtime = {}
for key in output:
if '# timestamp' in output[key]:
xtime['timeStamps'] = output[key]['# timestamp']
#print type(xtime['timeStamps'][0])
#print len(p)
#xaxtick = str(xtime['timeStamps'])
# plt.plot(range(8760),p)
# plt.show()
# print "p=" , p
# print "q=" , q
print "DONE RUNNING", modelDir
def omfCalibrate(workDir, feederPath, scadaPath):
'''calibrates a feeder and saves the calibrated tree at a location'''
with open(feederPath, "r") as jsonIn:
feederJson = json.load(jsonIn)
tree = feederJson.get("tree", {})
scadaSubPower = _processScadaData(workDir, scadaPath)
# Force FBS powerflow, because NR fails a lot.
for key in tree:
if tree[key].get("module", "").lower() == "powerflow":
tree[key] = {"module": "powerflow", "solver_method": "FBS"}
# Attach player.
classOb = {
"class": "player",
"variable_names": ["value"],
"variable_types": ["double"]
}
playerOb = {
"object": "player",
"property": "value",
"name": "scadaLoads",
"file": "subScada.player",
"loop": "0"
}
maxKey = feeder.getMaxKey(tree)
tree[maxKey + 1] = classOb
tree[maxKey + 2] = playerOb
# Make loads reference player.
loadTemplate = {
"object": "triplex_load",
"power_pf_12": "0.95",
"impedance_pf_12": "0.98",
"power_pf_12": "0.90",
"impedance_fraction_12": "0.7",
"power_fraction_12": "0.3"
}
for key in tree:
ob = tree[key]
if ob.get("object",
"") == "triplex_node" and ob.get("power_12", "") != "":
newOb = dict(loadTemplate)
newOb["name"] = ob.get("name", "")
newOb["parent"] = ob.get("parent", "")
newOb["phases"] = ob.get("phases", "")
newOb["nominal_voltage"] = ob.get("nominal_voltage", "")
newOb["latitude"] = ob.get("latitude", "0")
newOb["longitude"] = ob.get("longitude", "0")
oldPow = ob.get("power_12", "").replace("j", "d")
pythagPower = gridlabd._strClean(oldPow)
newOb["base_power_12"] = "scadaLoads.value*" + str(pythagPower)
tree[key] = newOb
# Search for the substation regulator and attach a recorder there.
for key in tree:
if tree[key].get('bustype', '').lower() == 'swing':
swingName = tree[key].get('name')
for key in tree:
if tree[key].get('object', '') == 'regulator' and tree[key].get(
'from', '') == swingName:
regIndex = key
SUB_REG_NAME = tree[key]['name']
recOb = {
"object": "recorder",
"parent": SUB_REG_NAME,
"property": "power_in.real,power_in.imag",
"file": "caliSub.csv",
"interval": "900"
}
tree[maxKey + 3] = recOb
HOURS = 100
feeder.adjustTime(tree, HOURS, "hours", "2011-01-01")
# Run Gridlabd.
output = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=workDir)
# Calculate scaling constant.
outRealPow = output["caliSub.csv"]["power_in.real"]
outImagPower = output["caliSub.csv"]["power_in.imag"]
outAppPowerKw = [(x[0]**2 + x[1]**2)**0.5 / 1000
for x in zip(outRealPow, outImagPower)]
# HACK: ignore first time step in output and input because GLD sometimes breaks the first step.
SCAL_CONST = sum(scadaSubPower[1:HOURS]) / sum(outAppPowerKw[1:HOURS])
# Rewrite the subScada.player file so all the power values are multiplied by the SCAL_CONSTANT.
newPlayData = []
with open(pJoin(workDir, "subScada.player"), "r") as playerFile:
for line in playerFile:
(key, val) = line.split(',')
newPlayData.append(
str(key) + ',' + str(float(val) * SCAL_CONST) + "\n")
with open(pJoin(workDir, "subScadaCalibrated.player"), "w") as playerFile:
for row in newPlayData:
playerFile.write(row)
# Test by running a glm with subScadaCalibrated.player and caliSub.csv2.
tree[maxKey + 2]["file"] = "subScadaCalibrated.player"
tree[maxKey + 3]["file"] = "caliSubCheck.csv"
secondOutput = gridlabd.runInFilesystem(tree,
keepFiles=True,
workDir=workDir)
plt.plot(outAppPowerKw[1:HOURS], label="initialGuess")
plt.plot(scadaSubPower[1:HOURS], label="scadaSubPower")
secondAppKw = [
(x[0]**2 + x[1]**2)**0.5 / 1000
for x in zip(secondOutput["caliSubCheck.csv"]["power_in.real"],
secondOutput["caliSubCheck.csv"]["power_in.imag"])
]
plt.plot(secondAppKw[1:HOURS], label="finalGuess")
plt.legend(loc=3)
plt.savefig(pJoin(workDir, "caliCheckPlot.png"))
# Write the final output.
with open(pJoin(workDir, "calibratedFeeder.json"), "w") as outJson:
playerString = open(pJoin(workDir, "subScadaCalibrated.player")).read()
feederJson["attachments"]["subScadaCalibrated.player"] = playerString
feederJson["tree"] = tree
json.dump(feederJson, outJson, indent=4)
return
def runPowerflowIter(tree, scadaSubPower):
'''Runs powerflow once, then iterates.'''
# Run initial powerflow to get power.
print "Starting calibration."
print "Goal of calibration: Error: %s, Iterations: <%s, trim: %s" % (
calibrateError[0], calibrateError[1], trim)
output = gridlabd.runInFilesystem(tree,
keepFiles=True,
workDir=pJoin(workDir, "gridlabD"))
outRealPow = output["caliSub.csv"]["measured_real_power"][
trim:simLength]
outImagPower = output["caliSub.csv"]["measured_reactive_power"][
trim:simLength]
outAppPowerKw = [(x[0]**2 + x[1]**2)**0.5 / 1000
for x in zip(outRealPow, outImagPower)]
lastFile = "subScada.player"
nextFile = "subScadaCalibrated.player"
nextPower = outAppPowerKw
error = (sum(outRealPow) / 1000 -
sum(scadaSubPower)) / sum(scadaSubPower)
iteration = 1
print "First error:", error
while abs(error) > calibrateError[0] and iteration < calibrateError[1]:
# Run calibration and iterate up to 5 times.
SCAL_CONST = sum(scadaSubPower) / sum(nextPower)
print "Calibrating & running again... Error: %s, Iteration: %s, SCAL_CONST: %s" % (
str(round(abs(error * 100),
6)), str(iteration), round(SCAL_CONST, 6))
newPlayData = []
with open(pJoin(pJoin(workDir, "gridlabD"), lastFile),
"r") as playerFile:
for line in playerFile:
(key, val) = line.split(',')
newPlayData.append(
str(key) + ',' + str(float(val) * SCAL_CONST) + "\n")
with open(pJoin(pJoin(workDir, "gridlabD"), nextFile),
"w") as playerFile:
for row in newPlayData:
playerFile.write(row)
tree[playerKey]["file"] = nextFile
tree[outputRecorderKey]["file"] = "caliSubCheck.csv"
nextOutput = gridlabd.runInFilesystem(tree,
keepFiles=True,
workDir=pJoin(
workDir, "gridlabD"))
outRealPowIter = nextOutput["caliSubCheck.csv"][
"measured_real_power"][trim:simLength]
outImagPowerIter = nextOutput["caliSubCheck.csv"][
"measured_reactive_power"][trim:simLength]
nextAppKw = [(x[0]**2 + x[1]**2)**0.5 / 1000
for x in zip(outRealPowIter, outImagPowerIter)]
lastFile = nextFile
nextFile = "subScadaCalibrated" + str(iteration) + ".player"
nextPower = nextAppKw
# Compute error and iterate.
error = (sum(outRealPowIter) / 1000 -
sum(scadaSubPower)) / sum(scadaSubPower)
iteration += 1
else:
if iteration == 1: outRealPowIter = outRealPow
SCAL_CONST = 1.0
print "Calibration done: Error: %s, Iteration: %s, SCAL_CONST: %s" % (
str(round(abs(error * 100),
2)), str(iteration), round(SCAL_CONST, 2))
return outRealPow, outRealPowIter, lastFile, iteration
def omfCalibrate(workDir, feederPath, scadaPath):
'''calibrates a feeder and saves the calibrated tree at a location'''
with open(feederPath, "r") as jsonIn:
feederJson = json.load(jsonIn)
tree = feederJson.get("tree", {})
scadaSubPower = _processScadaData(workDir,scadaPath)
# Force FBS powerflow, because NR fails a lot.
for key in tree:
if tree[key].get("module","").lower() == "powerflow":
tree[key] = {"module":"powerflow","solver_method":"FBS"}
# Attach player.
classOb = {"class":"player", "variable_names":["value"], "variable_types":["double"]}
playerOb = {"object":"player", "property":"value", "name":"scadaLoads", "file":"subScada.player", "loop":"0"}
maxKey = feeder.getMaxKey(tree)
tree[maxKey+1] = classOb
tree[maxKey+2] = playerOb
# Make loads reference player.
loadTemplate = {"object": "triplex_load",
"power_pf_12": "0.95",
"impedance_pf_12": "0.98",
"power_pf_12": "0.90",
"impedance_fraction_12": "0.7",
"power_fraction_12": "0.3"}
for key in tree:
ob = tree[key]
if ob.get("object","") == "triplex_node" and ob.get("power_12","") != "":
newOb = dict(loadTemplate)
newOb["name"] = ob.get("name", "")
newOb["parent"] = ob.get("parent", "")
newOb["phases"] = ob.get("phases", "")
newOb["nominal_voltage"] = ob.get("nominal_voltage","")
newOb["latitude"] = ob.get("latitude","0")
newOb["longitude"] = ob.get("longitude","0")
oldPow = ob.get("power_12","").replace("j","d")
pythagPower = gridlabd._strClean(oldPow)
newOb["base_power_12"] = "scadaLoads.value*" + str(pythagPower)
tree[key] = newOb
# Search for the substation regulator and attach a recorder there.
for key in tree:
if tree[key].get('bustype','').lower() == 'swing':
swingName = tree[key].get('name')
for key in tree:
if tree[key].get('object','') == 'regulator' and tree[key].get('from','') == swingName:
regIndex = key
SUB_REG_NAME = tree[key]['name']
recOb = {"object": "recorder",
"parent": SUB_REG_NAME,
"property": "power_in.real,power_in.imag",
"file": "caliSub.csv",
"interval": "900"}
tree[maxKey + 3] = recOb
HOURS = 100
feeder.adjustTime(tree, HOURS, "hours", "2011-01-01")
# Run Gridlabd.
output = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=workDir)
# Calculate scaling constant.
outRealPow = output["caliSub.csv"]["power_in.real"]
outImagPower = output["caliSub.csv"]["power_in.imag"]
outAppPowerKw = [(x[0]**2 + x[1]**2)**0.5/1000 for x in zip(outRealPow, outImagPower)]
# HACK: ignore first time step in output and input because GLD sometimes breaks the first step.
SCAL_CONST = sum(scadaSubPower[1:HOURS])/sum(outAppPowerKw[1:HOURS])
# Rewrite the subScada.player file so all the power values are multiplied by the SCAL_CONSTANT.
newPlayData = []
with open(pJoin(workDir, "subScada.player"), "r") as playerFile:
for line in playerFile:
(key,val) = line.split(',')
newPlayData.append(str(key) + ',' + str(float(val)*SCAL_CONST) + "\n")
with open(pJoin(workDir, "subScadaCalibrated.player"), "w") as playerFile:
for row in newPlayData:
playerFile.write(row)
# Test by running a glm with subScadaCalibrated.player and caliSub.csv2.
tree[maxKey+2]["file"] = "subScadaCalibrated.player"
tree[maxKey + 3]["file"] = "caliSubCheck.csv"
secondOutput = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=workDir)
plt.plot(outAppPowerKw[1:HOURS], label="initialGuess")
plt.plot(scadaSubPower[1:HOURS], label="scadaSubPower")
secondAppKw = [(x[0]**2 + x[1]**2)**0.5/1000
for x in zip(secondOutput["caliSubCheck.csv"]["power_in.real"], secondOutput["caliSubCheck.csv"]["power_in.imag"])]
plt.plot(secondAppKw[1:HOURS], label="finalGuess")
plt.legend(loc=3)
plt.savefig(pJoin(workDir,"caliCheckPlot.png"))
# Write the final output.
with open(pJoin(workDir,"calibratedFeeder.json"),"w") as outJson:
playerString = open(pJoin(workDir,"subScadaCalibrated.player")).read()
feederJson["attachments"]["subScadaCalibrated.player"] = playerString
feederJson["tree"] = tree
json.dump(feederJson, outJson, indent=4)
return
def heavyProcessing(modelDir, inputDict):
''' Run the model in its directory. WARNING: GRIDLAB CAN TAKE HOURS TO COMPLETE. '''
print "STARTING TO RUN", modelDir
beginTime = datetime.datetime.now()
# Get feeder name and data in.
try: os.mkdir(pJoin(modelDir,'gldContainer'))
except: pass
try:
feederName = inputDict["feederName1"]
inputDict["climateName"], latforpvwatts = zipCodeToClimateName(inputDict["zipCode"])
shutil.copy(pJoin(__metaModel__._omfDir, "data", "Climate", inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, "gldContainer", "climate.tmy2"))
startTime = datetime.datetime.now()
feederJson = json.load(open(pJoin(modelDir, feederName+'.omd')))
tree = feederJson["tree"]
# Set up GLM with correct time and recorders:
feeder.attachRecorders(tree, "Regulator", "object", "regulator")
feeder.attachRecorders(tree, "Capacitor", "object", "capacitor")
feeder.attachRecorders(tree, "Inverter", "object", "inverter")
feeder.attachRecorders(tree, "Windmill", "object", "windturb_dg")
feeder.attachRecorders(tree, "CollectorVoltage", None, None)
feeder.attachRecorders(tree, "Climate", "object", "climate")
feeder.attachRecorders(tree, "OverheadLosses", None, None)
feeder.attachRecorders(tree, "UndergroundLosses", None, None)
feeder.attachRecorders(tree, "TriplexLosses", None, None)
feeder.attachRecorders(tree, "TransformerLosses", None, None)
feeder.groupSwingKids(tree)
# Attach recorders for system voltage map:
stub = {'object':'group_recorder', 'group':'"class=node"', 'property':'voltage_A', 'interval':3600, 'file':'aVoltDump.csv'}
for phase in ['A','B','C']:
copyStub = dict(stub)
copyStub['property'] = 'voltage_' + phase
copyStub['file'] = phase.lower() + 'VoltDump.csv'
tree[feeder.getMaxKey(tree) + 1] = copyStub
feeder.adjustTime(tree=tree, simLength=float(inputDict["simLength"]),
simLengthUnits=inputDict["simLengthUnits"], simStartDate=inputDict["simStartDate"])
# RUN GRIDLABD IN FILESYSTEM (EXPENSIVE!)
rawOut = gridlabd.runInFilesystem(tree, attachments=feederJson["attachments"],
keepFiles=True, workDir=pJoin(modelDir,'gldContainer'))
cleanOut = {}
# Std Err and Std Out
cleanOut['stderr'] = rawOut['stderr']
cleanOut['stdout'] = rawOut['stdout']
# Time Stamps
for key in rawOut:
if '# timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# timestamp']
break
elif '# property.. timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# property.. timestamp']
else:
cleanOut['timeStamps'] = []
# Day/Month Aggregation Setup:
stamps = cleanOut.get('timeStamps',[])
level = inputDict.get('simLengthUnits','hours')
# Climate
for key in rawOut:
if key.startswith('Climate_') and key.endswith('.csv'):
cleanOut['climate'] = {}
cleanOut['climate']['Rain Fall (in/h)'] = hdmAgg(rawOut[key].get('rainfall'), sum, level)
cleanOut['climate']['Wind Speed (m/s)'] = hdmAgg(rawOut[key].get('wind_speed'), avg, level)
cleanOut['climate']['Temperature (F)'] = hdmAgg(rawOut[key].get('temperature'), max, level)
cleanOut['climate']['Snow Depth (in)'] = hdmAgg(rawOut[key].get('snowdepth'), max, level)
cleanOut['climate']['Direct Normal (W/sf)'] = hdmAgg(rawOut[key].get('solar_direct'), sum, level)
#cleanOut['climate']['Global Horizontal (W/sf)'] = hdmAgg(rawOut[key].get('solar_global'), sum, level)
climateWbySFList= hdmAgg(rawOut[key].get('solar_global'), sum, level)
#converting W/sf to W/sm
climateWbySMList= [x*10.76392 for x in climateWbySFList]
cleanOut['climate']['Global Horizontal (W/sm)']=climateWbySMList
# Voltage Band
if 'VoltageJiggle.csv' in rawOut:
cleanOut['allMeterVoltages'] = {}
cleanOut['allMeterVoltages']['Min'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['min(voltage_12.mag)']], min, level)
cleanOut['allMeterVoltages']['Mean'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['mean(voltage_12.mag)']], avg, level)
cleanOut['allMeterVoltages']['StdDev'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['std(voltage_12.mag)']], avg, level)
cleanOut['allMeterVoltages']['Max'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['max(voltage_12.mag)']], max, level)
# Power Consumption
cleanOut['Consumption'] = {}
# Set default value to be 0, avoiding missing value when computing Loads
cleanOut['Consumption']['Power'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['Losses'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['DG'] = [0] * int(inputDict["simLength"])
for key in rawOut:
if key.startswith('SwingKids_') and key.endswith('.csv'):
oneSwingPower = hdmAgg(vecPyth(rawOut[key]['sum(power_in.real)'],rawOut[key]['sum(power_in.imag)']), avg, level)
if 'Power' not in cleanOut['Consumption']:
cleanOut['Consumption']['Power'] = oneSwingPower
else:
cleanOut['Consumption']['Power'] = vecSum(oneSwingPower,cleanOut['Consumption']['Power'])
elif key.startswith('Inverter_') and key.endswith('.csv'):
realA = rawOut[key]['power_A.real']
realB = rawOut[key]['power_B.real']
realC = rawOut[key]['power_C.real']
imagA = rawOut[key]['power_A.imag']
imagB = rawOut[key]['power_B.imag']
imagC = rawOut[key]['power_C.imag']
oneDgPower = hdmAgg(vecSum(vecPyth(realA,imagA),vecPyth(realB,imagB),vecPyth(realC,imagC)), avg, level)
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(oneDgPower,cleanOut['Consumption']['DG'])
elif key.startswith('Windmill_') and key.endswith('.csv'):
vrA = rawOut[key]['voltage_A.real']
vrB = rawOut[key]['voltage_B.real']
vrC = rawOut[key]['voltage_C.real']
viA = rawOut[key]['voltage_A.imag']
viB = rawOut[key]['voltage_B.imag']
viC = rawOut[key]['voltage_C.imag']
crB = rawOut[key]['current_B.real']
crA = rawOut[key]['current_A.real']
crC = rawOut[key]['current_C.real']
ciA = rawOut[key]['current_A.imag']
ciB = rawOut[key]['current_B.imag']
ciC = rawOut[key]['current_C.imag']
powerA = vecProd(vecPyth(vrA,viA),vecPyth(crA,ciA))
powerB = vecProd(vecPyth(vrB,viB),vecPyth(crB,ciB))
powerC = vecProd(vecPyth(vrC,viC),vecPyth(crC,ciC))
oneDgPower = hdmAgg(vecSum(powerA,powerB,powerC), avg, level)
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(oneDgPower,cleanOut['Consumption']['DG'])
elif key in ['OverheadLosses.csv', 'UndergroundLosses.csv', 'TriplexLosses.csv', 'TransformerLosses.csv']:
realA = rawOut[key]['sum(power_losses_A.real)']
imagA = rawOut[key]['sum(power_losses_A.imag)']
realB = rawOut[key]['sum(power_losses_B.real)']
imagB = rawOut[key]['sum(power_losses_B.imag)']
realC = rawOut[key]['sum(power_losses_C.real)']
imagC = rawOut[key]['sum(power_losses_C.imag)']
oneLoss = hdmAgg(vecSum(vecPyth(realA,imagA),vecPyth(realB,imagB),vecPyth(realC,imagC)), avg, level)
if 'Losses' not in cleanOut['Consumption']:
cleanOut['Consumption']['Losses'] = oneLoss
else:
cleanOut['Consumption']['Losses'] = vecSum(oneLoss,cleanOut['Consumption']['Losses'])
elif key.startswith('Regulator_') and key.endswith('.csv'):
#split function to strip off .csv from filename and user rest of the file name as key. for example- Regulator_VR10.csv -> key would be Regulator_VR10
regName=""
regName = key
newkey=regName.split(".")[0]
cleanOut[newkey] ={}
cleanOut[newkey]['RegTapA'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['RegTapB'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['RegTapC'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['RegTapA'] = rawOut[key]['tap_A']
cleanOut[newkey]['RegTapB'] = rawOut[key]['tap_B']
cleanOut[newkey]['RegTapC'] = rawOut[key]['tap_C']
cleanOut[newkey]['RegPhases'] = rawOut[key]['phases'][0]
elif key.startswith('Capacitor_') and key.endswith('.csv'):
capName=""
capName = key
newkey=capName.split(".")[0]
cleanOut[newkey] ={}
cleanOut[newkey]['Cap1A'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['Cap1B'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['Cap1C'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['Cap1A'] = rawOut[key]['switchA']
cleanOut[newkey]['Cap1B'] = rawOut[key]['switchB']
cleanOut[newkey]['Cap1C'] = rawOut[key]['switchC']
cleanOut[newkey]['CapPhases'] = rawOut[key]['phases'][0]
# What percentage of our keys have lat lon data?
latKeys = [tree[key]['latitude'] for key in tree if 'latitude' in tree[key]]
latPerc = 1.0*len(latKeys)/len(tree)
if latPerc < 0.25: doNeato = True
else: doNeato = False
# Generate the frames for the system voltage map time traveling chart.
genTime = generateVoltChart(tree, rawOut, modelDir, neatoLayout=doNeato)
cleanOut['genTime'] = genTime
# Aggregate up the timestamps:
if level=='days':
cleanOut['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:10], 'days')
elif level=='months':
cleanOut['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:7], 'months')
# Write the output.
with open(pJoin(modelDir, "allOutputData.json"),"w") as outFile:
json.dump(cleanOut, outFile, indent=4)
# Update the runTime in the input file.
endTime = datetime.datetime.now()
inputDict["runTime"] = str(datetime.timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir, "allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent=4)
# Clean up the PID file.
os.remove(pJoin(modelDir, "gldContainer", "PID.txt"))
print "DONE RUNNING", modelDir
except Exception as e:
# If input range wasn't valid delete output, write error to disk.
cancel(modelDir)
thisErr = traceback.format_exc()
print 'ERROR IN MODEL', modelDir, thisErr
inputDict['stderr'] = thisErr
with open(os.path.join(modelDir,'stderr.txt'),'w') as errorFile:
errorFile.write(thisErr)
with open(pJoin(modelDir,"allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent=4)
finishTime = datetime.datetime.now()
inputDict["runTime"] = str(datetime.timedelta(seconds = int((finishTime - beginTime).total_seconds())))
with open(pJoin(modelDir, "allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent = 4)
try:
os.remove(pJoin(modelDir,"PPID.txt"))
except:
pass
