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"]
#add a check to see if there is already a climate object in the omd file
#if there is delete the climate from attachments and the climate object
attachKeys = feederJson["attachments"].keys()
for key in attachKeys:
if key.endswith('.tmy2'):
del feederJson['attachments'][key]
treeKeys = feederJson["tree"].keys()
for key in treeKeys:
if 'object' in feederJson['tree'][key]:
if feederJson['tree'][key]['object'] == 'climate':
del feederJson['tree'][key]
oldMax = feeder.getMaxKey(tree)
tree[oldMax + 1] = {'omftype':'module', 'argument':'climate'}
tree[oldMax + 2] ={'object':'climate','name':'Climate','interpolate':'QUADRATIC', 'tmyfile':'climate.tmy2'}
# 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
def runForeground(modelDir):
''' Run the model in its directory. WARNING: GRIDLAB CAN TAKE HOURS TO COMPLETE. '''
inputDict = json.load(open(pJoin(modelDir, 'allInputData.json')))
print "STARTING TO RUN", modelDir
beginTime = datetime.datetime.now()
# 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 the names of the feeders from the .omd files:
feederNames = [x[0:-4] for x in os.listdir(modelDir) if x.endswith(".omd")]
for i, key in enumerate(feederNames):
inputDict['feederName' + str(i + 1)] = feederNames[i]
# Run GridLAB-D once for each feeder:
for feederName in feederNames:
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"] = zipCodeToClimateName(inputDict["zipCode"])
shutil.copy(pJoin(_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 work(modelDir, inputDict):
''' Run the model in its directory. WARNING: GRIDLAB CAN TAKE HOURS TO COMPLETE. '''
# feederName = inputDict["feederName1"]
feederName = [x for x in os.listdir(modelDir) if x.endswith('.omd')][0][:-4]
inputDict["feederName1"] = feederName
inputDict["climateName"] = zipCodeToClimateName(inputDict["zipCode"])
shutil.copy(pJoin(__neoMetaModel__._omfDir, "data", "Climate", inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, "climate.tmy2"))
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"', 'interval':3600}
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
# Attach recorders for system voltage map, triplex:
stub = {'object':'group_recorder', 'group':'"class=triplex_node"', 'interval':3600}
for phase in ['1','2']:
copyStub = dict(stub)
copyStub['property'] = 'voltage_' + phase
copyStub['file'] = phase.lower() + 'nVoltDump.csv'
tree[feeder.getMaxKey(tree) + 1] = copyStub
# Attach current recorder for overhead_lines
currentStub = {'object':'group_recorder', 'group':'"class=overhead_line"', 'interval':3600}
for phase in ['A','B','C']:
copyCurrentStub = dict(currentStub)
copyCurrentStub['property'] = 'current_out_' + phase
copyCurrentStub['file'] = 'OH_line_current_phase' + phase + '.csv'
tree[feeder.getMaxKey(tree) + 1] = copyCurrentStub
rating_stub = {'object':'group_recorder', 'group':'"class=overhead_line"', 'interval':3600}
copyRatingStub = dict(rating_stub)
copyRatingStub['property'] = 'continuous_rating'
copyRatingStub['file'] = 'OH_line_cont_rating.csv'
tree[feeder.getMaxKey(tree) + 1] = copyRatingStub
flow_stub = {'object':'group_recorder', 'group':'"class=overhead_line"', 'interval':3600}
copyFlowStub = dict(flow_stub)
copyFlowStub['property'] = 'flow_direction'
copyFlowStub['file'] = 'OH_line_flow_direc.csv'
tree[feeder.getMaxKey(tree) + 1] = copyFlowStub
# Attach current recorder for underground_lines
currentStubOH = {'object':'group_recorder', 'group':'"class=underground_line"', 'interval':3600}
for phase in ['A','B','C']:
copyCurrentStubOH = dict(currentStubOH)
copyCurrentStubOH['property'] = 'current_out_' + phase
copyCurrentStubOH['file'] = 'UG_line_current_phase' + phase + '.csv'
tree[feeder.getMaxKey(tree) + 1] = copyCurrentStubOH
ug_rating_stub = {'object':'group_recorder', 'group':'"class=underground_line"', 'interval':3600}
copyUGRatingStub = dict(ug_rating_stub)
copyUGRatingStub['property'] = 'continuous_rating'
copyUGRatingStub['file'] = 'UG_line_cont_rating.csv'
tree[feeder.getMaxKey(tree) + 1] = copyUGRatingStub
ug_flow_stub = {'object':'group_recorder', 'group':'"class=underground_line"', 'interval':3600}
ugCopyFlowStub = dict(ug_flow_stub)
ugCopyFlowStub['property'] = 'flow_direction'
ugCopyFlowStub['file'] = 'UG_line_flow_direc.csv'
tree[feeder.getMaxKey(tree) + 1] = ugCopyFlowStub
# And get meters for system voltage map:
stub = {'object':'group_recorder', 'group':'"class=triplex_meter"', 'interval':3600}
for phase in ['1','2']:
copyStub = dict(stub)
copyStub['property'] = 'voltage_' + phase
copyStub['file'] = phase.lower() + 'mVoltDump.csv'
tree[feeder.getMaxKey(tree) + 1] = copyStub
for key in tree:
if 'bustype' in tree[key].keys():
if tree[key]['bustype'] == 'SWING':
tree[key]['object'] = 'meter'
swingN = tree[key]['name']
swingRecord = {'object':'recorder', 'property':'voltage_A,measured_real_power,measured_power','file':'subVoltsA.csv','parent':swingN, 'interval':60}
tree[feeder.getMaxKey(tree) + 1] = swingRecord
for key in tree:
if 'omftype' in tree[key].keys() and tree[key]['argument']=='minimum_timestep=3600':
tree[key]['argument'] = 'minimum_timestep=60'
# If there is a varvolt object in the tree, add recorder to swingbus and node from voltage_measurements property
# Find var_volt object
downLineNode = 'None'
for key in tree:
if 'object' in tree[key].keys() and tree[key]['object']=='volt_var_control':
downLineNode = tree[key]['voltage_measurements']
if downLineNode != 'None':
downNodeRecord = {'object':'recorder', 'property':'voltage_A','file':'firstDownlineVoltsA.csv','parent':downLineNode, 'interval':60}
tree[feeder.getMaxKey(tree) + 1] = downNodeRecord
# Violation recorder to display to users
# violationRecorder = {'object':'violation_recorder','node_continuous_voltage_limit_lower':0.95,'file':'Violation_Log.csv',
# 'secondary_dist_voltage_rise_lower_limit':-0.042,'substation_pf_lower_limit':0.85,'substation_breaker_C_limit':300,
# 'secondary_dist_voltage_rise_upper_limit':0.025,'substation_breaker_B_limit':300,'violation_flag':'ALLVIOLATIONS',
# 'node_instantaneous_voltage_limit_upper':1.1, 'inverter_v_chng_per_interval_lower_bound':-0.05, 'virtual_substation':swingN,
# 'substation_breaker_A_limit':300, 'xfrmr_thermal_limit_lower':0,'node_continuous_voltage_interval':300,'strict':'false',
# 'node_instantaneous_voltage_limit_lower':0,'line_thermal_limit_upper':1,'echo':'false','node_continuous_voltage_limit_upper':1.05,
# 'interval':30,'line_thermal_limit_lower':0,'summary':'Violation_Summary.csv','inverter_v_chng_interval':60,
# 'xfrmr_thermal_limit_upper':2,'inverter_v_chng_per_interval_upper_bound':0.050}
# tree[feeder.getMaxKey(tree) + 1] = violationRecorder
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))
# voltDumps have no values when gridlabD fails or the files dont exist
if not os.path.isfile(pJoin(modelDir,'aVoltDump.csv')):
with open (pJoin(modelDir,'stderr.txt')) as inFile:
stdErrText = inFile.read()
message = 'GridLAB-D crashed. Error log:\n' + stdErrText
raise Exception(message)
elif len(rawOut['aVoltDump.csv']['# timestamp']) == 0:
with open (pJoin(modelDir,'stderr.txt')) as inFile:
stdErrText = inFile.read()
message = 'GridLAB-D crashed. Error log:\n' + stdErrText
raise Exception(message)
outData = {}
# Std Err and Std Out
outData['stderr'] = rawOut['stderr']
outData['stdout'] = rawOut['stdout']
# Time Stamps
for key in rawOut:
if '# timestamp' in rawOut[key]:
outData['timeStamps'] = rawOut[key]['# timestamp']
break
elif '# property.. timestamp' in rawOut[key]:
outData['timeStamps'] = rawOut[key]['# property.. timestamp']
else:
outData['timeStamps'] = []
# Day/Month Aggregation Setup:
stamps = outData.get('timeStamps',[])
level = inputDict.get('simLengthUnits','hours')
# Climate
for key in rawOut:
if key.startswith('Climate_') and key.endswith('.csv'):
outData['climate'] = {}
outData['climate']['Rain Fall (in/h)'] = hdmAgg(rawOut[key].get('rainfall'), sum, level)
outData['climate']['Wind Speed (m/s)'] = hdmAgg(rawOut[key].get('wind_speed'), avg, level)
outData['climate']['Temperature (F)'] = hdmAgg(rawOut[key].get('temperature'), max, level)
outData['climate']['Snow Depth (in)'] = hdmAgg(rawOut[key].get('snowdepth'), max, level)
outData['climate']['Direct Normal (W/sf)'] = hdmAgg(rawOut[key].get('solar_direct'), sum, level)
#outData['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]
outData['climate']['Global Horizontal (W/sm)']=climateWbySMList
# Voltage Band
if 'VoltageJiggle.csv' in rawOut:
outData['allMeterVoltages'] = {}
outData['allMeterVoltages']['Min'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['min(voltage_12.mag)']], min, level)
outData['allMeterVoltages']['Mean'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['mean(voltage_12.mag)']], avg, level)
outData['allMeterVoltages']['StdDev'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['std(voltage_12.mag)']], avg, level)
outData['allMeterVoltages']['Max'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['max(voltage_12.mag)']], max, level)
# Power Consumption
outData['Consumption'] = {}
# Set default value to be 0, avoiding missing value when computing Loads
outData['Consumption']['Power'] = [0] * int(inputDict["simLength"])
outData['Consumption']['Losses'] = [0] * int(inputDict["simLength"])
outData['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 outData['Consumption']:
outData['Consumption']['Power'] = oneSwingPower
else:
outData['Consumption']['Power'] = vecSum(oneSwingPower,outData['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 outData['Consumption']:
outData['Consumption']['DG'] = oneDgPower
else:
outData['Consumption']['DG'] = vecSum(oneDgPower,outData['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 outData['Consumption']:
outData['Consumption']['DG'] = oneDgPower
else:
outData['Consumption']['DG'] = vecSum(oneDgPower,outData['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 outData['Consumption']:
outData['Consumption']['Losses'] = oneLoss
else:
outData['Consumption']['Losses'] = vecSum(oneLoss,outData['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]
outData[newkey] ={}
outData[newkey]['RegTapA'] = [0] * int(inputDict["simLength"])
outData[newkey]['RegTapB'] = [0] * int(inputDict["simLength"])
outData[newkey]['RegTapC'] = [0] * int(inputDict["simLength"])
outData[newkey]['RegTapA'] = rawOut[key]['tap_A']
outData[newkey]['RegTapB'] = rawOut[key]['tap_B']
outData[newkey]['RegTapC'] = rawOut[key]['tap_C']
outData[newkey]['RegPhases'] = rawOut[key]['phases'][0]
elif key.startswith('Capacitor_') and key.endswith('.csv'):
capName=""
capName = key
newkey=capName.split(".")[0]
outData[newkey] ={}
outData[newkey]['Cap1A'] = [0] * int(inputDict["simLength"])
outData[newkey]['Cap1B'] = [0] * int(inputDict["simLength"])
outData[newkey]['Cap1C'] = [0] * int(inputDict["simLength"])
outData[newkey]['Cap1A'] = rawOut[key]['switchA']
outData[newkey]['Cap1B'] = rawOut[key]['switchB']
outData[newkey]['Cap1C'] = rawOut[key]['switchC']
outData[newkey]['CapPhases'] = rawOut[key]['phases'][0]
# Capture voltages at the swingbus
# Loop through voltDump for swingbus voltages
subData = []
downData = []
with open(pJoin(modelDir,"subVoltsA.csv")) as subFile:
reader = csv.reader(subFile)
subData = [x for x in reader]
if downLineNode != 'None':
with open(pJoin(modelDir,"firstDownlineVoltsA.csv")) as downFile:
reader = csv.reader(downFile)
downData = [x for x in reader]
FIRST_DATA_ROW = 9
cleanDown = [stringToMag(x[1]) for x in downData[FIRST_DATA_ROW:-1]]
swingTimestamps = [x[0] for x in subData[FIRST_DATA_ROW:-1]]
cleanSub = [stringToMag(x[1]) for x in subData[FIRST_DATA_ROW:-1]]
# real_power / power
powerFactors = []
for row in subData[FIRST_DATA_ROW:-1]:
powerFactors.append(abs(float(row[2])/stringToMag(row[3])))
outData['powerFactors'] = powerFactors
outData['swingVoltage'] = cleanSub
outData['downlineNodeVolts'] = cleanDown
outData['swingTimestamps'] = swingTimestamps
# If there is a var volt system, find the min and max voltage for a band
minVoltBand = []
maxVoltBand = []
if downLineNode != 'None':
for key in tree:
objKeys = tree[key].keys()
if 'object' in objKeys:
if tree[key]['object']=='volt_var_control':
minVoltBand.append(float(tree[key]['minimum_voltages']))
maxVoltBand.append(float(tree[key]['maximum_voltages']))
outData['minVoltBand'] = minVoltBand
outData['maxVoltBand'] = maxVoltBand
# Violation Summary and Log
# violationData = ''
# violationArray = []
# with open(pJoin(modelDir,"Violation_Summary.csv")) as vioSum:
# reader = csv.reader(vioSum)
# for row in reader:
# violationArray.append(row)
# for row in violationArray[4:]:
# violationData += str(' '.join(row)) + "\n"
# outData["violationSummary"] = violationData
# violationLogArray = []
# violationLog = ''
# with open(pJoin(modelDir,"Violation_Log.csv")) as vioLog:
# logger = csv.reader(vioLog)
# for row in logger:
# violationLogArray.append(row)
# for row in violationLogArray[6:]:
# violationLog += str(' '.join(row)) + "\n"
# outData['violationLog'] = violationLog
# 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, mapTimestamp = generateVoltChart(tree, rawOut, modelDir, neatoLayout=doNeato)
outData['genTime'] = genTime
outData['mapTimestamp'] = mapTimestamp
# Aggregate up the timestamps:
if level=='days':
outData['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:10], 'days')
elif level=='months':
outData['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:7], 'months')
return outData
def runForeground(modelDir, inputDict, fs):
""" Run the model in its directory. WARNING: GRIDLAB CAN TAKE HOURS TO COMPLETE. """
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"))
fs.remove(pJoin(modelDir, feederName, "allOutputData.json"))
except Exception, e:
pass
if not os.path.isdir(pJoin(modelDir, feederName)):
# create subfolders for feeders
os.makedirs(pJoin(modelDir, feederName))
fs.export_from_fs_to_local(
pJoin("data", "Feeder", feederDir, feederName + ".json"), pJoin(modelDir, feederName, "feeder.json")
)
inputDict["climateName"], latforpvwatts = zipCodeToClimateName(inputDict["zipCode"], fs)
fs.export_from_fs_to_local(
pJoin("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"],
)
if "attachments" in feederJson:
attachments = feederJson["attachments"]
else:
attachments = []
# RUN GRIDLABD IN FILESYSTEM (EXPENSIVE!)
rawOut = gridlabd.runInFilesystem(
tree, attachments=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, stamps
)
cleanOut["climate"]["Wind Speed (m/s)"] = hdmAgg(
rawOut[key].get("wind_speed"), avg, level, stamps
)
cleanOut["climate"]["Temperature (F)"] = hdmAgg(
rawOut[key].get("temperature"), max, level, stamps
)
cleanOut["climate"]["Snow Depth (in)"] = hdmAgg(
rawOut[key].get("snowdepth"), max, level, stamps
)
cleanOut["climate"]["Direct Insolation (W/m^2)"] = hdmAgg(
rawOut[key].get("solar_direct"), sum, level, stamps
)
# 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, stamps
)
cleanOut["allMeterVoltages"]["Mean"] = hdmAgg(
[float(i / 2) for i in rawOut["VoltageJiggle.csv"]["mean(voltage_12.mag)"]], avg, level, stamps
)
cleanOut["allMeterVoltages"]["StdDev"] = hdmAgg(
[float(i / 2) for i in rawOut["VoltageJiggle.csv"]["std(voltage_12.mag)"]], avg, level, stamps
)
cleanOut["allMeterVoltages"]["Max"] = hdmAgg(
[float(i / 2) for i in rawOut["VoltageJiggle.csv"]["max(voltage_12.mag)"]], max, level, stamps
)
# 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,
stamps,
)
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,
stamps,
)
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, stamps)]
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,
stamps,
)
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 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"]
weather = inputDict["weather"]
if weather == "typical":
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()
else:
#hack for testing
makeClimateCsv('2010-07-01', '2010-08-01', 'DFW', 'Output/Automated dsoSimSuite Test/gldContainer/weather.csv')
startTime = datetime.datetime.now()
startTime = datetime.datetime.now()
feederJson = json.load(open(pJoin(modelDir, feederName+'.omd')))
tree = feederJson["tree"]
#add a check to see if there is already a climate object in the omd file
#if there is delete the climate from attachments and the climate object
attachKeys = feederJson["attachments"].keys()
for key in attachKeys:
if key.endswith('.tmy2'):
del feederJson['attachments'][key]
treeKeys = feederJson["tree"].keys()
for key in treeKeys:
if 'object' in feederJson['tree'][key]:
if feederJson['tree'][key]['object'] == 'climate':
del feederJson['tree'][key]
#add weather objects and modules to .glm if there is no climate file in the omd file
if weather == "historical":
oldMax = feeder.getMaxKey(tree)
tree[oldMax + 1] = {'omftype':'module', 'argument':'tape'}
tree[oldMax + 2] = {'omftype':'module', 'argument':'climate'}
tree[oldMax + 3] = {'object':'csv_reader', 'name':'weatherReader', 'filename':'weather.csv'}
tree[oldMax + 4] = {'object':'climate', 'name':'exampleClimate', 'tmyfile':'weather.csv', 'reader':'weatherReader'}
else:
oldMax = feeder.getMaxKey(tree)
tree[oldMax + 1] ={'object':'climate','name':'Climate','interpolate':'QUADRATIC', 'tmyfile':'climate.tmy2'}
# 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
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"]
#add a check to see if there is already a climate object in the omd file
#if there is delete the climate from attachments and the climate object
attachKeys = feederJson["attachments"].keys()
for key in attachKeys:
if key.endswith('.tmy2'):
del feederJson['attachments'][key]
treeKeys = feederJson["tree"].keys()
for key in treeKeys:
if 'object' in feederJson['tree'][key]:
if feederJson['tree'][key]['object'] == 'climate':
del feederJson['tree'][key]
oldMax = feeder.getMaxKey(tree)
tree[oldMax + 1] = {'omftype':'module','argument':'climate'}
tree[oldMax + 2] = {'object':'climate','name':'Climate','interpolate':'QUADRATIC','tmyfile':'climate.tmy2'}
# tree[oldMax + 3] = {'object':'capacitor','control':'VOLT','phases':'ABCN','name':'CAPTEST','parent':'tm_1','capacitor_A':'0.10 MVAr','capacitor_B':'0.10 MVAr','capacitor_C':'0.10 MVAr','time_delay':'300.0','nominal_voltage':'2401.7771','voltage_set_high':'2350.0','voltage_set_low':'2340.0','switchA':'CLOSED','switchB':'CLOSED','switchC':'CLOSED','control_level':'INDIVIDUAL','phases_connected':'ABCN','dwell_time':'0.0','pt_phases':'ABCN'}
# 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 recorder for waterheaters on/off
stub = {'object':'group_recorder', 'group':'"class=waterheater"', 'property':'is_waterheater_on', 'interval':3600, 'file':'allWaterheaterOn.csv'}
copyStub = dict(stub)
tree[feeder.getMaxKey(tree)+1] = copyStub
# Attach recorder for waterheater tank temperatures
stub = {'object':'group_recorder', 'group':'"class=waterheater"', 'property':'temperature', 'interval':3600, 'file':'allWaterheaterTemp.csv'}
copyStub = dict(stub)
tree[feeder.getMaxKey(tree)+1] = copyStub
# Attach collector for total waterheater load
stub = {'object':'collector', 'group':'"class=waterheater"', 'property':'sum(actual_load)', 'interval':3600, 'file':'allWaterheaterLoad.csv'}
copyStub = dict(stub)
tree[feeder.getMaxKey(tree)+1] = copyStub
# Attach collector for total network load
stub = {'object':'collector', 'group':'"class=triplex_meter"', 'property':'sum(measured_real_power)', 'interval':3600, 'file':'allMeterPower.csv'}
copyStub = dict(stub)
tree[feeder.getMaxKey(tree)+1] = copyStub
# Attach collector for total overall ZIPload power/load
stub = {'object':'collector', 'group':'"class=ZIPload"', 'property':'sum(base_power)', 'interval':3600, 'file':'allZIPloadPower.csv'}
copyStub = dict(stub)
tree[feeder.getMaxKey(tree)+1] = copyStub
# Attach recorder for each ZIPload power/load
stub = {'object':'group_recorder', 'group':'"class=ZIPload"', 'property':'base_power', 'interval':3600, 'file':'eachZIPloadPower.csv'}
copyStub = dict(stub)
tree[feeder.getMaxKey(tree)+1] = copyStub
# Attach recorder for all ZIPloads demand_rate
stub = {'object':'group_recorder', 'group':'"class=ZIPload"', 'property':'demand_rate', 'interval':3600, 'file':'allZIPloadDemand.csv'}
copyStub = dict(stub)
tree[feeder.getMaxKey(tree)+1] = copyStub
# Attach recorder for all ZIPloads on
stub = {'object':'group_recorder', 'group':'"class=ZIPload"', 'property':'number_of_devices_on', 'interval':3600, 'file':'allZIPloadOn.csv'}
copyStub = dict(stub)
tree[feeder.getMaxKey(tree)+1] = copyStub
# Attach passive_controller
tree[feeder.getMaxKey(tree)+1] = {'omftype':'module','argument':'market'}
tree[feeder.getMaxKey(tree)+1] = {'omftype':'class auction','argument':'{\n\tdouble my_avg; double my_std;\n}'}
tree[feeder.getMaxKey(tree)+1] = {'omftype':'class player','argument':'{\n\tdouble value;\n}'}
stub = {
'object':'player',
'name':'cppDays',
'file':'superCpp.player'
}
copyStub = dict(stub)
tree[feeder.getMaxKey(tree)+1] = copyStub
stub = {
'object':'player',
'name':'superClearing',
'file':'superClearingPrice.player',
'loop':10
}
copyStub = dict(stub)
tree[feeder.getMaxKey(tree)+1] = copyStub
stub = {
'object':'auction',
'name':'MARKET_1',
'my_std':0.037953,
'period':900,
'my_avg':0.110000,
'current_market.clearing_price':'superClearing.value',
'special_mode':'BUYERS_ONLY',
'unit': 'kW'
}
copyStub = dict(stub)
tree[feeder.getMaxKey(tree)+1] = copyStub
stub = {
'object':'passive_controller',
'name':'waterheater_controller_waterheater171923',
'parent':'waterheater171923',
'control_mode':'RAMP',
'range_high':5,
'range_low':-5,
'ramp_high':1,
'ramp_low':-1,
'period':900,
'setpoint':'is_waterheater_on',
'base_setpoint':1,
'expectation_object':'MARKET_1',
'expectation_property':'my_avg',
'observation_object':'MARKET_1',
'observation_property':'past_market.clearing_price',
'stdev_observation_property':'my_std',
'state_property':'override'
}
copyStub = dict(stub)
tree[feeder.getMaxKey(tree)+1] = copyStub
# stub = {
# 'object':'passive_controller',
# 'name':'ZIPload_controller_ZIPload171922',
# 'parent':'ZIPload171922',
# 'control_mode':'RAMP',
# 'range_high':5,
# 'range_low':-5,
# 'ramp_high':1,
# 'ramp_low':-1,
# 'period':900,
# 'setpoint':'base_power'
# 'base_setpoint':1,
# 'expectation_object':'MARKET_1',
# 'expectation_property':'my_avg',
# 'observation_object':'MARKET_1',
# 'observation_property':'past_market.clearing_price',
# 'stdev_observation_property':'my_std'
# 'state_property':'override'
# }
# copyStub = dict(stub)
# tree[feeder.getMaxKey(tree)+1] = copyStub
# Attach recorders for system voltage map:
stub = {'object':'group_recorder', 'group':'"class=node"', 'interval':3600}
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
# Attach recorders for system voltage map, triplex:
stub = {'object':'group_recorder', 'group':'"class=triplex_node"', 'interval':3600}
for phase in ['1','2']:
copyStub = dict(stub)
copyStub['property'] = 'voltage_' + phase
copyStub['file'] = phase.lower() + 'nVoltDump.csv'
tree[feeder.getMaxKey(tree) + 1] = copyStub
# And get meters for system voltage map:
stub = {'object':'group_recorder', 'group':'"class=triplex_meter"', 'interval':3600}
for phase in ['1','2']:
copyStub = dict(stub)
copyStub['property'] = 'voltage_' + phase
copyStub['file'] = phase.lower() + 'mVoltDump.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:
print key
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]
# Print gridBallast Outputs to allOutputData.json
cleanOut['gridBallast'] = {}
if 'allWaterheaterOn.csv' in rawOut:
cleanOut['gridBallast']['waterheaterOn'] = {}
for key in rawOut['allWaterheaterOn.csv']:
if key.startswith('waterheater'):
cleanOut['gridBallast']['waterheaterOn'][key] = rawOut.get('allWaterheaterOn.csv')[key]
if 'allWaterheaterTemp.csv' in rawOut:
cleanOut['gridBallast']['waterheaterTemp'] = {}
for key in rawOut['allWaterheaterTemp.csv']:
if key.startswith('waterheater'):
cleanOut['gridBallast']['waterheaterTemp'][key] = rawOut.get('allWaterheaterTemp.csv')[key]
if 'allMeterPower.csv' in rawOut:
cleanOut['gridBallast']['totalNetworkLoad'] = rawOut.get('allMeterPower.csv')['sum(measured_real_power)']
if ('allWaterheaterLoad.csv' in rawOut) and ('allZIPloadPower.csv' in rawOut):
cleanOut['gridBallast']['availabilityMagnitude'] = [x + y for x, y in zip(rawOut.get('allWaterheaterLoad.csv')['sum(actual_load)'], rawOut.get('allZIPloadPower.csv')['sum(base_power)'])]
if 'eachZIPloadPower.csv' in rawOut:
cleanOut['gridBallast']['ZIPloadPower'] = {}
for key in rawOut['eachZIPloadPower.csv']:
if key.startswith('ZIPload'):
cleanOut['gridBallast']['ZIPloadPower'][key] = rawOut.get('eachZIPloadPower.csv')[key]
if 'allZIPloadDemand.csv' in rawOut:
cleanOut['gridBallast']['ZIPloadDemand'] = {}
for key in rawOut['allZIPloadDemand.csv']:
if key.startswith('ZIPload'):
cleanOut['gridBallast']['ZIPloadDemand'][key] = rawOut.get('allZIPloadDemand.csv')[key]
if 'allZIPloadOn.csv' in rawOut:
cleanOut['gridBallast']['ZIPloadOn'] = {}
for key in rawOut['allZIPloadOn.csv']:
if key.startswith('ZIPload'):
cleanOut['gridBallast']['ZIPloadOn'][key] = rawOut.get('allZIPloadOn.csv')[key]
# EventTime calculations
eventTime = inputDict['eventTime']
eventLength = inputDict['eventLength']
eventLength = eventLength.split(':')
eventDuration = datetime.timedelta(hours=int(eventLength[0]), minutes=int(eventLength[1]))
eventStart = datetime.datetime.strptime(eventTime, '%Y-%m-%d %H:%M')
eventEnd = eventStart + eventDuration
cleanOut['gridBallast']['eventStart'] = str(eventStart)
cleanOut['gridBallast']['eventEnd'] = str(eventEnd)
# Drop timezone from timeStamp, Convert string to date
timeStamps = [x[:19] for x in cleanOut['timeStamps']]
dateTimeStamps = [datetime.datetime.strptime(x, '%Y-%m-%d %H:%M:%S') for x in timeStamps]
eventEndIdx = dateTimeStamps.index(eventEnd)
# Recovery Time
whOn = cleanOut['gridBallast']['waterheaterOn']
whOnList = whOn.values()
whOnZip = zip(*whOnList)
whOnSum = [sum(x) for x in whOnZip]
anyOn = [x > 0 for x in whOnSum]
tRecIdx = anyOn.index(True, eventEndIdx)
tRec = dateTimeStamps[tRecIdx]
cleanOut['gridBallast']['recoveryTime'] = str(tRec)
# Waterheaters Off-Duration
offDuration = tRec - eventStart
cleanOut['gridBallast']['offDuration'] = str(offDuration)
# Reserve Magnitude Target (RMT)
availMag = cleanOut['gridBallast']['availabilityMagnitude']
totNetLoad = cleanOut['gridBallast']['totalNetworkLoad']
# loadZip = zip(availMag,totNetLoad)
# rmt = [x[0]/x[1] for x in loadZip]
rmt = (1000*sum(availMag))/sum(totNetLoad)
cleanOut['gridBallast']['rmt'] = rmt
# Reserve Magnitude Variability Tolerance (RMVT)
avgAvailMag = sum(availMag)/len(availMag)
rmvtMax = max(availMag)/avgAvailMag
rmvtMin = min(availMag)/avgAvailMag
rmvt = rmvtMax - rmvtMin
cleanOut['gridBallast']['rmvt'] = rmvt
# Availability
notAvail = availMag.count(0)/len(timeStamps)
avail = (1-notAvail)*100
cleanOut['gridBallast']['availability'] = avail
# Waterheater Temperature Drop calculations
whTemp = cleanOut['gridBallast']['waterheaterTemp']
whTempList = whTemp.values()
whTempZip = zip(*whTempList)
whTempDrops = []
LOWER_LIMIT_TEMP = 125 # Used for calculating quality of service.
for time in whTempZip:
tempDrop = sum([t < LOWER_LIMIT_TEMP for t in time])
whTempDrops.append(tempDrop)
cleanOut['gridBallast']['waterheaterTempDrops'] = whTempDrops
# ZIPload calculations for Availability and QoS
zPower = cleanOut['gridBallast']['ZIPloadPower']
zPowerList = zPower.values()
zPowerZip = zip(*zPowerList)
zPowerSum = [sum(x) for x in zPowerZip]
zDemand = cleanOut['gridBallast']['ZIPloadDemand']
zDemandList = zDemand.values()
zDemandZip = zip(*zDemandList)
zDrops = []
for time in zDemandZip:
for each in zPowerZip:
zIdx = 0
if each[zIdx] == 0:
zPowerIdx += 1
zDrop = sum([t > 0 for t in time])
zDrops.append(zDrop)
else:
zDrops.append(0)
cleanOut['gridBallast']['qualityDrops'] = [x + y for x, y in zip(whTempDrops, zDrops)]
# 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
def work(modelDir, inputDict):
feederName = inputDict["feederName1"]
inputDict["climateName"] = zipCodeToClimateName(inputDict["zipCode"])
shutil.copy(pJoin(__neoMetaModel__._omfDir, "data", "Climate", inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, "climate.tmy2"))
feederJson = json.load(open(pJoin(modelDir, feederName+'.omd')))
tree = feederJson["tree"]
# tree[feeder.getMaxKey(tree)+1] = {'object':'capacitor','control':'VOLT','phases':'ABCN','name':'CAPTEST','parent':'tm_1','capacitor_A':'0.10 MVAr','capacitor_B':'0.10 MVAr','capacitor_C':'0.10 MVAr','time_delay':'300.0','nominal_voltage':'2401.7771','voltage_set_high':'2350.0','voltage_set_low':'2340.0','switchA':'CLOSED','switchB':'CLOSED','switchC':'CLOSED','control_level':'INDIVIDUAL','phases_connected':'ABCN','dwell_time':'0.0','pt_phases':'ABCN'}
# 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)
# System check - linux doesn't support newer GridLAB-D versions
if sys.platform == 'linux2':
pass
else:
# print feeder.getMaxKey(tree)
# tree[14,20,27,28,47] empty for UCS Egan, add climate object to tree[14]
# HACK: tree[10:19] is empty
tree[11] = {'omftype':'#include', 'argument':'\"hot_water_demand.glm\"'}
tree[12] = {'omftype':'#include', 'argument':'\"lock_mode_schedule.glm\"'}
tree[13] = {'omftype':'#include', 'argument':'\"control_priority_schedule.glm\"'}
# Attach frequency player
tree[14] = {'omftype':'class player', 'argument':'{double value;}'}
tree[feeder.getMaxKey(tree)+1] = {'object':'player', 'file':'frequency.PLAYER', 'property':'value', 'name':'frequency', 'loop':0}
# Set up GridBallast Controls
totalWH = 0
totalZIP = 0
gbWH = 0
gbZIP = 0
for key in tree.keys():
# Waterheater Controller properties
if ('name' in tree[key]) and (tree[key].get('object') == 'waterheater'):
totalWH += 1
gbWH += 1
# Frequency control parameters
tree[key]['enable_freq_control'] = 'true'
tree[key]['measured_frequency'] = 'frequency.value'
tree[key]['freq_lowlimit'] = 59
tree[key]['freq_uplimit'] = 61
tree[key]['heat_mode'] = 'ELECTRIC'
# tree[key]['average_delay_time'] = 60
# Voltage control parameters
# tree[key]['enable_volt_control'] = 'true'
# tree[key]['volt_lowlimit'] = 240.4
# tree[key]['volt_uplimit'] = 241.4
# Lock Mode parameters
# tree[key]['enable_lock'] = 'temp_lock_enable'
# tree[key]['lock_STATUS'] = 'temp_lock_status'
# Controller Priority: a.lock, b.freq, c.volt, d.therm
tree[key]['controller_priority'] = 3214 #default:therm>lock>freq>volt
# tree[key]['controller_priority'] = 1423 #freq>therm>volt>lock
# tree[key]['controller_priority'] = 'control_priority'
# fix waterheater property demand to water_demand for newer GridLAB-D versions
if 'demand' in tree[key]:
# tree[key]['water_demand'] = tree[key]['demand']
tree[key]['water_demand'] = 'weekday_hotwater*1'
del tree[key]['demand']
# ZIPload Controller properties
if ('name' in tree[key]) and (tree[key].get('object') == 'ZIPload'):
totalZIP += 1
if tree[key]['name'].startswith('responsive'):
gbZIP += 1
# Frequency control parameters
tree[key]['enable_freq_control'] = 'true'
tree[key]['measured_frequency'] = 'frequency.value'
tree[key]['freq_lowlimit'] = 59
tree[key]['freq_uplimit'] = 61
# tree[key]['average_delay_time'] = 60
# Voltage control parameters
# tree[key]['enable_volt_control'] = 'true'
# tree[key]['volt_lowlimit'] = 240.4
# tree[key]['volt_uplimit'] = 241.4
# Lock Mode parameters
# tree[key]['enable_lock'] = 'temp_lock_enable'
# tree[key]['lock_STATUS'] = 'temp_lock_status'
tree[key]['controller_priority'] = 4321 #default:lock>freq>volt>therm
# tree[key]['controller_priority'] = 2431 #freq>volt>lock>therm
# tree[key]['groupid'] = 'fan'
# Attach collector for total network load
tree[feeder.getMaxKey(tree)+1] = {'object':'collector', 'group':'"class=triplex_meter"', 'property':'sum(measured_real_power)', 'interval':60, 'file':'allMeterPower.csv'}
# Attach collector for total waterheater load
tree[feeder.getMaxKey(tree)+1] = {'object':'collector', 'group':'"class=waterheater"', 'property':'sum(actual_load)', 'interval':60, 'file':'allWaterheaterLoad.csv'}
# Attach collector for total ZIPload power/load
tree[feeder.getMaxKey(tree)+1] = {'object':'collector', 'group':'"class=ZIPload"', 'property':'sum(base_power)', 'interval':60, 'file':'allZIPloadPower.csv'}
# Attach recorder for each ZIPload power/load
tree[feeder.getMaxKey(tree)+1] = {'object':'group_recorder', 'group':'"class=ZIPload"', 'property':'base_power', 'interval':60, 'file':'eachZIPloadPower.csv'}
# Attach recorder for all ZIPloads demand_rate
tree[feeder.getMaxKey(tree)+1] = {'object':'group_recorder', 'group':'"class=ZIPload"', 'property':'demand_rate', 'interval':60, 'file':'allZIPloadDemand.csv'}
# Attach recorder for waterheaters on/off
tree[feeder.getMaxKey(tree)+1] = {'object':'group_recorder', 'group':'"class=waterheater"', 'property':'is_waterheater_on', 'interval':60, 'file':'allWaterheaterOn.csv'}
# Attach recorder for waterheater tank temperatures
tree[feeder.getMaxKey(tree)+1] = {'object':'group_recorder', 'group':'"class=waterheater"', 'property':'temperature', 'interval':60, 'file':'allWaterheaterTemp.csv'}
# Attach recorders for system voltage map:
stub = {'object':'group_recorder', 'group':'"class=node"', 'interval':60}
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
# Attach recorders for system voltage map, triplex:
stub = {'object':'group_recorder', 'group':'"class=triplex_node"', 'interval':60}
for phase in ['1','2']:
copyStub = dict(stub)
copyStub['property'] = 'voltage_' + phase
copyStub['file'] = phase.lower() + 'nVoltDump.csv'
tree[feeder.getMaxKey(tree) + 1] = copyStub
# And get meters for system voltage map:
stub = {'object':'group_recorder', 'group':'"class=triplex_meter"', 'interval':60}
for phase in ['1','2']:
copyStub = dict(stub)
copyStub['property'] = 'voltage_' + phase
copyStub['file'] = phase.lower() + 'mVoltDump.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))
outData = {}
# Std Err and Std Out
outData['stderr'] = rawOut['stderr']
outData['stdout'] = rawOut['stdout']
# Time Stamps
for key in rawOut:
if '# timestamp' in rawOut[key]:
outData['timeStamps'] = rawOut[key]['# timestamp']
break
elif '# property.. timestamp' in rawOut[key]:
outData['timeStamps'] = rawOut[key]['# property.. timestamp']
else:
outData['timeStamps'] = []
# Day/Month Aggregation Setup:
stamps = outData.get('timeStamps',[])
level = inputDict.get('simLengthUnits','hours')
# Climate
for key in rawOut:
if key.startswith('Climate_') and key.endswith('.csv'):
outData['climate'] = {}
outData['climate']['Rain Fall (in/h)'] = hdmAgg(rawOut[key].get('rainfall'), sum, level)
outData['climate']['Wind Speed (m/s)'] = hdmAgg(rawOut[key].get('wind_speed'), avg, level)
outData['climate']['Temperature (F)'] = hdmAgg(rawOut[key].get('temperature'), max, level)
outData['climate']['Snow Depth (in)'] = hdmAgg(rawOut[key].get('snowdepth'), max, level)
outData['climate']['Direct Normal (W/sf)'] = hdmAgg(rawOut[key].get('solar_direct'), sum, level)
#outData['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]
outData['climate']['Global Horizontal (W/sm)']=climateWbySMList
# Voltage Band
if 'VoltageJiggle.csv' in rawOut:
outData['allMeterVoltages'] = {}
outData['allMeterVoltages']['Min'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['min(voltage_12.mag)']], min, level)
outData['allMeterVoltages']['Mean'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['mean(voltage_12.mag)']], avg, level)
outData['allMeterVoltages']['StdDev'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['std(voltage_12.mag)']], avg, level)
outData['allMeterVoltages']['Max'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['max(voltage_12.mag)']], max, level)
# Power Consumption
outData['Consumption'] = {}
# Set default value to be 0, avoiding missing value when computing Loads
outData['Consumption']['Power'] = [0] * int(inputDict["simLength"])
outData['Consumption']['Losses'] = [0] * int(inputDict["simLength"])
outData['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 outData['Consumption']:
outData['Consumption']['Power'] = oneSwingPower
else:
outData['Consumption']['Power'] = vecSum(oneSwingPower,outData['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 outData['Consumption']:
outData['Consumption']['DG'] = oneDgPower
else:
outData['Consumption']['DG'] = vecSum(oneDgPower,outData['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 outData['Consumption']:
outData['Consumption']['DG'] = oneDgPower
else:
outData['Consumption']['DG'] = vecSum(oneDgPower,outData['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 outData['Consumption']:
outData['Consumption']['Losses'] = oneLoss
else:
outData['Consumption']['Losses'] = vecSum(oneLoss,outData['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]
outData[newkey] ={}
outData[newkey]['RegTapA'] = [0] * int(inputDict["simLength"])
outData[newkey]['RegTapB'] = [0] * int(inputDict["simLength"])
outData[newkey]['RegTapC'] = [0] * int(inputDict["simLength"])
outData[newkey]['RegTapA'] = rawOut[key]['tap_A']
outData[newkey]['RegTapB'] = rawOut[key]['tap_B']
outData[newkey]['RegTapC'] = rawOut[key]['tap_C']
outData[newkey]['RegPhases'] = rawOut[key]['phases'][0]
elif key.startswith('Capacitor_') and key.endswith('.csv'):
capName=""
capName = key
newkey=capName.split(".")[0]
outData[newkey] ={}
outData[newkey]['Cap1A'] = [0] * int(inputDict["simLength"])
outData[newkey]['Cap1B'] = [0] * int(inputDict["simLength"])
outData[newkey]['Cap1C'] = [0] * int(inputDict["simLength"])
outData[newkey]['Cap1A'] = rawOut[key]['switchA']
outData[newkey]['Cap1B'] = rawOut[key]['switchB']
outData[newkey]['Cap1C'] = rawOut[key]['switchC']
outData[newkey]['CapPhases'] = rawOut[key]['phases'][0]
# Print gridBallast Outputs to allOutputData.json
outData['gridBallast'] = {}
if 'allMeterPower.csv' in rawOut:
outData['gridBallast']['totalNetworkLoad'] = [x / 1000 for x in rawOut.get('allMeterPower.csv')['sum(measured_real_power)']] #Convert W to kW
if ('allZIPloadPower.csv' in rawOut) and ('allWaterheaterLoad.csv' in rawOut):
outData['gridBallast']['availabilityMagnitude'] = [x[0] + x[1] for x in zip(rawOut.get('allWaterheaterLoad.csv')['sum(actual_load)'], rawOut.get('allZIPloadPower.csv')['sum(base_power)'])]
if 'allZIPloadDemand.csv' in rawOut:
outData['gridBallast']['ZIPloadDemand'] = {}
for key in rawOut['allZIPloadDemand.csv']:
if (key.startswith('ZIPload')) or (key.startswith('responsive')) or (key.startswith('unresponsive')):
outData['gridBallast']['ZIPloadDemand'][key] = rawOut.get('allZIPloadDemand.csv')[key]
if 'eachZIPloadPower.csv' in rawOut:
outData['gridBallast']['ZIPloadPower'] = {}
for key in rawOut['eachZIPloadPower.csv']:
if (key.startswith('ZIPload')) or (key.startswith('responsive')) or (key.startswith('unresponsive')):
outData['gridBallast']['ZIPloadPower'][key] = rawOut.get('eachZIPloadPower.csv')[key]
if 'allWaterheaterOn.csv' in rawOut:
outData['gridBallast']['waterheaterOn'] = {}
for key in rawOut['allWaterheaterOn.csv']:
if (key.startswith('waterheater')) or (key.startswith('waterHeater')):
outData['gridBallast']['waterheaterOn'][key] = rawOut.get('allWaterheaterOn.csv')[key]
if 'allWaterheaterTemp.csv' in rawOut:
outData['gridBallast']['waterheaterTemp'] = {}
for key in rawOut['allWaterheaterTemp.csv']:
if (key.startswith('waterheater')) or (key.startswith('waterHeater')):
outData['gridBallast']['waterheaterTemp'][key] = rawOut.get('allWaterheaterTemp.csv')[key]
# System check - linux doesn't support newer GridLAB-D versions
if sys.platform == 'linux2':
pass
else:
outData['gridBallast']['penetrationLevel'] = 100*(gbWH+gbZIP)/(totalWH+totalZIP)
# Frequency Player
inArray = feederJson['attachments']['frequency.PLAYER'].split('\n')
tempArray = []
for each in inArray:
x = each.split(',')
y = float(x[1])
tempArray.append(y)
outData['frequencyPlayer'] = tempArray
# EventTime calculations
eventTime = inputDict['eventTime']
eventLength = inputDict['eventLength'].split(':')
eventDuration = datetime.timedelta(hours=int(eventLength[0]), minutes=int(eventLength[1]))
eventStart = datetime.datetime.strptime(eventTime, '%Y-%m-%d %H:%M')
eventEnd = eventStart + eventDuration
outData['gridBallast']['eventStart'] = str(eventStart)
outData['gridBallast']['eventEnd'] = str(eventEnd)
outData['gridBallast']['xMin'] = str(eventStart - datetime.timedelta(minutes=30))
outData['gridBallast']['xMax'] = str(eventEnd + datetime.timedelta(minutes=30))
# Convert string to date
# HACK: remove timezones, inconsistency in matching format
timeStampsDebug = [x[:19] for x in outData['timeStamps']]
dateTimeStamps = [datetime.datetime.strptime(x, '%Y-%m-%d %H:%M:%S') for x in timeStampsDebug]
eventEndIdx = dateTimeStamps.index(eventEnd)
# Recovery Time
whOn = outData['gridBallast']['waterheaterOn']
whOnList = whOn.values()
whOnZip = zip(*whOnList)
whOnSum = [sum(x) for x in whOnZip]
anyOn = [x > 0 for x in whOnSum]
tRecIdx = anyOn.index(True, eventEndIdx)
tRec = dateTimeStamps[tRecIdx]
recoveryTime = tRec - eventEnd
outData['gridBallast']['recoveryTime'] = str(recoveryTime)
# Waterheaters Off-Duration
offDuration = tRec - eventStart
outData['gridBallast']['offDuration'] = str(offDuration)
# Reserve Magnitude (RM)
availMag = outData['gridBallast']['availabilityMagnitude']
totalNetLoad = outData['gridBallast']['totalNetworkLoad']
availPerc = [100 * x[0]/x[1] for x in zip(availMag,totalNetLoad)]
outData['gridBallast']['availabilityPercent'] = availPerc
outData['gridBallast']['rm'] = [100 - x for x in availPerc]
# Average RM during event
eventRM = [100 - x[1] for x in zip(dateTimeStamps, availPerc) if (x[0] == eventStart) or (x[0] == eventEnd)]
outData['gridBallast']['rmAvg'] = np.mean(eventRM)
# Reserve Magnitude Variability Tolerance (RMVT)
outData['gridBallast']['rmvt'] = np.std(eventRM)
# Availability
rmt = 7
available = [x[1] > rmt for x in zip(dateTimeStamps, availPerc) if (x[0] < eventStart) or (x[0] > eventEnd)]
outData['gridBallast']['availability'] = 100.0 * sum(available) / (int(inputDict['simLength']) - int(eventLength[1]) - 1)
# Waterheater Temperature Drop calculations
whTemp = outData['gridBallast']['waterheaterTemp']
whTempList = whTemp.values()
whTempZip = zip(*whTempList)
whTempDrops = []
LOWER_LIMIT_TEMP = 110 # Used for calculating quality of service. Typical hot shower temp = 105 F.
for time in whTempZip:
tempDrop = sum([t < LOWER_LIMIT_TEMP for t in time])
whTempDrops.append(tempDrop)
outData['gridBallast']['waterheaterTempDrops'] = whTempDrops
# ZIPload calculations for Availability and QoS
zPower = outData['gridBallast']['ZIPloadPower']
zPowerList = zPower.values()
zPowerZip = zip(*zPowerList)
zDemand = outData['gridBallast']['ZIPloadDemand']
zDemandList = zDemand.values()
zDemandZip = zip(*zDemandList)
zDrops = []
for x, y in zip(zPowerZip,zDemandZip):
zDrop = 0
for i in range(len(x)):
if (x[i] == 0) and (y[i] > 0):
zDrop += 1
zDrops.append(zDrop)
outData['gridBallast']['qualityDrops'] = [x + y for x, y in zip(zDrops, whTempDrops)]
# 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)
outData['genTime'] = genTime
# Aggregate up the timestamps:
if level=='days':
outData['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:10], 'days')
elif level=='months':
outData['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:7], 'months')
return outData
def runForeground(modelDir, test_mode=False):
''' Run the model in its directory. WARNING: GRIDLAB CAN TAKE HOURS TO COMPLETE. '''
with open(pJoin(modelDir, 'allInputData.json')) as f:
inputDict = json.load(f)
print("STARTING TO RUN", modelDir)
beginTime = datetime.datetime.now()
# 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 the names of the feeders from the .omd files:
feederNames = [x[0:-4] for x in os.listdir(modelDir) if x.endswith(".omd")]
for i, key in enumerate(feederNames):
inputDict['feederName' + str(i + 1)] = feederNames[i]
# Run GridLAB-D once for each feeder:
for feederName in feederNames:
try:
os.remove(pJoin(modelDir, feederName, "allOutputData.json"))
except Exception as 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"] = weather.zipCodeToClimateName(
inputDict["zipCode"])
shutil.copy(
pJoin(_omfDir, "data", "Climate",
inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, feederName, "climate.tmy2"))
try:
startTime = datetime.datetime.now()
with open(pJoin(modelDir, feederName, "feeder.omd")) as f:
feederJson = json.load(f)
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:
if test_mode == True:
raise 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)
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)
# Integrate data into allOutputData.json, if error happens, cancel it
try:
output = {}
output["failures"] = {}
numOfFeeders = 0
for root, dirs, files in os.walk(modelDir):
# dump error info into dict
if "stderr.txt" in files:
with open(pJoin(root, "stderr.txt"), "r") as stderrFile:
tempString = stderrFile.read()
if "ERROR" in tempString or "FATAL" in tempString or "Traceback" in tempString:
output["failures"]["feeder_" +
str(os.path.split(root)[-1])] = {
"stderr": tempString
}
continue
# dump simulated data into dict
if "allOutputData.json" in files:
with open(pJoin(root, "allOutputData.json"),
"r") as feederOutputData:
numOfFeeders += 1
feederOutput = json.load(feederOutputData)
# TODO: a better feeder name
output["feeder_" + str(os.path.split(root)[-1])] = {}
output["feeder_" +
str(os.path.split(root)[-1]
)]["Consumption"] = feederOutput["Consumption"]
output["feeder_" + str(os.path.split(root)[-1])][
"allMeterVoltages"] = feederOutput["allMeterVoltages"]
output["feeder_" + str(os.path.split(
root)[-1])]["stderr"] = feederOutput["stderr"]
output["feeder_" + str(os.path.split(
root)[-1])]["stdout"] = feederOutput["stdout"]
# output[root] = {feederOutput["Consumption"], feederOutput["allMeterVoltages"], feederOutput["stdout"], feederOutput["stderr"]}
output["numOfFeeders"] = numOfFeeders
output["timeStamps"] = feederOutput.get("timeStamps", [])
output["climate"] = feederOutput.get("climate", [])
# Add feederNames to output so allInputData feederName changes don't cause output rendering to disappear.
for key, feederName in inputDict.items():
if 'feederName' in key:
output[key] = feederName
with open(pJoin(modelDir, "allOutputData.json"), "w") as outFile:
json.dump(output, outFile, indent=4)
try:
os.remove(pJoin(modelDir, "PPID.txt"))
except:
pass
# Send email to user on model success.
emailStatus = inputDict.get('emailStatus', 0)
if (emailStatus == "on"):
print("\n EMAIL ALERT ON")
email = session['user_id']
try:
with open("data/User/" + email + ".json") as f:
user = json.load(f)
modelPath, modelName = pSplit(modelDir)
message = "The model " + "<i>" + str(
modelName
) + "</i>" + " has successfully completed running. It ran for a total of " + str(
inputDict["runTime"]) + " seconds from " + str(
beginTime) + ", to " + str(finishTime) + "."
return web.send_link(email, message, user)
except Exception as e:
print("ERROR: Failed sending model status email to user: "******", with exception: \n", e)
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)
# Send email to user on model failure.
email = 'NoEmail'
try:
email = session['user_id']
with open("data/User/" + email + ".json") as f:
user = json.load(f)
modelPath, modelName = pSplit(modelDir)
message = "The model " + "<i>" + str(
modelName
) + "</i>" + " has failed to complete running. It ran for a total of " + str(
inputDict["runTime"]) + " seconds from " + str(
beginTime) + ", to " + str(finishTime) + "."
return web.send_link(email, message, user)
except Exception as e:
print("Failed sending model status email to user: "******", with exception: \n", e)
def run(modelDir, inputDict):
''' Run the model in its directory. '''
try:
# Set up GLM with correct time and recorders:
omd = json.load(open(pJoin(modelDir, 'feeder.omd')))
tree = omd.get('tree', {})
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, 120, 'hours', '2011-01-01')
# Run GridLAB-D
startTime = dt.datetime.now()
rawOut = gridlabd.runInFilesystem(tree,
attachments=omd.get(
'attachments', {}),
workDir=modelDir)
# Clean the output.
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)'] = rawOut[key].get(
'rainfall')
cleanOut['climate']['Wind Speed (m/s)'] = rawOut[key].get(
'wind_speed')
cleanOut['climate']['Temperature (F)'] = rawOut[key].get(
'temperature')
cleanOut['climate']['Snow Depth (in)'] = rawOut[key].get(
'snowdepth')
cleanOut['climate']['Direct Normal (W/sf)'] = rawOut[key].get(
'solar_direct')
climateWbySFList = rawOut[key].get('solar_global')
#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'] = [
float(i / 2)
for i in rawOut['VoltageJiggle.csv']['min(voltage_12.mag)']
]
cleanOut['allMeterVoltages']['Mean'] = [
float(i / 2)
for i in rawOut['VoltageJiggle.csv']['mean(voltage_12.mag)']
]
cleanOut['allMeterVoltages']['StdDev'] = [
float(i / 2)
for i in rawOut['VoltageJiggle.csv']['std(voltage_12.mag)']
]
cleanOut['allMeterVoltages']['Max'] = [
float(i / 2)
for i in rawOut['VoltageJiggle.csv']['max(voltage_12.mag)']
]
# Dump the results.
endTime = dt.datetime.now()
inputDict["runTime"] = str(
dt.timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir, "allInputData.json"), "w") as inFile:
json.dump(inputDict, inFile, indent=4)
with open(pJoin(modelDir, "allOutputData.json"), "w") as outFile:
json.dump(cleanOut, outFile, indent=4)
except:
# 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)
