def run(modelDir, inputDict):
try:
''' Run the model in its directory. '''
# Check whether model exist or not
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inputDict["created"] = str(dt.now())
# MAYBEFIX: remove this data dump. Check showModel in web.py and renderTemplate()
with open(pJoin(modelDir, "allInputData.json"),"w") as inputFile:
json.dump(inputDict, inputFile, indent = 4)
# Copy spcific climate data into model directory
inputDict["climateName"], latforpvwatts = zipCodeToClimateName(inputDict["zipCode"])
shutil.copy(pJoin(__metaModel__._omfDir, "data", "Climate", inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, "climate.tmy2"))
# Ready to run
startTime = dt.now()
# Set up SAM data structures.
ssc = nrelsam2013.SSCAPI()
dat = ssc.ssc_data_create()
# Required user inputs.
ssc.ssc_data_set_string(dat, "file_name", modelDir + "/climate.tmy2")
ssc.ssc_data_set_number(dat, "system_size", float(inputDict["SystemSize"]))
# SAM options where we take defaults.
ssc.ssc_data_set_number(dat, "derate", 0.97)
ssc.ssc_data_set_number(dat, "track_mode", 0)
ssc.ssc_data_set_number(dat, "azimuth", 180)
ssc.ssc_data_set_number(dat, "tilt_eq_lat", 1)
# Run PV system simulation.
mod = ssc.ssc_module_create("pvwattsv1")
ssc.ssc_module_exec(mod, dat)
# Set the timezone to be UTC, it won't affect calculation and display, relative offset handled in pvWatts.html
startDateTime = "2013-01-01 00:00:00 UTC"
# Timestamp output.
outData = {}
outData["timeStamps"] = [dt.strftime(
dt.strptime(startDateTime[0:19],"%Y-%m-%d %H:%M:%S") +
td(**{"hours":x}),"%Y-%m-%d %H:%M:%S") + " UTC" for x in range(int(8760))]
# HACK: makes it easier to calculate some things later.
outData["pythonTimeStamps"] = [dt(2012,1,1,0) + x*td(hours=1) for x in range(8760)]
# Geodata output.
outData["city"] = ssc.ssc_data_get_string(dat, "city")
outData["state"] = ssc.ssc_data_get_string(dat, "state")
outData["lat"] = ssc.ssc_data_get_number(dat, "lat")
outData["lon"] = ssc.ssc_data_get_number(dat, "lon")
outData["elev"] = ssc.ssc_data_get_number(dat, "elev")
# Weather output.
outData["climate"] = {}
outData["climate"]["Global Horizontal Radiation (W/m^2)"] = ssc.ssc_data_get_array(dat, "gh")
outData["climate"]["Plane of Array Irradiance (W/m^2)"] = ssc.ssc_data_get_array(dat, "poa")
outData["climate"]["Ambient Temperature (F)"] = ssc.ssc_data_get_array(dat, "tamb")
outData["climate"]["Cell Temperature (F)"] = ssc.ssc_data_get_array(dat, "tcell")
outData["climate"]["Wind Speed (m/s)"] = ssc.ssc_data_get_array(dat, "wspd")
# Power generation.
outData["powerOutputAc"] = ssc.ssc_data_get_array(dat, "ac")
# TODO: INSERT TJ CODE BELOW
tjCode(inputDict, outData)
del outData["pythonTimeStamps"]
# TODO: INSERT TJ CODE ABOVE
# Stdout/stderr.
outData["stdout"] = "Success"
outData["stderr"] = ""
# Write the output.
with open(pJoin(modelDir,"allOutputData.json"),"w") as outFile:
json.dump(outData, outFile, indent=4)
# Update the runTime in the input file.
endTime = dt.now()
inputDict["runTime"] = str(td(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir,"allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, 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)
''' Run the model in its directory. '''
# Delete output file every run if it exists
try:
os.remove(pJoin(modelDir,"allOutputData.json"))
except Exception, e:
pass
# Check whether model exist or not
try:
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inputDict["created"] = str(datetime.datetime.now())
# MAYBEFIX: remove this data dump. Check showModel in web.py and renderTemplate()
with open(pJoin(modelDir, "allInputData.json"),"w") as inputFile:
json.dump(inputDict, inputFile, indent = 4)
# Copy spcific climate data into model directory
inputDict["climateName"], latforpvwatts = zipCodeToClimateName(inputDict["zipCode"])
shutil.copy(pJoin(__metaModel__._omfDir, "data", "Climate", inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, "climate.tmy2"))
# Ready to run
startTime = datetime.datetime.now()
# Set up SAM data structures.
ssc = nrelsam2013.SSCAPI()
dat = ssc.ssc_data_create()
# Required user inputs.
ssc.ssc_data_set_string(dat, "file_name", modelDir + "/climate.tmy2")
ssc.ssc_data_set_number(dat, "system_size", float(inputDict["systemSize"]))
ssc.ssc_data_set_number(dat, "derate", 0.01 * float(inputDict["nonInverterEfficiency"]))
ssc.ssc_data_set_number(dat, "track_mode", float(inputDict["trackingMode"]))
ssc.ssc_data_set_number(dat, "azimuth", float(inputDict["azimuth"]))
# Advanced inputs with defaults.
if (inputDict.get("tilt",0) == "-"):
def runForeground(modelDir, inputDict):
''' Run the model in its directory. WARNING: GRIDLAB CAN TAKE HOURS TO COMPLETE. '''
# Check whether model exist or not
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inputDict["created"] = str(datetime.datetime.now())
print "STARTING TO RUN", modelDir
beginTime = datetime.datetime.now()
feederList = []
# Get prepare of data and clean workspace if re-run, If re-run remove all the data in the subfolders
for dirs in os.listdir(modelDir):
if os.path.isdir(pJoin(modelDir, dirs)):
shutil.rmtree(pJoin(modelDir, dirs))
# Get each feeder, prepare data in separate folders, and run there.
for key in sorted(inputDict, key=inputDict.get):
if key.startswith("feederName"):
feederName = inputDict[key]
feederList.append(feederName)
try:
os.remove(pJoin(modelDir, feederName, "allOutputData.json"))
except Exception, e:
pass
if not os.path.isdir(pJoin(modelDir, feederName)):
os.makedirs(pJoin(modelDir, feederName)) # create subfolders for feeders
shutil.copy(pJoin(modelDir, feederName + ".omd"),
pJoin(modelDir, feederName, "feeder.omd"))
inputDict["climateName"], latforpvwatts = zipCodeToClimateName(inputDict["zipCode"])
shutil.copy(pJoin(__metaModel__._omfDir, "data", "Climate", inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, feederName, "climate.tmy2"))
try:
startTime = datetime.datetime.now()
feederJson = json.load(open(pJoin(modelDir, feederName, "feeder.omd")))
tree = feederJson["tree"]
# Set up GLM with correct time and recorders:
feeder.attachRecorders(tree, "Regulator", "object", "regulator")
feeder.attachRecorders(tree, "Capacitor", "object", "capacitor")
feeder.attachRecorders(tree, "Inverter", "object", "inverter")
feeder.attachRecorders(tree, "Windmill", "object", "windturb_dg")
feeder.attachRecorders(tree, "CollectorVoltage", None, None)
feeder.attachRecorders(tree, "Climate", "object", "climate")
feeder.attachRecorders(tree, "OverheadLosses", None, None)
feeder.attachRecorders(tree, "UndergroundLosses", None, None)
feeder.attachRecorders(tree, "TriplexLosses", None, None)
feeder.attachRecorders(tree, "TransformerLosses", None, None)
feeder.groupSwingKids(tree)
feeder.adjustTime(tree=tree, simLength=float(inputDict["simLength"]),
simLengthUnits=inputDict["simLengthUnits"], simStartDate=inputDict["simStartDate"])
# RUN GRIDLABD IN FILESYSTEM (EXPENSIVE!)
rawOut = gridlabd.runInFilesystem(tree, attachments=feederJson["attachments"],
keepFiles=True, workDir=pJoin(modelDir, feederName))
cleanOut = {}
# Std Err and Std Out
cleanOut['stderr'] = rawOut['stderr']
cleanOut['stdout'] = rawOut['stdout']
# Time Stamps
for key in rawOut:
if '# timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# timestamp']
break
elif '# property.. timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# property.. timestamp']
else:
cleanOut['timeStamps'] = []
# Day/Month Aggregation Setup:
stamps = cleanOut.get('timeStamps',[])
level = inputDict.get('simLengthUnits','hours')
# Climate
for key in rawOut:
if key.startswith('Climate_') and key.endswith('.csv'):
cleanOut['climate'] = {}
cleanOut['climate']['Rain Fall (in/h)'] = hdmAgg(rawOut[key].get('rainfall'), sum, level)
cleanOut['climate']['Wind Speed (m/s)'] = hdmAgg(rawOut[key].get('wind_speed'), avg, level)
cleanOut['climate']['Temperature (F)'] = hdmAgg(rawOut[key].get('temperature'), max, level)
cleanOut['climate']['Snow Depth (in)'] = hdmAgg(rawOut[key].get('snowdepth'), max, level)
cleanOut['climate']['Direct Insolation (W/m^2)'] = hdmAgg(rawOut[key].get('solar_direct'), sum, level)
# Voltage Band
if 'VoltageJiggle.csv' in rawOut:
cleanOut['allMeterVoltages'] = {}
cleanOut['allMeterVoltages']['Min'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['min(voltage_12.mag)']], min, level)
cleanOut['allMeterVoltages']['Mean'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['mean(voltage_12.mag)']], avg, level)
cleanOut['allMeterVoltages']['StdDev'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['std(voltage_12.mag)']], avg, level)
cleanOut['allMeterVoltages']['Max'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['max(voltage_12.mag)']], max, level)
cleanOut['allMeterVoltages']['stdDevPos'] = [(x+y/2) for x,y in zip(cleanOut['allMeterVoltages']['Mean'], cleanOut['allMeterVoltages']['StdDev'])]
cleanOut['allMeterVoltages']['stdDevNeg'] = [(x-y/2) for x,y in zip(cleanOut['allMeterVoltages']['Mean'], cleanOut['allMeterVoltages']['StdDev'])]
# Total # of meters
count = 0
with open(pJoin(modelDir, feederName, "feeder.omd")) as f:
for line in f:
if "\"objectType\": \"triplex_meter\"" in line:
count+=1
print "count=", count
cleanOut['allMeterVoltages']['triplexMeterCount'] = float(count)
# Power Consumption
cleanOut['Consumption'] = {}
# Set default value to be 0, avoiding missing value when computing Loads
cleanOut['Consumption']['Power'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['Losses'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['DG'] = [0] * int(inputDict["simLength"])
for key in rawOut:
if key.startswith('SwingKids_') and key.endswith('.csv'):
oneSwingPower = hdmAgg(vecPyth(rawOut[key]['sum(power_in.real)'],rawOut[key]['sum(power_in.imag)']), avg, level)
if 'Power' not in cleanOut['Consumption']:
cleanOut['Consumption']['Power'] = oneSwingPower
else:
cleanOut['Consumption']['Power'] = vecSum(oneSwingPower,cleanOut['Consumption']['Power'])
elif key.startswith('Inverter_') and key.endswith('.csv'):
realA = rawOut[key]['power_A.real']
realB = rawOut[key]['power_B.real']
realC = rawOut[key]['power_C.real']
imagA = rawOut[key]['power_A.imag']
imagB = rawOut[key]['power_B.imag']
imagC = rawOut[key]['power_C.imag']
oneDgPower = hdmAgg(vecSum(vecPyth(realA,imagA),vecPyth(realB,imagB),vecPyth(realC,imagC)), avg, level)
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(oneDgPower,cleanOut['Consumption']['DG'])
elif key.startswith('Windmill_') and key.endswith('.csv'):
vrA = rawOut[key]['voltage_A.real']
vrB = rawOut[key]['voltage_B.real']
vrC = rawOut[key]['voltage_C.real']
viA = rawOut[key]['voltage_A.imag']
viB = rawOut[key]['voltage_B.imag']
viC = rawOut[key]['voltage_C.imag']
crB = rawOut[key]['current_B.real']
crA = rawOut[key]['current_A.real']
crC = rawOut[key]['current_C.real']
ciA = rawOut[key]['current_A.imag']
ciB = rawOut[key]['current_B.imag']
ciC = rawOut[key]['current_C.imag']
powerA = vecProd(vecPyth(vrA,viA),vecPyth(crA,ciA))
powerB = vecProd(vecPyth(vrB,viB),vecPyth(crB,ciB))
powerC = vecProd(vecPyth(vrC,viC),vecPyth(crC,ciC))
# HACK: multiply by negative one because turbine power sign is opposite all other DG:
oneDgPower = [-1.0 * x for x in hdmAgg(vecSum(powerA,powerB,powerC), avg, level)]
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(oneDgPower,cleanOut['Consumption']['DG'])
elif key in ['OverheadLosses.csv', 'UndergroundLosses.csv', 'TriplexLosses.csv', 'TransformerLosses.csv']:
realA = rawOut[key]['sum(power_losses_A.real)']
imagA = rawOut[key]['sum(power_losses_A.imag)']
realB = rawOut[key]['sum(power_losses_B.real)']
imagB = rawOut[key]['sum(power_losses_B.imag)']
realC = rawOut[key]['sum(power_losses_C.real)']
imagC = rawOut[key]['sum(power_losses_C.imag)']
oneLoss = hdmAgg(vecSum(vecPyth(realA,imagA),vecPyth(realB,imagB),vecPyth(realC,imagC)), avg, level)
if 'Losses' not in cleanOut['Consumption']:
cleanOut['Consumption']['Losses'] = oneLoss
else:
cleanOut['Consumption']['Losses'] = vecSum(oneLoss,cleanOut['Consumption']['Losses'])
# Aggregate up the timestamps:
if level=='days':
cleanOut['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:10], 'days')
elif level=='months':
cleanOut['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:7], 'months')
# Write the output.
with open(pJoin(modelDir, feederName, "allOutputData.json"),"w") as outFile:
json.dump(cleanOut, outFile, indent=4)
# Update the runTime in the input file.
endTime = datetime.datetime.now()
inputDict["runTime"] = str(datetime.timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir, feederName, "allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent=4)
# Clean up the PID file.
os.remove(pJoin(modelDir, feederName,"PID.txt"))
print "DONE RUNNING GRIDLABMULTI", modelDir, feederName
except Exception as e:
print "MODEL CRASHED GRIDLABMULTI", e, modelDir, feederName
cancel(pJoin(modelDir, feederName))
with open(pJoin(modelDir, feederName, "stderr.txt"), "a+") as stderrFile:
traceback.print_exc(file = stderrFile)
def runForeground(modelDir, inputDict):
''' Run the model in its directory. WARNING: GRIDLAB CAN TAKE HOURS TO COMPLETE. '''
# Check whether model exist or not
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inputDict["created"] = str(datetime.datetime.now())
print "STARTING TO RUN", modelDir
beginTime = datetime.datetime.now()
feederList = []
# Get prepare of data and clean workspace if re-run, If re-run remove all the data in the subfolders
for dirs in os.listdir(modelDir):
if os.path.isdir(pJoin(modelDir, dirs)):
shutil.rmtree(pJoin(modelDir, dirs))
# Get each feeder, prepare data in separate folders, and run there.
for key in sorted(inputDict, key=inputDict.get):
if key.startswith("feederName"):
feederDir, feederName = inputDict[key].split("___")
feederList.append(feederName)
try:
os.remove(pJoin(modelDir, feederName, "allOutputData.json"))
except Exception, e:
pass
if not os.path.isdir(pJoin(modelDir, feederName)):
os.makedirs(pJoin(modelDir, feederName)) # create subfolders for feeders
shutil.copy(pJoin(__metaModel__._omfDir, "data", "Feeder", feederDir, feederName + ".json"),
pJoin(modelDir, feederName, "feeder.json"))
inputDict["climateName"], latforpvwatts = zipCodeToClimateName(inputDict["zipCode"])
shutil.copy(pJoin(__metaModel__._omfDir, "data", "Climate", inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, feederName, "climate.tmy2"))
try:
startTime = datetime.datetime.now()
feederJson = json.load(open(pJoin(modelDir, feederName, "feeder.json")))
tree = feederJson["tree"]
# Set up GLM with correct time and recorders:
feeder.attachRecorders(tree, "Regulator", "object", "regulator")
feeder.attachRecorders(tree, "Capacitor", "object", "capacitor")
feeder.attachRecorders(tree, "Inverter", "object", "inverter")
feeder.attachRecorders(tree, "Windmill", "object", "windturb_dg")
feeder.attachRecorders(tree, "CollectorVoltage", None, None)
feeder.attachRecorders(tree, "Climate", "object", "climate")
feeder.attachRecorders(tree, "OverheadLosses", None, None)
feeder.attachRecorders(tree, "UndergroundLosses", None, None)
feeder.attachRecorders(tree, "TriplexLosses", None, None)
feeder.attachRecorders(tree, "TransformerLosses", None, None)
feeder.groupSwingKids(tree)
feeder.adjustTime(tree=tree, simLength=float(inputDict["simLength"]),
simLengthUnits=inputDict["simLengthUnits"], simStartDate=inputDict["simStartDate"])
# RUN GRIDLABD IN FILESYSTEM (EXPENSIVE!)
rawOut = gridlabd.runInFilesystem(tree, attachments=feederJson["attachments"],
keepFiles=True, workDir=pJoin(modelDir, feederName))
cleanOut = {}
# Std Err and Std Out
cleanOut['stderr'] = rawOut['stderr']
cleanOut['stdout'] = rawOut['stdout']
# Time Stamps
for key in rawOut:
if '# timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# timestamp']
break
elif '# property.. timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# property.. timestamp']
else:
cleanOut['timeStamps'] = []
# Day/Month Aggregation Setup:
stamps = cleanOut.get('timeStamps',[])
level = inputDict.get('simLengthUnits','hours')
# Climate
for key in rawOut:
if key.startswith('Climate_') and key.endswith('.csv'):
cleanOut['climate'] = {}
cleanOut['climate']['Rain Fall (in/h)'] = hdmAgg(rawOut[key].get('rainfall'), sum, level)
cleanOut['climate']['Wind Speed (m/s)'] = hdmAgg(rawOut[key].get('wind_speed'), avg, level)
cleanOut['climate']['Temperature (F)'] = hdmAgg(rawOut[key].get('temperature'), max, level)
cleanOut['climate']['Snow Depth (in)'] = hdmAgg(rawOut[key].get('snowdepth'), max, level)
cleanOut['climate']['Direct Insolation (W/m^2)'] = hdmAgg(rawOut[key].get('solar_direct'), sum, level)
# Voltage Band
if 'VoltageJiggle.csv' in rawOut:
cleanOut['allMeterVoltages'] = {}
cleanOut['allMeterVoltages']['Min'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['min(voltage_12.mag)']], min, level)
cleanOut['allMeterVoltages']['Mean'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['mean(voltage_12.mag)']], avg, level)
cleanOut['allMeterVoltages']['StdDev'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['std(voltage_12.mag)']], avg, level)
cleanOut['allMeterVoltages']['Max'] = hdmAgg([(i / 2) for i in rawOut['VoltageJiggle.csv']['max(voltage_12.mag)']], max, level)
cleanOut['allMeterVoltages']['stdDevPos'] = [(x+y/2) for x,y in zip(cleanOut['allMeterVoltages']['Mean'], cleanOut['allMeterVoltages']['StdDev'])]
cleanOut['allMeterVoltages']['stdDevNeg'] = [(x-y/2) for x,y in zip(cleanOut['allMeterVoltages']['Mean'], cleanOut['allMeterVoltages']['StdDev'])]
# Total # of meters
count = 0
with open(pJoin(modelDir, feederName, "feeder.json")) as f:
for line in f:
if "\"objectType\": \"triplex_meter\"" in line:
count+=1
print "count=", count
cleanOut['allMeterVoltages']['triplexMeterCount'] = float(count)
# Power Consumption
cleanOut['Consumption'] = {}
# Set default value to be 0, avoiding missing value when computing Loads
cleanOut['Consumption']['Power'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['Losses'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['DG'] = [0] * int(inputDict["simLength"])
for key in rawOut:
if key.startswith('SwingKids_') and key.endswith('.csv'):
oneSwingPower = hdmAgg(vecPyth(rawOut[key]['sum(power_in.real)'],rawOut[key]['sum(power_in.imag)']), avg, level)
if 'Power' not in cleanOut['Consumption']:
cleanOut['Consumption']['Power'] = oneSwingPower
else:
cleanOut['Consumption']['Power'] = vecSum(oneSwingPower,cleanOut['Consumption']['Power'])
elif key.startswith('Inverter_') and key.endswith('.csv'):
realA = rawOut[key]['power_A.real']
realB = rawOut[key]['power_B.real']
realC = rawOut[key]['power_C.real']
imagA = rawOut[key]['power_A.imag']
imagB = rawOut[key]['power_B.imag']
imagC = rawOut[key]['power_C.imag']
oneDgPower = hdmAgg(vecSum(vecPyth(realA,imagA),vecPyth(realB,imagB),vecPyth(realC,imagC)), avg, level)
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(oneDgPower,cleanOut['Consumption']['DG'])
elif key.startswith('Windmill_') and key.endswith('.csv'):
vrA = rawOut[key]['voltage_A.real']
vrB = rawOut[key]['voltage_B.real']
vrC = rawOut[key]['voltage_C.real']
viA = rawOut[key]['voltage_A.imag']
viB = rawOut[key]['voltage_B.imag']
viC = rawOut[key]['voltage_C.imag']
crB = rawOut[key]['current_B.real']
crA = rawOut[key]['current_A.real']
crC = rawOut[key]['current_C.real']
ciA = rawOut[key]['current_A.imag']
ciB = rawOut[key]['current_B.imag']
ciC = rawOut[key]['current_C.imag']
powerA = vecProd(vecPyth(vrA,viA),vecPyth(crA,ciA))
powerB = vecProd(vecPyth(vrB,viB),vecPyth(crB,ciB))
powerC = vecProd(vecPyth(vrC,viC),vecPyth(crC,ciC))
# HACK: multiply by negative one because turbine power sign is opposite all other DG:
oneDgPower = [-1.0 * x for x in hdmAgg(vecSum(powerA,powerB,powerC), avg, level)]
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(oneDgPower,cleanOut['Consumption']['DG'])
elif key in ['OverheadLosses.csv', 'UndergroundLosses.csv', 'TriplexLosses.csv', 'TransformerLosses.csv']:
realA = rawOut[key]['sum(power_losses_A.real)']
imagA = rawOut[key]['sum(power_losses_A.imag)']
realB = rawOut[key]['sum(power_losses_B.real)']
imagB = rawOut[key]['sum(power_losses_B.imag)']
realC = rawOut[key]['sum(power_losses_C.real)']
imagC = rawOut[key]['sum(power_losses_C.imag)']
oneLoss = hdmAgg(vecSum(vecPyth(realA,imagA),vecPyth(realB,imagB),vecPyth(realC,imagC)), avg, level)
if 'Losses' not in cleanOut['Consumption']:
cleanOut['Consumption']['Losses'] = oneLoss
else:
cleanOut['Consumption']['Losses'] = vecSum(oneLoss,cleanOut['Consumption']['Losses'])
# Aggregate up the timestamps:
if level=='days':
cleanOut['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:10], 'days')
elif level=='months':
cleanOut['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:7], 'months')
# Write the output.
with open(pJoin(modelDir, feederName, "allOutputData.json"),"w") as outFile:
json.dump(cleanOut, outFile, indent=4)
# Update the runTime in the input file.
endTime = datetime.datetime.now()
inputDict["runTime"] = str(datetime.timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir, feederName, "allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent=4)
# Clean up the PID file.
os.remove(pJoin(modelDir, feederName,"PID.txt"))
print "DONE RUNNING GRIDLABMULTI", modelDir, feederName
except Exception as e:
print "MODEL CRASHED GRIDLABMULTI", e, modelDir, feederName
cancel(pJoin(modelDir, feederName))
with open(pJoin(modelDir, feederName, "stderr.txt"), "a+") as stderrFile:
traceback.print_exc(file = stderrFile)
def run(modelDir, inputDict):
try:
''' Run the model in its directory. '''
# Check whether model exist or not
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inputDict["created"] = str(dt.datetime.now())
# MAYBEFIX: remove this data dump. Check showModel in web.py and renderTemplate()
with open(pJoin(modelDir, "allInputData.json"),"w") as inputFile:
json.dump(inputDict, inputFile, indent = 4)
# Copy spcific climate data into model directory
inputDict["climateName"], latforpvwatts = zipCodeToClimateName(inputDict["zipCode"])
shutil.copy(pJoin(__metaModel__._omfDir, "data", "Climate", inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, "climate.tmy2"))
# Ready to run
startTime = dt.datetime.now()
# Set up SAM data structures.
ssc = nrelsam2013.SSCAPI()
dat = ssc.ssc_data_create()
# Required user inputs.
ssc.ssc_data_set_string(dat, "file_name", modelDir + "/climate.tmy2")
# TODO: FIX THIS!!!! IT SHOULD BE AVGSYS*PEN*RESCUSTOMERS
ssc.ssc_data_set_number(dat, "system_size", float(inputDict["systemSize"]))
# SAM options where we take defaults.
ssc.ssc_data_set_number(dat, "derate", 0.97)
ssc.ssc_data_set_number(dat, "track_mode", 0)
ssc.ssc_data_set_number(dat, "azimuth", 180)
ssc.ssc_data_set_number(dat, "tilt_eq_lat", 1)
# Run PV system simulation.
mod = ssc.ssc_module_create("pvwattsv1")
ssc.ssc_module_exec(mod, dat)
# Set the timezone to be UTC, it won't affect calculation and display, relative offset handled in pvWatts.html
startDateTime = "2013-01-01 00:00:00 UTC"
# Timestamp output.
outData = {}
outData["timeStamps"] = [dt.datetime.strftime(
dt.datetime.strptime(startDateTime[0:19],"%Y-%m-%d %H:%M:%S") +
dt.timedelta(**{"hours":x}),"%Y-%m-%d %H:%M:%S") + " UTC" for x in range(int(8760))]
# Geodata output.
outData["city"] = ssc.ssc_data_get_string(dat, "city")
outData["state"] = ssc.ssc_data_get_string(dat, "state")
outData["lat"] = ssc.ssc_data_get_number(dat, "lat")
outData["lon"] = ssc.ssc_data_get_number(dat, "lon")
outData["elev"] = ssc.ssc_data_get_number(dat, "elev")
# Weather output.
outData["climate"] = {}
outData["climate"]["Global Horizontal Radiation (W/m^2)"] = ssc.ssc_data_get_array(dat, "gh")
outData["climate"]["Plane of Array Irradiance (W/m^2)"] = ssc.ssc_data_get_array(dat, "poa")
outData["climate"]["Ambient Temperature (F)"] = ssc.ssc_data_get_array(dat, "tamb")
outData["climate"]["Cell Temperature (F)"] = ssc.ssc_data_get_array(dat, "tcell")
outData["climate"]["Wind Speed (m/s)"] = ssc.ssc_data_get_array(dat, "wspd")
# Power generation.
outData["powerOutputAc"] = ssc.ssc_data_get_array(dat, "ac")
# Monthly aggregation outputs.
months = {"Jan":0,"Feb":1,"Mar":2,"Apr":3,"May":4,"Jun":5,"Jul":6,"Aug":7,"Sep":8,"Oct":9,"Nov":10,"Dec":11}
totMonNum = lambda x:sum([z for (y,z) in zip(outData["timeStamps"], outData["powerOutputAc"]) if y.startswith(startDateTime[0:4] + "-{0:02d}".format(x+1))])
outData["monthlyGeneration"] = [[a, roundSig(totMonNum(b),2)] for (a,b) in sorted(months.items(), key=lambda x:x[1])]
monthlyNoConsumerServedSales = []
monthlyKWhSold = []
monthlyRevenue = []
totalKWhSold = []
totalRevenue = []
for key in inputDict:
# MAYBEFIX: data in list may not be ordered by month.
if key.endswith("Sale"):
monthlyNoConsumerServedSales.append([key[:3].title(),float(inputDict.get(key, 0))])
elif key.endswith("KWh"):# the order of calculation matters
monthlyKWhSold.append([key[:3].title(),float(inputDict.get(key, 0))])
elif key.endswith("Rev"):
monthlyRevenue.append([key[:3].title(),float(inputDict.get(key, 0))])
elif key.endswith("KWhT"):
totalKWhSold.append([key[:3].title(),float(inputDict.get(key, 0))])
elif key.endswith("RevT"):
totalRevenue.append([key[:3].title(),float(inputDict.get(key, 0))])
outData["monthlyNoConsumerServedSales"] = sorted(monthlyNoConsumerServedSales, key=lambda x:months[x[0]])
outData["monthlyKWhSold"] = sorted(monthlyKWhSold, key=lambda x:months[x[0]])
outData["monthlyRevenue"] = sorted(monthlyRevenue, key=lambda x:months[x[0]])
outData["totalKWhSold"] = sorted(totalKWhSold, key=lambda x:months[x[0]])
outData["totalRevenue"] = sorted(totalRevenue, key=lambda x:months[x[0]])
outData["totalGeneration"] = [[sorted(months.items(), key=lambda x:x[1])[i][0], outData["monthlyGeneration"][i][1]*outData["monthlyNoConsumerServedSales"][i][1]*(float(inputDict.get("resPenetration", 5))/100/1000)] for i in range(12)]
outData["totalSolarSold"] = [[sorted(months.items(), key=lambda x:x[1])[i][0], outData["totalKWhSold"][i][1] - outData["totalGeneration"][i][1]] for i in range(12)]
##################
# TODO: add retailCost to the calculation.
##################
## Flow Diagram Calculations, and order of calculation matters
# BAU case
outData["BAU"] = {}
# E23 = E11
outData["BAU"]["totalKWhPurchased"] = float(inputDict.get("totalKWhPurchased", 1))
# E24 = SUM(E19:P19)
outData["BAU"]["totalKWhSales"] = sum([x[1] for x in totalKWhSold])
# E25 = E23-E24
outData["BAU"]["losses"] = float(inputDict.get("totalKWhPurchased", 0)) - sum([totalKWhSold[i][1] for i in range(12)])
# E26 = E25/E23
outData["BAU"]["effectiveLossRate"] = outData["BAU"]["losses"] / outData["BAU"]["totalKWhPurchased"]
# E27 = 0
outData["BAU"]["annualSolarGen"] = 0
# E28 = SUM(E17:P17)
outData["BAU"]["resNonSolarKWhSold"] = sum([monthlyKWhSold[i][1] for i in range(12)])
# E29 = 0
outData["BAU"]["solarResDemand"] = 0
# E30 = 0
outData["BAU"]["solarResSold"] = 0
# E31 = E24-E28
outData["BAU"]["nonResKWhSold"] = outData["BAU"]["totalKWhSales"] - outData["BAU"]["resNonSolarKWhSold"]
# E32 = 0
outData["BAU"]["costSolarGen"] = 0
# E33 = SUM(E20:P20)-SUM(E18:P18)+E10
outData["BAU"]["nonResRev"] = sum([totalRevenue[i][1] for i in range(12)]) - sum([monthlyRevenue[i][1] for i in range(12)]) + float(inputDict.get("otherElecRevenue"))
# E34 = (SUM(E18:P18)-SUM(E16:P16)*E6)/SUM(E17:P17)
outData["BAU"]["effectiveResRate"] = (sum ([monthlyRevenue[i][1] for i in range(12)]) - sum([monthlyNoConsumerServedSales[i][1] for i in range(12)])*float(inputDict.get("customServiceCharge", 0)))/sum([monthlyKWhSold[i][1] for i in range(12)])
# E35 = E34*E28+SUM(E16:P16)*E6
outData["BAU"]["resNonSolarRev"] = outData["BAU"]["effectiveResRate"] * outData["BAU"]["resNonSolarKWhSold"] + sum([monthlyNoConsumerServedSales[i][1] for i in range(12)])*float(inputDict.get("customServiceCharge", 0))
# E36 = E30*E34
outData["BAU"]["solarResRev"] = 0
# E37 = SUM(E48:E54)+SUM(E56:E62)-SUM(E65:E71), update after Form 7 model
outData["BAU"]["nonPowerCosts"] = 0
# E38 = E23-E25-E28-E30-E31
outData["BAU"]["energyAllBal"] = 0
# E39 = E36+E33+E35-E47-E72-E37
outData["BAU"]["dollarAllBal"] = 0
# E40 = 0
outData["BAU"]["avgMonthlyBillSolarCus"] = 0
# E41 = E35/SUM(E16:P16)
avgCustomerCount = (sum([monthlyNoConsumerServedSales[i][1] for i in range(12)])/12)
outData["BAU"]["avgMonthlyBillNonSolarCus"] = outData["BAU"]["resNonSolarRev"] / sum([monthlyNoConsumerServedSales[i][1] for i in range(12)])
# E42 = E63/E24, update after Form 7 model
outData["BAU"]["costofService"] = 0
# Solar case
outData["Solar"] = {}
# F27 = SUM(E15:P15)
outData["Solar"]["annualSolarGen"] = sum([outData["totalGeneration"][i][1] for i in range(12)])
# F24 = E24-F27
outData["Solar"]["totalKWhSales"] = sum([totalKWhSold[i][1] for i in range(12)]) - outData["Solar"]["annualSolarGen"]
# F23 =F24/(1-E26)
outData["Solar"]["totalKWhPurchased"] = outData["Solar"]["totalKWhSales"]/ (1-outData["BAU"]["effectiveLossRate"])
outData["totalsolarmonthly"] = [[sorted(months.items(), key=lambda x:x[1])[i][0], outData["totalSolarSold"][i][1] / (1-outData["BAU"]["effectiveLossRate"])] for i in range(12)]
# F25 = F23-F24
outData["Solar"]["losses"] = (outData["Solar"]["totalKWhPurchased"] - outData["Solar"]["totalKWhSales"])
# F26 = E26
outData["Solar"]["effectiveLossRate"] = outData["BAU"]["effectiveLossRate"]
# F28 = (1-E5)*E28
outData["Solar"]["resNonSolarKWhSold"] = (1-float(inputDict.get("resPenetration", 0))/100)*outData["BAU"]["resNonSolarKWhSold"]
# F29 = E5*E28
outData["Solar"]["solarResDemand"] = float(inputDict.get("resPenetration", 0))/100*outData["BAU"]["resNonSolarKWhSold"]
# F30 = F29-F27
outData["Solar"]["solarResSold"] = outData["Solar"]["solarResDemand"] - outData["Solar"]["annualSolarGen"]
# F31 = E31
outData["Solar"]["nonResKWhSold"] = outData["BAU"]["nonResKWhSold"]
# F32 = E9*F27
outData["Solar"]["costSolarGen"] = float(inputDict.get("solarLCoE", 0.07))*outData["Solar"]["annualSolarGen"]
# F33 = E33
outData["Solar"]["nonResRev"] = outData["BAU"]["nonResRev"]
# F34 = E34
outData["Solar"]["effectiveResRate"] = outData["BAU"]["effectiveResRate"]
# F35 = E35*(1-E5)
outData["Solar"]["resNonSolarRev"] = outData["BAU"]["resNonSolarRev"] * (1 - float(inputDict.get("resPenetration", 0.05))/100)
# F30*E34 = Solar revenue from selling at residential rate
solarSoldRateRev = outData["Solar"]["solarResSold"] * outData["Solar"]["effectiveResRate"]
# (E6+E7)*SUM(E16:P16)*E5 = Solar revenue from charges
solarChargesRev = (float(inputDict.get("customServiceCharge", 0))+float(inputDict.get("solarServiceCharge", 0)))*sum([monthlyNoConsumerServedSales[i][1] for i in range(12)])*float(inputDict.get("resPenetration", 0.05))/100
# F36 = F30*E34+(E6+E7)*SUM(E16:P16)*E5 = solarSoldRate + solarChargesRev
outData["Solar"]["solarResRev"] = solarSoldRateRev + solarChargesRev
# F37 = SUM(E48:E54)+SUM(E56:E62)-SUM(E65:E71) = E37, update after Form 7 model
outData["Solar"]["nonPowerCosts"] = 0
# F38 = F23-F25-F28-F30-E31
outData["Solar"]["energyAllBal"] = 0
# F39 = F36+E33+F35-F47-F72-E37
outData["Solar"]["dollarAllBal"] = 0
if (float(inputDict.get("resPenetration", 0.05)) > 0):
# F41 = (F35)/(SUM(E16:P16)*(1-E5))
outData["Solar"]["avgMonthlyBillNonSolarCus"] = outData["Solar"]["resNonSolarRev"] / (sum([monthlyNoConsumerServedSales[i][1] for i in range(12)])* (1 - float(inputDict.get("resPenetration", 0.05))/100))
# F42 = F30*E34/(SUM(E16:P16)*E5)+E6+E7
outData["Solar"]["avgMonthlyBillSolarCus"] = outData["Solar"]["solarResSold"] * outData["BAU"]["effectiveResRate"] / (sum([monthlyNoConsumerServedSales[i][1] for i in range(12)]) * float(inputDict.get("resPenetration", 0.05))/100) + float(inputDict.get("customServiceCharge", 0))+float(inputDict.get("solarServiceCharge", 0))
# F43 = (F27/(SUM(E16:P16)*E5))*E9
outData["Solar"]["avgMonthlyBillSolarSolarCus"] = (outData["Solar"]["annualSolarGen"] / (sum([monthlyNoConsumerServedSales[i][1] for i in range(12)]) * float(inputDict.get("resPenetration", 0.05))/100)) * float(inputDict.get("solarLCoE", 0.07))
else:
outData["Solar"]["avgMonthlyBillNonSolarCus"] = 0
outData["Solar"]["avgMonthlyBillSolarCus"] = 0
outData["Solar"]["avgMonthlyBillSolarSolarCus"] = 0
# Net Average Monthly Bill
avgMonthlyBillSolarNet = outData["Solar"]["avgMonthlyBillSolarCus"] + outData["Solar"]["avgMonthlyBillSolarSolarCus"]
outData["Solar"]["avgMonthlyBillSolarCus"] = avgMonthlyBillSolarNet
# F45 = F63/F24, update after Form 7 model
outData["Solar"]["costofService"] = 0
## Form 7 Model
# E46
outData["Solar"]["powerProExpense"] = outData["BAU"]["powerProExpense"] = float(inputDict.get("powerProExpense", 0))
# E47 != F47
outData["BAU"]["costPurchasedPower"] = float(inputDict.get("costPurchasedPower", 0))
# E48
outData["Solar"]["transExpense"] = outData["BAU"]["transExpense"] = float(inputDict.get("transExpense", 0))
# E49
outData["Solar"]["distriExpenseO"] = outData["BAU"]["distriExpenseO"] = float(inputDict.get("distriExpenseO", 0))
# E50
outData["Solar"]["distriExpenseM"] = outData["BAU"]["distriExpenseM"] = float(inputDict.get("distriExpenseM", 0))
# E51
outData["Solar"]["customerAccountExpense"] = outData["BAU"]["customerAccountExpense"] = float(inputDict.get("customerAccountExpense", 0))
# E52
outData["Solar"]["customerServiceExpense"] = outData["BAU"]["customerServiceExpense"] = float(inputDict.get("customerServiceExpense", 0))
# E53
outData["Solar"]["salesExpense"] = outData["BAU"]["salesExpense"] = float(inputDict.get("salesExpense", 0))
# E54
outData["Solar"]["adminGeneralExpense"] = outData["BAU"]["adminGeneralExpense"] = float(inputDict.get("adminGeneralExpense", 0))
# E56
outData["Solar"]["depreAmortiExpense"] = outData["BAU"]["depreAmortiExpense"] = float(inputDict.get("depreAmortiExpense", 0))
# E57
outData["Solar"]["taxExpensePG"] = outData["BAU"]["taxExpensePG"] = float(inputDict.get("taxExpensePG", 0))
# E58
outData["Solar"]["taxExpense"] = outData["BAU"]["taxExpense"] = float(inputDict.get("taxExpense", 0))
# E59
outData["Solar"]["interestLongTerm"] = outData["BAU"]["interestLongTerm"] = float(inputDict.get("interestLongTerm", 0))
# E60
outData["Solar"]["interestConstruction"] = outData["BAU"]["interestConstruction"] = float(inputDict.get("interestConstruction", 0))
# E61
outData["Solar"]["interestExpense"] = outData["BAU"]["interestExpense"] = float(inputDict.get("interestExpense", 0))
# E62
outData["Solar"]["otherDeductions"] = outData["BAU"]["otherDeductions"] = float(inputDict.get("otherDeductions", 0))
# E65
outData["Solar"]["nonOpMarginInterest"] = outData["BAU"]["nonOpMarginInterest"] = float(inputDict.get("nonOpMarginInterest", 0))
# E66
outData["Solar"]["fundsUsedConstruc"] = outData["BAU"]["fundsUsedConstruc"] = float(inputDict.get("fundsUsedConstruc", 0))
# E67
outData["Solar"]["incomeEquityInvest"] = outData["BAU"]["incomeEquityInvest"] = float(inputDict.get("incomeEquityInvest", 0))
# E68
outData["Solar"]["nonOpMarginOther"] = outData["BAU"]["nonOpMarginOther"] = float(inputDict.get("nonOpMarginOther", 0))
# E69
outData["Solar"]["genTransCapCredits"] = outData["BAU"]["genTransCapCredits"] = float(inputDict.get("genTransCapCredits", 0))
# E70
outData["Solar"]["otherCapCreditsPatroDivident"] = outData["BAU"]["otherCapCreditsPatroDivident"] = float(inputDict.get("otherCapCreditsPatroDivident", 0))
# E71
outData["Solar"]["extraItems"] = outData["BAU"]["extraItems"] = float(inputDict.get("extraItems", 0))
# Calculation
# E45 = SUM(E20:P20)+E10
outData["BAU"]["operRevPatroCap"] = sum([totalRevenue[i][1] for i in range(12)])+float(inputDict.get("otherElecRevenue", 0))
# E55 = SUM(E46:E54)
outData["BAU"]["totalOMExpense"] = float(inputDict.get("powerProExpense")) \
+ float(inputDict.get("costPurchasedPower")) \
+ float(inputDict.get("transExpense")) \
+ float(inputDict.get("distriExpenseO")) \
+ float(inputDict.get("distriExpenseM")) \
+ float(inputDict.get("customerAccountExpense")) \
+ float(inputDict.get("customerServiceExpense")) \
+ float(inputDict.get("salesExpense")) \
+ float(inputDict.get("adminGeneralExpense"))
# E63 = SUM(E55:E62)
outData["BAU"]["totalCostElecService"] = outData["BAU"]["totalOMExpense"] \
+ float(inputDict.get("depreAmortiExpense"))\
+ float(inputDict.get("taxExpensePG"))\
+ float(inputDict.get("taxExpense"))\
+ float(inputDict.get("interestLongTerm"))\
+ float(inputDict.get("interestExpense"))\
+ float(inputDict.get("interestConstruction"))\
+ outData["BAU"]["otherDeductions"]
# E64 = E45-E63
outData["BAU"]["patCapOperMargins"] = outData["BAU"]["operRevPatroCap"] - outData["BAU"]["totalCostElecService"]
# E72 = SUM(E64:E71)
outData["BAU"]["patCapital"] = outData["BAU"]["patCapOperMargins"]\
+ float(inputDict.get("nonOpMarginInterest"))\
+ float(inputDict.get("fundsUsedConstruc"))\
+ float(inputDict.get("incomeEquityInvest"))\
+ float(inputDict.get("nonOpMarginOther"))\
+ float(inputDict.get("genTransCapCredits"))\
+ float(inputDict.get("otherCapCreditsPatroDivident"))\
+ float(inputDict.get("extraItems"))
# F48 = E48-F27*E34+SUM(E16:P16)*E5*E7
outData["Solar"]["operRevPatroCap"] = outData["BAU"]["operRevPatroCap"] - outData["BAU"]["effectiveResRate"]*outData["Solar"]["annualSolarGen"] + sum([monthlyNoConsumerServedSales[i][1] for i in range(12)])*float(inputDict.get("resPenetration", 0.05))/100*float(inputDict.get("solarServiceCharge", 0))
# F47 = (F23)*E8
inputDict["costofPower"] = float(inputDict.get("costPurchasedPower", 0)) / float(inputDict.get("totalKWhPurchased", 0))
outData["Solar"]["costPurchasedPower"] = outData["Solar"]["totalKWhPurchased"] * float(inputDict.get("costofPower", 0))
inputDict["costofPower"] = round(inputDict["costofPower"],3)
# F55 = SUM(F46:F54)
outData["Solar"]["totalOMExpense"] = outData["Solar"]["powerProExpense"]\
+ outData["Solar"]["costPurchasedPower"]\
+ outData["Solar"]["transExpense"]\
+ outData["Solar"]["distriExpenseO"]\
+ outData["Solar"]["distriExpenseM"]\
+ outData["Solar"]["customerAccountExpense"]\
+ outData["Solar"]["customerServiceExpense"]\
+ outData["Solar"]["salesExpense"]\
+ outData["Solar"]["adminGeneralExpense"]
# F63 = E63
outData["Solar"]["totalCostElecService"] = outData["Solar"]["totalOMExpense"]\
+ outData["Solar"]["depreAmortiExpense"]\
+ outData["Solar"]["taxExpensePG"]\
+ outData["Solar"]["taxExpense"]\
+ outData["Solar"]["interestLongTerm"]\
+ outData["Solar"]["interestConstruction"]\
+ outData["Solar"]["interestExpense"]\
+ outData["Solar"]["otherDeductions"]
# F64 = F45 - F63
outData["Solar"]["patCapOperMargins"] = outData["Solar"]["operRevPatroCap"] - outData["Solar"]["totalCostElecService"]
# F72 = SUM(F64:F71)
outData["Solar"]["patCapital"] = outData["Solar"]["patCapOperMargins"]\
+ outData["Solar"]["nonOpMarginInterest"]\
+ outData["Solar"]["fundsUsedConstruc"]\
+ outData["Solar"]["incomeEquityInvest"]\
+ outData["Solar"]["nonOpMarginOther"]\
+ outData["Solar"]["genTransCapCredits"]\
+ outData["Solar"]["otherCapCreditsPatroDivident"]\
+ outData["Solar"]["extraItems"]
# E37 = SUM(E48:E54)+SUM(E56:E62)-SUM(E65:E71), update after Form 7 model
outData["BAU"]["nonPowerCosts"] = outData["BAU"]["transExpense"] \
+ outData["BAU"]["distriExpenseO"] \
+ outData["BAU"]["distriExpenseM"] \
+ outData["BAU"]["customerAccountExpense"] \
+ outData["BAU"]["customerServiceExpense"] \
+ outData["BAU"]["salesExpense"] \
+ outData["BAU"]["adminGeneralExpense"] \
+ outData["BAU"]["depreAmortiExpense"] \
+ outData["BAU"]["taxExpensePG"] \
+ outData["BAU"]["taxExpense"] \
+ outData["BAU"]["interestLongTerm"] \
+ outData["BAU"]["interestConstruction"] \
+ outData["BAU"]["interestExpense"] \
+ outData["BAU"]["otherDeductions"] \
- (outData["BAU"]["nonOpMarginInterest"] \
+ outData["BAU"]["fundsUsedConstruc"] \
+ outData["BAU"]["incomeEquityInvest"] \
+ outData["BAU"]["nonOpMarginOther"] \
+ outData["BAU"]["genTransCapCredits"] \
+ outData["BAU"]["otherCapCreditsPatroDivident"] \
+ outData["BAU"]["extraItems"])
# E42 = E63/E24, update after Form 7 model
outData["BAU"]["costofService"] = outData["BAU"]["totalCostElecService"] / outData["BAU"]["totalKWhSales"]
# F37 = SUM(E48:E54)+SUM(E56:E62)-SUM(E65:E71) = E37, update after Form 7 model
outData["Solar"]["nonPowerCosts"] = outData["BAU"]["nonPowerCosts"]
# F42 = F63/F24, update after Form 7 model
outData["Solar"]["costofService"] = outData["Solar"]["totalCostElecService"] / outData["Solar"]["totalKWhSales"]
# Stdout/stderr.
outData["stdout"] = "Success"
outData["stderr"] = ""
# Write the output.
with open(pJoin(modelDir,"allOutputData.json"),"w") as outFile:
json.dump(outData, outFile, indent=4)
# Update the runTime in the input file.
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)
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)
def heavyProcessing(modelDir, inputDict):
''' Run the model in its directory. WARNING: GRIDLAB CAN TAKE HOURS TO COMPLETE. '''
print "STARTING TO RUN", modelDir
beginTime = datetime.datetime.now()
# Get feeder name and data in.
try: os.mkdir(pJoin(modelDir,'gldContainer'))
except: pass
try:
feederName = inputDict["feederName1"]
inputDict["climateName"], latforpvwatts = zipCodeToClimateName(inputDict["zipCode"])
shutil.copy(pJoin(__metaModel__._omfDir, "data", "Climate", inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, "gldContainer", "climate.tmy2"))
startTime = datetime.datetime.now()
feederJson = json.load(open(pJoin(modelDir, feederName+'.omd')))
tree = feederJson["tree"]
# Set up GLM with correct time and recorders:
feeder.attachRecorders(tree, "Regulator", "object", "regulator")
feeder.attachRecorders(tree, "Capacitor", "object", "capacitor")
feeder.attachRecorders(tree, "Inverter", "object", "inverter")
feeder.attachRecorders(tree, "Windmill", "object", "windturb_dg")
feeder.attachRecorders(tree, "CollectorVoltage", None, None)
feeder.attachRecorders(tree, "Climate", "object", "climate")
feeder.attachRecorders(tree, "OverheadLosses", None, None)
feeder.attachRecorders(tree, "UndergroundLosses", None, None)
feeder.attachRecorders(tree, "TriplexLosses", None, None)
feeder.attachRecorders(tree, "TransformerLosses", None, None)
feeder.groupSwingKids(tree)
# Attach recorders for system voltage map:
stub = {'object':'group_recorder', 'group':'"class=node"', 'property':'voltage_A', 'interval':3600, 'file':'aVoltDump.csv'}
for phase in ['A','B','C']:
copyStub = dict(stub)
copyStub['property'] = 'voltage_' + phase
copyStub['file'] = phase.lower() + 'VoltDump.csv'
tree[feeder.getMaxKey(tree) + 1] = copyStub
feeder.adjustTime(tree=tree, simLength=float(inputDict["simLength"]),
simLengthUnits=inputDict["simLengthUnits"], simStartDate=inputDict["simStartDate"])
# RUN GRIDLABD IN FILESYSTEM (EXPENSIVE!)
rawOut = gridlabd.runInFilesystem(tree, attachments=feederJson["attachments"],
keepFiles=True, workDir=pJoin(modelDir,'gldContainer'))
cleanOut = {}
# Std Err and Std Out
cleanOut['stderr'] = rawOut['stderr']
cleanOut['stdout'] = rawOut['stdout']
# Time Stamps
for key in rawOut:
if '# timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# timestamp']
break
elif '# property.. timestamp' in rawOut[key]:
cleanOut['timeStamps'] = rawOut[key]['# property.. timestamp']
else:
cleanOut['timeStamps'] = []
# Day/Month Aggregation Setup:
stamps = cleanOut.get('timeStamps',[])
level = inputDict.get('simLengthUnits','hours')
# Climate
for key in rawOut:
if key.startswith('Climate_') and key.endswith('.csv'):
cleanOut['climate'] = {}
cleanOut['climate']['Rain Fall (in/h)'] = hdmAgg(rawOut[key].get('rainfall'), sum, level)
cleanOut['climate']['Wind Speed (m/s)'] = hdmAgg(rawOut[key].get('wind_speed'), avg, level)
cleanOut['climate']['Temperature (F)'] = hdmAgg(rawOut[key].get('temperature'), max, level)
cleanOut['climate']['Snow Depth (in)'] = hdmAgg(rawOut[key].get('snowdepth'), max, level)
cleanOut['climate']['Direct Normal (W/sf)'] = hdmAgg(rawOut[key].get('solar_direct'), sum, level)
#cleanOut['climate']['Global Horizontal (W/sf)'] = hdmAgg(rawOut[key].get('solar_global'), sum, level)
climateWbySFList= hdmAgg(rawOut[key].get('solar_global'), sum, level)
#converting W/sf to W/sm
climateWbySMList= [x*10.76392 for x in climateWbySFList]
cleanOut['climate']['Global Horizontal (W/sm)']=climateWbySMList
# Voltage Band
if 'VoltageJiggle.csv' in rawOut:
cleanOut['allMeterVoltages'] = {}
cleanOut['allMeterVoltages']['Min'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['min(voltage_12.mag)']], min, level)
cleanOut['allMeterVoltages']['Mean'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['mean(voltage_12.mag)']], avg, level)
cleanOut['allMeterVoltages']['StdDev'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['std(voltage_12.mag)']], avg, level)
cleanOut['allMeterVoltages']['Max'] = hdmAgg([float(i / 2) for i in rawOut['VoltageJiggle.csv']['max(voltage_12.mag)']], max, level)
# Power Consumption
cleanOut['Consumption'] = {}
# Set default value to be 0, avoiding missing value when computing Loads
cleanOut['Consumption']['Power'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['Losses'] = [0] * int(inputDict["simLength"])
cleanOut['Consumption']['DG'] = [0] * int(inputDict["simLength"])
for key in rawOut:
if key.startswith('SwingKids_') and key.endswith('.csv'):
oneSwingPower = hdmAgg(vecPyth(rawOut[key]['sum(power_in.real)'],rawOut[key]['sum(power_in.imag)']), avg, level)
if 'Power' not in cleanOut['Consumption']:
cleanOut['Consumption']['Power'] = oneSwingPower
else:
cleanOut['Consumption']['Power'] = vecSum(oneSwingPower,cleanOut['Consumption']['Power'])
elif key.startswith('Inverter_') and key.endswith('.csv'):
realA = rawOut[key]['power_A.real']
realB = rawOut[key]['power_B.real']
realC = rawOut[key]['power_C.real']
imagA = rawOut[key]['power_A.imag']
imagB = rawOut[key]['power_B.imag']
imagC = rawOut[key]['power_C.imag']
oneDgPower = hdmAgg(vecSum(vecPyth(realA,imagA),vecPyth(realB,imagB),vecPyth(realC,imagC)), avg, level)
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(oneDgPower,cleanOut['Consumption']['DG'])
elif key.startswith('Windmill_') and key.endswith('.csv'):
vrA = rawOut[key]['voltage_A.real']
vrB = rawOut[key]['voltage_B.real']
vrC = rawOut[key]['voltage_C.real']
viA = rawOut[key]['voltage_A.imag']
viB = rawOut[key]['voltage_B.imag']
viC = rawOut[key]['voltage_C.imag']
crB = rawOut[key]['current_B.real']
crA = rawOut[key]['current_A.real']
crC = rawOut[key]['current_C.real']
ciA = rawOut[key]['current_A.imag']
ciB = rawOut[key]['current_B.imag']
ciC = rawOut[key]['current_C.imag']
powerA = vecProd(vecPyth(vrA,viA),vecPyth(crA,ciA))
powerB = vecProd(vecPyth(vrB,viB),vecPyth(crB,ciB))
powerC = vecProd(vecPyth(vrC,viC),vecPyth(crC,ciC))
oneDgPower = hdmAgg(vecSum(powerA,powerB,powerC), avg, level)
if 'DG' not in cleanOut['Consumption']:
cleanOut['Consumption']['DG'] = oneDgPower
else:
cleanOut['Consumption']['DG'] = vecSum(oneDgPower,cleanOut['Consumption']['DG'])
elif key in ['OverheadLosses.csv', 'UndergroundLosses.csv', 'TriplexLosses.csv', 'TransformerLosses.csv']:
realA = rawOut[key]['sum(power_losses_A.real)']
imagA = rawOut[key]['sum(power_losses_A.imag)']
realB = rawOut[key]['sum(power_losses_B.real)']
imagB = rawOut[key]['sum(power_losses_B.imag)']
realC = rawOut[key]['sum(power_losses_C.real)']
imagC = rawOut[key]['sum(power_losses_C.imag)']
oneLoss = hdmAgg(vecSum(vecPyth(realA,imagA),vecPyth(realB,imagB),vecPyth(realC,imagC)), avg, level)
if 'Losses' not in cleanOut['Consumption']:
cleanOut['Consumption']['Losses'] = oneLoss
else:
cleanOut['Consumption']['Losses'] = vecSum(oneLoss,cleanOut['Consumption']['Losses'])
elif key.startswith('Regulator_') and key.endswith('.csv'):
#split function to strip off .csv from filename and user rest of the file name as key. for example- Regulator_VR10.csv -> key would be Regulator_VR10
regName=""
regName = key
newkey=regName.split(".")[0]
cleanOut[newkey] ={}
cleanOut[newkey]['RegTapA'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['RegTapB'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['RegTapC'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['RegTapA'] = rawOut[key]['tap_A']
cleanOut[newkey]['RegTapB'] = rawOut[key]['tap_B']
cleanOut[newkey]['RegTapC'] = rawOut[key]['tap_C']
cleanOut[newkey]['RegPhases'] = rawOut[key]['phases'][0]
elif key.startswith('Capacitor_') and key.endswith('.csv'):
capName=""
capName = key
newkey=capName.split(".")[0]
cleanOut[newkey] ={}
cleanOut[newkey]['Cap1A'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['Cap1B'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['Cap1C'] = [0] * int(inputDict["simLength"])
cleanOut[newkey]['Cap1A'] = rawOut[key]['switchA']
cleanOut[newkey]['Cap1B'] = rawOut[key]['switchB']
cleanOut[newkey]['Cap1C'] = rawOut[key]['switchC']
cleanOut[newkey]['CapPhases'] = rawOut[key]['phases'][0]
# What percentage of our keys have lat lon data?
latKeys = [tree[key]['latitude'] for key in tree if 'latitude' in tree[key]]
latPerc = 1.0*len(latKeys)/len(tree)
if latPerc < 0.25: doNeato = True
else: doNeato = False
# Generate the frames for the system voltage map time traveling chart.
genTime = generateVoltChart(tree, rawOut, modelDir, neatoLayout=doNeato)
cleanOut['genTime'] = genTime
# Aggregate up the timestamps:
if level=='days':
cleanOut['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:10], 'days')
elif level=='months':
cleanOut['timeStamps'] = aggSeries(stamps, stamps, lambda x:x[0][0:7], 'months')
# Write the output.
with open(pJoin(modelDir, "allOutputData.json"),"w") as outFile:
json.dump(cleanOut, outFile, indent=4)
# Update the runTime in the input file.
endTime = datetime.datetime.now()
inputDict["runTime"] = str(datetime.timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir, "allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent=4)
# Clean up the PID file.
os.remove(pJoin(modelDir, "gldContainer", "PID.txt"))
print "DONE RUNNING", modelDir
except Exception as e:
# If input range wasn't valid delete output, write error to disk.
cancel(modelDir)
thisErr = traceback.format_exc()
print 'ERROR IN MODEL', modelDir, thisErr
inputDict['stderr'] = thisErr
with open(os.path.join(modelDir,'stderr.txt'),'w') as errorFile:
errorFile.write(thisErr)
with open(pJoin(modelDir,"allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent=4)
finishTime = datetime.datetime.now()
inputDict["runTime"] = str(datetime.timedelta(seconds = int((finishTime - beginTime).total_seconds())))
with open(pJoin(modelDir, "allInputData.json"),"w") as inFile:
json.dump(inputDict, inFile, indent = 4)
try:
os.remove(pJoin(modelDir,"PPID.txt"))
except:
pass
def run(modelDir, inputDict):
try:
''' Run the model in its directory. '''
# Check whether model exist or not
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inputDict["created"] = str(dt.now())
# MAYBEFIX: remove this data dump. Check showModel in web.py and renderTemplate()
with open(pJoin(modelDir, "allInputData.json"), "w") as inputFile:
json.dump(inputDict, inputFile, indent=4)
# Copy spcific climate data into model directory
inputDict["climateName"], latforpvwatts = zipCodeToClimateName(
inputDict["zipCode"])
shutil.copy(
pJoin(__metaModel__._omfDir, "data", "Climate",
inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, "climate.tmy2"))
# Ready to run
startTime = dt.now()
# Set up SAM data structures.
ssc = nrelsam2013.SSCAPI()
dat = ssc.ssc_data_create()
# Required user inputs.
ssc.ssc_data_set_string(dat, "file_name", modelDir + "/climate.tmy2")
ssc.ssc_data_set_number(dat, "system_size",
float(inputDict["SystemSize"]))
# SAM options where we take defaults.
ssc.ssc_data_set_number(dat, "derate", 0.97)
ssc.ssc_data_set_number(dat, "track_mode", 0)
ssc.ssc_data_set_number(dat, "azimuth", 180)
ssc.ssc_data_set_number(dat, "tilt_eq_lat", 1)
# Run PV system simulation.
mod = ssc.ssc_module_create("pvwattsv1")
ssc.ssc_module_exec(mod, dat)
# Set the timezone to be UTC, it won't affect calculation and display, relative offset handled in pvWatts.html
startDateTime = "2013-01-01 00:00:00 UTC"
# Timestamp output.
outData = {}
outData["timeStamps"] = [
dt.strftime(
dt.strptime(startDateTime[0:19], "%Y-%m-%d %H:%M:%S") +
td(**{"hours": x}), "%Y-%m-%d %H:%M:%S") + " UTC"
for x in range(int(8760))
]
# HACK: makes it easier to calculate some things later.
outData["pythonTimeStamps"] = [
dt(2012, 1, 1, 0) + x * td(hours=1) for x in range(8760)
]
# Geodata output.
outData["city"] = ssc.ssc_data_get_string(dat, "city")
outData["state"] = ssc.ssc_data_get_string(dat, "state")
outData["lat"] = ssc.ssc_data_get_number(dat, "lat")
outData["lon"] = ssc.ssc_data_get_number(dat, "lon")
outData["elev"] = ssc.ssc_data_get_number(dat, "elev")
# Weather output.
outData["climate"] = {}
outData["climate"][
"Global Horizontal Radiation (W/m^2)"] = ssc.ssc_data_get_array(
dat, "gh")
outData["climate"][
"Plane of Array Irradiance (W/m^2)"] = ssc.ssc_data_get_array(
dat, "poa")
outData["climate"]["Ambient Temperature (F)"] = ssc.ssc_data_get_array(
dat, "tamb")
outData["climate"]["Cell Temperature (F)"] = ssc.ssc_data_get_array(
dat, "tcell")
outData["climate"]["Wind Speed (m/s)"] = ssc.ssc_data_get_array(
dat, "wspd")
# Power generation.
outData["powerOutputAc"] = ssc.ssc_data_get_array(dat, "ac")
# TODO: INSERT TJ CODE BELOW
tjCode(inputDict, outData)
del outData["pythonTimeStamps"]
# TODO: INSERT TJ CODE ABOVE
# Stdout/stderr.
outData["stdout"] = "Success"
outData["stderr"] = ""
# Write the output.
with open(pJoin(modelDir, "allOutputData.json"), "w") as outFile:
json.dump(outData, outFile, indent=4)
# Update the runTime in the input file.
endTime = dt.now()
inputDict["runTime"] = str(
td(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir, "allInputData.json"), "w") as inFile:
json.dump(inputDict, inFile, 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)
def run(modelDir, inputDict):
try:
''' Run the model in its directory. '''
# Check whether model exist or not
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inputDict["created"] = str(dt.datetime.now())
# MAYBEFIX: remove this data dump. Check showModel in web.py and renderTemplate()
with open(pJoin(modelDir, "allInputData.json"), "w") as inputFile:
json.dump(inputDict, inputFile, indent=4)
# Copy spcific climate data into model directory
inputDict["climateName"], latforpvwatts = zipCodeToClimateName(
inputDict["zipCode"])
shutil.copy(
pJoin(__metaModel__._omfDir, "data", "Climate",
inputDict["climateName"] + ".tmy2"),
pJoin(modelDir, "climate.tmy2"))
# Ready to run
startTime = dt.datetime.now()
# Set up SAM data structures.
ssc = nrelsam2013.SSCAPI()
dat = ssc.ssc_data_create()
# Required user inputs.
ssc.ssc_data_set_string(dat, "file_name", modelDir + "/climate.tmy2")
# TODO: FIX THIS!!!! IT SHOULD BE AVGSYS*PEN*RESCUSTOMERS
ssc.ssc_data_set_number(dat, "system_size",
float(inputDict["systemSize"]))
# SAM options where we take defaults.
ssc.ssc_data_set_number(dat, "derate", 0.97)
ssc.ssc_data_set_number(dat, "track_mode", 0)
ssc.ssc_data_set_number(dat, "azimuth", 180)
ssc.ssc_data_set_number(dat, "tilt_eq_lat", 1)
# Run PV system simulation.
mod = ssc.ssc_module_create("pvwattsv1")
ssc.ssc_module_exec(mod, dat)
# Set the timezone to be UTC, it won't affect calculation and display, relative offset handled in pvWatts.html
startDateTime = "2013-01-01 00:00:00 UTC"
# Timestamp output.
outData = {}
outData["timeStamps"] = [
dt.datetime.strftime(
dt.datetime.strptime(startDateTime[0:19], "%Y-%m-%d %H:%M:%S")
+ dt.timedelta(**{"hours": x}), "%Y-%m-%d %H:%M:%S") + " UTC"
for x in range(int(8760))
]
# Geodata output.
outData["city"] = ssc.ssc_data_get_string(dat, "city")
outData["state"] = ssc.ssc_data_get_string(dat, "state")
outData["lat"] = ssc.ssc_data_get_number(dat, "lat")
outData["lon"] = ssc.ssc_data_get_number(dat, "lon")
outData["elev"] = ssc.ssc_data_get_number(dat, "elev")
# Weather output.
outData["climate"] = {}
outData["climate"][
"Global Horizontal Radiation (W/m^2)"] = ssc.ssc_data_get_array(
dat, "gh")
outData["climate"][
"Plane of Array Irradiance (W/m^2)"] = ssc.ssc_data_get_array(
dat, "poa")
outData["climate"]["Ambient Temperature (F)"] = ssc.ssc_data_get_array(
dat, "tamb")
outData["climate"]["Cell Temperature (F)"] = ssc.ssc_data_get_array(
dat, "tcell")
outData["climate"]["Wind Speed (m/s)"] = ssc.ssc_data_get_array(
dat, "wspd")
# Power generation.
outData["powerOutputAc"] = ssc.ssc_data_get_array(dat, "ac")
# Monthly aggregation outputs.
months = {
"Jan": 0,
"Feb": 1,
"Mar": 2,
"Apr": 3,
"May": 4,
"Jun": 5,
"Jul": 6,
"Aug": 7,
"Sep": 8,
"Oct": 9,
"Nov": 10,
"Dec": 11
}
totMonNum = lambda x: sum([
z
for (y, z) in zip(outData["timeStamps"], outData["powerOutputAc"])
if y.startswith(startDateTime[0:4] + "-{0:02d}".format(x + 1))
])
outData["monthlyGeneration"] = [[a, roundSig(
totMonNum(b),
2)] for (a, b) in sorted(months.items(), key=lambda x: x[1])]
monthlyNoConsumerServedSales = []
monthlyKWhSold = []
monthlyRevenue = []
totalKWhSold = []
totalRevenue = []
for key in inputDict:
# MAYBEFIX: data in list may not be ordered by month.
if key.endswith("Sale"):
monthlyNoConsumerServedSales.append(
[key[:3].title(),
float(inputDict.get(key, 0))])
elif key.endswith("KWh"): # the order of calculation matters
monthlyKWhSold.append(
[key[:3].title(),
float(inputDict.get(key, 0))])
elif key.endswith("Rev"):
monthlyRevenue.append(
[key[:3].title(),
float(inputDict.get(key, 0))])
elif key.endswith("KWhT"):
totalKWhSold.append(
[key[:3].title(),
float(inputDict.get(key, 0))])
elif key.endswith("RevT"):
totalRevenue.append(
[key[:3].title(),
float(inputDict.get(key, 0))])
outData["monthlyNoConsumerServedSales"] = sorted(
monthlyNoConsumerServedSales, key=lambda x: months[x[0]])
outData["monthlyKWhSold"] = sorted(monthlyKWhSold,
key=lambda x: months[x[0]])
outData["monthlyRevenue"] = sorted(monthlyRevenue,
key=lambda x: months[x[0]])
outData["totalKWhSold"] = sorted(totalKWhSold,
key=lambda x: months[x[0]])
outData["totalRevenue"] = sorted(totalRevenue,
key=lambda x: months[x[0]])
outData["totalGeneration"] = [[
sorted(months.items(), key=lambda x: x[1])[i][0],
outData["monthlyGeneration"][i][1] *
outData["monthlyNoConsumerServedSales"][i][1] *
(float(inputDict.get("resPenetration", 5)) / 100 / 1000)
] for i in range(12)]
outData["totalSolarSold"] = [[
sorted(months.items(), key=lambda x: x[1])[i][0],
outData["totalKWhSold"][i][1] - outData["totalGeneration"][i][1]
] for i in range(12)]
##################
# TODO: add retailCost to the calculation.
##################
## Flow Diagram Calculations, and order of calculation matters
# BAU case
outData["BAU"] = {}
# E23 = E11
outData["BAU"]["totalKWhPurchased"] = float(
inputDict.get("totalKWhPurchased", 1))
# E24 = SUM(E19:P19)
outData["BAU"]["totalKWhSales"] = sum([x[1] for x in totalKWhSold])
# E25 = E23-E24
outData["BAU"]["losses"] = float(inputDict.get(
"totalKWhPurchased", 0)) - sum(
[totalKWhSold[i][1] for i in range(12)])
# E26 = E25/E23
outData["BAU"]["effectiveLossRate"] = outData["BAU"][
"losses"] / outData["BAU"]["totalKWhPurchased"]
# E27 = 0
outData["BAU"]["annualSolarGen"] = 0
# E28 = SUM(E17:P17)
outData["BAU"]["resNonSolarKWhSold"] = sum(
[monthlyKWhSold[i][1] for i in range(12)])
# E29 = 0
outData["BAU"]["solarResDemand"] = 0
# E30 = 0
outData["BAU"]["solarResSold"] = 0
# E31 = E24-E28
outData["BAU"]["nonResKWhSold"] = outData["BAU"][
"totalKWhSales"] - outData["BAU"]["resNonSolarKWhSold"]
# E32 = 0
outData["BAU"]["costSolarGen"] = 0
# E33 = SUM(E20:P20)-SUM(E18:P18)+E10
outData["BAU"]["nonResRev"] = sum([
totalRevenue[i][1] for i in range(12)
]) - sum([monthlyRevenue[i][1] for i in range(12)]) + float(
inputDict.get("otherElecRevenue"))
# E34 = (SUM(E18:P18)-SUM(E16:P16)*E6)/SUM(E17:P17)
outData["BAU"]["effectiveResRate"] = (
sum([monthlyRevenue[i][1] for i in range(12)]) -
sum([monthlyNoConsumerServedSales[i][1] for i in range(12)]) *
float(inputDict.get("customServiceCharge", 0))) / sum(
[monthlyKWhSold[i][1] for i in range(12)])
# E35 = E34*E28+SUM(E16:P16)*E6
outData["BAU"]["resNonSolarRev"] = outData["BAU"][
"effectiveResRate"] * outData["BAU"]["resNonSolarKWhSold"] + sum([
monthlyNoConsumerServedSales[i][1] for i in range(12)
]) * float(inputDict.get("customServiceCharge", 0))
# E36 = E30*E34
outData["BAU"]["solarResRev"] = 0
# E37 = SUM(E48:E54)+SUM(E56:E62)-SUM(E65:E71), update after Form 7 model
outData["BAU"]["nonPowerCosts"] = 0
# E38 = E23-E25-E28-E30-E31
outData["BAU"]["energyAllBal"] = 0
# E39 = E36+E33+E35-E47-E72-E37
outData["BAU"]["dollarAllBal"] = 0
# E40 = 0
outData["BAU"]["avgMonthlyBillSolarCus"] = 0
# E41 = E35/SUM(E16:P16)
avgCustomerCount = (
sum([monthlyNoConsumerServedSales[i][1] for i in range(12)]) / 12)
outData["BAU"]["avgMonthlyBillNonSolarCus"] = outData["BAU"][
"resNonSolarRev"] / sum(
[monthlyNoConsumerServedSales[i][1] for i in range(12)])
# E42 = E63/E24, update after Form 7 model
outData["BAU"]["costofService"] = 0
# Solar case
outData["Solar"] = {}
# F27 = SUM(E15:P15)
outData["Solar"]["annualSolarGen"] = sum(
[outData["totalGeneration"][i][1] for i in range(12)])
# F24 = E24-F27
outData["Solar"]["totalKWhSales"] = sum(
[totalKWhSold[i][1]
for i in range(12)]) - outData["Solar"]["annualSolarGen"]
# F23 =F24/(1-E26)
outData["Solar"]["totalKWhPurchased"] = outData["Solar"][
"totalKWhSales"] / (1 - outData["BAU"]["effectiveLossRate"])
outData["totalsolarmonthly"] = [[
sorted(months.items(),
key=lambda x: x[1])[i][0], outData["totalSolarSold"][i][1] /
(1 - outData["BAU"]["effectiveLossRate"])
] for i in range(12)]
# F25 = F23-F24
outData["Solar"]["losses"] = (outData["Solar"]["totalKWhPurchased"] -
outData["Solar"]["totalKWhSales"])
# F26 = E26
outData["Solar"]["effectiveLossRate"] = outData["BAU"][
"effectiveLossRate"]
# F28 = (1-E5)*E28
outData["Solar"]["resNonSolarKWhSold"] = (
1 - float(inputDict.get("resPenetration", 0)) /
100) * outData["BAU"]["resNonSolarKWhSold"]
# F29 = E5*E28
outData["Solar"]["solarResDemand"] = float(
inputDict.get("resPenetration",
0)) / 100 * outData["BAU"]["resNonSolarKWhSold"]
# F30 = F29-F27
outData["Solar"]["solarResSold"] = outData["Solar"][
"solarResDemand"] - outData["Solar"]["annualSolarGen"]
# F31 = E31
outData["Solar"]["nonResKWhSold"] = outData["BAU"]["nonResKWhSold"]
# F32 = E9*F27
outData["Solar"]["costSolarGen"] = float(
inputDict.get("solarLCoE",
0.07)) * outData["Solar"]["annualSolarGen"]
# F33 = E33
outData["Solar"]["nonResRev"] = outData["BAU"]["nonResRev"]
# F34 = E34
outData["Solar"]["effectiveResRate"] = outData["BAU"][
"effectiveResRate"]
# F35 = E35*(1-E5)
outData["Solar"][
"resNonSolarRev"] = outData["BAU"]["resNonSolarRev"] * (
1 - float(inputDict.get("resPenetration", 0.05)) / 100)
# F30*E34 = Solar revenue from selling at residential rate
solarSoldRateRev = outData["Solar"]["solarResSold"] * outData["Solar"][
"effectiveResRate"]
# (E6+E7)*SUM(E16:P16)*E5 = Solar revenue from charges
solarChargesRev = (
float(inputDict.get("customServiceCharge", 0)) +
float(inputDict.get("solarServiceCharge", 0))) * sum([
monthlyNoConsumerServedSales[i][1] for i in range(12)
]) * float(inputDict.get("resPenetration", 0.05)) / 100
# F36 = F30*E34+(E6+E7)*SUM(E16:P16)*E5 = solarSoldRate + solarChargesRev
outData["Solar"]["solarResRev"] = solarSoldRateRev + solarChargesRev
# F37 = SUM(E48:E54)+SUM(E56:E62)-SUM(E65:E71) = E37, update after Form 7 model
outData["Solar"]["nonPowerCosts"] = 0
# F38 = F23-F25-F28-F30-E31
outData["Solar"]["energyAllBal"] = 0
# F39 = F36+E33+F35-F47-F72-E37
outData["Solar"]["dollarAllBal"] = 0
if (float(inputDict.get("resPenetration", 0.05)) > 0):
# F41 = (F35)/(SUM(E16:P16)*(1-E5))
outData["Solar"]["avgMonthlyBillNonSolarCus"] = outData["Solar"][
"resNonSolarRev"] / (sum([
monthlyNoConsumerServedSales[i][1] for i in range(12)
]) * (1 - float(inputDict.get("resPenetration", 0.05)) / 100))
# F42 = F30*E34/(SUM(E16:P16)*E5)+E6+E7
outData["Solar"]["avgMonthlyBillSolarCus"] = outData["Solar"][
"solarResSold"] * outData["BAU"]["effectiveResRate"] / (sum(
[monthlyNoConsumerServedSales[i][1]
for i in range(12)]) * float(
inputDict.get("resPenetration", 0.05)) / 100) + float(
inputDict.get("customServiceCharge", 0)) + float(
inputDict.get("solarServiceCharge", 0))
# F43 = (F27/(SUM(E16:P16)*E5))*E9
outData["Solar"]["avgMonthlyBillSolarSolarCus"] = (
outData["Solar"]["annualSolarGen"] /
(sum([monthlyNoConsumerServedSales[i][1] for i in range(12)]) *
float(inputDict.get("resPenetration", 0.05)) / 100)) * float(
inputDict.get("solarLCoE", 0.07))
else:
outData["Solar"]["avgMonthlyBillNonSolarCus"] = 0
outData["Solar"]["avgMonthlyBillSolarCus"] = 0
outData["Solar"]["avgMonthlyBillSolarSolarCus"] = 0
# Net Average Monthly Bill
avgMonthlyBillSolarNet = outData["Solar"][
"avgMonthlyBillSolarCus"] + outData["Solar"][
"avgMonthlyBillSolarSolarCus"]
outData["Solar"]["avgMonthlyBillSolarCus"] = avgMonthlyBillSolarNet
# F45 = F63/F24, update after Form 7 model
outData["Solar"]["costofService"] = 0
## Form 7 Model
# E46
outData["Solar"]["powerProExpense"] = outData["BAU"][
"powerProExpense"] = float(inputDict.get("powerProExpense", 0))
# E47 != F47
outData["BAU"]["costPurchasedPower"] = float(
inputDict.get("costPurchasedPower", 0))
# E48
outData["Solar"]["transExpense"] = outData["BAU"][
"transExpense"] = float(inputDict.get("transExpense", 0))
# E49
outData["Solar"]["distriExpenseO"] = outData["BAU"][
"distriExpenseO"] = float(inputDict.get("distriExpenseO", 0))
# E50
outData["Solar"]["distriExpenseM"] = outData["BAU"][
"distriExpenseM"] = float(inputDict.get("distriExpenseM", 0))
# E51
outData["Solar"]["customerAccountExpense"] = outData["BAU"][
"customerAccountExpense"] = float(
inputDict.get("customerAccountExpense", 0))
# E52
outData["Solar"]["customerServiceExpense"] = outData["BAU"][
"customerServiceExpense"] = float(
inputDict.get("customerServiceExpense", 0))
# E53
outData["Solar"]["salesExpense"] = outData["BAU"][
"salesExpense"] = float(inputDict.get("salesExpense", 0))
# E54
outData["Solar"]["adminGeneralExpense"] = outData["BAU"][
"adminGeneralExpense"] = float(
inputDict.get("adminGeneralExpense", 0))
# E56
outData["Solar"]["depreAmortiExpense"] = outData["BAU"][
"depreAmortiExpense"] = float(
inputDict.get("depreAmortiExpense", 0))
# E57
outData["Solar"]["taxExpensePG"] = outData["BAU"][
"taxExpensePG"] = float(inputDict.get("taxExpensePG", 0))
# E58
outData["Solar"]["taxExpense"] = outData["BAU"]["taxExpense"] = float(
inputDict.get("taxExpense", 0))
# E59
outData["Solar"]["interestLongTerm"] = outData["BAU"][
"interestLongTerm"] = float(inputDict.get("interestLongTerm", 0))
# E60
outData["Solar"]["interestConstruction"] = outData["BAU"][
"interestConstruction"] = float(
inputDict.get("interestConstruction", 0))
# E61
outData["Solar"]["interestExpense"] = outData["BAU"][
"interestExpense"] = float(inputDict.get("interestExpense", 0))
# E62
outData["Solar"]["otherDeductions"] = outData["BAU"][
"otherDeductions"] = float(inputDict.get("otherDeductions", 0))
# E65
outData["Solar"]["nonOpMarginInterest"] = outData["BAU"][
"nonOpMarginInterest"] = float(
inputDict.get("nonOpMarginInterest", 0))
# E66
outData["Solar"]["fundsUsedConstruc"] = outData["BAU"][
"fundsUsedConstruc"] = float(inputDict.get("fundsUsedConstruc", 0))
# E67
outData["Solar"]["incomeEquityInvest"] = outData["BAU"][
"incomeEquityInvest"] = float(
inputDict.get("incomeEquityInvest", 0))
# E68
outData["Solar"]["nonOpMarginOther"] = outData["BAU"][
"nonOpMarginOther"] = float(inputDict.get("nonOpMarginOther", 0))
# E69
outData["Solar"]["genTransCapCredits"] = outData["BAU"][
"genTransCapCredits"] = float(
inputDict.get("genTransCapCredits", 0))
# E70
outData["Solar"]["otherCapCreditsPatroDivident"] = outData["BAU"][
"otherCapCreditsPatroDivident"] = float(
inputDict.get("otherCapCreditsPatroDivident", 0))
# E71
outData["Solar"]["extraItems"] = outData["BAU"]["extraItems"] = float(
inputDict.get("extraItems", 0))
# Calculation
# E45 = SUM(E20:P20)+E10
outData["BAU"]["operRevPatroCap"] = sum(
[totalRevenue[i][1]
for i in range(12)]) + float(inputDict.get("otherElecRevenue", 0))
# E55 = SUM(E46:E54)
outData["BAU"]["totalOMExpense"] = float(inputDict.get("powerProExpense")) \
+ float(inputDict.get("costPurchasedPower")) \
+ float(inputDict.get("transExpense")) \
+ float(inputDict.get("distriExpenseO")) \
+ float(inputDict.get("distriExpenseM")) \
+ float(inputDict.get("customerAccountExpense")) \
+ float(inputDict.get("customerServiceExpense")) \
+ float(inputDict.get("salesExpense")) \
+ float(inputDict.get("adminGeneralExpense"))
# E63 = SUM(E55:E62)
outData["BAU"]["totalCostElecService"] = outData["BAU"]["totalOMExpense"] \
+ float(inputDict.get("depreAmortiExpense"))\
+ float(inputDict.get("taxExpensePG"))\
+ float(inputDict.get("taxExpense"))\
+ float(inputDict.get("interestLongTerm"))\
+ float(inputDict.get("interestExpense"))\
+ float(inputDict.get("interestConstruction"))\
+ outData["BAU"]["otherDeductions"]
# E64 = E45-E63
outData["BAU"]["patCapOperMargins"] = outData["BAU"][
"operRevPatroCap"] - outData["BAU"]["totalCostElecService"]
# E72 = SUM(E64:E71)
outData["BAU"]["patCapital"] = outData["BAU"]["patCapOperMargins"]\
+ float(inputDict.get("nonOpMarginInterest"))\
+ float(inputDict.get("fundsUsedConstruc"))\
+ float(inputDict.get("incomeEquityInvest"))\
+ float(inputDict.get("nonOpMarginOther"))\
+ float(inputDict.get("genTransCapCredits"))\
+ float(inputDict.get("otherCapCreditsPatroDivident"))\
+ float(inputDict.get("extraItems"))
# F48 = E48-F27*E34+SUM(E16:P16)*E5*E7
outData["Solar"]["operRevPatroCap"] = outData["BAU"][
"operRevPatroCap"] - outData["BAU"]["effectiveResRate"] * outData[
"Solar"]["annualSolarGen"] + sum(
[monthlyNoConsumerServedSales[i][1]
for i in range(12)]) * float(
inputDict.get("resPenetration", 0.05)) / 100 * float(
inputDict.get("solarServiceCharge", 0))
# F47 = (F23)*E8
inputDict["costofPower"] = float(inputDict.get(
"costPurchasedPower", 0)) / float(
inputDict.get("totalKWhPurchased", 0))
outData["Solar"]["costPurchasedPower"] = outData["Solar"][
"totalKWhPurchased"] * float(inputDict.get("costofPower", 0))
inputDict["costofPower"] = round(inputDict["costofPower"], 3)
# F55 = SUM(F46:F54)
outData["Solar"]["totalOMExpense"] = outData["Solar"]["powerProExpense"]\
+ outData["Solar"]["costPurchasedPower"]\
+ outData["Solar"]["transExpense"]\
+ outData["Solar"]["distriExpenseO"]\
+ outData["Solar"]["distriExpenseM"]\
+ outData["Solar"]["customerAccountExpense"]\
+ outData["Solar"]["customerServiceExpense"]\
+ outData["Solar"]["salesExpense"]\
+ outData["Solar"]["adminGeneralExpense"]
# F63 = E63
outData["Solar"]["totalCostElecService"] = outData["Solar"]["totalOMExpense"]\
+ outData["Solar"]["depreAmortiExpense"]\
+ outData["Solar"]["taxExpensePG"]\
+ outData["Solar"]["taxExpense"]\
+ outData["Solar"]["interestLongTerm"]\
+ outData["Solar"]["interestConstruction"]\
+ outData["Solar"]["interestExpense"]\
+ outData["Solar"]["otherDeductions"]
# F64 = F45 - F63
outData["Solar"]["patCapOperMargins"] = outData["Solar"][
"operRevPatroCap"] - outData["Solar"]["totalCostElecService"]
# F72 = SUM(F64:F71)
outData["Solar"]["patCapital"] = outData["Solar"]["patCapOperMargins"]\
+ outData["Solar"]["nonOpMarginInterest"]\
+ outData["Solar"]["fundsUsedConstruc"]\
+ outData["Solar"]["incomeEquityInvest"]\
+ outData["Solar"]["nonOpMarginOther"]\
+ outData["Solar"]["genTransCapCredits"]\
+ outData["Solar"]["otherCapCreditsPatroDivident"]\
+ outData["Solar"]["extraItems"]
# E37 = SUM(E48:E54)+SUM(E56:E62)-SUM(E65:E71), update after Form 7 model
outData["BAU"]["nonPowerCosts"] = outData["BAU"]["transExpense"] \
+ outData["BAU"]["distriExpenseO"] \
+ outData["BAU"]["distriExpenseM"] \
+ outData["BAU"]["customerAccountExpense"] \
+ outData["BAU"]["customerServiceExpense"] \
+ outData["BAU"]["salesExpense"] \
+ outData["BAU"]["adminGeneralExpense"] \
+ outData["BAU"]["depreAmortiExpense"] \
+ outData["BAU"]["taxExpensePG"] \
+ outData["BAU"]["taxExpense"] \
+ outData["BAU"]["interestLongTerm"] \
+ outData["BAU"]["interestConstruction"] \
+ outData["BAU"]["interestExpense"] \
+ outData["BAU"]["otherDeductions"] \
- (outData["BAU"]["nonOpMarginInterest"] \
+ outData["BAU"]["fundsUsedConstruc"] \
+ outData["BAU"]["incomeEquityInvest"] \
+ outData["BAU"]["nonOpMarginOther"] \
+ outData["BAU"]["genTransCapCredits"] \
+ outData["BAU"]["otherCapCreditsPatroDivident"] \
+ outData["BAU"]["extraItems"])
# E42 = E63/E24, update after Form 7 model
outData["BAU"]["costofService"] = outData["BAU"][
"totalCostElecService"] / outData["BAU"]["totalKWhSales"]
# F37 = SUM(E48:E54)+SUM(E56:E62)-SUM(E65:E71) = E37, update after Form 7 model
outData["Solar"]["nonPowerCosts"] = outData["BAU"]["nonPowerCosts"]
# F42 = F63/F24, update after Form 7 model
outData["Solar"]["costofService"] = outData["Solar"][
"totalCostElecService"] / outData["Solar"]["totalKWhSales"]
# Stdout/stderr.
outData["stdout"] = "Success"
outData["stderr"] = ""
# Write the output.
with open(pJoin(modelDir, "allOutputData.json"), "w") as outFile:
json.dump(outData, outFile, indent=4)
# Update the runTime in the input file.
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)
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)