def calibrate_omd(start_date, omd_path, csv_path):
"""
Modify an .omd file so that it will run in GridLAB-D with the CSV of USCRN weather data.
:param start_date: the starting date of the GridLAB-D simulation
:type start_date: datetime
:param omd_path: an absolute path to the .omd file to modify
:type omd_path: str
:param csv_path: an absolute path to the CSV file that contains USCRN weather data
:type csv_path: str
"""
with open(omd_path, 'r') as f:
omd = json.load(f)
tree = omd["tree"]
# Delete all climate objects from the feeder. Also delete any csv_reader objects that are also named "WeatherReader"
weather_reader_name = "WeatherReader"
for key in tree.keys():
object_type = tree[key].get("object")
object_name = tree[key].get("name")
if object_type == "climate" or (object_type == "csv_reader" and
object_name == weather_reader_name):
del tree[key]
# Reinsert a new climate object and an associated csv_reader object
oldMax = feeder.getMaxKey(tree)
tree[oldMax + 1] = {'omftype': 'module', 'argument': 'tape'}
tree[oldMax + 2] = {'omftype': 'module', 'argument': 'climate'}
csv_name = os.path.basename(csv_path)
tree[oldMax + 3] = {
'object': 'csv_reader',
'name': weather_reader_name,
'filename': csv_name
}
climate_name = "MyClimate"
tree[oldMax + 4] = {
'object': 'climate',
'name': climate_name,
'reader': weather_reader_name,
'tmyfile': csv_name
}
# Set the time correctly. Modify certain objects in the feeder (e.g. recorder and clock)
feeder.adjustTime(
tree, 240, 'hours',
'{}-{}-{}'.format(start_date.year, start_date.month, start_date.day))
omd["tree"] = tree
# Add the weather attachment
with open(csv_path, 'r') as f:
weatherString = f.read()
if omd.get("attachments") is None:
omd["attachments"] = {}
omd['attachments'][csv_name] = weatherString
with open(omd_path, 'w') as f:
json.dump(omd, f, indent=4)
def runForeground(modelDir, inData):
'''This reads a glm file, changes the method of powerflow and reruns'''
print "STARTING TO RUN", modelDir
try:
startTime = dt.now()
if not os.path.isdir(modelDir):
os.makedirs(modelDir)
inData["created"] = str(startTime)
#read pre-calibrated feeder and run cvrdynamic
feederName = inData.get('feederName1', 'feeder1')
feederPath = pJoin(modelDir, feederName + '.omd')
# Reads a pre-calibrated feeder.
allOutput = {}
with open(feederPath, "r") as jsonIn:
feederJson = json.load(jsonIn)
localTree = feederJson.get("tree", {})
attachments = feederJson.get("attachments", {})
for key in localTree:
if "solver_method" in localTree[key].keys():
# print "current solver method", localTree[key]["solver_method"]
localTree[key]["solver_method"] = 'FBS'
#find the swing bus and recorder attached to substation
try:
for key in localTree:
if localTree[key].get('bustype', '').lower() == 'swing':
swingIndex = key
swingName = localTree[key].get('name')
if localTree[key].get(
'object', '') == 'regulator' and localTree[key].get(
'from', '') == swingName:
regIndex = key
regConfName = localTree[key]['configuration']
except:
raise ValueError('Invalid feeder selected:',
str(inData["feederName1"]))
#find the regulator and capacitor names and combine to form a string for volt-var control object
regKeys = []
accum_reg = ""
for key in localTree:
if localTree[key].get("object", "") == "regulator":
accum_reg += localTree[key].get("name", "ERROR") + ","
regKeys.append(key)
regstr = accum_reg[:-1]
# print regKeys
capKeys = []
accum_cap = ""
for key in localTree:
if localTree[key].get("object", "") == "capacitor":
accum_cap += localTree[key].get("name", "ERROR") + ","
capKeys.append(key)
if localTree[key].get("control", "").lower() == "manual":
localTree[key]['control'] = "VOLT"
# print "changing capacitor control from manual to volt"
capstr = accum_cap[:-1]
# print capKeys
# Attach recorders relevant to CVR.
recorders = [{
'object':
'collector',
'file':
'ZlossesTransformer.csv',
'group':
'class=transformer',
'limit':
'0',
'property':
'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'
}, {
'object':
'collector',
'file':
'ZlossesUnderground.csv',
'group':
'class=underground_line',
'limit':
'0',
'property':
'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'
}, {
'object':
'collector',
'file':
'ZlossesOverhead.csv',
'group':
'class=overhead_line',
'limit':
'0',
'property':
'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'
}, {
'object':
'recorder',
'file':
'Zregulator.csv',
'limit':
'0',
'parent':
localTree[regIndex]['name'],
'property':
'tap_A,tap_B,tap_C,power_in.real,power_in.imag'
}, {
'object':
'collector',
'file':
'ZvoltageJiggle.csv',
'group':
'class=triplex_meter',
'limit':
'0',
'property':
'min(voltage_12.mag),mean(voltage_12.mag),max(voltage_12.mag),std(voltage_12.mag)'
}, {
'object': 'recorder',
'file': 'ZsubstationTop.csv',
'limit': '0',
'parent': localTree[swingIndex]['name'],
'property': 'voltage_A,voltage_B,voltage_C'
}, {
'object': 'recorder',
'file': 'ZsubstationBottom.csv',
'limit': '0',
'parent': localTree[regIndex]['to'],
'property': 'voltage_A,voltage_B,voltage_C'
}]
#recorder object for capacitor switching - if capacitors exist
if capKeys != []:
for key in capKeys:
recorders.append({
'object': 'recorder',
'file': 'ZcapSwitch' + str(key) + '.csv',
'limit': '0',
'parent': localTree[key]['name'],
'property': 'switchA,switchB,switchC'
})
#attach recorder process
biggest = 1 + max([int(k) for k in localTree.keys()])
for index, rec in enumerate(recorders):
localTree[biggest + index] = rec
#run a reference load flow
HOURS = float(inData['simLengthHours'])
simStartDate = inData['simStart']
feeder.adjustTime(localTree, HOURS, "hours", simStartDate)
output = gridlabd.runInFilesystem(localTree,
attachments,
keepFiles=False,
workDir=modelDir)
try:
os.remove(pJoin(modelDir, "PID.txt"))
except:
pass
p = output['Zregulator.csv']['power_in.real']
q = output['Zregulator.csv']['power_in.imag']
#calculating length of simulation because it migth be different from the simulation input HOURS
simRealLength = int(len(p))
#time delays from configuration files
time_delay_reg = '30.0'
time_delay_cap = '300.0'
for key in localTree:
if localTree[key].get('object', '') == "regulator_configuration":
time_delay_reg = localTree[key]['time_delay']
# print "time_delay_reg",time_delay_reg
# if localTree[key].get('object','') == "capacitor":
# time_delay_cap = localTree[key]['time_delay']
# print "time_delay_cap",time_delay_cap
#change the recorder names
for key in localTree:
if localTree[key].get('object',
'') == "collector" or localTree[key].get(
'object', '') == "recorder":
if localTree[key].get('file', '').startswith('Z'):
localTree[key]['file'] = localTree[key].get(
'file', '').replace('Z', 'NewZ')
#create volt-var control object
max_key = max([int(key) for key in localTree.keys()])
# print max_key
localTree[max_key + 1] = {
'object': 'volt_var_control',
'name': 'IVVC1',
'control_method': 'ACTIVE',
'capacitor_delay': str(time_delay_cap),
'regulator_delay': str(time_delay_reg),
'desired_pf': '0.99',
'd_max': '0.6',
'd_min': '0.1',
'substation_link': str(localTree[regIndex]['name']),
'regulator_list': regstr,
'capacitor_list': capstr,
'voltage_measurements': str(inData.get("voltageNodes", "IVVC1")),
}
#running powerflow analysis via gridalab after attaching a regulator
feeder.adjustTime(localTree, HOURS, "hours", simStartDate)
output1 = gridlabd.runInFilesystem(localTree,
attachments,
keepFiles=True,
workDir=modelDir)
os.remove(pJoin(modelDir, "PID.txt"))
pnew = output1['NewZregulator.csv']['power_in.real']
qnew = output1['NewZregulator.csv']['power_in.imag']
#total real and imaginary losses as a function of time
def vecSum(u, v):
''' Add vectors u and v element-wise. Return has len <= len(u) and <=len(v). '''
return map(sum, zip(u, v))
def zeroVec(length):
''' Give a zero vector of input length. '''
return [0 for x in xrange(length)]
(realLoss, imagLoss, realLossnew, imagLossnew) = (zeroVec(int(HOURS))
for x in range(4))
for device in [
'ZlossesOverhead.csv', 'ZlossesTransformer.csv',
'ZlossesUnderground.csv'
]:
for letter in ['A', 'B', 'C']:
realLoss = vecSum(
realLoss,
output[device]['sum(power_losses_' + letter + '.real)'])
imagLoss = vecSum(
imagLoss,
output[device]['sum(power_losses_' + letter + '.imag)'])
realLossnew = vecSum(
realLossnew, output1['New' + device]['sum(power_losses_' +
letter + '.real)'])
imagLossnew = vecSum(
imagLossnew, output1['New' + device]['sum(power_losses_' +
letter + '.imag)'])
#voltage calculations and tap calculations
def divby2(u):
'''divides by 2'''
return u / 2
lowVoltage = []
meanVoltage = []
highVoltage = []
lowVoltagenew = []
meanVoltagenew = []
highVoltagenew = []
tap = {'A': [], 'B': [], 'C': []}
tapnew = {'A': [], 'B': [], 'C': []}
volt = {'A': [], 'B': [], 'C': []}
voltnew = {'A': [], 'B': [], 'C': []}
switch = {'A': [], 'B': [], 'C': []}
switchnew = {'A': [], 'B': [], 'C': []}
for letter in ['A', 'B', 'C']:
tap[letter] = output['Zregulator.csv']['tap_' + letter]
tapnew[letter] = output1['NewZregulator.csv']['tap_' + letter]
if capKeys != []:
switch[letter] = output['ZcapSwitch' + str(int(capKeys[0])) +
'.csv']['switch' + letter]
switchnew[letter] = output1['NewZcapSwitch' +
str(int(capKeys[0])) +
'.csv']['switch' + letter]
volt[letter] = map(
returnMag,
output['ZsubstationBottom.csv']['voltage_' + letter])
voltnew[letter] = map(
returnMag,
output1['NewZsubstationBottom.csv']['voltage_' + letter])
lowVoltage = map(divby2,
output['ZvoltageJiggle.csv']['min(voltage_12.mag)'])
lowVoltagenew = map(
divby2, output1['NewZvoltageJiggle.csv']['min(voltage_12.mag)'])
meanVoltage = map(divby2,
output['ZvoltageJiggle.csv']['mean(voltage_12.mag)'])
meanVoltagenew = map(
divby2, output1['NewZvoltageJiggle.csv']['mean(voltage_12.mag)'])
highVoltage = map(divby2,
output['ZvoltageJiggle.csv']['max(voltage_12.mag)'])
highVoltagenew = map(
divby2, output1['NewZvoltageJiggle.csv']['max(voltage_12.mag)'])
#energy calculations
whEnergy = []
whLosses = []
whLoads = []
whEnergy.append(sum(p) / 10**6)
whLosses.append(sum(realLoss) / 10**6)
whLoads.append((sum(p) - sum(realLoss)) / 10**6)
whEnergy.append(sum(pnew) / 10**6)
whLosses.append(sum(realLossnew) / 10**6)
whLoads.append((sum(pnew) - sum(realLossnew)) / 10**6)
indices = ['No IVVC', 'With IVVC']
# energySalesRed = (whLoads[1]-whLoads[0])*(inData['wholesaleEnergyCostPerKwh'])*1000
# lossSav = (whLosses[0]-whLosses[1])*inData['wholesaleEnergyCostPerKwh']*1000
# print energySalesRed, lossSav
#plots
ticks = []
plt.clf()
plt.title("total energy")
plt.ylabel("total load and losses (MWh)")
for element in range(2):
ticks.append(element)
bar_loss = plt.bar(element, whLosses[element], 0.15, color='red')
bar_load = plt.bar(element + 0.15,
whLoads[element],
0.15,
color='orange')
plt.legend([bar_load[0], bar_loss[0]], ['total load', 'total losses'],
bbox_to_anchor=(0., 0.915, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.1)
plt.xticks([t + 0.15 for t in ticks], indices)
plt.savefig(pJoin(modelDir, "totalEnergy.png"))
#real and imaginary power
plt.figure("real power")
plt.title("Real Power at substation")
plt.ylabel("substation real power (MW)")
pMW = [element / 10**6 for element in p]
pMWn = [element / 10**6 for element in pnew]
pw = plt.plot(pMW)
npw = plt.plot(pMWn)
plt.legend([pw[0], npw[0]], ['NO IVVC', 'WITH IVVC'],
bbox_to_anchor=(0., 0.915, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.1)
plt.savefig(pJoin(modelDir, "realPower.png"))
plt.figure("Reactive power")
plt.title("Reactive Power at substation")
plt.ylabel("substation reactive power (MVAR)")
qMVAR = [element / 10**6 for element in q]
qMVARn = [element / 10**6 for element in qnew]
iw = plt.plot(qMVAR)
niw = plt.plot(qMVARn)
plt.legend([iw[0], niw[0]], ['NO IVVC', 'WITH IVVC'],
bbox_to_anchor=(0., 0.915, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.1)
plt.savefig(pJoin(modelDir, "imaginaryPower.png"))
#voltage plots
plt.figure("voltages as a function of time")
f, ax = plt.subplots(2, sharex=True)
f.suptitle("Min and Max voltages on the feeder")
lv = ax[0].plot(lowVoltage, color='cadetblue')
mv = ax[0].plot(meanVoltage, color='blue')
hv = ax[0].plot(highVoltage, color='cadetblue')
ax[0].legend([lv[0], mv[0], hv[0]],
['low voltage', 'mean voltage', 'high voltage'],
bbox_to_anchor=(0., 0.915, 1., .1),
loc=3,
ncol=3,
mode="expand",
borderaxespad=0.1)
ax[0].set_ylabel('NO IVVC')
nlv = ax[1].plot(lowVoltagenew, color='cadetblue')
nmv = ax[1].plot(meanVoltagenew, color='blue')
nhv = ax[1].plot(highVoltagenew, color='cadetblue')
ax[1].set_ylabel('WITH IVVC')
plt.savefig(pJoin(modelDir, "Voltages.png"))
#tap positions
plt.figure("TAP positions NO IVVC")
f, ax = plt.subplots(6, sharex=True)
f.set_size_inches(10, 12.0)
#f.suptitle("Regulator Tap positions")
ax[0].plot(tap['A'])
ax[0].set_title("Regulator Tap positions NO IVVC")
ax[0].set_ylabel("TAP A")
ax[1].plot(tap['B'])
ax[1].set_ylabel("TAP B")
ax[2].plot(tap['C'])
ax[2].set_ylabel("TAP C")
ax[3].plot(tapnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel("TAP A")
ax[4].plot(tapnew['B'])
ax[4].set_ylabel("TAP B")
ax[5].plot(tapnew['C'])
ax[5].set_ylabel("TAP C")
for subplot in range(6):
ax[subplot].set_ylim(-20, 20)
f.tight_layout()
plt.savefig(pJoin(modelDir, "RegulatorTAPpositions.png"))
#substation voltages
plt.figure("substation voltage as a function of time")
f, ax = plt.subplots(6, sharex=True)
f.set_size_inches(10, 12.0)
#f.suptitle("voltages at substation NO IVVC")
ax[0].plot(volt['A'])
ax[0].set_title('Substation voltages NO IVVC')
ax[0].set_ylabel('voltage A')
ax[1].plot(volt['B'])
ax[1].set_ylabel('voltage B')
ax[2].plot(volt['C'])
ax[2].set_ylabel('voltage C')
ax[3].plot(voltnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel('voltage A')
ax[4].plot(voltnew['B'])
ax[4].set_ylabel('voltage B')
ax[5].plot(voltnew['C'])
ax[5].set_ylabel('voltage C')
f.tight_layout()
plt.savefig(pJoin(modelDir, "substationVoltages.png"))
#cap switches
plt.figure("capacitor switch state as a function of time")
f, ax = plt.subplots(6, sharex=True)
f.set_size_inches(10, 12.0)
#f.suptitle("Capacitor switch state NO IVVC")
ax[0].plot(switch['A'])
ax[0].set_title("Capacitor switch state NO IVVC")
ax[0].set_ylabel("switch A")
ax[1].plot(switch['B'])
ax[1].set_ylabel("switch B")
ax[2].plot(switch['C'])
ax[2].set_ylabel("switch C")
ax[3].plot(switchnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel("switch A")
ax[4].plot(switchnew['B'])
ax[4].set_ylabel("switch B")
ax[5].plot(switchnew['C'])
ax[5].set_ylabel("switch C")
for subplot in range(6):
ax[subplot].set_ylim(-2, 2)
f.tight_layout()
plt.savefig(pJoin(modelDir, "capacitorSwitch.png"))
#plt.show()
#monetization
monthNames = [
"January", "February", "March", "April", "May", "June", "July",
"August", "September", "October", "November", "December"
]
monthToSeason = {
'January': 'Winter',
'February': 'Winter',
'March': 'Spring',
'April': 'Spring',
'May': 'Spring',
'June': 'Summer',
'July': 'Summer',
'August': 'Summer',
'September': 'Fall',
'October': 'Fall',
'November': 'Fall',
'December': 'Winter'
}
#calculate the month and hour of simulation start and month and hour of simulation end
simStartTimestamp = simStartDate + " 00:00:00"
simFormattedDate = dt.strptime(simStartTimestamp, "%Y-%m-%d %H:%M:%S")
simStartMonthNum = int(simFormattedDate.strftime('%m'))
simstartMonth = monthNames[simStartMonthNum - 1]
simStartDay = int(simFormattedDate.strftime('%d'))
if calendar.isleap(int(simFormattedDate.strftime('%Y'))):
febDays = 29
else:
febDays = 28
monthHours = [
int(31 * 24),
int(febDays * 24),
int(31 * 24),
int(30 * 24),
int(31 * 24),
int(30 * 24),
int(31 * 24),
int(31 * 24),
int(30 * 24),
int(31 * 24),
int(30 * 24),
int(31 * 24)
]
simStartIndex = int(
sum(monthHours[:(simStartMonthNum - 1)]) + (simStartDay - 1) * 24)
temp = 0
cumulHours = [0]
for x in range(12):
temp += monthHours[x]
cumulHours.append(temp)
for i in range((simStartMonthNum), 13):
if int(simStartIndex + simRealLength) <= cumulHours[i] and int(
simStartIndex + simRealLength) > cumulHours[i - 1]:
simEndMonthNum = i - 1
simEndMonth = monthNames[simEndMonthNum]
# print simstartMonth,simEndMonth
#calculate peaks for the number of months in simulation
previndex = 0
monthPeak = {}
monthPeakNew = {}
peakSaveDollars = {}
energyLostDollars = {}
lossRedDollars = {}
simMonthList = monthNames[monthNames.index(simstartMonth):(
monthNames.index(simEndMonth) + 1)]
# print simMonthList
for monthElement in simMonthList:
# print monthElement
month = monthNames.index(monthElement)
index1 = int(previndex)
index2 = int(min((index1 + int(monthHours[month])), simRealLength))
monthPeak[monthElement] = max(p[index1:index2]) / 1000.0
monthPeakNew[monthElement] = max(pnew[index1:index2]) / 1000.0
peakSaveDollars[monthElement] = (
monthPeak[monthElement] - monthPeakNew[monthElement]) * float(
inData['peakDemandCost' +
str(monthToSeason[monthElement]) + 'PerKw'])
lossRedDollars[monthElement] = (
sum(realLoss[index1:index2]) / 1000.0 -
sum(realLossnew[index1:index2]) / 1000.0) * (float(
inData['wholesaleEnergyCostPerKwh']))
energyLostDollars[monthElement] = (
sum(p[index1:index2]) / 1000.0 - sum(pnew[index1:index2]) /
1000.0 - sum(realLoss[index1:index2]) / 1000.0 +
sum(realLossnew[index1:index2]) / 1000.0) * (
float(inData['wholesaleEnergyCostPerKwh']) -
float(inData['retailEnergyCostPerKwh']))
previndex = index2
#money charts
fig = plt.figure("cost benefit barchart", figsize=(10, 8))
ticks = range(len(simMonthList))
ticks1 = [element + 0.15 for element in ticks]
ticks2 = [element + 0.30 for element in ticks]
# print ticks
eld = [energyLostDollars[month] for month in simMonthList]
lrd = [lossRedDollars[month] for month in simMonthList]
psd = [peakSaveDollars[month] for month in simMonthList]
bar_eld = plt.bar(ticks, eld, 0.15, color='red')
bar_psd = plt.bar(ticks1, psd, 0.15, color='blue')
bar_lrd = plt.bar(ticks2, lrd, 0.15, color='green')
plt.legend([bar_eld[0], bar_psd[0], bar_lrd[0]], [
'energyLostDollars', 'peakReductionDollars', 'lossReductionDollars'
],
bbox_to_anchor=(0., 1.015, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.1)
monShort = [element[0:3] for element in simMonthList]
plt.xticks([t + 0.15 for t in ticks], monShort)
plt.ylabel('Utility Savings ($)')
plt.savefig(pJoin(modelDir, "spendChart.png"))
#cumulative savings graphs
fig = plt.figure("cost benefit barchart", figsize=(10, 5))
annualSavings = sum(eld) + sum(lrd) + sum(psd)
annualSave = lambda x: (annualSavings - float(inData['omCost'])
) * x - float(inData['capitalCost'])
simplePayback = float(
inData['capitalCost']) / (annualSavings - float(inData['omCost']))
plt.xlabel('Year After Installation')
plt.xlim(0, 30)
plt.ylabel('Cumulative Savings ($)')
plt.plot([0 for x in range(31)], c='gray')
plt.axvline(x=simplePayback, ymin=0, ymax=1, c='gray', linestyle='--')
plt.plot([annualSave(x) for x in range(31)], c='green')
plt.savefig(pJoin(modelDir, "savingsChart.png"))
#get exact time stamps from the CSV files generated by Gridlab-D
timeWithZone = output['Zregulator.csv']['# timestamp']
timestamps = [element[:19] for element in timeWithZone]
#data for highcharts
allOutput["timeStamps"] = timestamps
allOutput["noCVRPower"] = p
allOutput["withCVRPower"] = pnew
allOutput["noCVRLoad"] = whLoads[0]
allOutput["withCVRLoad"] = whLoads[1]
allOutput["noCVRLosses"] = whLosses[0]
allOutput["withCVRLosses"] = whLosses[1]
allOutput["noCVRTaps"] = tap
allOutput["withCVRTaps"] = tapnew
allOutput["noCVRSubVolts"] = volt
allOutput["withCVRSubVolts"] = voltnew
allOutput["noCVRCapSwitch"] = switch
allOutput["withCVRCapSwitch"] = switchnew
allOutput["noCVRHighVolt"] = highVoltage
allOutput["withCVRHighVolt"] = highVoltagenew
allOutput["noCVRLowVolt"] = lowVoltage
allOutput["withCVRLowVolt"] = lowVoltagenew
allOutput["noCVRMeanVolt"] = meanVoltage
allOutput["withCVRMeanVolt"] = meanVoltagenew
#monetization
allOutput["simMonthList"] = monShort
allOutput["energyLostDollars"] = energyLostDollars
allOutput["lossRedDollars"] = lossRedDollars
allOutput["peakSaveDollars"] = peakSaveDollars
allOutput["annualSave"] = [annualSave(x) for x in range(31)]
# Generate warnings
#TODO: Timezone adjustment
try:
# Check if times for simulation and scada match.
scadaDates = []
with open(pJoin(modelDir, "subScadaCalibrated1.player"),
"r") as scadaFile:
for line in scadaFile:
(date, val) = line.split(',')
scadaDates.append(str(date))
simFormattedEndDate = simFormattedDate + timedelta(hours=HOURS)
scadaStartDate = dt.strptime(scadaDates[0].split(' PST')[0],
"%Y-%m-%d %H:%M:%S")
scadaEndDate = dt.strptime(
scadaDates[len(scadaDates) - 1].split(' PST')[0],
"%Y-%m-%d %H:%M:%S")
beginRange = (scadaStartDate - simFormattedDate).total_seconds()
endRange = (scadaEndDate - simFormattedEndDate).total_seconds()
# Check if houses exist.
housesExist, voltageNodeExists = False, False
for key in localTree:
if localTree[key].get('object', '') == 'house':
housesExist = True
if localTree[key].get('name',
'') == str(inData.get("voltageNodes",
0)):
voltageNodeExists = True
if (beginRange > 0.0 or endRange < 0.0) and not housesExist:
allOutput[
"warnings"] = "<strong>WARNING:</strong> The simulation dates entered are not compatible with the scada curve in the feeder."
# Check if voltage node exists.
if not voltageNodeExists:
if allOutput.get('warnings', '') != "":
previousWarning = allOutput["warnings"]
allOutput[
"warnings"] = previousWarning + " The voltage node: " + str(
inData.get("voltageNodes",
0)) + " does not exist in the feeder."
else:
allOutput[
"warnings"] = "<strong>WARNING:</strong> The voltage node <i>" + str(
inData.get(
"voltageNodes",
0)) + "</i> does not exist in the feeder."
except:
pass
# Update the runTime in the input file.
endTime = dt.now()
inData["runTime"] = str(
timedelta(seconds=int((endTime - startTime).total_seconds())))
with open(pJoin(modelDir, "allInputData.json"), "w") as inFile:
json.dump(inData, inFile, indent=4)
with open(pJoin(modelDir, "allOutputData.json"), "w") as outFile:
json.dump(allOutput, outFile, indent=4)
# For autotest, there won't be such file.
try:
os.remove(pJoin(modelDir, "PPID.txt"))
except Exception, e:
pass
print "DONE RUNNING", modelDir
def attachVolts(workDir, feederPath, voltVectorA, voltVectorB, voltVectorC, simStartDate, simLength, simLengthUnits):
'''read voltage vectors of 3 different phases, run gridlabd, and attach output to the feeder.'''
try:
timeStamp = [simStartDate['Date']]
for x in range (1, 8760):
timeStamp.append(timeStamp[x-1] + dt.timedelta(hours=1))
firstDateTime = timeStamp[1]
with open(pJoin(pJoin(workDir,"gridlabD"),"phaseAVoltage.player"),"w") as voltFile:
for x in range(0, 8760):
timestamp = timeStamp[x]
voltage = str("%0.2f"%float(voltVectorA[x]))+"+0j"
line = timestamp.strftime("%Y-%m-%d %H:%M:%S") + " " + simStartDate['timeZone'] + "," + str(voltage) + "\n"
voltFile.write(line)
with open(pJoin(pJoin(workDir,"gridlabD"),"phaseBVoltage.player"),"w") as voltFile:
for x in range(0, 8760):
timestamp = timeStamp[x]
voltage = str("%0.2f"%float(voltVectorB[x]))+"-"+str("%0.4f"%float(random.uniform(6449,6460)))+"j"
line = timestamp.strftime("%Y-%m-%d %H:%M:%S") + " " + simStartDate['timeZone'] + "," + str(voltage) + "\n"
voltFile.write(line)
with open(pJoin(pJoin(workDir,"gridlabD"),"phaseCVoltage.player"),"w") as voltFile:
for x in range(0, 8760):
timestamp = timeStamp[x]
voltage = str("%0.2f"%float(voltVectorC[x]))+"+"+str("%0.4f"%float(random.uniform(6449,6460)))+"j"
line = timestamp.strftime("%Y-%m-%d %H:%M:%S") + " " + simStartDate['timeZone'] + "," + str(voltage) + "\n"
voltFile.write(line)
with open(feederPath, "r") as jsonIn:
feederJson = json.load(jsonIn)
tree = feederJson.get("tree", {})
# Find swingNode name.
for key in tree:
if tree[key].get('bustype','').lower() == 'swing':
swingName = tree[key].get('name')
# Attach player.
classOb = {'omftype':'class player','argument':'{double value;}'}
voltageObA = {"object":"player", "property":"voltage_A", "file":"phaseAVoltage.player", "loop":"0", "parent":swingName}
voltageObB = {"object":"player", "property":"voltage_B", "file":"phaseBVoltage.player", "loop":"0", "parent":swingName}
voltageObC = {"object":"player", "property":"voltage_C", "file":"phaseCVoltage.player", "loop":"0", "parent":swingName}
maxKey = feeder.getMaxKey(tree)
voltplayerKeyA = maxKey + 2
voltplayerKeyB = maxKey + 3
voltplayerKeyC = maxKey + 4
tree[maxKey+1] = classOb
tree[voltplayerKeyA] = voltageObA
tree[voltplayerKeyB] = voltageObB
tree[voltplayerKeyC] = voltageObC
# Adjust time and run output.
feeder.adjustTime(tree, simLength, simLengthUnits, firstDateTime.strftime("%Y-%m-%d %H:%M:%S"))
output = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=pJoin(workDir,"gridlabD"))
# Write the output.
with open(pJoin(workDir,"calibratedFeeder.omd"),"w") as outJson:
playerStringA = open(pJoin(pJoin(workDir,"gridlabD"),"phaseAVoltage.player")).read()
playerStringB = open(pJoin(pJoin(workDir,"gridlabD"),"phaseBVoltage.player")).read()
playerStringC = open(pJoin(pJoin(workDir,"gridlabD"),"phaseCVoltage.player")).read()
feederJson["attachments"]["phaseAVoltage.player"] = playerStringA
feederJson["attachments"]["phaseBVoltage.player"] = playerStringB
feederJson["attachments"]["phaseCVoltage.player"] = playerStringC
feederJson["tree"] = tree
json.dump(feederJson, outJson, indent=4)
return pJoin(workDir,"calibratedFeeder.omd"), True
except:
print "Failed to run gridlabD with voltage players."
return "", False
def omfCalibrate(workDir, feederPath, scadaPath, simStartDate, simLength, simLengthUnits, solver="FBS", calibrateError=(0.05,5), trim=5):
'''calibrates a feeder and saves the calibrated tree at a location.
Note: feeders with cap banks should be calibrated with cap banks OPEN.
We have seen cap banks throw off calibration.'''
with open(feederPath, "r") as jsonIn:
feederJson = json.load(jsonIn)
tree = feederJson.get("tree", {})
simLength = simLength + trim
# Process scada data.
scadaSubPower = _processScadaData(pJoin(workDir,"gridlabD"),scadaPath, simStartDate, simLengthUnits)
# Load specified solver.
for key in tree:
if tree[key].get("module","").lower() == "powerflow":
tree[key] = {"module":"powerflow","solver_method":solver}
# Attach player.
classOb = {'omftype':'class player','argument':'{double value;}'}
playerOb = {"object":"player", "property":"value", "name":"scadaLoads", "file":"subScada.player", "loop":"0"}
maxKey = feeder.getMaxKey(tree)
playerKey = maxKey + 2
tree[maxKey+1] = classOb
tree[playerKey] = playerOb
# Make loads reference player.
loadTemplate = {"object": "triplex_load",
"power_pf_12": "0.95",
"impedance_pf_12": "0.98",
"power_pf_12": "0.90",
"impedance_fraction_12": "0.7",
"power_fraction_12": "0.3"}
loadTemplateR = {"object": "load",
"impedance_pf_A": "0.98",
"impedance_pf_B": "0.98",
"impedance_pf_C": "0.98",
"power_pf_A": "0.90",
"power_pf_B": "0.90",
"power_pf_C": "0.90",
"impedance_fraction_A": "0.7",
"impedance_fraction_B": "0.7",
"impedance_fraction_C": "0.7",
"power_fraction_A": "0.3",
"power_fraction_B": "0.3",
"power_fraction_C": "0.3"}
for key in tree:
ob = tree[key]
if ob.get("object","") in ("triplex_node", "triplex_load") and (ob.get("power_12") or ob.get("base_power_12")):
# Add to triplex_nodes.
newOb = dict(loadTemplate)
newOb["name"] = ob.get("name", "")
newOb["parent"] = ob.get("parent", "")
newOb["phases"] = ob.get("phases", "")
newOb["nominal_voltage"] = ob.get("nominal_voltage","")
newOb["latitude"] = ob.get("latitude","0")
newOb["longitude"] = ob.get("longitude","0")
oldPow = ob.get("power_12","").replace("j","d")
if not oldPow:
oldPow = ob.get("base_power_12")
if "scadaloads.value*" in oldPow:
oldPow = oldPow[17:]
pythagPower = gridlabd._strClean(oldPow)
newOb["base_power_12"] = "scadaLoads.value*" + str(pythagPower)
tree[key] = newOb
elif ob.get("object","") == "load":
# Add to residential_loads too.
newOb = dict(loadTemplateR)
newOb["name"] = ob.get("name", "")
newOb["parent"] = ob.get("parent", "")
newOb["phases"] = ob.get("phases", "")
newOb["load_class"] = ob.get("load_class", "")
newOb["nominal_voltage"] = ob.get("nominal_voltage","")
newOb["latitude"] = ob.get("latitude","0")
newOb["longitude"] = ob.get("longitude","0")
try:
oldPow = ob.get("constant_power_A","").replace("j","d")
pythagPower = gridlabd._strClean(oldPow)
newOb["base_power_A"] = "scadaLoads.value*" + str(pythagPower)
except:
pass
try:
oldPow = ob.get("constant_power_B","").replace("j","d")
pythagPower = gridlabd._strClean(oldPow)
newOb["base_power_B"] = "scadaLoads.value*" + str(pythagPower)
except:
pass
try:
oldPow = ob.get("constant_power_C","").replace("j","d")
pythagPower = gridlabd._strClean(oldPow)
newOb["base_power_C"] = "scadaLoads.value*" + str(pythagPower)
except:
pass
tree[key] = newOb
# Convert swing bus to a meter.
for key in tree:
if tree[key].get('bustype','').lower() == 'swing' and tree[key].get('object','') != 'meter':
swingName = tree[key].get('name')
regIndex = key
tree[key]['object'] = 'meter'
# Search for the substation meter and attach a recorder there.
for key in tree:
if tree[key].get('bustype','').lower() == 'swing':
swingName = tree[key].get('name')
recOb = {"object": "recorder",
"parent": swingName,
"property": "measured_real_power,measured_reactive_power,measured_power",
"file": "caliSub.csv",
"interval": "3600"}
outputRecorderKey = maxKey + 3
tree[outputRecorderKey] = recOb
feeder.adjustTime(tree, simLength, simLengthUnits, simStartDate['Date'].strftime("%Y-%m-%d %H:%M:%S"))
# Run Gridlabd, calculate scaling constant.
def runPowerflowIter(tree,scadaSubPower):
'''Runs powerflow once, then iterates.'''
# Run initial powerflow to get power.
print "Starting calibration."
print "Goal of calibration: Error: %s, Iterations: <%s, trim: %s"%(calibrateError[0], calibrateError[1], trim)
output = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=pJoin(workDir,"gridlabD"))
outRealPow = output["caliSub.csv"]["measured_real_power"][trim:simLength]
outImagPower = output["caliSub.csv"]["measured_reactive_power"][trim:simLength]
outAppPowerKw = [(x[0]**2 + x[1]**2)**0.5/1000 for x in zip(outRealPow, outImagPower)]
lastFile = "subScada.player"
nextFile = "subScadaCalibrated.player"
nextPower = outAppPowerKw
error = (sum(outRealPow)/1000-sum(scadaSubPower))/sum(scadaSubPower)
iteration = 1
print "First error:", error
while abs(error)>calibrateError[0] and iteration<calibrateError[1]:
# Run calibration and iterate up to 5 times.
SCAL_CONST = sum(scadaSubPower)/sum(nextPower)
print "Calibrating & running again... Error: %s, Iteration: %s, SCAL_CONST: %s"%(str(round(abs(error*100),6)), str(iteration), round(SCAL_CONST,6))
newPlayData = []
with open(pJoin(pJoin(workDir,"gridlabD"), lastFile), "r") as playerFile:
for line in playerFile:
(key,val) = line.split(',')
newPlayData.append(str(key) + ',' + str(float(val)*SCAL_CONST) + "\n")
with open(pJoin(pJoin(workDir,"gridlabD"), nextFile), "w") as playerFile:
for row in newPlayData:
playerFile.write(row)
tree[playerKey]["file"] = nextFile
tree[outputRecorderKey]["file"] = "caliSubCheck.csv"
nextOutput = gridlabd.runInFilesystem(tree, keepFiles=True, workDir=pJoin(workDir,"gridlabD"))
outRealPowIter = nextOutput["caliSubCheck.csv"]["measured_real_power"][trim:simLength]
outImagPowerIter = nextOutput["caliSubCheck.csv"]["measured_reactive_power"][trim:simLength]
nextAppKw = [(x[0]**2 + x[1]**2)**0.5/1000
for x in zip(outRealPowIter, outImagPowerIter)]
lastFile = nextFile
nextFile = "subScadaCalibrated"+str(iteration)+".player"
nextPower = nextAppKw
# Compute error and iterate.
error = (sum(outRealPowIter)/1000-sum(scadaSubPower))/sum(scadaSubPower)
iteration+=1
else:
if iteration==1: outRealPowIter = outRealPow
SCAL_CONST = 1.0
print "Calibration done: Error: %s, Iteration: %s, SCAL_CONST: %s"%(str(round(abs(error*100),2)), str(iteration), round(SCAL_CONST,2))
return outRealPow, outRealPowIter, lastFile, iteration
outRealPow, outRealPowIter, lastFile, iteration = runPowerflowIter(tree,scadaSubPower[trim:simLength])
caliPowVectors = [[float(element) for element in scadaSubPower[trim:simLength]], [float(element)/1000 for element in outRealPow], [float(element)/1000 for element in outRealPowIter]]
labels = ["scadaSubPower","initialGuess","finalGuess"]
colors = ['red','lightblue','blue']
chartData = {"Title":"Substation Calibration Check (Iterated "+str(iteration+1)+"X)", "fileName":"caliCheckPlot", "colors":colors,"labels":labels, "timeZone":simStartDate['timeZone']}
# Trimming vectors to make them all the same length as the smallest vector
minCaliPowVecLen = min(len(caliPowVectors[0]), len(caliPowVectors[1]), len(caliPowVectors[2]))
caliPowVectors[0] = caliPowVectors[0][:minCaliPowVecLen]
caliPowVectors[1] = caliPowVectors[1][:minCaliPowVecLen]
caliPowVectors[2] = caliPowVectors[2][:minCaliPowVecLen]
print "Len:", len(caliPowVectors[0]), len(caliPowVectors[1]), len(caliPowVectors[2])
plotLine(workDir, caliPowVectors, chartData, simStartDate['Date']+dt.timedelta(hours=trim), simLengthUnits)
# Write the final output.
with open(pJoin(workDir,"calibratedFeeder.omd"),"w") as outJson:
playerString = open(pJoin(pJoin(workDir,"gridlabD"),lastFile)).read()
feederJson["attachments"][lastFile] = playerString
feederJson["tree"] = tree
json.dump(feederJson, outJson, indent=4)
return
def heavyProcessing(modelDir, inputDict):
''' Run the model in its directory. WARNING: GRIDLAB CAN TAKE HOURS TO COMPLETE. '''
print "STARTING TO RUN", modelDir
beginTime = datetime.datetime.now()
# Get feeder name and data in.
try: os.mkdir(pJoin(modelDir,'gldContainer'))
except: pass
try:
feederName = inputDict["feederName1"]
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 attachVolts(workDir, feederPath, voltVectorA, voltVectorB, voltVectorC,
simStartDate, simLength, simLengthUnits):
'''read voltage vectors of 3 different phases, run gridlabd, and attach output to the feeder.'''
try:
timeStamp = [simStartDate['Date']]
for x in range(1, 8760):
timeStamp.append(timeStamp[x - 1] + dt.timedelta(hours=1))
firstDateTime = timeStamp[1]
with open(pJoin(pJoin(workDir, "gridlabD"), "phaseAVoltage.player"),
"w") as voltFile:
for x in range(0, 8760):
timestamp = timeStamp[x]
voltage = str("%0.2f" % float(voltVectorA[x])) + "+0j"
line = timestamp.strftime(
"%Y-%m-%d %H:%M:%S"
) + " " + simStartDate['timeZone'] + "," + str(voltage) + "\n"
voltFile.write(line)
with open(pJoin(pJoin(workDir, "gridlabD"), "phaseBVoltage.player"),
"w") as voltFile:
for x in range(0, 8760):
timestamp = timeStamp[x]
voltage = str("%0.2f" % float(voltVectorB[x])) + "-" + str(
"%0.4f" % float(random.uniform(6449, 6460))) + "j"
line = timestamp.strftime(
"%Y-%m-%d %H:%M:%S"
) + " " + simStartDate['timeZone'] + "," + str(voltage) + "\n"
voltFile.write(line)
with open(pJoin(pJoin(workDir, "gridlabD"), "phaseCVoltage.player"),
"w") as voltFile:
for x in range(0, 8760):
timestamp = timeStamp[x]
voltage = str("%0.2f" % float(voltVectorC[x])) + "+" + str(
"%0.4f" % float(random.uniform(6449, 6460))) + "j"
line = timestamp.strftime(
"%Y-%m-%d %H:%M:%S"
) + " " + simStartDate['timeZone'] + "," + str(voltage) + "\n"
voltFile.write(line)
with open(feederPath, "r") as jsonIn:
feederJson = json.load(jsonIn)
tree = feederJson.get("tree", {})
# Find swingNode name.
for key in tree:
if tree[key].get('bustype', '').lower() == 'swing':
swingName = tree[key].get('name')
# Attach player.
classOb = {'omftype': 'class player', 'argument': '{double value;}'}
voltageObA = {
"object": "player",
"property": "voltage_A",
"file": "phaseAVoltage.player",
"loop": "0",
"parent": swingName
}
voltageObB = {
"object": "player",
"property": "voltage_B",
"file": "phaseBVoltage.player",
"loop": "0",
"parent": swingName
}
voltageObC = {
"object": "player",
"property": "voltage_C",
"file": "phaseCVoltage.player",
"loop": "0",
"parent": swingName
}
maxKey = feeder.getMaxKey(tree)
voltplayerKeyA = maxKey + 2
voltplayerKeyB = maxKey + 3
voltplayerKeyC = maxKey + 4
tree[maxKey + 1] = classOb
tree[voltplayerKeyA] = voltageObA
tree[voltplayerKeyB] = voltageObB
tree[voltplayerKeyC] = voltageObC
# Adjust time and run output.
feeder.adjustTime(tree, simLength, simLengthUnits,
firstDateTime.strftime("%Y-%m-%d %H:%M:%S"))
output = gridlabd.runInFilesystem(tree,
keepFiles=True,
workDir=pJoin(workDir, "gridlabD"))
# Write the output.
with open(pJoin(workDir, "calibratedFeeder.omd"), "w") as outJson:
playerStringA = open(
pJoin(pJoin(workDir, "gridlabD"),
"phaseAVoltage.player")).read()
playerStringB = open(
pJoin(pJoin(workDir, "gridlabD"),
"phaseBVoltage.player")).read()
playerStringC = open(
pJoin(pJoin(workDir, "gridlabD"),
"phaseCVoltage.player")).read()
feederJson["attachments"]["phaseAVoltage.player"] = playerStringA
feederJson["attachments"]["phaseBVoltage.player"] = playerStringB
feederJson["attachments"]["phaseCVoltage.player"] = playerStringC
feederJson["tree"] = tree
json.dump(feederJson, outJson, indent=4)
return pJoin(workDir, "calibratedFeeder.omd"), True
except:
print "Failed to run gridlabD with voltage players."
return "", False
# Delete all climate then reinsert.
reader_name = 'weatherReader'
climate_name = 'MyClimate'
for key in myTree.keys():
obName = myTree[key].get('name','')
obType = myTree[key].get('object','')
if obName in [reader_name, climate_name] or obType is 'climate':
del myTree[key]
oldMax = feeder.getMaxKey(myTree)
myTree[oldMax + 1] = {'omftype':'module', 'argument':'tape'}
myTree[oldMax + 2] = {'omftype':'module', 'argument':'climate'}
myTree[oldMax + 3] = {'object':'csv_reader', 'name':reader_name, 'filename':CSV_NAME}
myTree[oldMax + 4] = {'object':'climate', 'name':climate_name, 'reader': reader_name, 'tmyfile':CSV_NAME}
# Set the time correctly.
feeder.adjustTime(myTree, 240, 'hours', '{}-{}-{}'.format(INIT_TIME.year, INIT_TIME.month, INIT_TIME.day))
# Run here to test.
rawOut = runInFilesystem(myTree, attachments=[], keepFiles=True, workDir='.', glmName='./outFile.glm')
# Write back the full feeder.
# outJson = dict(myFeed)
# with open(CSV_NAME,'r') as weatherFile:
# weatherString = weatherFile.read()
# outJson['attachments']['weatheryearDCA.csv'] = weatherString
# outJson['tree'] = myTree
# try: os.remove('./Orville Tree Pond Calibrated With Weather.json')
# except: pass
# with open('./Orville Tree Pond Calibrated With Weather.json', 'w') as outFile:
# json.dump(outJson, outFile, 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"]
#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 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)
def work(modelDir,inputDict):
'''This reads a glm file, changes the method of powerflow and reruns'''
feederName = [x for x in os.listdir(modelDir) if x.endswith('.omd')][0][:-4]
inputDict['feederName1'] = feederName
feederPath = pJoin(modelDir,feederName+'.omd')
# Reads a pre-calibrated feeder.
outData = {}
with open(feederPath, 'r') as jsonIn:
feederJson = json.load(jsonIn)
localTree = feederJson.get('tree', {})
attachments = feederJson.get('attachments', {})
for key in localTree:
if 'solver_method' in localTree[key].keys():
localTree[key]['solver_method'] = 'FBS'
#find the swing bus and recorder attached to substation
try:
for key in localTree:
if localTree[key].get('bustype','').lower() == 'swing':
swingIndex = key
swingName = localTree[key].get('name')
if localTree[key].get('object','') == 'regulator' and localTree[key].get('from','') == swingName:
regIndex = key
regConfName = localTree[key]['configuration']
except: raise ValueError('Invalid feeder selected:', str(inputDict['feederName1']))
#find the regulator and capacitor names and combine to form a string for volt-var control object
regKeys = []
accum_reg = ''
for key in localTree:
if localTree[key].get('object','') == 'regulator':
accum_reg += localTree[key].get('name','ERROR') + ','
regKeys.append(key)
regstr = accum_reg[:-1]
capKeys = []
accum_cap = ''
for key in localTree:
if localTree[key].get('object','') == 'capacitor':
accum_cap += localTree[key].get('name','ERROR') + ','
capKeys.append(key)
if localTree[key].get('control','').lower() == 'manual':
localTree[key]['control'] = 'VOLT'
capstr = accum_cap[:-1]
# Attach recorders relevant to CVR.
recorders = [
{'object': 'collector',
'file': 'ZlossesTransformer.csv',
'group': 'class=transformer',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesUnderground.csv',
'group': 'class=underground_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesOverhead.csv',
'group': 'class=overhead_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'recorder',
'file': 'Zregulator.csv',
'limit': '0',
'parent': localTree[regIndex]['name'],
'property': 'tap_A,tap_B,tap_C,power_in.real,power_in.imag'},
{'object': 'collector',
'file': 'ZvoltageJiggle.csv',
'group': 'class=triplex_meter',
'limit': '0',
'property': 'min(voltage_12.mag),mean(voltage_12.mag),max(voltage_12.mag),std(voltage_12.mag)'},
{'object': 'recorder',
'file': 'ZsubstationTop.csv',
'limit': '0',
'parent': localTree[swingIndex]['name'],
'property': 'voltage_A,voltage_B,voltage_C'},
{'object': 'recorder',
'file': 'ZsubstationBottom.csv',
'limit': '0',
'parent': localTree[regIndex]['to'],
'property': 'voltage_A,voltage_B,voltage_C'}]
#recorder object for capacitor switching - if capacitors exist
if capKeys != []:
for key in capKeys:
recorders.append({'object': 'recorder',
'file': 'ZcapSwitch' + str(key) + '.csv',
'limit': '0',
'parent': localTree[key]['name'],
'property': 'switchA,switchB,switchC'})
#attach recorder process
biggest = 1 + max([int(k) for k in localTree.keys()])
for index, rec in enumerate(recorders):
localTree[biggest + index] = rec
#run a reference load flow
HOURS = float(inputDict['simLengthHours'])
simStartDate = inputDict['simStart']
feeder.adjustTime(localTree,HOURS,'hours',simStartDate)
output = gridlabd.runInFilesystem(localTree, attachments, keepFiles=False,workDir=modelDir)
try: os.remove(pJoin(modelDir,'PID.txt'))
except: pass
p = output['Zregulator.csv']['power_in.real']
q = output['Zregulator.csv']['power_in.imag']
#calculating length of simulation because it migth be different from the simulation input HOURS
simRealLength = int(len(p))
#time delays from configuration files
time_delay_reg = '30.0'
time_delay_cap = '300.0'
for key in localTree:
if localTree[key].get('object','') == 'regulator_configuration':
time_delay_reg = localTree[key]['time_delay']
# if localTree[key].get('object','') == "capacitor":
# time_delay_cap = localTree[key]['time_delay']
#change the recorder names
for key in localTree:
if localTree[key].get('object','') == 'collector' or localTree[key].get('object','') == 'recorder':
if localTree[key].get('file','').startswith('Z'):
localTree[key]['file'] = localTree[key].get('file','').replace('Z','NewZ')
#create volt-var control object
max_key = max([int(key) for key in localTree.keys()])
localTree[max_key+1] = {'object' : 'volt_var_control',
'name' : 'IVVC1',
'control_method' : 'ACTIVE',
'capacitor_delay' : str(time_delay_cap),
'regulator_delay' : str(time_delay_reg),
'desired_pf' : '0.99',
'd_max' : '0.6',
'd_min' : '0.1',
'substation_link' : str(localTree[regIndex]['name']),
'regulator_list' : regstr,
'capacitor_list': capstr,
'voltage_measurements': str(inputDict.get('voltageNodes', 'IVVC1')),
}
#running powerflow analysis via gridalab after attaching a regulator
feeder.adjustTime(localTree,HOURS,'hours',simStartDate)
output1 = gridlabd.runInFilesystem(localTree,attachments,keepFiles=True,workDir=modelDir)
os.remove(pJoin(modelDir,'PID.txt'))
pnew = output1['NewZregulator.csv']['power_in.real']
qnew = output1['NewZregulator.csv']['power_in.imag']
#total real and imaginary losses as a function of time
def vecSum(u,v):
''' Add vectors u and v element-wise. Return has len <= len(u) and <=len(v). '''
return map(sum, zip(u,v))
def zeroVec(length):
''' Give a zero vector of input length. '''
return [0 for x in xrange(length)]
(realLoss, imagLoss, realLossnew, imagLossnew) = (zeroVec(int(HOURS)) for x in range(4))
for device in ['ZlossesOverhead.csv','ZlossesTransformer.csv','ZlossesUnderground.csv']:
for letter in ['A','B','C']:
realLoss = vecSum(realLoss, output[device]['sum(power_losses_' + letter + '.real)'])
imagLoss = vecSum(imagLoss, output[device]['sum(power_losses_' + letter + '.imag)'])
realLossnew = vecSum(realLossnew, output1['New'+device]['sum(power_losses_' + letter + '.real)'])
imagLossnew = vecSum(imagLossnew, output1['New'+device]['sum(power_losses_' + letter + '.imag)'])
#voltage calculations and tap calculations
def divby2(u):
'''divides by 2'''
return u/2
lowVoltage = []
meanVoltage = []
highVoltage = []
lowVoltagenew = []
meanVoltagenew = []
highVoltagenew = []
tap = {'A':[],'B':[],'C':[]}
tapnew = {'A':[],'B':[],'C':[]}
volt = {'A':[],'B':[],'C':[]}
voltnew = {'A':[],'B':[],'C':[]}
switch = {'A':[],'B':[],'C':[]}
switchnew = {'A':[],'B':[],'C':[]}
for letter in ['A','B','C']:
tap[letter] = output['Zregulator.csv']['tap_' + letter]
tapnew[letter] = output1['NewZregulator.csv']['tap_' + letter]
if capKeys != []:
switch[letter] = output['ZcapSwitch' + str(int(capKeys[0])) + '.csv']['switch'+ letter]
switchnew[letter] = output1['NewZcapSwitch' + str(int(capKeys[0])) + '.csv']['switch'+ letter]
volt[letter] = map(returnMag,output['ZsubstationBottom.csv']['voltage_'+letter])
voltnew[letter] = map(returnMag,output1['NewZsubstationBottom.csv']['voltage_'+letter])
lowVoltage = map(divby2,output['ZvoltageJiggle.csv']['min(voltage_12.mag)'])
lowVoltagenew = map(divby2,output1['NewZvoltageJiggle.csv']['min(voltage_12.mag)'])
meanVoltage = map(divby2,output['ZvoltageJiggle.csv']['mean(voltage_12.mag)'])
meanVoltagenew = map(divby2,output1['NewZvoltageJiggle.csv']['mean(voltage_12.mag)'])
highVoltage = map(divby2,output['ZvoltageJiggle.csv']['max(voltage_12.mag)'])
highVoltagenew = map(divby2,output1['NewZvoltageJiggle.csv']['max(voltage_12.mag)'])
#energy calculations
whEnergy = []
whLosses = []
whLoads = []
whEnergy.append(sum(p)/10**6)
whLosses.append(sum(realLoss)/10**6)
whLoads.append((sum(p)-sum(realLoss))/10**6)
whEnergy.append(sum(pnew)/10**6)
whLosses.append(sum(realLossnew)/10**6)
whLoads.append((sum(pnew)-sum(realLossnew))/10**6)
indices = ['No IVVC', 'With IVVC']
# energySalesRed = (whLoads[1]-whLoads[0])*(inputDict['wholesaleEnergyCostPerKwh'])*1000
# lossSav = (whLosses[0]-whLosses[1])*inputDict['wholesaleEnergyCostPerKwh']*1000
#plots
ticks = []
plt.clf()
plt.title('total energy')
plt.ylabel('total load and losses (MWh)')
for element in range(2):
ticks.append(element)
bar_loss = plt.bar(element, whLosses[element], 0.15, color= 'red')
bar_load = plt.bar(element+0.15, whLoads[element], 0.15, color= 'orange')
plt.legend([bar_load[0],bar_loss[0]],['total load', 'total losses'],bbox_to_anchor=(0., 0.915, 1., .102), loc=3,
ncol=2, mode='expand', borderaxespad=0.1)
plt.xticks([t+0.15 for t in ticks],indices)
plt.savefig(pJoin(modelDir,'totalEnergy.png'))
#real and imaginary power
plt.figure('real power')
plt.title('Real Power at substation')
plt.ylabel('substation real power (MW)')
pMW = [element/10**6 for element in p]
pMWn = [element/10**6 for element in pnew]
pw = plt.plot(pMW)
npw = plt.plot(pMWn)
plt.legend([pw[0], npw[0]], ['NO IVVC','WITH IVVC'],bbox_to_anchor=(0., 0.915, 1., .102), loc=3,
ncol=2, mode='expand', borderaxespad=0.1)
plt.savefig(pJoin(modelDir,'realPower.png'))
plt.figure('Reactive power')
plt.title('Reactive Power at substation')
plt.ylabel('substation reactive power (MVAR)')
qMVAR = [element/10**6 for element in q]
qMVARn = [element/10**6 for element in qnew]
iw = plt.plot(qMVAR)
niw = plt.plot(qMVARn)
plt.legend([iw[0], niw[0]], ['NO IVVC','WITH IVVC'],bbox_to_anchor=(0., 0.915, 1., .102), loc=3,
ncol=2, mode='expand', borderaxespad=0.1)
plt.savefig(pJoin(modelDir,'imaginaryPower.png'))
#voltage plots
plt.figure('voltages as a function of time')
f,ax = plt.subplots(2,sharex=True)
f.suptitle('Min and Max voltages on the feeder')
lv = ax[0].plot(lowVoltage,color = 'cadetblue')
mv = ax[0].plot(meanVoltage,color = 'blue')
hv = ax[0].plot(highVoltage, color = 'cadetblue')
ax[0].legend([lv[0], mv[0], hv[0]], ['low voltage','mean voltage','high voltage'],bbox_to_anchor=(0., 0.915, 1., .1), loc=3,
ncol=3, mode='expand', borderaxespad=0.1)
ax[0].set_ylabel('NO IVVC')
nlv = ax[1].plot(lowVoltagenew,color = 'cadetblue')
nmv = ax[1].plot(meanVoltagenew,color = 'blue')
nhv = ax[1].plot(highVoltagenew, color = 'cadetblue')
ax[1].set_ylabel('WITH IVVC')
plt.savefig(pJoin(modelDir,'Voltages.png'))
#tap positions
plt.figure('TAP positions NO IVVC')
f,ax = plt.subplots(6,sharex=True)
f.set_size_inches(10,12.0)
#f.suptitle("Regulator Tap positions")
ax[0].plot(tap['A'])
ax[0].set_title('Regulator Tap positions NO IVVC')
ax[0].set_ylabel('TAP A')
ax[1].plot(tap['B'])
ax[1].set_ylabel('TAP B')
ax[2].plot(tap['C'])
ax[2].set_ylabel('TAP C')
ax[3].plot(tapnew['A'])
ax[3].set_title('WITH IVVC')
ax[3].set_ylabel('TAP A')
ax[4].plot(tapnew['B'])
ax[4].set_ylabel('TAP B')
ax[5].plot(tapnew['C'])
ax[5].set_ylabel('TAP C')
for subplot in range(6):
ax[subplot].set_ylim(-20,20)
f.tight_layout()
plt.savefig(pJoin(modelDir,'RegulatorTAPpositions.png'))
#substation voltages
plt.figure('substation voltage as a function of time')
f,ax = plt.subplots(6,sharex=True)
f.set_size_inches(10,12.0)
#f.suptitle("voltages at substation NO IVVC")
ax[0].plot(volt['A'])
ax[0].set_title('Substation voltages NO IVVC')
ax[0].set_ylabel('voltage A')
ax[1].plot(volt['B'])
ax[1].set_ylabel('voltage B')
ax[2].plot(volt['C'])
ax[2].set_ylabel('voltage C')
ax[3].plot(voltnew['A'])
ax[3].set_title('WITH IVVC')
ax[3].set_ylabel('voltage A')
ax[4].plot(voltnew['B'])
ax[4].set_ylabel('voltage B')
ax[5].plot(voltnew['C'])
ax[5].set_ylabel('voltage C')
f.tight_layout()
plt.savefig(pJoin(modelDir,'substationVoltages.png'))
#cap switches
plt.figure('capacitor switch state as a function of time')
f,ax = plt.subplots(6,sharex=True)
f.set_size_inches(10,12.0)
#f.suptitle("Capacitor switch state NO IVVC")
ax[0].plot(switch['A'])
ax[0].set_title('Capacitor switch state NO IVVC')
ax[0].set_ylabel('switch A')
ax[1].plot(switch['B'])
ax[1].set_ylabel('switch B')
ax[2].plot(switch['C'])
ax[2].set_ylabel('switch C')
ax[3].plot(switchnew['A'])
ax[3].set_title('WITH IVVC')
ax[3].set_ylabel('switch A')
ax[4].plot(switchnew['B'])
ax[4].set_ylabel('switch B')
ax[5].plot(switchnew['C'])
ax[5].set_ylabel('switch C')
for subplot in range(6):
ax[subplot].set_ylim(-2,2)
f.tight_layout()
plt.savefig(pJoin(modelDir,'capacitorSwitch.png'))
#plt.show()
#monetization
monthNames = ['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August',
'September', 'October', 'November', 'December']
monthToSeason = {'January':'Winter','February':'Winter','March':'Spring','April':'Spring',
'May':'Spring','June':'Summer','July':'Summer','August':'Summer',
'September':'Fall','October':'Fall','November':'Fall','December':'Winter'}
#calculate the month and hour of simulation start and month and hour of simulation end
simStartTimestamp = simStartDate + ' 00:00:00'
simFormattedDate = dt.strptime(simStartTimestamp,'%Y-%m-%d %H:%M:%S')
simStartMonthNum = int(simFormattedDate.strftime('%m'))
simstartMonth = monthNames[simStartMonthNum-1]
simStartDay = int(simFormattedDate.strftime('%d'))
if calendar.isleap(int(simFormattedDate.strftime('%Y'))):
febDays = 29
else:
febDays = 28
monthHours = [int(31*24),int(febDays*24),int(31*24),int(30*24),int(31*24),int(30*24),int(31*24),int(31*24),int(30*24),int(31*24),int(30*24),int(31*24)]
simStartIndex = int(sum(monthHours[:(simStartMonthNum-1)])+(simStartDay-1)*24)
temp = 0
cumulHours = [0]
for x in range(12):
temp += monthHours[x]
cumulHours.append(temp)
for i in range((simStartMonthNum),13):
if int(simStartIndex+simRealLength)<=cumulHours[i] and int(simStartIndex+simRealLength)>cumulHours[i-1]:
simEndMonthNum = i-1
simEndMonth = monthNames[simEndMonthNum]
#calculate peaks for the number of months in simulation
previndex = 0
monthPeak = {}
monthPeakNew = {}
peakSaveDollars = {}
energyLostDollars = {}
lossRedDollars = {}
simMonthList = monthNames[monthNames.index(simstartMonth):(monthNames.index(simEndMonth)+1)]
for monthElement in simMonthList:
month = monthNames.index(monthElement)
index1 = int(previndex)
index2 = int(min((index1 + int(monthHours[month])), simRealLength))
monthPeak[monthElement] = max(p[index1:index2])/1000.0
monthPeakNew[monthElement] = max(pnew[index1:index2])/1000.0
peakSaveDollars[monthElement] = (monthPeak[monthElement]-monthPeakNew[monthElement])*float(inputDict['peakDemandCost'+str(monthToSeason[monthElement])+'PerKw'])
lossRedDollars[monthElement] = (sum(realLoss[index1:index2])/1000.0 - sum(realLossnew[index1:index2])/1000.0)*(float(inputDict['wholesaleEnergyCostPerKwh']))
energyLostDollars[monthElement] = (sum(p[index1:index2])/1000.0 - sum(pnew[index1:index2])/1000.0 - sum(realLoss[index1:index2])/1000.0
+ sum(realLossnew[index1:index2])/1000.0 )*(float(inputDict['wholesaleEnergyCostPerKwh']) - float(inputDict['retailEnergyCostPerKwh']))
previndex = index2
#money charts
fig = plt.figure('cost benefit barchart',figsize=(10,8))
ticks = range(len(simMonthList))
ticks1 = [element+0.15 for element in ticks]
ticks2 = [element+0.30 for element in ticks]
eld = [energyLostDollars[month] for month in simMonthList]
lrd = [lossRedDollars[month] for month in simMonthList]
psd = [peakSaveDollars[month] for month in simMonthList]
bar_eld = plt.bar(ticks,eld,0.15,color='red')
bar_psd = plt.bar(ticks1,psd,0.15,color='blue')
bar_lrd = plt.bar(ticks2,lrd,0.15,color='green')
plt.legend([bar_eld[0], bar_psd[0], bar_lrd[0]], ['energyLostDollars','peakReductionDollars','lossReductionDollars'],bbox_to_anchor=(0., 1.015, 1., .102), loc=3,
ncol=2, mode='expand', borderaxespad=0.1)
monShort = [element[0:3] for element in simMonthList]
plt.xticks([t+0.15 for t in ticks],monShort)
plt.ylabel('Utility Savings ($)')
plt.savefig(pJoin(modelDir,'spendChart.png'))
#cumulative savings graphs
fig = plt.figure('cost benefit barchart',figsize=(10,5))
annualSavings = sum(eld) + sum(lrd) + sum(psd)
annualSave = lambda x:(annualSavings - float(inputDict['omCost'])) * x - float(inputDict['capitalCost'])
simplePayback = float(inputDict['capitalCost'])/(annualSavings - float(inputDict['omCost']))
plt.xlabel('Year After Installation')
plt.xlim(0,30)
plt.ylabel('Cumulative Savings ($)')
plt.plot([0 for x in range(31)],c='gray')
plt.axvline(x=simplePayback, ymin=0, ymax=1, c='gray', linestyle='--')
plt.plot([annualSave(x) for x in range(31)], c='green')
plt.savefig(pJoin(modelDir,'savingsChart.png'))
#get exact time stamps from the CSV files generated by Gridlab-D
timeWithZone = output['Zregulator.csv']['# timestamp']
timestamps = [element[:19] for element in timeWithZone]
#data for highcharts
outData['timeStamps'] = timestamps
outData['noCVRPower'] = p
outData['withCVRPower'] = pnew
outData['noCVRLoad'] = whLoads[0]
outData['withCVRLoad'] = whLoads[1]
outData['noCVRLosses'] = whLosses[0]
outData['withCVRLosses'] = whLosses[1]
outData['noCVRTaps'] = tap
outData['withCVRTaps'] = tapnew
outData['noCVRSubVolts'] = volt
outData['withCVRSubVolts'] = voltnew
outData['noCVRCapSwitch'] = switch
outData['withCVRCapSwitch'] = switchnew
outData['noCVRHighVolt'] = highVoltage
outData['withCVRHighVolt'] = highVoltagenew
outData['noCVRLowVolt'] = lowVoltage
outData['withCVRLowVolt'] = lowVoltagenew
outData['noCVRMeanVolt'] = meanVoltage
outData['withCVRMeanVolt'] = meanVoltagenew
#monetization
outData['simMonthList'] = monShort
outData['energyLostDollars'] = energyLostDollars
outData['lossRedDollars'] = lossRedDollars
outData['peakSaveDollars'] = peakSaveDollars
outData['annualSave'] = [annualSave(x) for x in range(31)]
# Generate warnings
#TODO: Timezone adjustment
try:
# Check if times for simulation and scada match.
scadaDates = []
with open(pJoin(modelDir,'subScadaCalibrated1.player'),'r') as scadaFile:
for line in scadaFile:
(date,val) = line.split(',')
scadaDates.append(str(date))
simFormattedEndDate = simFormattedDate + timedelta(hours=HOURS)
scadaStartDate = dt.strptime(scadaDates[0].split(' PST')[0],"%Y-%m-%d %H:%M:%S")
scadaEndDate = dt.strptime(scadaDates[len(scadaDates)-1].split(' PST')[0],"%Y-%m-%d %H:%M:%S")
beginRange = (scadaStartDate - simFormattedDate).total_seconds()
endRange = (scadaEndDate - simFormattedEndDate).total_seconds()
# Check if houses exist.
housesExist, voltageNodeExists = False, False
for key in localTree:
if localTree[key].get('object','') == 'house': housesExist = True
if localTree[key].get('name','') == str(inputDict.get('voltageNodes', 0)): voltageNodeExists = True
if (beginRange > 0.0 or endRange < 0.0) and not housesExist:
outData['warnings'] = '<strong>WARNING:</strong> The simulation dates entered are not compatible with the scada curve in the feeder.'
# Check if voltage node exists.
if not voltageNodeExists:
if outData.get('warnings','') != '':
previousWarning = outData['warnings']
outData['warnings'] = previousWarning + ' The voltage node: ' + str(inputDict.get('voltageNodes', 0)) + ' does not exist in the feeder.'
else: outData['warnings'] = '<strong>WARNING:</strong> The voltage node <i>' + str(inputDict.get('voltageNodes', 0)) + '</i> does not exist in the feeder.'
except:
pass
# # Update the runTime in the input file.
# endTime = dt.now()
# with open(pJoin(modelDir,"allInputData.json"),"w") as inFile:
# json.dump(inputDict, inFile, indent=4)
# with open(pJoin(modelDir,"outDataData.json"),"w") as outFile:
# json.dump(outData, outFile, indent=4)
# # For autotest, there won't be such file.
# try:
# os.remove(pJoin(modelDir, "PPID.txt"))
# except Exception, e:
# pass
return outData
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, inData, fs):
'''This reads a glm file, changes the method of powerflow and reruns'''
try:
startTime = datetime.now()
# calibrate and run cvrdynamic
feederPath = pJoin("data", "Feeder", inData[
"feederName"].split("___")[0], inData["feederName"].split("___")[1] + '.json')
fs.export_from_fs_to_local(feederPath, feederPath)
scadaPath = pJoin("uploads", (inData["scadaFile"] + '.tsv'))
fs.export_from_fs_to_local(scadaPath, scadaPath)
omf.calibrate.omfCalibrate(modelDir, feederPath, scadaPath)
allOutput = {}
print "here"
with open(pJoin(modelDir, "calibratedFeeder.json"), "r") as jsonIn:
feederJson = json.load(jsonIn)
localTree = feederJson.get("tree", {})
for key in localTree:
if "solver_method" in localTree[key].keys():
print "current solver method", localTree[key]["solver_method"]
localTree[key]["solver_method"] = 'FBS'
# find the swing bus and recorder attached to substation
for key in localTree:
if localTree[key].get('bustype', '').lower() == 'swing':
swingIndex = key
swingName = localTree[key].get('name')
if localTree[key].get('object', '') == 'regulator' and localTree[key].get('from', '') == swingName:
regIndex = key
regConfName = localTree[key]['configuration']
# find the regulator and capacitor names and combine to form a string
# for volt-var control object
regKeys = []
accum_reg = ""
for key in localTree:
if localTree[key].get("object", "") == "regulator":
accum_reg += localTree[key].get("name", "ERROR") + ","
regKeys.append(key)
regstr = accum_reg[:-1]
print regKeys
capKeys = []
accum_cap = ""
for key in localTree:
if localTree[key].get("object", "") == "capacitor":
accum_cap += localTree[key].get("name", "ERROR") + ","
capKeys.append(key)
if localTree[key].get("control", "").lower() == "manual":
localTree[key]['control'] = "VOLT"
print "changing capacitor control from manual to volt"
capstr = accum_cap[:-1]
print capKeys
# Attach recorders relevant to CVR.
recorders = [
{'object': 'collector',
'file': 'ZlossesTransformer.csv',
'group': 'class=transformer',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesUnderground.csv',
'group': 'class=underground_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'collector',
'file': 'ZlossesOverhead.csv',
'group': 'class=overhead_line',
'limit': '0',
'property': 'sum(power_losses_A.real),sum(power_losses_A.imag),sum(power_losses_B.real),sum(power_losses_B.imag),sum(power_losses_C.real),sum(power_losses_C.imag)'},
{'object': 'recorder',
'file': 'Zregulator.csv',
'limit': '0',
'parent': localTree[regIndex]['name'],
'property': 'tap_A,tap_B,tap_C,power_in.real,power_in.imag'},
{'object': 'collector',
'file': 'ZvoltageJiggle.csv',
'group': 'class=triplex_meter',
'limit': '0',
'property': 'min(voltage_12.mag),mean(voltage_12.mag),max(voltage_12.mag),std(voltage_12.mag)'},
{'object': 'recorder',
'file': 'ZsubstationTop.csv',
'limit': '0',
'parent': localTree[swingIndex]['name'],
'property': 'voltage_A,voltage_B,voltage_C'},
{'object': 'recorder',
'file': 'ZsubstationBottom.csv',
'limit': '0',
'parent': localTree[regIndex]['to'],
'property': 'voltage_A,voltage_B,voltage_C'}]
# recorder object for capacitor switching - if capacitors exist
if capKeys != []:
for key in capKeys:
recorders.append({'object': 'recorder',
'file': 'ZcapSwitch' + str(key) + '.csv',
'limit': '0',
'parent': localTree[key]['name'],
'property': 'switchA,switchB,switchC'})
# attach recorder process
biggest = 1 + max([int(k) for k in localTree.keys()])
for index, rec in enumerate(recorders):
localTree[biggest + index] = rec
# run a reference load flow
HOURS = float(inData['simLengthHours'])
simStartDate = inData['simStart']
feeder.adjustTime(localTree, HOURS, "hours", simStartDate)
output = gridlabd.runInFilesystem(
localTree, keepFiles=False, workDir=modelDir)
os.remove(pJoin(modelDir, "PID.txt"))
p = output['Zregulator.csv']['power_in.real']
q = output['Zregulator.csv']['power_in.imag']
# calculating length of simulation because it migth be different from
# the simulation input HOURS
simRealLength = int(len(p))
# time delays from configuration files
time_delay_reg = '30.0'
time_delay_cap = '300.0'
for key in localTree:
if localTree[key].get('object', '') == "regulator_configuration":
time_delay_reg = localTree[key]['time_delay']
print "time_delay_reg", time_delay_reg
# if localTree[key].get('object','') == "capacitor":
# time_delay_cap = localTree[key]['time_delay']
# print "time_delay_cap",time_delay_cap
# change the recorder names
for key in localTree:
if localTree[key].get('object', '') == "collector" or localTree[key].get('object', '') == "recorder":
if localTree[key].get('file', '').startswith('Z'):
localTree[key]['file'] = localTree[key].get(
'file', '').replace('Z', 'NewZ')
# create volt-var control object
max_key = max([int(key) for key in localTree.keys()])
print max_key
localTree[max_key + 1] = {'object': 'volt_var_control',
'name': 'IVVC1',
'control_method': 'ACTIVE',
'capacitor_delay': str(time_delay_cap),
'regulator_delay': str(time_delay_reg),
'desired_pf': '0.99',
'd_max': '0.6',
'd_min': '0.1',
'substation_link': str(localTree[regIndex]['name']),
'regulator_list': regstr,
'capacitor_list': capstr}
# running powerflow analysis via gridalab after attaching a regulator
feeder.adjustTime(localTree, HOURS, "hours", simStartDate)
output1 = gridlabd.runInFilesystem(
localTree, keepFiles=True, workDir=modelDir)
os.remove(pJoin(modelDir, "PID.txt"))
pnew = output1['NewZregulator.csv']['power_in.real']
qnew = output1['NewZregulator.csv']['power_in.imag']
# total real and imaginary losses as a function of time
def vecSum(u, v):
''' Add vectors u and v element-wise. Return has len <= len(u) and <=len(v). '''
return map(sum, zip(u, v))
def zeroVec(length):
''' Give a zero vector of input length. '''
return [0 for x in xrange(length)]
(realLoss, imagLoss, realLossnew, imagLossnew) = (zeroVec(int(HOURS))
for x in range(4))
for device in ['ZlossesOverhead.csv', 'ZlossesTransformer.csv', 'ZlossesUnderground.csv']:
for letter in ['A', 'B', 'C']:
realLoss = vecSum(
realLoss, output[device]['sum(power_losses_' + letter + '.real)'])
imagLoss = vecSum(
imagLoss, output[device]['sum(power_losses_' + letter + '.imag)'])
realLossnew = vecSum(
realLossnew, output1['New' + device]['sum(power_losses_' + letter + '.real)'])
imagLossnew = vecSum(
imagLossnew, output1['New' + device]['sum(power_losses_' + letter + '.imag)'])
# voltage calculations and tap calculations
def divby2(u):
'''divides by 2'''
return u / 2
lowVoltage = []
meanVoltage = []
highVoltage = []
lowVoltagenew = []
meanVoltagenew = []
highVoltagenew = []
tap = {'A': [], 'B': [], 'C': []}
tapnew = {'A': [], 'B': [], 'C': []}
volt = {'A': [], 'B': [], 'C': []}
voltnew = {'A': [], 'B': [], 'C': []}
switch = {'A': [], 'B': [], 'C': []}
switchnew = {'A': [], 'B': [], 'C': []}
for letter in ['A', 'B', 'C']:
tap[letter] = output['Zregulator.csv']['tap_' + letter]
tapnew[letter] = output1['NewZregulator.csv']['tap_' + letter]
if capKeys != []:
switch[letter] = output[
'ZcapSwitch' + str(int(capKeys[0])) + '.csv']['switch' + letter]
switchnew[letter] = output1[
'NewZcapSwitch' + str(int(capKeys[0])) + '.csv']['switch' + letter]
volt[letter] = map(
returnMag, output['ZsubstationBottom.csv']['voltage_' + letter])
voltnew[letter] = map(
returnMag, output1['NewZsubstationBottom.csv']['voltage_' + letter])
lowVoltage = map(
divby2, output['ZvoltageJiggle.csv']['min(voltage_12.mag)'])
lowVoltagenew = map(
divby2, output1['NewZvoltageJiggle.csv']['min(voltage_12.mag)'])
meanVoltage = map(
divby2, output['ZvoltageJiggle.csv']['mean(voltage_12.mag)'])
meanVoltagenew = map(
divby2, output1['NewZvoltageJiggle.csv']['mean(voltage_12.mag)'])
highVoltage = map(
divby2, output['ZvoltageJiggle.csv']['max(voltage_12.mag)'])
highVoltagenew = map(
divby2, output1['NewZvoltageJiggle.csv']['max(voltage_12.mag)'])
# energy calculations
whEnergy = []
whLosses = []
whLoads = []
whEnergy.append(sum(p) / 10**6)
whLosses.append(sum(realLoss) / 10**6)
whLoads.append((sum(p) - sum(realLoss)) / 10**6)
whEnergy.append(sum(pnew) / 10**6)
whLosses.append(sum(realLossnew) / 10**6)
whLoads.append((sum(pnew) - sum(realLossnew)) / 10**6)
indices = ['No IVVC', 'With IVVC']
# energySalesRed = (whLoads[1]-whLoads[0])*(inData['wholesaleEnergyCostPerKwh'])*1000
# lossSav = (whLosses[0]-whLosses[1])*inData['wholesaleEnergyCostPerKwh']*1000
# print energySalesRed, lossSav
# plots
ticks = []
plt.clf()
plt.title("total energy")
plt.ylabel("total load and losses (MWh)")
for element in range(2):
ticks.append(element)
bar_loss = plt.bar(element, whLosses[element], 0.15, color='red')
bar_load = plt.bar(
element + 0.15, whLoads[element], 0.15, color='orange')
plt.legend([bar_load[0], bar_loss[0]], ['total load', 'total losses'], bbox_to_anchor=(0., 0.915, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
plt.xticks([t + 0.15 for t in ticks], indices)
Plot.save_fig(plt, pJoin(modelDir, "totalEnergy.png"))
# real and imaginary power
plt.figure("real power")
plt.title("Real Power at substation")
plt.ylabel("substation real power (MW)")
pMW = [element / 10**6 for element in p]
pMWn = [element / 10**6 for element in pnew]
pw = plt.plot(pMW)
npw = plt.plot(pMWn)
plt.legend([pw[0], npw[0]], ['NO IVVC', 'WITH IVVC'], bbox_to_anchor=(0., 0.915, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
Plot.save_fig(plt, pJoin(modelDir, "realPower.png"))
plt.figure("Reactive power")
plt.title("Reactive Power at substation")
plt.ylabel("substation reactive power (MVAR)")
qMVAR = [element / 10**6 for element in q]
qMVARn = [element / 10**6 for element in qnew]
iw = plt.plot(qMVAR)
niw = plt.plot(qMVARn)
plt.legend([iw[0], niw[0]], ['NO IVVC', 'WITH IVVC'], bbox_to_anchor=(0., 0.915, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
Plot.save_fig(plt, pJoin(modelDir, "imaginaryPower.png"))
# voltage plots
plt.figure("voltages as a function of time")
f, ax = plt.subplots(2, sharex=True)
f.suptitle("Min and Max voltages on the feeder")
lv = ax[0].plot(lowVoltage, color='cadetblue')
mv = ax[0].plot(meanVoltage, color='blue')
hv = ax[0].plot(highVoltage, color='cadetblue')
ax[0].legend([lv[0], mv[0], hv[0]], ['low voltage', 'mean voltage', 'high voltage'], bbox_to_anchor=(0., 0.915, 1., .1), loc=3,
ncol=3, mode="expand", borderaxespad=0.1)
ax[0].set_ylabel('NO IVVC')
nlv = ax[1].plot(lowVoltagenew, color='cadetblue')
nmv = ax[1].plot(meanVoltagenew, color='blue')
nhv = ax[1].plot(highVoltagenew, color='cadetblue')
ax[1].set_ylabel('WITH IVVC')
Plot.save_fig(plt, pJoin(modelDir, "Voltages.png"))
# tap positions
plt.figure("TAP positions NO IVVC")
f, ax = plt.subplots(6, sharex=True)
f.set_size_inches(10, 12.0)
#f.suptitle("Regulator Tap positions")
ax[0].plot(tap['A'])
ax[0].set_title("Regulator Tap positions NO IVVC")
ax[0].set_ylabel("TAP A")
ax[1].plot(tap['B'])
ax[1].set_ylabel("TAP B")
ax[2].plot(tap['C'])
ax[2].set_ylabel("TAP C")
ax[3].plot(tapnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel("TAP A")
ax[4].plot(tapnew['B'])
ax[4].set_ylabel("TAP B")
ax[5].plot(tapnew['C'])
ax[5].set_ylabel("TAP C")
for subplot in range(6):
ax[subplot].set_ylim(-20, 20)
f.tight_layout()
Plot.save_fig(plt, pJoin(modelDir, "RegulatorTAPpositions.png"))
# substation voltages
plt.figure("substation voltage as a function of time")
f, ax = plt.subplots(6, sharex=True)
f.set_size_inches(10, 12.0)
#f.suptitle("voltages at substation NO IVVC")
ax[0].plot(volt['A'])
ax[0].set_title('Substation voltages NO IVVC')
ax[0].set_ylabel('voltage A')
ax[1].plot(volt['B'])
ax[1].set_ylabel('voltage B')
ax[2].plot(volt['C'])
ax[2].set_ylabel('voltage C')
ax[3].plot(voltnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel('voltage A')
ax[4].plot(voltnew['B'])
ax[4].set_ylabel('voltage B')
ax[5].plot(voltnew['C'])
ax[5].set_ylabel('voltage C')
f.tight_layout()
Plot.save_fig(plt, pJoin(modelDir, "substationVoltages.png"))
# cap switches
plt.figure("capacitor switch state as a function of time")
f, ax = plt.subplots(6, sharex=True)
f.set_size_inches(10, 12.0)
#f.suptitle("Capacitor switch state NO IVVC")
ax[0].plot(switch['A'])
ax[0].set_title("Capacitor switch state NO IVVC")
ax[0].set_ylabel("switch A")
ax[1].plot(switch['B'])
ax[1].set_ylabel("switch B")
ax[2].plot(switch['C'])
ax[2].set_ylabel("switch C")
ax[3].plot(switchnew['A'])
ax[3].set_title("WITH IVVC")
ax[3].set_ylabel("switch A")
ax[4].plot(switchnew['B'])
ax[4].set_ylabel("switch B")
ax[5].plot(switchnew['C'])
ax[5].set_ylabel("switch C")
for subplot in range(6):
ax[subplot].set_ylim(-2, 2)
f.tight_layout()
Plot.save_fig(plt, pJoin(modelDir, "capacitorSwitch.png"))
# plt.show()
# monetization
monthNames = ["January", "February", "March", "April", "May", "June", "July", "August",
"September", "October", "November", "December"]
monthToSeason = {'January': 'Winter', 'February': 'Winter', 'March': 'Spring', 'April': 'Spring',
'May': 'Spring', 'June': 'Summer', 'July': 'Summer', 'August': 'Summer',
'September': 'Fall', 'October': 'Fall', 'November': 'Fall', 'December': 'Winter'}
# calculate the month and hour of simulation start and month and hour
# of simulation end
simStartTimestamp = simStartDate + " 00:00:00"
simFormattedDate = datetime.strptime(
simStartTimestamp, "%Y-%m-%d %H:%M:%S")
simStartMonthNum = int(simFormattedDate.strftime('%m'))
simstartMonth = monthNames[simStartMonthNum - 1]
simStartDay = int(simFormattedDate.strftime('%d'))
if calendar.isleap(int(simFormattedDate.strftime('%Y'))):
febDays = 29
else:
febDays = 28
monthHours = [int(31 * 24), int(febDays * 24), int(31 * 24), int(30 * 24), int(31 * 24), int(
30 * 24), int(31 * 24), int(31 * 24), int(30 * 24), int(31 * 24), int(30 * 24), int(31 * 24)]
simStartIndex = int(
sum(monthHours[:(simStartMonthNum - 1)]) + (simStartDay - 1) * 24)
temp = 0
cumulHours = [0]
for x in range(12):
temp += monthHours[x]
cumulHours.append(temp)
for i in range((simStartMonthNum), 13):
if int(simStartIndex + simRealLength) <= cumulHours[i] and int(simStartIndex + simRealLength) > cumulHours[i - 1]:
simEndMonthNum = i - 1
simEndMonth = monthNames[simEndMonthNum]
print simstartMonth, simEndMonth
# calculate peaks for the number of months in simulation
previndex = 0
monthPeak = {}
monthPeakNew = {}
peakSaveDollars = {}
energyLostDollars = {}
lossRedDollars = {}
simMonthList = monthNames[
monthNames.index(simstartMonth):(monthNames.index(simEndMonth) + 1)]
print simMonthList
for monthElement in simMonthList:
print monthElement
month = monthNames.index(monthElement)
index1 = int(previndex)
index2 = int(min((index1 + int(monthHours[month])), simRealLength))
monthPeak[monthElement] = max(p[index1:index2]) / 1000.0
monthPeakNew[monthElement] = max(pnew[index1:index2]) / 1000.0
peakSaveDollars[monthElement] = (monthPeak[monthElement] - monthPeakNew[monthElement]) * float(
inData['peakDemandCost' + str(monthToSeason[monthElement]) + 'PerKw'])
lossRedDollars[monthElement] = (sum(realLoss[index1:index2]) / 1000.0 - sum(
realLossnew[index1:index2]) / 1000.0) * (float(inData['wholesaleEnergyCostPerKwh']))
energyLostDollars[monthElement] = (sum(p[index1:index2]) / 1000.0 - sum(pnew[index1:index2]) / 1000.0 - sum(realLoss[index1:index2]) / 1000.0
+ sum(realLossnew[index1:index2]) / 1000.0) * (float(inData['wholesaleEnergyCostPerKwh']) - float(inData['retailEnergyCostPerKwh']))
previndex = index2
# money charts
fig = plt.figure("cost benefit barchart", figsize=(10, 8))
ticks = range(len(simMonthList))
ticks1 = [element + 0.15 for element in ticks]
ticks2 = [element + 0.30 for element in ticks]
print ticks
eld = [energyLostDollars[month] for month in simMonthList]
lrd = [lossRedDollars[month] for month in simMonthList]
psd = [peakSaveDollars[month] for month in simMonthList]
bar_eld = plt.bar(ticks, eld, 0.15, color='red')
bar_psd = plt.bar(ticks1, psd, 0.15, color='blue')
bar_lrd = plt.bar(ticks2, lrd, 0.15, color='green')
plt.legend([bar_eld[0], bar_psd[0], bar_lrd[0]], ['energyLostDollars', 'peakReductionDollars', 'lossReductionDollars'], bbox_to_anchor=(0., 1.015, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.1)
monShort = [element[0:3] for element in simMonthList]
plt.xticks([t + 0.15 for t in ticks], monShort)
plt.ylabel('Utility Savings ($)')
Plot.save_fig(plt, pJoin(modelDir, "spendChart.png"))
# cumulative savings graphs
fig = plt.figure("cost benefit barchart", figsize=(10, 5))
annualSavings = sum(eld) + sum(lrd) + sum(psd)
annualSave = lambda x: (
annualSavings - float(inData['omCost'])) * x - float(inData['capitalCost'])
simplePayback = float(
inData['capitalCost']) / (annualSavings - float(inData['omCost']))
plt.xlabel('Year After Installation')
plt.xlim(0, 30)
plt.ylabel('Cumulative Savings ($)')
plt.plot([0 for x in range(31)], c='gray')
plt.axvline(x=simplePayback, ymin=0, ymax=1, c='gray', linestyle='--')
plt.plot([annualSave(x) for x in range(31)], c='green')
Plot.save_fig(plt, pJoin(modelDir, "savingsChart.png"))
# get exact time stamps from the CSV files generated by Gridlab-D
timeWithZone = output['Zregulator.csv']['# timestamp']
timestamps = [element[:19] for element in timeWithZone]
# data for highcharts
allOutput["timeStamps"] = timestamps
allOutput["noCVRPower"] = p
allOutput["withCVRPower"] = pnew
allOutput["noCVRLoad"] = whLoads[0]
allOutput["withCVRLoad"] = whLoads[1]
allOutput["noCVRLosses"] = whLosses[0]
allOutput["withCVRLosses"] = whLosses[1]
allOutput["noCVRTaps"] = tap
allOutput["withCVRTaps"] = tapnew
allOutput["noCVRSubVolts"] = volt
allOutput["withCVRSubVolts"] = voltnew
allOutput["noCVRCapSwitch"] = switch
allOutput["withCVRCapSwitch"] = switchnew
allOutput["noCVRHighVolt"] = highVoltage
allOutput["withCVRHighVolt"] = highVoltagenew
allOutput["noCVRLowVolt"] = lowVoltage
allOutput["withCVRLowVolt"] = lowVoltagenew
allOutput["noCVRMeanVolt"] = meanVoltage
allOutput["withCVRMeanVolt"] = meanVoltagenew
# monetization
allOutput["simMonthList"] = monShort
allOutput["energyLostDollars"] = energyLostDollars
allOutput["lossRedDollars"] = lossRedDollars
allOutput["peakSaveDollars"] = peakSaveDollars
allOutput["annualSave"] = [annualSave(x) for x in range(31)]
# Update the runTime in the input file.
endTime = datetime.now()
inData["runTime"] = str(
timedelta(seconds=int((endTime - startTime).total_seconds())))
fs.save(pJoin(modelDir, "allInputData.json"), json.dumps(inData, indent=4))
fs.save(pJoin(modelDir, "allOutputData.json"), json.dumps(allOutput, indent=4))
# For autotest, there won't be such file.
try:
os.remove(pJoin(modelDir, "PPID.txt"))
except:
pass
print "DONE RUNNING", modelDir
except Exception as e:
print "Oops, Model Crashed!!!"
cancel(modelDir)
print e
def 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 omfCalibrate(workDir,
feederPath,
scadaPath,
simStartDate,
simLength,
simLengthUnits,
solver="FBS",
calibrateError=(0.05, 5),
trim=5):
'''calibrates a feeder and saves the calibrated tree at a location.
Note: feeders with cap banks should be calibrated with cap banks OPEN.
We have seen cap banks throw off calibration.'''
with open(feederPath, "r") as jsonIn:
feederJson = json.load(jsonIn)
tree = feederJson.get("tree", {})
simLength = simLength + trim
# Process scada data.
scadaSubPower = _processScadaData(pJoin(workDir, "gridlabD"), scadaPath,
simStartDate, simLengthUnits)
# Load specified solver.
for key in tree:
if tree[key].get("module", "").lower() == "powerflow":
tree[key] = {"module": "powerflow", "solver_method": solver}
# Attach player.
classOb = {'omftype': 'class player', 'argument': '{double value;}'}
playerOb = {
"object": "player",
"property": "value",
"name": "scadaLoads",
"file": "subScada.player",
"loop": "0"
}
maxKey = feeder.getMaxKey(tree)
playerKey = maxKey + 2
tree[maxKey + 1] = classOb
tree[playerKey] = playerOb
# Make loads reference player.
loadTemplate = {
"object": "triplex_load",
"power_pf_12": "0.95",
"impedance_pf_12": "0.98",
"power_pf_12": "0.90",
"impedance_fraction_12": "0.7",
"power_fraction_12": "0.3"
}
loadTemplateR = {
"object": "load",
"impedance_pf_A": "0.98",
"impedance_pf_B": "0.98",
"impedance_pf_C": "0.98",
"power_pf_A": "0.90",
"power_pf_B": "0.90",
"power_pf_C": "0.90",
"impedance_fraction_A": "0.7",
"impedance_fraction_B": "0.7",
"impedance_fraction_C": "0.7",
"power_fraction_A": "0.3",
"power_fraction_B": "0.3",
"power_fraction_C": "0.3"
}
for key in tree:
ob = tree[key]
if ob.get("object", "") in ("triplex_node", "triplex_load") and (
ob.get("power_12") or ob.get("base_power_12")):
# Add to triplex_nodes.
newOb = dict(loadTemplate)
newOb["name"] = ob.get("name", "")
newOb["parent"] = ob.get("parent", "")
newOb["phases"] = ob.get("phases", "")
newOb["nominal_voltage"] = ob.get("nominal_voltage", "")
newOb["latitude"] = ob.get("latitude", "0")
newOb["longitude"] = ob.get("longitude", "0")
oldPow = ob.get("power_12", "").replace("j", "d")
if not oldPow:
oldPow = ob.get("base_power_12")
if "scadaloads.value*" in oldPow:
oldPow = oldPow[17:]
pythagPower = gridlabd._strClean(oldPow)
newOb["base_power_12"] = "scadaLoads.value*" + str(pythagPower)
tree[key] = newOb
elif ob.get("object", "") == "load":
# Add to residential_loads too.
newOb = dict(loadTemplateR)
newOb["name"] = ob.get("name", "")
newOb["parent"] = ob.get("parent", "")
newOb["phases"] = ob.get("phases", "")
newOb["load_class"] = ob.get("load_class", "")
newOb["nominal_voltage"] = ob.get("nominal_voltage", "")
newOb["latitude"] = ob.get("latitude", "0")
newOb["longitude"] = ob.get("longitude", "0")
try:
oldPow = ob.get("constant_power_A", "").replace("j", "d")
pythagPower = gridlabd._strClean(oldPow)
newOb["base_power_A"] = "scadaLoads.value*" + str(pythagPower)
except:
pass
try:
oldPow = ob.get("constant_power_B", "").replace("j", "d")
pythagPower = gridlabd._strClean(oldPow)
newOb["base_power_B"] = "scadaLoads.value*" + str(pythagPower)
except:
pass
try:
oldPow = ob.get("constant_power_C", "").replace("j", "d")
pythagPower = gridlabd._strClean(oldPow)
newOb["base_power_C"] = "scadaLoads.value*" + str(pythagPower)
except:
pass
tree[key] = newOb
# Convert swing bus to a meter.
for key in tree:
if tree[key].get('bustype', '').lower() == 'swing' and tree[key].get(
'object', '') != 'meter':
swingName = tree[key].get('name')
regIndex = key
tree[key]['object'] = 'meter'
# Search for the substation meter and attach a recorder there.
for key in tree:
if tree[key].get('bustype', '').lower() == 'swing':
swingName = tree[key].get('name')
recOb = {
"object": "recorder",
"parent": swingName,
"property":
"measured_real_power,measured_reactive_power,measured_power",
"file": "caliSub.csv",
"interval": "3600"
}
outputRecorderKey = maxKey + 3
tree[outputRecorderKey] = recOb
feeder.adjustTime(tree, simLength, simLengthUnits,
simStartDate['Date'].strftime("%Y-%m-%d %H:%M:%S"))
# Run Gridlabd, calculate scaling constant.
def runPowerflowIter(tree, scadaSubPower):
'''Runs powerflow once, then iterates.'''
# Run initial powerflow to get power.
print "Starting calibration."
print "Goal of calibration: Error: %s, Iterations: <%s, trim: %s" % (
calibrateError[0], calibrateError[1], trim)
output = gridlabd.runInFilesystem(tree,
keepFiles=True,
workDir=pJoin(workDir, "gridlabD"))
outRealPow = output["caliSub.csv"]["measured_real_power"][
trim:simLength]
outImagPower = output["caliSub.csv"]["measured_reactive_power"][
trim:simLength]
outAppPowerKw = [(x[0]**2 + x[1]**2)**0.5 / 1000
for x in zip(outRealPow, outImagPower)]
lastFile = "subScada.player"
nextFile = "subScadaCalibrated.player"
nextPower = outAppPowerKw
error = (sum(outRealPow) / 1000 -
sum(scadaSubPower)) / sum(scadaSubPower)
iteration = 1
print "First error:", error
while abs(error) > calibrateError[0] and iteration < calibrateError[1]:
# Run calibration and iterate up to 5 times.
SCAL_CONST = sum(scadaSubPower) / sum(nextPower)
print "Calibrating & running again... Error: %s, Iteration: %s, SCAL_CONST: %s" % (
str(round(abs(error * 100),
6)), str(iteration), round(SCAL_CONST, 6))
newPlayData = []
with open(pJoin(pJoin(workDir, "gridlabD"), lastFile),
"r") as playerFile:
for line in playerFile:
(key, val) = line.split(',')
newPlayData.append(
str(key) + ',' + str(float(val) * SCAL_CONST) + "\n")
with open(pJoin(pJoin(workDir, "gridlabD"), nextFile),
"w") as playerFile:
for row in newPlayData:
playerFile.write(row)
tree[playerKey]["file"] = nextFile
tree[outputRecorderKey]["file"] = "caliSubCheck.csv"
nextOutput = gridlabd.runInFilesystem(tree,
keepFiles=True,
workDir=pJoin(
workDir, "gridlabD"))
outRealPowIter = nextOutput["caliSubCheck.csv"][
"measured_real_power"][trim:simLength]
outImagPowerIter = nextOutput["caliSubCheck.csv"][
"measured_reactive_power"][trim:simLength]
nextAppKw = [(x[0]**2 + x[1]**2)**0.5 / 1000
for x in zip(outRealPowIter, outImagPowerIter)]
lastFile = nextFile
nextFile = "subScadaCalibrated" + str(iteration) + ".player"
nextPower = nextAppKw
# Compute error and iterate.
error = (sum(outRealPowIter) / 1000 -
sum(scadaSubPower)) / sum(scadaSubPower)
iteration += 1
else:
if iteration == 1: outRealPowIter = outRealPow
SCAL_CONST = 1.0
print "Calibration done: Error: %s, Iteration: %s, SCAL_CONST: %s" % (
str(round(abs(error * 100),
2)), str(iteration), round(SCAL_CONST, 2))
return outRealPow, outRealPowIter, lastFile, iteration
outRealPow, outRealPowIter, lastFile, iteration = runPowerflowIter(
tree, scadaSubPower[trim:simLength])
caliPowVectors = [[
float(element) for element in scadaSubPower[trim:simLength]
], [float(element) / 1000 for element in outRealPow],
[float(element) / 1000 for element in outRealPowIter]]
labels = ["scadaSubPower", "initialGuess", "finalGuess"]
colors = ['red', 'lightblue', 'blue']
chartData = {
"Title":
"Substation Calibration Check (Iterated " + str(iteration + 1) + "X)",
"fileName": "caliCheckPlot",
"colors": colors,
"labels": labels,
"timeZone": simStartDate['timeZone']
}
# Trimming vectors to make them all the same length as the smallest vector
minCaliPowVecLen = min(len(caliPowVectors[0]), len(caliPowVectors[1]),
len(caliPowVectors[2]))
caliPowVectors[0] = caliPowVectors[0][:minCaliPowVecLen]
caliPowVectors[1] = caliPowVectors[1][:minCaliPowVecLen]
caliPowVectors[2] = caliPowVectors[2][:minCaliPowVecLen]
print "Len:", len(caliPowVectors[0]), len(caliPowVectors[1]), len(
caliPowVectors[2])
plotLine(workDir, caliPowVectors, chartData,
simStartDate['Date'] + dt.timedelta(hours=trim), simLengthUnits)
# Write the final output.
with open(pJoin(workDir, "calibratedFeeder.omd"), "w") as outJson:
playerString = open(pJoin(pJoin(workDir, "gridlabD"), lastFile)).read()
feederJson["attachments"][lastFile] = playerString
feederJson["tree"] = tree
json.dump(feederJson, outJson, indent=4)
return
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 main():
''' JSON manipulation, Gridlab running, etc. goes here. '''
# Import data.
feedJson = json.load(open('./ABEC Frank Calibrated.json'))
tree = feedJson['tree']
# Input data, model-style.
inputDict = {'simLength':24,'simStartDate':'2011-01-01', 'simLengthUnits':'hours'}
# Add recorders.
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[omf.feeder.getMaxKey(tree) + 1] = copyStub
feeder.adjustTime(tree, inputDict['simLength'], inputDict['simLengthUnits'], inputDict['simStartDate'])
# Run gridlab.
allOutputData = runInFilesystem(tree, attachments=feedJson['attachments'], keepFiles=True, workDir='.', glmName='ABEC Frank SolverGen.glm')
try: os.remove('PID.txt')
except: pass
print 'Gridlab ran correctly', allOutputData.keys()
# Make plots.
#TODO: figure out what to do about neato taking like 2 minutes to run.
neatoLayout = True
# Detect the feeder nominal voltage:
for key in tree:
ob = tree[key]
if type(ob)==dict and ob.get('bustype','')=='SWING':
feedVoltage = float(ob.get('nominal_voltage',1))
# Make a graph object.
fGraph = omf.feeder.treeToNxGraph(tree)
if neatoLayout:
# HACK: work on a new graph without attributes because graphViz tries to read attrs.
cleanG = nx.Graph(fGraph.edges())
cleanG.add_nodes_from(fGraph)
positions = nx.graphviz_layout(cleanG, prog='neato')
else:
positions = {n:fGraph.node[n].get('pos',(0,0)) for n in fGraph}
# Plot all time steps.
for step, stamp in enumerate(allOutputData['aVoltDump.csv']['# timestamp']):
# Build voltage map.
nodeVolts = {}
for nodeName in [x for x in allOutputData['aVoltDump.csv'].keys() if x != '# timestamp']:
allVolts = []
for phase in ['A','B','C']:
v = complex(allOutputData[phase.lower() + 'VoltDump.csv'][nodeName][step])
phaseVolt = _pythag(v.real, v.imag)
if phaseVolt != 0.0:
if _digits(phaseVolt)>3:
# Normalize to 120 V standard
phaseVolt = phaseVolt*(120/feedVoltage)
allVolts.append(phaseVolt)
# HACK: Take average of all phases to collapse dimensionality.
nodeVolts[nodeName] = _avg(allVolts)
# Apply voltage map and chart it.
voltChart = plt.figure(figsize=(10,10))
plt.axes(frameon = 0)
plt.axis('off')
edgeIm = nx.draw_networkx_edges(fGraph, positions)
nodeIm = nx.draw_networkx_nodes(fGraph,
pos = positions,
node_color = [nodeVolts.get(n,0) for n in fGraph.nodes()],
linewidths = 0,
node_size = 30,
cmap = plt.cm.jet)
plt.sci(nodeIm)
plt.clim(110,130)
plt.colorbar()
plt.title(stamp)
voltChart.savefig('./pngs/volts' + str(step).zfill(3) + '.png')
# Reclaim memory by closing, deleting and garbage collecting the last chart.
voltChart.clf()
plt.close()
del voltChart
gc.collect()