def addScaledRandomHouses(inFeed):
''' Take a feeder, translate each triplex_node under a meter in to a scaled, semi-randomized house object. '''
houseArchetypes = _get_house_archetypes()
childrenPath = os.path.join(omf.omfDir, 'static', 'testFiles', 'houseChildren.glm')
childrenArchetypes = feeder.parse(childrenPath)
tripNodeKeys = _get_by_key_val(inFeed, 'object', 'triplex_node', getAll=True)
tripLoadKeys = [k for k in tripNodeKeys if 'parent' in inFeed[k]]
maxKey = feeder.getMaxKey(inFeed) + 1
inFeed[maxKey] = {'omftype': 'module', 'argument': 'residential'}
maxKey += 1
inFeed[maxKey] = {'omftype': '#include','argument': '\"schedulesResponsiveLoads.glm\"'}
maxKey += 1
for tripKey in tripLoadKeys:
tMeter = inFeed[_get_by_key_val(inFeed, 'name', inFeed[tripKey]['parent'])]
tPower = complex(inFeed[tripKey]['power_12']).real
newHouse = dict(random.choice(list(houseArchetypes.values())))
newHouse['name'] += '_' + str(tripKey)
newHouse['parent'] = tMeter['name']
newHouse['schedule_skew'] = str(random.gauss(2000,500))
newHouse['floor_area'] = str(500.0 + 0.50*tPower) # Add 500 because very small floor_areas break GLD.
newHouse['latitude'] = tMeter.get('latitude','0.0')
newHouse['longitude'] = tMeter.get('longitude','0.0')
inFeed[maxKey] = newHouse
maxKey += 1
for childKey in childrenArchetypes:
newChild = dict(childrenArchetypes[childKey])
newChild['name'] += '_' + str(tripKey) + '_' + str(childKey)
newChild['parent'] = newHouse['name']
newChild['latitude'] = tMeter.get('latitude','0.0')
newChild['longitude'] = tMeter.get('longitude','0.0')
newChild['schedule_skew'] = str(random.gauss(8000,1000))
inFeed[maxKey] = newChild
maxKey += 1
del inFeed[tripKey]
def createTreeWithFault(tree, faultType, faultLocation, startTime, stopTime):
treeCopy = copy.deepcopy(tree)
treeCopy[feeder.getMaxKey(treeCopy) + 1] = {
'module': 'reliability ',
'maximum_event_length': '300 s',
'report_event_log': 'TRUE'
}
faultType = '"' + faultType + '"'
outageParams = '"'+faultLocation+','+startTime.replace('\'','') + \
','+stopTime.replace('\'','')+'"'
treeCopy[feeder.getMaxKey(treeCopy) + 1] = {
'object': 'eventgen',
'name': 'ManualEventGen',
'parent': 'RelMetrics',
'fault_type': faultType,
'manual_outages': str(outageParams)
}
treeCopy[feeder.getMaxKey(treeCopy) + 1] = {
'object': 'fault_check ',
'name': 'test_fault',
'check_mode': 'ONCHANGE',
'eventgen_object': 'ManualEventGen',
'output_filename': 'Fault_check_out.txt'
}
treeCopy[feeder.getMaxKey(treeCopy) + 1] = {
'object': 'metrics',
'name': 'RelMetrics',
'report_file': 'Metrics_Output.csv',
'module_metrics_object': 'PwrMetrics',
'metrics_of_interest': '"SAIFI,SAIDI,CAIDI,ASAI,MAIFI"',
'customer_group': '"class=meter"',
'metric_interval': '5 h',
'report_interval': '5 h'
}
treeCopy[feeder.getMaxKey(treeCopy) + 1] = {
'object': 'power_metrics',
'name': 'PwrMetrics',
'base_time_value': '1 h'
}
return treeCopy
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 addRandomSolar(feed, item, count):
'''Adds a solar inverter and panel set, assgined to A, B, or C phase randomly'''
phase_list = ['A','B','C']
maxKey = feeder.getMaxKey(feed)
feed[maxKey + 1] = {
'object': 'inverter', 'name': 'new_solar_' + str(count), 'parent': feed[item]['name'],
'phases': rand.choice(phase_list) +'S', 'inverter_type': 'PWM', 'power_factor': '1.0',
'generator_status': 'ONLINE', 'generator_mode': 'CONSTANT_PF'
}
feed[maxKey + 2] = {
'object': 'solar', 'name': 'solar_' + str(count), 'parent': 'new_solar_' + str(count), 'area': '1000 sf',
'generator_status': 'ONLINE', 'efficiency': '0.2', 'generator_mode': 'SUPPLY_DRIVEN',
'panel_type': 'SINGLE_CRYSTAL_SILICON'
}
def addRandomSolar(feed, item, count):
'''Adds a solar inverter and panel set, assgined to A, B, or C phase randomly'''
phase_list = ['A', 'B', 'C']
maxKey = feeder.getMaxKey(feed)
feed[maxKey + 1] = {
'object': 'inverter',
'name': 'new_solar_' + str(count),
'parent': feed[item]['name'],
'phases': rand.choice(phase_list) + 'S',
'inverter_type': 'PWM',
'power_factor': '1.0',
'generator_status': 'ONLINE',
'generator_mode': 'CONSTANT_PF'
}
feed[maxKey + 2] = {
'object': 'solar',
'name': 'solar_' + str(count),
'parent': 'new_solar_' + str(count),
'area': '1000 sf',
'generator_status': 'ONLINE',
'efficiency': '0.2',
'generator_mode': 'SUPPLY_DRIVEN',
'panel_type': 'SINGLE_CRYSTAL_SILICON'
}
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 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
import omf.feeder as feeder
from omf.solvers.gridlabd import runInFilesystem
feed = feeder.parse('GC-12.47-1.glm')
maxKey = feeder.getMaxKey(feed)
print (feed[1])
feed[maxKey + 1] = {
'object': 'node', 'name': 'test_solar_node', 'phases': 'ABCN',
'nominal_voltage': '7200'
}
feed[maxKey + 2] = {
'object': 'underground_line', 'name': 'test_solar_line', 'phases': 'ABCN',
'from': 'test_solar_node', 'to': 'GC-12-47-1_node_26', 'length': '100',
'configuration': 'line_configuration:6'
}
feed[maxKey + 3] = {
'object': 'meter', 'name': 'test_solar_meter', 'parent': 'test_solar_node',
'phases': 'ABCN', 'nominal_voltage': '480'
}
feed[maxKey + 4] = {
'object': 'inverter', 'name': 'test_solar_inverter', 'parent': 'test_solar_meter',
'phases': 'AS', 'inverter_type': 'PWM', 'power_factor': '1.0',
'generator_status': 'ONLINE', 'generator_mode': 'CONSTANT_PF'
}
feed[maxKey + 5] = {
'object': 'solar', 'name': 'test_solar', 'parent': 'test_solar_inverter', 'area': '1000000 sf',
'generator_status': 'ONLINE', 'efficiency': '0.2', 'generator_mode': 'SUPPLY_DRIVEN',
'panel_type': 'SINGLE_CRYSTAL_SILICON'
}
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 writeNewGlmAndPlayers(omdPath, amiPath, outputDir):
''' Take a glm and an AMI data set, and create a new GLM and set of players that combine them. '''
# Pull in the main data objects.
with open(omdPath, 'r') as jsonFile:
omdObj = json.load(jsonFile)
omdName = basename(omdPath)
feederObj = omdObj['tree']
amiData = amiImport(amiPath)
# Make the output directory.
if not os.path.isdir(outputDir):
os.mkdir(outputDir)
# Attach the player class to feeder if needed.
omfTypes = set([feederObj[k].get('omftype', '') for k in feederObj])
if 'class player' not in omfTypes:
newKey = feeder.getMaxKey(feederObj)
feederObj[newKey + 1] = {
'omftype': 'class player',
'argument': '{double value;}'
}
# All meter names we have in the AMI data set.
meterNames = set([x.get('meterName', '') for x in amiData])
# Attach all the players.
for key in list(feederObj.keys()):
objName = feederObj[key].get('name', '')
dataPhases = set([
x.get('phase', '') for x in amiData
if x.get('meterName', '') == objName
])
# Handle primary system loads.
if feederObj[key].get('object',
'') == 'load' and objName in meterNames:
for phase in dataPhases:
# Write the player file:
createPlayerFile(
amiData, objName, phase,
outputDir + '/player_' + objName + '_' + phase + '.csv')
# Put the object in the GLM:
newKey = feeder.getMaxKey(feederObj)
feederObj[newKey + 1] = {
'object': 'player',
'property': 'constant_power_' + phase,
'file': 'player_' + objName + '_' + phase + '.csv',
'parent': objName
}
# Handle secondary system loads.
elif feederObj[key].get(
'object', '') == 'triplex_node' and objName in meterNames:
# Write the player file:
createPlayerFile(amiData, objName, 'S',
outputDir + '/player_' + objName + '_S.csv')
# Put the object in the GLM:
newKey = feeder.getMaxKey(feederObj)
feederObj[newKey + 1] = {
'object': 'player',
'property': 'power_12',
'file': 'player_' + objName + '_S.csv',
'parent': objName
}
# Write the GLM.
with open(outputDir + '/out.glm', 'w') as outGlmFile:
outString = feeder.sortedWrite(feederObj)
outGlmFile.write(outString)
#TODO: update omdObj tree object to match feederObj, and insert all .csv files in to the attachments, then write new .omd to outputDir.
# omd = json.load(open('feederName.omd'))
for player in os.listdir(outputDir):
if player.startswith('player'):
name = basename(player)
with open(pJoin(outputDir, player), 'r') as inFile:
playerContents = inFile.read()
omdObj['attachments'][name + '.player'] = playerContents
oneUp = pJoin(outputDir, '..')
with open(pJoin(oneUp, omdName), 'w') as outFile:
json.dump(omdObj, 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'}
# 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 work(modelDir, inputDict):
''' Run the model in its directory. '''
outData = {}
feederName = [x for x in os.listdir(modelDir)
if x.endswith('.omd')][0][:-4]
inputDict['feederName1'] = feederName
with open(pJoin(modelDir, feederName + '.omd')) as f:
omd = json.load(f)
if inputDict.get('layoutAlgorithm', 'geospatial') == 'geospatial':
neato = False
else:
neato = True
path = pJoin(modelDir, feederName + '.omd')
if path.endswith('.glm'):
tree = feeder.parse(path)
attachments = []
elif path.endswith('.omd'):
with open(path) as f:
omd = json.load(f)
tree = omd.get('tree', {})
attachments = omd.get('attachments', [])
else:
raise Exception('Invalid input file type. We require a .glm or .omd.')
# dictionary to hold info on lines present in glm
edge_bools = dict.fromkeys([
'underground_line', 'overhead_line', 'triplex_line', 'transformer',
'regulator', 'fuse', 'switch'
], False)
# Get rid of schedules and climate and check for all edge types:
for key in list(tree.keys()):
obtype = tree[key].get('object', '')
if obtype == 'underground_line':
edge_bools['underground_line'] = True
elif obtype == 'overhead_line':
edge_bools['overhead_line'] = True
elif obtype == 'triplex_line':
edge_bools['triplex_line'] = True
elif obtype == 'transformer':
edge_bools['transformer'] = True
elif obtype == 'regulator':
edge_bools['regulator'] = True
elif obtype == 'fuse':
edge_bools['fuse'] = True
elif obtype == 'switch':
edge_bools['switch'] = True
if tree[key].get('argument',
'') == '\"schedules.glm\"' or tree[key].get(
'tmyfile', '') != '':
del tree[key]
# print edge_bools
# Make sure we have a voltDump:
def safeInt(x):
try:
return int(x)
except:
return 0
biggestKey = max([safeInt(x) for x in tree.keys()])
tree[str(biggestKey * 10)] = {
'object': 'voltdump',
'filename': 'voltDump.csv'
}
tree[str(biggestKey * 10 + 1)] = {
'object': 'currdump',
'filename': 'currDump.csv'
}
# Line rating dumps
tree[feeder.getMaxKey(tree) + 1] = {'module': 'tape'}
for key in edge_bools.keys():
if edge_bools[key]:
tree[feeder.getMaxKey(tree) + 1] = {
'object': 'group_recorder',
'group': '"class=' + key + '"',
'limit': 1,
'property': 'continuous_rating',
'file': key + '_cont_rating.csv'
}
if edge_bools['regulator']:
tree[feeder.getMaxKey(tree) + 1] = {
'object': 'group_recorder',
'group': '"class=regulator"',
'limit': 1000,
'property': 'tap_A',
'file': 'tap_A.csv',
'interval': 0
}
tree[feeder.getMaxKey(tree) + 1] = {
'object': 'group_recorder',
'group': '"class=regulator"',
'limit': 1000,
'property': 'tap_B',
'file': 'tap_B.csv',
'interval': 0
}
tree[feeder.getMaxKey(tree) + 1] = {
'object': 'group_recorder',
'group': '"class=regulator"',
'limit': 1000,
'property': 'tap_C',
'file': 'tap_C.csv',
'interval': 0
}
# get start and stop time for the simulation
[startTime, stopTime] = ['', '']
for key in tree.keys():
obname = tree[key].get('object', '')
starttime = tree[key].get('starttime', '')
stoptime = tree[key].get('stoptime', '')
if starttime != '' and stoptime != '':
startTime = tree[key]['starttime']
stopTime = tree[key]['stoptime']
break
# Map to speed up name lookups.
nameToIndex = {tree[key].get('name', ''): key for key in tree.keys()}
# find the key of the relavant added DER components
addedDerKey = nameToIndex[inputDict['newGeneration']]
addedDerInverterKey = nameToIndex[tree[addedDerKey]['parent']]
addedBreakKey = nameToIndex[inputDict['newGenerationBreaker']]
poi = tree[addedBreakKey]['to']
# set solar generation to provided insolation value
insolation = float(inputDict['newGenerationInsolation'])
if insolation > 1000:
insolation = 1000
elif insolation < 0:
insolation = 0
# cant set insolation directly but without climate object it defaults to 1000
# whilch is about 10x max sun output and we can set shading factor between 0 and 1
# to effectively control insolation
tree[addedDerKey]['shading_factor'] = insolation / 1000
# initialize variables
flickerViolations = []
flickerThreshold = float(inputDict['flickerThreshold'])
voltageViolations = []
[upperVoltThresh, lowerVoltThresh,
lowerVoltThresh600] = [1.05, 0.95, 0.975]
thermalViolations = []
thermalThreshold = float(inputDict['thermalThreshold']) / 100
reversePowerFlow = []
tapViolations = []
tapThreshold = float(inputDict['tapThreshold'])
faults = ['SLG-A', 'SLG-B', 'SLG-C', 'TLG']
faultLocs = [
inputDict['newGenerationBreaker'], inputDict['newGenerationStepUp']
]
faultBreaker = [[] for i in range(2 * len(faults))
] # the 2 is for the 2 load conditions
faultStepUp = [[] for i in range(2 * len(faults))]
faultCurrentViolations = []
faultCurrentThreshold = float(inputDict['faultCurrentThreshold'])
faultPOIVolts = []
faultVoltsThreshold = float(inputDict['faultVoltsThreshold'])
# run analysis for both load conditions
for loadCondition in ['Peak', 'Min']:
# if a peak load file is provided, use it to set peak loads in the tree
if (loadCondition == 'Peak') and (inputDict['peakLoadData'] != ''):
peakLoadData = inputDict['peakLoadData'].split('\r\n')
for data in peakLoadData:
if str(data) != '':
key = data.split(',')[0]
val = data.split(',')[1]
tree[key]['power_12'] = val
elif (loadCondition == 'Min'):
# if a min load file is provided use is to set the min loads
if inputDict['minLoadData'] != '':
minLoadData = inputDict['minLoadData'].split('\r\n')
for data in minLoadData:
if str(data) != '':
key = data.split(',')[0]
val = data.split(',')[1]
tree[key]['power_12'] = val
else: # if no min load file is provided set min load to be 1/3 of peak + noise
for key in tree.keys():
obtype = tree[key].get('object', '')
if obtype == 'triplex_node':
load = tree[key].get('power_12', '')
if load != '':
load = float(load)
minLoad = (load / 3) + (load * 0.1 *
random.triangular(-1, 1))
tree[key]['power_12'] = str(minLoad)
# initialize variables
flicker = {}
[maxFlickerLocation, maxFlickerVal] = ['', 0]
# run analysis with DER on and off under both load conditions
for der in ['On', 'Off']:
# if der is Off set added DER offline, if its On set DER online
if der is 'Off':
tree[addedDerKey]['generator_status'] = 'OFFLINE'
tree[addedDerInverterKey]['generator_status'] = 'OFFLINE'
else: # der is on
tree[addedDerKey]['generator_status'] = 'ONLINE'
tree[addedDerInverterKey]['generator_status'] = 'ONLINE'
# run gridlab solver
data = runGridlabAndProcessData(tree,
attachments,
edge_bools,
workDir=modelDir)
print(tree[addedDerKey])
print(tree[addedDerInverterKey])
# generate voltage, current and thermal plots
filename = 'voltageDer' + der + loadCondition
chart = drawPlot(tree,
nodeDict=data['percentChangeVolts'],
neatoLayout=neato,
nodeFlagBounds=[114, 126],
defaultNodeVal=120)
chart.savefig(pJoin(modelDir, filename + 'Chart.png'))
with open(pJoin(modelDir, filename + 'Chart.png'), 'rb') as inFile:
outData[filename] = base64.standard_b64encode(
inFile.read()).decode('ascii')
filename = 'currentDer' + der + loadCondition
chart = drawPlot(tree,
nodeDict=data['edgeCurrentSum'],
neatoLayout=neato)
chart.savefig(pJoin(modelDir, filename + 'Chart.png'))
with open(pJoin(modelDir, filename + 'Chart.png'), 'rb') as inFile:
outData[filename] = base64.standard_b64encode(
inFile.read()).decode('ascii')
filename = 'thermalDer' + der + loadCondition
chart = drawPlot(tree,
nodeDict=data['edgeValsPU'],
neatoLayout=neato)
chart.savefig(pJoin(modelDir, filename + 'Chart.png'))
with open(pJoin(modelDir, filename + 'Chart.png'), 'rb') as inFile:
outData[filename] = base64.standard_b64encode(
inFile.read()).decode('ascii')
# calculate max and min voltage and track badwidth violations
[maxVoltsLocation, maxVoltsVal] = ['', 0]
[minVoltsLocation, minVoltsVal] = ['', float('inf')]
for key in data['nodeVolts'].keys():
voltVal = float(data['nodeVolts'][key])
nominalVoltVal = float(data['nominalVolts'][key])
if maxVoltsVal <= voltVal:
maxVoltsVal = voltVal
maxVoltsLocation = key
if minVoltsVal >= voltVal:
minVoltsVal = voltVal
minVoltsLocation = key
change = 100 * ((voltVal - nominalVoltVal) / nominalVoltVal)
if voltVal > 600:
violation = (voltVal >= (upperVoltThresh*nominalVoltVal)) or \
(voltVal <= (lowerVoltThresh600*nominalVoltVal))
else:
violation = (voltVal >= (upperVoltThresh*nominalVoltVal)) or \
(voltVal <= (lowerVoltThresh*nominalVoltVal))
content = [key, nominalVoltVal, voltVal, change, \
loadCondition +' Load, DER ' + der,violation]
voltageViolations.append(content)
outData['maxVolts' + loadCondition + 'Der' +
der] = [maxVoltsLocation, maxVoltsVal]
outData['minVolts' + loadCondition + 'Der' +
der] = [minVoltsLocation, minVoltsVal]
# check for thermal violations
for key in data['edgeValsPU'].keys():
thermalVal = float(data['edgeValsPU'][key])
content = [key, 100*thermalVal,\
loadCondition+' Load, DER '+der,(thermalVal>=thermalThreshold)]
thermalViolations.append(content)
if edge_bools['regulator']:
# check for reverse regulator powerflow
for key in tree.keys():
obtype = tree[key].get("object", "")
obname = tree[key].get("name", "")
if obtype == 'regulator':
powerVal = float(data['edgePower'][obname])
content = [obname, powerVal,\
loadCondition+' Load, DER '+der,(powerVal<0)]
reversePowerFlow.append(content)
# check for tap_position values and violations
if der == 'On':
tapPositions = copy.deepcopy(data['tapPositions'])
else: # der off
for tapType in ['tapA', 'tapB', 'tapC']:
for key in tapPositions[tapType].keys():
# calculate tapPositions
tapDerOn = int(tapPositions[tapType][key])
tapDerOff = int(data['tapPositions'][tapType][key])
tapDifference = abs(tapDerOn - tapDerOff)
# check for violations
content = [loadCondition, key+' '+tapType, tapDerOn, \
tapDerOff,tapDifference, (tapDifference>=tapThreshold)]
tapViolations.append(content)
#induce faults and measure fault currents
for faultLocation in faultLocs:
for faultNum, faultType in enumerate(faults):
faultIndex = faultNum
if loadCondition == 'Min':
faultIndex = faultNum + len(faults)
treeCopy = createTreeWithFault( tree, \
faultType, faultLocation, startTime, stopTime )
faultData = runGridlabAndProcessData(treeCopy, attachments, \
edge_bools, workDir=modelDir)
faultVolts = faultData['nodeVolts']
faultCurrents = faultData['edgeCurrentSum']
# get fault current values at the breaker when
# the fault is at the breaker
if faultLocation == inputDict['newGenerationBreaker']:
if der == 'On':
faultBreaker[faultIndex] = [
loadCondition, faultType
]
faultBreaker[faultIndex].append(\
float(faultCurrents[\
inputDict['newGenerationBreaker']]))
else: #der off
faultBreaker[faultIndex].append(\
float(faultCurrents[inputDict['newGenerationBreaker']]))
faultBreaker[faultIndex].append(\
faultBreaker[faultIndex][2] - \
faultBreaker[faultIndex][3])
# get fault voltage values at POI
preFaultval = data['nodeVolts'][poi]
postFaultVal = faultVolts[poi]
percentChange = 100 * (postFaultVal / preFaultval)
faultPOIVolts.append(['Der '+ der + ' ' + \
loadCondition + ' Load', poi, faultType, preFaultval,\
postFaultVal, percentChange, \
(percentChange>=faultVoltsThreshold)])
# get fault current values at the transformer when
# the fault is at the transformer
else: #faultLocation == newGenerationStepUp
if der == 'On':
faultStepUp[faultIndex] = [
loadCondition, faultType
]
faultStepUp[faultIndex].append(\
float(faultCurrents[\
inputDict['newGenerationStepUp']]))
else: #der off
faultStepUp[faultIndex].append(\
float(faultCurrents[inputDict[\
'newGenerationStepUp']]))
faultStepUp[faultIndex].append(\
faultStepUp[faultIndex][2] - \
faultStepUp[faultIndex][3])
# get fault violations when der is on
if der == 'On':
for key in faultCurrents.keys():
preFaultval = float(data['edgeCurrentSum'][key])
postFaultVal = float(faultCurrents[key])
difference = abs(preFaultval - postFaultVal)
if preFaultval == 0:
percentChange = 0
else:
percentChange = 100 * (difference /
preFaultval)
content = [loadCondition, faultLocation, faultType, key, \
preFaultval, postFaultVal, percentChange, \
(percentChange>=faultCurrentThreshold)]
faultCurrentViolations.append(content)
# calculate flicker, keep track of max, and violations
if der == 'On':
flicker = copy.deepcopy(data['nodeVolts'])
else: # der off
for key in flicker.keys():
# calculate flicker
derOn = float(flicker[key])
derOff = float(data['nodeVolts'][key])
flickerVal = 100 * (1 - (derOff / derOn))
flicker[key] = flickerVal
# check for max
if maxFlickerVal <= flickerVal:
maxFlickerVal = flickerVal
maxFlickerLocation = key
# check for violations
content = [key, flickerVal,loadCondition+' Load',\
(flickerVal>=flickerThreshold)]
flickerViolations.append(content)
# plot flicker
filename = 'flicker' + loadCondition
chart = drawPlot(tree, nodeDict=flicker, neatoLayout=neato)
chart.savefig(pJoin(modelDir, filename + 'Chart.png'))
with open(pJoin(modelDir, filename + 'Chart.png'), "rb") as inFile:
outData[filename] = base64.standard_b64encode(
inFile.read()).decode('ascii')
# save max flicker info to output dictionary
outData['maxFlicker' +
loadCondition] = [maxFlickerLocation, maxFlickerVal]
outData['voltageViolations'] = voltageViolations
outData['flickerViolations'] = flickerViolations
outData['thermalViolations'] = thermalViolations
outData['reversePowerFlow'] = reversePowerFlow
outData['tapViolations'] = tapViolations
outData['faultBreaker'] = faultBreaker
outData['faultStepUp'] = faultStepUp
outData['faultCurrentViolations'] = faultCurrentViolations
outData['faultPOIVolts'] = faultPOIVolts
return outData
def drawPlot(path,
workDir=None,
neatoLayout=False,
edgeLabs=None,
nodeLabs=None,
edgeCol=None,
nodeCol=None,
faultLoc=None,
faultType=None,
customColormap=False,
scaleMin=None,
scaleMax=None,
rezSqIn=400,
simTime='2000-01-01 0:00:00',
loadLoc=None):
''' Draw a color-coded map of the voltage drop on a feeder.
path is the full path to the GridLAB-D .glm file or OMF .omd file.
workDir is where GridLAB-D will run, if it's None then a temp dir is used.
neatoLayout=True means the circuit is displayed using a force-layout approach.
edgeCol property must be either 'Current', 'Power', 'Rating', 'PercentOfRating', or None
nodeCol property must be either 'Voltage', 'VoltageImbalance', 'perUnitVoltage', 'perUnit120Voltage', or None
edgeLabs and nodeLabs properties must be either 'Name', 'Value', or None
edgeCol and nodeCol can be set to false to avoid coloring edges or nodes
customColormap=True means use a one that is nicely scaled to perunit values highlighting extremes.
faultType and faultLoc are the type of fault and the name of the line that it occurs on.
Returns a matplotlib object.'''
# Be quiet matplotlib:
# warnings.filterwarnings("ignore")
if path.endswith('.glm'):
tree = feeder.parse(path)
attachments = []
elif path.endswith('.omd'):
with open(path) as f:
omd = json.load(f)
tree = omd.get('tree', {})
attachments = omd.get('attachments', [])
else:
raise Exception('Invalid input file type. We require a .glm or .omd.')
#print path
# add fault object to tree
def safeInt(x):
try:
return int(x)
except:
return 0
biggestKey = max([safeInt(x) for x in tree.keys()])
# Add Reliability module
tree[str(biggestKey * 10)] = {
"module": "reliability",
"maximum_event_length": "18000",
"report_event_log": "true"
}
CLOCK_START = simTime
dt_start = parser.parse(CLOCK_START)
dt_end = dt_start + relativedelta(seconds=+20)
CLOCK_END = str(dt_end)
CLOCK_RANGE = CLOCK_START + ',' + CLOCK_END
if faultType != None:
# Add eventgen object (the fault)
tree[str(biggestKey * 10 + 1)] = {
"object": "eventgen",
"name": "ManualEventGen",
"parent": "RelMetrics",
"fault_type": faultType,
"manual_outages": faultLoc + ',' + CLOCK_RANGE
} # TODO: change CLOCK_RANGE to read the actual start and stop time, not just hard-coded
# Add fault_check object
tree[str(biggestKey * 10 + 2)] = {
"object": "fault_check",
"name": "test_fault",
"check_mode": "ONCHANGE",
"eventgen_object": "ManualEventGen",
"output_filename": "Fault_check_out.txt"
}
# Add reliabilty metrics object
tree[str(biggestKey * 10 + 3)] = {
"object": "metrics",
"name": "RelMetrics",
"report_file": "Metrics_Output.csv",
"module_metrics_object": "PwrMetrics",
"metrics_of_interest": '"SAIFI,SAIDI,CAIDI,ASAI,MAIFI"',
"customer_group": '"groupid=METERTEST"',
"metric_interval": "5 h",
"report_interval": "5 h"
}
# Add power_metrics object
tree[str(biggestKey * 10 + 4)] = {
"object": "power_metrics",
"name": "PwrMetrics",
"base_time_value": "1 h"
}
# HACK: set groupid for all meters so outage stats are collected.
noMeters = True
for key in tree:
if tree[key].get('object', '') in ['meter', 'triplex_meter']:
tree[key]['groupid'] = "METERTEST"
noMeters = False
if noMeters:
raise Exception(
"No meters detected on the circuit. Please add at least one meter to allow for collection of outage statistics."
)
for key in tree:
if 'clock' in tree[key]:
tree[key]['starttime'] = "'" + CLOCK_START + "'"
tree[key]['stoptime'] = "'" + CLOCK_END + "'"
# dictionary to hold info on lines present in glm
edge_bools = dict.fromkeys([
'underground_line', 'overhead_line', 'triplex_line', 'transformer',
'regulator', 'fuse', 'switch'
], False)
# Map to speed up name lookups.
nameToIndex = {tree[key].get('name', ''): key for key in tree.keys()}
# Get rid of schedules and climate and check for all edge types:
for key in list(tree.keys()):
obtype = tree[key].get("object", "")
if obtype == 'underground_line':
edge_bools['underground_line'] = True
elif obtype == 'overhead_line':
edge_bools['overhead_line'] = True
elif obtype == 'triplex_line':
edge_bools['triplex_line'] = True
elif obtype == 'transformer':
edge_bools['transformer'] = True
elif obtype == 'regulator':
edge_bools['regulator'] = True
elif obtype == 'fuse':
edge_bools['fuse'] = True
elif obtype == 'switch':
edge_bools['switch'] = True
if tree[key].get("argument",
"") == "\"schedules.glm\"" or tree[key].get(
"tmyfile", "") != "":
del tree[key]
# Make sure we have a voltage dump and current dump:
tree[str(biggestKey * 10 + 5)] = {
"object": "voltdump",
"filename": "voltDump.csv"
}
tree[str(biggestKey * 10 + 6)] = {
"object": "currdump",
"filename": "currDump.csv"
}
# Line rating dumps
tree[feeder.getMaxKey(tree) + 1] = {'module': 'tape'}
for key in edge_bools.keys():
if edge_bools[key]:
tree[feeder.getMaxKey(tree) + 1] = {
'object': 'group_recorder',
'group': '"class=' + key + '"',
'property': 'continuous_rating',
'file': key + '_cont_rating.csv'
}
#Record initial status readout of each fuse/recloser/switch/sectionalizer before running
# Reminder: fuse objects have 'phase_X_status' instead of 'phase_X_state'
protDevices = dict.fromkeys(
['fuse', 'recloser', 'switch', 'sectionalizer'], False)
#dictionary of protective device initial states for each phase
protDevInitStatus = {}
#dictionary of protective devices final states for each phase after running Gridlab-D
protDevFinalStatus = {}
#dictionary of protective device types to help the testing and debugging process
protDevTypes = {}
protDevOpModes = {}
for key in tree:
obj = tree[key]
obType = obj.get('object')
if obType in protDevices.keys():
obName = obj.get('name', '')
protDevTypes[obName] = obType
if obType != 'fuse':
protDevOpModes[obName] = obj.get('operating_mode',
'INDIVIDUAL')
protDevices[obType] = True
protDevInitStatus[obName] = {}
protDevFinalStatus[obName] = {}
for phase in ['A', 'B', 'C']:
if obType != 'fuse':
phaseState = obj.get('phase_' + phase + '_state', 'CLOSED')
else:
phaseState = obj.get('phase_' + phase + '_status', 'GOOD')
if phase in obj.get('phases', ''):
protDevInitStatus[obName][phase] = phaseState
#print protDevInitStatus
#Create a recorder for protective device states
for key in protDevices.keys():
if protDevices[key]:
for phase in ['A', 'B', 'C']:
if key != 'fuse':
tree[feeder.getMaxKey(tree) + 1] = {
'object': 'group_recorder',
'group': '"class=' + key + '"',
'property': 'phase_' + phase + '_state',
'file': key + '_phase_' + phase + '_state.csv'
}
else:
tree[feeder.getMaxKey(tree) + 1] = {
'object': 'group_recorder',
'group': '"class=' + key + '"',
'property': 'phase_' + phase + '_status',
'file': key + '_phase_' + phase + '_state.csv'
}
# Run Gridlab.
if not workDir:
workDir = tempfile.mkdtemp()
print('@@@@@@', workDir)
# for i in range(6):
# gridlabOut = gridlabd.runInFilesystem(tree, attachments=attachments, workDir=workDir)
# #HACK: workaround for shoddy macOS gridlabd build.
# if 'error when setting parent' not in gridlabOut.get('stderr','OOPS'):
# break
gridlabOut = gridlabd.runInFilesystem(tree,
attachments=attachments,
workDir=workDir)
#Record final status readout of each fuse/recloser/switch/sectionalizer after running
try:
for key in protDevices.keys():
if protDevices[key]:
for phase in ['A', 'B', 'C']:
with open(pJoin(workDir,
key + '_phase_' + phase + '_state.csv'),
newline='') as statusFile:
reader = csv.reader(statusFile)
# loop past the header,
keys = []
vals = []
for row in reader:
if '# timestamp' in row:
keys = row
i = keys.index('# timestamp')
keys.pop(i)
vals = next(reader)
vals.pop(i)
for pos, key2 in enumerate(keys):
protDevFinalStatus[key2][phase] = vals[pos]
except:
pass
#print protDevFinalStatus
#compare initial and final states of protective devices
#quick compare to see if they are equal
#print cmp(protDevInitStatus, protDevFinalStatus)
#find which values changed
changedStates = {}
#read voltDump values into a dictionary.
try:
with open(pJoin(workDir, 'voltDump.csv'), newline='') as dumpFile:
reader = csv.reader(dumpFile)
next(reader) # Burn the header.
keys = next(reader)
voltTable = []
for row in reader:
rowDict = {}
for pos, key in enumerate(keys):
rowDict[key] = row[pos]
voltTable.append(rowDict)
except:
raise Exception(
'GridLAB-D failed to run with the following errors:\n' +
gridlabOut['stderr'])
# read currDump values into a dictionary
with open(pJoin(workDir, 'currDump.csv'), newline='') as currDumpFile:
reader = csv.reader(currDumpFile)
next(reader) # Burn the header.
keys = next(reader)
currTable = []
for row in reader:
rowDict = {}
for pos, key in enumerate(keys):
rowDict[key] = row[pos]
currTable.append(rowDict)
# read line rating values into a single dictionary
lineRatings = {}
rating_in_VA = []
for key1 in edge_bools.keys():
if edge_bools[key1]:
with open(pJoin(workDir, key1 + '_cont_rating.csv'),
newline='') as ratingFile:
reader = csv.reader(ratingFile)
# loop past the header,
keys = []
vals = []
for row in reader:
if '# timestamp' in row:
keys = row
i = keys.index('# timestamp')
keys.pop(i)
vals = next(reader)
vals.pop(i)
for pos, key2 in enumerate(keys):
lineRatings[key2] = abs(float(vals[pos]))
#edgeTupleRatings = lineRatings copy with to-from tuple as keys for labeling
edgeTupleRatings = {}
for edge in lineRatings:
for obj in tree.values():
if obj.get('name', '').replace('"', '') == edge:
nodeFrom = obj.get('from')
nodeTo = obj.get('to')
coord = (nodeFrom, nodeTo)
ratingVal = lineRatings.get(edge)
edgeTupleRatings[coord] = ratingVal
# Calculate average node voltage deviation. First, helper functions.
def digits(x):
''' Returns number of digits before the decimal in the float x. '''
return math.ceil(math.log10(x + 1))
def avg(l):
''' Average of a list of ints or floats. '''
# HACK: add a small value to the denominator to avoid divide by zero for out of service locations (i.e. zero voltage).
return sum(l) / (len(l) + 0.00000000000000001)
# Detect the feeder nominal voltage:
for key in tree:
ob = tree[key]
if type(ob) == dict and ob.get('bustype', '') == 'SWING':
feedVoltage = float(ob.get('nominal_voltage', 1))
# Tot it all up.
nodeVolts = {}
nodeVoltsPU = {}
nodeVoltsPU120 = {}
voltImbalances = {}
for row in voltTable:
allVolts = []
allVoltsPU = []
allDiffs = []
nodeName = row.get('node_name', '')
for phase in ['A', 'B', 'C']:
realVolt = abs(float(row['volt' + phase + '_real']))
imagVolt = abs(float(row['volt' + phase + '_imag']))
phaseVolt = math.sqrt((realVolt**2) + (imagVolt**2))
if phaseVolt != 0.0:
treeKey = nameToIndex.get(nodeName, 0)
nodeObj = tree.get(treeKey, {})
try:
nominal_voltage = float(nodeObj['nominal_voltage'])
except:
nominal_voltage = feedVoltage
allVolts.append(phaseVolt)
normVolt = (phaseVolt / nominal_voltage)
allVoltsPU.append(normVolt)
avgVolts = avg(allVolts)
avgVoltsPU = avg(allVoltsPU)
avgVoltsPU120 = 120 * avgVoltsPU
nodeVolts[nodeName] = float("{0:.2f}".format(avgVolts))
nodeVoltsPU[nodeName] = float("{0:.2f}".format(avgVoltsPU))
nodeVoltsPU120[nodeName] = float("{0:.2f}".format(avgVoltsPU120))
if len(allVolts) == 3:
voltA = allVolts.pop()
voltB = allVolts.pop()
voltC = allVolts.pop()
allDiffs.append(abs(float(voltA - voltB)))
allDiffs.append(abs(float(voltA - voltC)))
allDiffs.append(abs(float(voltB - voltC)))
maxDiff = max(allDiffs)
voltImbal = maxDiff / avgVolts
voltImbalances[nodeName] = float("{0:.2f}".format(voltImbal))
# Use float("{0:.2f}".format(avg(allVolts))) if displaying the node labels
nodeLoadNames = {}
nodeNames = {}
for key in nodeVolts.keys():
nodeNames[key] = key
if key == loadLoc:
nodeLoadNames[key] = "LOAD: " + key
# find edge currents by parsing currdump
edgeCurrentSum = {}
edgeCurrentMax = {}
for row in currTable:
allCurr = []
for phase in ['A', 'B', 'C']:
realCurr = abs(float(row['curr' + phase + '_real']))
imagCurr = abs(float(row['curr' + phase + '_imag']))
phaseCurr = math.sqrt((realCurr**2) + (imagCurr**2))
allCurr.append(phaseCurr)
edgeCurrentSum[row.get('link_name', '')] = sum(allCurr)
edgeCurrentMax[row.get('link_name', '')] = max(allCurr)
# When just showing current as labels, use sum of the three lines' current values, when showing the per unit values (current/rating), use the max of the three
#edgeTupleCurrents = edgeCurrents copy with to-from tuple as keys for labeling
edgeTupleCurrents = {}
#edgeValsPU = values normalized per unit by line ratings
edgeValsPU = {}
#edgeTupleValsPU = edgeValsPU copy with to-from tuple as keys for labeling
edgeTupleValsPU = {}
#edgeTuplePower = dict with to-from tuples as keys and sim power as values for debugging
edgeTuplePower = {}
#edgeTupleNames = dict with to-from tuples as keys and names as values for debugging
edgeTupleNames = {}
#edgeTupleFaultNames = dict with to-from tuples as keys and the name of the Fault as the only value
edgeTupleFaultNames = {}
#edgeTupleProtDevs = dict with to-from tuples as keys and the initial of the type of protective device as the value
edgeTupleProtDevs = {}
#linePhases = dictionary containing the number of phases on each line for line-width purposes
linePhases = {}
edgePower = {}
for edge in edgeCurrentSum:
for obj in tree.values():
obname = obj.get('name', '').replace('"', '')
if obname == edge:
objType = obj.get('object')
nodeFrom = obj.get('from')
nodeTo = obj.get('to')
coord = (nodeFrom, nodeTo)
currVal = edgeCurrentSum.get(edge)
voltVal = avg([nodeVolts.get(nodeFrom), nodeVolts.get(nodeTo)])
power = (currVal * voltVal) / 1000
lineRating = lineRatings.get(edge, 10.0**9)
edgePerUnitVal = (edgeCurrentMax.get(edge)) / lineRating
edgeTupleCurrents[coord] = "{0:.2f}".format(currVal)
edgeTuplePower[coord] = "{0:.2f}".format(power)
edgePower[edge] = power
edgeValsPU[edge] = edgePerUnitVal
edgeTupleValsPU[coord] = "{0:.2f}".format(edgePerUnitVal)
edgeTupleNames[coord] = edge
if faultLoc == edge:
edgeTupleFaultNames[coord] = "FAULT: " + edge
phaseStr = obj.get('phases', '').replace('"', '').replace(
'N', '').replace('S', '')
numPhases = len(phaseStr)
if (numPhases < 1) or (numPhases > 3):
numPhases = 1
linePhases[edge] = numPhases
protDevLabel = ""
protDevBlownStr = ""
if objType in protDevices.keys():
for phase in protDevFinalStatus[obname].keys():
if objType == 'fuse':
if protDevFinalStatus[obname][phase] == "BLOWN":
protDevBlownStr = "!"
else:
if protDevFinalStatus[obname][phase] == "OPEN":
protDevBlownStr = "!"
if objType == 'fuse':
protDevLabel = 'F'
elif objType == 'switch':
protDevLabel = 'S'
elif objType == 'recloser':
protDevLabel = 'R'
elif objType == 'sectionalizer':
protDevLabel = 'X'
edgeTupleProtDevs[coord] = protDevLabel + protDevBlownStr
#define which dict will be used for edge line color
edgeColors = edgeValsPU
#define which dict will be used for edge label
edgeLabels = edgeTupleValsPU
# Build the graph.
fGraph = feeder.treeToNxGraph(tree)
# TODO: consider whether we can set figsize dynamically.
wlVal = int(math.sqrt(float(rezSqIn)))
voltChart = plt.figure(figsize=(wlVal, wlVal))
plt.axes(frameon=0)
plt.axis('off')
voltChart.gca().set_aspect('equal')
plt.tight_layout()
#set axes step equal
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 = graphviz_layout(cleanG, prog='neato')
else:
remove_nodes = [
n for n in fGraph if fGraph.nodes[n].get('pos', (0, 0)) == (0, 0)
]
fGraph.remove_nodes_from(remove_nodes)
positions = {n: fGraph.nodes[n].get('pos', (0, 0)) for n in fGraph}
# Need to get edge names from pairs of connected node names.
edgeNames = []
for e in fGraph.edges():
edgeNames.append((fGraph.edges[e].get('name',
'BLANK')).replace('"', ''))
#create custom colormap
if customColormap:
if scaleMin != None and scaleMax != None:
scaleDif = scaleMax - scaleMin
custom_cm = matplotlib.colors.LinearSegmentedColormap.from_list(
'custColMap', [(scaleMin, 'blue'),
(scaleMin + (0.12 * scaleDif), 'darkgray'),
(scaleMin + (0.56 * scaleDif), 'darkgray'),
(scaleMin + (0.8 * scaleDif), 'red')])
vmin = scaleMin
vmax = scaleMax
else:
custom_cm = matplotlib.colors.LinearSegmentedColormap.from_list(
'custColMap', [(0.0, 'blue'), (0.15, 'darkgray'),
(0.7, 'darkgray'), (1.0, 'red')])
vmin = 0
vmax = 1.25
custom_cm.set_under(color='black')
else:
custom_cm = plt.cm.get_cmap('viridis')
if scaleMin != None and scaleMax != None:
vmin = scaleMin
vmax = scaleMax
else:
vmin = None
vmax = None
drawColorbar = False
emptyColors = {}
#draw edges with or without colors
if edgeCol != None:
drawColorbar = True
if edgeCol == "Current":
edgeList = [edgeCurrentSum.get(n, 1) for n in edgeNames]
drawColorbar = True
elif edgeCol == "Power":
edgeList = [edgePower.get(n, 1) for n in edgeNames]
drawColorbar = True
elif edgeCol == "Rating":
edgeList = [lineRatings.get(n, 10.0**9) for n in edgeNames]
drawColorbar = True
elif edgeCol == "PercentOfRating":
edgeList = [edgeValsPU.get(n, .5) for n in edgeNames]
drawColorbar = True
else:
edgeList = [emptyColors.get(n, .6) for n in edgeNames]
print(
"WARNING: edgeCol property must be 'Current', 'Power', 'Rating', 'PercentOfRating', or None"
)
else:
edgeList = [emptyColors.get(n, .6) for n in edgeNames]
edgeIm = nx.draw_networkx_edges(
fGraph,
pos=positions,
edge_color=edgeList,
width=[linePhases.get(n, 1) for n in edgeNames],
edge_cmap=custom_cm)
#draw edge labels
if edgeLabs != None:
if edgeLabs == "Name":
edgeLabels = edgeTupleNames
elif edgeLabs == "Fault":
edgeLabels = edgeTupleFaultNames
elif edgeLabs == "Value":
if edgeCol == "Current":
edgeLabels = edgeTupleCurrents
elif edgeCol == "Power":
edgeLabels = edgeTuplePower
elif edgeCol == "Rating":
edgeLabels = edgeTupleRatings
elif edgeCol == "PercentOfRating":
edgeLabels = edgeTupleValsPU
else:
edgeLabels = None
print(
"WARNING: edgeCol property cannot be set to None when edgeLabs property is set to 'Value'"
)
elif edgeLabs == "ProtDevs":
edgeLabels = edgeTupleProtDevs
else:
edgeLabs = None
print(
"WARNING: edgeLabs property must be either 'Name', 'Value', or None"
)
if edgeLabs != None:
edgeLabelsIm = nx.draw_networkx_edge_labels(fGraph,
pos=positions,
edge_labels=edgeLabels,
font_size=8)
# draw nodes with or without color
if nodeCol != None:
if nodeCol == "Voltage":
nodeList = [nodeVolts.get(n, 1) for n in fGraph.nodes()]
drawColorbar = True
elif nodeCol == "VoltageImbalance":
nodeList = [voltImbalances.get(n, 1) for n in fGraph.nodes()]
drawColorbar = True
elif nodeCol == "perUnitVoltage":
nodeList = [nodeVoltsPU.get(n, .5) for n in fGraph.nodes()]
drawColorbar = True
elif nodeCol == "perUnit120Voltage":
nodeList = [nodeVoltsPU120.get(n, 120) for n in fGraph.nodes()]
drawColorbar = True
else:
nodeList = [emptyColors.get(n, 1) for n in fGraph.nodes()]
print(
"WARNING: nodeCol property must be 'Voltage', 'VoltageImbalance', 'perUnitVoltage', 'perUnit120Voltage', or None"
)
else:
nodeList = [emptyColors.get(n, .6) for n in fGraph.nodes()]
nodeIm = nx.draw_networkx_nodes(fGraph,
pos=positions,
node_color=nodeList,
linewidths=0,
node_size=30,
vmin=vmin,
vmax=vmax,
cmap=custom_cm)
#draw node labels
nodeLabels = {}
if nodeLabs != None:
if nodeLabs == "Name":
nodeLabels = nodeNames
elif nodeLabs == "Value":
if nodeCol == "Voltage":
nodeLabels = nodeVolts
elif nodeCol == "VoltageImbalance":
nodeLabels = voltImbalances
elif nodeCol == "perUnitVoltage":
nodeLabels = nodeVoltsPU
elif nodeCol == "perUnit120Voltage":
nodeLabels = nodeVoltsPU120
else:
nodeLabels = None
print(
"WARNING: nodeCol property cannot be set to None when nodeLabs property is set to 'Value'"
)
#HACK: add hidden node label option for displaying specified load name
elif nodeLabs == "Load":
nodeLabels = nodeLoadNames
else:
nodeLabs = None
print(
"WARNING: nodeLabs property must be either 'Name', 'Value', or None"
)
if nodeLabs != None:
nodeLabelsIm = nx.draw_networkx_labels(fGraph,
pos=positions,
labels=nodeLabels,
font_size=8)
plt.sci(nodeIm)
# plt.clim(110,130)
if drawColorbar:
plt.colorbar()
return voltChart
# go through every entry in the circuit definition
for key in tree.keys():
# check to see if the clock actually exists and update timings if it does
if clockExists == False and tree[key].get('clock','') != '':
clockExists = True
tree[key]['starttime'] = '\"' + SIM_START_TIME + '\"'
tree[key]['stoptime'] = '\"' + SIM_STOP_TIME + '\"'
# check to see if the tape module actually exists
if tapeModuleExists == False and tree[key].get('argument','') == 'tape':
tapeModuleExists = True
# if there is no clock, add it
if clockExists == False:
tree[feeder.getMaxKey(tree) + 1] = {
'clock': 'clock',
'timezone': TIMEZONE,
'starttime': '\"' + SIM_START_TIME + '\"',
'stoptime': '\"' + SIM_STOP_TIME + '\"',
}
# if there is no tape module, add it
if tapeModuleExists == False:
tree[feeder.getMaxKey(tree) + 1] = {'module': 'tape'}
# add recorder object
tree[feeder.getMaxKey(tree) + 1] = {
'object': 'recorder',
'name': 'meterRecorder',
'parent': '\"' + FAULT_METER + '\"',
import omf.feeder as feeder
from omf.solvers.gridlabd import runInFilesystem
feed = feeder.parse('GC-12.47-1.glm')
maxKey = feeder.getMaxKey(feed)
print(feed[1])
feed[maxKey + 1] = {
'object': 'node',
'name': 'test_solar_node',
'phases': 'ABCN',
'nominal_voltage': '7200'
}
feed[maxKey + 2] = {
'object': 'underground_line',
'name': 'test_solar_line',
'phases': 'ABCN',
'from': 'test_solar_node',
'to': 'GC-12-47-1_node_26',
'length': '100',
'configuration': 'line_configuration:6'
}
feed[maxKey + 3] = {
'object': 'meter',
'name': 'test_solar_meter',
'parent': 'test_solar_node',
'phases': 'ABCN',
'nominal_voltage': '480'
}
feed[maxKey + 4] = {
weather_writer.writerow(['temperature','wind_speed','humidity','solar_dir','solar_diff','solar_global'])
for row in data_full:
weather_writer.writerow(row)
# Add stuff to the feeder.
myTree = feeder.parse(GLM_PATH)
# 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()
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 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
