def scaleCase9(networkJson, iterations):
newBuses = {}
newGens = {}
newBranches = {}
busCounter = 0
for x in range(iterations):
for key, bus in networkJson["bus"].iteritems():
newKey = str(int(key) + busCounter)
newBuses[newKey] = copy.deepcopy(bus)
newBuses[newKey]["bus_i"] = newKey
busCounter = busCounter + 9
genCounter = 0
for x in range(iterations):
for key, gen in networkJson["gen"].iteritems():
newKey = str(int(key) + genCounter)
newGens[newKey] = copy.deepcopy(gen)
newGens[newKey]["bus"] = newKey
genCounter = genCounter + 9
branchCounter = 0
for x in range(iterations):
for key, branch in networkJson["branch"].iteritems():
newKey = str(int(key) + branchCounter)
newBranches[newKey] = copy.deepcopy(branch)
newBranches[newKey]["fbus"] = str(
int(branch["fbus"]) + branchCounter)
newBranches[newKey]["tbus"] = str(
int(branch["tbus"]) + branchCounter)
branchCounter = branchCounter + 9
networkJson["bus"] = newBuses
networkJson["gen"] = newGens
networkJson["branch"] = newBranches
matStr = network.netToMat(networkJson, networkName)
with open("manyCase9Scaled.m", "w") as outMat:
for row in matStr:
outMat.write(row)
return networkJson
def work(modelDir, inputDict):
''' Run the model in its directory.'''
outData = {
'tableData' : {'volts': [[],[]], 'powerReal' : [[],[]], 'powerReact' : [[],[]]},
# 'charts' : {'volts' : '', 'powerReact' : '', 'powerReal' : ''},
'voltsChart' : '', 'powerReactChart' : '', 'powerRealChart' : '',
'stdout' : '', 'stderr' : ''
}
# Read feeder and convert to .mat.
try:
networkName = [x for x in os.listdir(modelDir) if x.endswith('.omt')][0][0:-4]
except:
networkName = 'case9'
with open(pJoin(modelDir,networkName+".omt")) as f:
networkJson = json.load(f)
matName = 'matIn'
matFileName = matName + '.m'
matStr = network.netToMat(networkJson, matName)
with open(pJoin(modelDir, matFileName),"w") as outMat:
for row in matStr: outMat.write(row)
# Build the MATPOWER command.
matDir = pJoin(__neoMetaModel__._omfDir,'solvers','matpower5.1')
if platform.system() == "Windows":
pathSep = ";"
else:
pathSep = ":"
matPath = '"' + pathSep.join([matDir,pJoin(matDir,'t'),pJoin(matDir,'extras')]) + '"'
algorithm = inputDict.get("algorithm","NR")
pfArg = "'pf.alg', '" + algorithm + "'"
modelArg = "'model', '" + inputDict.get("model","AC") + "'"
iterCode = "pf." + algorithm[:2].lower() + ".max_it"
pfItArg = "'" + iterCode + "', " + str(inputDict.get("iteration",10))
pfTolArg = "'pf.tol', " + str(inputDict.get("tolerance",math.pow(10,-8)))
pfEnflArg = "'pf.enforce_q_lims', " + str(inputDict.get("genLimits",0))
if platform.system() == "Windows":
# Find the location of octave-cli tool.
envVars = os.environ["PATH"].split(';')
octavePath = "C:\\Octave\\Octave-4.2.0"
for pathVar in envVars:
if "octave" in pathVar.lower():
octavePath = pathVar
# Run Windows-specific Octave command.
mpoptArg = "mpoption(" + pfArg + ", " + modelArg + ", " + pfItArg + ", " + pfTolArg+", " + pfEnflArg + ") "
cmd = "runpf('"+pJoin(modelDir,matFileName)+"'," + mpoptArg +")"
args = [octavePath + '\\bin\\octave-cli','-p',matPath, "--eval", cmd]
myOut = subprocess.check_output(args, shell=True)
with open(pJoin(modelDir, "matout.txt"), "w") as matOut:
matOut.write(myOut)
else:
# Run UNIX Octave command.
mpoptArg = "mpopt = mpoption("+pfArg+", "+modelArg+", "+pfItArg+", "+pfTolArg+", "+pfEnflArg+"); "
command = "octave -p " + matPath + "--no-gui --eval \""+mpoptArg+"runpf('"+pJoin(modelDir,matFileName)+"', mpopt)\" > \"" + pJoin(modelDir,"matout.txt") + "\""
proc = subprocess.Popen(command, stdout=subprocess.PIPE, shell=True)
print(command)
(out, err) = proc.communicate()
imgSrc = pJoin(__neoMetaModel__._omfDir,'scratch','transmission','inData')
# Read matout.txt and parse into outData.
gennums=[]
todo = None
with open(pJoin(modelDir,"matout.txt")) as f:
for i,line in enumerate(f):
# Determine what type of data is coming up.
if "How many?" in line:
todo = "count"
elif "Generator Data" in line:
todo = "gen"
lineNo = i
elif "Bus Data" in line:
todo = "node"
lineNo = i
elif "Branch Data" in line:
todo = "line"
lineNo = i
# Parse lines.
line = line.split(' ')
line = [a for a in line if a != '']
if todo=="count":
if "Buses" in line:
busCount = int(line[1])
elif "Generators" in line:
genCount = int(line[1])
elif "Loads" in line:
loadCount = int(line[1])
elif "Branches" in line:
branchCount = int(line[1])
elif "Transformers" in line:
transfCount = int(line[1])
todo = None
elif todo=="gen":
if i>(lineNo+4) and i<(lineNo+4+genCount+1):
# gen bus numbers.
gennums.append(line[1])
elif i>(lineNo+4+genCount+1):
todo = None
elif todo=="node":
if i>(lineNo+4) and i<(lineNo+4+busCount+1):
# voltage
if line[0] in gennums: comp="gen"
else: comp="node"
outData['tableData']['volts'][0].append(comp+str(line[0]))
outData['tableData']['powerReal'][0].append(comp+str(line[0]))
outData['tableData']['powerReact'][0].append(comp+str(line[0]))
outData['tableData']['volts'][1].append(line[1])
outData['tableData']['powerReal'][1].append(line[3])
outData['tableData']['powerReact'][1].append(line[4])
elif i>(lineNo+4+busCount+1):
todo = None
elif todo=="line":
if i>(lineNo+4) and i<(lineNo+4+branchCount+1):
# power
outData['tableData']['powerReal'][0].append("line"+str(line[0]))
outData['tableData']['powerReact'][0].append("line"+str(line[0]))
outData['tableData']['powerReal'][1].append(line[3])
outData['tableData']['powerReact'][1].append(line[4])
elif i>(lineNo+4+branchCount+1):
todo = None
# Massage the data.
for powerOrVolt in outData['tableData'].keys():
for i in range(len(outData['tableData'][powerOrVolt][1])):
if outData['tableData'][powerOrVolt][1][i]!='-':
outData['tableData'][powerOrVolt][1][i]=float(outData['tableData'][powerOrVolt][1][i])
#Create chart
nodeVolts = outData["tableData"]["volts"][1]
minNum = min(nodeVolts)
maxNum = max(nodeVolts)
norm = matplotlib.colors.Normalize(vmin=minNum, vmax=maxNum, clip=True)
cmViridis = plt.get_cmap('viridis')
mapper = cm.ScalarMappable(norm=norm, cmap=cmViridis)
mapper._A = []
plt.figure(figsize=(10,10))
plt.colorbar(mapper)
plt.axis('off')
plt.tight_layout()
plt.gca().invert_yaxis() # HACK: to make latitudes show up right. TODO: y-flip the transEdit.html and remove this.
plt.gca().set_aspect('equal')
busLocations = {}
i = 0
for busName, busInfo in networkJson["bus"].items():
y = float(busInfo["latitude"])
x = float(busInfo["longitude"])
plt.plot([x], [y], marker='o', markersize=12.0, color=mapper.to_rgba(nodeVolts[i]), zorder=5)
busLocations[busName] = [x, y]
i = i + 1
for genName, genInfo in networkJson["gen"].items():
x,y = busLocations[genInfo["bus"]]
plt.plot([x], [y], 's', color='gray', zorder=10, markersize=6.0)
for branchName, branchInfo in networkJson["branch"].items():
x1, y1 = busLocations[branchInfo["fbus"]]
x2, y2 = busLocations[branchInfo["tbus"]]
plt.plot([x1, x2], [y1,y2], color='black', marker = '', zorder=0)
plt.savefig(modelDir + '/output.png')
with open(pJoin(modelDir,"output.png"),"rb") as inFile:
outData["chart"] = base64.standard_b64encode(inFile.read()).decode('ascii')
# Stdout/stderr.
outData["stdout"] = "Success"
outData["stderr"] = ""
return outData
def work(modelDir, inputDict):
''' Run the model in its directory.'''
outData = {
'tableData' : {'volts': [[],[]], 'powerReal' : [[],[]], 'powerReact' : [[],[]]},
# 'charts' : {'volts' : '', 'powerReact' : '', 'powerReal' : ''},
'voltsChart' : '', 'powerReactChart' : '', 'powerRealChart' : '',
'stdout' : '', 'stderr' : ''
}
# Read feeder and convert to .mat.
try:
networkName = [x for x in os.listdir(modelDir) if x.endswith('.omt')][0][0:-4]
except:
networkName = 'case9'
networkJson = json.load(open(pJoin(modelDir,networkName+".omt")))
matName = 'matIn'
matFileName = matName + '.m'
matStr = network.netToMat(networkJson, matName)
with open(pJoin(modelDir, matFileName),"w") as outMat:
for row in matStr: outMat.write(row)
# Build the MATPOWER command.
matDir = pJoin(__neoMetaModel__._omfDir,'solvers','matpower5.1')
if platform.system() == "Windows":
pathSep = ";"
else:
pathSep = ":"
matPath = '"' + pathSep.join([matDir,pJoin(matDir,'t'),pJoin(matDir,'extras')]) + '"'
algorithm = inputDict.get("algorithm","NR")
pfArg = "'pf.alg', '" + algorithm + "'"
modelArg = "'model', '" + inputDict.get("model","AC") + "'"
iterCode = "pf." + algorithm[:2].lower() + ".max_it"
pfItArg = "'" + iterCode + "', " + str(inputDict.get("iteration",10))
pfTolArg = "'pf.tol', " + str(inputDict.get("tolerance",math.pow(10,-8)))
pfEnflArg = "'pf.enforce_q_lims', " + str(inputDict.get("genLimits",0))
if platform.system() == "Windows":
# Find the location of octave-cli tool.
envVars = os.environ["PATH"].split(';')
octavePath = "C:\\Octave\\Octave-4.2.0"
for pathVar in envVars:
if "octave" in pathVar.lower():
octavePath = pathVar
# Run Windows-specific Octave command.
mpoptArg = "mpoption(" + pfArg + ", " + modelArg + ", " + pfItArg + ", " + pfTolArg+", " + pfEnflArg + ") "
cmd = "runpf('"+pJoin(modelDir,matFileName)+"'," + mpoptArg +")"
args = [octavePath + '\\bin\\octave-cli','-p',matPath, "--eval", cmd]
myOut = subprocess.check_output(args, shell=True)
with open(pJoin(modelDir, "matout.txt"), "w") as matOut:
matOut.write(myOut)
else:
# Run UNIX Octave command.
mpoptArg = "mpopt = mpoption("+pfArg+", "+modelArg+", "+pfItArg+", "+pfTolArg+", "+pfEnflArg+"); "
command = "octave -p " + matPath + "--no-gui --eval \""+mpoptArg+"runpf('"+pJoin(modelDir,matFileName)+"', mpopt)\" > \"" + pJoin(modelDir,"matout.txt") + "\""
proc = subprocess.Popen(command, stdout=subprocess.PIPE, shell=True)
print command
(out, err) = proc.communicate()
imgSrc = pJoin(__neoMetaModel__._omfDir,'scratch','transmission','inData')
# Read matout.txt and parse into outData.
gennums=[]
todo = None
with open(pJoin(modelDir,"matout.txt")) as f:
for i,line in enumerate(f):
# Determine what type of data is coming up.
if "How many?" in line:
todo = "count"
elif "Generator Data" in line:
todo = "gen"
lineNo = i
elif "Bus Data" in line:
todo = "node"
lineNo = i
elif "Branch Data" in line:
todo = "line"
lineNo = i
# Parse lines.
line = line.split(' ')
line = filter(lambda a: a!= '', line)
if todo=="count":
if "Buses" in line:
busCount = int(line[1])
elif "Generators" in line:
genCount = int(line[1])
elif "Loads" in line:
loadCount = int(line[1])
elif "Branches" in line:
branchCount = int(line[1])
elif "Transformers" in line:
transfCount = int(line[1])
todo = None
elif todo=="gen":
if i>(lineNo+4) and i<(lineNo+4+genCount+1):
# gen bus numbers.
gennums.append(line[1])
elif i>(lineNo+4+genCount+1):
todo = None
elif todo=="node":
if i>(lineNo+4) and i<(lineNo+4+busCount+1):
# voltage
if line[0] in gennums: comp="gen"
else: comp="node"
outData['tableData']['volts'][0].append(comp+str(line[0]))
outData['tableData']['powerReal'][0].append(comp+str(line[0]))
outData['tableData']['powerReact'][0].append(comp+str(line[0]))
outData['tableData']['volts'][1].append(line[1])
outData['tableData']['powerReal'][1].append(line[3])
outData['tableData']['powerReact'][1].append(line[4])
elif i>(lineNo+4+busCount+1):
todo = None
elif todo=="line":
if i>(lineNo+4) and i<(lineNo+4+branchCount+1):
# power
outData['tableData']['powerReal'][0].append("line"+str(line[0]))
outData['tableData']['powerReact'][0].append("line"+str(line[0]))
outData['tableData']['powerReal'][1].append(line[3])
outData['tableData']['powerReact'][1].append(line[4])
elif i>(lineNo+4+branchCount+1):
todo = None
# Massage the data.
for powerOrVolt in outData['tableData'].keys():
for i in range(len(outData['tableData'][powerOrVolt][1])):
if outData['tableData'][powerOrVolt][1][i]!='-':
outData['tableData'][powerOrVolt][1][i]=float(outData['tableData'][powerOrVolt][1][i])
#Create chart
nodeVolts = outData["tableData"]["volts"][1]
minNum = min(nodeVolts)
maxNum = max(nodeVolts)
norm = matplotlib.colors.Normalize(vmin=minNum, vmax=maxNum, clip=True)
cmViridis = plt.get_cmap('viridis')
mapper = cm.ScalarMappable(norm=norm, cmap=cmViridis)
mapper._A = []
plt.figure(figsize=(10,10))
plt.colorbar(mapper)
plt.axis('off')
plt.tight_layout()
plt.gca().invert_yaxis() # HACK: to make latitudes show up right. TODO: y-flip the transEdit.html and remove this.
plt.gca().set_aspect('equal')
busLocations = {}
i = 0
for busName, busInfo in networkJson["bus"].items():
y = float(busInfo["latitude"])
x = float(busInfo["longitude"])
plt.plot([x], [y], marker='o', markersize=12.0, color=mapper.to_rgba(nodeVolts[i]), zorder=5)
busLocations[busName] = [x, y]
i = i + 1
for genName, genInfo in networkJson["gen"].items():
x,y = busLocations[genInfo["bus"]]
plt.plot([x], [y], 's', color='gray', zorder=10, markersize=6.0)
for branchName, branchInfo in networkJson["branch"].items():
x1, y1 = busLocations[branchInfo["fbus"]]
x2, y2 = busLocations[branchInfo["tbus"]]
plt.plot([x1, x2], [y1,y2], color='black', marker = '', zorder=0)
plt.savefig(modelDir + '/output.png')
with open(pJoin(modelDir,"output.png"),"rb") as inFile:
outData["chart"] = inFile.read().encode("base64")
# Stdout/stderr.
outData["stdout"] = "Success"
outData["stderr"] = ""
return outData