voltControlRooftopScale.py

import json, os, argparse
from omf import feeder
from os.path import join as pJoin
import pandas as pd
import numpy as np
import csv
import omf
import re
from datetime import datetime
from voltageDropVoltageViz import drawPlot
import sys

def ConvertAndwork(filePath, gb_on_off='on', area=500):
	#Converts omd to glm, adds in necessary recorder, collector, and attributes+parameters for gridballast gld to run on waterheaters and ziploads
	with open(filePath, 'r') as inFile:
		if gb_on_off == 'on':
			gb_status = 'true'
		else:
			gb_status = 'false'
		print ("gridballast is "+gb_on_off)
		area = str(area)
		inFeeder = json.load(inFile)
		attachments = inFeeder.get('attachments',[])
		include_files = attachments.keys()
		if 'schedules.glm' in include_files:
			with open('schedules.glm', 'w') as outFile:
				outFile.write(attachments['schedules.glm'].encode('utf8'))
		if 'schedulesResponsiveLoads.glm' in include_files:
			with open('schedulesResponsiveLoads.glm', 'w') as outFile:
				outFile.write(attachments['schedulesResponsiveLoads.glm'].encode('utf8'))
		inFeeder['tree'][u'01'] = {u'omftype': u'#include', u'argument': u'"hot_water_demand1.glm"'}
		inFeeder['tree'][u'011'] = {u'class': u'player', u'double': u'value'}# add in manually for now
		inFeeder['tree'][u'0111'] = {u'object': u'voltdump', u'filename': u'voltDump.csv'}
		name_volt_dict ={}
		solar_meters=[]
		wind_obs=[]
		substation = None 
		rooftopSolars = []
		rooftopInverters =[]
		for key, value in inFeeder['tree'].iteritems():
			if 'name' in value and 'solar' in value['name']:
				inverter_ob = value['parent']
				for key, value in inFeeder['tree'].iteritems():
					if 'name' in value and value['name']==inverter_ob:
						solar_meters.append(value['parent'])
			if 'name' in value and 'wind' in value['name']:
				wind_obs.append(value['name'])
			if 'name' in value and 'nominal_voltage' in value:
				name_volt_dict[value['name']] = {'Nominal_Voltage': value['nominal_voltage']}
			if 'object' in value and (value['object'] == 'waterheater'):
				inFeeder['tree'][key].update({'heat_mode':'ELECTRIC'})
				inFeeder['tree'][key].update({'enable_volt_control':gb_status})
				inFeeder['tree'][key].update({'volt_lowlimit':'113.99'})
				inFeeder['tree'][key].update({'volt_uplimit':'126.99'}) 
				inFeeder['tree'][key].pop('demand')
				inFeeder['tree'][key].update({'water_demand':'weekday_hotwater*1.00'})
			if'object' in value and (value['object']== 'ZIPload'):
				inFeeder['tree'][key].update({'enable_volt_control':gb_status})
				inFeeder['tree'][key].update({'volt_lowlimit':'113.99'})
				inFeeder['tree'][key].update({'volt_uplimit':'126.99'})
			if 'object' in value and (value['object']== 'house'):
				houseMeter = value['parent']
				houseName = value['name']
				houseLon = str(value['longitude'])
				houseLat = str(value['latitude'])
				rooftopSolar_inverter = houseName+"_rooftop_inverter;"
				rooftopSolars.append("object solar {\n\tname "+houseName+"_rooftopSolar;\n\tparent "+rooftopSolar_inverter+"\n\tgenerator_status ONLINE;\n\tefficiency 0.2;\n\tlongitude "+houseLon+";\n\tgenerator_mode SUPPLY_DRIVEN;\n\tpanel_type SINGLE_CRYSTAL_SILICON;\n\tlatitude "+houseLat+";\n\tarea "+area+";\n\t};\n")
				rooftopInverters.append("object inverter {\n\tphases ABCN;\n\tpower_factor 1.0;\n\tname "+rooftopSolar_inverter+"\n\tparent "+houseMeter+";\n\tinverter_type PWM;\n\tlongitude "+houseLon+";\n\tgenerator_mode CONSTANT_PF;\n\tlatitude "+houseLat+";\n\t};\n")
			if 'argument' in value and ('minimum_timestep' in value['argument']):
					interval = int(re.search(r'\d+', value['argument']).group())
			if 'bustype' in value and 'SWING' in value['bustype']:
				substation = value['name']
				value['object'] = 'meter'
		# Create Collectors for different load objects in circuit
		collectorwat=("object collector {\n\tname collector_Waterheater;\n\tgroup class=waterheater;\n\tproperty sum(actual_load);\n\tinterval "+str(interval)+";\n\tfile out_load_waterheaters.csv;\n};\n")
		collectorz=("object collector {\n\tname collector_ZIPloads;\n\tgroup class=ZIPload;\n\tproperty sum(base_power);\n\tinterval "+str(interval)+";\n\tfile out_load_ziploads.csv;\n};\n")
		collectorh=("object collector {\n\tname collector_HVAC;\n\tgroup class=house;\n\tproperty sum(heating_demand), sum(cooling_demand);\n\tinterval "+str(interval)+";\n\tfile out_HVAC.csv;\n};\n")
		# Measure powerflow over Triplex meters, this will determine if solar is generating power. Negative powerflow means solar is generating. Positive means no. 
		collectorRoof=("object collector {\n\tname collector_rooftop;\n\tgroup class=triplex_meter;\n\tproperty sum(measured_real_power);\n\tinterval "+str(interval)+";\n\tfile out_load_triplex.csv;\n};\n")
		#Create recorder for substation powerflow
		recordersub=("object recorder {\n\tinterval "+str(interval)+";\n\tproperty measured_real_power;\n\tfile out_substation_power.csv;\n\tparent "+str(substation)+";\n\t};\n")
		# Create Create a recorder for a solar roof object, just to record powerflow over that unit
		# recorderSolarRoof = ("object recorder {\n\tinterval "+str(interval)+";\n\tproperty measured_real_power;\n\tfile out_standard_solar_roof.csv;\n\tparent nreca_synthetic_meter_11283;\n\t};\n")
		# Create arrays of solar objects and wind objects to attach recorders to. 
		recorders = []
		recorderw=[]
		for i in range(len(solar_meters)):
			recorders.append(("object recorder {\n\tinterval "+str(interval)+";\n\tproperty measured_real_power;\n\tfile out_solar_"+str(i)+".csv;\n\tparent "+str(solar_meters[i])+";\n\t};\n"))
		for i in range(len(wind_obs)):
			recorderw.append(("object recorder {\n\tinterval "+str(interval)+";\n\tproperty Pconv;\n\tfile out_wind_"+str(i)+".csv;\n\tparent "+str(wind_obs[i])+";\n\t};\n"))

	with open('outGLM_rooftop.glm', "w") as outFile:
		# Write collectors and recorders to end
		# addedString = collectorwat+collectorz+collectorh+recordersub+collectorRoof+recorderSolarRoof
		addedString = collectorwat+collectorz+collectorh+recordersub+collectorRoof
		for i in recorders:
			addedString = addedString+i
		for i in recorderw:
			addedString = addedString + i
		for i, j in zip(rooftopInverters, rooftopSolars):
			#Write the recorders for solar and wind objects to end of .glm
			addedString = addedString + i + j
		outFile.write(feeder.sortedWrite(inFeeder['tree'])+addedString)


	os.system(omf.omfDir +'/solvers/gridlabd_gridballast/local_gd/bin/gridlabd outGLM_rooftop.glm')

	return name_volt_dict

def ListOffenders(name_volt_dict):
	#Go thorugh volt dump, and find out the voltage magnitude of all phases.
	#Add to name_volt_dict dictionary which contains node names and their nominal voltage
	data = pd.read_csv(('voltDump.csv'), skiprows=[0])
	for i, row in data['voltA_real'].iteritems():
		voltA_real = data.loc[i,'voltA_real']
		voltA_imag = data.loc[i,'voltA_imag']
		voltA_mag = np.sqrt(np.add((voltA_real*voltA_real), (voltA_imag*voltA_imag)))
		name_volt_dict[data.loc[i, 'node_name']].update({'Volt_A':voltA_mag})
		voltB_real = data.loc[i,'voltB_real']
		voltB_imag = data.loc[i,'voltB_imag']
		voltB_mag = np.sqrt(np.add((voltB_real*voltB_real), (voltB_imag*voltB_imag)))
		name_volt_dict[data.loc[i, 'node_name']].update({'Volt_B':voltB_mag})
		voltC_real = data.loc[i,'voltC_real']
		voltC_imag = data.loc[i,'voltC_imag']
		voltC_mag = np.sqrt(np.add((voltC_real*voltC_real), (voltC_imag*voltC_imag)))
		name_volt_dict[data.loc[i, 'node_name']].update({'Volt_C':voltC_mag})
	offenders = []
	offendersGen = []
	for name, volt in name_volt_dict.iteritems():
		if name in data['node_name'].values:
			if (float(volt['Volt_A'])/float(volt['Nominal_Voltage'])) > 1.05:
				offenders.append(tuple([name, float(volt['Volt_A'])/float(volt['Nominal_Voltage'])]))
				offendersGen.append(name)
			if (float(volt['Volt_B'])/float(volt['Nominal_Voltage'])) > 1.05:
				offenders.append(tuple([name, float(volt['Volt_B'])/float(volt['Nominal_Voltage'])]))
				offendersGen.append(name)
			if (float(volt['Volt_C'])/float(volt['Nominal_Voltage'])) > 1.05:
				offenders.append(tuple([name, float(volt['Volt_C'])/float(volt['Nominal_Voltage'])]))
				offendersGen.append(name)

	#Run through name_volt_dict, compare nominal voltage with voltage magnitude of each phase. 
	#IF greater than allowed range (1.05) append to offenders and offendersGen
	#offenders is a tuple of the node name, and the ratio between measured voltage/nominal voltage
	#offendersGen is just a list of the offender node names


	#remove duplicates in list
	offenders = list(set(offenders))
	offendersGen = list(set(offendersGen))

	#Calculate average overdose factor
	isum = 0
	offendersNames = []
	if len(offendersGen) > 0:
		for i in range(len(offenders)):
			isum = isum + offenders[i][1]
		overdose_factor = isum/(len(offendersGen))
		print ("average voltage overdose is by a factor of", overdose_factor) 
	print ("Number of offenders is", len(offendersGen))
	# Write out file, list of offenders and their voltage overdose 
	with open('offenders.csv', 'w') as f:
		wr = csv.writer(f, quoting=csv.QUOTE_ALL)
		wr.writerow(offenders)
	return offendersGen

def writeResults(offendersGen):
	dir_path = os.path.dirname(os.path.realpath(__file__))
	#Write powerflow results for generation and waterheater, zipload, and hvac (house) load objects
	#need to fix up testing for if file exsists based upon name written
	substation = pd.read_csv(('out_substation_power.csv'), comment='#', names=['timestamp', 'measured_real_power'])
	substation_power = substation['measured_real_power'][0]
	ziploads =  pd.read_csv(('out_load_ziploads.csv'), comment='#', names=['timestamp', 'measured_real_power'])
	zipload_power = ziploads['measured_real_power'][0]
	waterheaters = pd.read_csv(('out_load_waterheaters.csv'), comment='#', names=['timestamp', 'measured_real_power'])
	waterheater_power = waterheaters['measured_real_power'][0]
	HVAC = pd.read_csv(('out_HVAC.csv'), comment='#', names=['timestamp', 'heating_power', 'cooling_power'])
	HVAC_power = HVAC['heating_power'][0], HVAC['cooling_power'][0]
	triplex_solar_use = pd.read_csv(('out_load_triplex.csv'), comment='#', names=['timestamp', 'measured_real_power'])
	triplex_solar_use_power = triplex_solar_use['measured_real_power'][0]
	wind_power = []
	solar_power = []
	for file in os.listdir(dir_path):
		if 'out_wind' in file:
			wind = pd.read_csv((file), comment='#', names=['timestamp', 'Pconv'])['Pconv'][0]
			wind_power.append(wind)
	for file in os.listdir(dir_path):
		if 'out_solar' in file:
			solar = pd.read_csv((file), comment='#', names=['timestamp', 'measured_real_power'])['measured_real_power'][0]
			solar_power.append(solar)

	#Print Results
	print "Substation power", substation_power
	print "Zipload Power Use", zipload_power*1000
	print "Waterheater Power Use", waterheater_power*1000
	print "HVAC Power Use", (HVAC_power[0]+HVAC_power[1])*1000
	print "Triplex/Rooftop solar use total", (triplex_solar_use_power)
	#convert results to watts, write to dataframe
	df=pd.DataFrame(columns=('result', 'value'))
	df.loc[0]=['current time', datetime.today()]
	df.loc[1]=["Number of offenders", len(offendersGen)]
	df.loc[2]=["Substation Power", substation_power]
	df.loc[3]=["Zipload Power Use", zipload_power*1000]
	df.loc[4]=["Waterheater Power Use", waterheater_power*1000]
	df.loc[5]=["HVAC Power Use", (HVAC_power[0]+HVAC_power[1])*1000]
	df.loc[6]=["Rooftop solar use", triplex_solar_use_power]
	for i, j in enumerate(solar_power):
		df.loc[len(df)+1]=["Solar Power" +str(i), j]
		print ("Solar Power" +str(i), j)
	for i, j in enumerate(wind_power):
		df.loc[len(df)+1]=["Wind Power"+str(i), j]
		print ("Wind Power"+str(i), j)
	#Write Dataframe to .csv
	df.to_csv('Results.csv')



def _debugging(filePath, gb_on_off='on', area=500, keepFiles='True'):
	#Begin Main Function
	name_volt_dict = ConvertAndwork(filePath, gb_on_off, area)
	offendersGen = ListOffenders(name_volt_dict)
	writeResults(offendersGen)
	# Open Distnetviz on glm
	omf.distNetViz.viz('outGLM_rooftop.glm') #or model.omd
	# Visualize Voltage Regulation
	# voltRegViz('outGLM_rooftop.glm')
	# 	Remove Feeder
	if keepFiles == False:
		for file in os.listdir(dir_path):
			if 'out' in file or file == 'voltDump.csv':
				os.remove(file)



def voltRegViz(FNAME):
	chart = drawPlot(FNAME, neatoLayout=True, edgeCol=None, nodeLabs=None, edgeLabs=None, nodeCol = "perUnitVoltage", customColormap=True, rezSqIn=400)
	chart.savefig("./VOLTOUT.png")
	validFiles = ['_minutes.PLAYER', 'climate.tmy2', 'frequency.PLAYER1', "hot_water_demand1.glm", 'schedulesResponsiveLoads.glm']
	#remove uncessary files from visualization directory
	dir_path = os.path.dirname(os.path.realpath(__file__))
	for file in os.listdir(pJoin(dir_path, '_voltViz')):
		if file not in validFiles : 
			os.remove(pJoin('_voltViz', file))

if __name__ == '__main__':
	dir_path = os.path.dirname(os.path.realpath(__file__))
	if len(sys.argv) == 1:
		for file in os.listdir(dir_path):
			if 'out' in file or file == 'voltDump.csv':
				os.remove(file)
		_debugging(pJoin(dir_path, 'Olin Barre GH.omd'), gb_on_off='on', area=2000, keepFiles='True')
	else:
		#Parse Command Line
		for file in os.listdir(dir_path):
			if 'out' in file or file == 'voltDump.csv':
				os.remove(file)
		parser = argparse.ArgumentParser(description='Converts an OMD to GLM and runs it on gridlabd')
		parser.add_argument('file_path', metavar='base', type=str,
		                    help='Path to OMD. Put in quotes.')
		parser.add_argument('gridballast_on_off', metavar='gb', type=str, help='turn gb on or off, type on or off')
		parser.add_argument('area_of_rooftop_solar', metavar='roof', type=int, help='enter integer size in sqft of rooftop solar')
		parser.add_argument('keepFiles', metavar='files', type=str, help='to keep output files enter true, otherwise false')
		args = parser.parse_args()
		filePath = args.file_path
		gb_on_off = args.gridballast_on_off
		area=args.area_of_rooftop_solar
		keepFiles = args.keepFiles
		_debugging(filePath, gb_on_off, area, keepFiles)