def GHPCheck(individual, pathRaw, Qnom, gv):
"""
Computes the geothermal availability and modifies the individual to
comply with it
Parameters
----------
individual : list
pathRaw : float
Qnom : float
Nominal installed capacity in the district heating plant
"""
areaArray = np.array(
pd.read_csv(pathRaw + "/Geothermal.csv", usecols=["Area_geo"]))
buildArray = np.array(
pd.read_csv(pathRaw + "/Geothermal.csv", usecols=["Name"]))
buildList = sFn.extractList(pathRaw + "/Total.csv")
indCombi = sFn.readCombi(individual)
Qallowed = 0
for index, buildName in zip(indCombi, buildList):
if index == "1":
areaAvail = areaArray[np.where(buildArray == buildName)[0][0]][0]
Qallowed += np.ceil(
areaAvail / gv.GHP_A) * gv.GHP_HmaxSize #[W_th]
print Qallowed, "Qallowed"
if Qallowed < individual[11] * Qnom:
print "GHP share modified !"
if Qallowed < 1E-3:
oldValue = individual[11]
shareLoss = individual[11]
individual[10] = 0
individual[11] = 0
else:
oldValue = individual[11]
shareLoss = oldValue - Qallowed / Qnom
individual[11] = Qallowed / Qnom
# Adapt the other shares
nPlant = 0
for i in range(gv.nHeat - 1):
if individual[2 * i] > 0:
nPlant += 1
individual[2 * i +
1] += individual[2 * i + 1] * shareLoss / (1 -
oldValue)
if nPlant == 0: # there was only the GHP --> replaced by only NG Boiler
individual[2] = 1
individual[3] = 1 - individual[11]
def GHPCheck(individual, pathRaw, Qnom, gv):
"""
Computes the geothermal availability and modifies the individual to
comply with it
Parameters
----------
individual : list
pathRaw : float
Qnom : float
Nominal installed capacity in the district heating plant
"""
areaArray = np.array( pd.read_csv( pathRaw + "/Geothermal.csv", usecols=["Area_geo"] ) )
buildArray = np.array( pd.read_csv( pathRaw + "/Geothermal.csv", usecols=["Name"] ) )
buildList = sFn.extractList(pathRaw + "/Total.csv")
indCombi = sFn.readCombi(individual)
Qallowed = 0
for index, buildName in zip(indCombi, buildList):
if index == "1":
areaAvail = areaArray[ np.where(buildArray == buildName)[0][0] ][0]
Qallowed += np.ceil(areaAvail/gv.GHP_A) * gv.GHP_HmaxSize #[W_th]
print Qallowed, "Qallowed"
if Qallowed < individual[11] * Qnom:
print "GHP share modified !"
if Qallowed < 1E-3:
oldValue = individual[11]
shareLoss = individual[11]
individual[10] =0
individual[11] =0
else:
oldValue = individual[11]
shareLoss = oldValue - Qallowed / Qnom
individual[11] = Qallowed / Qnom
# Adapt the other shares
nPlant = 0
for i in range(gv.nHeat - 1):
if individual[2*i] > 0:
nPlant += 1
individual[2*i+1] += individual[2*i+1] * shareLoss / (1-oldValue)
if nPlant == 0: # there was only the GHP --> replaced by only NG Boiler
individual[2] = 1
individual[3] = 1-individual[11]
def decentralizeCosts(individual, pathX, gV):
indCombi = sFn.readCombi(individual, gV)
buildList = sFn.extractList(pathX.pathRaw + "/Total.csv")
costsDisc = 0
for i in range(len(indCombi)):
if indCombi[i] == "0": # Decentralized building
buildName = buildList[i]
DecentFile = pathX.pathDiscRes + "/DiscOp_" + buildName + "_result.csv"
df = pd.read_csv(DecentFile)
dfBest = df[df["Best configuration"] == 1]
costsDisc += dfBest["Annualized Investment Costs [CHF]"].iloc[0]
print costsDisc, "costsDisc"
return costsDisc
def decentralizeCosts(individual, pathX, gV):
indCombi = sFn.readCombi(individual, gV)
buildList = sFn.extractList(pathX.pathRaw + "/Total.csv")
costsDisc = 0
for i in range(len(indCombi)):
if indCombi[i] == "0": # Decentralized building
buildName = buildList[i]
DecentFile = pathX.pathDiscRes + "/DiscOp_" + buildName + "_result.csv"
df = pd.read_csv(DecentFile)
dfBest = df[df["Best configuration"] == 1]
costsDisc += dfBest["Annualized Investment Costs [CHF]"].iloc[0]
print costsDisc, "costsDisc"
return costsDisc
def checkNtw(individual, ntwList, locator, gv):
"""
Calls the network routine if necessary
Parameters
----------
individual : list
configuration considered
ntwList : list
list of DHN configuration previously encountered in the EA
locator : string
path to folders
"""
indCombi = sFn.readCombi(individual, gv)
print(indCombi)
if not (indCombi in ntwList) and indCombi.count("1") > 0:
ntwList.append(indCombi)
if indCombi.count("1") == 1:
total_demand = pd.read_csv(locator.pathNtwRes + "//" + "Total_" +
indCombi + ".csv")
building_names = total_demand.Name.values
print "Direct launch of network summary routine for", indCombi
nM.Network_Summary(locator, total_demand, building_names, gv,
indCombi)
else:
total_demand = sFn.createTotalNtwCsv(indCombi, locator)
building_names = total_demand.Name.values
# Run the substation and network routines
print "Re-run the substation routine for new network configuration", indCombi
sMain.subsMain(locator, total_demand, building_names, gv, indCombi)
print "Launch network summary routine"
nM.Network_Summary(locator, total_demand, building_names, gv,
indCombi)
def checkNtw(individual, ntwList, locator, gv):
"""
Calls the network routine if necessary
Parameters
----------
individual : list
configuration considered
ntwList : list
list of DHN configuration previously encountered in the EA
locator : string
path to folders
"""
indCombi = sFn.readCombi(individual, gv)
print(indCombi)
if not (indCombi in ntwList) and indCombi.count("1") > 0:
ntwList.append(indCombi)
if indCombi.count("1") == 1:
total_demand = pd.read_csv(locator.pathNtwRes + "//" + "Total_" + indCombi + ".csv")
building_names = total_demand.Name.values
print "Direct launch of network summary routine for", indCombi
nM.Network_Summary(locator, total_demand, building_names, gv, indCombi)
else:
total_demand = sFn.createTotalNtwCsv(indCombi, locator)
building_names = total_demand.Name.values
# Run the substation and network routines
print "Re-run the substation routine for new network configuration", indCombi
sMain.subsMain(locator, total_demand, building_names, gv, indCombi)
print "Launch network summary routine"
nM.Network_Summary(locator, total_demand, building_names, gv, indCombi)
def evalInd(individual, buildList, locator, extraCosts, extraCO2, extraPrim,
solarFeat, ntwFeat, gv):
"""
Evaluates an individual
Parameters
----------
individual : list
buildList : list of buildings in the district
pahthX : string
extraX : float
parameters previously computed
solarFeat / ntwFeat : class solarFeatures / ntwFeatures
Returns
-------
(costs, CO2, Prim) : tuple of floats
"""
print "Evaluate an individual"
print individual, "\n"
print "Check the individual"
nBuildings = len(buildList)
cCheck.controlCheck(individual, nBuildings, gv)
indCombi = sFn.readCombi(individual, gv)
costs = extraCosts
CO2 = extraCO2
prim = extraPrim
QUncoveredDesign = 0
QUncoveredAnnual = 0
print indCombi.count("0")
print indCombi.count("1")
if indCombi.count("0") == 0:
fNameNtw = "Network_summary_result_all.csv"
else:
fNameNtw = "Network_summary_result_" + indCombi + ".csv"
if indCombi.count("1") > 0:
Qheatmax = sFn.calcQmax(fNameNtw, locator.pathNtwRes, gv)
else:
Qheatmax = 0
print Qheatmax, "Qheatmax in network"
Qnom = Qheatmax * (1 + gv.Qmargin_ntw)
# Modify the individual with the extra GHP constraint
try:
cCheck.GHPCheck(individual, locator.pathRaw, Qnom, gv)
print "GHP constraint checked \n"
except:
print "No GHP constraint check possible \n"
# Export to context
dicoSupply = readInd(individual, Qheatmax, locator, gv)
dicoSupply.NETWORK_DATA_FILE = fNameNtw
if dicoSupply.nBuildingsConnected > 1:
if indCombi.count("0") == 0:
dicoSupply.fNameTotalCSV = locator.pathRaw + "/Total.csv"
else:
dicoSupply.fNameTotalCSV = locator.pathTotalNtw + "/Total_" + indCombi + ".csv"
else:
dicoSupply.fNameTotalCSV = locator.pathSubsRes + "/Total_" + indCombi + ".csv"
if indCombi.count("1") > 0:
#print "Dummy evaluation of", dicoSupply.configKey
#(slavePrim, slaveCO2, slaveCosts, QUncoveredDesign, QUncoveredAnnual) = sFn.dummyevaluate(individual)
print "Slave routine on", dicoSupply.configKey
(slavePrim, slaveCO2, slaveCosts, QUncoveredDesign,
QUncoveredAnnual) = sM.slaveMain(locator, fNameNtw, dicoSupply,
solarFeat, gv)
print slaveCosts, slaveCO2, slavePrim, "slaveCosts, slaveCO2, slavePrim \n"
costs += slaveCosts
CO2 += slaveCO2
prim += slavePrim
else:
print "No buildings connected to network \n"
print "Add extra costs"
(addCosts, addCO2, addPrim) = eM.addCosts(indCombi, buildList, locator,
dicoSupply, QUncoveredDesign,
QUncoveredAnnual, solarFeat,
ntwFeat, gv)
print addCosts, addCO2, addPrim, "addCosts, addCO2, addPrim \n"
if gv.ZernezFlag == 1:
coolCosts, coolCO2, coolPrim = 0, 0, 0
else:
(coolCosts, coolCO2, coolPrim) = coolMain.coolingMain(
locator, dicoSupply.configKey, ntwFeat,
dicoSupply.WasteServersHeatRecovery, gv)
print coolCosts, coolCO2, coolPrim, "coolCosts, coolCO2, coolPrim \n"
costs += addCosts + coolCosts
CO2 += addCO2 + coolCO2
prim += addPrim + coolPrim
print "Evaluation of", dicoSupply.configKey, "done"
print costs, CO2, prim, " = costs, CO2, prim \n"
return (costs, CO2, prim)
def readInd(individual, Qmax, locator, gv):
"""
Reads the list encoding a configuration and implementes the corresponding
for the slave routine's to use
Parameters
----------
individual : list
configuration from the Master routine
Qmax : float
peak heating demand
locator : string
path to raw files
Returns
-------
dicoSupply : class MasterSlaveVariables
"""
dicoSupply = MSVar.MasterSlaveVariables()
dicoSupply.configKey = "".join(str(e)[0:4] for e in individual)
indCombi = sFn.readCombi(individual, gv)
dicoSupply.nBuildingsConnected = indCombi.count(
"1") # counting the number of buildings connected
Qnom = Qmax * (1 + gv.Qmargin_ntw)
# Heating systems
#CHP units with NG & furnace with biomass wet
if individual[0] == 1 or individual[0] == 3:
if gv.Furnace_allowed == 1:
dicoSupply.Furnace_on = 1
dicoSupply.Furnace_Q_max = max(individual[1] * Qnom,
gv.QminShare * Qnom)
print dicoSupply.Furnace_Q_max, "Furnace wet"
dicoSupply.Furn_Moist_type = "wet"
elif gv.CC_allowed == 1:
dicoSupply.CC_on = 1
dicoSupply.CC_GT_SIZE = max(individual[1] * Qnom * 1.3,
gv.QminShare * Qnom * 1.3)
#1.3 is the conversion factor between the GT_Elec_size NG and Q_DHN
print dicoSupply.CC_GT_SIZE, "CC NG"
dicoSupply.gt_fuel = "NG"
#CHP units with BG& furnace with biomass dry
if individual[0] == 2 or individual[0] == 4:
if gv.Furnace_allowed == 1:
dicoSupply.Furnace_on = 1
dicoSupply.Furnace_Q_max = max(individual[1] * Qnom,
gv.QminShare * Qnom)
print dicoSupply.Furnace_Q_max, "Furnace dry"
dicoSupply.Furn_Moist_type = "dry"
elif gv.CC_allowed == 1:
dicoSupply.CC_on = 1
dicoSupply.CC_GT_SIZE = max(individual[1] * Qnom * 1.5,
gv.QminShare * Qnom * 1.5)
#1.5 is the conversion factor between the GT_Elec_size BG and Q_DHN
print dicoSupply.CC_GT_SIZE, "CC BG"
dicoSupply.gt_fuel = "BG"
# Base boiler NG
if individual[2] == 1:
dicoSupply.Boiler_on = 1
dicoSupply.Boiler_Q_max = max(individual[3] * Qnom,
gv.QminShare * Qnom)
print dicoSupply.Boiler_Q_max, "Boiler base NG"
dicoSupply.BoilerType = "NG"
# Base boiler BG
if individual[2] == 2:
dicoSupply.Boiler_on = 1
dicoSupply.Boiler_Q_max = max(individual[3] * Qnom,
gv.QminShare * Qnom)
print dicoSupply.Boiler_Q_max, "Boiler base BG"
dicoSupply.BoilerType = "BG"
# peak boiler NG
if individual[4] == 1:
dicoSupply.BoilerPeak_on = 1
dicoSupply.BoilerPeak_Q_max = max(individual[5] * Qnom,
gv.QminShare * Qnom)
print dicoSupply.BoilerPeak_Q_max, "Boiler peak NG"
dicoSupply.BoilerPeakType = "NG"
# peak boiler BG
if individual[4] == 2:
dicoSupply.BoilerPeak_on = 1
dicoSupply.BoilerPeak_Q_max = max(individual[5] * Qnom,
gv.QminShare * Qnom)
print dicoSupply.BoilerPeak_Q_max, "Boiler peak BG"
dicoSupply.BoilerPeakType = "BG"
# lake - heat pump
if individual[6] == 1 and gv.HPLake_allowed == 1:
dicoSupply.HP_Lake_on = 1
dicoSupply.HPLake_maxSize = max(individual[7] * Qnom,
gv.QminShare * Qnom)
print dicoSupply.HPLake_maxSize, "Lake"
# sewage - heatpump
if individual[8] == 1 and gv.HPSew_allowed == 1:
dicoSupply.HP_Sew_on = 1
dicoSupply.HPSew_maxSize = max(individual[9] * Qnom,
gv.QminShare * Qnom)
print dicoSupply.HPSew_maxSize, "Sewage"
# Gwound source- heatpump
if individual[10] == 1 and gv.GHP_allowed == 1:
dicoSupply.GHP_on = 1
GHP_Qmax = max(individual[11] * Qnom, gv.QminShare * Qnom)
dicoSupply.GHP_number = GHP_Qmax / gv.GHP_HmaxSize
print GHP_Qmax, "GHP"
# heat recovery servers and compresor
irank = gv.nHeat * 2
dicoSupply.WasteServersHeatRecovery = individual[irank]
dicoSupply.WasteCompressorHeatRecovery = individual[irank + 1]
# Solar systems
roof_area = np.array(
pd.read_csv(locator.get_total_demand(), usecols=["Aroof_m2"]))
areaAvail = 0
totalArea = 0
for i in range(len(indCombi)):
index = indCombi[i]
if index == "1":
areaAvail += roof_area[i][0]
totalArea += roof_area[i][0]
shareAvail = areaAvail / totalArea
irank = gv.nHeat * 2 + gv.nHR
dicoSupply.SOLAR_PART_PV = max(
individual[irank] * individual[irank + 1] * individual[irank + 6] *
shareAvail, 0)
print dicoSupply.SOLAR_PART_PV, "PV"
dicoSupply.SOLAR_PART_PVT = max(
individual[irank + 2] * individual[irank + 3] * individual[irank + 6] *
shareAvail, 0)
print dicoSupply.SOLAR_PART_PVT, "PVT"
dicoSupply.SOLAR_PART_SC = max(
individual[irank + 4] * individual[irank + 5] * individual[irank + 6] *
shareAvail, 0)
print dicoSupply.SOLAR_PART_SC, "SC"
return dicoSupply
def readInd(individual, Qmax, locator, gv):
"""
Reads the list encoding a configuration and implementes the corresponding
for the slave routine's to use
Parameters
----------
individual : list
configuration from the Master routine
Qmax : float
peak heating demand
locator : string
path to raw files
Returns
-------
dicoSupply : class MasterSlaveVariables
"""
dicoSupply = MSVar.MasterSlaveVariables()
dicoSupply.configKey = "".join(str(e)[0:4] for e in individual)
indCombi = sFn.readCombi(individual, gv)
dicoSupply.nBuildingsConnected = indCombi.count("1") # counting the number of buildings connected
Qnom = Qmax * (1+gv.Qmargin_ntw)
# Heating systems
#CHP units with NG & furnace with biomass wet
if individual[0] == 1 or individual[0] == 3:
if gv.Furnace_allowed == 1:
dicoSupply.Furnace_on = 1
dicoSupply.Furnace_Q_max = max(individual[1] * Qnom, gv.QminShare * Qnom)
print dicoSupply.Furnace_Q_max, "Furnace wet"
dicoSupply.Furn_Moist_type = "wet"
elif gv.CC_allowed == 1:
dicoSupply.CC_on = 1
dicoSupply.CC_GT_SIZE = max(individual[1] * Qnom * 1.3, gv.QminShare * Qnom * 1.3)
#1.3 is the conversion factor between the GT_Elec_size NG and Q_DHN
print dicoSupply.CC_GT_SIZE, "CC NG"
dicoSupply.gt_fuel = "NG"
#CHP units with BG& furnace with biomass dry
if individual[0] == 2 or individual[0] == 4:
if gv.Furnace_allowed == 1:
dicoSupply.Furnace_on = 1
dicoSupply.Furnace_Q_max = max(individual[1] * Qnom, gv.QminShare * Qnom)
print dicoSupply.Furnace_Q_max, "Furnace dry"
dicoSupply.Furn_Moist_type = "dry"
elif gv.CC_allowed == 1:
dicoSupply.CC_on = 1
dicoSupply.CC_GT_SIZE = max(individual[1] * Qnom * 1.5, gv.QminShare * Qnom * 1.5)
#1.5 is the conversion factor between the GT_Elec_size BG and Q_DHN
print dicoSupply.CC_GT_SIZE, "CC BG"
dicoSupply.gt_fuel = "BG"
# Base boiler NG
if individual[2] == 1:
dicoSupply.Boiler_on = 1
dicoSupply.Boiler_Q_max = max(individual[3] * Qnom, gv.QminShare * Qnom)
print dicoSupply.Boiler_Q_max, "Boiler base NG"
dicoSupply.BoilerType = "NG"
# Base boiler BG
if individual[2] == 2:
dicoSupply.Boiler_on = 1
dicoSupply.Boiler_Q_max = max(individual[3] * Qnom, gv.QminShare * Qnom)
print dicoSupply.Boiler_Q_max, "Boiler base BG"
dicoSupply.BoilerType = "BG"
# peak boiler NG
if individual[4] == 1:
dicoSupply.BoilerPeak_on = 1
dicoSupply.BoilerPeak_Q_max = max(individual[5] * Qnom, gv.QminShare * Qnom)
print dicoSupply.BoilerPeak_Q_max, "Boiler peak NG"
dicoSupply.BoilerPeakType = "NG"
# peak boiler BG
if individual[4] == 2:
dicoSupply.BoilerPeak_on = 1
dicoSupply.BoilerPeak_Q_max = max(individual[5] * Qnom, gv.QminShare * Qnom)
print dicoSupply.BoilerPeak_Q_max, "Boiler peak BG"
dicoSupply.BoilerPeakType = "BG"
# lake - heat pump
if individual[6] == 1 and gv.HPLake_allowed == 1:
dicoSupply.HP_Lake_on = 1
dicoSupply.HPLake_maxSize = max(individual[7] * Qnom, gv.QminShare * Qnom)
print dicoSupply.HPLake_maxSize, "Lake"
# sewage - heatpump
if individual[8] == 1 and gv.HPSew_allowed == 1:
dicoSupply.HP_Sew_on = 1
dicoSupply.HPSew_maxSize = max(individual[9] * Qnom, gv.QminShare * Qnom)
print dicoSupply.HPSew_maxSize, "Sewage"
# Gwound source- heatpump
if individual[10] == 1 and gv.GHP_allowed == 1:
dicoSupply.GHP_on = 1
GHP_Qmax = max(individual[11] * Qnom, gv.QminShare * Qnom)
dicoSupply.GHP_number = GHP_Qmax / gv.GHP_HmaxSize
print GHP_Qmax, "GHP"
# heat recovery servers and compresor
irank = gv.nHeat * 2
dicoSupply.WasteServersHeatRecovery = individual[irank]
dicoSupply.WasteCompressorHeatRecovery = individual[irank + 1]
# Solar systems
roof_area = np.array(pd.read_csv(locator.get_total_demand(), usecols=["Aroof_m2"]))
areaAvail = 0
totalArea = 0
for i in range( len(indCombi) ):
index = indCombi[i]
if index == "1":
areaAvail += roof_area[i][0]
totalArea += roof_area[i][0]
shareAvail = areaAvail / totalArea
irank = gv.nHeat * 2 + gv.nHR
dicoSupply.SOLAR_PART_PV = max(individual[irank] * individual[irank + 1] * individual[irank + 6] * shareAvail,0)
print dicoSupply.SOLAR_PART_PV, "PV"
dicoSupply.SOLAR_PART_PVT = max(individual[irank + 2] * individual[irank + 3] * individual[irank + 6] * shareAvail,0)
print dicoSupply.SOLAR_PART_PVT, "PVT"
dicoSupply.SOLAR_PART_SC = max(individual[irank + 4] * individual[irank + 5] * individual[irank + 6] * shareAvail,0)
print dicoSupply.SOLAR_PART_SC, "SC"
return dicoSupply
def evalInd(individual, buildList, locator, extraCosts, extraCO2, extraPrim, solarFeat, ntwFeat, gv):
"""
Evaluates an individual
Parameters
----------
individual : list
buildList : list of buildings in the district
pahthX : string
extraX : float
parameters previously computed
solarFeat / ntwFeat : class solarFeatures / ntwFeatures
Returns
-------
(costs, CO2, Prim) : tuple of floats
"""
print "Evaluate an individual"
print individual, "\n"
print "Check the individual"
nBuildings = len(buildList)
cCheck.controlCheck(individual, nBuildings, gv)
indCombi = sFn.readCombi(individual, gv)
costs = extraCosts
CO2 = extraCO2
prim = extraPrim
QUncoveredDesign = 0
QUncoveredAnnual = 0
print indCombi.count("0")
print indCombi.count("1")
if indCombi.count("0") == 0:
fNameNtw = "Network_summary_result_all.csv"
else:
fNameNtw = "Network_summary_result_" + indCombi + ".csv"
if indCombi.count("1") > 0:
Qheatmax = sFn.calcQmax(fNameNtw, locator.pathNtwRes, gv)
else:
Qheatmax = 0
print Qheatmax, "Qheatmax in network"
Qnom = Qheatmax * (1+gv.Qmargin_ntw)
# Modify the individual with the extra GHP constraint
try:
cCheck.GHPCheck(individual, locator.pathRaw, Qnom, gv)
print "GHP constraint checked \n"
except:
print "No GHP constraint check possible \n"
# Export to context
dicoSupply = readInd(individual, Qheatmax, locator, gv)
dicoSupply.NETWORK_DATA_FILE = fNameNtw
if dicoSupply.nBuildingsConnected > 1:
if indCombi.count("0") == 0:
dicoSupply.fNameTotalCSV = locator.pathRaw + "/Total.csv"
else:
dicoSupply.fNameTotalCSV = locator.pathTotalNtw + "/Total_" + indCombi + ".csv"
else:
dicoSupply.fNameTotalCSV = locator.pathSubsRes + "/Total_" + indCombi + ".csv"
if indCombi.count("1") > 0:
#print "Dummy evaluation of", dicoSupply.configKey
#(slavePrim, slaveCO2, slaveCosts, QUncoveredDesign, QUncoveredAnnual) = sFn.dummyevaluate(individual)
print "Slave routine on", dicoSupply.configKey
(slavePrim, slaveCO2, slaveCosts, QUncoveredDesign, QUncoveredAnnual) = sM.slaveMain(locator, fNameNtw, dicoSupply, solarFeat, gv)
print slaveCosts, slaveCO2, slavePrim, "slaveCosts, slaveCO2, slavePrim \n"
costs += slaveCosts
CO2 += slaveCO2
prim += slavePrim
else:
print "No buildings connected to network \n"
print "Add extra costs"
(addCosts, addCO2, addPrim) = eM.addCosts(indCombi, buildList, locator, dicoSupply, QUncoveredDesign, QUncoveredAnnual, solarFeat, ntwFeat, gv)
print addCosts, addCO2, addPrim, "addCosts, addCO2, addPrim \n"
if gv.ZernezFlag == 1:
coolCosts, coolCO2, coolPrim = 0,0,0
else:
(coolCosts, coolCO2, coolPrim) = coolMain.coolingMain(locator, dicoSupply.configKey, ntwFeat, dicoSupply.WasteServersHeatRecovery, gv)
print coolCosts, coolCO2, coolPrim, "coolCosts, coolCO2, coolPrim \n"
costs += addCosts + coolCosts
CO2 += addCO2 + coolCO2
prim += addPrim + coolPrim
print "Evaluation of", dicoSupply.configKey, "done"
print costs, CO2, prim, " = costs, CO2, prim \n"
return (costs, CO2, prim)
def mcda_indicators(individual, pathX, plot = 0):
"""
Computes the specific operational costs and the share of local resources
"""
configKey = "".join(str(e)[0:4] for e in individual)
print configKey
buildList = sFn.extractList(pathX.pathRaw + "/Total.csv")
gV = glob.globalVariables()
# Recover data from the PP activation file
resourcesFile = pathX.pathSlaveRes + "/" + configKey + "PPActivationPattern.csv"
resourcesdf = pd.read_csv(resourcesFile, usecols=["ESolarProducedPVandPVT", "Q_AddBoiler", "Q_BoilerBase", "Q_BoilerPeak", "Q_CC", "Q_GHP", \
"Q_HPLake", "Q_HPSew", "Q_primaryAddBackupSum", "Q_uncontrollable"])
Electricity_Solar = resourcesdf.ESolarProducedPVandPVT.sum()
Q_AddBoiler = resourcesdf.Q_AddBoiler.sum()
Q_BoilerBase = resourcesdf.Q_BoilerBase.sum()
Q_BoilerPeak = resourcesdf.Q_BoilerPeak.sum()
Q_CC = resourcesdf.Q_CC.sum()
Q_GHP = resourcesdf.Q_GHP.sum()
Q_HPLake = resourcesdf.Q_HPLake.sum()
Q_HPSew = resourcesdf.Q_HPSew.sum()
Q_storage_missmatch = resourcesdf.Q_primaryAddBackupSum.sum()
Q_uncontrollable = resourcesdf.Q_uncontrollable.sum()
# Recover data from the Storage Operation file
resourcesFile = pathX.pathSlaveRes + "/" + configKey + "StorageOperationData.csv"
resourcesdf = pd.read_csv(resourcesFile, usecols=["Q_SCandPVT_coldstream"])
Q_fromSolar = resourcesdf.Q_SCandPVT_coldstream.sum()
# Recover heating needs for decentralized buildings
indCombi = sFn.readCombi(individual, gV)
QfromNG = 0
QfromBG = 0
QfromGHP = 0
for i in range(len(indCombi)):
if indCombi[i] == "0": # Decentralized building
buildName = buildList[i]
DescentFile = pathX.pathDiscRes + "/DiscOp_" + buildName + "_result.csv"
df = pd.read_csv(DescentFile)
dfBest = df[ df["Best configuration"] == 1 ]
QfromNG += dfBest["QfromNG"].iloc[0]
QfromBG += dfBest["QfromBG"].iloc[0]
QfromGHP += dfBest["QfromGHP"].iloc[0]
# Recover electricity and cooling needs
totalFile = pathX.pathRaw + "/Total.csv"
df = pd.read_csv(totalFile, usecols=["Ealf", "Eauxf", "Ecaf", "Edataf", "Epf"])
arrayTotal = np.array(df)
totalElec = np.sum(arrayTotal) * 1E6 # [Wh]
df = pd.read_csv(totalFile, usecols=["Qcdataf", "Qcicef", "Qcpf", "Qcsf"])
arrayTotal = np.array(df)
if individual[12] == 0:
totalCool = ( np.sum((arrayTotal)[:,:-1]) + np.sum((arrayTotal)[:,-1:]) * (1+gV.DCNetworkLoss) ) * 1E6 # [Wh]
else:
totalCool = ( np.sum((arrayTotal)[:,1:-1]) + np.sum((arrayTotal)[:,-1:]) * (1+gV.DCNetworkLoss) ) * 1E6 # [Wh]
# Computes the specific operational costs
totalEnergy = Q_AddBoiler + Q_BoilerBase + Q_BoilerPeak + Q_CC + Q_GHP + Q_HPLake + \
Q_HPSew + Q_uncontrollable + totalElec + totalCool + \
QfromNG + QfromBG + QfromGHP# + Q_storage_missmatch
shareCC_NG = individual[0] % 2 * Q_CC / totalEnergy
shareCC_BG = ( individual[0] + 1 ) % 2 * Q_CC / totalEnergy
shareBB_NG = individual[2] % 2 * Q_BoilerBase / totalEnergy
shareBB_BG = ( individual[2] + 1 ) % 2 * Q_BoilerBase / totalEnergy
shareBP_NG = individual[4] % 2 * Q_BoilerPeak / totalEnergy
shareBP_BG = ( individual[4] + 1 ) % 2 * Q_BoilerPeak / totalEnergy
shareHPLake = Q_HPLake / totalEnergy
shareHPSew = Q_HPSew / totalEnergy
shareGHP = Q_GHP / totalEnergy
shareExtraNG = (Q_AddBoiler + Q_storage_missmatch) / totalEnergy
shareHR = (Q_uncontrollable - Q_fromSolar) / totalEnergy
shareHeatSolar = Q_fromSolar / totalEnergy
shareDecentralizedNG = QfromNG / totalEnergy
shareDecentralizedBG = QfromBG / totalEnergy
shareDecentralizedGHP = QfromGHP / totalEnergy
shareElecGrid = (totalElec - Electricity_Solar) / totalEnergy
shareElecSolar = Electricity_Solar / totalEnergy
shareCoolLake = totalCool / totalEnergy
printout = 1
if printout:
print 'CC_NG', individual[0] % 2 * Q_CC
print 'CC_BG', ( individual[0] + 1 ) % 2 * Q_CC
print 'BB_NG', individual[2] % 2 * Q_BoilerBase
print 'BB_BG', ( individual[2] + 1 ) % 2 * Q_BoilerBase
print 'BP_NG', individual[4] % 2 * Q_BoilerPeak
print 'BP_BG', ( individual[4] + 1 ) % 2 * Q_BoilerPeak
print 'HPLake', Q_HPLake
print 'HPSew', Q_HPSew
print 'GHP', Q_GHP
print 'ExtraNG', (Q_AddBoiler + Q_storage_missmatch)
print 'HR', (Q_uncontrollable - Q_fromSolar)
print 'HeatSolar', Q_fromSolar
print 'DecentralizedNG', QfromNG
print 'DecentralizedBG', QfromBG
print 'DecentralizedGHP', QfromGHP
print 'ElecGrid', (totalElec - Electricity_Solar)
print 'ElecSolar', Electricity_Solar
print 'CoolLake', totalCool
print 'shareCC_NG', shareCC_NG*100
print 'shareCC_BG', shareCC_BG*100
print 'shareBB_NG', shareBB_NG*100
print 'shareBB_BG', shareBB_BG*100
print 'shareBP_NG', shareBP_NG*100
print 'shareBP_BG', shareBP_BG*100
print 'shareHPLake', shareHPLake*100
print 'shareHPSew', shareHPSew*100
print 'shareGHP', shareGHP*100
print 'shareExtraNG', shareExtraNG*100
print 'shareHR', shareHR*100
print 'shareHeatSolar', shareHeatSolar*100
print 'shareDecentralizedNG', shareDecentralizedNG*100
print 'shareDecentralizedBG', shareDecentralizedBG*100
print 'shareDecentralizedGHP', shareDecentralizedGHP*100
print 'shareElecGrid' ,shareElecGrid*100
print 'shareElecSolar', shareElecSolar*100
print 'shareCoolLake', shareCoolLake*100
specificCosts = gV.ELEC_PRICE * shareElecGrid + \
gV.NG_PRICE * (shareCC_NG + shareBB_NG + shareBP_NG + shareExtraNG + shareDecentralizedNG) + \
gV.BG_PRICE * (shareCC_BG + shareBB_BG + shareBP_BG + shareDecentralizedBG)
# Computes the share of local resources
shareLocal = shareHPLake + shareHPSew + shareGHP + shareHR + shareHeatSolar + shareDecentralizedGHP + shareElecSolar + shareCoolLake
# Plots the pie chart for energy resources use
if plot == 1:
fig = plt.figure()
subplot = fig.add_subplot(111, adjustable = 'box', aspect = 1, title = 'Energy mix')
labels = ['Lake', 'Solar', 'HR', 'Ground', 'Gas', 'Grid']
shareLake = shareHPLake + shareCoolLake
shareSolar = shareHeatSolar + shareElecSolar
shareHRAll = shareHPSew + shareHR
shareGround = shareGHP + shareDecentralizedGHP
shareGas = 1 - shareLake - shareSolar - shareHRAll - shareGround - shareElecGrid
fracs = [ shareLake, shareSolar, shareHRAll, shareGround, shareGas, shareElecGrid ]
colors = ['RoyalBlue', 'Gold', 'LightGreen', 'SandyBrown', 'OrangeRed', 'Gray']
zipper = [ (l,f,c) for (l,f,c) in zip(labels,fracs,colors) if f > 0.001 ]
labelsPlot, fracsPlot, colorsPlot = map( list, zip(*zipper) )
subplot.pie(fracsPlot, labels = labelsPlot, colors = colorsPlot, startangle = 90, autopct='%1.1f%%', pctdistance = 0.65)
plt.show()
return specificCosts, shareLocal
