def checkNtw(individual, DHN_network_list, DCN_network_list, locator, gv,
config, building_names):
"""
This function calls the distribution routine if necessary
:param individual: network configuration considered
:param ntwList: list of DHN configurations previously encounterd in the master
:param locator: path to the folder
:type individual: list
:type ntwList: list
:type locator: string
:return: None
:rtype: Nonetype
"""
DHN_barcode, DCN_barcode, DHN_configuration, DCN_configuration = supportFn.individual_to_barcode(
individual, building_names)
if not (DHN_barcode in DHN_network_list) and DHN_barcode.count("1") > 0:
DHN_network_list.append(DHN_barcode)
total_demand = supportFn.createTotalNtwCsv(DHN_barcode, locator)
building_names = total_demand.Name.values
# Run the substation and distribution routines
substation.substation_main(locator,
total_demand,
building_names,
DHN_configuration,
DCN_configuration,
Flag=True)
summarize_network.network_main(locator, total_demand, building_names,
config, gv, DHN_barcode)
if not (DCN_barcode in DCN_network_list) and DCN_barcode.count("1") > 0:
DCN_network_list.append(DCN_barcode)
total_demand = supportFn.createTotalNtwCsv(DCN_barcode, locator)
building_names = total_demand.Name.values
# Run the substation and distribution routines
substation.substation_main(locator,
total_demand,
building_names,
DHN_configuration,
DCN_configuration,
Flag=True)
summarize_network.network_main(locator, total_demand, building_names,
config, gv, DCN_barcode)
def checkNtw(individual, ntwList, locator, gv):
"""
This function calls the distribution routine if necessary
:param individual: network configuration considered
:param ntwList: list of DHN configurations previously encounterd in the master
:param locator: path to the folder
:type individual: list
:type ntwList: list
:type locator: string
:return: None
:rtype: Nonetype
"""
indCombi = sFn.individual_to_barcode(individual, gv)
print indCombi, 2
if not (indCombi in ntwList) and indCombi.count("1") > 0:
ntwList.append(indCombi)
if indCombi.count("1") == 1:
total_demand = pd.read_csv(
os.path.join(locator.get_optimization_network_results_folder(),
"Total_%(indCombi)s.csv" % locals()))
building_names = total_demand.Name.values
print "Direct launch of distribution summary routine for", indCombi
nM.network_main(locator, total_demand, building_names, gv,
indCombi)
else:
total_demand = sFn.createTotalNtwCsv(indCombi, locator)
building_names = total_demand.Name.values
# Run the substation and distribution routines
print "Re-run the substation routine for new distribution configuration", indCombi
sMain.substation_main(locator, total_demand, building_names, gv,
indCombi)
print "Launch distribution summary routine"
nM.network_main(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 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 evaluation_main(individual, building_names, locator, solar_features,
network_features, gv, config, prices, lca, ind_num, gen):
"""
This function evaluates an individual
:param individual: list with values of the individual
:param building_names: list with names of buildings
:param locator: locator class
:param solar_features: solar features call to class
:param network_features: network features call to class
:param gv: global variables class
:param optimization_constants: class containing constants used in optimization
:param config: configuration file
:param prices: class of prices used in optimization
:type individual: list
:type building_names: list
:type locator: string
:type solar_features: class
:type network_features: class
:type gv: class
:type optimization_constants: class
:type config: class
:type prices: class
:return: Resulting values of the objective function. costs, CO2, prim
:rtype: tuple
"""
# Check the consistency of the individual or create a new one
individual = check_invalid(individual, len(building_names), config)
# Initialize objective functions costs, CO2 and primary energy
costs_USD = 0
GHG_tonCO2 = 0
PEN_MJoil = 0
Q_heating_uncovered_design_W = 0
Q_heating_uncovered_annual_W = 0
# Create the string representation of the individual
DHN_barcode, DCN_barcode, DHN_configuration, DCN_configuration = supportFn.individual_to_barcode(
individual, building_names)
if DHN_barcode.count("1") == gv.num_tot_buildings:
network_file_name_heating = "Network_summary_result_all.csv"
Q_DHNf_W = pd.read_csv(
locator.get_optimization_network_all_results_summary('all'),
usecols=["Q_DHNf_W"]).values
Q_heating_max_W = Q_DHNf_W.max()
elif DHN_barcode.count("1") == 0:
network_file_name_heating = "Network_summary_result_all.csv"
Q_heating_max_W = 0
else:
network_file_name_heating = "Network_summary_result_" + hex(
int(str(DHN_barcode), 2)) + ".csv"
if not os.path.exists(
locator.get_optimization_network_results_summary(DHN_barcode)):
total_demand = supportFn.createTotalNtwCsv(DHN_barcode, locator)
building_names = total_demand.Name.values
# Run the substation and distribution routines
substation.substation_main(locator,
total_demand,
building_names,
DHN_configuration,
DCN_configuration,
Flag=True)
summarize_network.network_main(locator, total_demand,
building_names, config, gv,
DHN_barcode)
Q_DHNf_W = pd.read_csv(
locator.get_optimization_network_results_summary(DHN_barcode),
usecols=["Q_DHNf_W"]).values
Q_heating_max_W = Q_DHNf_W.max()
if DCN_barcode.count("1") == gv.num_tot_buildings:
network_file_name_cooling = "Network_summary_result_all.csv"
if individual[
N_HEAT *
2] == 1: # if heat recovery is ON, then only need to satisfy cooling load of space cooling and refrigeration
Q_DCNf_W = pd.read_csv(
locator.get_optimization_network_all_results_summary('all'),
usecols=["Q_DCNf_space_cooling_and_refrigeration_W"]).values
else:
Q_DCNf_W = pd.read_csv(
locator.get_optimization_network_all_results_summary('all'),
usecols=[
"Q_DCNf_space_cooling_data_center_and_refrigeration_W"
]).values
Q_cooling_max_W = Q_DCNf_W.max()
elif DCN_barcode.count("1") == 0:
network_file_name_cooling = "Network_summary_result_all.csv"
Q_cooling_max_W = 0
else:
network_file_name_cooling = "Network_summary_result_" + hex(
int(str(DCN_barcode), 2)) + ".csv"
if not os.path.exists(
locator.get_optimization_network_results_summary(DCN_barcode)):
total_demand = supportFn.createTotalNtwCsv(DCN_barcode, locator)
building_names = total_demand.Name.values
# Run the substation and distribution routines
substation.substation_main(locator,
total_demand,
building_names,
DHN_configuration,
DCN_configuration,
Flag=True)
summarize_network.network_main(locator, total_demand,
building_names, config, gv,
DCN_barcode)
if individual[
N_HEAT *
2] == 1: # if heat recovery is ON, then only need to satisfy cooling load of space cooling and refrigeration
Q_DCNf_W = pd.read_csv(
locator.get_optimization_network_results_summary(DCN_barcode),
usecols=["Q_DCNf_space_cooling_and_refrigeration_W"]).values
else:
Q_DCNf_W = pd.read_csv(
locator.get_optimization_network_results_summary(DCN_barcode),
usecols=[
"Q_DCNf_space_cooling_data_center_and_refrigeration_W"
]).values
Q_cooling_max_W = Q_DCNf_W.max()
Q_heating_nom_W = Q_heating_max_W * (1 + Q_MARGIN_FOR_NETWORK)
Q_cooling_nom_W = Q_cooling_max_W * (1 + Q_MARGIN_FOR_NETWORK)
# Modify the individual with the extra GHP constraint
try:
check.GHPCheck(individual, locator, Q_heating_nom_W, gv)
except:
print "No GHP constraint check possible \n"
# Export to context
master_to_slave_vars = calc_master_to_slave_variables(
individual, Q_heating_max_W, Q_cooling_max_W, building_names, ind_num,
gen)
master_to_slave_vars.network_data_file_heating = network_file_name_heating
master_to_slave_vars.network_data_file_cooling = network_file_name_cooling
master_to_slave_vars.total_buildings = len(building_names)
master_to_slave_vars.DHN_barcode = DHN_barcode
master_to_slave_vars.DCN_barcode = DCN_barcode
if master_to_slave_vars.number_of_buildings_connected_heating > 1:
if DHN_barcode.count("0") == 0:
master_to_slave_vars.fNameTotalCSV = locator.get_total_demand()
else:
master_to_slave_vars.fNameTotalCSV = os.path.join(
locator.get_optimization_network_totals_folder(),
"Total_%(DHN_barcode)s.csv" % locals())
else:
master_to_slave_vars.fNameTotalCSV = locator.get_optimization_substations_total_file(
DHN_barcode)
if master_to_slave_vars.number_of_buildings_connected_cooling > 1:
if DCN_barcode.count("0") == 0:
master_to_slave_vars.fNameTotalCSV = locator.get_total_demand()
else:
master_to_slave_vars.fNameTotalCSV = os.path.join(
locator.get_optimization_network_totals_folder(),
"Total_%(DCN_barcode)s.csv" % locals())
else:
master_to_slave_vars.fNameTotalCSV = locator.get_optimization_substations_total_file(
DCN_barcode)
# Thermal Storage Calculations; Run storage optimization
costs_storage_USD, GHG_storage_tonCO2, PEN_storage_MJoil = storage_main.storage_optimization(
locator, master_to_slave_vars, lca, prices, config)
costs_USD += costs_storage_USD
GHG_tonCO2 += GHG_storage_tonCO2
PEN_MJoil += PEN_storage_MJoil
# District Heating Calculations
if config.district_heating_network:
if DHN_barcode.count("1") > 0:
(PEN_heating_MJoil, GHG_heating_tonCO2, costs_heating_USD,
Q_heating_uncovered_design_W, Q_heating_uncovered_annual_W
) = heating_main.heating_calculations_of_DH_buildings(
locator, master_to_slave_vars, gv, config, prices, lca)
else:
GHG_heating_tonCO2 = 0
costs_heating_USD = 0
PEN_heating_MJoil = 0
else:
GHG_heating_tonCO2 = 0
costs_heating_USD = 0
PEN_heating_MJoil = 0
costs_USD += costs_heating_USD
GHG_tonCO2 += GHG_heating_tonCO2
PEN_MJoil += PEN_heating_MJoil
# District Cooling Calculations
if gv.ZernezFlag == 1:
costs_cooling_USD, GHG_cooling_tonCO2, PEN_cooling_MJoil = 0, 0, 0
elif config.district_cooling_network:
reduced_timesteps_flag = False
(costs_cooling_USD, GHG_cooling_tonCO2, PEN_cooling_MJoil
) = cooling_main.cooling_calculations_of_DC_buildings(
locator, master_to_slave_vars, network_features, gv, prices, lca,
config, reduced_timesteps_flag)
else:
costs_cooling_USD, GHG_cooling_tonCO2, PEN_cooling_MJoil = 0, 0, 0
costs_USD += costs_cooling_USD
GHG_tonCO2 += GHG_cooling_tonCO2
PEN_MJoil += PEN_cooling_MJoil
# District Electricity Calculations
(costs_electricity_USD, GHG_electricity_tonCO2, PEN_electricity_MJoil
) = electricity_main.electricity_calculations_of_all_buildings(
DHN_barcode, DCN_barcode, locator, master_to_slave_vars,
network_features, gv, prices, lca, config)
costs_USD += costs_electricity_USD
GHG_tonCO2 += GHG_electricity_tonCO2
PEN_MJoil += PEN_electricity_MJoil
# Natural Gas Import Calculations. Prices, GHG and PEN are already included in the various sections.
# This is to save the files for further processing and plots
natural_gas_main.natural_gas_imports(master_to_slave_vars, locator, config)
# Capex Calculations
print "Add extra costs"
(costs_additional_USD,
GHG_additional_tonCO2, PEN_additional_MJoil) = cost_model.addCosts(
building_names, locator, master_to_slave_vars,
Q_heating_uncovered_design_W, Q_heating_uncovered_annual_W,
solar_features, network_features, gv, config, prices, lca)
costs_USD += costs_additional_USD
GHG_tonCO2 += GHG_additional_tonCO2
PEN_MJoil += PEN_additional_MJoil
summarize_individual.summarize_individual_main(master_to_slave_vars,
building_names, individual,
solar_features, locator,
config)
# Converting costs into float64 to avoid longer values
costs_USD = np.float64(costs_USD)
GHG_tonCO2 = np.float64(GHG_tonCO2)
PEN_MJoil = np.float64(PEN_MJoil)
print('Total costs = ' + str(costs_USD))
print('Total CO2 = ' + str(GHG_tonCO2))
print('Total prim = ' + str(PEN_MJoil))
# Saving capacity details of the individual
return costs_USD, GHG_tonCO2, PEN_MJoil, master_to_slave_vars, individual
def evaluation_main(individual, building_names, locator, extraCosts, extraCO2,
extraPrim, solar_features, network_features, gv, config,
prices, lca, ind_num, gen):
"""
This function evaluates an individual
:param individual: list with values of the individual
:param building_names: list with names of buildings
:param locator: locator class
:param extraCosts: costs calculated before optimization of specific energy services
(process heat and electricity)
:param extraCO2: green house gas emissions calculated before optimization of specific energy services
(process heat and electricity)
:param extraPrim: primary energy calculated before optimization ofr specific energy services
(process heat and electricity)
:param solar_features: solar features call to class
:param network_features: network features call to class
:param gv: global variables class
:param optimization_constants: class containing constants used in optimization
:param config: configuration file
:param prices: class of prices used in optimization
:type individual: list
:type building_names: list
:type locator: string
:type extraCosts: float
:type extraCO2: float
:type extraPrim: float
:type solar_features: class
:type network_features: class
:type gv: class
:type optimization_constants: class
:type config: class
:type prices: class
:return: Resulting values of the objective function. costs, CO2, prim
:rtype: tuple
"""
# Check the consistency of the individual or create a new one
individual = check_invalid(individual, len(building_names), config)
# Initialize objective functions costs, CO2 and primary energy
costs = extraCosts
CO2 = extraCO2
prim = extraPrim
QUncoveredDesign = 0
QUncoveredAnnual = 0
# Create the string representation of the individual
DHN_barcode, DCN_barcode, DHN_configuration, DCN_configuration = sFn.individual_to_barcode(
individual, building_names)
if DHN_barcode.count("1") == gv.num_tot_buildings:
network_file_name_heating = "Network_summary_result_all.csv"
Q_DHNf_W = pd.read_csv(
locator.get_optimization_network_all_results_summary('all'),
usecols=["Q_DHNf_W"]).values
Q_heating_max_W = Q_DHNf_W.max()
elif DHN_barcode.count("1") == 0:
network_file_name_heating = "Network_summary_result_all.csv"
Q_heating_max_W = 0
else:
network_file_name_heating = "Network_summary_result_" + hex(
int(str(DHN_barcode), 2)) + ".csv"
if not os.path.exists(
locator.get_optimization_network_results_summary(DHN_barcode)):
total_demand = sFn.createTotalNtwCsv(DHN_barcode, locator)
building_names = total_demand.Name.values
# Run the substation and distribution routines
sMain.substation_main(locator,
total_demand,
building_names,
DHN_configuration,
DCN_configuration,
Flag=True)
nM.network_main(locator, total_demand, building_names, config, gv,
DHN_barcode)
Q_DHNf_W = pd.read_csv(
locator.get_optimization_network_results_summary(DHN_barcode),
usecols=["Q_DHNf_W"]).values
Q_heating_max_W = Q_DHNf_W.max()
if DCN_barcode.count("1") == gv.num_tot_buildings:
network_file_name_cooling = "Network_summary_result_all.csv"
if individual[
N_HEAT *
2] == 1: # if heat recovery is ON, then only need to satisfy cooling load of space cooling and refrigeration
Q_DCNf_W = pd.read_csv(
locator.get_optimization_network_all_results_summary('all'),
usecols=["Q_DCNf_space_cooling_and_refrigeration_W"]).values
else:
Q_DCNf_W = pd.read_csv(
locator.get_optimization_network_all_results_summary('all'),
usecols=[
"Q_DCNf_space_cooling_data_center_and_refrigeration_W"
]).values
Q_cooling_max_W = Q_DCNf_W.max()
elif DCN_barcode.count("1") == 0:
network_file_name_cooling = "Network_summary_result_all.csv"
Q_cooling_max_W = 0
else:
network_file_name_cooling = "Network_summary_result_" + hex(
int(str(DCN_barcode), 2)) + ".csv"
if not os.path.exists(
locator.get_optimization_network_results_summary(DCN_barcode)):
total_demand = sFn.createTotalNtwCsv(DCN_barcode, locator)
building_names = total_demand.Name.values
# Run the substation and distribution routines
sMain.substation_main(locator,
total_demand,
building_names,
DHN_configuration,
DCN_configuration,
Flag=True)
nM.network_main(locator, total_demand, building_names, config, gv,
DCN_barcode)
if individual[
N_HEAT *
2] == 1: # if heat recovery is ON, then only need to satisfy cooling load of space cooling and refrigeration
Q_DCNf_W = pd.read_csv(
locator.get_optimization_network_results_summary(DCN_barcode),
usecols=["Q_DCNf_space_cooling_and_refrigeration_W"]).values
else:
Q_DCNf_W = pd.read_csv(
locator.get_optimization_network_results_summary(DCN_barcode),
usecols=[
"Q_DCNf_space_cooling_data_center_and_refrigeration_W"
]).values
Q_cooling_max_W = Q_DCNf_W.max()
Q_heating_nom_W = Q_heating_max_W * (1 + Q_MARGIN_FOR_NETWORK)
Q_cooling_nom_W = Q_cooling_max_W * (1 + Q_MARGIN_FOR_NETWORK)
# Modify the individual with the extra GHP constraint
try:
cCheck.GHPCheck(individual, locator, Q_heating_nom_W, gv)
except:
print "No GHP constraint check possible \n"
# Export to context
master_to_slave_vars = calc_master_to_slave_variables(
individual, Q_heating_max_W, Q_cooling_max_W, building_names, ind_num,
gen)
master_to_slave_vars.network_data_file_heating = network_file_name_heating
master_to_slave_vars.network_data_file_cooling = network_file_name_cooling
master_to_slave_vars.total_buildings = len(building_names)
if master_to_slave_vars.number_of_buildings_connected_heating > 1:
if DHN_barcode.count("0") == 0:
master_to_slave_vars.fNameTotalCSV = locator.get_total_demand()
else:
master_to_slave_vars.fNameTotalCSV = os.path.join(
locator.get_optimization_network_totals_folder(),
"Total_%(DHN_barcode)s.csv" % locals())
else:
master_to_slave_vars.fNameTotalCSV = locator.get_optimization_substations_total_file(
DHN_barcode)
if master_to_slave_vars.number_of_buildings_connected_cooling > 1:
if DCN_barcode.count("0") == 0:
master_to_slave_vars.fNameTotalCSV = locator.get_total_demand()
else:
master_to_slave_vars.fNameTotalCSV = os.path.join(
locator.get_optimization_network_totals_folder(),
"Total_%(DCN_barcode)s.csv" % locals())
else:
master_to_slave_vars.fNameTotalCSV = locator.get_optimization_substations_total_file(
DCN_barcode)
if config.optimization.isheating:
if DHN_barcode.count("1") > 0:
(slavePrim, slaveCO2, slaveCosts, QUncoveredDesign,
QUncoveredAnnual) = sM.slave_main(locator, master_to_slave_vars,
solar_features, gv, config,
prices, lca)
else:
slaveCO2 = 0
slaveCosts = 0
slavePrim = 0
else:
slaveCO2 = 0
slaveCosts = 0
slavePrim = 0
costs += slaveCosts
CO2 += slaveCO2
prim += slavePrim
if gv.ZernezFlag == 1:
coolCosts, coolCO2, coolPrim = 0, 0, 0
elif config.optimization.iscooling:
reduced_timesteps_flag = False
(coolCosts, coolCO2,
coolPrim) = coolMain.coolingMain(locator, master_to_slave_vars,
network_features, gv, prices, lca,
config, reduced_timesteps_flag)
else:
coolCosts, coolCO2, coolPrim = 0, 0, 0
print "Add extra costs"
(addCosts, addCO2,
addPrim) = eM.addCosts(DHN_barcode, DCN_barcode, building_names, locator,
master_to_slave_vars, QUncoveredDesign,
QUncoveredAnnual, solar_features, network_features,
gv, config, prices, lca)
costs += addCosts + coolCosts
CO2 += addCO2 + coolCO2
prim += addPrim + coolPrim
# Converting costs into float64 to avoid longer values
costs = np.float64(costs)
CO2 = np.float64(CO2)
prim = np.float64(prim)
print('Total costs = ' + str(costs))
print('Total CO2 = ' + str(CO2))
print('Total prim = ' + str(prim))
return costs, CO2, prim, master_to_slave_vars, individual