def district_cooling_network(locator,
master_to_slave_variables,
config,
prices,
network_features):
"""
Computes the parameters for the cooling of the complete DCN
:param cea.inputlocator.InputLocator locator: path to res folder
:param network_features: network features
:param prices: Prices imported from the database
:type network_features: class
:type prices: class
:return: costs, co2, prim
:rtype: tuple
"""
if master_to_slave_variables.DCN_exists:
# THERMAL STORAGE + NETWORK
# Import Temperatures from Network Summary:
Q_thermal_req_W, \
T_district_cooling_return_K, \
T_district_cooling_supply_K, \
mdot_kgpers = calc_network_summary_DCN(master_to_slave_variables)
# Initialize daily storage calss
T_ground_K = calculate_ground_temperature(locator)
daily_storage = LoadLevelingDailyStorage(master_to_slave_variables.Storage_cooling_on,
master_to_slave_variables.Storage_cooling_size_W,
min(T_district_cooling_supply_K) - DT_COOL,
max(T_district_cooling_return_K) - DT_COOL,
T_TANK_FULLY_DISCHARGED_K,
np.mean(T_ground_K)
)
# Import Data - potentials lake heat
if master_to_slave_variables.WS_BaseVCC_on == 1 or master_to_slave_variables.WS_PeakVCC_on == 1:
HPlake_Data = pd.read_csv(locator.get_water_body_potential())
Q_therm_Lake = np.array(HPlake_Data['QLake_kW']) * 1E3
total_WS_VCC_installed = master_to_slave_variables.WS_BaseVCC_size_W + master_to_slave_variables.WS_PeakVCC_size_W
Q_therm_Lake_W = [x if x < total_WS_VCC_installed else total_WS_VCC_installed for x in Q_therm_Lake]
T_source_average_Lake_K = np.array(HPlake_Data['Ts_C']) + 273
else:
Q_therm_Lake_W = np.zeros(HOURS_IN_YEAR)
T_source_average_Lake_K = np.zeros(HOURS_IN_YEAR)
# get properties of technology used in this script
absorption_chiller = AbsorptionChiller(pd.read_excel(locator.get_database_conversion_systems(), sheet_name="Absorption_chiller"), 'double')
CCGT_prop = calc_cop_CCGT(master_to_slave_variables.NG_Trigen_ACH_size_W, ACH_T_IN_FROM_CHP_K, "NG")
VCC_database = pd.read_excel(locator.get_database_conversion_systems(), sheet_name="Chiller")
technology_type = VCC_CODE_CENTRALIZED
VCC_database = VCC_database[VCC_database['code'] == technology_type]
max_VCC_capacity = int(VCC_database['cap_max'])
min_VCC_capacity = int(VCC_database['cap_min'])
# G_VALUE = VCC_database['ISENTROPIC_EFFICIENCY'] # create vessel to carry down gvalue and max_VCC_capacity, min_VCC_capacity to VCC module
# initialize variables
Q_Trigen_NG_gen_W = np.zeros(HOURS_IN_YEAR)
Q_BaseVCC_WS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_PeakVCC_WS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_BaseVCC_AS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_PeakVCC_AS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_DailyStorage_gen_directload_W = np.zeros(HOURS_IN_YEAR)
E_Trigen_NG_gen_W = np.zeros(HOURS_IN_YEAR)
E_BaseVCC_AS_req_W = np.zeros(HOURS_IN_YEAR)
E_PeakVCC_AS_req_W = np.zeros(HOURS_IN_YEAR)
E_BaseVCC_WS_req_W = np.zeros(HOURS_IN_YEAR)
E_PeakVCC_WS_req_W = np.zeros(HOURS_IN_YEAR)
NG_Trigen_req_W = np.zeros(HOURS_IN_YEAR)
Q_BackupVCC_AS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_Trigen_NG_gen_directload_W = np.zeros(HOURS_IN_YEAR)
Q_BaseVCC_WS_gen_directload_W = np.zeros(HOURS_IN_YEAR)
Q_PeakVCC_WS_gen_directload_W = np.zeros(HOURS_IN_YEAR)
Q_BaseVCC_AS_gen_directload_W = np.zeros(HOURS_IN_YEAR)
Q_PeakVCC_AS_gen_directload_W = np.zeros(HOURS_IN_YEAR)
Q_BackupVCC_AS_directload_W = np.zeros(HOURS_IN_YEAR)
for hour in range(HOURS_IN_YEAR): # cooling supply for all buildings excluding cooling loads from data centers
if Q_thermal_req_W[hour] > 0.0: # only if there is a cooling load!
daily_storage, \
thermal_output, \
electricity_output, \
gas_output = cooling_resource_activator(Q_thermal_req_W[hour],
T_district_cooling_supply_K[hour],
T_district_cooling_return_K[hour],
Q_therm_Lake_W[hour],
T_source_average_Lake_K[hour],
daily_storage,
T_ground_K[hour],
master_to_slave_variables,
absorption_chiller,
CCGT_prop,
min_VCC_capacity,
max_VCC_capacity)
Q_DailyStorage_gen_directload_W[hour] = thermal_output['Q_DailyStorage_gen_directload_W']
Q_Trigen_NG_gen_directload_W[hour] = thermal_output['Q_Trigen_NG_gen_directload_W']
Q_BaseVCC_WS_gen_directload_W[hour] = thermal_output['Q_BaseVCC_WS_gen_directload_W']
Q_PeakVCC_WS_gen_directload_W[hour] = thermal_output['Q_PeakVCC_WS_gen_directload_W']
Q_BaseVCC_AS_gen_directload_W[hour] = thermal_output['Q_BaseVCC_AS_gen_directload_W']
Q_PeakVCC_AS_gen_directload_W[hour] = thermal_output['Q_PeakVCC_AS_gen_directload_W']
Q_BackupVCC_AS_directload_W[hour] = thermal_output['Q_BackupVCC_AS_directload_W']
Q_Trigen_NG_gen_W[hour] = thermal_output['Q_Trigen_NG_gen_W']
Q_BaseVCC_WS_gen_W[hour] = thermal_output['Q_BaseVCC_WS_gen_W']
Q_PeakVCC_WS_gen_W[hour] = thermal_output['Q_PeakVCC_WS_gen_W']
Q_BaseVCC_AS_gen_W[hour] = thermal_output['Q_BaseVCC_AS_gen_W']
Q_PeakVCC_AS_gen_W[hour] = thermal_output['Q_PeakVCC_AS_gen_W']
Q_BackupVCC_AS_gen_W[hour] = thermal_output['Q_BackupVCC_AS_gen_W']
E_BaseVCC_WS_req_W[hour] = electricity_output['E_BaseVCC_WS_req_W']
E_PeakVCC_WS_req_W[hour] = electricity_output['E_PeakVCC_WS_req_W']
E_BaseVCC_AS_req_W[hour] = electricity_output['E_BaseVCC_AS_req_W']
E_PeakVCC_AS_req_W[hour] = electricity_output['E_PeakVCC_AS_req_W']
E_Trigen_NG_gen_W[hour] = electricity_output['E_Trigen_NG_gen_W']
NG_Trigen_req_W[hour] = gas_output['NG_Trigen_req_W']
#calculate the electrical capacity as a function of the peak produced by the turbine
master_to_slave_variables.NG_Trigen_CCGT_size_electrical_W = E_Trigen_NG_gen_W.max()
# BACK-UPP VCC - AIR SOURCE
scale = 'DISTRICT'
master_to_slave_variables.AS_BackupVCC_size_W = np.amax(Q_BackupVCC_AS_gen_W)
size_chiller_CT = master_to_slave_variables.AS_BackupVCC_size_W
if master_to_slave_variables.AS_BackupVCC_size_W != 0.0:
master_to_slave_variables.AS_BackupVCC_on = 1
Q_BackupVCC_AS_gen_W, E_BackupVCC_AS_req_W = np.vectorize(calc_vcc_CT_operation)(Q_BackupVCC_AS_gen_W,
T_district_cooling_return_K,
T_district_cooling_supply_K,
VCC_T_COOL_IN,
size_chiller_CT,
min_VCC_capacity,
max_VCC_capacity,
scale)
else:
E_BackupVCC_AS_req_W = np.zeros(HOURS_IN_YEAR)
# CAPEX (ANNUAL, TOTAL) AND OPEX (FIXED, VAR, ANNUAL) GENERATION UNITS
supply_systems = SupplySystemsDatabase(locator)
mdotnMax_kgpers = np.amax(mdot_kgpers)
performance_costs_generation, \
district_cooling_capacity_installed = cost_model.calc_generation_costs_capacity_installed_cooling(locator,
master_to_slave_variables,
supply_systems,
mdotnMax_kgpers
)
# CAPEX (ANNUAL, TOTAL) AND OPEX (FIXED, VAR, ANNUAL) STORAGE UNITS
performance_costs_storage = cost_model.calc_generation_costs_cooling_storage(locator,
master_to_slave_variables,
config,
daily_storage
)
# CAPEX (ANNUAL, TOTAL) AND OPEX (FIXED, VAR, ANNUAL) NETWORK
performance_costs_network, \
E_used_district_cooling_network_W = cost_model.calc_network_costs_cooling(locator,
master_to_slave_variables,
network_features,
"DC",
prices)
# MERGE COSTS AND EMISSIONS IN ONE FILE
performance = dict(performance_costs_generation, **performance_costs_storage)
district_cooling_costs = dict(performance, **performance_costs_network)
else:
Q_thermal_req_W = np.zeros(HOURS_IN_YEAR)
Q_DailyStorage_gen_directload_W = np.zeros(HOURS_IN_YEAR)
Q_Trigen_NG_gen_directload_W = np.zeros(HOURS_IN_YEAR)
Q_BaseVCC_WS_gen_directload_W = np.zeros(HOURS_IN_YEAR)
Q_PeakVCC_WS_gen_directload_W = np.zeros(HOURS_IN_YEAR)
Q_BaseVCC_AS_gen_directload_W = np.zeros(HOURS_IN_YEAR)
Q_PeakVCC_AS_gen_directload_W = np.zeros(HOURS_IN_YEAR)
Q_BackupVCC_AS_directload_W = np.zeros(HOURS_IN_YEAR)
Q_Trigen_NG_gen_W = np.zeros(HOURS_IN_YEAR)
Q_BaseVCC_WS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_PeakVCC_WS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_BaseVCC_AS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_PeakVCC_AS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_BackupVCC_AS_gen_W = np.zeros(HOURS_IN_YEAR)
E_Trigen_NG_gen_W = np.zeros(HOURS_IN_YEAR)
E_used_district_cooling_network_W = np.zeros(HOURS_IN_YEAR)
E_BaseVCC_WS_req_W = np.zeros(HOURS_IN_YEAR)
E_PeakVCC_WS_req_W = np.zeros(HOURS_IN_YEAR)
E_BaseVCC_AS_req_W = np.zeros(HOURS_IN_YEAR)
E_PeakVCC_AS_req_W = np.zeros(HOURS_IN_YEAR)
E_BackupVCC_AS_req_W = np.zeros(HOURS_IN_YEAR)
NG_Trigen_req_W = np.zeros(HOURS_IN_YEAR)
district_cooling_costs = {}
district_cooling_capacity_installed = {}
# SAVE
district_cooling_generation_dispatch = {
# demand of the network
"Q_districtcooling_sys_req_W": Q_thermal_req_W,
# ENERGY GENERATION TO DIRECT LOAD
# from storage
"Q_DailyStorage_gen_directload_W": Q_DailyStorage_gen_directload_W,
# cooling
"Q_Trigen_NG_gen_directload_W": Q_Trigen_NG_gen_directload_W,
"Q_BaseVCC_WS_gen_directload_W": Q_BaseVCC_WS_gen_directload_W,
"Q_PeakVCC_WS_gen_directload_W": Q_PeakVCC_WS_gen_directload_W,
"Q_BaseVCC_AS_gen_directload_W": Q_BaseVCC_AS_gen_directload_W,
"Q_PeakVCC_AS_gen_directload_W": Q_PeakVCC_AS_gen_directload_W,
"Q_BackupVCC_AS_directload_W": Q_BackupVCC_AS_directload_W,
# ENERGY GENERATION TOTAL
# cooling
"Q_Trigen_NG_gen_W": Q_Trigen_NG_gen_W,
"Q_BaseVCC_WS_gen_W": Q_BaseVCC_WS_gen_W,
"Q_PeakVCC_WS_gen_W": Q_PeakVCC_WS_gen_W,
"Q_BaseVCC_AS_gen_W": Q_BaseVCC_AS_gen_W,
"Q_PeakVCC_AS_gen_W": Q_PeakVCC_AS_gen_W,
"Q_BackupVCC_AS_W": Q_BackupVCC_AS_gen_W,
# electricity
"E_Trigen_NG_gen_W": E_Trigen_NG_gen_W
}
district_cooling_electricity_requirements_dispatch = {
# ENERGY REQUIREMENTS
# Electricity
"E_DCN_req_W": E_used_district_cooling_network_W,
"E_BaseVCC_WS_req_W": E_BaseVCC_WS_req_W,
"E_PeakVCC_WS_req_W": E_PeakVCC_WS_req_W,
"E_BaseVCC_AS_req_W": E_BaseVCC_AS_req_W,
"E_PeakVCC_AS_req_W": E_PeakVCC_AS_req_W,
"E_BackupVCC_AS_req_W": E_BackupVCC_AS_req_W,
}
district_cooling_fuel_requirements_dispatch = {
# fuels
"NG_Trigen_req_W": NG_Trigen_req_W
}
# PLOT RESULTS
return district_cooling_costs, \
district_cooling_generation_dispatch, \
district_cooling_electricity_requirements_dispatch, \
district_cooling_fuel_requirements_dispatch, \
district_cooling_capacity_installed
def disconnected_buildings_cooling_main(locator, building_names, total_demand, config, prices, lca):
"""
Computes the parameters for the operation of disconnected buildings output results in csv files.
There is no optimization at this point. The different cooling energy supply system configurations are calculated
and compared 1 to 1 to each other. it is a classical combinatorial problem.
The six supply system configurations include:
(VCC: Vapor Compression Chiller, ACH: Absorption Chiller, CT: Cooling Tower, Boiler)
(AHU: Air Handling Units, ARU: Air Recirculation Units, SCU: Sensible Cooling Units)
- config 0: Direct Expansion / Mini-split units (NOTE: this configuration is not fully built yet)
- config 1: VCC_to_AAS (AHU + ARU + SCU) + CT
- config 2: FP + single-effect ACH_to_AAS (AHU + ARU + SCU) + Boiler + CT
- config 3: ET + single-effect ACH_to_AAS (AHU + ARU + SCU) + Boiler + CT
- config 4: VCC_to_AA (AHU + ARU) + VCC_to_S (SCU) + CT
- config 5: VCC_to_AA (AHU + ARU) + single effect ACH_S (SCU) + CT + Boiler
Note:
1. Only cooling supply configurations are compared here. The demand for electricity is supplied from the grid,
and the demand for domestic hot water is supplied from electric boilers.
2. Single-effect chillers are coupled with flat-plate solar collectors, and the double-effect chillers are coupled
with evacuated tube solar collectors.
:param locator: locator class with paths to input/output files
:param building_names: list with names of buildings
:param config: cea.config
:param prices: prices class
:return: one .csv file with results of operations of disconnected buildings; one .csv file with operation of the
best configuration (Cost, CO2, Primary Energy)
"""
t0 = time.clock()
for building_name in building_names:
## Calculate cooling loads for different combinations
# SENSIBLE COOLING UNIT
Qc_nom_SCU_W, \
T_re_SCU_K, \
T_sup_SCU_K, \
mdot_SCU_kgpers = calc_combined_cooling_loads(building_name, locator, total_demand,
cooling_configuration=['scu'])
# AIR HANDLING UNIT + AIR RECIRCULATION UNIT
Qc_nom_AHU_ARU_W, \
T_re_AHU_ARU_K, \
T_sup_AHU_ARU_K, \
mdot_AHU_ARU_kgpers = calc_combined_cooling_loads(building_name, locator, total_demand,
cooling_configuration=['ahu', 'aru'])
# SENSIBLE COOLING UNIT + AIR HANDLING UNIT + AIR RECIRCULATION UNIT
Qc_nom_AHU_ARU_SCU_W, \
T_re_AHU_ARU_SCU_K, \
T_sup_AHU_ARU_SCU_K, \
mdot_AHU_ARU_SCU_kgpers = calc_combined_cooling_loads(building_name, locator, total_demand,
cooling_configuration=['ahu', 'aru', 'scu'])
## Get hourly hot water supply condition of Solar Collectors (SC)
# Flate Plate Solar Collectors
SC_FP_data, T_hw_in_FP_C, el_aux_SC_FP_Wh, q_sc_gen_FP_Wh = get_SC_data(building_name, locator, panel_type="FP")
Capex_a_SC_FP_USD, Opex_SC_FP_USD, Capex_SC_FP_USD = solar_collector.calc_Cinv_SC(SC_FP_data['Area_SC_m2'][0],
locator,
panel_type="FP")
# Evacuated Tube Solar Collectors
SC_ET_data, T_hw_in_ET_C, el_aux_SC_ET_Wh, q_sc_gen_ET_Wh = get_SC_data(building_name, locator, panel_type="ET")
Capex_a_SC_ET_USD, Opex_SC_ET_USD, Capex_SC_ET_USD = solar_collector.calc_Cinv_SC(SC_ET_data['Area_SC_m2'][0],
locator,
panel_type="ET")
## Calculate ground temperatures to estimate cold water supply temperatures for absorption chiller
T_ground_K = calculate_ground_temperature(locator,
config) # FIXME: change to outlet temperature from the cooling towers
## Initialize table to save results
# save costs of all supply configurations
operation_results = initialize_result_tables_for_supply_configurations(Qc_nom_SCU_W)
# save supply system activation of all supply configurations
cooling_dispatch = {}
## HOURLY OPERATION
print building_name, ' decentralized cooling supply system simulations...'
T_re_AHU_ARU_SCU_K = np.where(T_re_AHU_ARU_SCU_K > 0.0, T_re_AHU_ARU_SCU_K, T_sup_AHU_ARU_SCU_K)
## 0. DX operation
print 'Config 0: Direct Expansion Units -> AHU,ARU,SCU'
el_DX_hourly_Wh,\
q_DX_chw_Wh = np.vectorize(dx.calc_DX)(mdot_AHU_ARU_SCU_kgpers, T_sup_AHU_ARU_SCU_K, T_re_AHU_ARU_SCU_K)
DX_Status = np.where(q_DX_chw_Wh > 0.0, 1, 0)
# add electricity costs, CO2, PE
operation_results[0][7] += sum(lca.ELEC_PRICE * el_DX_hourly_Wh)
operation_results[0][8] += sum(el_DX_hourly_Wh * WH_TO_J / 1E6 * lca.EL_TO_CO2 / 1E3) # ton CO2
operation_results[0][9] += sum(el_DX_hourly_Wh * WH_TO_J / 1E6 * lca.EL_TO_OIL_EQ) # MJ oil
# activation
cooling_dispatch[0] = {'Q_DX_gen_directload_W': q_DX_chw_Wh,
'E_DX_req_W': el_DX_hourly_Wh,
'DX_Status': DX_Status,
'E_cs_cre_cdata_req_W': el_DX_hourly_Wh,
}
## 1. VCC (AHU + ARU + SCU) + CT
print 'Config 1: Vapor Compression Chillers -> AHU,ARU,SCU'
# VCC operation
el_VCC_Wh, q_VCC_cw_Wh, q_VCC_chw_Wh = calc_VCC_operation(T_re_AHU_ARU_SCU_K, T_sup_AHU_ARU_SCU_K,
mdot_AHU_ARU_SCU_kgpers)
VCC_Status = np.where(q_VCC_chw_Wh > 0.0, 1, 0)
# CT operation
q_CT_VCC_to_AHU_ARU_SCU_Wh = q_VCC_cw_Wh
Q_nom_CT_VCC_to_AHU_ARU_SCU_W, el_CT_Wh = calc_CT_operation(q_CT_VCC_to_AHU_ARU_SCU_Wh)
# add costs
el_total_Wh = el_VCC_Wh + el_CT_Wh
operation_results[1][7] += sum(lca.ELEC_PRICE * el_total_Wh) # CHF
operation_results[1][8] += sum(el_total_Wh * WH_TO_J / 1E6 * lca.EL_TO_CO2 / 1E3) # ton CO2
operation_results[1][9] += sum(el_total_Wh * WH_TO_J / 1E6 * lca.EL_TO_OIL_EQ) # MJ-oil-eq
cooling_dispatch[1] = {'Q_VCC_gen_directload_W': q_VCC_chw_Wh,
'E_VCC_req_W': el_VCC_Wh,
'E_CT_req_W': el_CT_Wh,
'E_cs_cre_cdata_req_W': el_total_Wh,
'VCC_Status': VCC_Status
}
## 2: SC_FP + single-effect ACH (AHU + ARU + SCU) + CT + Boiler + SC_FP
print 'Config 2: Flat-plate Solar Collectors + Single-effect Absorption chillers -> AHU,ARU,SCU'
# ACH operation
T_hw_out_single_ACH_K, \
el_single_ACH_Wh, \
q_cw_single_ACH_Wh, \
q_hw_single_ACH_Wh,\
q_chw_single_ACH_Wh = calc_ACH_operation(T_ground_K, T_hw_in_FP_C, T_re_AHU_ARU_SCU_K, T_sup_AHU_ARU_SCU_K,
locator, mdot_AHU_ARU_SCU_kgpers, ACH_TYPE_SINGLE)
ACH_Status = np.where(q_chw_single_ACH_Wh > 0.0, 1, 0)
# CT operation
q_CT_FP_to_single_ACH_to_AHU_ARU_SCU_Wh = q_cw_single_ACH_Wh
Q_nom_CT_FP_to_single_ACH_to_AHU_ARU_SCU_W, el_CT_Wh = calc_CT_operation(
q_CT_FP_to_single_ACH_to_AHU_ARU_SCU_Wh)
# boiler operation
q_gas_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh, \
Q_nom_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_W, \
q_load_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh = calc_boiler_operation(Qc_nom_AHU_ARU_SCU_W,
T_hw_out_single_ACH_K,
q_hw_single_ACH_Wh,
q_sc_gen_FP_Wh)
# add electricity costs
el_total_Wh = el_single_ACH_Wh + el_aux_SC_FP_Wh + el_CT_Wh
operation_results[2][7] += sum(lca.ELEC_PRICE * el_total_Wh) # CHF
operation_results[2][8] += sum(el_total_Wh * WH_TO_J / 1E6 * lca.EL_TO_CO2 / 1E3) # ton CO2
operation_results[2][9] += sum(el_total_Wh * WH_TO_J / 1E6 * lca.EL_TO_OIL_EQ) # MJ-oil-eq
# add gas costs
q_gas_total_Wh = q_gas_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh
operation_results[2][7] += sum(prices.NG_PRICE * q_gas_total_Wh) # CHF
operation_results[2][8] += sum(q_gas_total_Wh * WH_TO_J / 1E6 * lca.NG_BACKUPBOILER_TO_CO2_STD / 1E3) # ton CO2
operation_results[2][9] += sum(q_gas_total_Wh * WH_TO_J / 1E6 * lca.NG_BACKUPBOILER_TO_OIL_STD) # MJ-oil-eq
# add activation
cooling_dispatch[2] = {'Q_ACH_gen_directload_W': q_chw_single_ACH_Wh,
'ACH_Status': ACH_Status,
'Q_Boiler_ACH_W': q_load_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh,
'Q_SC_FP_ACH_W': q_sc_gen_FP_Wh,
'E_ACH_req_W': el_single_ACH_Wh,
'E_CT_req_W': el_CT_Wh,
'E_SC_FP_req_W': el_aux_SC_FP_Wh,
'E_cs_cre_cdata_req_W': el_total_Wh,
'NG_Boiler_req': q_gas_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh,
}
# 3: SC_ET + single-effect ACH (AHU + ARU + SCU) + CT + Boiler + SC_ET
print 'Config 3: Evacuated Tube Solar Collectors + Single-effect Absorption chillers -> AHU,ARU,SCU'
# ACH operation
T_hw_out_single_ACH_K, \
el_single_ACH_Wh, \
q_cw_single_ACH_Wh, \
q_hw_single_ACH_Wh,\
q_chw_single_ACH_Wh = calc_ACH_operation(T_ground_K, T_hw_in_ET_C, T_re_AHU_ARU_SCU_K, T_sup_AHU_ARU_SCU_K,
locator, mdot_AHU_ARU_SCU_kgpers, ACH_TYPE_SINGLE)
# CT operation
q_CT_ET_to_single_ACH_to_AHU_ARU_SCU_W = q_cw_single_ACH_Wh
Q_nom_CT_ET_to_single_ACH_to_AHU_ARU_SCU_W, el_CT_Wh = calc_CT_operation(q_CT_ET_to_single_ACH_to_AHU_ARU_SCU_W)
# burner operation
q_gas_for_burner_Wh, \
Q_nom_Burner_ET_to_single_ACH_to_AHU_ARU_SCU_W,\
q_burner_load_Wh = calc_burner_operation(Qc_nom_AHU_ARU_SCU_W, q_hw_single_ACH_Wh, q_sc_gen_ET_Wh)
# add electricity costs
el_total_Wh = el_single_ACH_Wh + el_aux_SC_ET_Wh + el_CT_Wh
operation_results[3][7] += sum(lca.ELEC_PRICE * el_total_Wh) # CHF
operation_results[3][8] += sum(el_total_Wh * WH_TO_J / 1E6 * lca.EL_TO_CO2 / 1E3) # ton CO2
operation_results[3][9] += sum(el_total_Wh * WH_TO_J / 1E6 * lca.EL_TO_OIL_EQ) # MJ-oil-eq
# add gas costs
operation_results[3][7] += sum(prices.NG_PRICE * q_gas_for_burner_Wh) # CHF
operation_results[3][8] += sum(
q_gas_for_burner_Wh * WH_TO_J / 1E6 * lca.NG_BACKUPBOILER_TO_CO2_STD / 1E3) # ton CO2
operation_results[3][9] += sum(
q_gas_for_burner_Wh * WH_TO_J / 1E6 * lca.NG_BACKUPBOILER_TO_OIL_STD) # MJ-oil-eq
# add activation
cooling_dispatch[3] = {'Q_ACH_gen_directload_W': q_chw_single_ACH_Wh,
'ACH_Status': ACH_Status,
'Q_Burner_ACH_W': q_burner_load_Wh,
'Q_SC_ET_ACH_W': q_sc_gen_ET_Wh,
'E_ACH_req_W': el_single_ACH_Wh,
'E_CT_req_W': el_CT_Wh,
'E_SC_FP_req_W': el_aux_SC_ET_Wh,
'E_cs_cre_cdata_req_W': el_total_Wh,
'NG_Burner_req': q_gas_for_burner_Wh,
}
# these two configurations are only activated when SCU is in use
if Qc_nom_SCU_W > 0.0:
# 4: VCC (AHU + ARU) + VCC (SCU) + CT
print 'Config 4: Vapor Compression Chillers(HT) -> SCU & Vapor Compression Chillers(LT) -> AHU,ARU'
# VCC (AHU + ARU) operation
el_VCC_to_AHU_ARU_Wh, \
q_cw_VCC_to_AHU_ARU_Wh,\
q_chw_VCC_to_AHU_ARU_Wh = calc_VCC_operation(T_re_AHU_ARU_K, T_sup_AHU_ARU_K, mdot_AHU_ARU_kgpers)
VCC_LT_Status = np.where(q_chw_VCC_to_AHU_ARU_Wh > 0.0, 1, 0)
# VCC(SCU) operation
el_VCC_to_SCU_Wh, \
q_cw_VCC_to_SCU_Wh,\
q_chw_VCC_to_SCU_Wh = calc_VCC_operation(T_re_SCU_K, T_sup_SCU_K, mdot_SCU_kgpers)
VCC_HT_Status = np.where(q_chw_VCC_to_AHU_ARU_Wh > 0.0, 1, 0)
# CT operation
q_CT_VCC_to_AHU_ARU_and_VCC_to_SCU_W = q_cw_VCC_to_AHU_ARU_Wh + q_cw_VCC_to_SCU_Wh
Q_nom_CT_VCC_to_AHU_ARU_and_VCC_to_SCU_W, el_CT_Wh = calc_CT_operation(q_CT_VCC_to_AHU_ARU_and_VCC_to_SCU_W)
# add el costs
el_total_Wh = el_VCC_to_AHU_ARU_Wh + el_VCC_to_SCU_Wh + el_CT_Wh
operation_results[4][7] += sum(lca.ELEC_PRICE * el_total_Wh) # CHF
operation_results[4][8] += sum(el_total_Wh * WH_TO_J / 1E6 * lca.EL_TO_CO2 / 1E3) # ton CO2
operation_results[4][9] += sum(el_total_Wh * WH_TO_J / 1E6 * lca.EL_TO_OIL_EQ) # MJ-oil-eq
# add activation
cooling_dispatch[4] = {'Q_VCC_LT_gen_directload_W': q_chw_VCC_to_AHU_ARU_Wh,
'Q_VCC_HT_gen_directload_W': q_chw_VCC_to_SCU_Wh,
'VCC_LT_Status': VCC_LT_Status,
'VCC_HT_Status': VCC_HT_Status,
'E_VCC_LT_req_W': el_VCC_to_AHU_ARU_Wh,
'E_VCC_HT_req_W': el_VCC_to_SCU_Wh,
'E_CT_req_W': el_CT_Wh,
'E_cs_cre_cdata_req_W': el_total_Wh
}
# 5: VCC (AHU + ARU) + ACH (SCU) + CT
print 'Config 5: Vapor Compression Chillers(LT) -> AHU,ARU & Flate-place SC + Absorption Chillers(HT) -> SCU'
# ACH (SCU) operation
T_hw_FP_ACH_to_SCU_K, \
el_FP_ACH_to_SCU_Wh, \
q_cw_FP_ACH_to_SCU_Wh, \
q_hw_FP_ACH_to_SCU_Wh,\
q_chw_FP_ACH_to_SCU_Wh = calc_ACH_operation(T_ground_K, T_hw_in_FP_C, T_re_SCU_K, T_sup_SCU_K, locator,
mdot_SCU_kgpers, ACH_TYPE_SINGLE)
ACH_HT_Status = np.where(q_chw_FP_ACH_to_SCU_Wh > 0.0, 1, 0)
# boiler operation
q_gas_for_boiler_Wh, \
Q_nom_boiler_VCC_to_AHU_ARU_and_FP_to_single_ACH_to_SCU_W,\
q_load_from_boiler_Wh = calc_boiler_operation(Qc_nom_SCU_W, T_hw_FP_ACH_to_SCU_K,
q_hw_FP_ACH_to_SCU_Wh, q_sc_gen_FP_Wh)
# CT operation
q_CT_VCC_to_AHU_ARU_and_single_ACH_to_SCU_Wh = q_cw_VCC_to_AHU_ARU_Wh + q_cw_FP_ACH_to_SCU_Wh
Q_nom_CT_VCC_to_AHU_ARU_and_FP_to_single_ACH_to_SCU_W, \
el_CT_Wh = calc_CT_operation(q_CT_VCC_to_AHU_ARU_and_single_ACH_to_SCU_Wh)
# add electricity costs
el_total_Wh = el_VCC_to_AHU_ARU_Wh + el_FP_ACH_to_SCU_Wh + el_aux_SC_FP_Wh + el_CT_Wh
operation_results[5][7] += sum(lca.ELEC_PRICE * el_total_Wh) # CHF
operation_results[5][8] += sum(el_total_Wh * WH_TO_J / 1E6 * lca.EL_TO_CO2 / 1E3) # ton CO2
operation_results[5][9] += sum(el_total_Wh * WH_TO_J / 1E6 * lca.EL_TO_OIL_EQ) # MJ-oil-eq
# add gas costs
q_gas_total_Wh = q_gas_for_boiler_Wh
operation_results[5][7] += sum(prices.NG_PRICE * q_gas_total_Wh) # CHF
operation_results[5][8] += sum(
q_gas_total_Wh * WH_TO_J / 1E6 * lca.NG_BACKUPBOILER_TO_CO2_STD / 1E3) # ton CO2
operation_results[5][9] += sum(q_gas_total_Wh * WH_TO_J / 1E6 * lca.NG_BACKUPBOILER_TO_OIL_STD) # MJ-oil-eq
# add activation
cooling_dispatch[5] = {'Q_VCC_LT_gen_directload_W': q_chw_VCC_to_AHU_ARU_Wh,
'Q_ACH_HT_gen_directload_W': q_chw_FP_ACH_to_SCU_Wh,
'VCC_LT_Status': VCC_LT_Status,
'ACH_HT_Status': ACH_HT_Status,
'E_VCC_LT_req_W': el_VCC_to_AHU_ARU_Wh,
'E_ACH_HT_req_W': el_FP_ACH_to_SCU_Wh,
'E_SC_FP_req_W': el_aux_SC_FP_Wh,
'E_CT_req_W': el_CT_Wh,
'E_cs_cre_cdata_req_W': el_total_Wh,
'NG_Boiler_req': q_gas_for_boiler_Wh,
}
## Calculate Capex/Opex
# Initialize arrays
number_of_configurations = len(operation_results)
Capex_a_USD = np.zeros((number_of_configurations, 1))
Capex_total_USD = np.zeros((number_of_configurations, 1))
Opex_a_fixed_USD = np.zeros((number_of_configurations, 1))
print 'Cost calculation...'
# 0: DX
Capex_a_DX_USD, Opex_fixed_DX_USD, Capex_DX_USD = dx.calc_Cinv_DX(Qc_nom_AHU_ARU_SCU_W)
# add costs
Capex_a_USD[0][0] = Capex_a_DX_USD
Capex_total_USD[0][0] = Capex_DX_USD
Opex_a_fixed_USD[0][0] = Opex_fixed_DX_USD
# 1: VCC + CT
Capex_a_VCC_USD, Opex_fixed_VCC_USD, Capex_VCC_USD = chiller_vapor_compression.calc_Cinv_VCC(
Qc_nom_AHU_ARU_SCU_W, locator, config, 'CH3')
Capex_a_CT_USD, Opex_fixed_CT_USD, Capex_CT_USD = cooling_tower.calc_Cinv_CT(
Q_nom_CT_VCC_to_AHU_ARU_SCU_W, locator, 'CT1')
# add costs
Capex_a_USD[1][0] = Capex_a_CT_USD + Capex_a_VCC_USD
Capex_total_USD[1][0] = Capex_CT_USD + Capex_VCC_USD
Opex_a_fixed_USD[1][0] = Opex_fixed_CT_USD + Opex_fixed_VCC_USD
# 2: single effect ACH + CT + Boiler + SC_FP
Capex_a_ACH_USD, Opex_fixed_ACH_USD, Capex_ACH_USD = chiller_absorption.calc_Cinv_ACH(
Qc_nom_AHU_ARU_SCU_W, locator, ACH_TYPE_SINGLE)
Capex_a_CT_USD, Opex_fixed_CT_USD, Capex_CT_USD = cooling_tower.calc_Cinv_CT(
Q_nom_CT_FP_to_single_ACH_to_AHU_ARU_SCU_W, locator, 'CT1')
Capex_a_boiler_USD, Opex_fixed_boiler_USD, Capex_boiler_USD = boiler.calc_Cinv_boiler(
Q_nom_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_W, locator, config, 'BO1')
Capex_a_USD[2][0] = Capex_a_CT_USD + Capex_a_ACH_USD + Capex_a_boiler_USD + Capex_a_SC_FP_USD
Capex_total_USD[2][0] = Capex_CT_USD + Capex_ACH_USD + Capex_boiler_USD + Capex_SC_FP_USD
Opex_a_fixed_USD[2][
0] = Opex_fixed_CT_USD + Opex_fixed_ACH_USD + Opex_fixed_boiler_USD + Opex_SC_FP_USD
# 3: double effect ACH + CT + Boiler + SC_ET
Capex_a_ACH_USD, Opex_fixed_ACH_USD, Capex_ACH_USD = chiller_absorption.calc_Cinv_ACH(
Qc_nom_AHU_ARU_SCU_W, locator, ACH_TYPE_SINGLE)
Capex_a_CT_USD, Opex_fixed_CT_USD, Capex_CT_USD = cooling_tower.calc_Cinv_CT(
Q_nom_CT_ET_to_single_ACH_to_AHU_ARU_SCU_W, locator, 'CT1')
Capex_a_burner_USD, Opex_fixed_burner_USD, Capex_burner_USD = burner.calc_Cinv_burner(
Q_nom_Burner_ET_to_single_ACH_to_AHU_ARU_SCU_W, locator, config, 'BO1')
Capex_a_USD[3][0] = Capex_a_CT_USD + Capex_a_ACH_USD + Capex_a_burner_USD + Capex_a_SC_ET_USD
Capex_total_USD[3][0] = Capex_CT_USD + Capex_ACH_USD + Capex_burner_USD + Capex_SC_ET_USD
Opex_a_fixed_USD[3][
0] = Opex_fixed_CT_USD + Opex_fixed_ACH_USD + Opex_fixed_burner_USD + Opex_SC_ET_USD
# these two configurations are only activated when SCU is in use
if Qc_nom_SCU_W > 0.0:
# 4: VCC (AHU + ARU) + VCC (SCU) + CT
Capex_a_VCC_AA_USD, Opex_VCC_AA_USD, Capex_VCC_AA_USD = chiller_vapor_compression.calc_Cinv_VCC(
Qc_nom_AHU_ARU_W, locator, config, 'CH3')
Capex_a_VCC_S_USD, Opex_VCC_S_USD, Capex_VCC_S_USD = chiller_vapor_compression.calc_Cinv_VCC(
Qc_nom_SCU_W, locator, config, 'CH3')
Capex_a_CT_USD, Opex_fixed_CT_USD, Capex_CT_USD = cooling_tower.calc_Cinv_CT(
Q_nom_CT_VCC_to_AHU_ARU_and_VCC_to_SCU_W, locator, 'CT1')
Capex_a_USD[4][0] = Capex_a_CT_USD + Capex_a_VCC_AA_USD + Capex_a_VCC_S_USD
Capex_total_USD[4][0] = Capex_CT_USD + Capex_VCC_AA_USD + Capex_VCC_S_USD
Opex_a_fixed_USD[4][0] = Opex_fixed_CT_USD + Opex_VCC_AA_USD + Opex_VCC_S_USD
# 5: VCC (AHU + ARU) + ACH (SCU) + CT + Boiler + SC_FP
Capex_a_ACH_S_USD, Opex_fixed_ACH_S_USD, Capex_ACH_S_USD = chiller_absorption.calc_Cinv_ACH(
Qc_nom_SCU_W, locator, ACH_TYPE_SINGLE)
Capex_a_CT_USD, Opex_fixed_CT_USD, Capex_CT_USD = cooling_tower.calc_Cinv_CT(
Q_nom_CT_VCC_to_AHU_ARU_and_FP_to_single_ACH_to_SCU_W, locator, 'CT1')
Capex_a_boiler_USD, Opex_fixed_boiler_USD, Capex_boiler_USD = boiler.calc_Cinv_boiler(
Q_nom_boiler_VCC_to_AHU_ARU_and_FP_to_single_ACH_to_SCU_W, locator, config, 'BO1')
Capex_a_USD[5][0] = Capex_a_CT_USD + Capex_a_VCC_AA_USD + Capex_a_ACH_S_USD + \
Capex_a_SC_FP_USD + Capex_a_boiler_USD
Capex_total_USD[5][0] = Capex_CT_USD + Capex_VCC_AA_USD + Capex_ACH_S_USD + \
Capex_SC_FP_USD + Capex_boiler_USD
Opex_a_fixed_USD[5][0] = Opex_fixed_CT_USD + Opex_VCC_AA_USD + Opex_fixed_ACH_S_USD + \
Opex_SC_FP_USD + Opex_fixed_boiler_USD
## write all results from the configurations into TotalCosts, TotalCO2, TotalPrim
Opex_a_USD, TAC_USD, TotalCO2, TotalPrim = compile_TAC_CO2_Prim(Capex_a_USD, Opex_a_fixed_USD,
number_of_configurations, operation_results)
## Determine the best configuration
Best, indexBest = rank_results(TAC_USD, TotalCO2, TotalPrim, number_of_configurations)
# Save results in csv file
performance_results = {
"DX to AHU_ARU_SCU Share": operation_results[:, 0],
"VCC to AHU_ARU_SCU Share": operation_results[:, 1],
"single effect ACH to AHU_ARU_SCU Share (FP)": operation_results[:, 2],
"single effect ACH to AHU_ARU_SCU Share (ET)": operation_results[:, 3],
"VCC to AHU_ARU Share": operation_results[:, 4],
"VCC to SCU Share": operation_results[:, 5],
"single effect ACH to SCU Share (FP)": operation_results[:, 6],
"Capex_a_USD": Capex_a_USD[:, 0],
"Capex_total_USD": Capex_total_USD[:, 0],
"Opex_a_USD": Opex_a_USD[:, 1],
"Opex_a_fixed_USD": Opex_a_fixed_USD[:, 0],
"Opex_a_var_USD": operation_results[:, 7],
"GHG_tonCO2": operation_results[:, 8],
"PEN_MJoil": operation_results[:, 9],
"TAC_USD": TAC_USD[:, 1],
"Best configuration": Best[:, 0]
}
performance_results_df = pd.DataFrame(performance_results)
performance_results_df.to_csv(
locator.get_optimization_decentralized_folder_building_result_cooling(building_name))
# save activation for the best supply system configuration
best_activation_df = pd.DataFrame.from_dict(cooling_dispatch[indexBest]) #
best_activation_df.to_csv(
locator.get_optimization_decentralized_folder_building_cooling_activation(building_name))
print time.clock() - t0, "seconds process time for the decentralized Building Routine \n"
def disconnected_cooling_for_building(building_name, supply_systems, lca,
locator, prices, total_demand):
chiller_prop = supply_systems.Absorption_chiller
boiler_cost_data = supply_systems.Boiler
scale = 'BUILDING'
VCC_chiller = chiller_vapor_compression.VaporCompressionChiller(
locator, scale)
## Calculate cooling loads for different combinations
# SENSIBLE COOLING UNIT
Qc_nom_SCU_W, \
T_re_SCU_K, \
T_sup_SCU_K, \
mdot_SCU_kgpers = calc_combined_cooling_loads(building_name, locator, total_demand,
cooling_configuration=['scu'])
# AIR HANDLING UNIT + AIR RECIRCULATION UNIT
Qc_nom_AHU_ARU_W, \
T_re_AHU_ARU_K, \
T_sup_AHU_ARU_K, \
mdot_AHU_ARU_kgpers = calc_combined_cooling_loads(building_name, locator, total_demand,
cooling_configuration=['ahu', 'aru'])
# SENSIBLE COOLING UNIT + AIR HANDLING UNIT + AIR RECIRCULATION UNIT
Qc_nom_AHU_ARU_SCU_W, \
T_re_AHU_ARU_SCU_K, \
T_sup_AHU_ARU_SCU_K, \
mdot_AHU_ARU_SCU_kgpers = calc_combined_cooling_loads(building_name, locator, total_demand,
cooling_configuration=['ahu', 'aru', 'scu'])
## Get hourly hot water supply condition of Solar Collectors (SC)
# Flate Plate Solar Collectors
SC_FP_data, T_hw_in_FP_C, el_aux_SC_FP_Wh, q_sc_gen_FP_Wh = get_SC_data(
building_name, locator, panel_type="FP")
Capex_a_SC_FP_USD, Opex_SC_FP_USD, Capex_SC_FP_USD = solar_collector.calc_Cinv_SC(
SC_FP_data['Area_SC_m2'][0], locator, panel_type="FP")
# Evacuated Tube Solar Collectors
SC_ET_data, T_hw_in_ET_C, el_aux_SC_ET_Wh, q_sc_gen_ET_Wh = get_SC_data(
building_name, locator, panel_type="ET")
Capex_a_SC_ET_USD, Opex_SC_ET_USD, Capex_SC_ET_USD = solar_collector.calc_Cinv_SC(
SC_ET_data['Area_SC_m2'][0], locator, panel_type="ET")
## Calculate ground temperatures to estimate cold water supply temperatures for absorption chiller
T_ground_K = calculate_ground_temperature(
locator) # FIXME: change to outlet temperature from the cooling towers
## Initialize table to save results
# save costs of all supply configurations
operation_results = initialize_result_tables_for_supply_configurations(
Qc_nom_SCU_W)
# save supply system activation of all supply configurations
cooling_dispatch = {}
## HOURLY OPERATION
print('{building_name} decentralized cooling supply system simulations...'.
format(building_name=building_name))
T_re_AHU_ARU_SCU_K = np.where(T_re_AHU_ARU_SCU_K > 0.0, T_re_AHU_ARU_SCU_K,
T_sup_AHU_ARU_SCU_K)
## 0. DX operation
print('{building_name} Config 0: Direct Expansion Units -> AHU,ARU,SCU'.
format(building_name=building_name))
el_DX_hourly_Wh, \
q_DX_chw_Wh = np.vectorize(dx.calc_DX)(mdot_AHU_ARU_SCU_kgpers, T_sup_AHU_ARU_SCU_K, T_re_AHU_ARU_SCU_K)
DX_Status = np.where(q_DX_chw_Wh > 0.0, 1, 0)
# add electricity costs, CO2, PE
operation_results[0][7] += sum(prices.ELEC_PRICE * el_DX_hourly_Wh)
operation_results[0][8] += sum(
calc_emissions_Whyr_to_tonCO2yr(el_DX_hourly_Wh,
lca.EL_TO_CO2_EQ)) # ton CO2
# activation
cooling_dispatch[0] = {
'Q_DX_AS_gen_directload_W': q_DX_chw_Wh,
'E_DX_AS_req_W': el_DX_hourly_Wh,
'E_cs_cre_cdata_req_W': el_DX_hourly_Wh,
}
# capacity of cooling technologies
operation_results[0][0] = Qc_nom_AHU_ARU_SCU_W
operation_results[0][1] = Qc_nom_AHU_ARU_SCU_W # 1: DX_AS
system_COP = np.nanmedian(
np.divide(q_DX_chw_Wh[None, :], el_DX_hourly_Wh[None, :]).flatten())
operation_results[0][9] += system_COP
## 1. VCC (AHU + ARU + SCU) + CT
print(
'{building_name} Config 1: Vapor Compression Chillers -> AHU,ARU,SCU'.
format(building_name=building_name))
# VCC operation
el_VCC_Wh, q_VCC_cw_Wh, q_VCC_chw_Wh = calc_VCC_operation(
T_re_AHU_ARU_SCU_K, T_sup_AHU_ARU_SCU_K, mdot_AHU_ARU_SCU_kgpers,
VCC_chiller)
VCC_Status = np.where(q_VCC_chw_Wh > 0.0, 1, 0)
# CT operation
q_CT_VCC_to_AHU_ARU_SCU_Wh = q_VCC_cw_Wh
Q_nom_CT_VCC_to_AHU_ARU_SCU_W, el_CT_Wh = calc_CT_operation(
q_CT_VCC_to_AHU_ARU_SCU_Wh)
# add costs
el_total_Wh = el_VCC_Wh + el_CT_Wh
operation_results[1][7] += sum(prices.ELEC_PRICE * el_total_Wh) # CHF
operation_results[1][8] += sum(
calc_emissions_Whyr_to_tonCO2yr(el_total_Wh,
lca.EL_TO_CO2_EQ)) # ton CO2
system_COP_list = np.divide(q_VCC_chw_Wh[None, :],
el_total_Wh[None, :]).flatten()
system_COP = np.nansum(
q_VCC_chw_Wh[None, :] * system_COP_list) / np.nansum(
q_VCC_chw_Wh[None, :]) # weighted average of the system efficiency
operation_results[1][9] += system_COP
cooling_dispatch[1] = {
'Q_BaseVCC_AS_gen_directload_W': q_VCC_chw_Wh,
'E_BaseVCC_AS_req_W': el_VCC_Wh,
'E_CT_req_W': el_CT_Wh,
'E_cs_cre_cdata_req_W': el_total_Wh,
}
# capacity of cooling technologies
operation_results[1][0] = Qc_nom_AHU_ARU_SCU_W
operation_results[1][2] = Qc_nom_AHU_ARU_SCU_W # 2: BaseVCC_AS
## 2: SC_FP + single-effect ACH (AHU + ARU + SCU) + CT + Boiler + SC_FP
print(
'{building_name} Config 2: Flat-plate Solar Collectors + Single-effect Absorption chillers -> AHU,ARU,SCU'
.format(building_name=building_name))
# ACH operation
T_hw_out_single_ACH_K, \
el_single_ACH_Wh, \
q_cw_single_ACH_Wh, \
q_hw_single_ACH_Wh, \
q_chw_single_ACH_Wh = calc_ACH_operation(T_ground_K, T_hw_in_FP_C, T_re_AHU_ARU_SCU_K, T_sup_AHU_ARU_SCU_K,
chiller_prop, mdot_AHU_ARU_SCU_kgpers, ACH_TYPE_SINGLE)
ACH_Status = np.where(q_chw_single_ACH_Wh > 0.0, 1, 0)
# CT operation
q_CT_FP_to_single_ACH_to_AHU_ARU_SCU_Wh = q_cw_single_ACH_Wh
Q_nom_CT_FP_to_single_ACH_to_AHU_ARU_SCU_W, el_CT_Wh = calc_CT_operation(
q_CT_FP_to_single_ACH_to_AHU_ARU_SCU_Wh)
# boiler operation
q_gas_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh, \
Q_nom_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_W, \
q_load_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh = calc_boiler_operation(Qc_nom_AHU_ARU_SCU_W,
T_hw_out_single_ACH_K,
q_hw_single_ACH_Wh,
q_sc_gen_FP_Wh)
# add electricity costs
el_total_Wh = el_single_ACH_Wh + el_aux_SC_FP_Wh + el_CT_Wh
operation_results[2][7] += sum(prices.ELEC_PRICE * el_total_Wh) # CHF
operation_results[2][8] += sum(
calc_emissions_Whyr_to_tonCO2yr(el_total_Wh,
lca.EL_TO_CO2_EQ)) # ton CO2
# add gas costs
q_gas_total_Wh = q_gas_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh
operation_results[2][7] += sum(prices.NG_PRICE * q_gas_total_Wh) # CHF
operation_results[2][8] += sum(
calc_emissions_Whyr_to_tonCO2yr(q_gas_total_Wh,
lca.NG_TO_CO2_EQ)) # ton CO2
# add activation
cooling_dispatch[2] = {
'Q_ACH_gen_directload_W': q_chw_single_ACH_Wh,
'Q_Boiler_NG_ACH_W': q_load_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh,
'Q_SC_FP_ACH_W': q_sc_gen_FP_Wh,
'E_ACH_req_W': el_single_ACH_Wh,
'E_CT_req_W': el_CT_Wh,
'E_SC_FP_req_W': el_aux_SC_FP_Wh,
'E_cs_cre_cdata_req_W': el_total_Wh,
'NG_Boiler_req': q_gas_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh,
}
# capacity of cooling technologies
operation_results[2][0] = Qc_nom_AHU_ARU_SCU_W
operation_results[2][4] = Qc_nom_AHU_ARU_SCU_W # 4: ACH_SC_FP
q_total_load = q_chw_single_ACH_Wh[None, :] + q_sc_gen_FP_Wh[
None, :] + q_load_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh[None, :]
system_COP_list = np.divide(
q_total_load,
(el_total_Wh[None, :] +
q_gas_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh[None, :])).flatten()
system_COP = np.nansum(q_total_load * system_COP_list) / np.nansum(
q_total_load) # weighted average of the system efficiency
operation_results[2][9] += system_COP
# 3: SC_ET + single-effect ACH (AHU + ARU + SCU) + CT + Boiler + SC_ET
print(
'{building_name} Config 3: Evacuated Tube Solar Collectors + Single-effect Absorption chillers -> AHU,ARU,SCU'
.format(building_name=building_name))
# ACH operation
T_hw_out_single_ACH_K, \
el_single_ACH_Wh, \
q_cw_single_ACH_Wh, \
q_hw_single_ACH_Wh, \
q_chw_single_ACH_Wh = calc_ACH_operation(T_ground_K, T_hw_in_ET_C, T_re_AHU_ARU_SCU_K, T_sup_AHU_ARU_SCU_K,
chiller_prop, mdot_AHU_ARU_SCU_kgpers, ACH_TYPE_SINGLE)
# CT operation
q_CT_ET_to_single_ACH_to_AHU_ARU_SCU_W = q_cw_single_ACH_Wh
Q_nom_CT_ET_to_single_ACH_to_AHU_ARU_SCU_W, el_CT_Wh = calc_CT_operation(
q_CT_ET_to_single_ACH_to_AHU_ARU_SCU_W)
# burner operation
q_gas_for_burner_Wh, \
Q_nom_Burner_ET_to_single_ACH_to_AHU_ARU_SCU_W, \
q_burner_load_Wh = calc_burner_operation(Qc_nom_AHU_ARU_SCU_W, q_hw_single_ACH_Wh, q_sc_gen_ET_Wh)
# add electricity costs
el_total_Wh = el_single_ACH_Wh + el_aux_SC_ET_Wh + el_CT_Wh
operation_results[3][7] += sum(prices.ELEC_PRICE * el_total_Wh) # CHF
operation_results[3][8] += sum(
calc_emissions_Whyr_to_tonCO2yr(el_total_Wh,
lca.EL_TO_CO2_EQ)) # ton CO2
# add gas costs
operation_results[3][7] += sum(prices.NG_PRICE *
q_gas_for_burner_Wh) # CHF
operation_results[3][8] += sum(
calc_emissions_Whyr_to_tonCO2yr(q_gas_for_burner_Wh,
lca.NG_TO_CO2_EQ)) # ton CO2
# add activation
cooling_dispatch[3] = {
'Q_ACH_gen_directload_W': q_chw_single_ACH_Wh,
'Q_Burner_NG_ACH_W': q_burner_load_Wh,
'Q_SC_ET_ACH_W': q_sc_gen_ET_Wh,
'E_ACH_req_W': el_single_ACH_Wh,
'E_CT_req_W': el_CT_Wh,
'E_SC_ET_req_W': el_aux_SC_ET_Wh,
'E_cs_cre_cdata_req_W': el_total_Wh,
'NG_Burner_req': q_gas_for_burner_Wh,
}
# capacity of cooling technologies
operation_results[3][0] = Qc_nom_AHU_ARU_SCU_W
operation_results[3][5] = Qc_nom_AHU_ARU_SCU_W
q_total_load = (q_burner_load_Wh[None, :] + q_chw_single_ACH_Wh[None, :] +
q_sc_gen_ET_Wh[None, :])
system_COP_list = np.divide(
q_total_load,
(el_total_Wh[None, :] + q_gas_for_burner_Wh[None, :])).flatten()
system_COP = np.nansum(q_total_load * system_COP_list) / np.nansum(
q_total_load) # weighted average of the system efficiency
operation_results[3][9] += system_COP
# these two configurations are only activated when SCU is in use
if Qc_nom_SCU_W > 0.0:
# 4: VCC (AHU + ARU) + VCC (SCU) + CT
print(
'{building_name} Config 4: Vapor Compression Chillers(HT) -> SCU & Vapor Compression Chillers(LT) -> AHU,ARU'
.format(building_name=building_name))
# VCC (AHU + ARU) operation
el_VCC_to_AHU_ARU_Wh, \
q_cw_VCC_to_AHU_ARU_Wh, \
q_chw_VCC_to_AHU_ARU_Wh = calc_VCC_operation(T_re_AHU_ARU_K, T_sup_AHU_ARU_K, mdot_AHU_ARU_kgpers, VCC_chiller)
VCC_LT_Status = np.where(q_chw_VCC_to_AHU_ARU_Wh > 0.0, 1, 0)
# VCC(SCU) operation
el_VCC_to_SCU_Wh, \
q_cw_VCC_to_SCU_Wh, \
q_chw_VCC_to_SCU_Wh = calc_VCC_operation(T_re_SCU_K, T_sup_SCU_K, mdot_SCU_kgpers, VCC_chiller)
VCC_HT_Status = np.where(q_chw_VCC_to_AHU_ARU_Wh > 0.0, 1, 0)
# CT operation
q_CT_VCC_to_AHU_ARU_and_VCC_to_SCU_W = q_cw_VCC_to_AHU_ARU_Wh + q_cw_VCC_to_SCU_Wh
Q_nom_CT_VCC_to_AHU_ARU_and_VCC_to_SCU_W, el_CT_Wh = calc_CT_operation(
q_CT_VCC_to_AHU_ARU_and_VCC_to_SCU_W)
# add el costs
el_total_Wh = el_VCC_to_AHU_ARU_Wh + el_VCC_to_SCU_Wh + el_CT_Wh
operation_results[4][7] += sum(prices.ELEC_PRICE * el_total_Wh) # CHF
operation_results[4][8] += sum(
calc_emissions_Whyr_to_tonCO2yr(el_total_Wh,
lca.EL_TO_CO2_EQ)) # ton CO2
# add activation
cooling_dispatch[4] = {
'Q_BaseVCC_AS_gen_directload_W': q_chw_VCC_to_AHU_ARU_Wh,
'Q_BaseVCCHT_AS_gen_directload_W': q_chw_VCC_to_SCU_Wh,
'E_BaseVCC_req_W': el_VCC_to_AHU_ARU_Wh,
'E_VCC_HT_req_W': el_VCC_to_SCU_Wh,
'E_CT_req_W': el_CT_Wh,
'E_cs_cre_cdata_req_W': el_total_Wh
}
# capacity of cooling technologies
operation_results[4][0] = Qc_nom_AHU_ARU_SCU_W
operation_results[4][2] = Qc_nom_AHU_ARU_W # 2: BaseVCC_AS
operation_results[4][3] = Qc_nom_SCU_W # 3: VCCHT_AS
system_COP_list = np.divide(
q_CT_VCC_to_AHU_ARU_and_VCC_to_SCU_W[None, :],
el_total_Wh[None, :]).flatten()
system_COP = np.nansum(
q_CT_VCC_to_AHU_ARU_and_VCC_to_SCU_W[None, :] *
system_COP_list) / np.nansum(q_CT_VCC_to_AHU_ARU_and_VCC_to_SCU_W[
None, :]) # weighted average of the system efficiency
operation_results[4][9] += system_COP
# 5: VCC (AHU + ARU) + ACH (SCU) + CT
print(
'{building_name} Config 5: Vapor Compression Chillers(LT) -> AHU,ARU & Flate-place SC + Absorption Chillers(HT) -> SCU'
.format(building_name=building_name))
# ACH (SCU) operation
T_hw_FP_ACH_to_SCU_K, \
el_FP_ACH_to_SCU_Wh, \
q_cw_FP_ACH_to_SCU_Wh, \
q_hw_FP_ACH_to_SCU_Wh, \
q_chw_FP_ACH_to_SCU_Wh = calc_ACH_operation(T_ground_K, T_hw_in_FP_C, T_re_SCU_K, T_sup_SCU_K, chiller_prop,
mdot_SCU_kgpers, ACH_TYPE_SINGLE)
ACH_HT_Status = np.where(q_chw_FP_ACH_to_SCU_Wh > 0.0, 1, 0)
# boiler operation
q_gas_for_boiler_Wh, \
Q_nom_boiler_VCC_to_AHU_ARU_and_FP_to_single_ACH_to_SCU_W, \
q_load_from_boiler_Wh = calc_boiler_operation(Qc_nom_SCU_W, T_hw_FP_ACH_to_SCU_K,
q_hw_FP_ACH_to_SCU_Wh, q_sc_gen_FP_Wh)
# CT operation
q_CT_VCC_to_AHU_ARU_and_single_ACH_to_SCU_Wh = q_cw_VCC_to_AHU_ARU_Wh + q_cw_FP_ACH_to_SCU_Wh
Q_nom_CT_VCC_to_AHU_ARU_and_FP_to_single_ACH_to_SCU_W, \
el_CT_Wh = calc_CT_operation(q_CT_VCC_to_AHU_ARU_and_single_ACH_to_SCU_Wh)
# add electricity costs
el_total_Wh = el_VCC_to_AHU_ARU_Wh + el_FP_ACH_to_SCU_Wh + el_aux_SC_FP_Wh + el_CT_Wh
operation_results[5][7] += sum(prices.ELEC_PRICE * el_total_Wh) # CHF
operation_results[5][8] += sum(
calc_emissions_Whyr_to_tonCO2yr(el_total_Wh,
lca.EL_TO_CO2_EQ)) # ton CO2
# add gas costs
q_gas_total_Wh = q_gas_for_boiler_Wh
operation_results[5][7] += sum(prices.NG_PRICE * q_gas_total_Wh) # CHF
operation_results[5][8] += sum(
calc_emissions_Whyr_to_tonCO2yr(q_gas_total_Wh,
lca.NG_TO_CO2_EQ)) # ton CO2
# add activation
cooling_dispatch[5] = {
'Q_BaseVCC_AS_gen_directload_W': q_chw_VCC_to_AHU_ARU_Wh,
'Q_ACHHT_AS_gen_directload_W': q_chw_FP_ACH_to_SCU_Wh,
'E_BaseVCC_req_W': el_VCC_to_AHU_ARU_Wh,
'E_ACHHT_req_W': el_FP_ACH_to_SCU_Wh,
'E_SC_FP_ACH_req_W': el_aux_SC_FP_Wh,
'E_CT_req_W': el_CT_Wh,
'E_cs_cre_cdata_req_W': el_total_Wh,
'Q_BaseBoiler_NG_req': q_gas_for_boiler_Wh,
}
# capacity of cooling technologies
operation_results[5][0] = Qc_nom_AHU_ARU_SCU_W
operation_results[5][2] = Qc_nom_AHU_ARU_W # 2: BaseVCC_AS
operation_results[5][6] = Qc_nom_SCU_W # 6: ACHHT_SC_FP
q_total_load = q_CT_VCC_to_AHU_ARU_and_single_ACH_to_SCU_Wh[
None, :] + q_gas_for_boiler_Wh[None, :]
system_COP_list = np.divide(q_total_load,
el_total_Wh[None, :]).flatten()
system_COP = np.nansum(q_total_load * system_COP_list) / np.nansum(
q_total_load) # weighted average of the system efficiency
operation_results[5][9] += system_COP
## Calculate Capex/Opex
# Initialize arrays
number_of_configurations = len(operation_results)
Capex_a_USD = np.zeros((number_of_configurations, 1))
Capex_total_USD = np.zeros((number_of_configurations, 1))
Opex_a_fixed_USD = np.zeros((number_of_configurations, 1))
print('{building_name} Cost calculation...'.format(
building_name=building_name))
# 0: DX
Capex_a_DX_USD, Opex_fixed_DX_USD, Capex_DX_USD = dx.calc_Cinv_DX(
Qc_nom_AHU_ARU_SCU_W)
# add costs
Capex_a_USD[0][0] = Capex_a_DX_USD
Capex_total_USD[0][0] = Capex_DX_USD
Opex_a_fixed_USD[0][0] = Opex_fixed_DX_USD
# 1: VCC + CT
Capex_a_VCC_USD, Opex_fixed_VCC_USD, Capex_VCC_USD = chiller_vapor_compression.calc_Cinv_VCC(
Qc_nom_AHU_ARU_SCU_W, locator, 'CH3')
Capex_a_CT_USD, Opex_fixed_CT_USD, Capex_CT_USD = cooling_tower.calc_Cinv_CT(
Q_nom_CT_VCC_to_AHU_ARU_SCU_W, locator, 'CT1')
# add costs
Capex_a_USD[1][0] = Capex_a_CT_USD + Capex_a_VCC_USD
Capex_total_USD[1][0] = Capex_CT_USD + Capex_VCC_USD
Opex_a_fixed_USD[1][0] = Opex_fixed_CT_USD + Opex_fixed_VCC_USD
# 2: single effect ACH + CT + Boiler + SC_FP
Capex_a_ACH_USD, Opex_fixed_ACH_USD, Capex_ACH_USD = chiller_absorption.calc_Cinv_ACH(
Qc_nom_AHU_ARU_SCU_W, supply_systems.Absorption_chiller,
ACH_TYPE_SINGLE)
Capex_a_CT_USD, Opex_fixed_CT_USD, Capex_CT_USD = cooling_tower.calc_Cinv_CT(
Q_nom_CT_FP_to_single_ACH_to_AHU_ARU_SCU_W, locator, 'CT1')
Capex_a_boiler_USD, Opex_fixed_boiler_USD, Capex_boiler_USD = boiler.calc_Cinv_boiler(
Q_nom_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_W, 'BO1',
boiler_cost_data)
Capex_a_USD[2][
0] = Capex_a_CT_USD + Capex_a_ACH_USD + Capex_a_boiler_USD + Capex_a_SC_FP_USD
Capex_total_USD[2][
0] = Capex_CT_USD + Capex_ACH_USD + Capex_boiler_USD + Capex_SC_FP_USD
Opex_a_fixed_USD[2][
0] = Opex_fixed_CT_USD + Opex_fixed_ACH_USD + Opex_fixed_boiler_USD + Opex_SC_FP_USD
# 3: double effect ACH + CT + Boiler + SC_ET
Capex_a_ACH_USD, Opex_fixed_ACH_USD, Capex_ACH_USD = chiller_absorption.calc_Cinv_ACH(
Qc_nom_AHU_ARU_SCU_W, supply_systems.Absorption_chiller,
ACH_TYPE_SINGLE)
Capex_a_CT_USD, Opex_fixed_CT_USD, Capex_CT_USD = cooling_tower.calc_Cinv_CT(
Q_nom_CT_ET_to_single_ACH_to_AHU_ARU_SCU_W, locator, 'CT1')
Capex_a_burner_USD, Opex_fixed_burner_USD, Capex_burner_USD = burner.calc_Cinv_burner(
Q_nom_Burner_ET_to_single_ACH_to_AHU_ARU_SCU_W, boiler_cost_data,
'BO1')
Capex_a_USD[3][
0] = Capex_a_CT_USD + Capex_a_ACH_USD + Capex_a_burner_USD + Capex_a_SC_ET_USD
Capex_total_USD[3][
0] = Capex_CT_USD + Capex_ACH_USD + Capex_burner_USD + Capex_SC_ET_USD
Opex_a_fixed_USD[3][
0] = Opex_fixed_CT_USD + Opex_fixed_ACH_USD + Opex_fixed_burner_USD + Opex_SC_ET_USD
# these two configurations are only activated when SCU is in use
if Qc_nom_SCU_W > 0.0:
# 4: VCC (AHU + ARU) + VCC (SCU) + CT
Capex_a_VCC_AA_USD, Opex_VCC_AA_USD, Capex_VCC_AA_USD = chiller_vapor_compression.calc_Cinv_VCC(
Qc_nom_AHU_ARU_W, locator, 'CH3')
Capex_a_VCC_S_USD, Opex_VCC_S_USD, Capex_VCC_S_USD = chiller_vapor_compression.calc_Cinv_VCC(
Qc_nom_SCU_W, locator, 'CH3')
Capex_a_CT_USD, Opex_fixed_CT_USD, Capex_CT_USD = cooling_tower.calc_Cinv_CT(
Q_nom_CT_VCC_to_AHU_ARU_and_VCC_to_SCU_W, locator, 'CT1')
Capex_a_USD[4][
0] = Capex_a_CT_USD + Capex_a_VCC_AA_USD + Capex_a_VCC_S_USD
Capex_total_USD[4][
0] = Capex_CT_USD + Capex_VCC_AA_USD + Capex_VCC_S_USD
Opex_a_fixed_USD[4][
0] = Opex_fixed_CT_USD + Opex_VCC_AA_USD + Opex_VCC_S_USD
# 5: VCC (AHU + ARU) + ACH (SCU) + CT + Boiler + SC_FP
Capex_a_ACH_S_USD, Opex_fixed_ACH_S_USD, Capex_ACH_S_USD = chiller_absorption.calc_Cinv_ACH(
Qc_nom_SCU_W, supply_systems.Absorption_chiller, ACH_TYPE_SINGLE)
Capex_a_CT_USD, Opex_fixed_CT_USD, Capex_CT_USD = cooling_tower.calc_Cinv_CT(
Q_nom_CT_VCC_to_AHU_ARU_and_FP_to_single_ACH_to_SCU_W, locator,
'CT1')
Capex_a_boiler_USD, Opex_fixed_boiler_USD, Capex_boiler_USD = boiler.calc_Cinv_boiler(
Q_nom_boiler_VCC_to_AHU_ARU_and_FP_to_single_ACH_to_SCU_W, 'BO1',
boiler_cost_data)
Capex_a_USD[5][0] = Capex_a_CT_USD + Capex_a_VCC_AA_USD + Capex_a_ACH_S_USD + \
Capex_a_SC_FP_USD + Capex_a_boiler_USD
Capex_total_USD[5][0] = Capex_CT_USD + Capex_VCC_AA_USD + Capex_ACH_S_USD + \
Capex_SC_FP_USD + Capex_boiler_USD
Opex_a_fixed_USD[5][0] = Opex_fixed_CT_USD + Opex_VCC_AA_USD + Opex_fixed_ACH_S_USD + \
Opex_SC_FP_USD + Opex_fixed_boiler_USD
## write all results from the configurations into TotalCosts, TotalCO2, TotalPrim
Opex_a_USD, TAC_USD, TotalCO2, TotalPrim = compile_TAC_CO2_Prim(
Capex_a_USD, Opex_a_fixed_USD, number_of_configurations,
operation_results)
## Determine the best configuration
Best, indexBest = rank_results(TAC_USD, TotalCO2, TotalPrim,
number_of_configurations)
# Save results in csv file
performance_results = {
"Nominal heating load": operation_results[:, 0],
"Capacity_DX_AS_W": operation_results[:, 1],
"Capacity_BaseVCC_AS_W": operation_results[:, 2],
"Capacity_VCCHT_AS_W": operation_results[:, 3],
"Capacity_ACH_SC_FP_W": operation_results[:, 4],
"Capaticy_ACH_SC_ET_W": operation_results[:, 5],
"Capacity_ACHHT_FP_W": operation_results[:, 6],
"Capex_a_USD": Capex_a_USD[:, 0],
"Capex_total_USD": Capex_total_USD[:, 0],
"Opex_fixed_USD": Opex_a_fixed_USD[:, 0],
"Opex_var_USD": operation_results[:, 7],
"GHG_tonCO2": operation_results[:, 8],
"TAC_USD": TAC_USD[:, 1],
"Best configuration": Best[:, 0],
"system_COP": operation_results[:, 9],
}
performance_results_df = pd.DataFrame(performance_results)
performance_results_df.to_csv(
locator.get_optimization_decentralized_folder_building_result_cooling(
building_name),
index=False)
# save activation for the best supply system configuration
best_activation_df = pd.DataFrame.from_dict(cooling_dispatch[indexBest]) #
best_activation_df.to_csv(
locator.
get_optimization_decentralized_folder_building_cooling_activation(
building_name),
index=False)
def district_cooling_network(locator, master_to_slave_variables, config,
prices, lca, network_features):
"""
Computes the parameters for the cooling of the complete DCN
:param locator: path to res folder
:param network_features: network features
:param prices: Prices imported from the database
:type locator: string
:type network_features: class
:type prices: class
:return: costs, co2, prim
:rtype: tuple
"""
# THERMAL STORAGE + NETWORK
# Import Temperatures from Network Summary:
Q_thermal_req_W, \
T_district_cooling_return_K, \
T_district_cooling_supply_K,\
mdot_kgpers = calc_network_summary_DCN(locator, master_to_slave_variables)
print(
"CALCULATING ECOLOGICAL COSTS OF DAILY COOLING STORAGE - DUE TO OPERATION (IF ANY)"
)
# Initialize daily storage calss
T_ground_K = calculate_ground_temperature(locator, config)
daily_storage = LoadLevelingDailyStorage(
master_to_slave_variables.Storage_cooling_on,
master_to_slave_variables.Storage_cooling_size_W,
min(T_district_cooling_supply_K) - DT_COOL,
max(T_district_cooling_return_K) - DT_COOL, T_TANK_FULLY_DISCHARGED_K,
np.mean(T_ground_K))
# Import Data - potentials lake heat
if master_to_slave_variables.WS_BaseVCC_on == 1 or master_to_slave_variables.WS_PeakVCC_on == 1:
HPlake_Data = pd.read_csv(locator.get_lake_potential())
Q_therm_Lake = np.array(HPlake_Data['QLake_kW']) * 1E3
total_WS_VCC_installed = master_to_slave_variables.WS_BaseVCC_size_W + master_to_slave_variables.WS_PeakVCC_size_W
Q_therm_Lake_W = [
x if x < total_WS_VCC_installed else total_WS_VCC_installed
for x in Q_therm_Lake
]
T_source_average_Lake_K = np.array(HPlake_Data['Ts_C']) + 273
else:
Q_therm_Lake_W = np.zeros(HOURS_IN_YEAR)
T_source_average_Lake_K = np.zeros(HOURS_IN_YEAR)
Q_Trigen_NG_gen_W = np.zeros(HOURS_IN_YEAR)
Q_BaseVCC_WS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_PeakVCC_WS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_BaseVCC_AS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_PeakVCC_AS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_BackupVCC_AS_gen_W = np.zeros(HOURS_IN_YEAR)
Q_DailyStorage_gen_W = np.zeros(HOURS_IN_YEAR)
opex_var_Trigen_NG_USDhr = np.zeros(HOURS_IN_YEAR)
opex_var_BaseVCC_WS_USDhr = np.zeros(HOURS_IN_YEAR)
opex_var_PeakVCC_WS_USDhr = np.zeros(HOURS_IN_YEAR)
opex_var_BaseVCC_AS_USDhr = np.zeros(HOURS_IN_YEAR)
opex_var_PeakVCC_AS_USDhr = np.zeros(HOURS_IN_YEAR)
opex_var_BackupVCC_AS_USDhr = np.zeros(HOURS_IN_YEAR)
E_Trigen_NG_gen_W = np.zeros(HOURS_IN_YEAR)
E_BaseVCC_AS_req_W = np.zeros(HOURS_IN_YEAR)
E_PeakVCC_AS_req_W = np.zeros(HOURS_IN_YEAR)
E_BaseVCC_WS_req_W = np.zeros(HOURS_IN_YEAR)
E_PeakVCC_WS_req_W = np.zeros(HOURS_IN_YEAR)
E_BackupVCC_AS_req_W = np.zeros(HOURS_IN_YEAR)
NG_Trigen_req_W = np.zeros(HOURS_IN_YEAR)
source_Trigen_NG = np.zeros(HOURS_IN_YEAR)
source_BaseVCC_WS = np.zeros(HOURS_IN_YEAR)
source_PeakVCC_WS = np.zeros(HOURS_IN_YEAR)
source_BaseVCC_AS = np.zeros(HOURS_IN_YEAR)
source_PeakVCC_AS = np.zeros(HOURS_IN_YEAR)
for hour in range(
HOURS_IN_YEAR
): # cooling supply for all buildings excluding cooling loads from data centers
if Q_thermal_req_W[hour] > 0.0: # only if there is a cooling load!
daily_storage, \
activation_output, \
thermal_output, \
electricity_output, \
gas_output = cooling_resource_activator(Q_thermal_req_W[hour],
T_district_cooling_supply_K[hour],
T_district_cooling_return_K[hour],
Q_therm_Lake_W[hour],
T_source_average_Lake_K[hour],
daily_storage,
T_ground_K[hour],
lca,
master_to_slave_variables,
hour,
prices,
locator)
source_Trigen_NG[hour] = activation_output["source_Trigen_NG"]
source_BaseVCC_WS[hour] = activation_output["source_BaseVCC_WS"]
source_PeakVCC_WS[hour] = activation_output["source_PeakVCC_WS"]
source_BaseVCC_AS[hour] = activation_output["source_BaseVCC_AS"]
source_PeakVCC_AS[hour] = activation_output["source_PeakVCC_AS"]
Q_Trigen_NG_gen_W[hour] = thermal_output['Q_Trigen_NG_gen_W']
Q_BaseVCC_WS_gen_W[hour] = thermal_output['Q_BaseVCC_WS_gen_W']
Q_PeakVCC_WS_gen_W[hour] = thermal_output['Q_PeakVCC_WS_gen_W']
Q_BaseVCC_AS_gen_W[hour] = thermal_output['Q_BaseVCC_AS_gen_W']
Q_PeakVCC_AS_gen_W[hour] = thermal_output['Q_PeakVCC_AS_gen_W']
Q_BackupVCC_AS_gen_W[hour] = thermal_output['Q_BackupVCC_AS_gen_W']
Q_DailyStorage_gen_W[hour] = thermal_output[
'Q_DailyStorage_WS_gen_W']
E_BaseVCC_WS_req_W[hour] = electricity_output['E_BaseVCC_WS_req_W']
E_PeakVCC_WS_req_W[hour] = electricity_output['E_PeakVCC_WS_req_W']
E_BaseVCC_AS_req_W[hour] = electricity_output['E_BaseVCC_AS_req_W']
E_PeakVCC_AS_req_W[hour] = electricity_output['E_PeakVCC_AS_req_W']
E_BackupVCC_AS_req_W[hour] = electricity_output[
'E_BackupVCC_AS_req_W']
E_Trigen_NG_gen_W[hour] = electricity_output['E_Trigen_NG_gen_W']
NG_Trigen_req_W = gas_output['NG_Trigen_req_W']
# BACK-UPP VCC - AIR SOURCE
master_to_slave_variables.AS_BackupVCC_size_W = np.amax(
Q_BackupVCC_AS_gen_W)
if master_to_slave_variables.AS_BackupVCC_size_W != 0:
master_to_slave_variables.AS_BackupVCC_on = 1
for hour in range(HOURS_IN_YEAR):
opex_var_BackupVCC_AS_USDhr[hour], \
Q_BackupVCC_AS_gen_W[hour], \
E_BackupVCC_AS_req_W[hour] = calc_vcc_CT_operation(Q_BackupVCC_AS_gen_W[hour],
T_district_cooling_return_K[hour],
T_district_cooling_supply_K[hour],
VCC_T_COOL_IN,
lca)
# CAPEX (ANNUAL, TOTAL) AND OPEX (FIXED, VAR, ANNUAL) GENERATION UNITS
performance_costs_generation = cost_model.calc_generation_costs_cooling(
locator, master_to_slave_variables, config)
# CAPEX (ANNUAL, TOTAL) AND OPEX (FIXED, VAR, ANNUAL) STORAGE UNITS
performance_costs_storage = cost_model.calc_generation_costs_cooling_storage(
locator, master_to_slave_variables, config, daily_storage)
# CAPEX (ANNUAL, TOTAL) AND OPEX (FIXED, VAR, ANNUAL) NETWORK
performance_costs_network, \
E_used_district_cooling_network_W = cost_model.calc_network_costs_cooling(locator,
master_to_slave_variables,
network_features,
lca,
"DC")
# MERGE COSTS AND EMISSIONS IN ONE FILE
performance = dict(performance_costs_generation,
**performance_costs_storage)
district_cooling_costs = dict(performance, **performance_costs_network)
# SAVE
district_cooling_generation_dispatch = {
# demand of the network
"Q_districtcooling_sys_req_W": Q_thermal_req_W,
# Status of each technology 1 = on, 0 = off in every hour
"Trigen_NG_Status": source_Trigen_NG,
"BaseVCC_WS_Status": source_BaseVCC_WS,
"PeakVCC_WS_Status": source_PeakVCC_WS,
"BaseVCC_AS_Status": source_BaseVCC_AS,
"PeakVCC_AS_Status": source_PeakVCC_AS,
# ENERGY GENERATION
# from storage
"Q_DailyStorage_gen_directload_W": Q_DailyStorage_gen_W,
# cooling
"Q_Trigen_NG_gen_directload_W": Q_Trigen_NG_gen_W,
"Q_BaseVCC_WS_gen_directload_W": Q_BaseVCC_WS_gen_W,
"Q_PeakVCC_WS_gen_directload_W": Q_PeakVCC_WS_gen_W,
"Q_BaseVCC_AS_gen_directload_W": Q_BaseVCC_AS_gen_W,
"Q_PeakVCC_AS_gen_directload_W": Q_PeakVCC_AS_gen_W,
"Q_BackupVCC_AS_directload_W": Q_BackupVCC_AS_gen_W,
# electricity
"E_Trigen_NG_gen_W": E_Trigen_NG_gen_W
}
district_cooling_electricity_requirements_dispatch = {
# ENERGY REQUIREMENTS
# Electricity
"E_DCN_req_W": E_used_district_cooling_network_W,
"E_BaseVCC_WS_req_W": E_BaseVCC_WS_req_W,
"E_PeakVCC_WS_req_W": E_PeakVCC_WS_req_W,
"E_BaseVCC_AS_req_W": E_BaseVCC_AS_req_W,
"E_PeakVCC_AS_req_W": E_PeakVCC_AS_req_W,
"E_BackupVCC_AS_req_W": E_BackupVCC_AS_req_W,
}
district_cooling_fuel_requirements_dispatch = {
# fuels
"NG_Trigen_req_W": NG_Trigen_req_W
}
# PLOT RESULTS
return district_cooling_costs, \
district_cooling_generation_dispatch, \
district_cooling_electricity_requirements_dispatch,\
district_cooling_fuel_requirements_dispatch