# -*- coding: utf-8 -*- """ Created on Tue Sep 3 14:19:35 2024 @author: chris """ # import libraries import pandas as pd from scipy.interpolate import interp1d from math import ceil import json # PySAM unit modules import PySAM.TroughPhysicalIph as tr # system model import PySAM.LcoefcrDesign as lh # LCOH model # user inputs ================================================================= weather_files = ['denver_co_39.74_-104.992_psm3-2-2-tmy_60_tmy', 'boston_ma_42.3587_-71.0567_psm3-2-2-tmy_60_tmy'] location_names = ['Denver, CO', 'Boston, MA'] # for output process_temps = [100, 300, 500] # industrial process temperatures (C) solar_multiples = [1, 3, 5] thermal_storage_capacities = [24, 72, 120] # hours demand = 100 # industrial process heat demand size (MWth) # create default SAM model ==================================================== # create an instance of the TcstroughEmpirical module with defaults from the Parabolic Trough - LCOH Calculator configuration system_model = tr.default('PhysicalTroughIPHLCOHCalculator') lcoh_model = lh.from_existing(system_model, 'PhysicalTroughIPHLCOHCalculator') # attempted fix to utf-8 encoding error (temporary) =========================== # # Create a new instance of the TroughPhysicalIph and LcoefcrDesign module # system_model = tr.new() # lcoh_model = lh.new() # # Get the system model inputs from the JSON file # with open('PhysicalTroughIPHLCOHCalculator_default_trough_physical_iph.json', 'r') as f: # tr_inputs = json.load(f) # # Iterate through the input key-value pairs and set the module inputs # for k, v in tr_inputs.items(): # # temporary fix to 'adjust' variable mal-naming # if 'adjust' in k: # k = k.split('adjust_')[1] # if k != 'number_inputs': # system_model.value(k, v) # # Get the LCOH model inputs from the JSON file # with open('PhysicalTroughIPHLCOHCalculator_default_lcoefcr_design.json', 'r') as f: # lh_inputs = json.load(f) # # Iterate through the input key-value pairs and set the module inputs # for k, v in lh_inputs.items(): # # temporary fix to 'adjust' variable mal-naming # if 'adjust' in k: # k = k.split('adjust_')[1] # if k != 'number_inputs': # lcoh_model.value(k, v) # non-iterative inputs ======================================================== # (changed default SAM values, but will not change / perturb further) # tax assumptions lcoh_model.value('sales_tax_rate', 0) lcoh_model.value('c_tax_rate', 0) # fixed operating cost lcoh_model.value('fixed_operating_cost', 80 * demand * 1000) # 2023 USD / yr. # iterative inputs ============================================================ # (calculated or obtained automatically by the code for each case) i, loc = 0, 0 for weather_file in weather_files: # by location # Location name (for output) loc += 1 location_name = location_names[loc] # Look up design point DNI (W/m2) from weather file weather_file_path = 'C:\\Users\\chris\\SAM Downloaded Weather Files\\' + weather_file + '.csv' df = pd.read_csv(weather_file_path) I_bn_des_value = int(df.iloc[4118,5]) # DNI at noon on the summer solstice (June 21 in northern hemisphere) (W/m2) print(I_bn_des_value) system_model.value('I_bn_des_value', I_bn_des_value) for process_temp in process_temps: # by process temperature # Set loop outlet temperature T_loop_out = process_temp # C system_model.value('T_loop_out', T_loop_out) # C # Select heat transfer fluid if T_loop_out <= 200: system_model.value('combo_htf_type', 'Pressurized Water') # field HTF system_model.value('combo_tes_htf_type', 'Pressurized Water') # tank HTF min_operating_temp = 10 # C max_operating_temp = 220 # C rho = interp1d([10, 20, 30, 40, 50, 60, 70, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220] + 273.15, # K [999.7, 998.2, 995.6, 992.2, 988, 983.2, 977.7, 971.8, 965.3, 958.4, 951, 943.2, 934.9, 926.2, 917.1, 907.5, 897.5, 887.1, 876.1, 864.7, 852.8, 840.3]) # kg/m3 cp = interp1d([10, 20, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220] + 273.15, # K [4.23, 4.19, 4.18, 4.19, 4.20, 4.22, 4.23, 4.25, 4.27, 4.29, 4.31, 4.34, 4.37, 4.40, 4.44, 4.49, 4.54, 4.60]*1000) # J/kgK elif T_loop_out <= 250: system_model.value('combo_htf_type', 'Dowtherm Q') # field HTF system_model.value('combo_tes_htf_type', 'Dowtherm Q') # tank HTF min_operating_temp = -35 # C max_operating_temp = 330 # C # rho = interp1d(...) # cp = iterp1d(...) else: system_model.value('combo_htf_type', 'Hitec Solar Salt') # field HTF system_model.value('combo_tes_htf_type', 'Hitec Solar Salt') # tank HTF min_operating_temp = 238 # C max_operating_temp = 593 # C rho = interp1d([0, 1E9], [1750, 1750]) # placeholder (kg/m3) cp = interp1d([0, 1E9], [1550, 1550]) # placeholder (J/kgK) # Set loop inlet temperature T_loop_in_des = max(40, min_operating_temp + 20) # C system_model.value('T_loop_in_des', T_loop_in_des) # C # Freeze protection temperature system_model.value('T_fp', min_operating_temp) # C # Tank heater setpoints system_model.value('cold_tank_Thtr', T_loop_in_des - 30) # C system_model.value('hot_tank_Thtr', T_loop_out - 40) # C for thermal_storage_capacity in thermal_storage_capacities: # by thermal storage capacity # Calculate number of storage tanks required Q_tes_des = demand * thermal_storage_capacity # MWh(th) T_tes_cold = T_loop_in_des + 273.15 # K T_tes_hot = T_loop_out + 273.15 # K T_tes_ave = 0.5*(T_tes_hot + T_tes_cold) # K rho_ave, cp_ave = rho(T_tes_ave), cp(T_tes_ave) # kg/m3, J/kgK available_HTF_volume = Q_tes_des*3600 / (rho_ave * cp_ave / 1000 * (T_tes_hot - T_tes_cold)) # volume required to supply design hours of thermal energy storage (m3) h_min, h_tank = 0.5, 15 # m available_HTF_volume /= 1 - h_min / h_tank # additional volume necessary due to minimum tank limits system_model.value('tank_pairs', ceil(available_HTF_volume / 18850)) for solar_multiple in solar_multiples: # by solar multiple # execute models system_model.execute() lcoh_model.execute() print('Case ' + str(i) + ':') print(' Location = ' + location_name) print(' Demand Size = ' + str(demand) + ' MWth') print(' Process Temperature = ' + str(process_temp) + ' C') print(' Solar Multiple = ' + str(solar_multiple)) print(' Thermal Storage Capacity = ' + str(thermal_storage_capacity) + ' hours') print('Results:') print(' Capacity Factor = ' + str(system_model.Outputs.capacity_factor)) print(' LCOH = ' + str(lcoh_model.Outputs.lcoe_fcr) + ' $/kWh(th)')