diff --git a/setup.py b/setup.py index d8565034..670368ca 100644 --- a/setup.py +++ b/setup.py @@ -12,7 +12,7 @@ "watertap==1.0.0rc0", "idaes-pse==2.5.0", "pyomo==6.7.3", - "nrel-pysam == 5.1.0", + "nrel-pysam == 6.0.0", ], extras_require={ "dev": [ diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/CST.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/CST.py index db7a34d5..3efa9163 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/CST.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/CST.py @@ -6,6 +6,7 @@ Block, Constraint, SolverFactory, + Param, ) import os @@ -30,6 +31,8 @@ EnergyCosting, ) +import pickle + __all__ = [ "build_cst", "init_cst", @@ -58,54 +61,87 @@ def build_cst(blk, __file__=None): if __file__ == None: cwd = os.getcwd() - __file__ = cwd + r"\src\watertap_contrib\reflo\solar_models\surrogate\trough\\" + __file__ = ( + cwd + "/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/cst/" + ) dataset_filename = os.path.join( - os.path.dirname(__file__), r"data\test_trough_data.pkl" + os.path.dirname(__file__), + r"trough_kbhdp_heat_load_1_50_hours_storage_24_T_loop_out_300.pkl", ) + + # Updating pickle file output column names + with open(dataset_filename, "rb") as f: + df = pickle.load(f) + + # Rename the columns + df.rename(columns={"annual_energy": "heat_annual"}, inplace=True) + df.rename(columns={"electrical_load": "electricity_annual"}, inplace=True) + + # Save the modified DataFrame back as a pickle + with open(dataset_filename, "wb") as f: + pickle.dump(df, f) + surrogate_filename = os.path.join( os.path.dirname(__file__), - r"data\test_trough_data_heat_load_100_500_hours_storage_0_26.json", + r"trough_kbhdp_heat_load_1_50_hours_storage_24_T_loop_out_300.json", ) - input_bounds = dict(heat_load=[100, 500], hours_storage=[0, 26]) - input_units = dict(heat_load="MW", hours_storage="hour") + input_bounds = dict(heat_load=[1, 50]) # , hours_storage=[23, 24]) + input_units = dict(heat_load="MW") # , hours_storage="hour") input_variables = { - "labels": ["heat_load", "hours_storage"], + "labels": ["heat_load"], # "hours_storage"], "bounds": input_bounds, "units": input_units, } - output_units = dict(heat_annual_scaled="kWh", electricity_annual_scaled="kWh") + output_units = dict( + heat_annual_scaled="kWh", + electricity_annual_scaled="kWh", + total_aperture_area_scaled="m**2", + ) output_variables = { - "labels": ["heat_annual_scaled", "electricity_annual_scaled"], + "labels": [ + "heat_annual_scaled", + "electricity_annual_scaled", + "total_aperture_area_scaled", + ], "units": output_units, } blk.unit = TroughSurrogate( - surrogate_model_file=surrogate_filename, + # surrogate_model_file=surrogate_filename, + surrogate_filename_save=surrogate_filename, dataset_filename=dataset_filename, input_variables=input_variables, output_variables=output_variables, scale_training_data=True, ) + if hasattr(blk.unit, "hours_storage"): + print("Hours of storage is already any input parameter") + else: + print("Creating hours of storage parameter") + blk.unit.hours_storage = Param(initialize=24, units=pyunits.h, mutable=True) + def init_cst(blk): # Fix input variables for initialization - blk.unit.hours_storage.fix() - blk.unit.heat_load.fix() blk.unit.initialize() - blk.unit.heat_load.unfix() - def set_system_op_conditions(m): m.fs.system_capacity.fix() -def set_cst_op_conditions(blk, hours_storage=6): - blk.unit.hours_storage.fix(hours_storage) +def set_cst_op_conditions(blk, heat_load=10, hours_storage=6): + + if isinstance(m.fs.cst.unit.hours_storage, pyo.Param): + blk.unit.hours_storage.set_value(hours_storage) + + if isinstance(m.fs.cst.unit.hours_storage, pyo.Var): + blk.unit.hours_storage.fix(hours_storage) + blk.unit.heat_load.fix(heat_load) def add_cst_costing(blk, costing_block): @@ -113,12 +149,13 @@ def add_cst_costing(blk, costing_block): def calc_costing(m, blk): - blk.costing.heat_cost.set_value(0) blk.costing.cost_process() + # Updated to be 0 because this factor is not included in SAM + blk.costing.maintenance_labor_chemical_factor.fix(0) blk.costing.initialize() # TODO: Connect to the treatment volume - blk.costing.add_LCOW(m.fs.system_capacity) + # blk.costing.add_LCOW(m.fs.system_capacity) def report_cst(m, blk): @@ -149,9 +186,9 @@ def report_cst_costing(m, blk): print(f"\n\n-------------------- CST Costing Report --------------------\n") print("\n") - print( - f'{"LCOW":<30s}{value(blk.costing.LCOW):<20,.2f}{pyunits.get_units(blk.costing.LCOW)}' - ) + # print( + # f'{"LCOW":<30s}{value(blk.costing.LCOW):<20,.2f}{pyunits.get_units(blk.costing.LCOW)}' + # ) print( f'{"Capital Cost":<30s}{value(blk.costing.total_capital_cost):<20,.2f}{pyunits.get_units(blk.costing.total_capital_cost)}' @@ -181,14 +218,6 @@ def report_cst_costing(m, blk): # f'{"Heat Cost":<30s}{value(blk.costing.aggregate_flow_costs["heat"]):<20,.2f}{pyunits.get_units(blk.costing.aggregate_flow_costs["heat"])}' # ) - # print( - # f'{"Elec Flow":<30s}{value(blk.costing.aggregate_flow_electricity):<20,.2f}{pyunits.get_units(blk.costing.aggregate_flow_electricity)}' - # ) - - # print( - # f'{"Elec Cost":<30s}{value(blk.costing.aggregate_flow_costs["electricity"]):<20,.2f}{pyunits.get_units(blk.costing.aggregate_flow_costs["electricity"])}' - # ) - if __name__ == "__main__": @@ -199,17 +228,47 @@ def report_cst_costing(m, blk): build_cst(m.fs.cst) + set_cst_op_conditions(m.fs.cst, heat_load=50, hours_storage=24) init_cst(m.fs.cst) - set_cst_op_conditions(m.fs.cst) - add_cst_costing(m.fs.cst, costing_block=m.fs.costing) calc_costing(m, m.fs) - m.fs.costing.aggregate_flow_heat.fix(-70000) results = solver.solve(m) print(degrees_of_freedom(m)) report_cst(m, m.fs.cst.unit) report_cst_costing(m, m.fs) - # m.fs.costing.used_flows.display() + print( + f'{"Elec Flow":<30s}{value(m.fs.costing.aggregate_flow_electricity):<20,.2f}{pyunits.get_units(m.fs.costing.aggregate_flow_electricity)}' + ) + + print( + f'{"Elec Cost":<30s}{value(m.fs.costing.aggregate_flow_costs["electricity"]):<20,.2f}{pyunits.get_units(m.fs.costing.aggregate_flow_costs["electricity"])}' + ) + + m.fs.costing.add_LCOH() + print("LCOH:", m.fs.costing.LCOH()) + print("Hours of storage:", m.fs.cst.unit.hours_storage()) + print("Aperture area:", m.fs.cst.unit.total_aperture_area()) + + print("CST fixed cost:", m.fs.cst.unit.costing.fixed_operating_cost()) + + # Calcualating LCOH like SAM + cost = m.fs.costing + lcoh = ( + cost.total_capital_cost * cost.capital_recovery_factor + + cost.total_operating_cost + ) / m.fs.cst.unit.heat_annual + + print("\nManual LCOH check\n") + print("CRF:", cost.capital_recovery_factor()) + print( + "Numerator:", + ( + cost.total_capital_cost * cost.capital_recovery_factor + + cost.total_operating_cost + )(), + ) + print("Denominator:", m.fs.cst.unit.heat_annual()) + print("Calculated LCOH:", lcoh()) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/MD.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/MD.py index 9f99dda9..8f3171fd 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/MD.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/MD.py @@ -225,27 +225,31 @@ def init_md(blk, verbose=True, solver=None): # Build connection to permeate state junction blk.permeate.properties[0]._flow_vol_phase - @blk.Constraint( - doc="Assign the permeate flow rate to its respective state junction" - ) def get_permeate_flow(b): - num_modules = b.mp.get_active_process_blocks()[-1].fs.vagmd.num_modules + # num_modules = b.unit.mp.get_active_process_blocks()[-1].fs.vagmd.num_modules - return ( - b.permeate.properties[0].flow_vol_phase["Liq"] - == - # pyunits.convert( - pyunits.convert( - ( - num_modules - * b.mp.get_active_process_blocks()[-1].fs.acc_distillate_volume - / ( - b.mp.get_active_process_blocks()[-1].fs.dt - * (blk.n_time_points - 1) - ) - ), - to_units=pyunits.m**3 / pyunits.s, + vagmd = b.unit.mp.get_active_process_blocks()[-1].fs.vagmd + num_modules = pyunits.convert( + vagmd.system_capacity + / sum( + b.unit.mp.get_active_process_blocks()[i].fs.vagmd.permeate_flux + for i in range(blk.n_time_points) ) + * blk.n_time_points + / b.unit.mp.get_active_process_blocks()[0].fs.vagmd.module_area, + to_units=pyunits.dimensionless, + ) + + return b.permeate.properties[0].flow_vol_phase["Liq"] == pyunits.convert( + ( + num_modules + * b.unit.mp.get_active_process_blocks()[-1].fs.acc_distillate_volume + / ( + b.unit.mp.get_active_process_blocks()[-1].fs.dt + * (blk.n_time_points - 1) + ) + ), + to_units=pyunits.m**3 / pyunits.s, ) blk.permeate.properties[0].flow_mass_phase_comp["Liq", "TDS"].fix(0) @@ -261,15 +265,18 @@ def get_permeate_flow(b): doc="Assign the concentrate flow rate to its respective state junction" ) def get_concentrate_flow(b): - num_modules = b.mp.get_active_process_blocks()[-1].fs.vagmd.num_modules + num_modules = b.unit.mp.get_active_process_blocks()[-1].fs.vagmd.num_modules return b.concentrate.properties[0].flow_vol_phase["Liq"] == pyunits.convert( ( - num_modules - * blk.model_options["initial_batch_volume"] - * pyunits.L - * (1 - b.mp.get_active_process_blocks()[-1].fs.acc_recovery_ratio) - / (b.mp.get_active_process_blocks()[-1].fs.dt * (blk.n_time_points - 1)) + b.unit.mp.get_active_process_blocks()[-1].fs.vagmd.system_capacity + * (1 - m.water_recovery) + / m.water_recovery + # num_modules + # * blk.model_input["initial_batch_volume"] + # * pyunits.L + # * (1 - b.unit.mp.get_active_process_blocks()[-1].fs.acc_recovery_ratio) + # / (b.unit.mp.get_active_process_blocks()[-1].fs.dt * (blk.n_time_points - 1)) ), to_units=pyunits.m**3 / pyunits.s, ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/cst/trough_kbhdp_heat_load_1_100_hours_storage_24_T_loop_out_300.pkl b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/cst/trough_kbhdp_heat_load_1_100_hours_storage_24_T_loop_out_300.pkl new file mode 100644 index 00000000..96311cc7 Binary files /dev/null and b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/cst/trough_kbhdp_heat_load_1_100_hours_storage_24_T_loop_out_300.pkl differ diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/cst/trough_kbhdp_heat_load_1_50_hours_storage_24_T_loop_out_300.pkl b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/cst/trough_kbhdp_heat_load_1_50_hours_storage_24_T_loop_out_300.pkl new file mode 100644 index 00000000..993f2356 Binary files /dev/null and b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/cst/trough_kbhdp_heat_load_1_50_hours_storage_24_T_loop_out_300.pkl differ diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/cst/trough_physical_iph-reflo.json b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/cst/trough_physical_iph-reflo.json new file mode 100644 index 00000000..4e179dc8 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/cst/trough_physical_iph-reflo.json @@ -0,0 +1,206 @@ +{ + "is_dispatch" : 0, + "file_name" : "/Applications/SAM_2024.12.12/SAM.app/Contents/solar_resource/tucson_az_32.116521_-110.933042_psmv3_60_tmy.csv", + "q_pb_design" : 10, + "nHCEt" : 4, + "nColt" : 4, + "nHCEVar" : 4, + "FieldConfig" : 1, + "eta_pump" : 0.84999999999999998, + "Fluid" : 21, + "accept_loc" : 1, + "HDR_rough" : 4.57e-05, + "theta_stow" : 170, + "theta_dep" : 10, + "Row_Distance" : 15, + "T_loop_in_des" : 90, + "T_loop_out" : 300, + "T_startup" : 159.30000000000001, + "T_shutdown" : 159.30000000000001, + "use_abs_or_rel_mdot_limit" : 0, + "m_dot_htfmin" : 1, + "m_dot_htfmax" : 12, + "f_htfmin" : 0.25, + "f_htfmax" : 1.2, + "field_fl_props" : [ [ 20, 4.1799999999999997, 999, 0.001, 9.9999999999999995e-07, 0.58699999999999997, 85.299999999999997 ], [ 40, 4.1799999999999997, 993, 0.00065300000000000004, 6.5799999999999999e-07, 0.61799999999999999, 169 ], [ 60, 4.1799999999999997, 984, 0.00046700000000000002, 4.75e-07, 0.64200000000000002, 252 ], [ 80, 4.1900000000000004, 972, 0.00035500000000000001, 3.65e-07, 0.65700000000000003, 336 ], [ 100, 4.21, 959, 0.00028200000000000002, 2.9400000000000001e-07, 0.66600000000000004, 420 ], [ 120, 4.25, 944, 0.000233, 2.4600000000000001e-07, 0.67000000000000004, 505 ], [ 140, 4.2800000000000002, 927, 0.00019699999999999999, 2.1199999999999999e-07, 0.67000000000000004, 590 ], [ 160, 4.3399999999999999, 908, 0.00017100000000000001, 1.8799999999999999e-07, 0.66700000000000004, 676 ], [ 180, 4.4000000000000004, 887, 0.00014999999999999999, 1.6899999999999999e-07, 0.66100000000000003, 764 ], [ 200, 4.4900000000000002, 865, 0.000134, 1.55e-07, 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1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ] ], + "f_turb_tou_periods" : [ 1, 1, 1, 1, 1, 1, 1, 1, 1 ], + "is_tod_pc_target_also_pc_max" : 0, + "pb_fixed_par" : 0.0054999999999999997, + "bop_array" : [ 0, 1, 0, 0.48299999999999998, 0 ], + "aux_array" : [ 0.023, 1, 0.48299999999999998, 0.57099999999999995, 0 ], + "water_usage_per_wash" : 0.69999999999999996, + "washing_frequency" : 12, + "calc_design_pipe_vals" : 1, + "V_hdr_cold_max" : 3, + "V_hdr_cold_min" : 2, + "V_hdr_hot_max" : 3, + "V_hdr_hot_min" : 2, + "N_max_hdr_diams" : 10, + "L_rnr_pb" : 25, + "L_rnr_per_xpan" : 70, + "L_xpan_hdr" : 20, + "L_xpan_rnr" : 20, + "Min_rnr_xpans" : 1, + "northsouth_field_sep" : 20, + "N_hdr_per_xpan" : 2, + "offset_xpan_hdr" : 1, + "custom_sf_pipe_sizes" : 0, + "sf_rnr_diams" : [ [ -1 ] ], + "sf_rnr_wallthicks" : [ [ -1 ] ], + "sf_rnr_lengths" : [ [ -1 ] ], + "sf_hdr_diams" : [ [ -1 ] ], + "sf_hdr_wallthicks" : [ [ -1 ] ], + "sf_hdr_lengths" : [ [ -1 ] ], + "has_hot_tank_bypass" : 0, + "T_tank_hot_inlet_min" : 400, + "tes_pump_coef" : 0.14999999999999999, + "V_tes_des" : 1.8500000000000001, + "custom_tes_p_loss" : 0, + "k_tes_loss_coeffs" : [ [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ] ], + "custom_tes_pipe_sizes" : 0, + "tes_diams" : [ [ -1 ] ], + "tes_wallthicks" : [ [ -1 ] ], + "use_solar_mult_or_aperture_area" : 0, + "specified_solar_multiple" : 2.3, + "specified_total_aperture" : 20000, + "non_solar_field_land_area_multiplier" : 1.1000000000000001, + "trough_loop_control" : [ 4, 1, 1, 4, 1, 1, 3, 1, 1, 2, 1, 1, 1 ], + "csp_dtr_cost_site_improvements_cost_per_m2" : 16, + "csp_dtr_cost_solar_field_cost_per_m2" : 297, + "csp_dtr_cost_htf_system_cost_per_m2" : 60, + "csp_dtr_cost_storage_cost_per_kwht" : 62, + "csp_dtr_cost_heat_sink_cost_per_kwe" : 120, + "csp_dtr_cost_bop_per_kwe" : 90, + "csp_dtr_cost_contingency_percent" : 7, + "csp_dtr_cost_epc_per_acre" : 0, + "csp_dtr_cost_epc_percent" : 11, + "csp_dtr_cost_epc_per_watt" : 0, + "csp_dtr_cost_epc_fixed" : 0, + "csp_dtr_cost_plm_per_acre" : 10000, + "csp_dtr_cost_plm_percent" : 0, + "csp_dtr_cost_plm_per_watt" : 0, + "csp_dtr_cost_plm_fixed" : 0, + "csp_dtr_cost_sales_tax_percent" : 80, + "sales_tax_rate" : 5, + "adjust_constant" : 4, + "adjust_en_timeindex" : 0, + "adjust_en_periods" : 0, + "adjust_timeindex" : [ 0 ], + "adjust_periods" : [ [ 0, 0, 0 ] ] +} diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/run_pysam_kbhdp_trough.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/run_pysam_kbhdp_trough.py new file mode 100644 index 00000000..d57066c8 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/run_pysam_kbhdp_trough.py @@ -0,0 +1,198 @@ +################################################################################# +# WaterTAP Copyright (c) 2020-2023, The Regents of the University of California, +# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, +# National Renewable Energy Laboratory, and National Energy Technology +# Laboratory (subject to receipt of any required approvals from the U.S. Dept. +# of Energy). All rights reserved. +# +# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license +# information, respectively. These files are also available online at the URL +# "https://github.com/watertap-org/watertap/" +################################################################################# + +import json +from os.path import join, dirname +from math import floor, ceil, isnan +import numpy as np +import pandas as pd +import time +import multiprocessing +from itertools import product +import matplotlib.pyplot as plt +import PySAM.TroughPhysicalIph as iph +import os + +# TODO: +# Annual energy for year 1 is a little different than that calculated in SAM + + +def read_module_datafile(file_name): + with open(file_name, "r") as file: + data = json.load(file) + return data + + +def load_config(modules, file_names=None, module_data=None): + """ + Loads parameter values into PySAM modules, either from files or supplied dicts + + :param modules: List of PySAM modules + :param file_names: List of JSON file paths containing parameter values for respective modules + :param module_data: List of dictionaries containing parameter values for respective modules + + :returns: no return value + """ + for i in range(len(modules)): + if file_names is not None: + assert len(file_names) == len(modules) + data = read_module_datafile(file_names[i]) + elif module_data is not None: + assert len(module_data) == len(modules) + data = module_data[i] + else: + raise Exception("Either file_names or module_data must be assigned.") + + missing_values = [] # for debugging + for k, v in data.items(): + if k != "number_inputs": + try: + modules[i].value(k, v) + except: + missing_values.append(k) + pass + + +def setup_model( + model_name, + weather_file=None, + weather_data=None, + config_files=None, + config_data=None, +): + tech_model = iph.new() + modules = [tech_model] + + load_config(modules, config_files, config_data) + if weather_file is not None: + tech_model.Weather.file_name = weather_file + elif weather_data is not None: + tech_model.Weather.solar_resource_data = weather_data + else: + raise Exception("Either weather_file or weather_data must be specified.") + + return { + "tech_model": tech_model, + } + + +def run_model(modules, heat_load=None, hours_storage=None): + tech_model = modules["tech_model"] + + if heat_load is not None: + tech_model.value("q_pb_design", heat_load) + if hours_storage is not None: + tech_model.value("tshours", hours_storage) + tech_model.execute() + + # NOTE: freeze_protection_field can sometimes be nan (when it should be 0) and this causes other nan's + # Thus, freeze_protection, annual_energy and capacity_factor must be calculated manually + # annual_energy = tech_model.Outputs.annual_energy # [kWht] net, does not include that used for freeze protection + # freeze_protection = tech_model.Outputs.annual_thermal_consumption # [kWht] + # capacity_factor = tech_model.Outputs.capacity_factor # [%] + + freeze_protection_field = tech_model.Outputs.annual_field_freeze_protection + freeze_protection_field = ( + 0 if isnan(freeze_protection_field) else freeze_protection_field + ) # occasionally seen to be nan + freeze_protection_tes = tech_model.Outputs.annual_tes_freeze_protection + freeze_protection_tes = 0 if isnan(freeze_protection_tes) else freeze_protection_tes + freeze_protection = freeze_protection_field + freeze_protection_tes + annual_energy = ( + tech_model.Outputs.annual_energy - freeze_protection + ) # [kWht] net, does not include that used for freeze protection + capacity_factor = ( + annual_energy / (tech_model.value("q_pb_design") * 1e3 * 8760) * 100 + ) # [%] + + electrical_load = tech_model.Outputs.annual_electricity_consumption # [kWhe] + solar_multiplier = tech_model.Outputs.solar_mult + total_aperture_reflective_area = tech_model.Outputs.total_aperture # [m2] + nloops = tech_model.Outputs.nLoops + + return { + "annual_energy": annual_energy, # [kWh] annual net thermal energy in year 1 + "freeze_protection": freeze_protection, # [kWht] + "capacity_factor": capacity_factor, # [%] capacity factor + "electrical_load": electrical_load, # [kWhe] + "solar_multiplier": solar_multiplier, + "total_aperture_area": total_aperture_reflective_area, + "number_loops": nloops, + } + + +def setup_and_run( + model_name, weather_file, config_data, heat_load +): # , hours_storage): + modules = setup_model( + model_name, weather_file=weather_file, config_data=config_data + ) + result = run_model(modules, heat_load) # S, hours_storage) + return result + + +######################################################################################################### +if __name__ == "__main__": + # Model name is not relevant in WaterTAP-REFLO package because cost is calculated using REFLO costing packages + model_name = "TroughPhysicalIph_PhysicalTroughIPHLCOHCalculator" + __location__ = os.path.realpath( + os.path.join(os.getcwd(), os.path.dirname(__file__)) + ) + + config_files = [ + os.path.join(__location__, "cst/trough_physical_iph-reflo.json"), + ] + weather_file = os.path.join(__location__, "el_paso_texas-KBHDP-weather.csv") + dataset_filename = os.path.join( + __location__, + "cst/trough_kbhdp_heat_load_1_100_hours_storage_24_T_loop_out_300.pkl", + ) # output dataset for surrogate training + + config_data = [read_module_datafile(config_file) for config_file in config_files] + del config_data[0]["file_name"] # remove weather filename + + # Run parametrics via multiprocessing + data = [] + heat_loads = np.linspace(1, 100, 200) # [MWt] + # hours_storages = np.linspace(20, 24, 5) # [hr] + arguments = list(product(heat_loads)) # , hours_storages)) + df = pd.DataFrame(arguments, columns=["heat_load"]) # , "hours_storage"]) + + time_start = time.process_time() + with multiprocessing.Pool(processes=6) as pool: + args = [(model_name, weather_file, config_data, *args) for args in arguments] + results = pool.starmap(setup_and_run, args) + time_stop = time.process_time() + print("Multiprocessing time:", time_stop - time_start, "\n") + + df_results = pd.DataFrame(results) + + df = pd.concat( + [ + df, + df_results[ + [ + "annual_energy", + "freeze_protection", + "capacity_factor", + "electrical_load", + "solar_multiplier", + "total_aperture_area", + "number_loops", + ] + ], + ], + axis=1, + ) + df.to_pickle(dataset_filename) + + pass diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/__init__.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/__init__.py new file mode 100644 index 00000000..5f3ed52b --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/__init__.py @@ -0,0 +1,3 @@ +from .components import * +from .permian_pretreatment import * +from .permian_SOA import * diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/CST.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/CST.py new file mode 100644 index 00000000..399d707e --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/CST.py @@ -0,0 +1,281 @@ +from pyomo.environ import ( + ConcreteModel, + value, + assert_optimal_termination, + units as pyunits, + Block, + Constraint, + SolverFactory, + Param, +) +import os + +from idaes.core import FlowsheetBlock, UnitModelCostingBlock +from idaes.core.solvers import get_solver + +from watertap.core.util.model_diagnostics.infeasible import * +from idaes.core.util.scaling import * + +from watertap_contrib.reflo.solar_models.surrogate.trough.trough_surrogate import ( + TroughSurrogate, +) + +from idaes.core.util.model_statistics import ( + degrees_of_freedom, + number_variables, + number_total_constraints, + number_unused_variables, +) + +from watertap_contrib.reflo.costing import ( + EnergyCosting, +) + +import pickle + +__all__ = [ + "build_cst", + "init_cst", + "set_cst_op_conditions", + "add_cst_costing", + "report_cst", + "report_cst_costing", +] + + +def build_system(): + m = ConcreteModel() + m.fs = FlowsheetBlock(dynamic=False) + m.fs.costing = EnergyCosting() + + m.fs.system_capacity = Var(initialize=6000, units=pyunits.m**3 / pyunits.day) + + m.fs.cst = FlowsheetBlock(dynamic=False) + + return m + + +def build_cst(blk, __file__=None): + + print(f'\n{"=======> BUILDING CST SYSTEM <=======":^60}\n') + + if __file__ == None: + cwd = os.getcwd() + __file__ = ( + cwd + "/src/watertap_contrib/reflo/analysis/case_studies/permian/data/cst/" + ) + + dataset_filename = os.path.join( + os.path.dirname(__file__), + r"trough_permian_heat_load_1_100_hours_storage_24_T_loop_out_300.pkl", + ) + + # Updating pickle file output column names + with open(dataset_filename, "rb") as f: + df = pickle.load(f) + + # Rename the columns + df.rename(columns={"annual_energy": "heat_annual"}, inplace=True) + df.rename(columns={"electrical_load": "electricity_annual"}, inplace=True) + + # Save the modified DataFrame back as a pickle + with open(dataset_filename, "wb") as f: + pickle.dump(df, f) + + surrogate_filename = os.path.join( + os.path.dirname(__file__), + r"trough_permian_heat_load_1_100_hours_storage_24_T_loop_out_300.json", + ) + + input_bounds = dict(heat_load=[1, 100]) # , hours_storage=[23, 24]) + input_units = dict(heat_load="MW") # , hours_storage="hour") + input_variables = { + "labels": ["heat_load"], # "hours_storage"], + "bounds": input_bounds, + "units": input_units, + } + + output_units = dict( + heat_annual_scaled="kWh", + electricity_annual_scaled="kWh", + total_aperture_area_scaled="m**2", + ) + output_variables = { + "labels": [ + "heat_annual_scaled", + "electricity_annual_scaled", + "total_aperture_area_scaled", + ], + "units": output_units, + } + + blk.unit = TroughSurrogate( + surrogate_model_file=surrogate_filename, + # surrogate_filename_save=surrogate_filename, + dataset_filename=dataset_filename, + input_variables=input_variables, + output_variables=output_variables, + scale_training_data=True, + ) + + if hasattr(blk.unit, "hours_storage"): + print("Hours of storage is already any input parameter") + else: + print("Creating hours of storage parameter") + blk.unit.hours_storage = Param(initialize=24, units=pyunits.h, mutable=True) + + +def init_cst(blk): + # Fix input variables for initialization + blk.unit.initialize() + + + +def set_system_op_conditions(m): + m.fs.system_capacity.fix() + + +def set_cst_op_conditions(blk, heat_load=10, hours_storage=6): + + if isinstance(blk.unit.hours_storage, pyo.Param): + blk.unit.hours_storage.set_value(hours_storage) + + if isinstance(blk.unit.hours_storage, pyo.Var): + blk.unit.hours_storage.fix(hours_storage) + + blk.unit.heat_load.fix(heat_load) + +def add_cst_costing(blk, costing_block): + blk.unit.costing = UnitModelCostingBlock(flowsheet_costing_block=costing_block) + + +def calc_costing(m, blk): + blk.costing.cost_process() + # Updated to be 0 because this factor is not included in SAM + blk.costing.maintenance_labor_chemical_factor.fix(0) + blk.costing.initialize() + + +def report_cst(m, blk): + # blk = m.fs.cst + print(f"\n\n-------------------- CST Report --------------------\n") + print("\n") + + print( + f'{"Heat load":<30s}{value(blk.heat_load):<20,.2f}{pyunits.get_units(blk.heat_load)}' + ) + + print( + f'{"Heat annual":<30s}{value(blk.heat_annual):<20,.2f}{pyunits.get_units(blk.heat_annual)}' + ) + + print(f'{"Heat":<30s}{value(blk.heat):<20,.2f}{pyunits.get_units(blk.heat)}') + + print( + f'{"Electricity annual":<30s}{value(blk.electricity_annual):<20,.2f}{pyunits.get_units(blk.electricity_annual)}' + ) + + print( + f'{"Electricity":<30s}{value(blk.electricity):<20,.2f}{pyunits.get_units(blk.electricity)}' + ) + + +def report_cst_costing(m, blk): + print(f"\n\n-------------------- CST Costing Report --------------------\n") + print("\n") + + # print( + # f'{"LCOW":<30s}{value(blk.costing.LCOW):<20,.2f}{pyunits.get_units(blk.costing.LCOW)}' + # ) + + print( + f'{"Capital Cost":<30s}{value(blk.costing.total_capital_cost):<20,.2f}{pyunits.get_units(blk.costing.total_capital_cost)}' + ) + + print( + f'{"Fixed Operating Cost":<30s}{value(blk.costing.total_fixed_operating_cost):<20,.2f}{pyunits.get_units(blk.costing.total_fixed_operating_cost)}' + ) + + print( + f'{"Variable Operating Cost":<30s}{value(blk.costing.total_variable_operating_cost):<20,.2f}{pyunits.get_units(blk.costing.total_variable_operating_cost)}' + ) + + print( + f'{"Total Operating Cost":<30s}{value(blk.costing.total_operating_cost):<20,.2f}{pyunits.get_units(blk.costing.total_operating_cost)}' + ) + + # print( + # f'{"Aggregated Variable Operating Cost":<30s}{value(blk.costing.aggregate_variable_operating_cost):<20,.2f}{pyunits.get_units(blk.costing.aggregate_variable_operating_cost)}' + # ) + + # print( + # f'{"Heat flow":<30s}{value(blk.costing.aggregate_flow_heat):<20,.2f}{pyunits.get_units(blk.costing.aggregate_flow_heat)}' + # ) + + # print( + # f'{"Heat Cost":<30s}{value(blk.costing.aggregate_flow_costs["heat"]):<20,.2f}{pyunits.get_units(blk.costing.aggregate_flow_costs["heat"])}' + # ) + + +if __name__ == "__main__": + + solver = get_solver() + solver = SolverFactory("ipopt") + + m = build_system() + + build_cst(m.fs.cst) + + set_cst_op_conditions(m.fs.cst, heat_load=50, hours_storage=24) + init_cst(m.fs.cst) + + add_cst_costing(m.fs.cst, costing_block=m.fs.costing) + calc_costing(m, m.fs) + + print("Direct cost:", m.fs.cst.unit.costing.direct_cost()) + + # assert False + + try: + results = solver.solve(m) + except: + print_close_to_bounds(m) + + print(degrees_of_freedom(m)) + report_cst(m, m.fs.cst.unit) + report_cst_costing(m, m.fs) + + print( + f'{"Elec Flow":<30s}{value(m.fs.costing.aggregate_flow_electricity):<20,.2f}{pyunits.get_units(m.fs.costing.aggregate_flow_electricity)}' + ) + + print( + f'{"Elec Cost":<30s}{value(m.fs.costing.aggregate_flow_costs["electricity"]):<20,.2f}{pyunits.get_units(m.fs.costing.aggregate_flow_costs["electricity"])}' + ) + + m.fs.costing.add_LCOH() + print("LCOH:", m.fs.costing.LCOH()) + print("Hours of storage:", m.fs.cst.unit.hours_storage()) + print("Aperture area:", m.fs.cst.unit.total_aperture_area()) + print("Land area:", m.fs.cst.unit.land_area()) + + print("CST fixed cost:", m.fs.cst.unit.costing.fixed_operating_cost()) + + # Calcualating LCOH like SAM + cost = m.fs.costing + lcoh = ( + cost.total_capital_cost * cost.capital_recovery_factor + + cost.total_operating_cost + ) / m.fs.cst.unit.heat_annual + + print("\nManual LCOH check\n") + print("CRF:", cost.capital_recovery_factor()) + print( + "Numerator:", + ( + cost.total_capital_cost * cost.capital_recovery_factor + + cost.total_operating_cost + )(), + ) + print("Denominator:", m.fs.cst.unit.heat_annual()) + print("Calculated LCOH:", lcoh()) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/EC.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/EC.py new file mode 100644 index 00000000..78762c21 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/EC.py @@ -0,0 +1,302 @@ +import pathlib +from pyomo.environ import ( + ConcreteModel, + value, + TransformationFactory, + Param, + Var, + Constraint, + Set, + Expression, + Objective, + Block, + RangeSet, + check_optimal_termination, + assert_optimal_termination, + units as pyunits, +) +from pyomo.util.calc_var_value import calculate_variable_from_constraint as cvc + +from idaes.core import FlowsheetBlock, UnitModelCostingBlock +from idaes.core.util.initialization import propagate_state +from idaes.core.util.model_statistics import * +from idaes.core.util.scaling import * +from idaes.models.unit_models import Product, Feed, StateJunction, Separator + +from watertap.costing import WaterTAPCosting +from watertap.costing.zero_order_costing import ZeroOrderCosting +from watertap.core.util.model_diagnostics import * +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.core.util.initialization import * +from watertap.core.solvers import get_solver +from watertap.core.wt_database import Database +from watertap.core.zero_order_properties import ( + WaterParameterBlock as WaterParameterBlockZO, +) +from watertap.unit_models.zero_order import ElectrocoagulationZO + +from watertap_contrib.reflo.core import REFLODatabase +from watertap_contrib.reflo.costing import ( + TreatmentCosting, + EnergyCosting, + REFLOCosting, +) + + +rho = 1000 * pyunits.kg / pyunits.m**3 +reflo_dir = pathlib.Path(__file__).resolve().parents[4] +case_study_yaml = f"{reflo_dir}/data/technoeconomic/permian_case_study.yaml" + +__all__ = [ + "build_ec", + "set_ec_operating_conditions", + "set_ec_scaling", + "init_ec", + "add_ec_costing", +] + + +def build_system(): + """Function to create concrete model for individual unit model flowsheet""" + m = ConcreteModel() + m.db = REFLODatabase() + + m.fs = FlowsheetBlock(dynamic=False) + m.fs.properties = WaterParameterBlockZO(solute_list=["tds"]) + m.fs.costing = TreatmentCosting(case_study_definition=case_study_yaml) + + m.fs.feed = Feed(property_package=m.fs.properties) + + m.fs.EC = FlowsheetBlock(dynamic=False) + + build_ec(m, m.fs.EC) + + m.fs.feed_to_unit = Arc( + source=m.fs.feed.outlet, + destination=m.fs.EC.feed.inlet, + ) + + TransformationFactory("network.expand_arcs").apply_to(m) + + return m + + +def build_ec(m, blk, prop_package=None): + """Function to build EC unit model""" + + print(f'\n{"=======> BUILDING EC SYSTEM <=======":^60}\n') + if prop_package is None: + prop_package = m.fs.properties + + blk.feed = StateJunction(property_package=prop_package) + blk.product = StateJunction(property_package=prop_package) + blk.disposal = StateJunction(property_package=prop_package) + + blk.unit = ElectrocoagulationZO( + property_package=prop_package, + database=m.db, + electrode_material="aluminum", + reactor_material="pvc", + overpotential_calculation="calculated", + process_subtype="permian", + ) + + blk.feed_to_ec = Arc( + source=blk.feed.outlet, + destination=blk.unit.inlet, + ) + + blk.ec_to_product = Arc( + source=blk.unit.treated, + destination=blk.product.inlet, + ) + + blk.ec_to_disposal = Arc( + source=blk.unit.byproduct, + destination=blk.disposal.inlet, + ) + + TransformationFactory("network.expand_arcs").apply_to(m) + + +def set_system_operating_conditions(m, Qin=5, tds=130): + """This function sets the system operating conditions for individual unit model flowsheet""" + + Qin = Qin * pyunits.Mgallons / pyunits.day + flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + m.tds = tds + + # TODO: rho should probably be higher for 130 g/L + flow_mass_water = pyunits.convert(Qin * rho, to_units=pyunits.kg / pyunits.s) + inlet_dict = {"tds": tds * pyunits.kg / pyunits.m**3} + m.fs.feed.properties[0].flow_mass_comp["H2O"].fix(flow_mass_water) + m.fs.feed.properties[0].conc_mass_comp + + for solute, solute_conc in inlet_dict.items(): + flow_mass_solute = pyunits.convert( + Qin * solute_conc, to_units=pyunits.kg / pyunits.s + ) + m.fs.feed.properties[0].flow_mass_comp[solute].fix(flow_mass_solute) + m.fs.EC.unit.properties_in[0].flow_mass_comp[solute].set_value(flow_mass_solute) + + +def set_ec_operating_conditions(m, blk, conv=5e3, **kwargs): + """Set EC operating conditions""" + + blk.unit.load_parameters_from_database(use_default_removal=True) + # blk.unit.conductivity.unfix() + # tds_ec_conversion = conv * (pyunits.mg * pyunits.m) / (pyunits.liter * pyunits.S) + + # blk.unit.conductivity_constr = Constraint( + # expr=blk.unit.conductivity + # == pyunits.convert( + # blk.feed.properties[0].conc_mass_comp["tds"] / tds_ec_conversion, + # to_units=pyunits.S / pyunits.m, + # ) + # ) + for k, v in kwargs.items(): + try: + vv = getattr(blk.unit, k) + except: + continue + print(f"{blk.name} {vv.name} {v}") + if isinstance(vv, Var): + vv.fix(v) + if isinstance(vv, Param): + vv.set_value(v) + + print(f"Electrocoagulation") + print(f"\tblock DOF = {degrees_of_freedom(blk)}\n") + print(f"\tunit DOF = {degrees_of_freedom(blk.unit)}\n") + + +def set_ec_scaling(m, blk, calc_blk_scaling_factors=False): + + set_scaling_factor(blk.unit.properties_in[0].flow_vol, 1e7) + set_scaling_factor(blk.unit.properties_in[0].conc_mass_comp["tds"], 1e5) + set_scaling_factor(blk.unit.charge_loading_rate, 1e3) + set_scaling_factor(blk.unit.cell_voltage, 1) + set_scaling_factor(blk.unit.anode_area, 1e-3) + set_scaling_factor(blk.unit.cathode_area, 1e-3) + set_scaling_factor(blk.unit.current_density, 1e-1) + set_scaling_factor(blk.unit.applied_current, 1e-6) + set_scaling_factor(blk.unit.metal_dose, 1e3) + set_scaling_factor(blk.unit.electrode_thick, 1e3) + set_scaling_factor(blk.unit.electrode_mass, 1e-4) + set_scaling_factor(blk.unit.electrode_volume, 1) + set_scaling_factor(blk.unit.electrode_gap, 1e3) + set_scaling_factor(blk.unit.conductivity, 0.1) + set_scaling_factor(blk.unit.overpotential, 1) + set_scaling_factor(blk.unit.reactor_volume, 0.1) + set_scaling_factor(blk.unit.ohmic_resistance, 1e7) + set_scaling_factor(blk.unit.charge_loading_rate, 1e-3) + set_scaling_factor(blk.unit.power_required, 1e-6) + set_scaling_factor(blk.unit.overpotential_k1, 1) + set_scaling_factor(blk.unit.overpotential_k2, 1) + + # Calculate scaling factors only for EC block if in full case study flowsheet + # so we don't prematurely set scaling factors + if calc_blk_scaling_factors: + calculate_scaling_factors(blk) + + # otherwise calculate all scaling factors + else: + calculate_scaling_factors(m) + + +def init_system(m, solver=None): + """Initialize system for individual unit process flowsheet""" + if solver is None: + solver = get_solver() + + optarg = solver.options + + print("\n\n-------------------- INITIALIZING SYSTEM --------------------\n\n") + print(f"System Degrees of Freedom: {degrees_of_freedom(m)}") + print(f"EC Degrees of Freedom: {degrees_of_freedom(m.fs.EC.unit)}") + assert_no_degrees_of_freedom(m) + print("\n\n") + + m.fs.feed.initialize(optarg=optarg) + propagate_state(m.fs.feed_to_unit) + + init_ec(m, m.fs.EC) + + +def init_ec(m, blk, solver=None): + """Initialize EC model""" + + if solver is None: + solver = get_solver() + + optarg = solver.options + + blk.feed.initialize(optarg=optarg) + propagate_state(blk.feed_to_ec) + + cvc(blk.unit.overpotential, blk.unit.eq_overpotential) + cvc(blk.unit.applied_current, blk.unit.eq_applied_current) + cvc(blk.unit.anode_area, blk.unit.eq_electrode_area_total) + cvc(blk.unit.ohmic_resistance, blk.unit.eq_ohmic_resistance) + + blk.unit.initialize(optarg=optarg) + propagate_state(blk.ec_to_product) + propagate_state(blk.ec_to_disposal) + + blk.product.initialize() + blk.disposal.initialize() + print(f"Electrocoagulation") + print(f"\tblock DOF after init = {degrees_of_freedom(blk)}\n") + print(f"\tunit DOF after init = {degrees_of_freedom(blk.unit)}\n") + + +def add_system_costing(m): + """Add system level costing components""" + + # m.fs.costing.electricity_cost.fix(0.07) + add_ec_costing(m, m.fs.EC) + calc_costing(m, m.fs.EC) + + +def add_ec_costing(m, blk, flowsheet_costing_block=None): + """Add EC model costing components""" + if flowsheet_costing_block is None: + flowsheet_costing_block = m.fs.costing + blk.unit.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block + ) + + +def calc_costing(m, blk): + """Add system level solve for costing""" + m.fs.costing.cost_process() + m.fs.costing.add_LCOW(blk.unit.properties_treated[0].flow_vol) + m.fs.costing.add_electricity_intensity(blk.unit.properties_treated[0].flow_vol) + + +def report_EC(blk): + print(f'{f"Stream":<20}{f"FLOW RATE H2O":<20}{f"FLOW RATE TDS":<20}') + print( + f'{"FEED":<20}{value(blk.feed.properties[0].flow_mass_comp["H2O"]):<20.2f}{value(blk.feed.properties[0].flow_mass_comp["tds"]):<20.2f} kg/s' + ) + print( + f'{"PRODUCT":<20}{value(blk.product.properties[0].flow_mass_comp["H2O"]):<20.2f}{value(blk.product.properties[0].flow_mass_comp["tds"]):<20.2f} kg/s' + ) + print( + f'{"DISPOSAL":<20}{value(blk.disposal.properties[0].flow_mass_comp["H2O"]):<20.2f}{value(blk.disposal.properties[0].flow_mass_comp["tds"]):<20.2f} kg/s' + ) + + +if __name__ == "__main__": + + m = build_system() + set_system_operating_conditions(m, tds=130) + set_ec_operating_conditions(m, m.fs.EC) + set_ec_scaling(m, m.fs.EC) + init_system(m) + add_system_costing(m) + + solver = get_solver() + results = solver.solve(m) + assert_optimal_termination(results) + print(f"LCOW = {m.fs.costing.LCOW()}") diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/MD.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/MD.py new file mode 100644 index 00000000..c162d4ca --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/MD.py @@ -0,0 +1,547 @@ +import os +import math +import numpy as np +from pyomo.environ import ( + ConcreteModel, + value, + Param, + Var, + Constraint, + Set, + Expression, + TransformationFactory, + Objective, + NonNegativeReals, + Block, + RangeSet, + check_optimal_termination, + units as pyunits, + SolverFactory, +) +from pyomo.network import Arc, SequentialDecomposition +from pyomo.util.check_units import assert_units_consistent +from idaes.core import FlowsheetBlock, UnitModelCostingBlock, MaterialFlowBasis +from idaes.core.solvers import get_solver +from idaes.core.util.initialization import propagate_state as _prop_state +import idaes.core.util.scaling as iscale +from idaes.core.util.scaling import ( + constraint_scaling_transform, + calculate_scaling_factors, + set_scaling_factor, +) +import idaes.logger as idaeslogger +from idaes.core.util.exceptions import InitializationError +from idaes.models.unit_models import Product, Feed, StateJunction, Separator +from idaes.core.util.model_statistics import * + +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.property_models.seawater_prop_pack import SeawaterParameterBlock + +from watertap_contrib.reflo.costing import ( + TreatmentCosting, + EnergyCosting, + REFLOCosting, +) +from watertap.costing.zero_order_costing import ZeroOrderCosting + +# Flowsheet function imports +from watertap_contrib.reflo.analysis.multiperiod.vagmd_batch.VAGMD_batch_flowsheet import ( + build_vagmd_flowsheet, + fix_dof_and_initialize, +) + +from watertap_contrib.reflo.analysis.multiperiod.vagmd_batch.VAGMD_batch_design_model import ( + get_n_time_points, +) + +from watertap_contrib.reflo.analysis.multiperiod.vagmd_batch.VAGMD_batch_multiperiod_unit_model import ( + VAGMDbatchSurrogate, +) + +from watertap_contrib.reflo.analysis.multiperiod.vagmd_batch.VAGMD_batch_multiperiod_flowsheet import ( + get_vagmd_batch_variable_pairs, + unfix_dof, + build_VAGMD_batch_multiperiod_fs, +) + +from idaes.apps.grid_integration.multiperiod.multiperiod import MultiPeriodModel + +import matplotlib.pyplot as plt + +__all__ = [ + "build_md", + "set_md_model_options", + "init_md", + "report_MD", + "report_md_costing", +] + + +def propagate_state(arc): + _prop_state(arc) + + +def build_system(Qin=5, Cin=130, water_recovery=0.4): + m = ConcreteModel() + m.fs = FlowsheetBlock(dynamic=False) + m.fs.costing = TreatmentCosting() + + m.inlet_flow_rate = pyunits.convert( + Qin * pyunits.Mgallons / pyunits.day, to_units=pyunits.m**3 / pyunits.s + ) + m.inlet_salinity = pyunits.convert( + Cin * pyunits.g / pyunits.liter, to_units=pyunits.kg / pyunits.m**3 + ) + m.water_recovery = water_recovery + + # Property package + m.fs.properties = SeawaterParameterBlock() + + # Create feed, product and concentrate state blocks + m.fs.feed = Feed(property_package=m.fs.properties) + m.fs.product = Product(property_package=m.fs.properties) + m.fs.disposal = Product(property_package=m.fs.properties) + + # Create MD unit model at flowsheet level + m.fs.md = FlowsheetBlock(dynamic=False) + build_md(m, m.fs.md, prop_package=m.fs.properties) + add_connections(m) + + return m + + +def add_connections(m): + + m.fs.feed_to_md = Arc(source=m.fs.feed.outlet, destination=m.fs.md.feed.inlet) + + m.fs.md_to_product = Arc( + source=m.fs.md.permeate.outlet, destination=m.fs.product.inlet + ) + + m.fs.md_to_disposal = Arc( + source=m.fs.md.concentrate.outlet, destination=m.fs.disposal.inlet + ) + + TransformationFactory("network.expand_arcs").apply_to(m) + + +def set_md_model_options(m, blk, n_time_points=None): + + m.system_capacity = m.water_recovery * pyunits.convert( + m.inlet_flow_rate, to_units=pyunits.m**3 / pyunits.day + ) + m.feed_salinity = pyunits.convert(m.inlet_salinity, to_units=pyunits.g / pyunits.L) + + model_options = { + "dt": None, + "system_capacity": value(m.system_capacity), # m3/day + "feed_flow_rate": 750, # L/h + "evap_inlet_temp": 80, + "cond_inlet_temp": 20, + "feed_temp": 25, + "feed_salinity": value(m.feed_salinity), # g/L + "initial_batch_volume": 50, # L + "module_type": "AS7C1.5L", # "AS26C7.2L" + "cooling_system_type": "closed", + "cooling_inlet_temp": 25, + "recovery_ratio": m.water_recovery, + } + + if n_time_points == None: + # Calculate the number of periods to reach target recovery rate by solving the system first + n_time_points = get_n_time_points( + dt=model_options["dt"], + feed_flow_rate=model_options["feed_flow_rate"], + evap_inlet_temp=model_options["evap_inlet_temp"], + cond_inlet_temp=model_options["cond_inlet_temp"], + feed_temp=model_options["feed_temp"], + feed_salinity=model_options["feed_salinity"], + recovery_ratio=model_options["recovery_ratio"], + initial_batch_volume=model_options["initial_batch_volume"], + module_type=model_options["module_type"], + cooling_system_type=model_options["cooling_system_type"], + cooling_inlet_temp=model_options["cooling_inlet_temp"], + ) + + blk.model_input = model_options + blk.n_time_points = n_time_points + + +def build_md(m, blk, prop_package=None) -> None: + + print(f'\n{"=======> BUILDING MEMBRANE DISTILLATION SYSTEM <=======":^60}\n') + if prop_package is None: + prop_package = m.fs.properties + + # Build a feed, permeate and brine state function for MD + blk.feed = StateJunction(property_package=prop_package) + blk.permeate = StateJunction(property_package=prop_package) + blk.concentrate = StateJunction(property_package=prop_package) + + set_md_model_options(m, blk, n_time_points=None) + + blk.unit = VAGMDbatchSurrogate(model_input=blk.model_input) + + +def init_md(m, blk, verbose=True, solver=None): + # blk = m.fs.md + blk.feed.initialize() + + # Build connection to permeate state junction + blk.permeate.properties[0]._flow_vol_phase + + @blk.Constraint( + doc="Assign the permeate flow rate to its respective state junction" + ) + def get_permeate_flow(b): + # num_modules = b.unit.mp.get_active_process_blocks()[-1].fs.vagmd.num_modules + + vagmd = b.unit.mp.get_active_process_blocks()[-1].fs.vagmd + num_modules = pyunits.convert( + vagmd.system_capacity + / sum( + b.unit.mp.get_active_process_blocks()[i].fs.vagmd.permeate_flux + for i in range(blk.n_time_points) + ) + * blk.n_time_points + / b.unit.mp.get_active_process_blocks()[0].fs.vagmd.module_area, + to_units=pyunits.dimensionless, + ) + + return b.permeate.properties[0].flow_vol_phase["Liq"] == pyunits.convert( + ( + num_modules + * b.unit.mp.get_active_process_blocks()[-1].fs.acc_distillate_volume + / ( + b.unit.mp.get_active_process_blocks()[-1].fs.dt + * (blk.n_time_points - 1) + ) + ), + to_units=pyunits.m**3 / pyunits.s, + ) + + blk.permeate.properties[0].flow_mass_phase_comp["Liq", "TDS"].fix(0) + blk.permeate.properties[0].pressure.fix(101325) + blk.permeate.properties[0].temperature.fix(298.15) + + # # Build connection to concentrate state junction + + blk.concentrate.properties[0]._flow_vol_phase + blk.concentrate.properties[0]._conc_mass_phase_comp + + @blk.Constraint( + doc="Assign the concentrate flow rate to its respective state junction" + ) + def get_concentrate_flow(b): + num_modules = b.unit.mp.get_active_process_blocks()[-1].fs.vagmd.num_modules + + return b.concentrate.properties[0].flow_vol_phase["Liq"] == pyunits.convert( + ( + b.unit.mp.get_active_process_blocks()[-1].fs.vagmd.system_capacity + * (1 - m.water_recovery) + / m.water_recovery + # num_modules + # * blk.model_input["initial_batch_volume"] + # * pyunits.L + # * (1 - b.unit.mp.get_active_process_blocks()[-1].fs.acc_recovery_ratio) + # / (b.unit.mp.get_active_process_blocks()[-1].fs.dt * (blk.n_time_points - 1)) + ), + to_units=pyunits.m**3 / pyunits.s, + ) + + @blk.Constraint( + doc="Assign the concentrate concentration to its respective state junction" + ) + def get_concentrate_conc(b): + return b.concentrate.properties[0].conc_mass_phase_comp[ + "Liq", "TDS" + ] == pyunits.convert( + b.unit.mp.get_active_process_blocks()[-1] + .fs.vagmd.feed_props[0] + .conc_mass_phase_comp["Liq", "TDS"], + to_units=pyunits.kg / pyunits.m**3, + ) + + blk.concentrate.properties[0].pressure.fix(101325) + blk.concentrate.properties[0].temperature.fix(298.15) + + # # set_md_initial_conditions(blk) + + +def init_system(m, verbose=True, solver=None): + if solver is None: + solver = get_solver() + + optarg = solver.options + + print( + "\n\n-------------------- INITIALIZING MEMBRANE DISTILLATION --------------------\n\n" + ) + print(f"System Degrees of Freedom: {degrees_of_freedom(m)}") + print("\n\n") + + m.fs.feed.initialize() + propagate_state(m.fs.feed_to_md) + + init_md(m, m.fs.md, verbose=True, solver=None) + + propagate_state(m.fs.md_to_product) + m.fs.product.initialize() + + propagate_state(m.fs.md_to_disposal) + m.fs.disposal.initialize() + + +def set_system_op_conditions(m): + + feed_flow_rate = m.fs.md.model_input["feed_flow_rate"] + feed_salinity = m.fs.md.model_input["feed_salinity"] + feed_temp = m.fs.md.model_input["feed_temp"] + + m.fs.feed.properties.calculate_state( + var_args={ + ("flow_vol_phase", "Liq"): pyunits.convert( + feed_flow_rate * pyunits.L / pyunits.h, + to_units=pyunits.m**3 / pyunits.s, + ), + ("conc_mass_phase_comp", ("Liq", "TDS")): feed_salinity, + ("temperature", None): feed_temp + 273.15, + ("pressure", None): 101325, + }, + hold_state=True, + ) + + +def calc_costing(m, blk): + m.fs.costing.capital_recovery_factor.fix(0.08764) + m.fs.costing.wacc.unfix() + + m.fs.costing.cost_process() + m.fs.costing.initialize() + + # Touching variables to solve for volumetric flow rate + m.fs.product.properties[0].flow_vol_phase + + prod_flow = pyunits.convert( + m.fs.product.properties[0].flow_vol_phase["Liq"], + to_units=pyunits.m**3 / pyunits.day, + ) + + m.fs.costing.add_annual_water_production(prod_flow) + m.fs.costing.add_LCOW(prod_flow) + + +def solve(m, solver=None, tee=True, raise_on_failure=True): + # ---solving--- + if solver is None: + solver = get_solver() + + print("\n--------- SOLVING ---------\n") + + results = solver.solve(m, tee=tee) + + if check_optimal_termination(results): + print("\n--------- OPTIMAL SOLVE!!! ---------\n") + return results + msg = ( + "The current configuration is infeasible. Please adjust the decision variables." + ) + if raise_on_failure: + print_infeasible_bounds(m) + print_close_to_bounds(m) + + raise RuntimeError(msg) + else: + print(msg) + return results + + +def report_MD(m, blk): + + # blk = m.fs.md + active_blks = blk.unit.mp.get_active_process_blocks() + + print(f"\n\n-------------------- MD Operations Report --------------------\n") + print("\n") + + print( + f'{"System Capacity":<30s}{value(active_blks[0].fs.vagmd.system_capacity):<10,.2f}{pyunits.get_units(active_blks[0].fs.vagmd.system_capacity)}' + ) + + # print( + # f'{"Feed stream salinity":<30s}{value(m.fs.feed.properties[0].conc_mass_phase_comp["Liq","TDS"]):<10.2f}{pyunits.get_units(m.fs.feed.properties[0].conc_mass_phase_comp["Liq","TDS"])}' + # ) + + # print( + # f'{"MD Period 1 Feed salinity":<30s}{value(blk.feed.properties[0].conc_mass_phase_comp["Liq","TDS"]):<10.2f}{pyunits.get_units(blk.feed.properties[0].conc_mass_phase_comp["Liq","TDS"])}' + # ) + + print( + f'{"Number of modules:":<30s}{value(active_blks[-1].fs.vagmd.num_modules):<10.2f}' + ) + + print(f'{"Membrane type":<30s}{active_blks[-1].fs.vagmd.config.module_type}') + + print( + f'{"Accumulated recovery":<30s}{value(active_blks[-1].fs.acc_recovery_ratio):<10.2f}{pyunits.get_units(active_blks[-1].fs.acc_recovery_ratio)}' + ) + + perm_flow = pyunits.convert( + blk.permeate.properties[0].flow_vol_phase["Liq"], + to_units=pyunits.m**3 / pyunits.day, + ) + + print( + f'{"Permeate flow rate":<30s}{value(perm_flow):<10,.2f}{pyunits.get_units(perm_flow)}' + ) + + conc_flow = pyunits.convert( + blk.concentrate.properties[0].flow_vol_phase["Liq"], + to_units=pyunits.m**3 / pyunits.day, + ) + + print( + f'{"Concentrate flow rate":<30s}{value(conc_flow):<10,.2f}{pyunits.get_units(conc_flow)}' + ) + + print( + f'{"Concentrate concentration":<30s}{value(blk.concentrate.properties[0].conc_mass_phase_comp["Liq","TDS"]):<10.2f}{pyunits.get_units(blk.concentrate.properties[0].conc_mass_phase_comp["Liq","TDS"])}' + ) + + # prod_flow = pyunits.convert( + # m.fs.product.properties[0].flow_vol_phase["Liq"], + # to_units=pyunits.m**3 / pyunits.day, + # ) + + # print( + # f'{"Product flow rate":<30s}{value(prod_flow):<10,.2f}{pyunits.get_units(prod_flow)}' + # ) + + # disp_flow = pyunits.convert( + # m.fs.disposal.properties[0].flow_vol_phase["Liq"], + # to_units=pyunits.m**3 / pyunits.day, + # ) + + # print( + # f'{"Disposal flow rate":<30s}{value(disp_flow):<10,.2f}{pyunits.get_units(disp_flow)}' + # ) + + print( + f'{"STEC":<30s}{value(active_blks[-1].fs.specific_energy_consumption_thermal):<10.2f}{pyunits.get_units(active_blks[-1].fs.specific_energy_consumption_thermal)}' + ) + + print( + f'{"SEC":<30s}{value(active_blks[-1].fs.specific_energy_consumption_electric):<10.2f}{pyunits.get_units(active_blks[-1].fs.specific_energy_consumption_electric)}' + ) + + print( + f'{"Overall thermal requirement":<30s}{value(blk.unit.overall_thermal_power_requirement):<10.2f}{pyunits.get_units(blk.unit.overall_thermal_power_requirement)}' + ) + + print( + f'{"Overall elec requirement":<30s}{value(blk.unit.overall_elec_power_requirement):<10.2f}{pyunits.get_units(blk.unit.overall_elec_power_requirement)}' + ) + + +def report_md_costing(m, blk): + + active_blks = blk.md.unit.mp.get_active_process_blocks() + + print(f"\n\n-------------------- MD Costing Report --------------------\n") + print("\n") + + print( + f'{"Capital Cost":<30s}{value(active_blks[-1].fs.vagmd.costing.capital_cost):<20,.2f}{pyunits.get_units(active_blks[-1].fs.vagmd.costing.capital_cost)}' + ) + + print( + f'{"Fixed Operating Cost":<30s}{value(active_blks[-1].fs.vagmd.costing.fixed_operating_cost):<20,.2f}{pyunits.get_units(active_blks[-1].fs.vagmd.costing.fixed_operating_cost)}' + ) + + # print( + # f'{"Variable Operating Cost":<30s}{value(blk.costing.variable_operating_cost):<20,.2f}{pyunits.get_units(blk.costing.variable_operating_cost)}' + # ) + + # print( + # f'{"Aggregated Variable Operating Cost":<30s}{value(blk.costing.aggregate_variable_operating_cost):<20,.2f}{pyunits.get_units(blk.costing.aggregate_variable_operating_cost)}' + # ) + + # print( + # f'{"Total Operating Cost":<30s}{value(blk.costing.total_operating_cost):<20,.2f}{pyunits.get_units(blk.costing.total_operating_cost)}' + # ) + + print( + f'{"Membrane Cost":<30s}{value(active_blks[-1].fs.vagmd.costing.module_cost):<20,.2f}{pyunits.get_units(active_blks[-1].fs.vagmd.costing.module_cost)}' + ) + + # print( + # f'{"Heat flow":<30s}{value(blk.costing.aggregate_flow_heat):<20,.2f}{pyunits.get_units(blk.costing.aggregate_flow_heat)}' + # ) + + # print( + # f'{"Aggregated Heat Cost":<30s}{value(blk.costing.aggregate_flow_costs["heat"]):<20,.2f}{pyunits.get_units(blk.costing.aggregate_flow_costs["heat"])}' + # ) + + # print( + # f'{"Elec Flow":<30s}{value(blk.costing.aggregate_flow_electricity):<20,.2f}{pyunits.get_units(blk.costing.aggregate_flow_electricity)}' + # ) + + # print( + # f'{"Aggregated Elec Cost":<30s}{value(blk.costing.aggregate_flow_costs["electricity"]):<20,.2f}{pyunits.get_units(blk.costing.aggregate_flow_costs["electricity"])}' + # ) + + +if __name__ == "__main__": + m = build_system() + set_system_op_conditions(m) + init_system(m) + + results = solve(m, tee=False) + + m.fs.disposal.properties[0].flow_vol_phase + + m.fs.md.unit.add_costing_module(m.fs.costing) + + calc_costing(m, m.fs) + + print("\nSystem Degrees of Freedom:", degrees_of_freedom(m), "\n") + + assert degrees_of_freedom(m) == 0 + + results = solve(m) + print("\n--------- Cost solve Completed ---------\n") + + print( + "Inlet flow rate in m3/day:", + value( + pyunits.convert( + m.fs.feed.properties[0].flow_vol_phase["Liq"], + pyunits.m**3 / pyunits.day, + ) + ), + ) + report_MD(m, m.fs.md) + report_md_costing(m, m.fs) + + print("\n") + print( + f'Sys Feed Flow Rate: {value(pyunits.convert(m.fs.feed.properties[0].flow_vol_phase["Liq"], pyunits.m ** 3 / pyunits.day)):<10.2f} m3/day' + ) + print( + f'MD Feed Flow Rate: {value(pyunits.convert(m.fs.md.feed.properties[0].flow_vol_phase["Liq"], pyunits.m ** 3 / pyunits.day)):<10.2f} m3/day' + ) + print( + f'Sys Perm Flow Rate: {value(pyunits.convert(m.fs.product.properties[0].flow_vol_phase["Liq"], pyunits.m ** 3 / pyunits.day)):<10.2f} m3/day' + ) + print( + f'MD Perm Flow Rate: {value(pyunits.convert(m.fs.md.permeate.properties[0].flow_vol_phase["Liq"], pyunits.m ** 3 / pyunits.day)):<10.2f} m3/day' + ) + print( + f'Sys Conc Flow Rate: {value(pyunits.convert(m.fs.disposal.properties[0].flow_vol_phase["Liq"], pyunits.m ** 3 / pyunits.day)):<10.2f} m3/day' + ) + print( + f'MD Conc Flow Rate: {value(pyunits.convert(m.fs.md.concentrate.properties[0].flow_vol_phase["Liq"], pyunits.m ** 3 / pyunits.day)):<10.2f} m3/day' + ) + print( + f'Calculated Recovery: {value(m.fs.md.permeate.properties[0].flow_vol_phase["Liq"] / (m.fs.md.permeate.properties[0].flow_vol_phase["Liq"] + m.fs.md.concentrate.properties[0].flow_vol_phase["Liq"])):<10.2f}' + ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/MVC.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/MVC.py new file mode 100644 index 00000000..e978667c --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/MVC.py @@ -0,0 +1,1250 @@ +import os +import pathlib +import math +from pyomo.environ import ( + ConcreteModel, + value, + TransformationFactory, + Param, + Var, + Constraint, + Set, + Expression, + Objective, + RangeSet, + check_optimal_termination, + assert_optimal_termination, + units as pyunits, +) +from pyomo.util.calc_var_value import calculate_variable_from_constraint as cvc +from pyomo.network import Arc, SequentialDecomposition +from pyomo.util.check_units import assert_units_consistent +from idaes.core import FlowsheetBlock, UnitModelCostingBlock +from idaes.core.util.initialization import propagate_state +import idaes.core.util.scaling as iscale +from idaes.core import MaterialFlowBasis +from idaes.core.util.scaling import ( + constraint_scaling_transform, + calculate_scaling_factors, + set_scaling_factor, +) +import idaes.logger as idaeslogger +from idaes.models.unit_models import ( + Product, + Feed, + Mixer, + StateJunction, + Separator, + Heater, +) +from idaes.models.unit_models.separator import SplittingType +from idaes.models.unit_models.heat_exchanger import ( + HeatExchanger, + HeatExchangerFlowPattern, +) +from idaes.models.unit_models.mixer import MomentumMixingType +from idaes.core.util.model_statistics import * + +from watertap.core.solvers import get_solver +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.property_models.multicomp_aq_sol_prop_pack import MCASParameterBlock +from watertap.core.util.initialization import * + +from watertap.unit_models.pressure_changer import Pump +from watertap.unit_models.mvc.components import Evaporator +from watertap.unit_models.mvc.components import Compressor +from watertap.unit_models.mvc.components import Condenser +from watertap.unit_models.mvc.components.lmtd_chen_callback import ( + delta_temperature_chen_callback, +) + +from watertap.property_models.seawater_prop_pack import SeawaterParameterBlock +from watertap.property_models.water_prop_pack import ( + WaterParameterBlock as SteamParameterBlock, +) +from watertap_contrib.reflo.costing import TreatmentCosting +from watertap_contrib.reflo.analysis.case_studies.permian.components.translator_sw_to_water import ( + Translator_SW_to_Water, +) + +__all__ = [ + "build_mvc", + "build_and_run_mvc", + "set_mvc_operating_conditions", + "set_mvc_scaling", + "init_mvc", + "add_mvc_costing", + "scale_mvc_costs", + "display_metrics", + "display_costing", + "display_design", + "run_sequential_decomposition", +] + +solver = get_solver() + +reflo_dir = pathlib.Path(__file__).resolve().parents[4] +case_study_yaml = f"{reflo_dir}/data/technoeconomic/permian_case_study.yaml" +rho = 1000 * pyunits.kg / pyunits.m**3 + +_log = idaeslog.getLogger("permian_MVC") + + +def build_and_run_mvc(recovery=0.5, Qin=4.9, tds=118, **kwargs): + + m = build_mvc_system(recovery=recovery) + mvc = m.fs.MVC + m.fs.optimal_solve_mvc = Var(initialize=0) + m.fs.optimal_solve_mvc.fix() + set_system_operating_conditions(m, Qin=Qin, tds=tds, feed_temp=25) + set_mvc_operating_conditions(m, mvc) + set_mvc_scaling(m, mvc) + init_system(m, mvc) + + m.fs.costing.LCOW_obj = Objective(expr=m.fs.costing.LCOW) + + mvc.evaporator.area.unfix() + mvc.evaporator.outlet_brine.temperature[0].unfix() + mvc.compressor.pressure_ratio.unfix() + # mvc.compressor.pressure_ratio.fix(1.6) + mvc.hx_distillate.area.unfix() + mvc.hx_brine.area.unfix() + mvc.recovery_mass.unfix() + mvc.recovery_vol.fix(m.recovery_vol) + print(f"\n~~~~~FOURTH MVC SOLVE~~~~") + try: + results = solve_mvc(m) + print(f"termination MVC FOURTH {results.solver.termination_condition}") + except: + pass + + display_metrics(m, mvc) + display_design(m, mvc) + # del m.fs.costing.LCOW_obj + # mvc.evaporator.area.fix() + # mvc.hx_distillate.area.fix() + # mvc.hx_brine.area.fix() + mvc.compressor.pressure_ratio.fix(1.6) + print(f"dof MVC FINAL = {degrees_of_freedom(m)}") + # assert degrees_of_freedom(m) == 0 + m.fs.product.properties[0].flow_vol_phase + # m.fs.product.properties[0].conc_mass_phase_comp + m.fs.product.initialize() + m.fs.disposal.properties[0].flow_vol_phase + # m.fs.disposal.properties[0].conc_mass_phase_comp + + print(f"\n~~~~~FINAL MVC SOLVE~~~~") + try: + results = solve_mvc(m) + print(f"termination MVC FINAL {results.solver.termination_condition}") + if not check_optimal_termination(results): + m.fs.optimal_solve_mvc.fix(0) + except: + pass + # m.fs.costing.LCOW.display() + + display_metrics(m, mvc) + display_design(m, mvc) + + return m + + +def solve_mvc(m): + solver = get_solver() + try: + results = solver.solve(m, tee=False) + print(f"termination MVC {results.solver.termination_condition}") + assert_optimal_termination(results) + m.fs.optimal_solve_mvc.fix(1) + except: + results = solver.solve(m, tee=False) + print(f"termination MVC {results.solver.termination_condition}") + assert_optimal_termination(results) + m.fs.optimal_solve_mvc.fix(1) + + return results + + +def build_mvc_system(recovery=0.5, **kwargs): + m = ConcreteModel() + m.recovery_mass = recovery + m.recovery_vol = recovery + m.fs = FlowsheetBlock(dynamic=False) + m.fs.costing = TreatmentCosting() + m.fs.costing.electricity_cost.fix(0.0626) + # m.fs.costing.electricity_cost.fix(0.1) + m.fs.costing.heat_cost.fix(0.01) + + m.fs.properties_feed = SeawaterParameterBlock() + m.fs.properties_vapor = SteamParameterBlock() + + m.fs.feed = Feed(property_package=m.fs.properties_feed) + m.fs.product = Product(property_package=m.fs.properties_feed) + m.fs.disposal = Product(property_package=m.fs.properties_feed) + + m.fs.MVC = mvc = FlowsheetBlock(dynamic=False) + + build_mvc(m, mvc, **kwargs) + + m.fs.feed_to_mvc = Arc(source=m.fs.feed.outlet, destination=mvc.feed.inlet) + + m.fs.mvc_to_product = Arc(source=mvc.product.outlet, destination=m.fs.product.inlet) + + m.fs.mvc_to_disposal = Arc( + source=mvc.disposal.outlet, destination=m.fs.disposal.inlet + ) + + add_mvc_costing(m, mvc) + # print(pyunits.get_units(mvc.evaporator.costing.capital_cost)) + # assert False + m.fs.costing.cost_process() + m.fs.costing.add_annual_water_production(mvc.product.properties[0].flow_vol) + m.fs.costing.add_LCOW(mvc.product.properties[0].flow_vol) + m.fs.costing.add_specific_energy_consumption( + mvc.product.properties[0].flow_vol, name="SEC" + ) + + m.fs.costing.heat_exchanger.material_factor_cost.fix(5) + m.fs.costing.evaporator.material_factor_cost.fix(5) + m.fs.costing.compressor.unit_cost.fix(1 * 7364) + + TransformationFactory("network.expand_arcs").apply_to(m) + + return m + + +def build_mvc(m, blk, external_heating=True): + + print(f'\n{"=======> BUILDING MVC SYSTEM <=======":^60}\n') + + blk.feed = StateJunction(property_package=m.fs.properties_feed) + blk.product = StateJunction(property_package=m.fs.properties_feed) + blk.disposal = StateJunction(property_package=m.fs.properties_feed) + + blk.recovery_mass = Var( + initialize=0.5, bounds=(0, 1), units=pyunits.dimensionless, doc="MVC recovery" + ) + + blk.recovery_vol = Var( + initialize=0.5, + bounds=(0, 1), + units=pyunits.dimensionless, + doc="MVC volumetric recovery", + ) + + # Evaporator + blk.evaporator = Evaporator( + property_package_feed=m.fs.properties_feed, + property_package_vapor=m.fs.properties_vapor, + ) + # Compressor + blk.compressor = Compressor(property_package=m.fs.properties_vapor) + + # Condenser + blk.condenser = Condenser(property_package=m.fs.properties_vapor) + + # Translator SW to Water + blk.tb_sw_to_water = Translator_SW_to_Water( + inlet_property_package=m.fs.properties_vapor, + outlet_property_package=m.fs.properties_feed, + ) + + blk.pump_feed = Pump(property_package=m.fs.properties_feed) + blk.pump_brine = Pump(property_package=m.fs.properties_feed) + blk.pump_distillate = Pump(property_package=m.fs.properties_feed) + + blk.separator = Separator( + property_package=m.fs.properties_feed, + outlet_list=["hx_distillate_cold", "hx_brine_cold"], + split_basis=SplittingType.totalFlow, + ) + + blk.hx_distillate = HeatExchanger( + hot_side_name="hot", + cold_side_name="cold", + hot={"property_package": m.fs.properties_feed, "has_pressure_change": True}, + cold={ + "property_package": m.fs.properties_feed, + "has_pressure_change": True, + }, + delta_temperature_callback=delta_temperature_chen_callback, + flow_pattern=HeatExchangerFlowPattern.countercurrent, + ) + # Set lower bound of approach temperatures + blk.hx_distillate.delta_temperature_in.setlb(0) + blk.hx_distillate.delta_temperature_out.setlb(0) + blk.hx_distillate.area.setlb(5) + + blk.hx_brine = HeatExchanger( + hot_side_name="hot", + cold_side_name="cold", + hot={"property_package": m.fs.properties_feed, "has_pressure_change": True}, + cold={ + "property_package": m.fs.properties_feed, + "has_pressure_change": True, + }, + delta_temperature_callback=delta_temperature_chen_callback, + flow_pattern=HeatExchangerFlowPattern.countercurrent, + ) + # Set lower bound of approach temperatures + blk.hx_brine.delta_temperature_in.setlb(0) + blk.hx_brine.delta_temperature_out.setlb(0) + blk.hx_brine.area.setlb(5) + + blk.mixer_feed = Mixer( + property_package=m.fs.properties_feed, + momentum_mixing_type=MomentumMixingType.equality, + inlet_list=["hx_distillate_cold", "hx_brine_cold"], + ) + + blk.feed_to_pump = Arc(source=blk.feed.outlet, destination=blk.pump_feed.inlet) + blk.pump_to_separator = Arc( + source=blk.pump_feed.outlet, destination=blk.separator.inlet + ) + blk.sep_dist_cold_to_hx_dist_cold = Arc( + source=blk.separator.hx_distillate_cold, + destination=blk.hx_distillate.cold_inlet, + ) + blk.sep_brine_cold_to_hx_brine_cold = Arc( + source=blk.separator.hx_brine_cold, destination=blk.hx_brine.cold_inlet + ) + blk.hx_dist_cold_to_mixer = Arc( + source=blk.hx_distillate.cold_outlet, + destination=blk.mixer_feed.hx_distillate_cold, + ) + blk.hx_brine_cold_to_mixer = Arc( + source=blk.hx_brine.cold_outlet, destination=blk.mixer_feed.hx_brine_cold + ) + blk.mixer_feed_to_evaporator = Arc( + source=blk.mixer_feed.outlet, destination=blk.evaporator.inlet_feed + ) + blk.evaporator_to_compressor = Arc( + source=blk.evaporator.outlet_vapor, destination=blk.compressor.inlet + ) + blk.compressor_to_condenser = Arc( + source=blk.compressor.outlet, destination=blk.condenser.inlet + ) + blk.evaporator_to_brine_pump = Arc( + source=blk.evaporator.outlet_brine, destination=blk.pump_brine.inlet + ) + + blk.brine_pump_to_hx_brine_hot = Arc( + source=blk.pump_brine.outlet, destination=blk.hx_brine.hot_inlet + ) + blk.hx_brine_hot_to_disposal = Arc( + source=blk.hx_brine.hot_outlet, destination=blk.disposal.inlet + ) + blk.condenser_to_translator = Arc( + source=blk.condenser.outlet, destination=blk.tb_sw_to_water.inlet + ) + blk.translated_to_dist_pump = Arc( + source=blk.tb_sw_to_water.outlet, destination=blk.pump_distillate.inlet + ) + + blk.dist_pump_to_hx_dist_hot = Arc( + source=blk.pump_distillate.outlet, destination=blk.hx_distillate.hot_inlet + ) + blk.hx_dist_hot_to_product = Arc( + source=blk.hx_distillate.hot_outlet, destination=blk.product.inlet + ) + + blk.eq_recovery_mass = Constraint( + expr=blk.evaporator.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"] + == blk.recovery_mass + * ( + blk.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"] + + blk.feed.properties[0].flow_mass_phase_comp["Liq", "TDS"] + ) + ) + + blk.eq_recovery_vol = Constraint( + expr=blk.product.properties[0].flow_vol_phase["Liq"] + == blk.recovery_vol * (blk.feed.properties[0].flow_vol_phase["Liq"]) + ) + + blk.eq_separator_split_frac = Constraint( + expr=blk.separator.split_fraction[0, "hx_distillate_cold"] == blk.recovery_mass + ) + + if external_heating: + add_external_heating(m, blk) + + TransformationFactory("network.expand_arcs").apply_to(m) + + blk.evaporator.connect_to_condenser(blk.condenser) + _log.info("MVC flowsheet built") + + +def set_mvc_operating_conditions( + m, + blk, + recovery=0.5, + inlet_brine_temp_guess=50, # degC + outlet_brine_temp=70, # degC + steam_temp_ub=75, + **kwargs, +): + """ + Generic initial point for MVC system. + """ + + blk.feed.properties[0].mass_frac_phase_comp["Liq", "TDS"].fix(0.1) + blk.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"].fix(40) + # Feed pump + blk.pump_feed.efficiency_pump[0].fix(0.8) + blk.pump_feed.control_volume.deltaP[0].fix(7e3) + + # Separator + blk.separator.split_fraction[0, "hx_distillate_cold"] = 0.5 + + # Distillate HX + blk.hx_distillate.overall_heat_transfer_coefficient[0].fix(2e3) + blk.hx_distillate.area.fix(125) + blk.hx_distillate.cold.deltaP[0].fix(7e3) + blk.hx_distillate.hot.deltaP[0].fix(7e3) + + # Brine HX + blk.hx_brine.overall_heat_transfer_coefficient[0].fix(2e3) + blk.hx_brine.area.fix(115) + blk.hx_brine.cold.deltaP[0].fix(7e3) + blk.hx_brine.hot.deltaP[0].fix(7e3) + + # Evaporator + blk.evaporator.properties_vapor[0].temperature.setub(steam_temp_ub + 273.15) + blk.evaporator.inlet_feed.temperature[0] = ( + inlet_brine_temp_guess + 273.15 + ) # provide guess + blk.evaporator.outlet_brine.temperature[0].fix(outlet_brine_temp + 273.15) + blk.evaporator.U.fix(3e3) # W/K-m^2 + blk.evaporator.area.setub(1e4) # m^2 + # blk.evaporator.area.set_value(4275) # m^2 + + # Compressor + blk.compressor.control_volume.properties_out[0].temperature.setub(450) + blk.compressor.pressure_ratio.fix(1.6) + blk.compressor.efficiency.fix(0.8) + + # Brine pump + blk.pump_brine.efficiency_pump[0].fix(0.8) + blk.pump_brine.control_volume.deltaP[0].fix(4e4) + + # Distillate pump + blk.pump_distillate.efficiency_pump[0].fix(0.8) + blk.pump_distillate.control_volume.deltaP[0].fix(4e4) + + # Fix 0 TDS + blk.tb_sw_to_water.properties_out[0].flow_mass_phase_comp["Liq", "TDS"].fix(1e-5) + + print("DOF after setting operating conditions: ", degrees_of_freedom(blk)) + + +def set_system_operating_conditions(m, Qin=1, tds=130, feed_temp=25): + + global flow_in + + Qin = Qin * pyunits.Mgallons / pyunits.day + tds = tds * pyunits.g / pyunits.liter + flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + + m.fs.feed.properties.calculate_state( + var_args={ + ("flow_vol_phase", ("Liq")): flow_in, + ("conc_mass_phase_comp", ("Liq", "TDS")): tds, + ("pressure", None): 101325, + ("temperature", None): 273.15 + feed_temp, + }, + hold_state=True, + ) + + +def set_mvc_scaling( + m, + blk, + properties_feed=None, + properties_vapor=None, + calc_blk_scaling_factors=True, +): + + if properties_feed is None: + properties_feed = m.fs.properties_feed + + if properties_vapor is None: + properties_vapor = m.fs.properties_vapor + + properties_feed.set_default_scaling("flow_mass_phase_comp", 1, index=("Liq", "H2O")) + properties_feed.set_default_scaling( + "flow_mass_phase_comp", 1e2, index=("Liq", "TDS") + ) + properties_vapor.set_default_scaling( + "flow_mass_phase_comp", 1, index=("Vap", "H2O") + ) + properties_vapor.set_default_scaling( + "flow_mass_phase_comp", 1, index=("Liq", "H2O") + ) + + set_scaling_factor(blk.external_heating, 1e-6) + + # MVC FEED + # set_scaling_factor( + # blk.feed.properties[0.0].conc_mass_phase_comp["Liq", "TDS"], 1e-2 + # ) + # set_scaling_factor(blk.hx_distillate.hot_side.properties_in[0].mass_frac_phase_comp["Liq", "TDS"], 1e2) + + # MVC PRODUCT + + # MVC DISPOSAL + + # PUMPS + set_scaling_factor(blk.pump_feed.control_volume.work, 1e-3) + set_scaling_factor(blk.pump_brine.control_volume.work, 1e-3) + set_scaling_factor(blk.pump_distillate.control_volume.work, 1e-3) + + # DISTILLATE HX + set_scaling_factor(blk.hx_distillate.hot.heat, 1e-3) + set_scaling_factor(blk.hx_distillate.cold.heat, 1e-3) + set_scaling_factor(blk.hx_distillate.overall_heat_transfer_coefficient, 1e-3) + + set_scaling_factor(blk.hx_distillate.area, 1e-1) + constraint_scaling_transform(blk.hx_distillate.cold_side.pressure_balance[0], 1e-5) + constraint_scaling_transform(blk.hx_distillate.hot_side.pressure_balance[0], 1e-5) + + # BRINE HX + set_scaling_factor(blk.hx_brine.hot.heat, 1e-3) + set_scaling_factor(blk.hx_brine.cold.heat, 1e-3) + set_scaling_factor(blk.hx_brine.overall_heat_transfer_coefficient, 1e-3) + set_scaling_factor(blk.hx_brine.area, 1e-1) + constraint_scaling_transform(blk.hx_brine.cold_side.pressure_balance[0], 1e-5) + constraint_scaling_transform(blk.hx_brine.hot_side.pressure_balance[0], 1e-5) + + # EVAPORATOR + # set_scaling_factor(blk.evaporator.properties_brine[0].pressure, 1e-4) + set_scaling_factor(blk.evaporator.area, 1e-3) + set_scaling_factor(blk.evaporator.U, 1e-3) + set_scaling_factor(blk.evaporator.delta_temperature_in, 1e-1) + set_scaling_factor(blk.evaporator.delta_temperature_out, 1e-1) + set_scaling_factor(blk.evaporator.lmtd, 1e-1) + # set_scaling_factor(blk.evaporator.heat_transfer, 1e-7) + + # COMPRESSOR + set_scaling_factor(blk.compressor.control_volume.work, 1e-6) + # set_scaling_factor( + # blk.compressor.control_volume.properties_in[0].enth_flow_phase["Liq"], 1 + # ) + + # CONDENSER + set_scaling_factor(blk.condenser.control_volume.heat, 1e-5) + + # if hasattr(blk.evaporator, "costing"): + # scale_mvc_costs(m, blk) + + if calc_blk_scaling_factors: + calculate_scaling_factors(blk) + + else: + calculate_scaling_factors(m) + + +def init_system(m, blk, **kwargs): + + m.fs.feed.initialize() + propagate_state(m.fs.feed_to_mvc) + + init_mvc(m, blk, **kwargs) + + m.fs.product.initialize() + propagate_state(m.fs.mvc_to_product) + + m.fs.disposal.initialize() + propagate_state(m.fs.mvc_to_disposal) + + +def init_mvc( + m, + blk, + feed_props=None, + delta_temperature_in=10, + delta_temperature_out=None, + solver=None, +): + """ + Initialization routine for generic MVC setup. + To be used with external heating. + """ + + if solver is None: + solver = get_solver() + solver.options["halt_on_ampl_error"] = "yes" + # solver.options["tee"] = True + optarg = solver.options + + if feed_props is None: + feed_props = m.fs.feed.properties[0] + + blk.recovery_mass.fix(0.5) + + blk.feed.properties[0].mass_frac_phase_comp["Liq", "TDS"] + + blk.feed.properties[0].temperature.fix(value(feed_props.temperature)) + blk.feed.properties[0].pressure.fix(value(feed_props.pressure)) + + solver.solve(blk.feed) + + _log.info(f"{blk.name} feed initialization complete.") + + # Propagate vapor flow rate based on given recovery + blk.evaporator.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"] = ( + blk.recovery_mass + * ( + blk.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"] + + blk.feed.properties[0].flow_mass_phase_comp["Liq", "TDS"] + ) + ) + blk.evaporator.properties_vapor[0].flow_mass_phase_comp["Liq", "H2O"] = 0 + + # Propagate brine salinity and flow rate + blk.evaporator.properties_brine[0].mass_frac_phase_comp["Liq", "TDS"] = ( + blk.feed.properties[0].mass_frac_phase_comp["Liq", "TDS"] + / (1 - blk.recovery_mass) + ) + blk.evaporator.properties_brine[0].mass_frac_phase_comp["Liq", "H2O"] = ( + 1 - blk.evaporator.properties_brine[0].mass_frac_phase_comp["Liq", "TDS"].value + ) + blk.evaporator.properties_brine[0].flow_mass_phase_comp["Liq", "TDS"] = ( + blk.feed.properties[0].flow_mass_phase_comp["Liq", "TDS"] + ) + blk.evaporator.properties_brine[0].flow_mass_phase_comp["Liq", "H2O"] = ( + blk.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"] + - blk.evaporator.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"] + ) + + # Initialize feed pump + propagate_state(blk.feed_to_pump) + blk.pump_feed.initialize(optarg=optarg, solver="ipopt-watertap") + _log.info(f"{blk.name} feed pump initialization complete.") + + # Initialize separator + propagate_state(blk.pump_to_separator) + # Touch property for initialization + blk.separator.mixed_state[0].mass_frac_phase_comp["Liq", "TDS"] + blk.separator.split_fraction[0, "hx_distillate_cold"].fix(blk.recovery_mass.value) + blk.separator.mixed_state.initialize(optarg=optarg, solver="ipopt-watertap") + + # Touch properties for initialization + blk.separator.hx_brine_cold_state[0].mass_frac_phase_comp["Liq", "TDS"] + blk.separator.hx_distillate_cold_state[0].mass_frac_phase_comp["Liq", "TDS"] + blk.separator.initialize(optarg=optarg, solver="ipopt-watertap") + blk.separator.split_fraction[0, "hx_distillate_cold"].unfix() + _log.info(f"{blk.name} separator initialization complete.") + + # Initialize distillate heat exchanger + propagate_state(blk.sep_dist_cold_to_hx_dist_cold) + blk.hx_distillate.cold_outlet.temperature[0] = ( + blk.evaporator.inlet_feed.temperature[0].value + ) + blk.hx_distillate.cold_outlet.pressure[0] = blk.evaporator.inlet_feed.pressure[ + 0 + ].value + blk.hx_distillate.hot_inlet.flow_mass_phase_comp[0, "Liq", "H2O"] = ( + blk.evaporator.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"].value + ) + blk.hx_distillate.hot_inlet.flow_mass_phase_comp[0, "Liq", "TDS"] = 1e-4 + blk.hx_distillate.hot_inlet.temperature[0] = ( + blk.evaporator.outlet_brine.temperature[0].value + ) + blk.hx_distillate.hot_inlet.pressure[0] = 101325 + blk.hx_distillate.initialize(solver="ipopt-watertap") + _log.info(f"{blk.name} Distillate HX initialization complete.") + + # Initialize brine heat exchanger + propagate_state(blk.sep_brine_cold_to_hx_brine_cold) + blk.hx_brine.cold_outlet.temperature[0] = blk.evaporator.inlet_feed.temperature[ + 0 + ].value + blk.hx_brine.cold_outlet.pressure[0] = blk.evaporator.inlet_feed.pressure[0].value + blk.hx_brine.hot_inlet.flow_mass_phase_comp[0, "Liq", "H2O"] = ( + blk.evaporator.properties_brine[0].flow_mass_phase_comp["Liq", "H2O"] + ) + blk.hx_brine.hot_inlet.flow_mass_phase_comp[0, "Liq", "TDS"] = ( + blk.evaporator.properties_brine[0].flow_mass_phase_comp["Liq", "TDS"] + ) + blk.hx_brine.hot_inlet.temperature[0] = blk.evaporator.outlet_brine.temperature[ + 0 + ].value + blk.hx_brine.hot_inlet.pressure[0] = 101325 + blk.hx_brine.initialize(solver="ipopt-watertap") + _log.info(f"{blk.name} Brine HX initialization complete.") + + # Initialize mixer + propagate_state(blk.hx_dist_cold_to_mixer) + propagate_state(blk.hx_brine_cold_to_mixer) + blk.mixer_feed.initialize(solver="ipopt-watertap") + blk.mixer_feed.pressure_equality_constraints[0, 2].deactivate() + _log.info(f"{blk.name} Mixer initialization complete.") + # print(f"\ndof @ 1 = {degrees_of_freedom(blk)}\n") + + # Initialize evaporator + propagate_state(blk.mixer_feed_to_evaporator) + blk.external_heating.fix() + blk.evaporator.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"].fix() + # fixes and unfixes those values + blk.evaporator.initialize( + delta_temperature_in=delta_temperature_in, + delta_temperature_out=delta_temperature_out, + solver="ipopt-watertap", + ) + blk.external_heating.unfix() + blk.evaporator.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"].unfix() + + # Initialize compressor + propagate_state(blk.evaporator_to_compressor) + blk.compressor.initialize(solver="ipopt-watertap") + _log.info(f"{blk.name} Compressor initialization complete.") + + # Initialize condenser + try: + propagate_state(blk.compressor_to_condenser) + blk.condenser.initialize( + heat=-blk.evaporator.heat_transfer.value, solver="ipopt-watertap" + ) + _log.info(f"{blk.name} Condenser initialization complete.") + except: + print_infeasible_constraints(blk.condenser) + assert False + + # Initialize brine pump + propagate_state(blk.evaporator_to_brine_pump) + blk.pump_brine.initialize(optarg=optarg, solver="ipopt-watertap") + _log.info(f"{blk.name} Brine Pump initialization complete.") + # propagate_state(blk.brine_pump_to_hx_brine_hot) + + # Initialize distillate pump + propagate_state(blk.condenser_to_translator) # to translator block + propagate_state(blk.translated_to_dist_pump) # from translator block to pump + blk.pump_distillate.control_volume.properties_in[0].temperature = ( + blk.condenser.control_volume.properties_out[0].temperature.value + ) + blk.pump_distillate.control_volume.properties_in[0].pressure = ( + blk.condenser.control_volume.properties_out[0].pressure.value + ) + blk.pump_distillate.initialize(optarg=optarg, solver="ipopt-watertap") + _log.info(f"{blk.name} Distillate Pump initialization complete.") + # propagate_state(blk.dist_pump_to_hx_dist_hot) + + # Propagate brine state + propagate_state(blk.hx_brine_hot_to_disposal) + propagate_state(blk.hx_dist_hot_to_product) + + # print(f"\ndof @ 2 = {degrees_of_freedom(blk)}\n") + + run_sequential_decomposition( + m, + blk, + delta_temperature_in=delta_temperature_in, + delta_temperature_out=delta_temperature_out, + ) + + blk.product.initialize() + _log.info(f"{blk.name} Product initialization complete.") + blk.disposal.initialize() + _log.info(f"{blk.name} Disposal initialization complete.") + + m.fs.costing.initialize() + results = solver.solve(blk, tee=False) + print(f"MVC solve termination {results.solver.termination_condition}") + _log.info(f"MVC solve termination {results.solver.termination_condition}") + assert_optimal_termination(results) + + print(f"blk dof at end of init = {degrees_of_freedom(blk)}") + + blk.pump_brine.control_volume.deltaP[0].unfix() + blk.disposal.properties[0].pressure.fix(101325) + # print(f"\ndof @ 3 blk = {degrees_of_freedom(blk)}\n") + # print(f"\ndof @ 3 model = {degrees_of_freedom(m)}\n") + # _log.info_high(f"terminatinon {results.solver.termination_condition}") + + print(f"\n~~~~~FIRST SOLVE~~~~") + blk.obj = Objective(expr=blk.external_heating) + print(f"blk dof = {degrees_of_freedom(blk)}") + print(f"model dof = {degrees_of_freedom(m)}") + results = solver.solve(blk, tee=False) + assert_optimal_termination(results) + print(f"MVC FIRST solve termination {results.solver.termination_condition}") + _log.info(f"MVC FIRST solve termination {results.solver.termination_condition}") + display_metrics(m, blk) + display_design(m, blk) + + blk.external_heating.fix(0) + del blk.obj + blk.external_heating.fix(0) + blk.evaporator.area.unfix() + blk.evaporator.outlet_brine.temperature[0].unfix() + blk.compressor.pressure_ratio.unfix() + blk.hx_distillate.area.unfix() + blk.hx_brine.area.unfix() + + print(f"\n~~~~~SECOND SOLVE~~~~") + + print(f"blk dof = {degrees_of_freedom(blk)}") + print(f"model dof = {degrees_of_freedom(m)}") + results = solver.solve(blk, tee=False) + assert_optimal_termination(results) + print(f"MVC SECOND solve termination {results.solver.termination_condition}") + _log.info(f"MVC SECOND solve termination {results.solver.termination_condition}") + + display_metrics(m, blk) + display_design(m, blk) + + mvc_feed_state_vars = blk.feed.properties[0].define_port_members() + feed_state_vars = feed_props.define_port_members() + blk.feed.properties[0].mass_frac_phase_comp.unfix() + for k, v in mvc_feed_state_vars.items(): + if v.is_indexed(): + for i, vv in v.items(): + vv.fix(value(feed_state_vars[k][i])) + else: + v.fix(value(feed_state_vars[k])) + try: + print(f"\n~~~~~THIRD SOLVE~~~~") + print(f"blk dof = {degrees_of_freedom(blk)}") + print(f"model dof = {degrees_of_freedom(m)}") + blk.feed.initialize() + m.fs.costing.initialize() + results = solver.solve(blk, tee=False) + # results = solve_mvc(blk) + assert_optimal_termination(results) + print(f"MVC THIRD solve termination {results.solver.termination_condition}") + _log.info(f"MVC THIRD solve termination {results.solver.termination_condition}") + + display_metrics(m, blk) + display_design(m, blk) + except: + print(f"MVC THIRD SOLVE FAILED!!\n") + pass + + # print(f"\n~~~~~FOURTH SOLVE~~~~") + # blk.evaporator.area.unfix() + # blk.evaporator.outlet_brine.temperature[0].unfix() + # blk.compressor.pressure_ratio.unfix() + # blk.hx_distillate.area.unfix() + # blk.hx_brine.area.unfix() + # blk.recovery_mass.fix(m.recovery_mass) + # print(f"blk dof = {degrees_of_freedom(blk)}") + # print(f"model dof = {degrees_of_freedom(m)}") + # results = solver.solve(blk, tee=False) + # print(f"termination {results.solver.termination_condition}") + # assert_optimal_termination(results) + + # display_metrics(m, blk) + # display_design(m, blk) + + mvc_feed_state_vars = blk.feed.properties[0].define_port_members() + feed_state_vars = feed_props.define_port_members() + for k, v in mvc_feed_state_vars.items(): + if v.is_indexed(): + for i, vv in v.items(): + vv.unfix() + else: + v.unfix() + + blk.feed.initialize() + + print(f"Initialization done, blk dof = {degrees_of_freedom(blk)}") + print(f"Initialization done, model dof = {degrees_of_freedom(m)}") + + +def run_sequential_decomposition( + m, + blk, + delta_temperature_in=60, + delta_temperature_out=None, + tear_solver="cbc", + iterlim=5, +): + + def func_initialize(unit): + print(unit.local_name) + print(f"dof = {degrees_of_freedom(unit)}\n") + # if unit.local_name == "feed": + if unit.local_name in ["feed", "product", "disposal"]: + pass + elif unit.local_name == "condenser": + unit.initialize( + heat=-unit.flowsheet().evaporator.heat_transfer.value, + optarg=solver.options, + solver="ipopt-watertap", + ) + elif unit.local_name == "evaporator": + unit.flowsheet().external_heating.fix() + unit.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"].fix() + unit.initialize( + delta_temperature_in=delta_temperature_in, + delta_temperature_out=delta_temperature_out, + solver="ipopt-watertap", + ) + unit.flowsheet().external_heating.unfix() + unit.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"].unfix() + elif unit.local_name == "separator": + unit.split_fraction[0, "hx_distillate_cold"].fix( + unit.flowsheet().recovery_mass.value + ) + unit.initialize(solver="ipopt-watertap") + unit.split_fraction[0, "hx_distillate_cold"].unfix() + elif unit.local_name == "mixer_feed": + unit.initialize(solver="ipopt-watertap") + unit.pressure_equality_constraints[0, 2].deactivate() + # elif unit.local_name == "hx_distillate": + # unit.cold_outlet.temperature[0] = blk.evaporator.inlet_feed.temperature[ + # 0 + # ].value + # unit.cold_outlet.pressure[0] = blk.evaporator.inlet_feed.pressure[0].value + # unit.hot_inlet.flow_mass_phase_comp[0, "Liq", "H2O"] = ( + # blk.evaporator.properties_vapor[0] + # .flow_mass_phase_comp["Vap", "H2O"] + # .value + # ) + # unit.hot_inlet.flow_mass_phase_comp[0, "Liq", "TDS"] = 1e-4 + # unit.hot_inlet.temperature[0] = blk.evaporator.outlet_brine.temperature[ + # 0 + # ].value + # unit.hot_inlet.pressure[0] = 101325 + # unit.initialize(solver="ipopt-watertap") + else: + unit.initialize(solver="ipopt-watertap") + + seq = SequentialDecomposition(tear_solver=tear_solver) + seq.options.log_info = True + seq.options.iterLim = iterlim + seq.run(blk, func_initialize) + + +def add_external_heating(m, blk): + """ + Add additional heat source so infeasible designs can be used + as initial guess prior to optimization + """ + + blk.external_heating = Var( + initialize=0, + units=pyunits.watt, + bounds=(0, None), + doc="External heating for evaporator", + ) + + blk.evaporator.eq_energy_balance.deactivate() + blk.evaporator.eq_energy_balance_with_external_heat = Constraint( + expr=blk.evaporator.heat_transfer + + blk.external_heating + + blk.evaporator.properties_feed[0].enth_flow + == blk.evaporator.properties_brine[0].enth_flow + + blk.evaporator.properties_vapor[0].enth_flow_phase["Vap"] + ) + set_scaling_factor(blk.external_heating, 1e-6) + + +def add_mvc_costing(m, blk, flowsheet_costing_block=None): + + if flowsheet_costing_block is None: + flowsheet_costing_block = m.fs.costing + + flowsheet_costing_block.base_currency = pyunits.USD_2023 + + blk.evaporator.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block + ) + blk.compressor.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block + ) + + blk.pump_feed.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block + ) + blk.pump_distillate.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block + ) + blk.pump_brine.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block + ) + blk.hx_distillate.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block + ) + blk.hx_brine.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block + ) + blk.mixer_feed.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block + ) + + # m.fs.costing.TIC.fix(2) + # m.fs.costing.electricity_cost = 0.1 # 0.15 + flowsheet_costing_block.heat_exchanger.material_factor_cost.fix(5) + flowsheet_costing_block.evaporator.material_factor_cost.fix(5) + flowsheet_costing_block.compressor.unit_cost.fix(1 * 7364) + + +def set_up_optimization(m, blk): + """ + Add objective and unfix design variables + """ + if hasattr(blk, "LCOW_obj"): + blk.del_component(blk.LCOW_obj) + blk.LCOW_obj = Objective(expr=m.fs.costing.LCOW) + blk.external_heating.fix(0) + blk.evaporator.area.unfix() + blk.evaporator.outlet_brine.temperature[0].unfix() + blk.compressor.pressure_ratio.unfix() + blk.hx_distillate.area.unfix() + blk.hx_brine.area.unfix() + + +def design_mvc(m, blk): + """ + After system is initialized, full design routine. + """ + # First minimize external heating required + # blk.external_heating.unfix() + blk.external_heating_obj = Objective(expr=blk.external_heating) + print(f"MVC DOF @ A = {degrees_of_freedom(blk)}") + + results = solver.solve(m) + assert_optimal_termination(results) + print(f"MVC first solve {results.solver.termination_condition}") + + print(f"\n~~~~~FIRST SOLVE~~~~") + display_metrics(m, mvc) + display_design(m, mvc) + + blk.del_component(blk.external_heating_obj) + + # Add LCOW objective; unfix design variables + set_up_optimization(m, blk) + # blk.evaporator.eq_energy_balance.activate() + # blk.evaporator.eq_energy_balance_with_external_heat.deactivate() + + print(f"MVC DOF @ B = {degrees_of_freedom(m)}") + results = solver.solve(m) + assert_optimal_termination(results) + print(f"MVC second solve {results.solver.termination_condition}") + + print(f"\n~~~~~SECOND SOLVE~~~~") + display_metrics(m, mvc) + display_design(m, mvc) + + print(f"MVC DOF @ C = {degrees_of_freedom(m)}") + + # blk.evaporator.eq_energy_balance.activate() + blk.evaporator.area.fix() + blk.evaporator.outlet_brine.temperature[0].fix() + blk.hx_distillate.area.fix() + blk.hx_brine.area.fix() + + print(f"MVC DOF final = {degrees_of_freedom(m)}") + results = solver.solve(m) + assert_optimal_termination(results) + print(f"MVC final solve {results.solver.termination_condition}") + print(f"\n~~~~~FINAL SOLVE~~~~") + display_metrics(m, mvc) + display_design(m, mvc) + + +def display_metrics(m, blk): + print("\nSystem metrics") + print( + "Feed flow rate: %.2f kg/s" + % ( + blk.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"].value + + blk.feed.properties[0].flow_mass_phase_comp["Liq", "TDS"].value + ) + ) + print( + "Feed salinity: %.2f g/kg" + % (blk.feed.properties[0].mass_frac_phase_comp["Liq", "TDS"].value * 1e3) + ) + print( + "Brine salinity: %.2f g/kg" + % ( + blk.evaporator.properties_brine[0].mass_frac_phase_comp["Liq", "TDS"].value + * 1e3 + ) + ) + print( + "Product flow rate: %.2f kg/s" + % blk.evaporator.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"].value + ) + print( + "Recovery: %.2f %%" + % (blk.recovery_mass.value * 100) + ) + print( + "Specific energy consumption: %.2f kWh/m3" + % value(m.fs.costing.SEC) + ) + print( + "Levelized cost of water: %.2f $/m3" % value(m.fs.costing.LCOW) + ) + print( + "External Q: %.2f W" % blk.external_heating.value + ) # should be 0 for optimization + + +def display_design(m, blk): + print("\nState variables") + print( + "Preheated feed temperature: %.2f K" + % blk.evaporator.properties_feed[0].temperature.value + ) + print( + "Evaporator (brine, vapor) temperature: %.2f K" + % blk.evaporator.properties_brine[0].temperature.value + ) + print( + "Evaporator (brine, vapor) pressure: %.5f kPa" + % (blk.evaporator.properties_vapor[0].pressure.value * 1e-3) + ) + print( + "Compressed vapor temperature: %.5f K" + % blk.compressor.control_volume.properties_out[0].temperature.value + ) + print( + "Compressed vapor pressure: %.5f kPa" + % (blk.compressor.control_volume.properties_out[0].pressure.value * 1e-3) + ) + print( + "Condensed vapor temperature: %.5f K" + % blk.condenser.control_volume.properties_out[0].temperature.value + ) + + print("\nDesign variables") + print("Brine heat exchanger area: %.2f m2" % blk.hx_brine.area.value) + print( + "Distillate heat exchanger area: %.2f m2" + % blk.hx_distillate.area.value + ) + print( + "Compressor pressure ratio: %.2f" + % blk.compressor.pressure_ratio.value + ) + print( + "Evaporator area: %.2f m2" % blk.evaporator.area.value + ) + print( + "Evaporator LMTD: %.2f K" % blk.evaporator.lmtd.value + ) + + +def display_costing(m, mvc): + print("\n\n---------MVC COSTING---------") + print(f"\n{'LCOW':<30} {m.fs.costing.LCOW():<20.2f} $/m3") + print(f"{'SEC':<30} {m.fs.costing.SEC():<20.2f} kWh/m3") + print( + f"{'Aggregate Electricity Flow':<30} {m.fs.costing.aggregate_flow_electricity():<20.2f} kW" + ) + print(f"{'Total Capital Cost':<30} ${m.fs.costing.total_capital_cost():<20.2f}") + + print( + f"\n{'Evaporator Capital Cost':<30} ${mvc.evaporator.costing.capital_cost():<20.2f}" + ) + print(f"{'Evaporator Area':<30} {mvc.evaporator.area():<20.2f} m2") + + print( + f"\n{'Compressor Capital Cost':<30} ${mvc.compressor.costing.capital_cost():<20.2f}" + ) + print(f"{'Compressor Efficiency':<30} {mvc.compressor.efficiency():<20.2f} ---") + print(f"{'Compressor Work':<30} {mvc.compressor.control_volume.work[0]():<20.2f} W") + print( + f"{'Compressor Pressure Ratio':<30} {mvc.compressor.pressure_ratio():<20.2f} ---" + ) + print( + f"{'Compressor Steam Flow In':<30} {mvc.compressor.control_volume.properties_in[0].flow_mass_phase_comp['Vap', 'H2O']():<20.2f} kg/s" + ) + + print( + f"\n{'Feed Pump Capital Cost':<30} ${mvc.pump_feed.costing.capital_cost():<20.2f}" + ) + print(f"{'Feed Pump Work':<30} {mvc.pump_feed.work_mechanical[0]():<20.2f} W") + + print( + f"\n{'Distillate Pump Capital Cost':<30} ${mvc.pump_distillate.costing.capital_cost():<20.2f}" + ) + print( + f"{'Distillate Pump Work':<30} {pyunits.convert(mvc.pump_distillate.work_mechanical[0], to_units=pyunits.watt)():<20.2f} W" + ) + + print( + f"\n{'Brine Pump Capital Cost':<30} ${mvc.pump_brine.costing.capital_cost():<20.2f}" + ) + print(f"{'Brine Pump Work':<30} {mvc.pump_brine.work_mechanical[0]():<20.2f} W") + + print( + f"\n{'HX Distillate Capital Cost':<30} ${mvc.hx_distillate.costing.capital_cost():<20.2f}" + ) + print(f"{'HX Distillate Area':<30} {mvc.hx_distillate.area():<20.2f} m2") + + print( + f"\n{'HX Brine Capital Cost':<30} ${mvc.hx_brine.costing.capital_cost():<20.2f}" + ) + print(f"{'HX Brine Area':<30} {mvc.hx_brine.area():<20.2f} m2") + + print( + f"\n{'Mixer Capital Cost':<30} ${mvc.mixer_feed.costing.capital_cost():<20.2f}" + ) + print( + f"{'Mixer Flow Vol':<30} {mvc.mixer_feed.mixed_state[0].flow_vol():<20.5f} m3/s" + ) + + +def calculate_cost_sf(cost): + print(cost.name, cost.value) + if cost.value in [0, None]: + sf = 1e-2 + else: + sf = 10 ** -(math.log10(abs(cost.value))) + iscale.set_scaling_factor(cost, sf) + + +def scale_mvc_costs(m, blk): + calculate_cost_sf(blk.hx_distillate.costing.capital_cost) + calculate_cost_sf(blk.hx_brine.costing.capital_cost) + calculate_cost_sf(blk.mixer_feed.costing.capital_cost) + calculate_cost_sf(blk.evaporator.costing.capital_cost) + calculate_cost_sf(blk.compressor.costing.capital_cost) + # calculate_cost_sf(m.fs.costing.aggregate_capital_cost) + # calculate_cost_sf(m.fs.costing.aggregate_flow_costs["electricity"]) + # calculate_cost_sf(m.fs.costing.total_capital_cost) + # calculate_cost_sf(m.fs.costing.total_operating_cost) + + calculate_scaling_factors(m) + + print("Scaled costs") + + +if __name__ == "__main__": + m = build_and_run_mvc(recovery=0.5, Qin=5.01, tds=130) + # m.fs.MVC.recovery_vol.display() + # m.fs.costing.total_capital_cost.display() + # m.fs.costing.total_operating_cost.display() + # m.fs.product.properties[0].flow_vol_phase.display() + # m.fs.MVC.product.properties[0].flow_vol_phase.display() + # m.fs.costing.LCOW.display() + + +## USED TO RE-INIT MVC @ THIRD SOLVE +# blk.condenser.initialize(heat=-blk.evaporator.heat_transfer.value) + +# blk.external_heating.fix() +# blk.evaporator.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"].fix() +# blk.evaporator.initialize( +# delta_temperature_in=delta_temperature_in, +# delta_temperature_out=delta_temperature_out, +# solver="ipopt-watertap", +# ) +# blk.external_heating.unfix() +# blk.evaporator.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"].unfix() + +# blk.separator.split_fraction[0, "hx_distillate_cold"].fix( +# blk.recovery_mass.value +# ) +# blk.separator.initialize(solver="ipopt-watertap") +# blk.separator.split_fraction[0, "hx_distillate_cold"].unfix() + +# blk.mixer_feed.initialize(solver="ipopt-watertap") +# blk.mixer_feed.pressure_equality_constraints[0, 2].deactivate() diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/__init__.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/__init__.py new file mode 100644 index 00000000..6b9c7939 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/__init__.py @@ -0,0 +1,9 @@ +from .cartridge_filtration import * +from .EC import * +from .oxidation import * +from .MVC import * +from .deep_well_injection import * + +from .translator_zo_to_sw import Translator_ZO_to_SW +from .translator_sw_to_zo import Translator_SW_to_ZO +from .translator_sw_to_water import Translator_SW_to_Water diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/cartridge_filtration.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/cartridge_filtration.py new file mode 100644 index 00000000..3aa580d4 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/cartridge_filtration.py @@ -0,0 +1,276 @@ +import pathlib +from pyomo.environ import ( + ConcreteModel, + value, + TransformationFactory, + Param, + Var, + Constraint, + Set, + Expression, + Objective, + NonNegativeReals, + Block, + RangeSet, + check_optimal_termination, + assert_optimal_termination, + units as pyunits, +) +from pyomo.network import Arc, SequentialDecomposition +from pyomo.util.check_units import assert_units_consistent +from pyomo.util.calc_var_value import calculate_variable_from_constraint as cvc + +from idaes.core import FlowsheetBlock, UnitModelCostingBlock +from idaes.core.util.initialization import propagate_state as propagate_state +import idaes.core.util.scaling as iscale +from idaes.core import MaterialFlowBasis +from idaes.core.util.scaling import ( + constraint_scaling_transform, + calculate_scaling_factors, + set_scaling_factor, +) +from idaes.models.unit_models import Product, Feed, StateJunction, Separator +from idaes.core.util.model_statistics import * + +from watertap.core.solvers import get_solver +from watertap.core import Database +from watertap_contrib.reflo.core.wt_reflo_database import REFLODatabase +from watertap.unit_models.zero_order import CartridgeFiltrationZO +from watertap.core.zero_order_properties import WaterParameterBlock as ZO +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.core.util.initialization import * + +from watertap_contrib.reflo.costing import ( + TreatmentCosting, + EnergyCosting, + REFLOCosting, +) + +reflo_dir = pathlib.Path(__file__).resolve().parents[4] + +case_study_yaml = f"{reflo_dir}/data/technoeconomic/permian_case_study.yaml" + +rho = 1000 * pyunits.kg / pyunits.m**3 + + +__all__ = [ + "build_cartridge_filtration", + "set_cart_filt_scaling", + "set_cart_filt_op_conditions", + "add_cartridge_filtration_costing", + "init_cart_filt", +] + + +def build_system(): + m = ConcreteModel() + m.db = REFLODatabase() + m.fs = FlowsheetBlock(dynamic=False) + m.fs.costing = TreatmentCosting(case_study_definition=case_study_yaml) + m.fs.properties = ZO(solute_list=["tds"]) + m.fs.feed = Feed(property_package=m.fs.properties) + m.fs.product = Product(property_package=m.fs.properties) + m.fs.disposal = Product(property_package=m.fs.properties) + + m.fs.cart_filt = FlowsheetBlock(dynamic=False) + build_cartridge_filtration(m, m.fs.cart_filt, prop_package=m.fs.properties) + + m.fs.feed_to_cart = Arc( + source=m.fs.feed.outlet, + destination=m.fs.cart_filt.feed.inlet, + ) + + m.fs.cart_to_product = Arc( + source=m.fs.cart_filt.product.outlet, + destination=m.fs.product.inlet, + ) + + m.fs.cart_to_disposal = Arc( + source=m.fs.cart_filt.disposal.outlet, + destination=m.fs.disposal.inlet, + ) + + TransformationFactory("network.expand_arcs").apply_to(m) + + return m + + +def build_cartridge_filtration(m, blk, prop_package=None) -> None: + + print(f'\n{"=======> BUILDING CARTRIDGE FILTRATION SYSTEM <=======":^60}\n') + + if prop_package is None: + prop_package = m.fs.properties + + blk.feed = StateJunction(property_package=prop_package) + blk.product = StateJunction(property_package=prop_package) + blk.disposal = StateJunction(property_package=prop_package) + + blk.unit = CartridgeFiltrationZO( + property_package=prop_package, + database=m.db, + ) + + blk.feed_to_unit = Arc( + source=blk.feed.outlet, + destination=blk.unit.inlet, + ) + + blk.unit_to_product = Arc( + source=blk.unit.treated, + destination=blk.product.inlet, + ) + + blk.unit_to_disposal = Arc( + source=blk.unit.byproduct, + destination=blk.disposal.inlet, + ) + + TransformationFactory("network.expand_arcs").apply_to(m) + + +def set_system_operating_conditions(m, Qin=5): + print( + "\n\n-------------------- SETTING SYSTEM OPERATING CONDITIONS --------------------\n\n" + ) + Qin = Qin * pyunits.Mgal / pyunits.day + flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + flow_mass_water = pyunits.convert(Qin * rho, to_units=pyunits.kg / pyunits.s) + inlet_dict = {"tds": 130 * pyunits.kg / pyunits.m**3} + m.fs.feed.properties[0].flow_mass_comp["H2O"].fix(flow_mass_water) + + for solute, solute_conc in inlet_dict.items(): + flow_mass_solute = pyunits.convert( + flow_in * solute_conc, to_units=pyunits.kg / pyunits.s + ) + sf = 1 / value(flow_mass_solute) + m.fs.feed.properties[0].flow_mass_comp[solute].fix(flow_mass_solute) + m.fs.cart_filt.unit.properties_in[0].flow_mass_comp[solute].set_value( + flow_mass_solute + ) + m.fs.properties.set_default_scaling( + "flow_mass_comp", + sf, + index=(solute), + ) + m.fs.properties.set_default_scaling( + "conc_mass_comp", + 1 / solute_conc(), + index=(solute), + ) + + m.fs.properties.set_default_scaling( + "flow_mass_comp", + 1 / value(flow_mass_water), + index=("H2O"), + ) + calculate_scaling_factors(m) + + +def set_cart_filt_scaling(m, blk, calc_blk_scaling_factors=False): + set_scaling_factor(blk.unit.energy_electric_flow_vol_inlet, 1e4) + + # Calculate scaling factors only for CF block if in full case study flowsheet + # so we don't prematurely set scaling factors + if calc_blk_scaling_factors: + calculate_scaling_factors(blk) + + # otherwise calculate all scaling factors + else: + calculate_scaling_factors(m) + + +def set_cart_filt_op_conditions(m, blk, **kwargs): + + # data = m.db.get_unit_operation_parameters("chemical_addition") + blk.unit.load_parameters_from_database() + + print(f"Cartridge Filtration") + print(f"\tblock DOF = {degrees_of_freedom(blk)}\n") + print(f"\tunit DOF = {degrees_of_freedom(blk.unit)}\n") + + +def add_cartridge_filtration_costing(m, blk, flowsheet_costing_block=None): + if flowsheet_costing_block is None: + flowsheet_costing_block = m.fs.costing + blk.unit.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block + ) + + +def init_system(blk, solver=None, flow_out=None): + if solver is None: + solver = get_solver() + if flow_out is None: + flow_out = blk.fs.feed.properties[0].flow_vol + + print("\n\n-------------------- INITIALIZING SYSTEM --------------------\n\n") + print(f"System Degrees of Freedom: {degrees_of_freedom(m)}") + print(f"Cartridge Filt Degrees of Freedom: {degrees_of_freedom(m.fs.cart_filt)}") + + m.fs.feed.initialize() + propagate_state(m.fs.feed_to_cart) + # m.fs.cart_filt.unit.initialize() + init_cart_filt(m, m.fs.cart_filt) + propagate_state(m.fs.cart_to_product) + m.fs.product.initialize() + + m.fs.costing.cost_process() + m.fs.costing.initialize() + m.fs.costing.add_LCOW(flow_out) + + +def init_cart_filt(m, blk): + blk.feed.initialize() + propagate_state(blk.feed_to_unit) + blk.unit.initialize() + propagate_state(blk.unit_to_product) + blk.product.initialize() + propagate_state(blk.unit_to_disposal) + blk.disposal.initialize() + print("Cartridge Filtration") + print(f"\tblock DOF after init = {degrees_of_freedom(blk)}\n") + print(f"\tunit DOF after init = {degrees_of_freedom(blk.unit)}\n") + + +def print_cart_filt_costing_breakdown(blk): + + print( + f'{"Chem Addition Capital Cost":<35s}{f"${blk.unit.costing.capital_cost():<25,.0f}"}' + ) + # print( + # f'{"Chem Addition Operating Cost":<35s}{f"${blk.unit.costing.fixed_operating_cost():<25,.0f}"}' + # ) + + +def solve(m, solver=None, tee=True, raise_on_failure=True): + # ---solving--- + if solver is None: + solver = get_solver() + + print("\n--------- SOLVING ---------\n") + + results = solver.solve(m, tee=tee) + + if check_optimal_termination(results): + print("\n--------- OPTIMAL SOLVE!!! ---------\n") + return results + msg = ( + "The current configuration is infeasible. Please adjust the decision variables." + ) + if raise_on_failure: + raise RuntimeError(msg) + else: + return results + + +if __name__ == "__main__": + + m = build_system() + set_system_operating_conditions(m) + set_cart_filt_op_conditions(m, m.fs.cart_filt) + + add_cartridge_filtration_costing(m, m.fs.cart_filt) + init_system(m) + solve(m) + print(f"LCOW = {m.fs.costing.LCOW()}") diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/deep_well_injection.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/deep_well_injection.py new file mode 100644 index 00000000..6fadb004 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/deep_well_injection.py @@ -0,0 +1,235 @@ +import os +import math +import numpy as np +from pyomo.environ import ( + ConcreteModel, + value, + Param, + Var, + Constraint, + Set, + Expression, + TransformationFactory, + Objective, + NonNegativeReals, + Block, + RangeSet, + assert_optimal_termination, + check_optimal_termination, + units as pyunits, +) +from pyomo.network import Arc, SequentialDecomposition +from pyomo.util.check_units import assert_units_consistent +from idaes.core import FlowsheetBlock, UnitModelCostingBlock, MaterialFlowBasis +from idaes.core.solvers import get_solver +from idaes.core.util.initialization import propagate_state +import idaes.core.util.scaling as iscale +from idaes.core.util.scaling import ( + constraint_scaling_transform, + calculate_scaling_factors, + set_scaling_factor, +) +import idaes.logger as idaeslogger +from idaes.core.util.exceptions import InitializationError +from idaes.models.unit_models import Product, Feed, StateJunction, Separator +from idaes.core.util.model_statistics import * + +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.property_models.seawater_prop_pack import SeawaterParameterBlock + +from watertap_contrib.reflo.costing import ( + TreatmentCosting, + EnergyCosting, + REFLOCosting, +) + +from watertap_contrib.reflo.unit_models.deep_well_injection import DeepWellInjection +from watertap_contrib.reflo.costing.units.deep_well_injection import ( + blm_costing_params_dict, +) + + +# reflo_dir = pathlib.Path(__file__).resolve().parents[4] +# case_study_yaml = f"{reflo_dir}/data/technoeconomic/permian_case_study.yaml" +rho = 1000 * pyunits.kg / pyunits.m**3 + + +__all__ = [ + "build_dwi", + "build_and_run_dwi", + "init_dwi", + "add_dwi_costing", + "report_DWI", + "print_DWI_costing_breakdown", +] + + +def build_and_run_dwi(Qin=5, tds=130, **kwargs): + + m = build_system() + m.fs.optimal_solve_dwi = Var(initialize=1) + m.fs.optimal_solve_dwi.fix() + m.fs.feed.properties[0].conc_mass_phase_comp + add_dwi_costing(m, m.fs.DWI) + m.fs.costing.cost_process() + m.fs.costing.add_LCOW(m.fs.feed.properties[0].flow_vol_phase["Liq"]) + set_system_operating_conditions(m, Qin=Qin, tds=tds, **kwargs) + print(f"dof = {degrees_of_freedom(m)}") + init_system(m, m.fs.DWI) + + solver = get_solver() + results = solver.solve(m) + # assert_optimal_termination(results) + if not check_optimal_termination(results): + m.fs.optimal_solve_dwi.fix(0) + # m.fs.feed.properties[0].conc_mass_phase_comp.display() + # print(f"LCOW = {m.fs.costing.LCOW()}") + + return m + + +def build_system(): + m = ConcreteModel() + m.fs = FlowsheetBlock(dynamic=False) + m.fs.costing = TreatmentCosting() + m.fs.properties = SeawaterParameterBlock() + m.fs.feed = Feed(property_package=m.fs.properties) + + m.fs.DWI = FlowsheetBlock(dynamic=False) + build_dwi(m, m.fs.DWI, m.fs.properties) + + m.fs.feed_to_dwi = Arc(source=m.fs.feed.outlet, destination=m.fs.DWI.feed.inlet) + + TransformationFactory("network.expand_arcs").apply_to(m) + + return m + + +def build_dwi(m, blk, prop_package, injection_well_depth=5000): + + print(f'\n{"=======> BUILDING DEEP WELL INJECTION SYSTEM <=======":^60}\n') + + blk.feed = StateJunction(property_package=prop_package) + blk.unit = DeepWellInjection( + property_package=prop_package, injection_well_depth=injection_well_depth + ) + + blk.feed_to_unit = Arc(source=blk.feed.outlet, destination=blk.unit.inlet) + + +def set_system_operating_conditions(m, Qin=5, tds=130): + + Qin = Qin * pyunits.Mgallons / pyunits.day + flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + flow_mass_water = pyunits.convert(Qin * rho, to_units=pyunits.kg / pyunits.s) + flow_mass_tds = pyunits.convert( + Qin * tds * pyunits.g / pyunits.liter, to_units=pyunits.kg / pyunits.s + ) + + m.fs.feed.properties.calculate_state( + var_args={ + ("flow_vol_phase", "Liq"): flow_in, + ("conc_mass_phase_comp", ("Liq", "TDS")): tds * pyunits.g / pyunits.liter, + ("temperature", None): 298.15, + ("pressure", None): 101325, + }, + hold_state=True, + ) + + # m.fs.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"].fix(flow_mass_water) + # m.fs.feed.properties[0].flow_mass_phase_comp["Liq", "TDS"].fix(flow_mass_tds) + # m.fs.feed.properties[0].temperature.fix(293) + # m.fs.feed.properties[0].pressure.fix(101325) + + m.fs.properties.set_default_scaling( + "flow_mass_phase_comp", + value(1 / flow_mass_water), + index=("Liq", "H2O"), + ) + + m.fs.properties.set_default_scaling( + "flow_mass_phase_comp", + value(1 / flow_mass_tds), + index=("Liq", "TDS"), + ) + + +def init_system(m, blk): + + m.fs.feed.initialize() + propagate_state(m.fs.feed_to_dwi) + init_dwi(m, blk) + print("DWI") + print(f"\tblock DOF after init = {degrees_of_freedom(blk)}\n") + print(f"\tunit DOF after init = {degrees_of_freedom(blk.unit)}\n") + + +def init_dwi(m, blk, solver=None): + if solver is None: + solver = get_solver() + + optarg = solver.options + + blk.feed.initialize() + propagate_state(blk.feed_to_unit) + blk.unit.initialize(optarg=optarg, outlvl=idaeslogger.INFO) + + +def add_dwi_costing(m, blk, flowsheet_costing_block=None): + """ + Add DWI costing using BLM approach + """ + if flowsheet_costing_block is None: + flowsheet_costing_block = m.fs.costing + + blk.unit.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block, + costing_method_arguments={ + "cost_method": "as_opex" + }, # could be "as_capex" or "blm" + ) + flowsheet_costing_block.deep_well_injection.dwi_lcow.set_value(0.1) + + +def report_DWI(m, blk): + print(f"\n\n-------------------- DWI Report --------------------\n") + print("\n") + print( + f'{"Injection Well Depth":<30s}{value(blk.unit.config.injection_well_depth):<10.3f}{pyunits.get_units(blk.unit.config.injection_well_depth)}' + ) + + +def print_DWI_costing_breakdown(m, blk): + print(f"\n\n-------------------- DWI Costing Breakdown --------------------\n") + print("\n") + print(f'{"Capital Cost":<30s}{f"${blk.unit.costing.capital_cost():<25,.0f}"}') + print( + f'{"Capital Cost":<30s}{f"${blk.unit.costing.variable_operating_cost():<25,.0f}"}' + ) + + +if __name__ == "__main__": + file_dir = os.path.dirname(os.path.abspath(__file__)) + m = build_and_run_dwi(Qin=5, tds=130) + + # m = build_system() + # add_dwi_costing(m, m.fs.DWI) + # m.fs.costing.cost_process() + # m.fs.costing.add_LCOW(m.fs.feed.properties[0].flow_vol_phase["Liq"]) + # set_system_operating_conditions(m) + print(f"dof = {degrees_of_freedom(m)}") + # init_system(m, m.fs.DWI) + + # solver = get_solver() + # results = solver.solve(m) + # assert_optimal_termination(results) + + # print(f"LCOW = {m.fs.costing.LCOW()}") + + # # init_DWI(m, m.fs.DWI) + # # add_DWI_costing(m, m.fs.DWI) + # # m.fs.costing.cost_process() + # # solve(m) + + # # report_DWI(m, m.fs.DWI) + # # print_DWI_costing_breakdown(m, m.fs.DWI) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/denormalizer_cryst.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/denormalizer_cryst.py new file mode 100644 index 00000000..1f1422ea --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/denormalizer_cryst.py @@ -0,0 +1,168 @@ +################################################################################# +# WaterTAP Copyright (c) 2020-2024, The Regents of the University of California, +# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, +# National Renewable Energy Laboratory, and National Energy Technology +# Laboratory (subject to receipt of any required approvals from the U.S. Dept. +# of Energy). All rights reserved. +# +# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license +# information, respectively. These files are also available online at the URL +# "https://github.com/watertap-org/watertap/" +################################################################################# + +# Import Pyomo libraries +from pyomo.common.config import ConfigBlock, ConfigValue, In, Bool + +# Import IDAES cores +from idaes.core import declare_process_block_class, UnitModelBlockData +from idaes.models.unit_models.translator import TranslatorData +from idaes.core.util.config import ( + is_reaction_parameter_block, + is_physical_parameter_block, +) + +from idaes.core.util.exceptions import ConfigurationError +from idaes.core.util.model_statistics import degrees_of_freedom +from idaes.core.solvers import get_solver +import idaes.logger as idaeslog +import idaes.core.util.scaling as iscale + +from idaes.core.util.exceptions import InitializationError + +from pyomo.environ import ( + Param, + units as pyunits, + check_optimal_termination, + Set, +) + +__author__ = "Zhuoran Zhang" + + +# Set up logger +_log = idaeslog.getLogger(__name__) + + +@declare_process_block_class("Denormalizer_Cryst") +class Denormalizer_Cryst_Data(TranslatorData): + """ + Temporary translator to normalize the crystallization feed flow + """ + + CONFIG = TranslatorData.CONFIG() + + def build(self): + + super().build() + + @self.Constraint(doc="Isothermal") + def eq_temperature(b): + return b.properties_in[0].temperature == b.properties_out[0].temperature + + @self.Constraint(doc="Isobaric") + def eq_pressure(b): + return b.properties_in[0].pressure == b.properties_out[0].pressure + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow water equation", + ) + def eq_flow_mass_water(blk, t): + return ( + blk.properties_out[t].flow_mass_phase_comp["Liq", "H2O"] + == blk.properties_in[t].flow_mass_phase_comp["Liq", "H2O"] * 10 + ) + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow TDS equation", + ) + def eq_flow_mass_tds(blk, t): + return ( + blk.properties_out[t].flow_mass_phase_comp["Liq", "NaCl"] + == blk.properties_in[t].flow_mass_phase_comp["Liq", "NaCl"] * 10 + ) + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow vapor equation", + ) + def eq_flow_mass_vapor(blk, t): + return blk.properties_out[t].flow_mass_phase_comp["Vap", "H2O"] == 0 + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow sol equation", + ) + def eq_flow_mass_sol(blk, t): + return blk.properties_out[t].flow_mass_phase_comp["Sol", "NaCl"] == 0 + + def initialize_build( + self, + state_args_in=None, + state_args_out=None, + outlvl=idaeslog.NOTSET, + solver=None, + optarg=None, + ): + """ + This method calls the initialization method of the state blocks. + + Keyword Arguments: + state_args_in : a dict of arguments to be passed to the inlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + state_args_out : a dict of arguments to be passed to the outlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + outlvl : sets output level of initialization routine + optarg : solver options dictionary object (default=None, use + default solver options) + solver : str indicating which solver to use during + initialization (default = None, use default solver) + + Returns: + None + """ + init_log = idaeslog.getInitLogger(self.name, outlvl, tag="unit") + + # Create solver + opt = get_solver(solver, optarg) + + # --------------------------------------------------------------------- + # Initialize state block + flags = self.properties_in.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_in, + hold_state=True, + ) + + self.properties_out.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_out, + ) + + if degrees_of_freedom(self) != 0: + raise Exception( + f"{self.name} degrees of freedom were not 0 at the beginning " + f"of initialization. DoF = {degrees_of_freedom(self)}" + ) + + with idaeslog.solver_log(init_log, idaeslog.DEBUG) as slc: + res = opt.solve(self, tee=slc.tee) + + self.properties_in.release_state(flags=flags, outlvl=outlvl) + + init_log.info(f"Initialization Complete: {idaeslog.condition(res)}") + + if not check_optimal_termination(res): + raise InitializationError( + f"{self.name} failed to initialize successfully. Please check " + f"the output logs for more information." + ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/multi_effect_crystallizer.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/multi_effect_crystallizer.py new file mode 100644 index 00000000..45fe54d2 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/multi_effect_crystallizer.py @@ -0,0 +1,346 @@ +import pathlib +from pyomo.environ import ( + ConcreteModel, + value, + TransformationFactory, + Param, + Var, + Constraint, + Set, + Expression, + Objective, + Block, + RangeSet, + check_optimal_termination, + assert_optimal_termination, + units as pyunits, +) +from pyomo.util.calc_var_value import calculate_variable_from_constraint as cvc + +from idaes.core import FlowsheetBlock, UnitModelCostingBlock +from idaes.core.util.initialization import propagate_state +from idaes.core.util.model_statistics import * +from idaes.core.util.scaling import * +from watertap.core.util.model_diagnostics import * +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.core.util.initialization import * +from watertap.core.solvers import get_solver + +from watertap.property_models.unit_specific.cryst_prop_pack import ( + NaClParameterBlock, + NaClStateBlock, +) +from watertap.property_models.water_prop_pack import ( + WaterParameterBlock as SteamParameterBlock, + WaterStateBlock, +) +from watertap_contrib.reflo.unit_models.multi_effect_crystallizer import ( + MultiEffectCrystallizer, +) + +# from watertap_contrib.reflo.unit_models.crystallizer_effect import CrystallizerEffect + +from watertap_contrib.reflo.costing import ( + TreatmentCosting, + EnergyCosting, + REFLOCosting, +) + +__all__ = [ + "build_system", + "build_mec", + "set_mec_op_conditions", + "add_mec_costing", + "init_mec", + "unfix_mec", + "mec_rescaling", +] + + +def build_system(): + m = ConcreteModel() + m.fs = FlowsheetBlock(dynamic=False) + + m.fs.properties_vapor = SteamParameterBlock() + m.fs.properties_NaCl = NaClParameterBlock() + + m.fs.costing = TreatmentCosting() + + build_mec( + m, + m.fs, + prop_package=m.fs.properties_NaCl, + prop_package_vapor=m.fs.properties_vapor, + ) + + return m + + +def build_mec(m, blk, prop_package, prop_package_vapor) -> None: + + if prop_package is None: + prop_package = NaClParameterBlock() + if prop_package_vapor is None: + prop_package_vapor = SteamParameterBlock() + + blk.unit = MultiEffectCrystallizer( + property_package=prop_package, property_package_vapor=prop_package_vapor + ) + + +def set_mec_op_conditions( + m, + blk, + operating_pressures=[0.4455, 0.2758, 0.1651, 0.095], + nacl_yield=0.7, + heat_transfer_coefficient=0.13, +) -> None: + + mec = blk.unit + + # Guessed values for initialization + flow_in = 5 + rho = 1000 * pyunits.kg / pyunits.m**3 + conc_in = 160 * pyunits.g / pyunits.L + feed_pressure = 101325 + feed_temperature = 273.15 + 20 + ### TOTAL GOING INTO MEC + flow_vol_in = pyunits.convert( + flow_in * pyunits.Mgallons / pyunits.day, to_units=pyunits.m**3 / pyunits.s + ) + flow_mass_phase_water_total = pyunits.convert( + flow_vol_in * rho, to_units=pyunits.kg / pyunits.s + ) + flow_mass_phase_salt_total = pyunits.convert( + flow_vol_in * conc_in, to_units=pyunits.kg / pyunits.s + ) + ### TOTAL INTO EACH EFFECT INITIAL + """ + Note: In the initial solve of the system, assume the total feed flow rate is 1 kg/s, + which is align to the default value, in order to guarantee a solution in the initial solve. + """ + # flow_mass_phase_water_per = 116.2473764168908 / 100 * pyunits.kg / pyunits.s + # flow_mass_phase_salt_per = 28.478213652777765 / 100 * pyunits.kg / pyunits.s + # flow_mass_phase_water_per = 116 / 100 * pyunits.kg / pyunits.s + # flow_mass_phase_salt_per = 28 / 100 * pyunits.kg / pyunits.s + + flow_mass_phase_water_per = ( + flow_mass_phase_water_total + / (flow_mass_phase_water_total + flow_mass_phase_salt_total) + * pyunits.kg + / pyunits.s + ) + flow_mass_phase_salt_per = ( + flow_mass_phase_salt_total + / (flow_mass_phase_water_total + flow_mass_phase_salt_total) + * pyunits.kg + / pyunits.s + ) + + saturated_steam_pressure = 101325 * pyunits.Pa + pyunits.convert( + 3 * pyunits.bar, to_units=pyunits.Pa + ) + + ### FIX UNIT MODEL PARAMETERS + for (_, eff), op_pressure in zip(mec.effects.items(), operating_pressures): + + eff.effect.properties_in[0].flow_mass_phase_comp["Liq", "H2O"].fix( + flow_mass_phase_water_per + ) + eff.effect.properties_in[0].flow_mass_phase_comp["Liq", "NaCl"].fix( + flow_mass_phase_salt_per + ) + + eff.effect.properties_in[0].pressure.fix(feed_pressure) + eff.effect.properties_in[0].temperature.fix(feed_temperature) + + eff.effect.properties_in[0].flow_mass_phase_comp["Sol", "NaCl"].fix(0) + eff.effect.properties_in[0].flow_mass_phase_comp["Vap", "H2O"].fix(0) + eff.effect.properties_in[0].conc_mass_phase_comp[...] + + eff.effect.crystallization_yield["NaCl"].fix(nacl_yield) + eff.effect.crystal_growth_rate.fix() + eff.effect.souders_brown_constant.fix() + eff.effect.crystal_median_length.fix() + + eff.effect.pressure_operating.fix( + pyunits.convert(op_pressure * pyunits.bar, to_units=pyunits.Pa) + ) + eff.effect.overall_heat_transfer_coefficient.fix(heat_transfer_coefficient) + + first_effect = mec.effects[1].effect + + first_effect.overall_heat_transfer_coefficient.fix(heat_transfer_coefficient) + first_effect.heating_steam[0].pressure_sat + first_effect.heating_steam[0].dh_vap_mass + first_effect.heating_steam.calculate_state( + var_args={ + ("flow_mass_phase_comp", ("Liq", "H2O")): 0, + ("pressure", None): saturated_steam_pressure, + ("pressure_sat", None): saturated_steam_pressure, + }, + hold_state=True, + ) + first_effect.heating_steam[0].flow_mass_phase_comp["Vap", "H2O"].unfix() + + ### FIX CV PROPERTIES EXCEPT FOR THE LIQUID FLOW RATES + mec.control_volume.properties_in[0].pressure.fix(feed_pressure) + mec.control_volume.properties_in[0].temperature.fix(feed_temperature) + mec.control_volume.properties_in[0].flow_mass_phase_comp["Sol", "NaCl"].fix(0) + + """ + Check DOF + """ + for n, eff in mec.effects.items(): + assert degrees_of_freedom(eff.effect) == 0 + + +def init_mec(m, blk): + mec = blk.unit + + ### INITIALIZE FOR EACH EFFECT + for n, eff in mec.effects.items(): + eff.effect.initialize() + + ### UNFIX THE INLET FLOW RATES OF EACH EFFECT + for n, eff in mec.effects.items(): + if n > 1: + eff.effect.properties_in[0].flow_mass_phase_comp["Liq", "H2O"].unfix() + eff.effect.properties_in[0].flow_mass_phase_comp["Liq", "NaCl"].unfix() + eff.effect.properties_in[0].conc_mass_phase_comp["Liq", "NaCl"].fix() + + for n, eff in mec.effects.items(): + if n == 1: + assert degrees_of_freedom(eff.effect) == 0 + else: + assert degrees_of_freedom(eff.effect) == 1 + + ### FULLY SOLVE THE MODEL + m.fs.properties_NaCl.set_default_scaling( + "flow_mass_phase_comp", 1e-1, index=("Liq", "H2O") + ) + m.fs.properties_NaCl.set_default_scaling( + "flow_mass_phase_comp", 1e-1, index=("Liq", "NaCl") + ) + m.fs.properties_NaCl.set_default_scaling( + "flow_mass_phase_comp", 1e-1, index=("Vap", "H2O") + ) + m.fs.properties_NaCl.set_default_scaling( + "flow_mass_phase_comp", 1e-1, index=("Sol", "NaCl") + ) + m.fs.properties_vapor.set_default_scaling( + "flow_mass_phase_comp", 1e-1, index=("Vap", "H2O") + ) + m.fs.properties_vapor.set_default_scaling( + "flow_mass_phase_comp", 1, index=("Liq", "H2O") + ) + + calculate_scaling_factors(blk) + + solver = get_solver() + results = solver.solve(blk) + assert_optimal_termination(results) + + +def unfix_mec(blk): + mec = blk.unit + + first_effect = mec.effects[1].effect + ### Release 1st effect flow rate and fix total flow rate instead + first_effect.properties_in[0].flow_mass_phase_comp["Liq", "H2O"].unfix() + first_effect.properties_in[0].flow_mass_phase_comp["Liq", "NaCl"].unfix() + + mec.inlet.temperature[0].unfix() + mec.inlet.pressure[0].unfix() + + +def mec_rescaling( + blk, + flow_mass_phase_water_total=116.247 / 10, + flow_mass_phase_salt_total=28.478 / 10, +): + """ + Note: Rescaling is probably needed for extremely large feed flow, + """ + blk.properties_NaCl.set_default_scaling( + "flow_mass_phase_comp", + 1 / value(flow_mass_phase_water_total), + index=("Liq", "H2O"), + ) + blk.properties_NaCl.set_default_scaling( + "flow_mass_phase_comp", + 1 / value(flow_mass_phase_salt_total), + index=("Liq", "NaCl"), + ) + blk.properties_NaCl.set_default_scaling( + "flow_mass_phase_comp", 10, index=("Vap", "H2O") + ) + blk.properties_NaCl.set_default_scaling( + "flow_mass_phase_comp", 1e-2, index=("Sol", "NaCl") + ) + blk.properties_vapor.set_default_scaling( + "flow_mass_phase_comp", 1e-2, index=("Vap", "H2O") + ) + blk.properties_vapor.set_default_scaling( + "flow_mass_phase_comp", 1, index=("Liq", "H2O") + ) + + +def add_mec_costing(m, blk, flowsheet_costing_block=None): + if flowsheet_costing_block is None: + flowsheet_costing_block = m.fs.costing + blk.unit.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block, + ) + + +def solve(m, solver=None, tee=True, raise_on_failure=True): + # ---solving--- + if solver is None: + solver = get_solver() + + print("\n--------- SOLVING ---------\n") + + results = solver.solve(m, tee=tee) + + if check_optimal_termination(results): + print("\n--------- OPTIMAL SOLVE!!! ---------\n") + return results + msg = ( + "The current configuration is infeasible. Please adjust the decision variables." + ) + if raise_on_failure: + raise RuntimeError(msg) + else: + return results + + +if __name__ == "__main__": + + m = build_system() + + set_mec_op_conditions(m, m.fs, heat_transfer_coefficient=0.13) + init_mec(m, m.fs) + unfix_mec(m.fs) + + flow_mass_phase_water_total = 11.6 + flow_mass_phase_salt_total = 2.8 + + m.fs.unit.inlet.flow_mass_phase_comp[0, "Liq", "H2O"].fix( + flow_mass_phase_water_total + ) + m.fs.unit.inlet.flow_mass_phase_comp[0, "Liq", "NaCl"].fix( + flow_mass_phase_salt_total + ) + + m.fs.unit.inlet.temperature[0].fix(273.15 + 30.51) + m.fs.unit.inlet.pressure[0].fix(101325) + # mec_rescaling(m.fs) + add_mec_costing(m, m.fs) + + print("") + print("here") + print("") + m.fs.unit.inlet.display() + + solve(m) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/normalizer_cryst.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/normalizer_cryst.py new file mode 100644 index 00000000..ab6f77e5 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/normalizer_cryst.py @@ -0,0 +1,168 @@ +################################################################################# +# WaterTAP Copyright (c) 2020-2024, The Regents of the University of California, +# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, +# National Renewable Energy Laboratory, and National Energy Technology +# Laboratory (subject to receipt of any required approvals from the U.S. Dept. +# of Energy). All rights reserved. +# +# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license +# information, respectively. These files are also available online at the URL +# "https://github.com/watertap-org/watertap/" +################################################################################# + +# Import Pyomo libraries +from pyomo.common.config import ConfigBlock, ConfigValue, In, Bool + +# Import IDAES cores +from idaes.core import declare_process_block_class, UnitModelBlockData +from idaes.models.unit_models.translator import TranslatorData +from idaes.core.util.config import ( + is_reaction_parameter_block, + is_physical_parameter_block, +) + +from idaes.core.util.exceptions import ConfigurationError +from idaes.core.util.model_statistics import degrees_of_freedom +from idaes.core.solvers import get_solver +import idaes.logger as idaeslog +import idaes.core.util.scaling as iscale + +from idaes.core.util.exceptions import InitializationError + +from pyomo.environ import ( + Param, + units as pyunits, + check_optimal_termination, + Set, +) + +__author__ = "Zhuoran Zhang" + + +# Set up logger +_log = idaeslog.getLogger(__name__) + + +@declare_process_block_class("Normalizer_Cryst") +class Normalizer_Cryst_Data(TranslatorData): + """ + Temporary translator to normalize the crystallization feed flow + """ + + CONFIG = TranslatorData.CONFIG() + + def build(self): + + super().build() + + @self.Constraint(doc="Isothermal") + def eq_temperature(b): + return b.properties_in[0].temperature == b.properties_out[0].temperature + + @self.Constraint(doc="Isobaric") + def eq_pressure(b): + return b.properties_in[0].pressure == b.properties_out[0].pressure + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow water equation", + ) + def eq_flow_mass_water(blk, t): + return ( + blk.properties_out[t].flow_mass_phase_comp["Liq", "H2O"] + == blk.properties_in[t].flow_mass_phase_comp["Liq", "H2O"] / 10 + ) + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow TDS equation", + ) + def eq_flow_mass_tds(blk, t): + return ( + blk.properties_out[t].flow_mass_phase_comp["Liq", "NaCl"] + == blk.properties_in[t].flow_mass_phase_comp["Liq", "NaCl"] / 10 + ) + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow vapor equation", + ) + def eq_flow_mass_vapor(blk, t): + return blk.properties_out[t].flow_mass_phase_comp["Vap", "H2O"] == 0 + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow sol equation", + ) + def eq_flow_mass_sol(blk, t): + return blk.properties_out[t].flow_mass_phase_comp["Sol", "NaCl"] == 0 + + def initialize_build( + self, + state_args_in=None, + state_args_out=None, + outlvl=idaeslog.NOTSET, + solver=None, + optarg=None, + ): + """ + This method calls the initialization method of the state blocks. + + Keyword Arguments: + state_args_in : a dict of arguments to be passed to the inlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + state_args_out : a dict of arguments to be passed to the outlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + outlvl : sets output level of initialization routine + optarg : solver options dictionary object (default=None, use + default solver options) + solver : str indicating which solver to use during + initialization (default = None, use default solver) + + Returns: + None + """ + init_log = idaeslog.getInitLogger(self.name, outlvl, tag="unit") + + # Create solver + opt = get_solver(solver, optarg) + + # --------------------------------------------------------------------- + # Initialize state block + flags = self.properties_in.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_in, + hold_state=True, + ) + + self.properties_out.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_out, + ) + + if degrees_of_freedom(self) != 0: + raise Exception( + f"{self.name} degrees of freedom were not 0 at the beginning " + f"of initialization. DoF = {degrees_of_freedom(self)}" + ) + + with idaeslog.solver_log(init_log, idaeslog.DEBUG) as slc: + res = opt.solve(self, tee=slc.tee) + + self.properties_in.release_state(flags=flags, outlvl=outlvl) + + init_log.info(f"Initialization Complete: {idaeslog.condition(res)}") + + if not check_optimal_termination(res): + raise InitializationError( + f"{self.name} failed to initialize successfully. Please check " + f"the output logs for more information." + ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/oxidation.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/oxidation.py new file mode 100644 index 00000000..c03dcfde --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/oxidation.py @@ -0,0 +1,249 @@ +import pathlib +from pyomo.environ import ( + ConcreteModel, + value, + TransformationFactory, + Param, + Var, + Constraint, + Set, + Expression, + Objective, + NonNegativeReals, + Block, + RangeSet, + check_optimal_termination, + assert_optimal_termination, + units as pyunits, +) +from pyomo.network import Arc, SequentialDecomposition +from pyomo.util.check_units import assert_units_consistent +from pyomo.util.calc_var_value import calculate_variable_from_constraint as cvc + +from idaes.core import FlowsheetBlock, UnitModelCostingBlock +from idaes.core.util.initialization import propagate_state +from idaes.core.util.scaling import ( + constraint_scaling_transform, + calculate_scaling_factors, + set_scaling_factor, +) +from idaes.models.unit_models import Product, Feed, StateJunction, Separator +from idaes.core.util.model_statistics import * + +from watertap.core.solvers import get_solver +from watertap.core import Database +from watertap_contrib.reflo.core.wt_reflo_database import REFLODatabase +from watertap.unit_models.zero_order import ChemicalAdditionZO +from watertap.core.wt_database import Database +from watertap.core.zero_order_properties import WaterParameterBlock as ZO +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.property_models.multicomp_aq_sol_prop_pack import MCASParameterBlock +from watertap.core.util.initialization import * + +from watertap_contrib.reflo.costing import ( + TreatmentCosting, + EnergyCosting, + REFLOCosting, +) + +reflo_dir = pathlib.Path(__file__).resolve().parents[4] +case_study_yaml = f"{reflo_dir}/data/technoeconomic/permian_case_study.yaml" +rho = 1000 * pyunits.kg / pyunits.m**3 + + +__all__ = [ + "build_chem_addition", + "set_chem_addition_op_conditions", + "set_chem_addition_scaling", + "add_chem_addition_costing", + "init_chem_addition", +] + + +def build_system(): + m = ConcreteModel() + m.db = REFLODatabase() + m.fs = FlowsheetBlock(dynamic=False) + m.fs.costing = TreatmentCosting(case_study_definition=case_study_yaml) + m.fs.properties = ZO(solute_list=["tds"]) + m.fs.feed = Feed(property_package=m.fs.properties) + m.fs.product = Product(property_package=m.fs.properties) + + m.fs.chem_addition = FlowsheetBlock(dynamic=False) + + build_chem_addition(m, m.fs.chem_addition, m.fs.properties) + + m.fs.feed_to_chem = Arc( + source=m.fs.feed.outlet, + destination=m.fs.chem_addition.feed.inlet, + ) + + m.fs.chem_to_product = Arc( + source=m.fs.chem_addition.product.outlet, + destination=m.fs.product.inlet, + ) + + TransformationFactory("network.expand_arcs").apply_to(m) + + return m + + +def build_chem_addition(m, blk, prop_package=None) -> None: + + print(f'\n{"=======> BUILDING CHEMICAL ADDITION SYSTEM <=======":^60}\n') + + if prop_package is None: + prop_package = m.fs.properties + + blk.feed = StateJunction(property_package=prop_package) + blk.product = StateJunction(property_package=prop_package) + + blk.unit = ChemicalAdditionZO( + property_package=prop_package, + database=m.db, + process_subtype="hydrogen_peroxide", + ) + blk.feed_to_unit = Arc( + source=blk.feed.outlet, + destination=blk.unit.inlet, + ) + + blk.unit_to_product = Arc( + source=blk.unit.outlet, + destination=blk.product.inlet, + ) + + TransformationFactory("network.expand_arcs").apply_to(m) + + +def set_system_operating_conditions(m, Qin=5, tds=130): + print( + "\n\n-------------------- SETTING SYSTEM OPERATING CONDITIONS --------------------\n\n" + ) + Qin = Qin * pyunits.Mgal / pyunits.day + tds = tds * pyunits.kg / pyunits.m**3 + + flow_mass_water = pyunits.convert(Qin * rho, to_units=pyunits.kg / pyunits.s) + flow_mass_tds = pyunits.convert(Qin * tds, to_units=pyunits.kg / pyunits.s) + + m.fs.feed.properties[0].flow_mass_comp["H2O"].fix(flow_mass_water) + m.fs.feed.properties[0].flow_mass_comp["tds"].fix(flow_mass_tds) + m.fs.chem_addition.unit.properties[0].flow_mass_comp["tds"].set_value(flow_mass_tds) + + +def set_chem_addition_scaling(m, blk, calc_blk_scaling_factors=False): + + set_scaling_factor(blk.unit.chemical_dosage, 0.1) + set_scaling_factor(blk.unit.solution_density, 1e-3) + set_scaling_factor(blk.unit.chemical_flow_vol, 1e6) + set_scaling_factor(blk.unit.electricity, 1e4) + + # Calculate scaling factors only for chem addition block if in full case study flowsheet + # so we don't prematurely set scaling factors + if calc_blk_scaling_factors: + calculate_scaling_factors(blk) + + # otherwise calculate all scaling factors + else: + calculate_scaling_factors(m) + + +def set_chem_addition_op_conditions(m, blk, **kwargs): + + blk.unit.load_parameters_from_database() + for k, v in kwargs.items(): + print(blk.name, k) + try: + vv = getattr(blk.unit, k) + except: + continue + print(f"{blk.name} {vv.name} {v}") + if isinstance(vv, Var): + vv.fix(v) + if isinstance(vv, Param): + vv.set_value(v) + + print(f"Chem Addition") + print(f"\tblock DOF = {degrees_of_freedom(blk)}\n") + print(f"\tunit DOF = {degrees_of_freedom(blk.unit)}\n") + + +def add_chem_addition_costing(m, blk, flowsheet_costing_block=None): + if flowsheet_costing_block is None: + flowsheet_costing_block = m.fs.costing + blk.unit.costing = UnitModelCostingBlock( + flowsheet_costing_block=flowsheet_costing_block + ) + + +def init_system(blk, solver=None, flow_out=None): + if solver is None: + solver = get_solver() + if flow_out is None: + flow_out = blk.fs.feed.properties[0].flow_vol + + print("\n\n-------------------- INITIALIZING SYSTEM --------------------\n\n") + print(f"System Degrees of Freedom: {degrees_of_freedom(m)}") + print(f"Chem Addition Degrees of Freedom: {degrees_of_freedom(m.fs.chem_addition)}") + + m.fs.feed.initialize() + propagate_state(m.fs.feed_to_chem) + init_chem_addition(m, m.fs.chem_addition) + propagate_state(m.fs.chem_to_product) + m.fs.product.initialize() + + m.fs.costing.cost_process() + m.fs.costing.initialize() + m.fs.costing.add_LCOW(flow_out) + + +def init_chem_addition(m, blk): + blk.feed.initialize() + propagate_state(blk.feed_to_unit) + blk.unit.initialize() + propagate_state(blk.unit_to_product) + print(f"Chem Addition") + print(f"\tblock DOF after init = {degrees_of_freedom(blk)}\n") + print(f"\tunit DOF after init = {degrees_of_freedom(blk.unit)}\n") + + +def print_chem_addition_costing_breakdown(blk): + print( + f'{"Hydrogen Peroxide Dose":<35s}{f"{blk.unit.chemical_dosage[0]():<25,.0f} mg/L"}' + ) + print( + f'{"Chem Addition Capital Cost":<35s}{f"${blk.unit.costing.capital_cost():<25,.0f}"}' + ) + + +def solve(m, solver=None, tee=True, raise_on_failure=True): + + if solver is None: + solver = get_solver() + + print("\n--------- SOLVING ---------\n") + + results = solver.solve(m, tee=tee) + + if check_optimal_termination(results): + print("\n--------- OPTIMAL SOLVE!!! ---------\n") + return results + msg = ( + "The current configuration is infeasible. Please adjust the decision variables." + ) + if raise_on_failure: + raise RuntimeError(msg) + else: + return results + + +if __name__ == "__main__": + m = build_system() + set_system_operating_conditions(m) + set_chem_addition_op_conditions(m, m.fs.chem_addition) + add_chem_addition_costing(m, m.fs.chem_addition) + set_chem_addition_scaling(m, m.fs.chem_addition, calc_blk_scaling_factors=True) + init_system(m) + solve(m) + print_chem_addition_costing_breakdown(m.fs.chem_addition) + print(f"LCOW = {m.fs.costing.LCOW()}") diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_sw_to_nacl.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_sw_to_nacl.py new file mode 100644 index 00000000..06485341 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_sw_to_nacl.py @@ -0,0 +1,152 @@ +################################################################################# +# WaterTAP Copyright (c) 2020-2024, The Regents of the University of California, +# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, +# National Renewable Energy Laboratory, and National Energy Technology +# Laboratory (subject to receipt of any required approvals from the U.S. Dept. +# of Energy). All rights reserved. +# +# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license +# information, respectively. These files are also available online at the URL +# "https://github.com/watertap-org/watertap/" +################################################################################# + +# Import Pyomo libraries +from pyomo.common.config import ConfigBlock, ConfigValue, In, Bool + +# Import IDAES cores +from idaes.core import declare_process_block_class, UnitModelBlockData +from idaes.models.unit_models.translator import TranslatorData +from idaes.core.util.config import ( + is_reaction_parameter_block, + is_physical_parameter_block, +) + +from idaes.core.util.exceptions import ConfigurationError +from idaes.core.util.model_statistics import degrees_of_freedom +from idaes.core.solvers import get_solver +import idaes.logger as idaeslog +import idaes.core.util.scaling as iscale + +from idaes.core.util.exceptions import InitializationError + +from pyomo.environ import ( + Param, + units as pyunits, + check_optimal_termination, + Set, +) + +__author__ = "Zhuoran Zhang" + + +# Set up logger +_log = idaeslog.getLogger(__name__) + + +@declare_process_block_class("Translator_SW_to_NaCl") +class Translator_SW_to_NaCl_Data(TranslatorData): + """ + Translator block for Seawater to NaCl property packages + """ + + CONFIG = TranslatorData.CONFIG() + + def build(self): + + super().build() + + @self.Constraint(doc="Isothermal") + def eq_temperature(b): + return b.properties_in[0].temperature == b.properties_out[0].temperature + + @self.Constraint(doc="Isobaric") + def eq_pressure(b): + return b.properties_in[0].pressure == b.properties_out[0].pressure + + @self.Constraint( + doc="Equality mass flow water equation", + ) + def eq_flow_mass_water(b): + return ( + b.properties_in[0].flow_mass_phase_comp["Liq", "H2O"] + == b.properties_out[0].flow_mass_phase_comp["Liq", "H2O"] + ) + + @self.Constraint( + doc="Equality mass flow TDS equation", + ) + def eq_flow_mass_tds(b): + return ( + b.properties_in[0].flow_mass_phase_comp["Liq", "TDS"] + == b.properties_out[0].flow_mass_phase_comp["Liq", "NaCl"] + ) + + def initialize_build( + self, + state_args_in=None, + state_args_out=None, + outlvl=idaeslog.NOTSET, + solver=None, + optarg=None, + ): + """ + This method calls the initialization method of the state blocks. + + Keyword Arguments: + state_args_in : a dict of arguments to be passed to the inlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + state_args_out : a dict of arguments to be passed to the outlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + outlvl : sets output level of initialization routine + optarg : solver options dictionary object (default=None, use + default solver options) + solver : str indicating which solver to use during + initialization (default = None, use default solver) + + Returns: + None + """ + init_log = idaeslog.getInitLogger(self.name, outlvl, tag="unit") + + # Create solver + opt = get_solver(solver, optarg) + + # --------------------------------------------------------------------- + # Initialize state block + flags = self.properties_in.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_in, + hold_state=True, + ) + + self.properties_out.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_out, + ) + + if degrees_of_freedom(self) != 0: + raise Exception( + f"{self.name} degrees of freedom were not 0 at the beginning " + f"of initialization. DoF = {degrees_of_freedom(self)}" + ) + + with idaeslog.solver_log(init_log, idaeslog.DEBUG) as slc: + res = opt.solve(self, tee=slc.tee) + + self.properties_in.release_state(flags=flags, outlvl=outlvl) + + init_log.info(f"Initialization Complete: {idaeslog.condition(res)}") + + if not check_optimal_termination(res): + raise InitializationError( + f"{self.name} failed to initialize successfully. Please check " + f"the output logs for more information." + ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_sw_to_water.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_sw_to_water.py new file mode 100644 index 00000000..adc3163e --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_sw_to_water.py @@ -0,0 +1,152 @@ +################################################################################# +# WaterTAP Copyright (c) 2020-2024, The Regents of the University of California, +# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, +# National Renewable Energy Laboratory, and National Energy Technology +# Laboratory (subject to receipt of any required approvals from the U.S. Dept. +# of Energy). All rights reserved. +# +# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license +# information, respectively. These files are also available online at the URL +# "https://github.com/watertap-org/watertap/" +################################################################################# + +# Import Pyomo libraries +from pyomo.common.config import ConfigBlock, ConfigValue, In, Bool + +# Import IDAES cores +from idaes.core import declare_process_block_class, UnitModelBlockData +from idaes.models.unit_models.translator import TranslatorData +from idaes.core.util.config import ( + is_reaction_parameter_block, + is_physical_parameter_block, +) + +from idaes.core.util.exceptions import ConfigurationError +from idaes.core.util.model_statistics import degrees_of_freedom +from idaes.core.solvers import get_solver +import idaes.logger as idaeslog +import idaes.core.util.scaling as iscale + +from idaes.core.util.exceptions import InitializationError + +from pyomo.environ import ( + Param, + units as pyunits, + check_optimal_termination, + Set, +) + +__author__ = "Kurban Sitterley" + + +# Set up logger +_log = idaeslog.getLogger(__name__) + + +@declare_process_block_class("Translator_SW_to_Water") +class Translator_ZO_to_SW_Data(TranslatorData): + """ + Translator block for Seawater to Water property packages + """ + + CONFIG = TranslatorData.CONFIG() + + def build(self): + + super().build() + + @self.Constraint(doc="Isothermal") + def eq_temperature(b): + return b.properties_in[0].temperature == b.properties_out[0].temperature + + @self.Constraint(doc="Isobaric") + def eq_pressure(b): + return b.properties_in[0].pressure == b.properties_out[0].pressure + + @self.Constraint( + doc="Equality mass flow water equation", + ) + def eq_flow_mass_water(b): + return ( + b.properties_in[0].flow_mass_phase_comp["Liq", "H2O"] + == b.properties_out[0].flow_mass_phase_comp["Liq", "H2O"] + ) + + # @self.Constraint( + # doc="Equality mass flow TDS equation", + # ) + # def eq_flow_mass_tds(b): + # return ( + # b.properties_in[0].flow_mass_phase_comp["Liq", "TDS"] + # == b.properties_out[0].flow_mass_phase_comp["Liq", "TDS"] + # ) + + def initialize_build( + self, + state_args_in=None, + state_args_out=None, + outlvl=idaeslog.NOTSET, + solver=None, + optarg=None, + ): + """ + This method calls the initialization method of the state blocks. + + Keyword Arguments: + state_args_in : a dict of arguments to be passed to the inlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + state_args_out : a dict of arguments to be passed to the outlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + outlvl : sets output level of initialization routine + optarg : solver options dictionary object (default=None, use + default solver options) + solver : str indicating which solver to use during + initialization (default = None, use default solver) + + Returns: + None + """ + init_log = idaeslog.getInitLogger(self.name, outlvl, tag="unit") + + # Create solver + opt = get_solver(solver, optarg) + + # --------------------------------------------------------------------- + # Initialize state block + flags = self.properties_in.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_in, + hold_state=True, + ) + + self.properties_out.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_out, + ) + + if degrees_of_freedom(self) != 0: + raise Exception( + f"{self.name} degrees of freedom were not 0 at the beginning " + f"of initialization. DoF = {degrees_of_freedom(self)}" + ) + + with idaeslog.solver_log(init_log, idaeslog.DEBUG) as slc: + res = opt.solve(self, tee=slc.tee) + + self.properties_in.release_state(flags=flags, outlvl=outlvl) + + init_log.info(f"Initialization Complete: {idaeslog.condition(res)}") + + if not check_optimal_termination(res): + raise InitializationError( + f"{self.name} failed to initialize successfully. Please check " + f"the output logs for more information." + ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_sw_to_zo.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_sw_to_zo.py new file mode 100644 index 00000000..f5452348 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_sw_to_zo.py @@ -0,0 +1,146 @@ +################################################################################# +# WaterTAP Copyright (c) 2020-2024, The Regents of the University of California, +# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, +# National Renewable Energy Laboratory, and National Energy Technology +# Laboratory (subject to receipt of any required approvals from the U.S. Dept. +# of Energy). All rights reserved. +# +# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license +# information, respectively. These files are also available online at the URL +# "https://github.com/watertap-org/watertap/" +################################################################################# + +# Import Pyomo libraries +from pyomo.common.config import ConfigBlock, ConfigValue, In, Bool + +# Import IDAES cores +from idaes.core import declare_process_block_class, UnitModelBlockData +from idaes.models.unit_models.translator import TranslatorData +from idaes.core.util.config import ( + is_reaction_parameter_block, + is_physical_parameter_block, +) + +from idaes.core.util.exceptions import ConfigurationError +from idaes.core.util.model_statistics import degrees_of_freedom +from idaes.core.solvers import get_solver +import idaes.logger as idaeslog +import idaes.core.util.scaling as iscale + +from idaes.core.util.exceptions import InitializationError + +from pyomo.environ import ( + Param, + units as pyunits, + check_optimal_termination, + Set, +) + +__author__ = "Zachary Binger" + + +# Set up logger +_log = idaeslog.getLogger(__name__) + + +@declare_process_block_class("Translator_SW_to_ZO") +class Translator_ZO_to_SW_Data(TranslatorData): + """ + Translator block for ZO to Seawater property packages + """ + + CONFIG = TranslatorData.CONFIG() + + def build(self): + + super().build() + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow water equation", + ) + def eq_flow_mass_water(blk, t): + return ( + blk.properties_in[t].flow_mass_phase_comp["Liq", "H2O"] + == blk.properties_out[t].flow_mass_comp["H2O"] + ) + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow TDS equation", + ) + def eq_flow_mass_tds(blk, t): + return ( + blk.properties_in[t].flow_mass_phase_comp["Liq", "TDS"] + == blk.properties_out[t].flow_mass_comp["tds"] + ) + + def initialize_build( + self, + state_args_in=None, + state_args_out=None, + outlvl=idaeslog.NOTSET, + solver=None, + optarg=None, + ): + """ + This method calls the initialization method of the state blocks. + + Keyword Arguments: + state_args_in : a dict of arguments to be passed to the inlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + state_args_out : a dict of arguments to be passed to the outlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + outlvl : sets output level of initialization routine + optarg : solver options dictionary object (default=None, use + default solver options) + solver : str indicating which solver to use during + initialization (default = None, use default solver) + + Returns: + None + """ + init_log = idaeslog.getInitLogger(self.name, outlvl, tag="unit") + + # Create solver + opt = get_solver(solver, optarg) + + # --------------------------------------------------------------------- + # Initialize state block + flags = self.properties_in.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_in, + hold_state=True, + ) + + self.properties_out.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_out, + ) + + if degrees_of_freedom(self) != 0: + raise Exception( + f"{self.name} degrees of freedom were not 0 at the beginning " + f"of initialization. DoF = {degrees_of_freedom(self)}" + ) + + with idaeslog.solver_log(init_log, idaeslog.DEBUG) as slc: + res = opt.solve(self, tee=slc.tee) + + self.properties_in.release_state(flags=flags, outlvl=outlvl) + + init_log.info(f"Initialization Complete: {idaeslog.condition(res)}") + + if not check_optimal_termination(res): + raise InitializationError( + f"{self.name} failed to initialize successfully. Please check " + f"the output logs for more information." + ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_zo_to_nacl.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_zo_to_nacl.py new file mode 100644 index 00000000..993f65e0 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_zo_to_nacl.py @@ -0,0 +1,146 @@ +################################################################################# +# WaterTAP Copyright (c) 2020-2024, The Regents of the University of California, +# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, +# National Renewable Energy Laboratory, and National Energy Technology +# Laboratory (subject to receipt of any required approvals from the U.S. Dept. +# of Energy). All rights reserved. +# +# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license +# information, respectively. These files are also available online at the URL +# "https://github.com/watertap-org/watertap/" +################################################################################# + +# Import Pyomo libraries +from pyomo.common.config import ConfigBlock, ConfigValue, In, Bool + +# Import IDAES cores +from idaes.core import declare_process_block_class, UnitModelBlockData +from idaes.models.unit_models.translator import TranslatorData +from idaes.core.util.config import ( + is_reaction_parameter_block, + is_physical_parameter_block, +) + +from idaes.core.util.exceptions import ConfigurationError +from idaes.core.util.model_statistics import degrees_of_freedom +from idaes.core.solvers import get_solver +import idaes.logger as idaeslog +import idaes.core.util.scaling as iscale + +from idaes.core.util.exceptions import InitializationError + +from pyomo.environ import ( + Param, + units as pyunits, + check_optimal_termination, + Set, +) + +__author__ = "Zhuoran Zhang" + + +# Set up logger +_log = idaeslog.getLogger(__name__) + + +@declare_process_block_class("Translator_ZO_to_NaCl") +class Translator_ZO_to_NaCl_Data(TranslatorData): + """ + Translator block for ZO to NaCl property packages + """ + + CONFIG = TranslatorData.CONFIG() + + def build(self): + + super().build() + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow water equation", + ) + def eq_flow_mass_water(blk, t): + return ( + blk.properties_out[t].flow_mass_phase_comp["Liq", "H2O"] + == blk.properties_in[t].flow_mass_comp["H2O"] + ) + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow TDS equation", + ) + def eq_flow_mass_tds(blk, t): + return ( + blk.properties_out[t].flow_mass_phase_comp["Liq", "NaCl"] + == blk.properties_in[t].flow_mass_comp["tds"] + ) + + def initialize_build( + self, + state_args_in=None, + state_args_out=None, + outlvl=idaeslog.NOTSET, + solver=None, + optarg=None, + ): + """ + This method calls the initialization method of the state blocks. + + Keyword Arguments: + state_args_in : a dict of arguments to be passed to the inlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + state_args_out : a dict of arguments to be passed to the outlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + outlvl : sets output level of initialization routine + optarg : solver options dictionary object (default=None, use + default solver options) + solver : str indicating which solver to use during + initialization (default = None, use default solver) + + Returns: + None + """ + init_log = idaeslog.getInitLogger(self.name, outlvl, tag="unit") + + # Create solver + opt = get_solver(solver, optarg) + + # --------------------------------------------------------------------- + # Initialize state block + flags = self.properties_in.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_in, + hold_state=True, + ) + + self.properties_out.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_out, + ) + + if degrees_of_freedom(self) != 0: + raise Exception( + f"{self.name} degrees of freedom were not 0 at the beginning " + f"of initialization. DoF = {degrees_of_freedom(self)}" + ) + + with idaeslog.solver_log(init_log, idaeslog.DEBUG) as slc: + res = opt.solve(self, tee=slc.tee) + + self.properties_in.release_state(flags=flags, outlvl=outlvl) + + init_log.info(f"Initialization Complete: {idaeslog.condition(res)}") + + if not check_optimal_termination(res): + raise InitializationError( + f"{self.name} failed to initialize successfully. Please check " + f"the output logs for more information." + ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_zo_to_sw.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_zo_to_sw.py new file mode 100644 index 00000000..bd3e29a8 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/translator_zo_to_sw.py @@ -0,0 +1,146 @@ +################################################################################# +# WaterTAP Copyright (c) 2020-2024, The Regents of the University of California, +# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, +# National Renewable Energy Laboratory, and National Energy Technology +# Laboratory (subject to receipt of any required approvals from the U.S. Dept. +# of Energy). All rights reserved. +# +# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license +# information, respectively. These files are also available online at the URL +# "https://github.com/watertap-org/watertap/" +################################################################################# + +# Import Pyomo libraries +from pyomo.common.config import ConfigBlock, ConfigValue, In, Bool + +# Import IDAES cores +from idaes.core import declare_process_block_class, UnitModelBlockData +from idaes.models.unit_models.translator import TranslatorData +from idaes.core.util.config import ( + is_reaction_parameter_block, + is_physical_parameter_block, +) + +from idaes.core.util.exceptions import ConfigurationError +from idaes.core.util.model_statistics import degrees_of_freedom +from idaes.core.solvers import get_solver +import idaes.logger as idaeslog +import idaes.core.util.scaling as iscale + +from idaes.core.util.exceptions import InitializationError + +from pyomo.environ import ( + Param, + units as pyunits, + check_optimal_termination, + Set, +) + +__author__ = "Zachary Binger" + + +# Set up logger +_log = idaeslog.getLogger(__name__) + + +@declare_process_block_class("Translator_ZO_to_SW") +class Translator_ZO_to_SW_Data(TranslatorData): + """ + Translator block for ZO to Seawater property packages + """ + + CONFIG = TranslatorData.CONFIG() + + def build(self): + + super().build() + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow water equation", + ) + def eq_flow_mass_water(blk, t): + return ( + blk.properties_out[t].flow_mass_phase_comp["Liq", "H2O"] + == blk.properties_in[t].flow_mass_comp["H2O"] + ) + + @self.Constraint( + self.flowsheet().time, + doc="Equality mass flow TDS equation", + ) + def eq_flow_mass_tds(blk, t): + return ( + blk.properties_out[t].flow_mass_phase_comp["Liq", "TDS"] + == blk.properties_in[t].flow_mass_comp["tds"] + ) + + def initialize_build( + self, + state_args_in=None, + state_args_out=None, + outlvl=idaeslog.NOTSET, + solver=None, + optarg=None, + ): + """ + This method calls the initialization method of the state blocks. + + Keyword Arguments: + state_args_in : a dict of arguments to be passed to the inlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + state_args_out : a dict of arguments to be passed to the outlet + property package (to provide an initial state for + initialization (see documentation of the specific + property package) (default = None). + outlvl : sets output level of initialization routine + optarg : solver options dictionary object (default=None, use + default solver options) + solver : str indicating which solver to use during + initialization (default = None, use default solver) + + Returns: + None + """ + init_log = idaeslog.getInitLogger(self.name, outlvl, tag="unit") + + # Create solver + opt = get_solver(solver, optarg) + + # --------------------------------------------------------------------- + # Initialize state block + flags = self.properties_in.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_in, + hold_state=True, + ) + + self.properties_out.initialize( + outlvl=outlvl, + optarg=optarg, + solver=solver, + state_args=state_args_out, + ) + + if degrees_of_freedom(self) != 0: + raise Exception( + f"{self.name} degrees of freedom were not 0 at the beginning " + f"of initialization. DoF = {degrees_of_freedom(self)}" + ) + + with idaeslog.solver_log(init_log, idaeslog.DEBUG) as slc: + res = opt.solve(self, tee=slc.tee) + + self.properties_in.release_state(flags=flags, outlvl=outlvl) + + init_log.info(f"Initialization Complete: {idaeslog.condition(res)}") + + if not check_optimal_termination(res): + raise InitializationError( + f"{self.name} failed to initialize successfully. Please check " + f"the output logs for more information." + ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/data/carlsbad_NM_weather_tmy-2023-full.csv b/src/watertap_contrib/reflo/analysis/case_studies/permian/data/carlsbad_NM_weather_tmy-2023-full.csv new file mode 100644 index 00000000..4292f520 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/data/carlsbad_NM_weather_tmy-2023-full.csv @@ -0,0 +1,8763 @@ +Source,Location ID,City,State,Country,Latitude,Longitude,Time Zone,Elevation,Local Time Zone,Clearsky DHI Units,Clearsky DNI Units,Clearsky GHI Units,Dew Point Units,DHI Units,DNI Units,GHI Units,Solar Zenith Angle Units,Temperature Units,Pressure Units,Relative Humidity Units,Precipitable Water Units,Wind Direction Units,Wind Speed Units,Cloud Type -15,Cloud Type 0,Cloud Type 1,Cloud Type 2,Cloud Type 3,Cloud Type 4,Cloud Type 5,Cloud Type 6,Cloud Type 7,Cloud Type 8,Cloud Type 9,Cloud Type 10,Cloud Type 11,Cloud Type 12,Fill Flag 0,Fill Flag 1,Fill Flag 2,Fill Flag 3,Fill Flag 4,Fill Flag 5,Surface Albedo Units,Version +NSRDB,504320,-,-,-,32.41,-104.22,0,953,-7,w/m2,w/m2,w/m2,c,w/m2,w/m2,w/m2,Degree,c,mbar,%,cm,Degrees,m/s,N/A,Clear,Probably Clear,Fog,Water,Super-Cooled Water,Mixed,Opaque Ice,Cirrus,Overlapping,Overshooting,Unknown,Dust,Smoke,N/A,Missing Image,Low Irradiance,Exceeds Clearsky,Missing CLoud Properties,Rayleigh Violation,N/A,4.0.1 +Year,Month,Day,Hour,Minute,Temperature,Alpha,AOD,Asymmetry,Clearsky DHI,Clearsky DNI,Clearsky GHI,Cloud Fill Flag,Cloud Type,Dew Point,DHI,DNI,Fill Flag,GHI,Ozone,Relative Humidity,Solar Zenith Angle,SSA,Surface Albedo,Pressure,Precipitable Water,Wind Direction,Wind Speed +2020,1,1,0,30,5.1000000000000005,1.26,0.025,0.61,0,0,0,0,0,-6.7,0,0,0,0,0.316,42.09,96.24000000000001,0.91,0.19,901,0.7000000000000001,160,1.3 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1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ] ], + "f_turb_tou_periods" : [ 1, 1, 1, 1, 1, 1, 1, 1, 1 ], + "is_tod_pc_target_also_pc_max" : 0, + "pb_fixed_par" : 0.0054999999999999997, + "bop_array" : [ 0, 1, 0, 0.48299999999999998, 0 ], + "aux_array" : [ 0.023, 1, 0.48299999999999998, 0.57099999999999995, 0 ], + "water_usage_per_wash" : 0.69999999999999996, + "washing_frequency" : 12, + "calc_design_pipe_vals" : 1, + "V_hdr_cold_max" : 3, + "V_hdr_cold_min" : 2, + "V_hdr_hot_max" : 3, + "V_hdr_hot_min" : 2, + "N_max_hdr_diams" : 10, + "L_rnr_pb" : 25, + "L_rnr_per_xpan" : 70, + "L_xpan_hdr" : 20, + "L_xpan_rnr" : 20, + "Min_rnr_xpans" : 1, + "northsouth_field_sep" : 20, + "N_hdr_per_xpan" : 2, + "offset_xpan_hdr" : 1, + "custom_sf_pipe_sizes" : 0, + "sf_rnr_diams" : [ [ -1 ] ], + "sf_rnr_wallthicks" : [ [ -1 ] ], + "sf_rnr_lengths" : [ [ -1 ] ], + "sf_hdr_diams" : [ [ -1 ] ], + "sf_hdr_wallthicks" : [ [ -1 ] ], + "sf_hdr_lengths" : [ [ -1 ] ], + "has_hot_tank_bypass" : 0, + "T_tank_hot_inlet_min" : 400, + "tes_pump_coef" : 0.14999999999999999, + "V_tes_des" : 1.8500000000000001, + "custom_tes_p_loss" : 0, + "k_tes_loss_coeffs" : [ [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ] ], + "custom_tes_pipe_sizes" : 0, + "tes_diams" : [ [ -1 ] ], + "tes_wallthicks" : [ [ -1 ] ], + "use_solar_mult_or_aperture_area" : 0, + "specified_solar_multiple" : 2.3, + "specified_total_aperture" : 20000, + "non_solar_field_land_area_multiplier" : 1.1000000000000001, + "trough_loop_control" : [ 4, 1, 1, 4, 1, 1, 3, 1, 1, 2, 1, 1, 1 ], + "csp_dtr_cost_site_improvements_cost_per_m2" : 16, + "csp_dtr_cost_solar_field_cost_per_m2" : 297, + "csp_dtr_cost_htf_system_cost_per_m2" : 60, + "csp_dtr_cost_storage_cost_per_kwht" : 62, + "csp_dtr_cost_heat_sink_cost_per_kwe" : 120, + "csp_dtr_cost_bop_per_kwe" : 90, + "csp_dtr_cost_contingency_percent" : 7, + "csp_dtr_cost_epc_per_acre" : 0, + "csp_dtr_cost_epc_percent" : 11, + "csp_dtr_cost_epc_per_watt" : 0, + "csp_dtr_cost_epc_fixed" : 0, + "csp_dtr_cost_plm_per_acre" : 10000, + "csp_dtr_cost_plm_percent" : 0, + "csp_dtr_cost_plm_per_watt" : 0, + "csp_dtr_cost_plm_fixed" : 0, + "csp_dtr_cost_sales_tax_percent" : 80, + "sales_tax_rate" : 5, + "adjust_constant" : 4, + "adjust_en_timeindex" : 0, + "adjust_en_periods" : 0, + "adjust_timeindex" : [ 0 ], + "adjust_periods" : [ [ 0, 0, 0 ] ] +} diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/data/run_pysam_permian_trough.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/data/run_pysam_permian_trough.py new file mode 100644 index 00000000..e2c676de --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/data/run_pysam_permian_trough.py @@ -0,0 +1,198 @@ +################################################################################# +# WaterTAP Copyright (c) 2020-2023, The Regents of the University of California, +# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, +# National Renewable Energy Laboratory, and National Energy Technology +# Laboratory (subject to receipt of any required approvals from the U.S. Dept. +# of Energy). All rights reserved. +# +# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license +# information, respectively. These files are also available online at the URL +# "https://github.com/watertap-org/watertap/" +################################################################################# + +import json +from os.path import join, dirname +from math import floor, ceil, isnan +import numpy as np +import pandas as pd +import time +import multiprocessing +from itertools import product +import matplotlib.pyplot as plt +import PySAM.TroughPhysicalIph as iph +import os + +# TODO: +# Annual energy for year 1 is a little different than that calculated in SAM + + +def read_module_datafile(file_name): + with open(file_name, "r") as file: + data = json.load(file) + return data + + +def load_config(modules, file_names=None, module_data=None): + """ + Loads parameter values into PySAM modules, either from files or supplied dicts + + :param modules: List of PySAM modules + :param file_names: List of JSON file paths containing parameter values for respective modules + :param module_data: List of dictionaries containing parameter values for respective modules + + :returns: no return value + """ + for i in range(len(modules)): + if file_names is not None: + assert len(file_names) == len(modules) + data = read_module_datafile(file_names[i]) + elif module_data is not None: + assert len(module_data) == len(modules) + data = module_data[i] + else: + raise Exception("Either file_names or module_data must be assigned.") + + missing_values = [] # for debugging + for k, v in data.items(): + if k != "number_inputs": + try: + modules[i].value(k, v) + except: + missing_values.append(k) + pass + + +def setup_model( + model_name, + weather_file=None, + weather_data=None, + config_files=None, + config_data=None, +): + tech_model = iph.new() + modules = [tech_model] + + load_config(modules, config_files, config_data) + if weather_file is not None: + tech_model.Weather.file_name = weather_file + elif weather_data is not None: + tech_model.Weather.solar_resource_data = weather_data + else: + raise Exception("Either weather_file or weather_data must be specified.") + + return { + "tech_model": tech_model, + } + + +def run_model(modules, heat_load=None, hours_storage=None): + tech_model = modules["tech_model"] + + if heat_load is not None: + tech_model.value("q_pb_design", heat_load) + if hours_storage is not None: + tech_model.value("tshours", hours_storage) + tech_model.execute() + + # NOTE: freeze_protection_field can sometimes be nan (when it should be 0) and this causes other nan's + # Thus, freeze_protection, annual_energy and capacity_factor must be calculated manually + # annual_energy = tech_model.Outputs.annual_energy # [kWht] net, does not include that used for freeze protection + # freeze_protection = tech_model.Outputs.annual_thermal_consumption # [kWht] + # capacity_factor = tech_model.Outputs.capacity_factor # [%] + + freeze_protection_field = tech_model.Outputs.annual_field_freeze_protection + freeze_protection_field = ( + 0 if isnan(freeze_protection_field) else freeze_protection_field + ) # occasionally seen to be nan + freeze_protection_tes = tech_model.Outputs.annual_tes_freeze_protection + freeze_protection_tes = 0 if isnan(freeze_protection_tes) else freeze_protection_tes + freeze_protection = freeze_protection_field + freeze_protection_tes + annual_energy = ( + tech_model.Outputs.annual_energy - freeze_protection + ) # [kWht] net, does not include that used for freeze protection + capacity_factor = ( + annual_energy / (tech_model.value("q_pb_design") * 1e3 * 8760) * 100 + ) # [%] + + electrical_load = tech_model.Outputs.annual_electricity_consumption # [kWhe] + solar_multiplier = tech_model.Outputs.solar_mult + total_aperture_reflective_area = tech_model.Outputs.total_aperture # [m2] + nloops = tech_model.Outputs.nLoops + + return { + "annual_energy": annual_energy, # [kWh] annual net thermal energy in year 1 + "freeze_protection": freeze_protection, # [kWht] + "capacity_factor": capacity_factor, # [%] capacity factor + "electrical_load": electrical_load, # [kWhe] + "solar_multiplier": solar_multiplier, + "total_aperture_area": total_aperture_reflective_area, + "number_loops": nloops, + } + + +def setup_and_run( + model_name, weather_file, config_data, heat_load +): # , hours_storage): + modules = setup_model( + model_name, weather_file=weather_file, config_data=config_data + ) + result = run_model(modules, heat_load) # S, hours_storage) + return result + + +######################################################################################################### +if __name__ == "__main__": + # Model name is not relevant in WaterTAP-REFLO package because cost is calculated using REFLO costing packages + model_name = "TroughPhysicalIph_PhysicalTroughIPHLCOHCalculator" + __location__ = os.path.realpath( + os.path.join(os.getcwd(), os.path.dirname(__file__)) + ) + + config_files = [ + os.path.join(__location__, "cst/trough_physical_iph-reflo.json"), + ] + weather_file = os.path.join(__location__, "carlsbad_NM_weather_tmy-2023-full.csv") + dataset_filename = os.path.join( + __location__, + "cst/trough_permian_heat_load_1_100_hours_storage_24_T_loop_out_300.pkl", + ) # output dataset for surrogate training + + config_data = [read_module_datafile(config_file) for config_file in config_files] + del config_data[0]["file_name"] # remove weather filename + + # Run parametrics via multiprocessing + data = [] + heat_loads = np.linspace(1, 100, 200) # [MWt] + # hours_storages = np.linspace(20, 24, 5) # [hr] + arguments = list(product(heat_loads)) # , hours_storages)) + df = pd.DataFrame(arguments, columns=["heat_load"]) # , "hours_storage"]) + + time_start = time.process_time() + with multiprocessing.Pool(processes=6) as pool: + args = [(model_name, weather_file, config_data, *args) for args in arguments] + results = pool.starmap(setup_and_run, args) + time_stop = time.process_time() + print("Multiprocessing time:", time_stop - time_start, "\n") + + df_results = pd.DataFrame(results) + + df = pd.concat( + [ + df, + df_results[ + [ + "annual_energy", + "freeze_protection", + "capacity_factor", + "electrical_load", + "solar_multiplier", + "total_aperture_area", + "number_loops", + ] + ], + ], + axis=1, + ) + df.to_pickle(dataset_filename) + + pass diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_SOA-old.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_SOA-old.py new file mode 100644 index 00000000..9a67aeb7 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_SOA-old.py @@ -0,0 +1,590 @@ +import pathlib +from pyomo.environ import ( + ConcreteModel, + value, + TransformationFactory, + Param, + Var, + Constraint, + Set, + Expression, + Objective, + NonNegativeReals, + Block, + RangeSet, + check_optimal_termination, + assert_optimal_termination, + units as pyunits, +) +from pyomo.network import Arc, SequentialDecomposition +from pyomo.util.check_units import assert_units_consistent +from pyomo.util.calc_var_value import calculate_variable_from_constraint as cvc + +from idaes.core import FlowsheetBlock, UnitModelCostingBlock +from idaes.core.util.initialization import propagate_state as _prop_state +import idaes.core.util.scaling as iscale +from idaes.core import MaterialFlowBasis +from idaes.core.util.scaling import ( + constraint_scaling_transform, + calculate_scaling_factors, + set_scaling_factor, +) +import idaes.logger as idaeslogger +from idaes.core.util.exceptions import InitializationError +from idaes.models.unit_models import ( + Product, + Feed, + StateJunction, + Separator, + Mixer, + MixingType, + MomentumMixingType, +) +from idaes.core.util.model_statistics import * +from idaes.core.util.initialization import propagate_state + +from watertap.core.solvers import get_solver +from watertap.core import Database +from watertap_contrib.reflo.core.wt_reflo_database import REFLODatabase +from watertap.core.zero_order_properties import WaterParameterBlock as ZO +from watertap.property_models.multicomp_aq_sol_prop_pack import ( + MCASParameterBlock as MCAS, +) + +# from watertap.costing.zero_order_costing import ZeroOrderCosting +from watertap_contrib.reflo.kurby import * +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.core.util.initialization import * +from watertap.property_models.seawater_prop_pack import SeawaterParameterBlock +from watertap.property_models.water_prop_pack import ( + WaterParameterBlock as SteamParameterBlock, +) +from watertap_contrib.reflo.costing import ( + TreatmentCosting, + EnergyCosting, + REFLOCosting, +) +from watertap_contrib.reflo.analysis.case_studies.KBHDP.utils import * +from watertap_contrib.reflo.analysis.case_studies.permian import * +from watertap_contrib.reflo.unit_models.deep_well_injection import DeepWellInjection + +reflo_dir = pathlib.Path(__file__).resolve().parents[3] +case_study_yaml = f"{reflo_dir}/data/technoeconomic/permian_case_study.yaml" +rho = 1125 * pyunits.kg / pyunits.m**3 +rho_water = 995 * pyunits.kg / pyunits.m**3 + +solver = get_solver() + +__all__ = [ + "build_permian_SOA", + "set_operating_conditions_SOA", + "add_treatment_costing", + "set_SOA_scaling", + "init_SOA_system", + "run_permian_SOA", +] + + +def build_permian_SOA(mvc_recovery=0.5): + """ + Build Permian state-of-the-art flowsheet + """ + + m = ConcreteModel() + m.mvc_recovery = mvc_recovery + m.fs = FlowsheetBlock(dynamic=False) + m.db = REFLODatabase() + + m.fs.properties = ZO(solute_list=["tds"]) + + m.fs.properties_feed = SeawaterParameterBlock() + m.fs.properties_vapor = SteamParameterBlock() + + # Begin building Treatment Block + m.fs.treatment = treat = Block() + + treat.feed = Feed(property_package=m.fs.properties) + treat.product = Product(property_package=m.fs.properties_feed) + + # Add translator blocks + treat.zo_to_sw_feed = Translator_ZO_to_SW( + inlet_property_package=m.fs.properties, + outlet_property_package=m.fs.properties_feed, + ) + + treat.zo_to_sw_disposal = Translator_ZO_to_SW( + inlet_property_package=m.fs.properties, + outlet_property_package=m.fs.properties_feed, + ) + + # treat.sw_to_zo = Translator_SW_to_ZO( + # inlet_property_package=m.fs.properties_feed, + # outlet_property_package=m.fs.properties, + # ) + + treat.disposal_ZO_mixer = Mixer( + property_package=m.fs.properties, + num_inlets=2, + inlet_list=["ec_disposal", "cart_filt_disposal"], + energy_mixing_type=MixingType.none, + momentum_mixing_type=MomentumMixingType.none, + ) + + treat.disposal_SW_mixer = Mixer( + property_package=m.fs.properties_feed, + num_inlets=2, + inlet_list=["zo_mixer", "mvc_disposal"], + energy_mixing_type=MixingType.none, + momentum_mixing_type=MomentumMixingType.equality, + ) + + treat.chem_addition = FlowsheetBlock(dynamic=False) + build_chem_addition(m, treat.chem_addition) + + treat.EC = FlowsheetBlock(dynamic=False) + build_ec(m, treat.EC) + + treat.cart_filt = FlowsheetBlock(dynamic=False) + build_cartridge_filtration(m, treat.cart_filt) + + treat.MVC = FlowsheetBlock(dynamic=False) + build_mvc(m, treat.MVC) + + treat.DWI = FlowsheetBlock(dynamic=False) + build_dwi(m, treat.DWI, m.fs.properties_feed) + + # BUILD PRODUCT STREAM + # feed > chem_addition > EC > cart_filt > ZO_to_SW_translator > MVC > product + treat.feed_to_chem_addition = Arc( + source=treat.feed.outlet, destination=treat.chem_addition.feed.inlet + ) + + treat.chem_addition_to_ec = Arc( + source=treat.chem_addition.product.outlet, destination=treat.EC.feed.inlet + ) + + treat.ec_to_cart_filt = Arc( + source=treat.EC.product.outlet, destination=treat.cart_filt.feed.inlet + ) + + # from ZO to SW - feed + treat.cart_filt_to_translator = Arc( + source=treat.cart_filt.product.outlet, destination=treat.zo_to_sw_feed.inlet + ) + + treat.cart_filt_translated_to_mvc = Arc( + source=treat.zo_to_sw_feed.outlet, destination=treat.MVC.feed.inlet + ) + + treat.mvc_to_product = Arc( + source=treat.MVC.product.outlet, destination=treat.product.inlet + ) + + # BUILD DISPOSAL STREAM + # EC > ZO_mixer > ZO_to_SW_translator > disposal_mixer > disposal_mixer > DWI + # cart_filt > ZO_mixer + # MVC > disposal_mixer + + treat.ec_to_disposal_mix = Arc( + source=treat.EC.disposal.outlet, destination=treat.disposal_ZO_mixer.ec_disposal + ) + + treat.cart_filt_to_disposal_mix = Arc( + source=treat.cart_filt.disposal.outlet, + destination=treat.disposal_ZO_mixer.cart_filt_disposal, + ) + + treat.disposal_ZO_mix_to_translator = Arc( + source=treat.disposal_ZO_mixer.outlet, destination=treat.zo_to_sw_disposal.inlet + ) + + treat.disposal_ZO_mix_translated_to_disposal_SW_mixer = Arc( + source=treat.zo_to_sw_disposal.outlet, + destination=treat.disposal_SW_mixer.zo_mixer, + ) + + treat.mvc_disposal_to_translator = Arc( + source=treat.MVC.disposal.outlet, + destination=treat.disposal_SW_mixer.mvc_disposal, + ) + + treat.disposal_SW_mixer_to_dwi = Arc( + source=treat.disposal_SW_mixer.outlet, destination=treat.DWI.feed.inlet + ) + + TransformationFactory("network.expand_arcs").apply_to(m) + + treat.recovery = Var( + initialize=0.5, + bounds=(0, 1.0001), + units=pyunits.dimensionless, + doc="Overall system recovery", + ) + + # m.fs.treatment.eq_recovery = Constraint( + # expr=m.fs.treatment.recovery * m.fs.treatment.feed.properties[0].flow_vol + # == m.fs.treatment.product.properties[0].flow_vol_phase["Liq"] + # ) + + add_treatment_costing(m) + + return m + + +def set_operating_conditions_SOA(m, Qin=5, tds=130, **kwargs): + + global flow_mass_water, flow_mass_tds, flow_in + m.fs.properties.dens_mass_default = rho + + Qin = Qin * pyunits.Mgallons / pyunits.day + m.flow_in = flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + flow_mass_water = pyunits.convert(Qin * rho_water, to_units=pyunits.kg / pyunits.s) + flow_mass_tds = pyunits.convert( + Qin * tds * pyunits.g / pyunits.liter, to_units=pyunits.kg / pyunits.s + ) + + m.fs.treatment.feed.properties[0].flow_mass_comp["H2O"].fix(flow_mass_water) + m.fs.treatment.feed.properties[0].flow_mass_comp["tds"].fix(flow_mass_tds) + m.fs.treatment.feed.properties[0].conc_mass_comp[...] + + set_chem_addition_op_conditions(m, m.fs.treatment.chem_addition, **kwargs) + set_ec_operating_conditions(m, m.fs.treatment.EC, **kwargs) + set_cart_filt_op_conditions(m, m.fs.treatment.cart_filt, **kwargs) + set_mvc_operating_conditions(m, m.fs.treatment.MVC, **kwargs) + + +def add_treatment_costing(m): + + m.fs.treatment.costing = TreatmentCosting(case_study_definition=case_study_yaml) + add_chem_addition_costing( + m, m.fs.treatment.chem_addition, flowsheet_costing_block=m.fs.treatment.costing + ) + add_ec_costing(m, m.fs.treatment.EC, flowsheet_costing_block=m.fs.treatment.costing) + add_cartridge_filtration_costing( + m, m.fs.treatment.cart_filt, flowsheet_costing_block=m.fs.treatment.costing + ) + add_mvc_costing( + m, m.fs.treatment.MVC, flowsheet_costing_block=m.fs.treatment.costing + ) + add_dwi_costing( + m, m.fs.treatment.DWI, flowsheet_costing_block=m.fs.treatment.costing + ) + + m.fs.treatment.costing.cost_process() + + +def set_SOA_scaling(m, **kwargs): + + set_permian_pretreatment_scaling(m, calculate_m_scaling_factors=False) + + set_mvc_scaling(m, m.fs.treatment.MVC, calc_blk_scaling_factors=True) + + # SW DISPOSAL MIXER + # MVC disposal inlet + set_scaling_factor( + m.fs.treatment.disposal_SW_mixer.mvc_disposal_state[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 1e-2, + ) + set_scaling_factor( + m.fs.treatment.disposal_SW_mixer.mvc_disposal_state[0].flow_mass_phase_comp[ + "Liq", "TDS" + ], + 0.1, + ) + + calculate_scaling_factors(m) + + +def init_SOA_system(m, mvc_inlet_temp=50, **kwargs): + + treat = m.fs.treatment + + treat.feed.initialize() + propagate_state(treat.feed_to_chem_addition) + + init_chem_addition(m, treat.chem_addition) + propagate_state(treat.chem_addition_to_ec) + + init_ec(m, treat.EC) + propagate_state(treat.ec_to_cart_filt) + propagate_state(treat.ec_to_disposal_mix) + + init_cart_filt(m, treat.cart_filt) + propagate_state(treat.cart_filt_to_translator) + propagate_state(treat.cart_filt_to_disposal_mix) + + treat.disposal_ZO_mixer.initialize() + propagate_state(treat.disposal_ZO_mix_to_translator) + + treat.zo_to_sw_disposal.outlet.temperature[0].fix(293.15) + treat.zo_to_sw_disposal.outlet.pressure[0].fix(101325) + treat.zo_to_sw_disposal.initialize() + + treat.zo_to_sw_feed.properties_out[0].temperature.fix(273.15 + mvc_inlet_temp) + # treat.zo_to_sw_feed.properties_out[0].temperature.set_value(273.15 + mvc_inlet_temp) # K + treat.zo_to_sw_feed.properties_out[0].pressure.fix(101325) + treat.zo_to_sw_feed.initialize() + + propagate_state(treat.cart_filt_translated_to_mvc) + init_mvc(m, treat.MVC, feed_props=treat.zo_to_sw_feed.properties_out[0]) + propagate_state(treat.mvc_to_product) + propagate_state(treat.mvc_disposal_to_translator) + + propagate_state(treat.disposal_ZO_mix_translated_to_disposal_SW_mixer) + treat.disposal_SW_mixer.initialize() + treat.disposal_SW_mixer.mixed_state[0].pressure.fix(101325) + # treat.disposal_SW_mixer.mixed_state[0].temperature.fix() + + propagate_state(treat.disposal_SW_mixer_to_dwi) + + init_dwi(m, treat.DWI) + + treat.product.initialize() + treat.costing.initialize() + assert False + + +def run_permian_SOA(recovery=0.5, **kwargs): + """ + Run Permian state-of-the-art case study + """ + + m = build_permian_SOA() + treat = m.fs.treatment + mvc = treat.MVC + mvc.feed.properties[0].conc_mass_phase_comp + + set_operating_conditions_SOA(m, **kwargs) + set_SOA_scaling(m) + + # treat.feed.properties[0].flow_vol + # treat.feed.properties[0].conc_mass_comp + treat.chem_addition.unit.chemical_flow_vol[0] = 1e-5 + # treat.feed.properties[0].conc_mass_comp.display() + # assert False + + # m.fs.treatment.costing.initialize() + # check_jac(m) + # assert False + + init_SOA_system(m) + + # check_jac(m) + # mvc.evaporator.display() + # assert False + # check_vars(m.fs.treatment.MVC.hx_brine, skip_list=["properties_feed", "properties_vapor", "_ref"]) + # assert False + + flow_vol = treat.product.properties[0].flow_vol_phase["Liq"] + treat.product.properties[0].flow_vol_phase["Liq"] = value(recovery * m.flow_in) + + treat.costing.add_LCOW(flow_vol) + treat.costing.add_specific_energy_consumption(flow_vol, name="SEC") + treat.costing.initialize() + # results = solver.solve(m) + # assert_optimal_termination(results) + + # First, minimize external heating + # mvc.external_heating_obj = Objective(expr=mvc.external_heating) + try: + print(f"DOF = {degrees_of_freedom(m)}") + results = solver.solve(mvc, tee=True) + # results = solver.solve(m, tee=True) + assert_optimal_termination(results) + except: + print_infeasible_constraints(m) + print_variables_close_to_bounds(m) + print("SOLVE FAILED") + return m + print(f"DOF = {degrees_of_freedom(m)}") + + # Next, minimize LCOW for MVC design + # mvc.del_component(mvc.external_heating_obj) + # treat.LCOW_obj = Objective(expr=treat.costing.LCOW) + + # treat.costing.electricity_cost.fix(0.07) + + try: + mvc.evaporator.area.unfix() + results = solver.solve(m, tee=True) + assert_optimal_termination(results) + except: + print_infeasible_constraints(m) + print_variables_close_to_bounds(m) + print("SOLVE FAILED") + return m + return m + # Optimize design + mvc.external_heating.fix(0) # Remove external heating + mvc.evaporator.area.unfix() + mvc.evaporator.outlet_brine.temperature[0].unfix() + mvc.compressor.pressure_ratio.unfix() + mvc.hx_distillate.area.unfix() + mvc.hx_brine.area.unfix() + # treat.zo_to_sw_feed.properties_out[0].temperature.unfix() + + # Add flowsheet level recovery + treat.eq_recovery = Constraint( + expr=treat.recovery * treat.feed.properties[0].flow_vol + == treat.product.properties[0].flow_vol_phase["Liq"] + ) + treat.recovery.fix(recovery) + + # Unfix MVC recovery + mvc.recovery.unfix() + + try: + results = solver.solve(m) + assert_optimal_termination(results) + except: + print_infeasible_constraints(m) + print_variables_close_to_bounds(m) + print("SOLVE FAILED") + return m + print(f"DOF = {degrees_of_freedom(m)}") + + mvc.evaporator.area.fix() + # mvc.evaporator.outlet_brine.temperature[0].fix() + mvc.compressor.pressure_ratio.fix() + mvc.hx_distillate.area.fix() + # mvc.hx_brine.area.fix() + mvc.recovery.fix() # effectively fixes split_fraction on separator + + mvc.compressor.control_volume.properties_out[0.0].temperature.setub(500) + + # try: + print(f"DOF = {degrees_of_freedom(m)}") + # mvc.feed.properties[0].conc_mass_phase_comp + results = solver.solve(m, tee=False) + assert_optimal_termination(results) + mvc.hx_brine.area.fix() + print(f"DOF = {degrees_of_freedom(m)}") + results = solver.solve(m, tee=False) + assert_optimal_termination(results) + + return m + + +# def run_permian_SOA(recovery=0.5): +# """ +# Run Permian state-of-the-art case study +# """ + +# m = build_permian_SOA() +# treat = m.fs.treatment +# mvc = treat.MVC + +# set_operating_conditions_SOA(m) +# set_SOA_scaling(m) + +# treat.feed.properties[0].flow_vol + +# init_SOA_system(m) + +# flow_vol = treat.product.properties[0].flow_vol_phase["Liq"] +# treat.product.properties[0].flow_vol_phase["Liq"] = value(recovery * flow_in) + +# treat.costing.add_LCOW(flow_vol) +# treat.costing.add_specific_energy_consumption(flow_vol, name="SEC") +# treat.costing.initialize() +# results = solver.solve(m) +# assert_optimal_termination(results) +# # mvc.external_heating.display() +# # assert False + +# # First, minimize external heating +# # mvc.external_heating_obj = Objective(expr=mvc.external_heating) + +# # try: +# # results = solver.solve(m) +# # assert_optimal_termination(results) +# # except: +# # print_infeasible_constraints(m) +# # print_variables_close_to_bounds(m) +# # print("SOLVE FAILED") +# print(f"DOF = {degrees_of_freedom(m)}") +# # return m +# # assert False + +# # Next, minimize LCOW for MVC design +# # mvc.del_component(mvc.external_heating_obj) +# treat.LCOW_obj = Objective(expr=treat.costing.LCOW) + +# treat.costing.electricity_cost.fix(0.07) + +# try: +# results = solver.solve(m) +# assert_optimal_termination(results) +# except: +# print_infeasible_constraints(m) +# print_variables_close_to_bounds(m) +# print("SOLVE FAILED") +# return m + +# # Optimize design +# mvc.external_heating.fix(0) # Remove external heating +# mvc.evaporator.area.unfix() +# mvc.evaporator.outlet_brine.temperature[0].unfix() +# mvc.compressor.pressure_ratio.unfix() +# mvc.hx_distillate.area.unfix() +# mvc.hx_brine.area.unfix() +# # treat.zo_to_sw_feed.properties_out[0].temperature.unfix() + +# # Add flowsheet level recovery +# treat.eq_recovery = Constraint( +# expr=treat.recovery * treat.feed.properties[0].flow_vol +# == treat.product.properties[0].flow_vol_phase["Liq"] +# ) +# treat.recovery.fix(recovery) + +# # Unfix MVC recovery +# mvc.recovery.unfix() + +# results = solver.solve(m) +# assert_optimal_termination(results) +# print(f"DOF = {degrees_of_freedom(m)}") + +# mvc.evaporator.area.fix() +# # mvc.evaporator.outlet_brine.temperature[0].fix() +# mvc.compressor.pressure_ratio.fix() +# mvc.hx_distillate.area.fix() +# mvc.hx_brine.area.fix() +# mvc.recovery.fix() # effectively fixes split_fraction on separator + +# # TODO: This results in 1 DOF +# # Possible additional DOF are +# # EC conductivity +# # temperature/pressure on dispoal mixer +# # mvc.pump_brine.control_volume.deltaP[0].fix() +# # treat.zo_to_sw_feed.properties_out[0].temperature.fix() +# # treat.EC.unit.conductivity.fix() + +# mvc.compressor.control_volume.properties_out[0.0].temperature.setub(500) + +# # try: +# print(f"DOF = {degrees_of_freedom(m)}") +# mvc.feed.properties[0].conc_mass_phase_comp +# results = solver.solve(m) +# assert_optimal_termination(results) +# # print(f"termination {results.solver.termination_condition}") +# # print(f"DOF = {degrees_of_freedom(m)}") +# # except: +# # print_infeasible_constraints(m) +# # print_variables_close_to_bounds(m) +# # print("SOLVE FAILED") + +# return m + + +if __name__ == "__main__": + + m = run_permian_SOA() + # treat = m.fs.treatment + # mvc = treat.MVC + # mvc.evaporator.outlet_brine.display() + # # treat.disposal_SW_mixer.display() + # # print(m.fs.treatment.costing.LCOW(), m.fs.treatment.EC.unit.conductivity()) + # # treat.feed.conc_mass_comp.display() + # mvc.feed.display() diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_SOA.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_SOA.py new file mode 100644 index 00000000..78014409 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_SOA.py @@ -0,0 +1,396 @@ +import pandas as pd +import numpy as np +import time +import pathlib +from pyomo.environ import ( + ConcreteModel, + value, + TransformationFactory, + Param, + Var, + Constraint, + Set, + Expression, + Objective, + NonNegativeReals, + Block, + RangeSet, + check_optimal_termination, + assert_optimal_termination, + units as pyunits, +) +from pyomo.network import Arc, SequentialDecomposition +from pyomo.util.check_units import assert_units_consistent +from pyomo.util.calc_var_value import calculate_variable_from_constraint as cvc + +from idaes.core import FlowsheetBlock, UnitModelCostingBlock +from idaes.core.util.initialization import propagate_state as _prop_state +import idaes.core.util.scaling as iscale +from idaes.core import MaterialFlowBasis +from idaes.core.util.scaling import ( + constraint_scaling_transform, + calculate_scaling_factors, + set_scaling_factor, +) +import idaes.logger as idaeslogger +from idaes.core.util.exceptions import InitializationError +from idaes.models.unit_models import ( + Product, + Feed, + StateJunction, + Separator, + Mixer, + MixingType, + MomentumMixingType, +) +from idaes.core.util.model_statistics import * +from idaes.core.util.initialization import propagate_state + +from watertap.core.solvers import get_solver +from watertap.core import Database +from watertap_contrib.reflo.core.wt_reflo_database import REFLODatabase +from watertap.core.zero_order_properties import WaterParameterBlock as ZO +from watertap.property_models.multicomp_aq_sol_prop_pack import ( + MCASParameterBlock as MCAS, +) + +# from watertap.costing.zero_order_costing import ZeroOrderCosting +# from watertap_contrib.reflo.kurby import * +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.core.util.initialization import * +from watertap.property_models.seawater_prop_pack import SeawaterParameterBlock +from watertap.property_models.water_prop_pack import ( + WaterParameterBlock as SteamParameterBlock, +) +from watertap_contrib.reflo.costing import ( + TreatmentCosting, + EnergyCosting, + REFLOCosting, +) +from watertap_contrib.reflo.analysis.case_studies.KBHDP.utils import * +from watertap_contrib.reflo.analysis.case_studies.permian import * +from watertap_contrib.reflo.unit_models.deep_well_injection import DeepWellInjection + +reflo_dir = pathlib.Path(__file__).resolve().parents[3] +case_study_yaml = f"{reflo_dir}/data/technoeconomic/permian_case_study.yaml" +rho = 1125 * pyunits.kg / pyunits.m**3 +rho_water = 995 * pyunits.kg / pyunits.m**3 + +solver = get_solver() + +__all__ = ["build_and_run_permian_SOA", "solve_permian_SOA"] + + +def build_and_run_permian_SOA( + pretreatment_recovery=0.98, recovery=0.5, Qin=5, tds=130, **kwargs +): + m_pre = build_and_run_permian_pretreatment(Qin=Qin, tds=tds, **kwargs) + + # results = solve_permian_SOA(m_pre) + # m.fs.treatment.product.display() + flow_to_mvc = Qin * value(m_pre.fs.treatment.EC.unit.recovery_frac_mass_H2O[0]) + flow_to_mvc = flow_to_mvc * value( + m_pre.fs.treatment.cart_filt.unit.recovery_frac_mass_H2O[0] + ) + tds_to_mvc = value( + pyunits.convert( + m_pre.fs.treatment.product.properties[0].conc_mass_phase_comp["Liq", "TDS"], + to_units=pyunits.gram / pyunits.liter, + ) + ) + # print(f"Flow to MVC: {flow_to_mvc} MGD") + # print(f"TDS to MVC: {tds_to_mvc} g/L") + + m_mvc = build_and_run_mvc( + recovery=recovery, Qin=Qin * pretreatment_recovery, tds=tds_to_mvc, **kwargs + ) + + m_mvc.fs.disposal.properties[0].flow_vol_phase + m_mvc.fs.disposal.properties[0].conc_mass_phase_comp + m_mvc.fs.disposal.initialize() + + flow_to_dwi = value( + pyunits.convert( + m_mvc.fs.disposal.properties[0].flow_vol_phase["Liq"], + to_units=pyunits.Mgallons / pyunits.day, + ) + ) + tds_to_dwi = value( + pyunits.convert( + m_mvc.fs.disposal.properties[0].conc_mass_phase_comp["Liq", "TDS"], + to_units=pyunits.gram / pyunits.liter, + ) + ) + # m_mvc.fs.disposal.properties[0].display() + # assert False + m_dwi = build_and_run_dwi(Qin=flow_to_dwi, tds=tds_to_dwi, **kwargs) + # results = solve_permian_SOA(m_dwi) + + # print(f"Flow to pretreatment: {Qin} MGD") + # print(f"TDS to pretreatment: {tds} g/L") + + # print(f"Flow to MVC: {flow_to_mvc} MGD") + # print(f"TDS to MVC: {tds_to_mvc} g/L") + + # print(f"Flow to DWI: {flow_to_dwi} MGD") + # print(f"TDS to DWI: {tds_to_dwi} g/L") + + product_flow = value( + pyunits.convert( + m_mvc.fs.product.properties[0].flow_vol_phase["Liq"], + to_units=pyunits.m**3 / pyunits.year, + ) + ) + product_flow_mgd = value( + pyunits.convert( + m_mvc.fs.product.properties[0].flow_vol_phase["Liq"], + to_units=pyunits.Mgallons / pyunits.day, + ) + ) + system_recovery = product_flow_mgd / Qin + flow_to_product = product_flow_mgd + + m = ConcreteModel() + m.fs = FlowsheetBlock(dynamic=False) + m.fs.costing = Block() + m.fs.optimal_solve_system = Var(initialize=1) + m.fs.optimal_solve_system.fix(1) + + m.fs.recovery = Var(initialize=recovery) + m.fs.recovery.fix() + m.fs.system_recovery = Var(initialize=system_recovery) + m.fs.system_recovery.fix() + m.fs.flow_mgd = Var(initialize=Qin) + m.fs.flow_mgd.fix() + m.fs.flow_to_mvc = Var(initialize=flow_to_mvc) + m.fs.flow_to_mvc.fix() + m.fs.flow_to_dwi = Var(initialize=flow_to_dwi) + m.fs.flow_to_dwi.fix() + m.fs.flow_to_product = Var(initialize=flow_to_product) + m.fs.flow_to_product.fix() + + m.fs.tds = Var(initialize=tds) + m.fs.tds.fix() + m.fs.tds_to_mvc = Var(initialize=tds_to_mvc) + m.fs.tds_to_mvc.fix() + m.fs.tds_to_dwi = Var(initialize=tds_to_dwi) + m.fs.tds_to_dwi.fix() + + m.fs.costing.total_capital_cost = Var( + initialize=1e6, bounds=(0, None), units=pyunits.USD_2023 + ) + m.fs.costing.pretreatment_capital_cost = Var( + initialize=m_pre.fs.treatment.costing.total_capital_cost(), bounds=(0, None) + ) + m.fs.costing.MVC_capital_cost = Var( + initialize=m_mvc.fs.costing.total_capital_cost(), bounds=(0, None) + ) + m.fs.costing.DWI_capital_cost = Var( + initialize=m_dwi.fs.costing.total_capital_cost(), bounds=(0, None) + ) + m.fs.costing.LCOW = Var(initialize=5, bounds=(0, None)) + + m.fs.costing.pretreatment_capital_cost.fix() + m.fs.costing.MVC_capital_cost.fix() + m.fs.costing.DWI_capital_cost.fix() + + m.fs.costing.aggregate_flow_electricity = Expression( + expr=m_pre.fs.treatment.costing.aggregate_flow_electricity() + + m_mvc.fs.costing.aggregate_flow_electricity() + # + m_dwi.fs.costing.aggregate_flow_electricity() + ) + m.fs.costing.total_operating_cost = Expression( + expr=m_pre.fs.treatment.costing.total_operating_cost() + + m_mvc.fs.costing.total_operating_cost() + + m_dwi.fs.costing.total_operating_cost(), + ) + m.fs.costing.annualized_capital_cost = Expression( + expr=m.fs.costing.total_capital_cost + * m_dwi.fs.costing.capital_recovery_factor() + ) + + m.fs.costing.total_capital_cost_constr = Constraint( + expr=m.fs.costing.total_capital_cost + == m.fs.costing.pretreatment_capital_cost + + m.fs.costing.MVC_capital_cost + + m.fs.costing.DWI_capital_cost + ) + + numerator = m.fs.costing.annualized_capital_cost + m.fs.costing.total_operating_cost + + m.fs.costing.LCOW_constr = Constraint( + expr=m.fs.costing.LCOW + == (m.fs.costing.annualized_capital_cost + m.fs.costing.total_operating_cost) + / product_flow + ) + + # m_mvc.fs.costing.LCOW.display() + # results = solver.solve(m) + assert degrees_of_freedom(m) == 0 + results = solve_permian_SOA(m) + + # print(f"System CAPEX = {m.fs.costing.total_capital_cost()}") + # print(f"System OPEX = {m.fs.costing.total_operating_cost()}") + # print( + # f"System Aggregate Flow Electricity = {m.fs.costing.aggregate_flow_electricity()}" + # ) + # print(f"numerator = {numerator()}") + # print(f"product_flow = {product_flow}") + print(f"System LCOW = {m.fs.costing.LCOW()}") + + print( + f"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%" + ) + print( + f"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% FINISHED %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%" + ) + print( + f"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% {Qin}, {tds}, {recovery} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%" + ) + print( + f"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%" + ) + return m, m_pre, m_mvc, m_dwi + + +def solve_permian_SOA(m): + solver = get_solver() + results = solver.solve(m) + if not check_optimal_termination(results): + results = solver.solve(m) + if not check_optimal_termination(results): + m.fs.optimal_solve_system.fix(0) + return results + + +if __name__ == "__main__": + + from watertap_contrib.reflo.kurby import * + + m, m_pre, m_mvc, m_dwi = build_and_run_permian_SOA(Qin=5, tds=130) + + # results_dict = build_results_dict(m) + # results_dict["flow_mgd"] = list() + # results_dict["tds"] = list() + + recovery = [0.5, 0.55] + qs = [5] + salt = [90] + + recovery = [0.4, 0.45, 0.5, 0.55, 0.6, 0.65] + # recovery = [0.45] + qs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] + salt = [75, 90, 105, 120, 130, 135, 150, 165] + + results_df = pd.DataFrame() + results_df_pre = pd.DataFrame() + results_df_mvc = pd.DataFrame() + results_df_dwi = pd.DataFrame() + + for r in recovery: + + tmp_results_dict = build_results_dict(m) + tmp_results_dict["flow_mgd"] = list() + tmp_results_dict["tds"] = list() + tmp_results_dict["rerun"] = list() + + tmp_results_dict_pre = build_results_dict(m_pre) + tmp_results_dict_pre["flow_mgd"] = list() + tmp_results_dict_pre["tds"] = list() + tmp_results_dict_pre["rerun"] = list() + + tmp_results_dict_mvc = build_results_dict(m_mvc) + tmp_results_dict_mvc["flow_mgd"] = list() + tmp_results_dict_mvc["tds"] = list() + tmp_results_dict_mvc["rerun"] = list() + + tmp_results_dict_dwi = build_results_dict(m_dwi) + tmp_results_dict_dwi["flow_mgd"] = list() + tmp_results_dict_dwi["tds"] = list() + tmp_results_dict_dwi["rerun"] = list() + for q in qs: + for s in salt: + rerun = 0 + tds = s + try: + m, m_pre, m_mvc, m_dwi = build_and_run_permian_SOA( + Qin=q, tds=tds, recovery=r + ) + except: + rerun = 1 + # tds = s * 1.01 + m, m_pre, m_mvc, m_dwi = build_and_run_permian_SOA( + Qin=q + 0.01, tds=s * 1.01, recovery=r + ) + tmp_results_dict = results_dict_append(m, tmp_results_dict) + tmp_results_dict["flow_mgd"].append(q) + tmp_results_dict["tds"].append(tds) + tmp_results_dict["rerun"].append(rerun) + + tmp_results_dict_pre = results_dict_append(m_pre, tmp_results_dict_pre) + tmp_results_dict_pre["flow_mgd"].append(q) + tmp_results_dict_pre["tds"].append(tds) + tmp_results_dict_pre["rerun"].append(rerun) + + tmp_results_dict_mvc = results_dict_append(m_mvc, tmp_results_dict_mvc) + tmp_results_dict_mvc["flow_mgd"].append(q) + tmp_results_dict_mvc["tds"].append(tds) + tmp_results_dict_mvc["rerun"].append(rerun) + + tmp_results_dict_dwi = results_dict_append(m_dwi, tmp_results_dict_dwi) + tmp_results_dict_dwi["flow_mgd"].append(q) + tmp_results_dict_dwi["tds"].append(tds) + tmp_results_dict_dwi["rerun"].append(rerun) + + results_df = pd.concat([results_df, pd.DataFrame.from_dict(tmp_results_dict)]) + results_df_pre = pd.concat( + [results_df_pre, pd.DataFrame.from_dict(tmp_results_dict_pre)] + ) + results_df_mvc = pd.concat( + [results_df_mvc, pd.DataFrame.from_dict(tmp_results_dict_mvc)] + ) + results_df_dwi = pd.concat( + [results_df_dwi, pd.DataFrame.from_dict(tmp_results_dict_dwi)] + ) + # results_dict = results_dict_append(m, results_dict, tmp_results_dict=tmp_results_dict) + save_dir = "/Users/ksitterl/Documents/Python/watertap-reflo/watertap-reflo/src/watertap_contrib/reflo/analysis/case_studies/permian/SOA_results" + # pprint.pprint(results_dict) + timestr = time.strftime("%Y%m%d-%H%M%S") + # results_df.to_csv(f"permian_soa_results_{timestr}.csv", index=False) + # results_df_pre.to_csv(f"permian_soa_results_pre_{timestr}.csv", index=False) + # results_df_mvc.to_csv(f"permian_soa_results_mvc_{timestr}.csv", index=False) + # results_df_dwi.to_csv(f"permian_soa_results_dwi_{timestr}.csv", index=False) + # # m = build_and_run_permian_SOA(Qin=5, tds=105) + mvc_col_dict = dict() + for c in results_df_mvc.columns: + mvc_col_dict[c] = c.replace("fs.MVC.", "MVC.").replace( + "fs.costing", "MVC_costing" + ) + results_df_mvc.rename(columns=mvc_col_dict, inplace=True) + + dwi_col_dict = dict() + for c in results_df_dwi.columns: + dwi_col_dict[c] = c.replace("fs.DWI.", "DWI.").replace( + "fs.costing", "DWI_costing" + ) + results_df_dwi.rename(columns=dwi_col_dict, inplace=True) + # results_df.rename( + # columns={ + # "fs.costing.LCOW": "system_LCOW", + # "fs.costing.total_capital_cost": "system_total_capital_cost", + # "fs.costing.total_operating_cost": "system_total_operating_cost", + # }, inplace=True + # ) + results_merged = pd.merge( + results_df, results_df_pre, on=["flow_mgd", "tds", "rerun"] + ) + results_merged = pd.merge( + results_merged, results_df_mvc, on=["flow_mgd", "tds", "rerun"] + ) + results_merged = pd.merge( + results_merged, results_df_dwi, on=["flow_mgd", "tds", "rerun"] + ) + + results_merged.to_csv( + f"{save_dir}/permian_soa_results_MERGED_{timestr}.csv", index=False + ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_ST1_MD.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_ST1_MD.py new file mode 100644 index 00000000..1c0d7338 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_ST1_MD.py @@ -0,0 +1,701 @@ +import pathlib +from pyomo.environ import ( + ConcreteModel, + value, + TransformationFactory, + Param, + Var, + Constraint, + Set, + Expression, + Objective, + NonNegativeReals, + Block, + RangeSet, + check_optimal_termination, + assert_optimal_termination, + units as pyunits, +) +from pyomo.network import Arc, SequentialDecomposition +from pyomo.util.calc_var_value import calculate_variable_from_constraint as cvc + +from idaes.core import FlowsheetBlock, UnitModelCostingBlock +import idaes.core.util.scaling as iscale +from idaes.core import MaterialFlowBasis +from idaes.core.util.scaling import ( + constraint_scaling_transform, + calculate_scaling_factors, + set_scaling_factor, +) +import idaes.logger as idaeslogger +from idaes.core.util.exceptions import InitializationError +from idaes.models.unit_models import ( + Product, + Feed, + StateJunction, + Separator, + Mixer, + MixingType, + MomentumMixingType, +) +from idaes.core.util.model_statistics import * +from idaes.core.util.initialization import propagate_state + +from watertap.core.solvers import get_solver +from watertap_contrib.reflo.core.wt_reflo_database import REFLODatabase +from watertap.core.zero_order_properties import WaterParameterBlock as ZO + + +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.core.util.initialization import * +from watertap.property_models.seawater_prop_pack import SeawaterParameterBlock +from watertap.property_models.water_prop_pack import ( + WaterParameterBlock as SteamParameterBlock, +) +from watertap_contrib.reflo.costing import ( + TreatmentCosting, + EnergyCosting, + REFLOSystemCosting, +) +from watertap_contrib.reflo.analysis.case_studies.permian.components import * +from watertap_contrib.reflo.analysis.case_studies.permian.components.MD import * +from watertap_contrib.reflo.analysis.case_studies.permian.components.CST import * + +reflo_dir = pathlib.Path(__file__).resolve().parents[3] +case_study_yaml = f"{reflo_dir}/data/technoeconomic/permian_case_study.yaml" +# rho = 1125 * pyunits.kg / pyunits.m**3 +# rho_water = 997 * pyunits.kg / pyunits.m**3 + +solver = get_solver() + +__all__ = [ + "build_permian_st1_md", + "set_operating_conditions_st1_md", + "add_treatment_costing_st1_md", + "set_permian_pretreatment_scaling_st1_md", + "init_system_st1_md", + "run_permian_st1_md", +] + +# TODO: +# Add back CST +# Update membrane type and MD recovery + + +def get_stream_density(Qin=5, tds=130, **kwargs): + + m = ConcreteModel() + m.fs = FlowsheetBlock(dynamic=False) + Qin = Qin * pyunits.Mgallons / pyunits.day + flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + m.fs.properties_feed = SeawaterParameterBlock() + m.fs.feed_sw = Feed(property_package=m.fs.properties_feed) + m.fs.feed_sw.properties.calculate_state( + var_args={ + ("flow_vol_phase", "Liq"): flow_in, + ("conc_mass_phase_comp", ("Liq", "TDS")): tds * pyunits.g / pyunits.liter, + ("temperature", None): 300, + ("pressure", None): 101325, + }, + hold_state=True, + ) + + m.fs.feed_sw.initialize() + rho = ( + value(m.fs.feed_sw.properties[0].dens_mass_phase["Liq"]) + * pyunits.kg + / pyunits.m**3 + ) + + return rho + + +def build_permian_st1_md(Qin=5, Q_md=0.22478, Cin=118, water_recovery=0.2, rho=None): + """ + Build Permian pretreatment flowsheet + """ + + m = ConcreteModel() + m.fs = FlowsheetBlock(dynamic=False) + m.db = REFLODatabase() + + m.fs.properties = ZO(solute_list=["tds"]) + m.fs.properties.dens_mass_default = rho + + m.fs.properties_feed = SeawaterParameterBlock() + m.fs.properties_vapor = SteamParameterBlock() + + # Begin building Treatment Block + m.fs.treatment = treat = Block() + + treat.feed = Feed(property_package=m.fs.properties) + treat.product = Product(property_package=m.fs.properties_feed) + + m.inlet_flow_rate = pyunits.convert( + Q_md * pyunits.m**3 / pyunits.s, to_units=pyunits.m**3 / pyunits.s + ) + m.inlet_salinity = pyunits.convert( + Cin * pyunits.g / pyunits.liter, to_units=pyunits.kg / pyunits.m**3 + ) + + m.water_recovery = water_recovery + + # Add translator blocks + treat.zo_to_sw_feed = Translator_ZO_to_SW( + inlet_property_package=m.fs.properties, + outlet_property_package=m.fs.properties_feed, + ) + + treat.zo_to_sw_disposal = Translator_ZO_to_SW( + inlet_property_package=m.fs.properties, + outlet_property_package=m.fs.properties_feed, + ) + + treat.disposal_ZO_mixer = Mixer( + property_package=m.fs.properties, + num_inlets=2, + inlet_list=["ec_disposal", "cart_filt_disposal"], + energy_mixing_type=MixingType.none, + momentum_mixing_type=MomentumMixingType.none, + ) + + treat.disposal_SW_mixer = Mixer( + property_package=m.fs.properties_feed, + num_inlets=2, + inlet_list=["zo_mixer", "md_disposal"], + energy_mixing_type=MixingType.none, + momentum_mixing_type=MomentumMixingType.none, + ) + + treat.chem_addition = FlowsheetBlock(dynamic=False) + build_chem_addition(m, treat.chem_addition) + + treat.EC = FlowsheetBlock(dynamic=False) + build_ec(m, treat.EC) + + treat.cart_filt = FlowsheetBlock(dynamic=False) + build_cartridge_filtration(m, treat.cart_filt) + + treat.md = FlowsheetBlock(dynamic=False) + build_md(m, treat.md, m.fs.properties_feed) + + treat.DWI = FlowsheetBlock(dynamic=False) + build_dwi(m, treat.DWI, m.fs.properties_feed) + + # BUILD PRODUCT STREAM + # feed > chem_addition > EC > cart_filt > ZO_to_SW_translator > desal unit > product + treat.feed_to_chem_addition = Arc( + source=treat.feed.outlet, destination=treat.chem_addition.feed.inlet + ) + + treat.chem_addition_to_ec = Arc( + source=treat.chem_addition.product.outlet, destination=treat.EC.feed.inlet + ) + + treat.ec_to_cart_filt = Arc( + source=treat.EC.product.outlet, destination=treat.cart_filt.feed.inlet + ) + + # from ZO to SW - feed + treat.cart_filt_to_translator = Arc( + source=treat.cart_filt.product.outlet, destination=treat.zo_to_sw_feed.inlet + ) + + treat.cart_filt_translated_to_md = Arc( + source=treat.zo_to_sw_feed.outlet, destination=treat.md.feed.inlet + ) + + treat.md_to_product = Arc( + source=treat.md.permeate.outlet, destination=treat.product.inlet + ) + + # BUILD DISPOSAL STREAM + # EC > ZO_mixer > ZO_to_SW_translator > disposal_mixer > disposal_mixer > DWI + # cart_filt > ZO_mixer + # MD unit > disposal_mixer + + treat.ec_to_disposal_mix = Arc( + source=treat.EC.disposal.outlet, destination=treat.disposal_ZO_mixer.ec_disposal + ) + + treat.cart_filt_to_disposal_mix = Arc( + source=treat.cart_filt.disposal.outlet, + destination=treat.disposal_ZO_mixer.cart_filt_disposal, + ) + + treat.disposal_ZO_mix_to_translator = Arc( + source=treat.disposal_ZO_mixer.outlet, destination=treat.zo_to_sw_disposal.inlet + ) + + treat.disposal_ZO_mix_translated_to_disposal_SW_mixer = Arc( + source=treat.zo_to_sw_disposal.outlet, + destination=treat.disposal_SW_mixer.zo_mixer, + ) + + treat.md_disposal_to_translator = Arc( + source=treat.md.concentrate.outlet, + destination=treat.disposal_SW_mixer.md_disposal, + ) + + treat.disposal_SW_mixer_to_dwi = Arc( + source=treat.disposal_SW_mixer.outlet, destination=treat.DWI.feed.inlet + ) + + TransformationFactory("network.expand_arcs").apply_to(m) + + # Build energy block + m.fs.energy = energy = Block() + m.fs.energy.cst = FlowsheetBlock() + build_cst(m.fs.energy.cst) + + # Add treatment costing + m.fs.treatment.costing = TreatmentCosting(case_study_definition=case_study_yaml) + m.fs.energy.costing = EnergyCosting() + + return m + + +def set_operating_conditions_st1_md(m, rho, Qin=5, tds=130, **kwargs): + + global flow_mass_water, flow_mass_tds, flow_in + + Qin = Qin * pyunits.Mgallons / pyunits.day + flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + flow_mass_water = pyunits.convert(Qin * rho, to_units=pyunits.kg / pyunits.s) + flow_mass_tds = pyunits.convert( + Qin * tds * pyunits.g / pyunits.liter, to_units=pyunits.kg / pyunits.s + ) + + m.fs.treatment.feed.properties[0].flow_mass_comp["H2O"].fix( + flow_mass_water - flow_mass_tds + ) + m.fs.treatment.feed.properties[0].flow_mass_comp["tds"].fix(flow_mass_tds) + m.fs.treatment.feed.properties[0].conc_mass_comp[...] + + set_chem_addition_op_conditions(m, m.fs.treatment.chem_addition, **kwargs) + set_ec_operating_conditions(m, m.fs.treatment.EC, **kwargs) + set_cart_filt_op_conditions(m, m.fs.treatment.cart_filt) + + set_cst_op_conditions(m.fs.energy.cst, hours_storage=24) + + +def set_permian_pretreatment_scaling_st1_md( + m, calclate_m_scaling_factors=False, **kwargs +): + + m.fs.properties.set_default_scaling( + "flow_mass_comp", + # 1 / value(flow_mass_water), + 1e-2, + index=("H2O"), + ) + + m.fs.properties.set_default_scaling( + "flow_mass_comp", + # 1 / value(flow_mass_tds), + 0.1, + index=("tds"), + ) + + m.fs.properties_feed.set_default_scaling( + "flow_mass_phase_comp", + 0.1, + index=("Liq", "TDS"), + ) + + m.fs.properties_feed.set_default_scaling( + "flow_mass_phase_comp", + 1e-2, + index=("Liq", "H2O"), + ) + + set_chem_addition_scaling( + m, m.fs.treatment.chem_addition, calc_blk_scaling_factors=True + ) + + set_cart_filt_scaling(m, m.fs.treatment.cart_filt, calc_blk_scaling_factors=True) + + set_ec_scaling(m, m.fs.treatment.EC, calc_blk_scaling_factors=True) + + set_scaling_factor( + m.fs.treatment.product.properties[0].flow_mass_phase_comp["Liq", "H2O"], 1e-2 + ) + set_scaling_factor( + m.fs.treatment.product.properties[0].flow_mass_phase_comp["Liq", "TDS"], 1e5 + ) + + # ZO to SW feed translator + set_scaling_factor( + m.fs.treatment.zo_to_sw_feed.properties_out[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 1e-2, + ) + set_scaling_factor( + m.fs.treatment.zo_to_sw_feed.properties_out[0].flow_mass_phase_comp[ + "Liq", "TDS" + ], + 0.1, + ) + + # ZO to SW disposal translator + set_scaling_factor( + m.fs.treatment.zo_to_sw_disposal.properties_in[0].flow_mass_comp["H2O"], + 1, + ) + set_scaling_factor( + m.fs.treatment.zo_to_sw_disposal.properties_in[0].flow_mass_comp["tds"], + 1, + ) + set_scaling_factor( + m.fs.treatment.zo_to_sw_disposal.properties_out[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 1, + ) + set_scaling_factor( + m.fs.treatment.zo_to_sw_disposal.properties_out[0].flow_mass_phase_comp[ + "Liq", "TDS" + ], + 1, + ) + + # ZO DISPOSAL MIXER + # CF inlet + set_scaling_factor( + m.fs.treatment.disposal_ZO_mixer.cart_filt_disposal_state[0].flow_mass_comp[ + "H2O" + ], + 100, + ) + set_scaling_factor( + m.fs.treatment.disposal_ZO_mixer.cart_filt_disposal_state[0].flow_mass_comp[ + "tds" + ], + 1e8, + ) + + # EC inlet + set_scaling_factor( + m.fs.treatment.disposal_ZO_mixer.ec_disposal_state[0].flow_mass_comp["H2O"], + 1, + ) + set_scaling_factor( + m.fs.treatment.disposal_ZO_mixer.ec_disposal_state[0].flow_mass_comp["tds"], + 1, + ) + + # mixed state + set_scaling_factor( + m.fs.treatment.disposal_ZO_mixer.mixed_state[0].flow_mass_comp["H2O"], + 1, + ) + set_scaling_factor( + m.fs.treatment.disposal_ZO_mixer.mixed_state[0].flow_mass_comp["tds"], + 1, + ) + # SW DISPOSAL MIXER + # ZO mixer inlet + set_scaling_factor( + m.fs.treatment.disposal_SW_mixer.zo_mixer_state[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 100, + ) + set_scaling_factor( + m.fs.treatment.disposal_SW_mixer.zo_mixer_state[0].flow_mass_phase_comp[ + "Liq", "TDS" + ], + 10, + ) + + set_scaling_factor( + m.fs.treatment.disposal_SW_mixer.md_disposal_state[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 1e-3, + ) + set_scaling_factor( + m.fs.treatment.disposal_SW_mixer.md_disposal_state[0].flow_mass_phase_comp[ + "Liq", "TDS" + ], + 1e-2, + ) + + # mixed state outlet + set_scaling_factor( + m.fs.treatment.disposal_SW_mixer.mixed_state[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 1e-1, + ) + set_scaling_factor( + m.fs.treatment.disposal_SW_mixer.mixed_state[0].flow_mass_phase_comp[ + "Liq", "TDS" + ], + 1e-2, + ) + + # DWI + set_scaling_factor( + m.fs.treatment.DWI.unit.properties[0].flow_mass_phase_comp["Liq", "H2O"], + 1e-3, + ) + set_scaling_factor( + m.fs.treatment.DWI.unit.properties[0].flow_mass_phase_comp["Liq", "TDS"], + 1e-1, + ) + + if calclate_m_scaling_factors: + print("calclate_m_scaling_factors\n\n\n") + calculate_scaling_factors(m) + + +def init_system_st1_md(m, **kwargs): + + treat = m.fs.treatment + + treat.feed.initialize() + propagate_state(treat.feed_to_chem_addition) + + init_chem_addition(m, treat.chem_addition) + + propagate_state(treat.chem_addition_to_ec) + + init_ec(m, treat.EC) + propagate_state(treat.ec_to_cart_filt) + propagate_state(treat.ec_to_disposal_mix) + + init_cart_filt(m, treat.cart_filt) + propagate_state(treat.cart_filt_to_translator) + propagate_state(treat.cart_filt_to_disposal_mix) + + treat.disposal_ZO_mixer.initialize() + propagate_state(treat.disposal_ZO_mix_to_translator) + + # NOTE: If the selected temperature is similar to md_disposal temperature, the mixer has issues in the solve + treat.zo_to_sw_disposal.outlet.temperature[0].fix(300) + treat.zo_to_sw_disposal.outlet.pressure[0].fix(101325) + treat.zo_to_sw_disposal.initialize() + + treat.zo_to_sw_feed.properties_out[0].temperature.fix(300) + treat.zo_to_sw_feed.properties_out[0].pressure.fix(101325) + treat.zo_to_sw_feed.initialize() + + propagate_state(treat.cart_filt_translated_to_md) + + init_md(m, treat.md) + propagate_state(treat.md_to_product) + propagate_state(treat.md_disposal_to_translator) + + propagate_state(treat.disposal_ZO_mix_translated_to_disposal_SW_mixer) + # NOTE: variable that affects DOF in unclear way + + treat.disposal_SW_mixer.initialize() + treat.disposal_SW_mixer.mixed_state[0].temperature.fix(300) + treat.disposal_SW_mixer.mixed_state[0].pressure.fix() + + propagate_state(treat.disposal_SW_mixer_to_dwi) + # NOTE: variables that affect DOF in unclear way + # treat.DWI.feed.properties[0].temperature.fix() + # treat.DWI.feed.properties[0].pressure.fix() + treat.DWI.unit.properties[0].flow_vol_phase + treat.DWI.unit.properties[0].conc_mass_phase_comp + init_dwi(m, treat.DWI) + + treat.product.properties[0].flow_vol_phase + treat.product.properties[0].conc_mass_phase_comp + treat.product.initialize() + + init_cst(m.fs.energy.cst) + + +def add_costing_st1_md(m, heat_price=0.018, electricity_price=0.0626): + + add_chem_addition_costing( + m, m.fs.treatment.chem_addition, flowsheet_costing_block=m.fs.treatment.costing + ) + add_ec_costing(m, m.fs.treatment.EC, flowsheet_costing_block=m.fs.treatment.costing) + add_cartridge_filtration_costing( + m, m.fs.treatment.cart_filt, flowsheet_costing_block=m.fs.treatment.costing + ) + add_dwi_costing( + m, m.fs.treatment.DWI, flowsheet_costing_block=m.fs.treatment.costing + ) + m.fs.treatment.md.unit.add_costing_module(m.fs.treatment.costing) + + m.fs.treatment.costing.cost_process() + m.fs.treatment.costing.add_annual_water_production( + m.fs.treatment.product.properties[0].flow_vol + ) + m.fs.treatment.costing.add_LCOW(m.fs.treatment.product.properties[0].flow_vol) + + # Add energy costing + + add_cst_costing(m.fs.energy.cst, m.fs.energy.costing) + + m.fs.energy.costing.cost_process() + m.fs.energy.costing.add_LCOH() + + # Add system costing + m.fs.costing = REFLOSystemCosting() + m.fs.costing.heat_cost_buy.fix(heat_price) + m.fs.costing.electricity_cost_buy.set_value(electricity_price) + m.fs.costing.cost_process() + + m.fs.costing.add_LCOT(m.fs.treatment.product.properties[0].flow_vol) + m.fs.costing.add_LCOH() + + print("\n--------- INITIALIZING SYSTEM COSTING ---------\n") + + m.fs.energy.costing.initialize() + m.fs.treatment.costing.initialize() + m.fs.costing.initialize() + + +def run_permian_st1_md(Qin=5, tds=130, water_recovery=0.3, **kwargs): + """ + Run Permian pretreatment flowsheet + """ + rho = get_stream_density(Qin, tds) + + m = build_permian_st1_md(rho=rho, water_recovery=water_recovery) + treat = m.fs.treatment + + set_operating_conditions_st1_md(m, rho) + set_permian_pretreatment_scaling_st1_md( + m, calclate_m_scaling_factors=True + ) # Doesn't solve without this even before costing + + treat.feed.properties[0].flow_vol + + init_system_st1_md(m) + print(f"DOF = {degrees_of_freedom(m)}") + + # Unfix CST heat + m.fs.energy.cst.unit.heat_load.unfix() + + results = solver.solve(m) + print_infeasible_constraints(m) + assert_optimal_termination(results) + + print("\n--------- Before costing solve Completed ---------\n") + report_MD(m, treat.md) + + iscale.calculate_scaling_factors(m.fs.treatment.md.unit.mp) + if ( + iscale.get_scaling_factor( + m.fs.treatment.md.unit.overall_thermal_power_requirement + ) + is None + ): + iscale.set_scaling_factor( + m.fs.treatment.md.unit.overall_thermal_power_requirement, 1e-6 + ) + + if ( + iscale.get_scaling_factor(m.fs.treatment.md.unit.overall_elec_power_requirement) + is None + ): + iscale.set_scaling_factor( + m.fs.treatment.md.unit.overall_elec_power_requirement, 1e-4 + ) + + if ( + iscale.get_scaling_factor( + m.fs.treatment.md.unit.mp.get_active_process_blocks()[ + -1 + ].fs.vagmd.system_capacity + ) + is None + ): + iscale.set_scaling_factor( + m.fs.treatment.md.unit.mp.get_active_process_blocks()[ + -1 + ].fs.vagmd.system_capacity, + 1e6, + ) + + print("CST Heat load:", value(m.fs.energy.cst.unit.heat_load)) + print("CST Heat:", value(m.fs.energy.cst.unit.heat)) + + # Add costing + add_costing_st1_md(m) + + m.fs.energy.cst.unit.heat_load.fix() + m.fs.lcot_objective = Objective(expr=m.fs.costing.LCOT) + + try: + results = solver.solve(m) + print_infeasible_constraints(m) + except ValueError: + print_infeasible_constraints(m) + assert_optimal_termination(results) + print("\n--------- After costing solve Completed ---------\n") + + print("CST Heat load:", value(m.fs.energy.cst.unit.heat_load)) + print("CST Heat:", value(m.fs.energy.cst.unit.heat)) + + return m + + +if __name__ == "__main__": + + m = run_permian_st1_md(Qin=5, tds=130, water_recovery=0.1) + treat = m.fs.treatment + report_MD(m, treat.md) + print(f"DOF = {degrees_of_freedom(m)}") + + system_recovery = ( + treat.product.properties[0].flow_vol() / treat.feed.properties[0].flow_vol() + ) + print("\n") + print(f"Pretreatment Recovery: {system_recovery:.2f}") + + print( + f"Inlet flow_vol: {treat.feed.properties[0].flow_vol():.5f} {pyunits.get_units(treat.feed.properties[0].flow_vol)}" + ) + print( + f'Inlet TDS conc: {treat.feed.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.feed.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'EC feed TDS conc: {treat.EC.feed.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.EC.feed.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'EC product TDS conc: {treat.EC.product.properties[0].conc_mass_comp["tds"]():.2f} { pyunits.get_units(treat.EC.product.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'EC disposal TDS conc: {treat.EC.disposal.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.EC.disposal.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'CF feed TDS conc: {treat.cart_filt.product.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.cart_filt.product.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'Product TDS conc: {treat.product.properties[0].conc_mass_phase_comp["Liq", "TDS"]():.2f} {pyunits.get_units(treat.product.properties[0].conc_mass_phase_comp["Liq", "TDS"]())}' + ) + + print( + f'Product flow_vol: {treat.product.properties[0].flow_vol_phase["Liq"]():.2f} {pyunits.get_units(treat.product.properties[0].flow_vol_phase["Liq"])}' + ) + + print( + f'DWI flow_vol: {treat.DWI.unit.properties[0].flow_vol_phase["Liq"]():.6f} {pyunits.get_units(treat.DWI.unit.properties[0].flow_vol_phase["Liq"])}' + ) + + print( + f'DWI TDS conc: {treat.DWI.unit.properties[0].conc_mass_phase_comp["Liq", "TDS"]():.2f} {pyunits.get_units(treat.DWI.unit.properties[0].conc_mass_phase_comp["Liq", "TDS"])}' + ) + print(f"DWI pressure: {treat.DWI.feed.properties[0].pressure()} Pa") + + print( + f"Translator pressure: {treat.disposal_SW_mixer.zo_mixer_state[0].pressure()} Pa" + ) + + print( + f'{"Aggregated Heat Cost":<30s}{value(m.fs.treatment.costing.aggregate_flow_costs["heat"]):<20,.2f}{pyunits.get_units(m.fs.treatment.costing.aggregate_flow_costs["heat"])}' + ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_ST2_MD.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_ST2_MD.py new file mode 100644 index 00000000..a5a3258d --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_ST2_MD.py @@ -0,0 +1,777 @@ +import pathlib +from pyomo.environ import ( + ConcreteModel, + value, + TransformationFactory, + Param, + Var, + Constraint, + Set, + Expression, + Objective, + NonNegativeReals, + Block, + RangeSet, + check_optimal_termination, + assert_optimal_termination, + units as pyunits, +) +from pyomo.network import Arc, SequentialDecomposition +from pyomo.util.calc_var_value import calculate_variable_from_constraint as cvc + +from idaes.core import FlowsheetBlock, UnitModelCostingBlock +import idaes.core.util.scaling as iscale +from idaes.core import MaterialFlowBasis +from idaes.core.util.scaling import ( + constraint_scaling_transform, + calculate_scaling_factors, + set_scaling_factor, +) +import idaes.logger as idaeslogger +from idaes.core.util.exceptions import InitializationError +from idaes.models.unit_models import ( + Product, + Feed, + StateJunction, + Separator, + Mixer, + MixingType, + MomentumMixingType, +) +from idaes.core.util.model_statistics import * +from idaes.core.util.initialization import propagate_state + +from watertap.core.solvers import get_solver +from watertap_contrib.reflo.core.wt_reflo_database import REFLODatabase +from watertap.core.zero_order_properties import WaterParameterBlock as ZO +from watertap.property_models.unit_specific.cryst_prop_pack import NaClParameterBlock +from watertap.property_models.seawater_prop_pack import SeawaterParameterBlock +from watertap.property_models.water_prop_pack import ( + WaterParameterBlock as SteamParameterBlock, +) +from idaes.core import MaterialBalanceType +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.core.util.initialization import * + +from watertap_contrib.reflo.costing import TreatmentCosting, EnergyCosting +from watertap_contrib.reflo.analysis.case_studies.permian.components import * +from watertap_contrib.reflo.analysis.case_studies.permian.components.MD import * +from watertap_contrib.reflo.analysis.case_studies.permian.components.translator_zo_to_nacl import * +from watertap_contrib.reflo.analysis.case_studies.permian.components.translator_sw_to_nacl import * +from watertap_contrib.reflo.analysis.case_studies.permian.components.normalizer_cryst import * +from watertap_contrib.reflo.analysis.case_studies.permian.components.denormalizer_cryst import * +from watertap_contrib.reflo.analysis.case_studies.permian.components.multi_effect_crystallizer import * + +reflo_dir = pathlib.Path(__file__).resolve().parents[3] +case_study_yaml = f"{reflo_dir}/data/technoeconomic/permian_case_study.yaml" +# rho = 1125 * pyunits.kg / pyunits.m**3 +# rho_water = 997 * pyunits.kg / pyunits.m**3 + +solver = get_solver() + +__all__ = [ + "build_permian_st2_md", + "set_operating_conditions_st2_md", + "add_treatment_costing_st2_md", + "set_permian_pretreatment_scaling_st2_md", + "init_system_st2_md", + "run_permian_st2_md", +] + +# TODO: +# Update membrane type and MD recovery + + +def get_stream_density(Qin=5, tds=130, **kwargs): + # global rho + + m = ConcreteModel() + m.fs = FlowsheetBlock(dynamic=False) + Qin = Qin * pyunits.Mgallons / pyunits.day + flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + m.fs.properties_feed = SeawaterParameterBlock() + m.fs.feed_sw = Feed(property_package=m.fs.properties_feed) + m.fs.feed_sw.properties.calculate_state( + var_args={ + ("flow_vol_phase", "Liq"): flow_in, + ("conc_mass_phase_comp", ("Liq", "TDS")): tds * pyunits.g / pyunits.liter, + ("temperature", None): 300, + ("pressure", None): 101325, + }, + hold_state=True, + ) + + m.fs.feed_sw.initialize() + rho = ( + value(m.fs.feed_sw.properties[0].dens_mass_phase["Liq"]) + * pyunits.kg + / pyunits.m**3 + ) + + # rho = m.fs.feed_sw.properties[0].dens_mass_phase["Liq"] + + return rho + + +def build_permian_st2_md(Qin=5, Q_md=0.22478, Cin=118, water_recovery=0.2, rho=None): + """ + Build Permian pretreatment flowsheet + """ + + m = ConcreteModel() + m.fs = FlowsheetBlock(dynamic=False) + m.db = REFLODatabase() + + m.fs.properties = ZO(solute_list=["tds"]) + m.fs.properties.dens_mass_default = rho + + m.fs.properties_feed = SeawaterParameterBlock() + m.fs.properties_vapor = SteamParameterBlock() + m.fs.properties_NaCl = NaClParameterBlock() + + # Begin building Treatment Block + m.fs.treatment = treat = Block() + + treat.feed = Feed(property_package=m.fs.properties) + # treat.product = Product(property_package=m.fs.properties_NaCl) + + m.inlet_flow_rate = pyunits.convert( + Q_md * pyunits.m**3 / pyunits.s, to_units=pyunits.m**3 / pyunits.s + ) + m.inlet_salinity = pyunits.convert( + Cin * pyunits.g / pyunits.liter, to_units=pyunits.kg / pyunits.m**3 + ) + + m.water_recovery = water_recovery + + # Add translator blocks + treat.zo_to_sw_feed = Translator_ZO_to_SW( + inlet_property_package=m.fs.properties, + outlet_property_package=m.fs.properties_feed, + ) + + treat.zo_mix_to_nacl_disposal = Translator_ZO_to_NaCl( + inlet_property_package=m.fs.properties, + outlet_property_package=m.fs.properties_NaCl, + ) + + treat.disposal_ZO_mixer = Mixer( + property_package=m.fs.properties, + num_inlets=2, + inlet_list=["ec_disposal", "cart_filt_disposal"], + energy_mixing_type=MixingType.none, + momentum_mixing_type=MomentumMixingType.none, + ) + + treat.sw_to_nacl_product = Translator_SW_to_NaCl( + inlet_property_package=m.fs.properties_feed, + outlet_property_package=m.fs.properties_NaCl, + ) + + treat.sw_to_nacl_disposal = Translator_SW_to_NaCl( + inlet_property_package=m.fs.properties_feed, + outlet_property_package=m.fs.properties_NaCl, + ) + + treat.disposal_NaCl_mixer = Mixer( + property_package=m.fs.properties_NaCl, + num_inlets=2, + inlet_list=["zo_mixer", "md_disposal"], + material_balance_type=MaterialBalanceType.componentPhase, + energy_mixing_type=MixingType.none, + momentum_mixing_type=MomentumMixingType.none, + ) + + treat.norm_feed = Normalizer_Cryst( + inlet_property_package=m.fs.properties_NaCl, + outlet_property_package=m.fs.properties_NaCl, + ) + + treat.chem_addition = FlowsheetBlock(dynamic=False) + build_chem_addition(m, treat.chem_addition) + + treat.EC = FlowsheetBlock(dynamic=False) + build_ec(m, treat.EC) + + treat.cart_filt = FlowsheetBlock(dynamic=False) + build_cartridge_filtration(m, treat.cart_filt) + + treat.md = FlowsheetBlock(dynamic=False) + build_md(m, treat.md, m.fs.properties_feed) + + # BUILD PRODUCT STREAM + # feed > chem_addition > EC > cart_filt > ZO_to_SW_translator > desal unit > product + treat.feed_to_chem_addition = Arc( + source=treat.feed.outlet, destination=treat.chem_addition.feed.inlet + ) + + treat.chem_addition_to_ec = Arc( + source=treat.chem_addition.product.outlet, destination=treat.EC.feed.inlet + ) + + treat.ec_to_cart_filt = Arc( + source=treat.EC.product.outlet, destination=treat.cart_filt.feed.inlet + ) + + # from ZO to SW - feed + treat.cart_filt_to_translator = Arc( + source=treat.cart_filt.product.outlet, destination=treat.zo_to_sw_feed.inlet + ) + + treat.cart_filt_translated_to_md = Arc( + source=treat.zo_to_sw_feed.outlet, destination=treat.md.feed.inlet + ) + + treat.md_to_product = Arc( + source=treat.md.permeate.outlet, destination=treat.sw_to_nacl_product.inlet + ) + + # BUILD DISPOSAL STREAM + # EC > ZO_mixer > ZO_to_NaCl_translator > disposal_mixer > disposal_mixer > DWI + # cart_filt > ZO_mixer + # MD unit > disposal_mixer + + treat.ec_to_disposal_mix = Arc( + source=treat.EC.disposal.outlet, destination=treat.disposal_ZO_mixer.ec_disposal + ) + + treat.cart_filt_to_disposal_mix = Arc( + source=treat.cart_filt.disposal.outlet, + destination=treat.disposal_ZO_mixer.cart_filt_disposal, + ) + + treat.disposal_ZO_mix_to_nacl_translator = Arc( + source=treat.disposal_ZO_mixer.outlet, + destination=treat.zo_mix_to_nacl_disposal.inlet, + ) + + treat.md_disposal_to_nacl_translator = Arc( + source=treat.md.concentrate.outlet, + destination=treat.sw_to_nacl_disposal.inlet, + ) + + treat.disposal_ZO_mix_translated_to_disposal_NaCl_mixer = Arc( + source=treat.zo_mix_to_nacl_disposal.outlet, + destination=treat.disposal_NaCl_mixer.zo_mixer, + ) + + treat.md_disposal_translated_to_disposal_NaCl_mixer = Arc( + source=treat.sw_to_nacl_disposal.outlet, + destination=treat.disposal_NaCl_mixer.md_disposal, + ) + + treat.mixer_to_normalized_feed = Arc( + source=treat.disposal_NaCl_mixer.outlet, + destination=treat.norm_feed.inlet, + ) + + TransformationFactory("network.expand_arcs").apply_to(m) + + return m + + +def set_operating_conditions_st2_md(m, rho, Qin=5, tds=130, **kwargs): + + global flow_mass_water, flow_mass_tds, flow_in + + Qin = Qin * pyunits.Mgallons / pyunits.day + flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + flow_mass_water = pyunits.convert(Qin * rho, to_units=pyunits.kg / pyunits.s) + flow_mass_tds = pyunits.convert( + Qin * tds * pyunits.g / pyunits.liter, to_units=pyunits.kg / pyunits.s + ) + + m.fs.treatment.feed.properties[0].flow_mass_comp["H2O"].fix( + flow_mass_water - flow_mass_tds + ) + m.fs.treatment.feed.properties[0].flow_mass_comp["tds"].fix(flow_mass_tds) + m.fs.treatment.feed.properties[0].conc_mass_comp[...] + + set_chem_addition_op_conditions(m, m.fs.treatment.chem_addition, **kwargs) + set_ec_operating_conditions(m, m.fs.treatment.EC, **kwargs) + set_cart_filt_op_conditions(m, m.fs.treatment.cart_filt) + + +def add_treatment_costing_st2_md(m): + + m.fs.treatment.costing = TreatmentCosting(case_study_definition=case_study_yaml) + add_chem_addition_costing( + m, m.fs.treatment.chem_addition, flowsheet_costing_block=m.fs.treatment.costing + ) + add_ec_costing(m, m.fs.treatment.EC, flowsheet_costing_block=m.fs.treatment.costing) + add_cartridge_filtration_costing( + m, m.fs.treatment.cart_filt, flowsheet_costing_block=m.fs.treatment.costing + ) + + m.fs.treatment.md.unit.add_costing_module(m.fs.treatment.costing) + + add_mec_costing( + m, m.fs.treatment.mec, flowsheet_costing_block=m.fs.treatment.costing + ) + + m.fs.treatment.costing.cost_process() + m.fs.treatment.costing.add_annual_water_production( + m.fs.treatment.product.properties[0].flow_vol + ) + + +def set_permian_pretreatment_scaling_st2_md( + m, calclate_m_scaling_factors=False, **kwargs +): + + m.fs.properties.set_default_scaling( + "flow_mass_comp", + # 1 / value(flow_mass_water), + 1e-2, + index=("H2O"), + ) + + m.fs.properties.set_default_scaling( + "flow_mass_comp", + # 1 / value(flow_mass_tds), + 0.1, + index=("tds"), + ) + + m.fs.properties_feed.set_default_scaling( + "flow_mass_phase_comp", + 0.1, + index=("Liq", "TDS"), + ) + + m.fs.properties_feed.set_default_scaling( + "flow_mass_phase_comp", + 1e-2, + index=("Liq", "H2O"), + ) + + set_chem_addition_scaling( + m, m.fs.treatment.chem_addition, calc_blk_scaling_factors=True + ) + + set_cart_filt_scaling(m, m.fs.treatment.cart_filt, calc_blk_scaling_factors=True) + + set_ec_scaling(m, m.fs.treatment.EC, calc_blk_scaling_factors=True) + + # ZO to SW feed translator + set_scaling_factor( + m.fs.treatment.zo_to_sw_feed.properties_out[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 1e-2, + ) + set_scaling_factor( + m.fs.treatment.zo_to_sw_feed.properties_out[0].flow_mass_phase_comp[ + "Liq", "TDS" + ], + 0.1, + ) + + # ZO to NaCl disposal translator + # set_scaling_factor( + # m.fs.treatment.zo_mix_to_nacl_disposal.properties_in[0].flow_mass_comp["H2O"], + # 1, + # ) + # set_scaling_factor( + # m.fs.treatment.zo_mix_to_nacl_disposal.properties_in[0].flow_mass_comp["tds"], + # 1, + # ) + # set_scaling_factor( + # m.fs.treatment.zo_mix_to_nacl_disposal.properties_out[0].flow_mass_phase_comp[ + # "Liq", "H2O" + # ], + # 1, + # ) + # set_scaling_factor( + # m.fs.treatment.zo_mix_to_nacl_disposal.properties_out[0].flow_mass_phase_comp[ + # "Liq", "NaCl" + # ], + # 1, + # ) + + # # ZO DISPOSAL MIXER + # # CF inlet + # set_scaling_factor( + # m.fs.treatment.disposal_ZO_mixer.cart_filt_disposal_state[0].flow_mass_comp[ + # "H2O" + # ], + # 100, + # ) + # set_scaling_factor( + # m.fs.treatment.disposal_ZO_mixer.cart_filt_disposal_state[0].flow_mass_comp[ + # "tds" + # ], + # 1e8, + # ) + + # EC inlet + # set_scaling_factor( + # m.fs.treatment.disposal_ZO_mixer.ec_disposal_state[0].flow_mass_comp["H2O"], + # 1, + # ) + # set_scaling_factor( + # m.fs.treatment.disposal_ZO_mixer.ec_disposal_state[0].flow_mass_comp["tds"], + # 1, + # ) + + # # mixed state + # set_scaling_factor( + # m.fs.treatment.disposal_ZO_mixer.mixed_state[0].flow_mass_comp["H2O"], + # 1, + # ) + # set_scaling_factor( + # m.fs.treatment.disposal_ZO_mixer.mixed_state[0].flow_mass_comp["tds"], + # 1, + # ) + # NaCl DISPOSAL MIXER + # ZO mixer inlet + set_scaling_factor( + m.fs.treatment.disposal_NaCl_mixer.zo_mixer_state[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 100, + ) + set_scaling_factor( + m.fs.treatment.disposal_NaCl_mixer.zo_mixer_state[0].flow_mass_phase_comp[ + "Liq", "NaCl" + ], + 10, + ) + + set_scaling_factor( + m.fs.treatment.disposal_NaCl_mixer.md_disposal_state[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 1e-3, + ) + set_scaling_factor( + m.fs.treatment.disposal_NaCl_mixer.md_disposal_state[0].flow_mass_phase_comp[ + "Liq", "NaCl" + ], + 1e-2, + ) + + # mixed state outlet + set_scaling_factor( + m.fs.treatment.disposal_NaCl_mixer.mixed_state[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 1e-1, + ) + set_scaling_factor( + m.fs.treatment.disposal_NaCl_mixer.mixed_state[0].flow_mass_phase_comp[ + "Liq", "NaCl" + ], + 1e-2, + ) + + if calclate_m_scaling_factors: + print("calclate_m_scaling_factors\n\n\n") + calculate_scaling_factors(m) + + +def init_system_st2_md(m, **kwargs): + + treat = m.fs.treatment + + treat.feed.initialize() + propagate_state(treat.feed_to_chem_addition) + + init_chem_addition(m, treat.chem_addition) + propagate_state(treat.chem_addition_to_ec) + + init_ec(m, treat.EC) + propagate_state(treat.ec_to_cart_filt) + propagate_state(treat.ec_to_disposal_mix) + + init_cart_filt(m, treat.cart_filt) + propagate_state(treat.cart_filt_to_translator) + propagate_state(treat.cart_filt_to_disposal_mix) + + treat.disposal_ZO_mixer.initialize() + propagate_state(treat.disposal_ZO_mix_to_nacl_translator) + + # NOTE: If the selected temperature is similar to md_disposal temperature, the mixer has issues in the solve + treat.zo_mix_to_nacl_disposal.outlet.temperature[0].fix(300) + treat.zo_mix_to_nacl_disposal.outlet.pressure[0].fix(101325) + treat.zo_mix_to_nacl_disposal.outlet.flow_mass_phase_comp[0, "Vap", "H2O"].fix(0) + treat.zo_mix_to_nacl_disposal.outlet.flow_mass_phase_comp[0, "Sol", "NaCl"].fix(0) + treat.zo_mix_to_nacl_disposal.initialize() + + treat.zo_to_sw_feed.properties_out[0].temperature.fix(300) + treat.zo_to_sw_feed.properties_out[0].pressure.fix(101325) + treat.zo_to_sw_feed.initialize() + + propagate_state(treat.cart_filt_translated_to_md) + + init_md(m, treat.md) + propagate_state(treat.md_to_product) + propagate_state(treat.md_disposal_to_nacl_translator) + + treat.sw_to_nacl_disposal.outlet.flow_mass_phase_comp[0, "Vap", "H2O"].fix(0) + treat.sw_to_nacl_disposal.outlet.flow_mass_phase_comp[0, "Sol", "NaCl"].fix(0) + + propagate_state(treat.disposal_ZO_mix_translated_to_disposal_NaCl_mixer) + propagate_state(treat.md_disposal_translated_to_disposal_NaCl_mixer) + # # NOTE: variable that affects DOF in unclear way + + treat.disposal_NaCl_mixer.initialize() + treat.disposal_NaCl_mixer.mixed_state[0].temperature.fix(300) + treat.disposal_NaCl_mixer.mixed_state[0].pressure.fix(101325) + + propagate_state(treat.mixer_to_normalized_feed) + + +def run_permian_st2_md( + permian_cryst_config, Qin=5, tds=130, water_recovery=0.3, **kwargs +): + """ + Run Permian pretreatment flowsheet + """ + rho = get_stream_density(Qin, tds) + + m = build_permian_st2_md(rho=rho, water_recovery=water_recovery) + treat = m.fs.treatment + + set_operating_conditions_st2_md(m, rho) + set_permian_pretreatment_scaling_st2_md( + m, calclate_m_scaling_factors=True + ) # Doesn't solve without this even before costing + + treat.feed.properties[0].flow_vol + + init_system_st2_md(m) + print(f"DOF = {degrees_of_freedom(m)}") + + results = solver.solve(m) + # print_infeasible_constraints(m) + assert_optimal_termination(results) + + print("\n--------- Before costing solve Completed ---------\n") + report_MD(m, treat.md) + + treat.mec = FlowsheetBlock(dynamic=False) + build_mec( + m, + treat.mec, + prop_package=m.fs.properties_NaCl, + prop_package_vapor=m.fs.properties_vapor, + ) + + set_mec_op_conditions( + m, + treat.mec, + operating_pressures=permian_cryst_config["operating_pressures"], + nacl_yield=permian_cryst_config["nacl_yield"], + ) + init_mec(m, treat.mec) + + unfix_mec(treat.mec) + + treat.cryst_feed_H2O_constraint = Constraint( + expr=treat.mec.unit.inlet.flow_mass_phase_comp[0, "Liq", "H2O"] + == treat.norm_feed.outlet.flow_mass_phase_comp[0, "Liq", "H2O"] + ) + treat.cryst_feed_NaCl_constraint = Constraint( + expr=treat.mec.unit.inlet.flow_mass_phase_comp[0, "Liq", "NaCl"] + == treat.norm_feed.outlet.flow_mass_phase_comp[0, "Liq", "NaCl"] + ) + treat.cryst_feed_temp_constraint = Constraint( + expr=treat.mec.unit.inlet.temperature[0] + == treat.norm_feed.outlet.temperature[0] + ) + treat.cryst_feed_pressure_constraint = Constraint( + expr=treat.mec.unit.inlet.pressure[0] == treat.norm_feed.outlet.pressure[0] + ) + + print("Water", treat.norm_feed.outlet.flow_mass_phase_comp[0, "Liq", "H2O"]()) + print("Nacl", treat.norm_feed.outlet.flow_mass_phase_comp[0, "Liq", "NaCl"]()) + print("Temp", treat.norm_feed.outlet.temperature[0]()) + print("Pressure", treat.norm_feed.outlet.pressure[0]()) + + # mec_rescaling(treat.mec, + # flow_mass_phase_water_total = treat.norm_feed.outlet.flow_mass_phase_comp[0, "Liq", "H2O"]()) + + treat.denorm_cryst_product = Denormalizer_Cryst( + inlet_property_package=m.fs.properties_NaCl, + outlet_property_package=m.fs.properties_NaCl, + ) + + treat.product_NaCl_mixer = Mixer( + property_package=m.fs.properties_NaCl, + num_inlets=2, + inlet_list=["md_product", "cryst_product"], + material_balance_type=MaterialBalanceType.componentPhase, + energy_mixing_type=MixingType.extensive, + momentum_mixing_type=MomentumMixingType.none, + ) + + treat.product = Product(property_package=m.fs.properties_NaCl) + + treat.cryst_product_to_denomalizer = Arc( + source=treat.mec.unit.outlet, + destination=treat.denorm_cryst_product.inlet, + ) # (8) + treat.md_translator_to_product_NaCl_mixer = Arc( + source=treat.sw_to_nacl_product.outlet, + destination=treat.product_NaCl_mixer.md_product, + ) # (7) + treat.cryst_denomalizer_to_product_NaCl_mixer = Arc( + source=treat.denorm_cryst_product.outlet, + destination=treat.product_NaCl_mixer.cryst_product, + ) # (9) + treat.product_NaCl_mixer_to_product = Arc( + source=treat.product_NaCl_mixer.outlet, + destination=treat.product.inlet, + ) # (10) + + TransformationFactory("network.expand_arcs").apply_to(m) + + treat.sw_to_nacl_product.outlet.flow_mass_phase_comp[0, "Vap", "H2O"].fix(0) + treat.sw_to_nacl_product.outlet.flow_mass_phase_comp[0, "Sol", "NaCl"].fix(0) + treat.sw_to_nacl_product.initialize() + + propagate_state(treat.cryst_product_to_denomalizer) + treat.denorm_cryst_product.initialize() + + propagate_state(treat.md_translator_to_product_NaCl_mixer) + propagate_state(treat.cryst_denomalizer_to_product_NaCl_mixer) + + treat.product_NaCl_mixer.outlet.pressure[0].fix() + treat.product_NaCl_mixer.initialize() + + propagate_state(treat.product_NaCl_mixer_to_product) + + treat.product.properties[0].flow_vol + treat.product.properties[0].flow_vol_phase + treat.product.initialize() + + print(f"DOF = {degrees_of_freedom(m)}") + results = solver.solve(m) + # print_infeasible_constraints(m) + assert_optimal_termination(results) + + print(m.fs.treatment.product.display()) + + # Add costing + add_treatment_costing_st2_md(m) + + # iscale.calculate_scaling_factors(m.fs.treatment.md.unit.mp) + # if ( + # iscale.get_scaling_factor( + # m.fs.treatment.md.unit.overall_thermal_power_requirement + # ) + # is None + # ): + # iscale.set_scaling_factor( + # m.fs.treatment.md.unit.overall_thermal_power_requirement, 1e-6 + # ) + + # if ( + # iscale.get_scaling_factor(m.fs.treatment.md.unit.overall_elec_power_requirement) + # is None + # ): + # iscale.set_scaling_factor( + # m.fs.treatment.md.unit.overall_elec_power_requirement, 1e-4 + # ) + + # if ( + # iscale.get_scaling_factor( + # m.fs.treatment.md.unit.mp.get_active_process_blocks()[ + # -1 + # ].fs.vagmd.system_capacity + # ) + # is None + # ): + # iscale.set_scaling_factor( + # m.fs.treatment.md.unit.mp.get_active_process_blocks()[ + # -1 + # ].fs.vagmd.system_capacity, + # 1e6, + # ) + + treat.costing.initialize() + + flow_vol = treat.product.properties[0].flow_vol_phase["Liq"] + treat.costing.electricity_cost.fix(0.0626) + treat.costing.heat_cost.set_value(0.018) + treat.costing.add_LCOW(flow_vol) + treat.costing.add_specific_energy_consumption(flow_vol, name="SEC") + + try: + results = solver.solve(m) + print_infeasible_constraints(m) + except ValueError: + print_infeasible_constraints(m) + assert_optimal_termination(results) + print("\n--------- After costing solve Completed ---------\n") + + print(f"LCOW = {m.fs.treatment.costing.LCOW()}") + + return m + + +if __name__ == "__main__": + + permian_cryst_config = { + "operating_pressures": [ + 0.4455, + 0.2758, + 0.1651, + 0.095, + ], # Operating pressure of each effect (bar) + "nacl_yield": 0.7, # Yield + } + + m = run_permian_st2_md( + Qin=5, tds=130, water_recovery=0.1, permian_cryst_config=permian_cryst_config + ) + + treat = m.fs.treatment + report_MD(m, treat.md) + print(f"DOF = {degrees_of_freedom(m)}") + + # system_recovery = ( + # treat.product.properties[0].flow_vol() / treat.feed.properties[0].flow_vol() + # ) + + # print(f"Pretreatment Recovery: {system_recovery:.2f}") + + print( + f"Inlet flow_vol: {treat.feed.properties[0].flow_vol():.5f} {pyunits.get_units(treat.feed.properties[0].flow_vol)}" + ) + print( + f'Inlet TDS conc: {treat.feed.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.feed.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'EC feed TDS conc: {treat.EC.feed.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.EC.feed.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'EC product TDS conc: {treat.EC.product.properties[0].conc_mass_comp["tds"]():.2f} { pyunits.get_units(treat.EC.product.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'EC disposal TDS conc: {treat.EC.disposal.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.EC.disposal.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'CF feed TDS conc: {treat.cart_filt.product.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.cart_filt.product.properties[0].conc_mass_comp["tds"])}' + ) + + # print( + # f'Product TDS conc: {treat.product.properties[0].conc_mass_phase_comp["Liq", "TDS"]():.2f} {pyunits.get_units(treat.product.properties[0].conc_mass_phase_comp["Liq", "TDS"]())}' + # ) + + # print( + # f'Product flow_vol: {treat.product.properties[0].flow_vol_phase["Liq"]():.2f} {pyunits.get_units(treat.product.properties[0].flow_vol_phase["Liq"])}' + # ) + + print( + f"Translator pressure: {treat.disposal_NaCl_mixer.zo_mixer_state[0].pressure()} Pa" + ) + + # print( + # f'{"Aggregated Heat Cost":<30s}{value(m.fs.treatment.costing.aggregate_flow_costs["heat"]):<20,.2f}{pyunits.get_units(m.fs.treatment.costing.aggregate_flow_costs["heat"])}' + # ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_pretreatment.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_pretreatment.py new file mode 100644 index 00000000..93ad3eb2 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_pretreatment.py @@ -0,0 +1,624 @@ +import pathlib +from pyomo.environ import ( + ConcreteModel, + value, + TransformationFactory, + Param, + Var, + Constraint, + Set, + Expression, + Objective, + NonNegativeReals, + Block, + RangeSet, + check_optimal_termination, + assert_optimal_termination, + units as pyunits, +) +from pyomo.network import Arc, SequentialDecomposition +from pyomo.util.calc_var_value import calculate_variable_from_constraint as cvc + +from idaes.core import FlowsheetBlock, UnitModelCostingBlock +import idaes.core.util.scaling as iscale +from idaes.core import MaterialFlowBasis +from idaes.core.util.scaling import ( + constraint_scaling_transform, + calculate_scaling_factors, + set_scaling_factor, +) +import idaes.logger as idaeslogger +from idaes.core.util.exceptions import InitializationError +from idaes.models.unit_models import ( + Product, + Feed, + StateJunction, + Separator, + Mixer, + MixingType, + MomentumMixingType, +) +from idaes.core.util.model_statistics import * +from idaes.core.util.initialization import propagate_state + +from watertap.core.solvers import get_solver +from watertap_contrib.reflo.core.wt_reflo_database import REFLODatabase +from watertap.core.zero_order_properties import WaterParameterBlock as ZO + + +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.core.util.initialization import * +from watertap.property_models.seawater_prop_pack import SeawaterParameterBlock +from watertap.property_models.water_prop_pack import ( + WaterParameterBlock as SteamParameterBlock, +) +from watertap_contrib.reflo.costing import TreatmentCosting, EnergyCosting +from watertap_contrib.reflo.analysis.case_studies.permian import * + +reflo_dir = pathlib.Path(__file__).resolve().parents[3] +case_study_yaml = f"{reflo_dir}/data/technoeconomic/permian_case_study.yaml" +rho = 1125 * pyunits.kg / pyunits.m**3 +rho_water = 995 * pyunits.kg / pyunits.m**3 + +solver = get_solver() + +__all__ = [ + "build_permian_pretreatment", + "set_operating_conditions", + "add_treatment_costing", + "set_permian_pretreatment_scaling", + "init_system", + "build_and_run_permian_pretreatment", +] + + +def get_stream_density(Qin=5, tds=130, **kwargs): + + x = ConcreteModel() + x.fs = FlowsheetBlock(dynamic=False) + Qin = Qin * pyunits.Mgallons / pyunits.day + flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + x.fs.properties_feed = SeawaterParameterBlock() + x.fs.feed_sw = Feed(property_package=x.fs.properties_feed) + x.fs.feed_sw.properties.calculate_state( + var_args={ + ("flow_vol_phase", "Liq"): flow_in, + ("conc_mass_phase_comp", ("Liq", "TDS")): tds * pyunits.g / pyunits.liter, + ("temperature", None): 298.15, + ("pressure", None): 101325, + }, + hold_state=True, + ) + + x.fs.feed_sw.initialize() + + rho = ( + value(x.fs.feed_sw.properties[0].dens_mass_phase["Liq"]) + * pyunits.kg + / pyunits.m**3 + ) + return rho + + # print(m.fs.feed_sw.properties[0].dens_mass_phase.display()) + + +def build_permian_pretreatment(rho=None, **kwargs): + """ + Build Permian pretreatment flowsheet + """ + if rho is None: + raise ValueError("need a rho!") + m = ConcreteModel() + m.fs = FlowsheetBlock(dynamic=False) + m.db = REFLODatabase() + + m.fs.properties = ZO(solute_list=["tds"]) + m.fs.properties.dens_mass_default = rho + + m.fs.properties_feed = SeawaterParameterBlock() + m.fs.properties_vapor = SteamParameterBlock() + + # Begin building Treatment Block + m.fs.treatment = treat = Block() + + treat.feed = Feed(property_package=m.fs.properties) + treat.desal = StateJunction(property_package=m.fs.properties_feed) + treat.product = Product(property_package=m.fs.properties_feed) + + # Add translator blocks + treat.zo_to_sw_feed = Translator_ZO_to_SW( + inlet_property_package=m.fs.properties, + outlet_property_package=m.fs.properties_feed, + ) + + treat.zo_to_sw_disposal = Translator_ZO_to_SW( + inlet_property_package=m.fs.properties, + outlet_property_package=m.fs.properties_feed, + ) + + # treat.sw_to_zo = Translator_SW_to_ZO( + # inlet_property_package=m.fs.properties_feed, + # outlet_property_package=m.fs.properties, + # ) + + treat.disposal_ZO_mixer = Mixer( + property_package=m.fs.properties, + num_inlets=2, + inlet_list=["ec_disposal", "cart_filt_disposal"], + energy_mixing_type=MixingType.none, + momentum_mixing_type=MomentumMixingType.none, + ) + + treat.disposal_SW_mixer = Mixer( + property_package=m.fs.properties_feed, + num_inlets=1, + inlet_list=["zo_mixer"], + # num_inlets=2, + # inlet_list=["zo_mixer", "mvc_disposal"], + energy_mixing_type=MixingType.none, + momentum_mixing_type=MomentumMixingType.equality, + ) + + treat.chem_addition = FlowsheetBlock(dynamic=False) + build_chem_addition(m, treat.chem_addition) + + treat.EC = FlowsheetBlock(dynamic=False) + build_ec(m, treat.EC) + + treat.cart_filt = FlowsheetBlock(dynamic=False) + build_cartridge_filtration(m, treat.cart_filt) + + treat.DWI = FlowsheetBlock(dynamic=False) + build_dwi(m, treat.DWI, m.fs.properties_feed) + + # BUILD PRODUCT STREAM + # feed > chem_addition > EC > cart_filt > ZO_to_SW_translator > desal unit > product + treat.feed_to_chem_addition = Arc( + source=treat.feed.outlet, destination=treat.chem_addition.feed.inlet + ) + + treat.chem_addition_to_ec = Arc( + source=treat.chem_addition.product.outlet, destination=treat.EC.feed.inlet + ) + + treat.ec_to_cart_filt = Arc( + source=treat.EC.product.outlet, destination=treat.cart_filt.feed.inlet + ) + + # from ZO to SW - feed + treat.cart_filt_to_translator = Arc( + source=treat.cart_filt.product.outlet, destination=treat.zo_to_sw_feed.inlet + ) + + treat.cart_filt_translated_to_desal = Arc( + source=treat.zo_to_sw_feed.outlet, destination=treat.desal.inlet + ) + + treat.desal_to_product = Arc( + source=treat.desal.outlet, destination=treat.product.inlet + ) + + # BUILD DISPOSAL STREAM + # EC > ZO_mixer > ZO_to_SW_translator > disposal_mixer > disposal_mixer > DWI + # cart_filt > ZO_mixer + # desal unit > disposal_mixer + + treat.ec_to_disposal_mix = Arc( + source=treat.EC.disposal.outlet, destination=treat.disposal_ZO_mixer.ec_disposal + ) + + treat.cart_filt_to_disposal_mix = Arc( + source=treat.cart_filt.disposal.outlet, + destination=treat.disposal_ZO_mixer.cart_filt_disposal, + ) + + treat.disposal_ZO_mix_to_translator = Arc( + source=treat.disposal_ZO_mixer.outlet, destination=treat.zo_to_sw_disposal.inlet + ) + + treat.disposal_ZO_mix_translated_to_disposal_SW_mixer = Arc( + source=treat.zo_to_sw_disposal.outlet, + destination=treat.disposal_SW_mixer.zo_mixer, + ) + + treat.disposal_SW_mixer_to_dwi = Arc( + source=treat.disposal_SW_mixer.outlet, destination=treat.DWI.feed.inlet + ) + + TransformationFactory("network.expand_arcs").apply_to(m) + + treat.recovery = Var( + initialize=0.5, + bounds=(0, 1.0001), + units=pyunits.dimensionless, + doc="Overall system recovery", + ) + + # m.fs.treatment.eq_recovery = Constraint( + # expr=m.fs.treatment.recovery * m.fs.treatment.feed.properties[0].flow_vol + # == m.fs.treatment.product.properties[0].flow_vol_phase["Liq"] + # ) + + add_treatment_costing(m) + + return m + + +def set_operating_conditions(m, Qin=5, tds=130, **kwargs): + + global flow_mass_water, flow_mass_tds, flow_in + + Qin = Qin * pyunits.Mgallons / pyunits.day + flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + flow_mass_water = pyunits.convert(Qin * m.rho, to_units=pyunits.kg / pyunits.s) + flow_mass_tds = pyunits.convert( + Qin * tds * pyunits.g / pyunits.liter, to_units=pyunits.kg / pyunits.s + ) + + m.fs.treatment.feed.properties[0].flow_mass_comp["H2O"].fix( + flow_mass_water - flow_mass_tds + ) + m.fs.treatment.feed.properties[0].flow_mass_comp["tds"].fix(flow_mass_tds) + m.fs.treatment.feed.properties[0].conc_mass_comp[...] + + set_chem_addition_op_conditions(m, m.fs.treatment.chem_addition, **kwargs) + set_ec_operating_conditions(m, m.fs.treatment.EC, **kwargs) + set_cart_filt_op_conditions(m, m.fs.treatment.cart_filt) + + +def add_treatment_costing(m): + + m.fs.treatment.costing = TreatmentCosting(case_study_definition=case_study_yaml) + add_chem_addition_costing( + m, m.fs.treatment.chem_addition, flowsheet_costing_block=m.fs.treatment.costing + ) + add_ec_costing(m, m.fs.treatment.EC, flowsheet_costing_block=m.fs.treatment.costing) + add_cartridge_filtration_costing( + m, m.fs.treatment.cart_filt, flowsheet_costing_block=m.fs.treatment.costing + ) + + add_dwi_costing( + m, m.fs.treatment.DWI, flowsheet_costing_block=m.fs.treatment.costing + ) + + m.fs.treatment.costing.cost_process() + + +def set_permian_pretreatment_scaling(m, calclate_m_scaling_factors=False, **kwargs): + + m.fs.properties.set_default_scaling( + "flow_mass_comp", + # 1 / value(flow_mass_water), + 1e-2, + index=("H2O"), + ) + + m.fs.properties.set_default_scaling( + "flow_mass_comp", + # 1 / value(flow_mass_tds), + 0.1, + index=("tds"), + ) + + m.fs.properties_feed.set_default_scaling( + "flow_mass_phase_comp", + 0.1, + index=("Liq", "TDS"), + ) + + m.fs.properties_feed.set_default_scaling( + "flow_mass_phase_comp", + 1e-2, + index=("Liq", "H2O"), + ) + + set_chem_addition_scaling( + m, m.fs.treatment.chem_addition, calc_blk_scaling_factors=True + ) + + set_cart_filt_scaling(m, m.fs.treatment.cart_filt, calc_blk_scaling_factors=True) + + set_ec_scaling(m, m.fs.treatment.EC, calc_blk_scaling_factors=True) + + set_scaling_factor( + m.fs.treatment.product.properties[0].flow_mass_phase_comp["Liq", "H2O"], 1e-2 + ) + set_scaling_factor( + m.fs.treatment.product.properties[0].flow_mass_phase_comp["Liq", "TDS"], 1e5 + ) + + # ZO to SW feed translator + set_scaling_factor( + m.fs.treatment.zo_to_sw_feed.properties_out[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 1e-2, + ) + set_scaling_factor( + m.fs.treatment.zo_to_sw_feed.properties_out[0].flow_mass_phase_comp[ + "Liq", "TDS" + ], + 0.1, + ) + + # ZO to SW disposal translator + set_scaling_factor( + m.fs.treatment.zo_to_sw_disposal.properties_in[0].flow_mass_comp["H2O"], + 1, + ) + set_scaling_factor( + m.fs.treatment.zo_to_sw_disposal.properties_in[0].flow_mass_comp["tds"], + 1, + ) + set_scaling_factor( + m.fs.treatment.zo_to_sw_disposal.properties_out[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 1, + ) + set_scaling_factor( + m.fs.treatment.zo_to_sw_disposal.properties_out[0].flow_mass_phase_comp[ + "Liq", "TDS" + ], + 1, + ) + + # ZO DISPOSAL MIXER + # CF inlet + set_scaling_factor( + m.fs.treatment.disposal_ZO_mixer.cart_filt_disposal_state[0].flow_mass_comp[ + "H2O" + ], + 100, + ) + set_scaling_factor( + m.fs.treatment.disposal_ZO_mixer.cart_filt_disposal_state[0].flow_mass_comp[ + "tds" + ], + 1e8, + ) + + # EC inlet + set_scaling_factor( + m.fs.treatment.disposal_ZO_mixer.ec_disposal_state[0].flow_mass_comp["H2O"], + 1, + ) + set_scaling_factor( + m.fs.treatment.disposal_ZO_mixer.ec_disposal_state[0].flow_mass_comp["tds"], + 1, + ) + + # mixed state + set_scaling_factor( + m.fs.treatment.disposal_ZO_mixer.mixed_state[0].flow_mass_comp["H2O"], + 1, + ) + set_scaling_factor( + m.fs.treatment.disposal_ZO_mixer.mixed_state[0].flow_mass_comp["tds"], + 1, + ) + # SW DISPOSAL MIXER + # ZO mixer inlet + set_scaling_factor( + m.fs.treatment.disposal_SW_mixer.zo_mixer_state[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 1, + ) + set_scaling_factor( + m.fs.treatment.disposal_SW_mixer.zo_mixer_state[0].flow_mass_phase_comp[ + "Liq", "TDS" + ], + 1, + ) + + # mixed state outlet + set_scaling_factor( + m.fs.treatment.disposal_SW_mixer.mixed_state[0].flow_mass_phase_comp[ + "Liq", "H2O" + ], + 1e-2, + ) + set_scaling_factor( + m.fs.treatment.disposal_SW_mixer.mixed_state[0].flow_mass_phase_comp[ + "Liq", "TDS" + ], + 0.1, + ) + + if calclate_m_scaling_factors: + print("calclate_m_scaling_factors\n\n\n") + calculate_scaling_factors(m) + + +def init_system(m, **kwargs): + + treat = m.fs.treatment + + treat.feed.initialize() + propagate_state(treat.feed_to_chem_addition) + + init_chem_addition(m, treat.chem_addition) + propagate_state(treat.chem_addition_to_ec) + + init_ec(m, treat.EC) + propagate_state(treat.ec_to_cart_filt) + propagate_state(treat.ec_to_disposal_mix) + + init_cart_filt(m, treat.cart_filt) + propagate_state(treat.cart_filt_to_translator) + propagate_state(treat.cart_filt_to_disposal_mix) + + treat.disposal_ZO_mixer.initialize() + propagate_state(treat.disposal_ZO_mix_to_translator) + + treat.zo_to_sw_disposal.outlet.temperature[0].fix(298.15) + treat.zo_to_sw_disposal.outlet.pressure[0].fix() + treat.zo_to_sw_disposal.initialize() + + treat.zo_to_sw_feed.properties_out[0].temperature.fix(298.15) + treat.zo_to_sw_feed.properties_out[0].pressure.fix() + treat.zo_to_sw_feed.initialize() + + propagate_state(treat.cart_filt_translated_to_desal) + + treat.desal.initialize() + + propagate_state(treat.desal_to_product) + + propagate_state(treat.disposal_ZO_mix_translated_to_disposal_SW_mixer) + # NOTE: variable that affects DOF in unclear way + treat.disposal_SW_mixer.initialize() + treat.disposal_SW_mixer.mixed_state[0].temperature.fix() + # treat.disposal_SW_mixer.zo_mixer_state[0].pressure.fix() + + propagate_state(treat.disposal_SW_mixer_to_dwi) + + treat.DWI.unit.properties[0].conc_mass_phase_comp + treat.DWI.unit.properties[0].flow_vol_phase + + # NOTE: variables that affect DOF in unclear way + # treat.DWI.feed.properties[0].temperature.fix() + # treat.DWI.feed.properties[0].pressure.fix() + init_dwi(m, treat.DWI) + + treat.product.properties[0].conc_mass_phase_comp + treat.product.properties[0].flow_vol_phase + + treat.product.initialize() + + +def solve_permian_pretreatment(m): + print(f"DOF = {degrees_of_freedom(m)}") + try: + results = solver.solve(m) + assert_optimal_termination(results) + except: + print_infeasible_constraints(m) + + +def build_and_run_permian_pretreatment(Qin=5, tds=130, **kwargs): + """ + Run Permian pretreatment flowsheet + """ + rho = get_stream_density(Qin=Qin, tds=tds) + + m = build_permian_pretreatment(rho=rho) + m.rho = rho + m.fs.optimal_solve_pre = Var(initialize=1) + m.fs.rho = Var(initialize=rho()) + m.fs.rho.fix() + treat = m.fs.treatment + + set_operating_conditions(m, Qin=Qin, tds=tds, **kwargs) + set_permian_pretreatment_scaling(m, calclate_m_scaling_factors=True) + + treat.feed.properties[0].flow_vol + treat.product.properties[0].flow_vol_phase + + init_system(m) + print(f"DOF = {degrees_of_freedom(m)}") + + flow_vol = treat.product.properties[0].flow_vol_phase["Liq"] + treat.costing.electricity_cost.fix(0.0626) + treat.costing.add_LCOW(flow_vol) + treat.costing.add_specific_energy_consumption(flow_vol, name="SEC") + treat.costing.initialize() + + print(f"DOF = {degrees_of_freedom(m)}") + try: + results = solver.solve(m) + assert_optimal_termination(results) + m.fs.optimal_solve_pre.fix(1) + except: + m.fs.optimal_solve_pre.fix(0) + print_infeasible_constraints(m) + + print(f"LCOW = {m.fs.treatment.costing.LCOW()}") + + return m + + +if __name__ == "__main__": + + m = build_and_run_permian_pretreatment(Qin=5) + treat = m.fs.treatment + + print(f"DOF After Solve = {degrees_of_freedom(m)}") + + system_recovery = ( + treat.product.properties[0].flow_vol() / treat.feed.properties[0].flow_vol() + ) + + print(f"Pretreatment Recovery: {system_recovery:.2f}") + + print( + f"Inlet flow_vol: {treat.feed.properties[0].flow_vol():.5f} {pyunits.get_units(treat.feed.properties[0].flow_vol)}" + ) + print( + f'Inlet TDS conc: {treat.feed.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.feed.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'EC feed TDS conc: {treat.EC.feed.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.EC.feed.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'EC product TDS conc: {treat.EC.product.properties[0].conc_mass_comp["tds"]():.2f} { pyunits.get_units(treat.EC.product.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'EC disposal TDS conc: {treat.EC.disposal.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.EC.disposal.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'CF feed TDS conc: {treat.cart_filt.feed.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.cart_filt.feed.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'CF unit inlet TDS conc: {treat.cart_filt.unit.properties_in[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.cart_filt.product.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'CF unit outlet TDS conc: {treat.cart_filt.unit.properties_treated[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.cart_filt.product.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'CF unit waste TDS conc: {treat.cart_filt.unit.properties_byproduct[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.cart_filt.product.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'CF product TDS conc: {treat.cart_filt.product.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.cart_filt.product.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'CF disposal TDS conc: {treat.cart_filt.disposal.properties[0].conc_mass_comp["tds"]():.2f} {pyunits.get_units(treat.cart_filt.product.properties[0].conc_mass_comp["tds"])}' + ) + + print( + f'Product TDS conc: {treat.product.properties[0].conc_mass_phase_comp["Liq", "TDS"]():.2f} {pyunits.get_units(treat.product.properties[0].conc_mass_phase_comp["Liq", "TDS"])}' + ) + + print( + f'Product flow_vol: {treat.product.properties[0].flow_vol_phase["Liq"]():.6f} {pyunits.get_units(treat.product.properties[0].flow_vol_phase["Liq"])}' + ) + + print( + f'DWI flow_vol: {treat.DWI.unit.properties[0].flow_vol_phase["Liq"]():.6f} {pyunits.get_units(treat.DWI.unit.properties[0].flow_vol_phase["Liq"])}' + ) + + print( + f'DWI TDS conc: {treat.DWI.unit.properties[0].conc_mass_phase_comp["Liq", "TDS"]():.2f} {pyunits.get_units(treat.DWI.unit.properties[0].conc_mass_phase_comp["Liq", "TDS"])}' + ) + print(f"DWI pressure: {treat.DWI.feed.properties[0].pressure()} Pa") + + print( + f"Translator pressure: {treat.disposal_SW_mixer.zo_mixer_state[0].pressure()} Pa" + ) + print(f"System recovery: {system_recovery*100:.2f}%") + print( + f"Feed Flow: {pyunits.convert(treat.feed.properties[0].flow_vol,to_units=pyunits.Mgallons / pyunits.day,)():.2f} MGD" + ) + print( + f"Product Flow: {pyunits.convert(treat.product.properties[0].flow_vol_phase['Liq'],to_units=pyunits.Mgallons / pyunits.day,)():.2f} MGD" + ) diff --git a/src/watertap_contrib/reflo/core/solar_energy_base.py b/src/watertap_contrib/reflo/core/solar_energy_base.py index 5e16593b..d8fda269 100644 --- a/src/watertap_contrib/reflo/core/solar_energy_base.py +++ b/src/watertap_contrib/reflo/core/solar_energy_base.py @@ -26,6 +26,7 @@ from idaes.core import UnitModelBlockData, declare_process_block_class from idaes.core.util.model_statistics import degrees_of_freedom from idaes.core.util.exceptions import InitializationError +from idaes.core.surrogate.metrics import compute_fit_metrics from idaes.core.surrogate.surrogate_block import SurrogateBlock from idaes.core.surrogate.pysmo_surrogate import PysmoRBFTrainer, PysmoSurrogate from idaes.core.surrogate.sampling.data_utils import split_training_validation @@ -39,6 +40,7 @@ class SolarModelType(StrEnum): surrogate = "surrogate" physical = "physical" + pysam = "pysam" @declare_process_block_class("SolarEnergyBase") @@ -84,6 +86,15 @@ class SolarEnergyBaseData(UnitModelBlockData): doc="""User provided surrogate model .json file.""", ), ) + CONFIG.declare( + "surrogate_filename_save", + ConfigValue( + default=None, + domain=str, + description="Filename used to save surrogate model to .json", + doc="""Filename used to save surrogate model file to .json""", + ), + ) CONFIG.declare( "dataset_filename", ConfigValue( @@ -149,11 +160,11 @@ class SolarEnergyBaseData(UnitModelBlockData): is scaled to the largest value in the dataset.""", ), ) + # TODO: do we need this number_samples config? CONFIG.declare( "number_samples", ConfigValue( - default=100, - domain=int, + default=None, description="Number of samples from dataset to build surrogate", doc="""Number of samples to use from dataset to build surrogate model.""", ), @@ -167,6 +178,31 @@ class SolarEnergyBaseData(UnitModelBlockData): doc=""""Fraction of dataset to use as training data for surrogate""", ), ) + CONFIG.declare( + "rbf_basis_function", + ConfigValue( + default="gaussian", + description="Basis function to use for PysmoRBFTrainer config", + doc=""""Basis function to use for PysmoRBFTrainer config""", + ), + ) + CONFIG.declare( + "rbf_solution_method", + ConfigValue( + default="algebraic", + description="Solution method to use for PysmoRBFTrainer config", + doc=""""Solution method to use for PysmoRBFTrainer config""", + ), + ) + CONFIG.declare( + "rbf_regularization", + ConfigValue( + default=True, + domain=bool, + description="Flag to indicate to use regularization for PysmoRBFTrainer config", + doc=""""Flag to indicate to use regularization for PysmoRBFTrainer config""", + ), + ) def build(self): super().build() @@ -207,7 +243,7 @@ def build(self): if self.config.dataset_bounds == dict(): self.dataset_bounds = self.input_bounds else: - self.datset_bounds = self.config.dataset_bounds + self.dataset_bounds = self.config.dataset_bounds def initialize( self, state_args=None, outlvl=idaeslog.NOTSET, solver=None, optarg=None @@ -252,13 +288,20 @@ def create_rbf_surrogate(self): ) # Set PySMO options - # TODO: make this CONFIG for base? - self.trainer.config.basis_function = "gaussian" # default = gaussian - self.trainer.config.solution_method = "algebraic" # default = algebraic - self.trainer.config.regularization = True # default = True + self.trainer.config.basis_function = ( + self.config.rbf_basis_function + ) # default = gaussian + self.trainer.config.solution_method = ( + self.config.rbf_solution_method + ) # default = algebraic + self.trainer.config.regularization = ( + self.config.rbf_regularization + ) # default = True + self.log.info( f"Training RBF Surrogate with {self.trainer.config.basis_function} basis function and {self.trainer.config.solution_method} solution method." ) + self.trained_rbf = self.trainer.train_surrogate() self.log.info(f"Training Complete.") @@ -276,11 +319,18 @@ def create_rbf_surrogate(self): self.input_bounds, ) - self.surrogate_file = self.config.dataset_filename.replace(".pkl", "") - for k, v in self.input_bounds.items(): - self.surrogate_file += f"_{k}_{v[0]}_{v[1]}" + if self.config.surrogate_filename_save is None: + self.surrogate_filename_save = self.config.dataset_filename.replace( + ".pkl", "" + ) + else: + self.surrogate_filename_save = self.config.surrogate_filename_save.replace( + ".json", "" + ) - _ = self.surrogate.save_to_file(self.surrogate_file + ".json", overwrite=True) + _ = self.surrogate.save_to_file( + self.surrogate_filename_save + ".json", overwrite=True + ) sys.stdout = oldstdout @@ -304,9 +354,14 @@ def get_surrogate_data( self.pickle_df = self.pickle_df[ (self.pickle_df[col] >= lo) & (self.pickle_df[col] <= hi) ].copy() - self.data = self.pickle_df.sample( - n=self.config.number_samples, random_state=len(self.pickle_df) - ) + + if self.config.number_samples is None: + self.data = self.pickle_df + else: + self.data = self.pickle_df.sample( + n=self.config.number_samples, random_state=len(self.pickle_df) + ) + self.data_training, self.data_validation = split_training_validation( self.data, self.config.training_fraction, seed=len(self.data) ) @@ -366,7 +421,6 @@ def add_surrogate_variables(self): self.surrogate_outputs = [] for output_var_name, bounds in self.output_bounds.items(): - # TODO: Allow user to set bounds for output variables? units = self.output_units[output_var_name] v_out = Var( initialize=1e4, @@ -377,18 +431,21 @@ def add_surrogate_variables(self): self.surrogate_outputs.append(v_out) self.add_component(output_var_name, v_out) + def compute_fit_metrics(self): + return compute_fit_metrics(self.surrogate, self.data) + def load_surrogate(self): stream = StringIO() oldstdout = sys.stdout sys.stdout = stream if self.config.surrogate_model_file is not None: - self.surrogate_file = self.config.surrogate_model_file + self.surrogate_model_file = self.config.surrogate_model_file self.log.info("Loading surrogate.") self.surrogate_blk = SurrogateBlock(concrete=True) - self.surrogate = PysmoSurrogate.load_from_file(self.surrogate_file) + self.surrogate = PysmoSurrogate.load_from_file(self.surrogate_model_file) self.surrogate_blk.build_model( self.surrogate, input_vars=self.surrogate_inputs, diff --git a/src/watertap_contrib/reflo/costing/solar/trough_surrogate.py b/src/watertap_contrib/reflo/costing/solar/trough_surrogate.py index 54ead501..121b10eb 100644 --- a/src/watertap_contrib/reflo/costing/solar/trough_surrogate.py +++ b/src/watertap_contrib/reflo/costing/solar/trough_surrogate.py @@ -23,18 +23,32 @@ def build_trough_surrogate_cost_param_block(blk): costing = blk.parent_block() - blk.base_storage_hours = pyo.Param( - mutable=True, - initialize=6, - units=pyo.units.hour, - doc="Hours of storage that capital cost per capacity is based on", + blk.cost_per_land_area = pyo.Var( + initialize=10000, + units=costing.base_currency / pyo.units.acre, + bounds=(0, None), + doc="Cost per acre of land", + ) + + blk.cost_per_total_aperture_area = pyo.Var( + initialize=373, + units=costing.base_currency / pyo.units.m**2, + bounds=(0, None), + doc="Cost per m2 of total aperture area (includes site improvement 16 $/m2, solar field 297 $/m2, HTF system 60 $/m2)", ) - blk.cost_per_capacity_capital = pyo.Var( - initialize=560, + blk.cost_per_heat_sink = pyo.Var( + initialize=120, units=costing.base_currency / pyo.units.kW, bounds=(0, None), - doc="Cost per kW (thermal) for the trough plant, assuming six hours storage", + doc="Cost for expenses related to installation of the heat sink, including labor and equipment per kWh (thermal) heat load", + ) + + blk.cost_per_balance_of_plant = pyo.Var( + initialize=90, + units=costing.base_currency / pyo.units.kW, + bounds=(0, None), + doc="Cost per thermal kilowatt of heat sink capacity for expenses related to installation of the heat sink, including labor and equipment", ) blk.cost_per_storage_capital = pyo.Var( @@ -51,6 +65,13 @@ def build_trough_surrogate_cost_param_block(blk): doc="Fraction of direct costs for contingency", ) + blk.indirect_frac_direct_cost = pyo.Var( + initialize=0.11, + units=pyo.units.dimensionless, + bounds=(0, 1), + doc="Fraction of direct costs for indirect costs associated with engineer-procure-construction (EPC)", + ) + blk.tax_frac_direct_cost = pyo.Var( initialize=0.05, units=pyo.units.dimensionless, @@ -59,15 +80,15 @@ def build_trough_surrogate_cost_param_block(blk): ) blk.fixed_operating_by_capacity = pyo.Var( - initialize=8, - units=costing.base_currency / (pyo.units.kW * costing.base_period), + initialize=103758, + units=costing.base_currency, bounds=(0, None), - doc="Fixed operating cost of trough plant per kW capacity", + doc="Fixed operating cost of trough plant in SAM. Not a function of electricity generated", ) blk.variable_operating_by_generation = pyo.Var( - initialize=0.001, - units=costing.base_currency / (pyo.units.kWh * costing.base_period), + initialize=0.002, + units=costing.base_currency / (pyo.units.kWh), bounds=(0, None), doc="Variable operating cost of trough plant per kWh generated", ) @@ -93,20 +114,37 @@ def cost_trough_surrogate(blk): doc="Direct cost of trough plant", ) + blk.indirect_cost = pyo.Var( + initialize=0, + units=blk.config.flowsheet_costing_block.base_currency, + bounds=(0, None), + doc="Inirect cost of trough plant", + ) + blk.direct_cost_constraint = pyo.Constraint( expr=blk.direct_cost == ( - pyo.units.convert(trough.heat_load, to_units=pyo.units.kW) + trough.total_aperture_area * trough_params.cost_per_total_aperture_area + + pyo.units.convert(trough.heat_load, to_units=pyo.units.kW) + * trough.hours_storage + * trough_params.cost_per_storage_capital + + pyo.units.convert(trough.heat_load, to_units=pyo.units.kW) * ( - trough_params.cost_per_capacity_capital - - trough_params.base_storage_hours - * trough_params.cost_per_storage_capital - + trough.hours_storage * trough_params.cost_per_storage_capital + trough_params.cost_per_heat_sink + + trough_params.cost_per_balance_of_plant ) ) * (1 + trough_params.contingency_frac_direct_cost) ) + blk.indirect_cost_constraint = pyo.Constraint( + expr=blk.indirect_cost + == ( + blk.direct_cost * trough_params.indirect_frac_direct_cost + + trough.land_area * trough_params.cost_per_land_area + ) + ) + blk.costing_package.add_cost_factor(blk, None) blk.capital_cost_constraint = pyo.Constraint( expr=blk.capital_cost @@ -115,9 +153,7 @@ def cost_trough_surrogate(blk): ) blk.fixed_operating_cost_constraint = pyo.Constraint( - expr=blk.fixed_operating_cost - == trough_params.fixed_operating_by_capacity - * pyo.units.convert(trough.heat_load, to_units=pyo.units.kW) + expr=blk.fixed_operating_cost == trough_params.fixed_operating_by_capacity ) blk.variable_operating_cost_constraint = pyo.Constraint( diff --git a/src/watertap_contrib/reflo/costing/units/multi_effect_crystallizer.py b/src/watertap_contrib/reflo/costing/units/multi_effect_crystallizer.py index f5191ebe..070ffcd4 100644 --- a/src/watertap_contrib/reflo/costing/units/multi_effect_crystallizer.py +++ b/src/watertap_contrib/reflo/costing/units/multi_effect_crystallizer.py @@ -23,6 +23,11 @@ class MultiEffectCrystallizerCostType(StrEnum): volume_basis = "volume_basis" +class WorkCostType(StrEnum): + heat = "heat" + steam = "steam" + + def build_recovered_nacl_cost_param_block(blk): blk.cost = pyo.Param( @@ -126,7 +131,9 @@ def build_multi_effect_crystallizer_cost_param_block(blk): parameter_block_name="multi_effect_crystallizer", ) def cost_multi_effect_crystallizer( - blk, cost_type=MultiEffectCrystallizerCostType.mass_basis + blk, + cost_type=MultiEffectCrystallizerCostType.mass_basis, + cost_work_as=WorkCostType.steam, ): """ Function for costing the forced circulation crystallizer by the mass flow of produced crystals. @@ -134,12 +141,15 @@ def cost_multi_effect_crystallizer( Args: cost_type: Option for crystallizer cost function type - volume or mass basis + cost_work_as: Option for costing the work done in first effect as either the cost of the steam or the cost + of heat to produce the steam """ global costing_package costing_package = blk.costing_package make_capital_cost_var(blk) costing_package.add_cost_factor(blk, "TIC") + costing_package.cost_work_as = cost_work_as if cost_type == MultiEffectCrystallizerCostType.mass_basis: effect_costing_method = cost_crystallizer_effect_by_crystal_mass @@ -352,7 +362,13 @@ def _cost_effect_flows(effect, effect_number): ) if effect_number == 1: - costing_package.cost_flow( - effect.heating_steam[0].flow_vol_phase["Vap"], - "steam", - ) + if costing_package.cost_work_as == WorkCostType.steam: + costing_package.cost_flow( + effect.heating_steam[0].flow_vol_phase["Vap"], + "steam", + ) + if costing_package.cost_work_as == WorkCostType.heat: + costing_package.cost_flow( + pyo.units.convert(effect.work_mechanical[0], to_units=pyo.units.kW), + "heat", + ) diff --git a/src/watertap_contrib/reflo/data/technoeconomic/cartridge_filtration.yaml b/src/watertap_contrib/reflo/data/technoeconomic/cartridge_filtration.yaml new file mode 100644 index 00000000..4b360635 --- /dev/null +++ b/src/watertap_contrib/reflo/data/technoeconomic/cartridge_filtration.yaml @@ -0,0 +1,36 @@ +default: + recovery_frac_mass_H2O: + value: 0.9999 + units: dimensionless + reference: Defined based on the Carlsbad case study data. + default_removal_frac_mass_comp: + value: 0 + units: dimensionless + removal_frac_mass_comp: + nonvolatile_toc: + value: 0.2 + units: dimensionless + constituent_longform: Nonvolatile TOC + tss: + value: 0.9 + units: dimensionless + constituent_longform: Total Suspended Solids (TSS) + tds: + value: 0. + units: dimensionless + constituent_longform: Total Dissolved Solids (TDS) + energy_electric_flow_vol_inlet: + value: 0.0002 # todo: revisit this value later on + units: kWh/m^3 + capital_cost: + basis: flow_vol + cost_factor: None + reference_state: + value: 1 + units: Mgallons/day + capital_a_parameter: + value: 0.72557e6 + units: USD_2014 + capital_b_parameter: + value: 0.5862 + units: dimensionless \ No newline at end of file diff --git a/src/watertap_contrib/reflo/data/technoeconomic/chemical_addition.yaml b/src/watertap_contrib/reflo/data/technoeconomic/chemical_addition.yaml new file mode 100644 index 00000000..bfba6ee0 --- /dev/null +++ b/src/watertap_contrib/reflo/data/technoeconomic/chemical_addition.yaml @@ -0,0 +1,51 @@ +default: + # This is a placeholder that is required by the database class and testing + chemical_dosage: + value: 1 + units: mg/L + solution_density: + value: 1000 + units: kg/m^3 + ratio_in_solution: + value: 0.5 + units: dimensionless +sulfuric_acid: + chemical_dosage: + value: 10 + units: mg/L + solution_density: + value: 1781 + units: kg/m^3 + ratio_in_solution: + value: 1 + units: dimensionless + capital_cost: + basis: chemical_flow_mass + cost_factor: TPEC + capital_a_parameter: + value: 900.97 + units: USD_2007 + capital_b_parameter: + value: 0.6179 + units: dimensionless +hydrogen_peroxide: + chemical_dosage: + value: 10 + units: mg/L + solution_density: + value: 1781 + units: kg/m^3 + ratio_in_solution: + value: 1 + units: dimensionless + capital_cost: + basis: chemical_flow_mass + cost_factor: TPEC + capital_a_parameter: + value: 900.97 + units: USD_2007 + reference: Sulfuric acid addition costing params; McGivney & Kawamura + capital_b_parameter: + value: 0.6179 + units: dimensionless + reference: Sulfuric acid addition costing params; McGivney & Kawamura \ No newline at end of file diff --git a/src/watertap_contrib/reflo/data/technoeconomic/electrocoagulation.yaml b/src/watertap_contrib/reflo/data/technoeconomic/electrocoagulation.yaml index 648800d6..d6e69f45 100644 --- a/src/watertap_contrib/reflo/data/technoeconomic/electrocoagulation.yaml +++ b/src/watertap_contrib/reflo/data/technoeconomic/electrocoagulation.yaml @@ -196,10 +196,10 @@ permian: units: dimensionless removal_frac_mass_comp: tds: - value: 0.7 + value: 0.11 units: dimensionless silica: - value: 0.7 + value: 0.95 units: dimensionless capital_cost: cost_factor: TPEC diff --git a/src/watertap_contrib/reflo/data/technoeconomic/permian_case_study.yaml b/src/watertap_contrib/reflo/data/technoeconomic/permian_case_study.yaml new file mode 100644 index 00000000..16eba766 --- /dev/null +++ b/src/watertap_contrib/reflo/data/technoeconomic/permian_case_study.yaml @@ -0,0 +1,7 @@ +base_currency: USD_2023 +base_period: year +defined_flows: + hydrogen_peroxide: + value: 1.53 + units: USD_2020/kg + purity: 1 \ No newline at end of file diff --git a/src/watertap_contrib/reflo/solar_models/surrogate/trough/data/trough_heat_load_1_50_hours_storage_24.pkl b/src/watertap_contrib/reflo/solar_models/surrogate/trough/data/trough_heat_load_1_50_hours_storage_24.pkl new file mode 100644 index 00000000..c462f3ef Binary files /dev/null and b/src/watertap_contrib/reflo/solar_models/surrogate/trough/data/trough_heat_load_1_50_hours_storage_24.pkl differ diff --git a/src/watertap_contrib/reflo/solar_models/surrogate/trough/data/trough_heat_load_1_50_hours_storage_24_T_loop_out_150.pkl b/src/watertap_contrib/reflo/solar_models/surrogate/trough/data/trough_heat_load_1_50_hours_storage_24_T_loop_out_150.pkl new file mode 100644 index 00000000..7bccf3ff Binary files /dev/null and b/src/watertap_contrib/reflo/solar_models/surrogate/trough/data/trough_heat_load_1_50_hours_storage_24_T_loop_out_150.pkl differ diff --git a/src/watertap_contrib/reflo/solar_models/surrogate/trough/data/trough_heat_load_1_50_hours_storage_24_T_loop_out_200.pkl b/src/watertap_contrib/reflo/solar_models/surrogate/trough/data/trough_heat_load_1_50_hours_storage_24_T_loop_out_200.pkl new file mode 100644 index 00000000..c8d8dbb7 Binary files /dev/null and b/src/watertap_contrib/reflo/solar_models/surrogate/trough/data/trough_heat_load_1_50_hours_storage_24_T_loop_out_200.pkl differ diff --git a/src/watertap_contrib/reflo/solar_models/surrogate/trough/trough_surrogate.py b/src/watertap_contrib/reflo/solar_models/surrogate/trough/trough_surrogate.py index 400438ad..87f8a7c6 100644 --- a/src/watertap_contrib/reflo/solar_models/surrogate/trough/trough_surrogate.py +++ b/src/watertap_contrib/reflo/solar_models/surrogate/trough/trough_surrogate.py @@ -13,6 +13,8 @@ import pandas as pd from pyomo.environ import ( + Var, + Param, value, Expression, Constraint, @@ -48,6 +50,24 @@ def build(self): self.add_surrogate_variables() self.get_surrogate_data() + self.row_spacing = Param( + initialize=15, + units=pyunits.m, + mutable=True, + doc="Spacing between rows of collectors ", + ) + + self.maximum_sca_width = Param( + initialize=8.2, + units=pyunits.m, + mutable=True, + doc="Width of solar collector assembly (sca) aperture", + ) + + self.land_area = Var( + initialize=0, units=pyunits.acre, bounds=(0, None), doc="Land area in acres" + ) + self.heat_annual = Expression( expr=self.heat_annual_scaled / self.heat_annual_scaling, doc="Annual heat generated by trough in kWh", @@ -58,6 +78,11 @@ def build(self): doc="Annual electricity consumed by trough in kWh", ) + self.total_aperture_area = Expression( + expr=self.total_aperture_area_scaled / self.total_aperture_area_scaling, + doc="Annual electricity consumed by trough in kWh", + ) + if self.config.surrogate_model_file is not None: self.surrogate_file = self.config.surrogate_model_file self.load_surrogate() @@ -76,6 +101,16 @@ def build(self): * pyunits.convert(1 * pyunits.hour, to_units=pyunits.year) ) + # Solar Field Area (acres) = Actual Aperture (m²) × Row Spacing (m) / Maximum SCA Width (m) × 0.0002471 (acres/m²) + + self.land_area_constraint = Constraint( + expr=self.land_area + == pyunits.convert( + self.total_aperture_area * self.row_spacing / self.maximum_sca_width, + to_units=pyunits.acre, + ) + ) + def calculate_scaling_factors(self): if iscale.get_scaling_factor(self.hours_storage) is None: sf = iscale.get_scaling_factor(self.hours_storage, default=1) @@ -105,6 +140,15 @@ def calculate_scaling_factors(self): sf = iscale.get_scaling_factor(self.electricity, default=1e-3, warning=True) iscale.set_scaling_factor(self.electricity, sf) + + if iscale.get_scaling_factor(self.total_aperture_area) is None: + sf = iscale.get_scaling_factor(self.total_aperture_area, default=1e-6, warning=True) + iscale.set_scaling_factor(self.total_aperture_area, sf) + + if iscale.get_scaling_factor(self.land_area) is None: + sf = iscale.get_scaling_factor(self.land_area, default=1e-1, warning=True) + iscale.set_scaling_factor(self.land_area, sf) + def initialize_build( self, outlvl=idaeslog.NOTSET,