diff --git a/.github/workflows/checks.yml b/.github/workflows/checks.yml index cd07f832..fe6a6cd2 100644 --- a/.github/workflows/checks.yml +++ b/.github/workflows/checks.yml @@ -51,7 +51,7 @@ jobs: - noneditable include: - os: linux - os-version: ubuntu-latest + os-version: ubuntu-22.04 - os: win64 os-version: windows-latest steps: diff --git a/.gitignore b/.gitignore index 316913d4..9eade4c6 100644 --- a/.gitignore +++ b/.gitignore @@ -150,3 +150,10 @@ auto-save-list # other *.json +*.h5 +*.svg +*.jpg +*.csv +*.png +*.pkl +*.rtf \ No newline at end of file diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_RPT_1.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_RPT_1.py index a73758c0..a72cf7f1 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_RPT_1.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_RPT_1.py @@ -68,7 +68,7 @@ def main(): # box_solve_problem(m) # solve(m, debug=True) # scale_costing(m) - optimize(m, ro_mem_area=None, water_recovery=0.8, grid_frac=None, objective="LCOW") + optimize(m, ro_mem_area=20000, water_recovery=0.8, grid_frac=None, objective="LCOT") solve(m, debug=False) # # display_flow_table(m) # display_system_stream_table(m) @@ -89,8 +89,10 @@ def main(): def build_sweep( grid_frac=None, - heat_price=None, + elec_price=None, water_recovery=None, + ro_mem_area=None, + objective="LCOT", ): m = build_system(RE=True) @@ -102,7 +104,14 @@ def build_sweep( init_system(m) add_costing(m) scale_costing(m) - optimize(m, ro_mem_area=None, water_recovery=0.8, grid_frac=None, objective="LCOW") + optimize( + m, + ro_mem_area=ro_mem_area, + water_recovery=water_recovery, + grid_frac=grid_frac, + elec_price=elec_price, + objective=objective, + ) return m @@ -171,7 +180,7 @@ def build_treatment(m): build_ec(m, treatment.EC, prop_package=m.fs.UF_properties) build_UF(m, treatment.UF, prop_package=m.fs.UF_properties) - build_ro(m, treatment.RO, prop_package=m.fs.RO_properties) + build_ro(m, treatment.RO, prop_package=m.fs.RO_properties, number_of_stages=1) build_DWI(m, treatment.DWI, prop_package=m.fs.RO_properties) m.fs.units = [ @@ -311,6 +320,7 @@ def add_energy_costing(m): ) energy.costing.cost_process() + energy.costing.add_LCOE() energy.costing.initialize() @@ -323,11 +333,11 @@ def add_costing(m): add_energy_costing(m) m.fs.costing = REFLOSystemCosting() - m.fs.costing.base_currency = pyunits.USD_2020 m.fs.costing.cost_process() m.fs.costing.add_annual_water_production(treatment.product.properties[0].flow_vol) m.fs.costing.add_LCOW(treatment.product.properties[0].flow_vol) + m.fs.costing.add_LCOT(treatment.product.properties[0].flow_vol) m.fs.costing.initialize() @@ -508,7 +518,7 @@ def init_treatment(m, verbose=True, solver=None): assert_no_degrees_of_freedom(m) treatment.feed.initialize(optarg=optarg) propagate_state(treatment.feed_to_translator) - + report_MCAS_stream_conc(m, treatment.feed.properties[0.0]) treatment.MCAS_to_TDS_translator.initialize(optarg=optarg) propagate_state(treatment.translator_to_EC) @@ -531,7 +541,7 @@ def init_treatment(m, verbose=True, solver=None): # propagate_state(treatment.ro_to_dwi) treatment.product.initialize(optarg=optarg) - # init_DWI(m, treatment.DWI) + init_DWI(m, treatment.DWI) display_system_stream_table(m) @@ -612,6 +622,7 @@ def optimize( fixed_pressure=None, ro_mem_area=None, grid_frac=None, + elec_price=None, objective="LCOW", ): treatment = m.fs.treatment @@ -620,6 +631,8 @@ def optimize( if objective == "LCOW": m.fs.lcow_objective = Objective(expr=m.fs.costing.LCOW) + elif objective == "LCOT": + m.fs.lcow_objective = Objective(expr=m.fs.costing.LCOT) else: m.fs.membrane_area_objective = Objective(expr=treatment.RO.stage[1].module.area) @@ -651,8 +664,12 @@ def optimize( if ro_mem_area is not None: print(f"\n------- Fixed RO Membrane Area at {ro_mem_area} -------\n") + # for idx, stage in treatment.RO.stage.items(): + # stage.module.area.fix(ro_mem_area) + treatment.RO.total_membrane_area.fix(ro_mem_area) for idx, stage in treatment.RO.stage.items(): - stage.module.area.fix(ro_mem_area) + stage.module.area.unfix() + stage.module.area.setub(1e6) else: lower_bound = 1e3 upper_bound = 2e5 @@ -669,6 +686,24 @@ def optimize( m.fs.energy.pv.design_size.unfix() m.fs.energy.pv.annual_energy.unfix() + if elec_price is not None: + m.fs.costing.frac_elec_from_grid.unfix() + m.fs.energy.pv.design_size.unfix() + m.fs.energy.pv.annual_energy.unfix() + + for idx, stage in treatment.RO.stage.items(): + stage.module.width.setub(5000) + stage.module.feed_side.velocity[0, 0].unfix() + stage.module.feed_side.velocity[0, 1].setlb(0.0) + stage.module.feed_side.K.setlb(1e-6) + stage.module.feed_side.friction_factor_darcy.setub(50) + stage.module.flux_mass_phase_comp.setub(1) + # stage.module.flux_mass_phase_comp.setlb(1e-5) + stage.module.feed_side.cp_modulus.setub(10) + stage.module.rejection_phase_comp.setlb(1e-4) + stage.module.feed_side.N_Re.setlb(1) + stage.module.recovery_mass_phase_comp.setlb(1e-7) + def report_MCAS_stream_conc(m, stream): solute_set = m.fs.MCAS_properties.solute_set diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_RPT_2.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_RPT_2.py index 193da8c9..b64e5b62 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_RPT_2.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_RPT_2.py @@ -66,17 +66,20 @@ def main(): init_system(m) add_costing(m) scale_costing(m) - box_solve_problem(m) - # solve(m, debug=True) + # box_solve_problem(m) + # # solve(m, debug=True) - optimize(m, water_recovery=0.35, grid_frac_heat=0.5, objective="LCOW") + optimize(m, water_recovery=0.35, heat_price=0.005, objective="LCOW") solve(m, debug=True) - display_system_stream_table(m) - report_LTMED(m) - report_pump(m, m.fs.treatment.pump) + # display_system_stream_table(m) + # report_LTMED(m) + # report_pump(m, m.fs.treatment.pump) report_fpc(m) - display_costing_breakdown(m) + m.fs.costing.LCOW.display() + m.fs.energy.costing.LCOH.display() + m.fs.costing.LCOT.display() + # display_costing_breakdown(m) return m @@ -99,6 +102,7 @@ def build_sweep( m, water_recovery=water_recovery, grid_frac_heat=grid_frac_heat, + heat_price=heat_price, objective="LCOW", ) @@ -302,6 +306,7 @@ def add_energy_costing(m): add_fpc_costing(m, energy.costing) energy.costing.cost_process() + energy.costing.add_LCOH() energy.costing.initialize() @@ -313,11 +318,11 @@ def add_costing(m): add_energy_costing(m) m.fs.costing = REFLOSystemCosting() - # m.fs.costing.base_currency = pyunits.USD_2020 m.fs.costing.cost_process() m.fs.costing.add_annual_water_production(treatment.product.properties[0].flow_vol) m.fs.costing.add_LCOW(treatment.product.properties[0].flow_vol) + m.fs.costing.add_LCOT(treatment.product.properties[0].flow_vol) m.fs.costing.initialize() @@ -605,6 +610,8 @@ def optimize( if objective == "LCOW": m.fs.lcow_objective = Objective(expr=m.fs.costing.LCOW) + if objective == "LCOT": + m.fs.lcot_objective = Objective(expr=m.fs.costing.LCOT) if water_recovery is not None: print(f"\n------- Fixed Recovery at {100*water_recovery}% -------") @@ -616,7 +623,8 @@ def optimize( m.fs.costing.frac_heat_from_grid.fix(grid_frac_heat) if heat_price is not None: - m.fs.energy.FPC.heat_load.unfix() + energy.FPC.heat_load.unfix() + energy.FPC.hours_storage.unfix() m.fs.costing.frac_heat_from_grid.unfix() m.fs.costing.heat_cost_buy.fix(heat_price) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_RPT_3.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_RPT_3.py new file mode 100644 index 00000000..126fe898 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_RPT_3.py @@ -0,0 +1,578 @@ +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, + REFLOSystemCosting, +) + +from watertap_contrib.reflo.analysis.case_studies.KBHDP.components.MD import * +from watertap_contrib.reflo.analysis.case_studies.KBHDP.components.FPC import * +from watertap_contrib.reflo.analysis.case_studies.KBHDP.components.deep_well_injection import * +from watertap_contrib.reflo.analysis.case_studies.KBHDP.utils import * +import pandas as pd + +import pathlib + +reflo_dir = pathlib.Path(__file__).resolve().parents[3] +case_study_yaml = f"{reflo_dir}/data/technoeconomic/kbhdp_case_study.yaml" + +__all__ = [ + "build_system", + "add_connections", + "add_costing", + "add_system_costing", + "set_inlet_conditions", + "set_operating_conditions", + "init_system", + "print_results_summary", +] + +__location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__))) +weather_file = os.path.join(__location__, "el_paso_texas-KBHDP-weather.csv") +param_file = os.path.join(__location__, "swh-kbhdp.json") + + +def propagate_state(arc): + _prop_state(arc) + + +def build_system(Qin=4, Cin=12, water_recovery=0.5): + + m = ConcreteModel() + m.fs = FlowsheetBlock() + m.fs.treatment = Block() + m.fs.energy = Block() + + 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 + + m.fs.treatment.costing = TreatmentCosting() + m.fs.energy.costing = EnergyCosting() + + # Property package + m.fs.properties = SeawaterParameterBlock() + + # Create feed, product and concentrate state blocks + m.fs.treatment.feed = Feed(property_package=m.fs.properties) + m.fs.treatment.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.treatment.md = FlowsheetBlock() + + build_md( + m, + m.fs.treatment.md, + ) + m.fs.treatment.dwi = FlowsheetBlock() + build_DWI(m, m.fs.treatment.dwi, m.fs.properties) + + m.fs.energy.FPC = FlowsheetBlock() + build_fpc(m) + + return m + + +def add_connections(m): + + treatment = m.fs.treatment + + treatment.feed_to_md = Arc( + source=treatment.feed.outlet, destination=treatment.md.feed.inlet + ) + + treatment.md_to_product = Arc( + source=treatment.md.permeate.outlet, destination=treatment.product.inlet + ) + + treatment.md_to_dwi = Arc( + source=treatment.md.concentrate.outlet, + destination=treatment.dwi.unit.inlet, + ) + + TransformationFactory("network.expand_arcs").apply_to(m) + + +def add_costing(m, treatment_costing_block=None, energy_costing_block=None): + # Solving the system before adding costing + # solver = SolverFactory("ipopt") + if treatment_costing_block is None: + treatment_costing_block = m.fs.treatment.costing + if energy_costing_block is None: + energy_costing_block = m.fs.energy.costing + solver = get_solver() + solve(m, solver=solver, tee=False) + add_fpc_costing(m, costing_block=energy_costing_block) + add_md_costing(m.fs.treatment.md.mp, treatment_costing_block) + add_DWI_costing( + m.fs.treatment, m.fs.treatment.dwi, costing_blk=treatment_costing_block + ) + # System costing + treatment_costing_block.cost_process() + energy_costing_block.cost_process() + m.fs.costing = REFLOSystemCosting() + m.fs.costing.cost_process() + + print("\n--------- INITIALIZING SYSTEM COSTING ---------\n") + + treatment_costing_block.initialize() + energy_costing_block.initialize() + m.fs.costing.initialize() + m.fs.costing.add_annual_water_production( + m.fs.treatment.product.properties[0].flow_vol + ) + m.fs.costing.add_LCOT(m.fs.treatment.product.properties[0].flow_vol) + m.fs.costing.add_LCOH() + + +def calc_costing(m, heat_price=0.01, electricity_price=0.07): + # Touching variables to solve for volumetric flow rate + m.fs.product.properties[0].flow_vol_phase + + # Treatment costing + # Overwriting values in yaml + m.fs.treatment.costing.heat_cost.fix(heat_price) + m.fs.treatment.costing.electricity_cost.fix(electricity_price) + m.fs.treatment.costing.cost_process() + + m.fs.treatment.costing.initialize() + + m.fs.treatment.costing.add_annual_water_production( + m.fs.product.properties[0].flow_vol + ) + m.fs.treatment.costing.add_LCOW(m.fs.product.properties[0].flow_vol) + + # Energy costing + m.fs.energy.costing.electricity_cost.fix(electricity_price) + m.fs.energy.costing.cost_process() + + m.fs.energy.costing.initialize() + m.fs.energy.costing.add_annual_water_production(m.fs.product.properties[0].flow_vol) + m.fs.energy.costing.add_LCOH() + + +def add_constraints(m): + treatment = m.fs.treatment + + m.fs.water_recovery = Var( + initialize=m.water_recovery, + bounds=(0, 0.99), + domain=NonNegativeReals, + units=pyunits.dimensionless, + doc="System Water Recovery", + ) + + m.fs.eq_water_recovery = Constraint( + expr=treatment.feed.properties[0].flow_vol * m.fs.water_recovery + == treatment.product.properties[0].flow_vol + ) + + +def set_scaling(m): + + m.fs.properties.set_default_scaling( + "flow_mass_phase_comp", 0.1, index=("Liq", "H2O") + ) + m.fs.properties.set_default_scaling("flow_mass_phase_comp", 1, index=("Liq", "TDS")) + + calculate_scaling_factors(m) + + +def set_inlet_conditions(m): + + print(f'\n{"=======> SETTING FEED CONDITIONS <=======":^60}\n') + + m.fs.treatment.feed.properties.calculate_state( + var_args={ + ("flow_vol_phase", "Liq"): m.inlet_flow_rate, + ("conc_mass_phase_comp", ("Liq", "TDS")): m.inlet_salinity, + ("temperature", None): 298.15, + ("pressure", None): 101325, + }, + hold_state=True, + ) + + +def set_operating_conditions(m, hours_storage=8): + set_inlet_conditions(m) + set_fpc_op_conditions(m, hours_storage=hours_storage, temperature_hot=80) + + +def init_system(m, blk, verbose=True, solver=None): + if solver is None: + solver = get_solver() + + treatment = m.fs.treatment + + print("\n\n-------------------- INITIALIZING SYSTEM --------------------\n\n") + print(f"System Degrees of Freedom: {degrees_of_freedom(m)}") + + treatment.feed.initialize() + + init_md(treatment.md) + + propagate_state(treatment.md_to_product) + treatment.product.initialize() + + propagate_state(treatment.md_to_dwi) + # m.fs.disposal.initialize() + + init_DWI(m, blk.treatment.dwi, verbose=True, solver=None) + + init_fpc(m.fs.energy) + + +def solve(m, solver=None, tee=True, raise_on_failure=True): + # ---solving--- + if solver is None: + solver = get_solver() + # solver.options["max_iter"] = 5000 + # solver.options["halt_on_ampl_error"] = "yes" + + 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 optimize(m): + m.fs.costing.frac_heat_from_grid.unfix() + m.fs.obj = Objective(expr=m.fs.costing.LCOT) + + +def report_costing(blk): + + print(f"\n\n-------------------- System Costing Report --------------------\n") + print("\n") + + print(f'{"LCOT":<30s}{value(blk.LCOT):<20,.2f}{pyunits.get_units(blk.LCOT)}') + + print( + f'{"Capital Cost":<30s}{value(blk.total_capital_cost):<20,.2f}{pyunits.get_units(blk.total_capital_cost)}' + ) + + print( + f'{"Total Operating Cost":<30s}{value(blk.total_operating_cost):<20,.2f}{pyunits.get_units(blk.total_operating_cost)}' + ) + + print( + f'{"Agg Fixed Operating Cost":<30s}{value(blk.aggregate_fixed_operating_cost):<20,.2f}{pyunits.get_units(blk.aggregate_fixed_operating_cost)}' + ) + + print( + f'{"Agg Variable Operating Cost":<30s}{value(blk.aggregate_variable_operating_cost):<20,.2f}{pyunits.get_units(blk.aggregate_variable_operating_cost)}' + ) + + print( + f'{"Heat flow":<30s}{value(blk.aggregate_flow_heat):<20,.2f}{pyunits.get_units(blk.aggregate_flow_heat)}' + ) + + # print( + # f'{"Total heat cost":<30s}{value(blk.total_heat_operating_cost):<20,.2f}{pyunits.get_units(blk.total_heat_operating_cost)}' + # ) + + print( + f'{"Heat purchased":<30s}{value(blk.aggregate_flow_heat_purchased):<20,.2f}{pyunits.get_units(blk.aggregate_flow_heat_purchased)}' + ) + + print( + f'{"Heat sold":<30s}{value(blk.aggregate_flow_heat_sold):<20,.2f}{pyunits.get_units(blk.aggregate_flow_heat_sold)}' + ) + + print( + f'{"Elec Flow":<30s}{value(blk.aggregate_flow_electricity):<20,.2f}{pyunits.get_units(blk.aggregate_flow_electricity)}' + ) + + # print( + # f'{"Total elec cost":<30s}{value(blk.total_electric_operating_cost):<20,.2f}{pyunits.get_units(blk.total_electric_operating_cost)}' + # ) + + print( + f'{"Elec purchased":<30s}{value(blk.aggregate_flow_electricity_purchased):<20,.2f}{pyunits.get_units(blk.aggregate_flow_electricity_purchased)}' + ) + + print( + f'{"Elec sold":<30s}{value(blk.aggregate_flow_electricity_sold):<20,.2f}{pyunits.get_units(blk.aggregate_flow_electricity_sold)}' + ) + + +def main( + water_recovery=0.5, + heat_price=0.07, + electricity_price=0.07, + frac_heat_from_grid=0.01, + hours_storage=8, + run_optimization=True, +): + # Build MD, DWI and FPC + m = build_system() + add_connections(m) + add_constraints(m) + set_operating_conditions(m) + set_scaling(m) + # check_jac(m) + init_system(m, m.fs) + print(f"dof = {degrees_of_freedom(m)}") + results = solve(m.fs.treatment.md.mp) + # results = solve(m.fs.treatment.md) + # results = solve(m.fs.treatment) + # results = solve(m.fs.energy) + results = solve(m) + print(f"termination {results.solver.termination_condition}") + add_costing(m) + + print(f"dof = {degrees_of_freedom(m)}") + results = solve(m) + print(f"termination 2 {results.solver.termination_condition}") + + +def print_results_summary(m): + + print(f"\nAfter Optimization System Degrees of Freedom: {degrees_of_freedom(m)}") + + print("\n") + print( + f'{"Treatment LCOW":<30s}{value(m.fs.treatment.costing.LCOW):<10.2f}{pyunits.get_units(m.fs.treatment.costing.LCOW)}' + ) + + print("\n") + print( + f'{"Energy LCOH":<30s}{value(m.fs.energy.costing.LCOH):<10.2f}{pyunits.get_units(m.fs.energy.costing.LCOH)}' + ) + + print("\n") + print( + f'{"System LCOT":<30s}{value(m.fs.costing.LCOT) :<10.2f}{pyunits.get_units(m.fs.costing.LCOT)}' + ) + + print("\n") + print( + f'{"Percent from the grid":<30s}{value(m.fs.costing.frac_heat_from_grid):<10.2f}{pyunits.get_units(m.fs.costing.frac_heat_from_grid)}' + ) + + report_MD(m, m.fs.treatment.md) + report_md_costing(m, m.fs.treatment) + + print_DWI_costing_breakdown(m.fs.treatment, m.fs.treatment.dwi) + + report_fpc(m, m.fs.energy.fpc.unit) + report_fpc_costing(m, m.fs.energy) + report_costing(m.fs.costing) + + +def save_results(m): + + results_df = pd.DataFrame( + columns=[ + "water_recovery", + "heat_price", + "LCOH", + "hours_storage", + "frac_heat_from_grid", + "product_annual_production", + "utilization_factor", + "capital_recovery_factor", + "unit", + "cost_component", + "cost", + "norm_cost_component", + ] + ) + + capex_output = { + "FPC": value(m.fs.energy.fpc.unit.costing.capital_cost) + * value(m.fs.costing.capital_recovery_factor), + "MD": value( + m.fs.treatment.md.unit.get_active_process_blocks()[ + -1 + ].fs.vagmd.costing.capital_cost + ) + * value(m.fs.costing.capital_recovery_factor), + "DWI": 0, + "Heat": 0, + "Electricity": 0, + } + + fixed_opex_output = { + "FPC": value(m.fs.energy.fpc.unit.costing.fixed_operating_cost) + + value(m.fs.energy.fpc.unit.costing.capital_cost) + * value(m.fs.energy.costing.maintenance_labor_chemical_factor), + "MD": value( + m.fs.treatment.md.unit.get_active_process_blocks()[ + -1 + ].fs.vagmd.costing.fixed_operating_cost + ) + + value( + m.fs.treatment.md.unit.get_active_process_blocks()[ + -1 + ].fs.vagmd.costing.capital_cost + ) + * value(m.fs.treatment.costing.maintenance_labor_chemical_factor), + "DWI": 0, + "Heat": 0, + "Electricity": 0, + } + variable_opex_output = { + "FPC": 0, + "MD": 0, + "DWI": value(m.fs.treatment.dwi.unit.costing.variable_operating_cost), + "Heat": value(m.fs.costing.total_heat_operating_cost), + "Electricity": value(m.fs.costing.total_electric_operating_cost), + } + + for unit in ["FPC", "MD", "DWI", "Heat", "Electricity"]: + # Add fixed_opex + temp = { + "water_recovery": value(m.fs.water_recovery), + "heat_price": value(m.fs.costing.heat_cost_buy), + "LCOH": value(m.fs.energy.costing.LCOH), + "hours_storage": value(m.fs.energy.fpc.unit.hours_storage), + "frac_heat_from_grid": value(m.fs.costing.frac_heat_from_grid), + "product_annual_production": value(m.fs.costing.annual_water_production), + "utilization_factor": value(m.fs.costing.utilization_factor), + "capital_recovery_factor": value(m.fs.costing.capital_recovery_factor), + "unit": unit, + "cost_component": "fixed_opex", + "cost": fixed_opex_output[unit], + } + results_df = results_df.append(temp, ignore_index=True) + # Add variable opex + temp = { + "water_recovery": value(m.fs.water_recovery), + "heat_price": value(m.fs.costing.heat_cost_buy), + "LCOH": value(m.fs.energy.costing.LCOH), + "hours_storage": value(m.fs.energy.fpc.unit.hours_storage), + "frac_heat_from_grid": value(m.fs.costing.frac_heat_from_grid), + "product_annual_production": value(m.fs.costing.annual_water_production), + "utilization_factor": value(m.fs.costing.utilization_factor), + "capital_recovery_factor": value(m.fs.costing.capital_recovery_factor), + "unit": unit, + "cost_component": "variable_opex", + "cost": variable_opex_output[unit], + } + results_df = results_df.append(temp, ignore_index=True) + + # Add opex + temp = { + "water_recovery": value(m.fs.water_recovery), + "heat_price": value(m.fs.costing.heat_cost_buy), + "LCOH": value(m.fs.energy.costing.LCOH), + "hours_storage": value(m.fs.energy.fpc.unit.hours_storage), + "frac_heat_from_grid": value(m.fs.costing.frac_heat_from_grid), + "product_annual_production": value(m.fs.costing.annual_water_production), + "utilization_factor": value(m.fs.costing.utilization_factor), + "capital_recovery_factor": value(m.fs.costing.capital_recovery_factor), + "unit": unit, + "cost_component": "opex", + "cost": variable_opex_output[unit] + fixed_opex_output[unit], + } + results_df = results_df.append(temp, ignore_index=True) + + # Add capex + temp = { + "water_recovery": value(m.fs.water_recovery), + "heat_price": value(m.fs.costing.heat_cost_buy), + "LCOH": value(m.fs.energy.costing.LCOH), + "hours_storage": value(m.fs.energy.fpc.unit.hours_storage), + "frac_heat_from_grid": value(m.fs.costing.frac_heat_from_grid), + "product_annual_production": value(m.fs.costing.annual_water_production), + "utilization_factor": value(m.fs.costing.utilization_factor), + "capital_recovery_factor": value(m.fs.costing.capital_recovery_factor), + "unit": unit, + "cost_component": "capex", + "cost": capex_output[unit], + } + results_df = results_df.append(temp, ignore_index=True) + + results_df["norm_cost_component"] = ( + results_df["cost"] + / results_df["product_annual_production"] + / results_df["utilization_factor"] + ) + + file_name = ( + "RPT3_water_recovery_" + + str(value(m.fs.water_recovery)) + + "_heat_price_" + + str(value(m.fs.costing.heat_cost_buy)) + + "_hours_storage_" + + str(value(m.fs.energy.fpc.unit.hours_storage)) + ) + + # results_df.to_csv( + # r"C:\Users\mhardika\Documents\SETO\Case Studies\RPT3\RPT3_results\\" + # + file_name + # + ".csv" + # ) + # Flow cost + + +if __name__ == "__main__": + + main( + water_recovery=0.8, + heat_price=0.08, + electricity_price=0.07, + frac_heat_from_grid=0.5, + hours_storage=6, + run_optimization=False, + ) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_SOA.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_SOA.py index 8bde955a..4e331fba 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_SOA.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_SOA.py @@ -28,7 +28,7 @@ from idaes.core import FlowsheetBlock, UnitModelCostingBlock from idaes.models.unit_models import Product, Feed, StateJunction, Separator -from watertap.core.wt_database import Database +from watertap_contrib.reflo.core import REFLODatabase from watertap.core.util.model_diagnostics.infeasible import * from watertap.core.util.initialization import * from watertap.property_models.NaCl_prop_pack import NaClParameterBlock @@ -41,6 +41,7 @@ TreatmentCosting, EnergyCosting, REFLOCosting, + REFLOSystemCosting, ) from watertap_contrib.reflo.analysis.case_studies.KBHDP import * @@ -72,29 +73,25 @@ def main(): file_dir = os.path.dirname(os.path.abspath(__file__)) m = build_system() - display_system_build(m) add_connections(m) add_constraints(m) set_operating_conditions(m) + apply_scaling(m) init_system(m) add_costing(m) - display_system_build(m) - optimize(m, ro_mem_area=None, water_recovery=0.75) + optimize(m, ro_mem_area=None, water_recovery=0.6) solve(m, debug=True) - display_system_stream_table(m) - report_softener(m) - report_UF(m, m.fs.UF) - report_RO(m, m.fs.RO) - display_costing_breakdown(m) - print_all_results(m) + + print(m.fs.treatment.product.display()) + print(m.fs.treatment.product.properties[0].flow_vol_phase.display()) + print(m.fs.treatment.costing.display()) + print(m.fs.treatment.costing.LCOW.display()) def build_system(): m = ConcreteModel() - m.db = Database() + m.db = REFLODatabase() m.fs = FlowsheetBlock(dynamic=False) - m.fs.costing = REFLOCosting() - m.fs.costing.base_currency = pyunits.USD_2020 m.fs.MCAS_properties = MCASParameterBlock( solute_list=[ @@ -113,45 +110,52 @@ def build_system(): m.fs.RO_properties = NaClParameterBlock() m.fs.UF_properties = WaterParameterBlock(solute_list=["tds", "tss"]) - m.fs.feed = Feed(property_package=m.fs.MCAS_properties) - m.fs.product = Product(property_package=m.fs.RO_properties) - m.fs.disposal = Product(property_package=m.fs.RO_properties) + build_treatment(m) + + return m + + +def build_treatment(m): + treatment = m.fs.treatment = Block() + + treatment.feed = Feed(property_package=m.fs.MCAS_properties) + treatment.product = Product(property_package=m.fs.RO_properties) + treatment.sludge = Product(property_package=m.fs.MCAS_properties) + treatment.UF_waste = Product(property_package=m.fs.UF_properties) # Define the Unit Models - m.fs.softener = FlowsheetBlock(dynamic=False) - m.fs.UF = FlowsheetBlock(dynamic=False) - m.fs.pump = Pump(property_package=m.fs.RO_properties) - m.fs.RO = FlowsheetBlock(dynamic=False) - m.fs.DWI = FlowsheetBlock(dynamic=False) - - # Define the Translator Blocks - m.fs.MCAS_to_NaCl_translator = Translator_MCAS_to_NACL( - inlet_property_package=m.fs.MCAS_properties, - outlet_property_package=m.fs.RO_properties, - has_phase_equilibrium=False, - outlet_state_defined=True, - ) + treatment.softener = FlowsheetBlock(dynamic=False) + treatment.UF = FlowsheetBlock(dynamic=False) + treatment.pump = Pump(property_package=m.fs.RO_properties) + treatment.RO = FlowsheetBlock(dynamic=False) + treatment.DWI = FlowsheetBlock(dynamic=False) - m.fs.MCAS_to_TDS_translator = Translator_MCAS_to_TDS( + treatment.MCAS_to_TDS_translator = Translator_MCAS_to_TDS( inlet_property_package=m.fs.MCAS_properties, outlet_property_package=m.fs.UF_properties, has_phase_equilibrium=False, outlet_state_defined=True, ) - m.fs.TDS_to_NaCl_translator = Translator_TDS_to_NACL( + treatment.TDS_to_NaCl_translator = Translator_TDS_to_NACL( inlet_property_package=m.fs.UF_properties, outlet_property_package=m.fs.RO_properties, has_phase_equilibrium=False, outlet_state_defined=True, ) - build_softener(m, m.fs.softener, prop_package=m.fs.MCAS_properties) - build_UF(m, m.fs.UF, prop_package=m.fs.UF_properties) - build_ro(m, m.fs.RO, prop_package=m.fs.RO_properties, number_of_stages=2) - build_DWI(m, m.fs.DWI, prop_package=m.fs.RO_properties) + build_softener(m, treatment.softener, prop_package=m.fs.MCAS_properties) + build_UF(m, treatment.UF, prop_package=m.fs.UF_properties) + build_ro(m, treatment.RO, prop_package=m.fs.RO_properties, number_of_stages=2) + build_DWI(m, treatment.DWI, prop_package=m.fs.RO_properties) - m.fs.units = [m.fs.softener, m.fs.UF, m.fs.pump, m.fs.RO, m.fs.DWI] + m.fs.units = [ + treatment.softener, + treatment.UF, + treatment.pump, + treatment.RO, + treatment.DWI, + ] m.fs.MCAS_properties.set_default_scaling( "flow_mass_phase_comp", 10**-1, index=("Liq", "H2O") @@ -160,6 +164,10 @@ def build_system(): "flow_mass_phase_comp", 10**-1, index=("Liq", "NaCl") ) + m.fs.UF_properties.set_default_scaling("flow_mass_comp", 1e-2, index=("H2O")) + m.fs.UF_properties.set_default_scaling("flow_mass_comp", 1, index=("tds")) + m.fs.UF_properties.set_default_scaling("flow_mass_comp", 1e5, index=("tss")) + m.fs.RO_properties.set_default_scaling( "flow_mass_phase_comp", 1, index=("Liq", "H2O") ) @@ -177,60 +185,74 @@ def build_sweep(): add_connections(m) add_constraints(m) set_operating_conditions(m) + apply_scaling(m) init_system(m) add_costing(m) display_system_build(m) - optimize(m, ro_mem_area=None, water_recovery=0.75) + optimize(m, ro_mem_area=None, water_recovery=0.6) return m def add_connections(m): + treatment = m.fs.treatment + + treatment.feed_to_softener = Arc( + source=treatment.feed.outlet, + destination=treatment.softener.unit.inlet, + ) - m.fs.feed_to_softener = Arc( - source=m.fs.feed.outlet, - destination=m.fs.softener.unit.inlet, + treatment.softener_to_translator = Arc( + source=treatment.softener.unit.outlet, + destination=treatment.MCAS_to_TDS_translator.inlet, ) - m.fs.softener_to_translator = Arc( - source=m.fs.softener.unit.outlet, - destination=m.fs.MCAS_to_TDS_translator.inlet, + treatment.softener_to_sludge = Arc( + source=treatment.softener.unit.waste, + destination=treatment.sludge.inlet, ) - m.fs.translator_to_UF = Arc( - source=m.fs.MCAS_to_TDS_translator.outlet, - destination=m.fs.UF.feed.inlet, + treatment.translator_to_UF = Arc( + source=treatment.MCAS_to_TDS_translator.outlet, + destination=treatment.UF.feed.inlet, ) - m.fs.UF_to_translator3 = Arc( - source=m.fs.UF.product.outlet, - destination=m.fs.TDS_to_NaCl_translator.inlet, + treatment.UF_to_translator3 = Arc( + source=treatment.UF.product.outlet, + destination=treatment.TDS_to_NaCl_translator.inlet, ) - m.fs.translator_to_pump = Arc( - source=m.fs.TDS_to_NaCl_translator.outlet, - destination=m.fs.pump.inlet, + treatment.UF_to_waste = Arc( + source=treatment.UF.disposal.outlet, + destination=treatment.UF_waste.inlet, ) - m.fs.pump_to_ro = Arc( - source=m.fs.pump.outlet, - destination=m.fs.RO.feed.inlet, + treatment.translator_to_pump = Arc( + source=treatment.TDS_to_NaCl_translator.outlet, + destination=treatment.pump.inlet, ) - m.fs.ro_to_product = Arc( - source=m.fs.RO.product.outlet, - destination=m.fs.product.inlet, + treatment.pump_to_ro = Arc( + source=treatment.pump.outlet, + destination=treatment.RO.feed.inlet, ) - m.fs.ro_to_disposal = Arc( - source=m.fs.RO.disposal.outlet, - destination=m.fs.DWI.feed.inlet, + treatment.ro_to_product = Arc( + source=treatment.RO.product.outlet, + destination=treatment.product.inlet, + ) + + treatment.ro_to_disposal = Arc( + source=treatment.RO.disposal.outlet, + destination=treatment.DWI.feed.inlet, ) TransformationFactory("network.expand_arcs").apply_to(m) def add_constraints(m): + treatment = m.fs.treatment + m.fs.water_recovery = Var( initialize=0.5, bounds=(0, 0.99), @@ -239,66 +261,54 @@ def add_constraints(m): doc="System Water Recovery", ) - m.fs.feed_flow_mass = Var( - initialize=1, - bounds=(0.00001, 1e6), - domain=NonNegativeReals, - units=pyunits.kg / pyunits.s, - doc="System Feed Flowrate", - ) - - m.fs.feed_flow_vol = Var( - initialize=1, - bounds=(0.00001, 1e6), - domain=NonNegativeReals, - units=pyunits.L / pyunits.s, - doc="System Feed Flowrate", - ) - - m.fs.perm_flow_mass = Var( - initialize=1, - bounds=(0.00001, 1e6), - domain=NonNegativeReals, - units=pyunits.kg / pyunits.s, - doc="System Produce Flowrate", - ) - m.fs.eq_water_recovery = Constraint( - expr=m.fs.feed.properties[0].flow_vol_phase["Liq"] * m.fs.water_recovery - == m.fs.product.properties[0].flow_vol_phase["Liq"] + expr=treatment.feed.properties[0].flow_vol * m.fs.water_recovery + == treatment.product.properties[0].flow_vol ) - m.fs.feed.properties[0].conc_mass_phase_comp - m.fs.product.properties[0].conc_mass_phase_comp - m.fs.disposal.properties[0].conc_mass_phase_comp - m.fs.MCAS_to_NaCl_translator.properties_in[0.0].conc_mass_phase_comp - m.fs.MCAS_to_NaCl_translator.properties_out[0.0].conc_mass_phase_comp + +def apply_scaling(m): + treatment = m.fs.treatment + add_UF_scaling(treatment.UF) + add_ro_scaling(m, treatment.RO) + calculate_scaling_factors(m) def add_costing(m): + treatment = m.fs.treatment + # treatment.costing = TreatmentCosting() + treatment.costing = REFLOCosting() - m.fs.pump.costing = UnitModelCostingBlock( - flowsheet_costing_block=m.fs.costing, + # energy = m.fs.energy = Block() + # energy.costing = EnergyCosting() + + treatment.pump.costing = UnitModelCostingBlock( + flowsheet_costing_block=treatment.costing, ) - add_softener_costing(m, m.fs.softener, m.fs.costing) - add_UF_costing(m, m.fs.UF, m.fs.costing) - add_ro_costing(m, m.fs.RO, m.fs.costing) - add_DWI_costing(m, m.fs.DWI, m.fs.costing) + add_softener_costing(m, treatment.softener, treatment.costing) + add_UF_costing(m, treatment.UF, treatment.costing) + add_ro_costing(m, treatment.RO, treatment.costing) + add_DWI_costing(m, treatment.DWI, treatment.costing) + + # treatment.costing.cost_process() + # treatment.costing.initialize() - m.fs.costing.cost_process() - m.fs.costing.add_annual_water_production(m.fs.product.properties[0].flow_vol) - m.fs.costing.add_LCOW(m.fs.product.properties[0].flow_vol) + # energy.costing.cost_process() + # energy.costing.initialize() - m.fs.costing.initialize() + # m.fs.costing = REFLOCosting() + # m.fs.costing.cost_process() - m.fs.costing.total_annualized_cost = pyo.Expression( - expr=( - m.fs.costing.total_capital_cost * m.fs.costing.capital_recovery_factor - + m.fs.costing.total_operating_cost - ), - doc="Total annualized cost of operation", + treatment.costing.cost_process() + + treatment.costing.add_annual_water_production( + treatment.product.properties[0].flow_vol ) + treatment.costing.add_LCOW(treatment.product.properties[0].flow_vol_phase["Liq"]) + + # m.fs.costing.initialize() + treatment.costing.initialize() def define_inlet_composition(m): @@ -316,17 +326,28 @@ def define_inlet_composition(m): def set_inlet_conditions( m, Qin=4, - supply_pressure=1.1e5, - primary_pump_pressure=15e5, + water_recovery=None, + supply_pressure=101325, ): print(f'\n{"=======> SETTING OPERATING CONDITIONS <=======":^60}\n') - feed_temperature = 293 - Qin = Qin * pyunits.Mgal / pyunits.day - flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) - rho = 1000 * pyunits.kg / pyunits.m**3 - flow_mass_phase_water = pyunits.convert(Qin * rho, to_units=pyunits.kg / pyunits.s) + treatment = m.fs.treatment + + # Convert Q_in from MGD to kg/s + Qin = pyunits.convert( + Qin * pyunits.Mgallon * pyunits.day**-1, to_units=pyunits.L / pyunits.s + ) + feed_density = 1000 * pyunits.kg / pyunits.m**3 + print('\n=======> SETTING FEED CONDITIONS <======="\n') + print(f"Flow Rate: {value(Qin):<10.2f}{pyunits.get_units(Qin)}") + + if Qin is None: + treatment.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"].fix(1) + else: + treatment.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"].fix( + Qin * feed_density + ) inlet_dict = { "Ca_2+": 0.61 * pyunits.kg / pyunits.m**3, @@ -339,50 +360,33 @@ def set_inlet_conditions( "SO2_-4+": 0.23 * pyunits.kg / pyunits.m**3, } - calc_state_dict = { - ("flow_vol_phase", "Liq"): value(flow_in), - ("pressure", None): 101325, - ("temperature", None): 298, - } - for solute, solute_conc in inlet_dict.items(): - calc_state_dict[("conc_mass_phase_comp", ("Liq", solute))] = solute_conc - 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_phase_comp["Liq", solute].set_value( - flow_mass_solute + treatment.feed.properties[0].flow_mass_phase_comp["Liq", solute].fix( + pyunits.convert( + ( + treatment.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"] + / (1000 * pyunits.kg / pyunits.m**3) + ) + * solute_conc, + to_units=pyunits.kg / pyunits.s, + ) ) m.fs.MCAS_properties.set_default_scaling( "flow_mass_phase_comp", - sf, - index=("Liq", solute), - ) - m.fs.MCAS_properties.set_default_scaling( - "conc_mass_phase_comp", - 1 / solute_conc(), - index=("Liq", solute), - ) - m.fs.MCAS_properties.set_default_scaling( - "mass_frac_phase_comp", - 1 / value(flow_mass_solute / flow_mass_phase_water), + 1 / value(treatment.feed.properties[0].flow_mass_phase_comp["Liq", solute]), index=("Liq", solute), ) - m.fs.MCAS_properties.set_default_scaling( "flow_mass_phase_comp", - 1 / value(m.fs.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"]), + 1 / value(treatment.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"]), index=("Liq", "H2O"), ) - calculate_scaling_factors(m) - m.fs.feed.properties.calculate_state(var_args=calc_state_dict, hold_state=True) - calculate_scaling_factors(m) + feed_temperature = 273.15 + 20 # # initialize feed - m.fs.feed.pressure[0].fix(supply_pressure) - m.fs.feed.temperature[0].fix(feed_temperature) + treatment.feed.pressure[0].fix(supply_pressure) + treatment.feed.temperature[0].fix(feed_temperature) def display_unfixed_vars(blk, report=True): @@ -396,55 +400,65 @@ def display_unfixed_vars(blk, report=True): def set_operating_conditions(m, RO_pressure=20e5, supply_pressure=1.1e5): + treatment = m.fs.treatment pump_efi = 0.8 # pump efficiency [-] - set_inlet_conditions(m, Qin=4, supply_pressure=1.1e5) - set_softener_op_conditions(m, m.fs.softener.unit) - set_UF_op_conditions(m.fs.UF) - m.fs.pump.efficiency_pump.fix(pump_efi) - m.fs.pump.control_volume.properties_in[0].pressure.fix(supply_pressure) - m.fs.pump.control_volume.properties_out[0].pressure.fix(RO_pressure) - set_ro_system_operating_conditions( - m, - m.fs.RO, - mem_area=10000, - ) + set_inlet_conditions(m, Qin=4) + set_softener_op_conditions(m, treatment.softener.unit) + set_UF_op_conditions(treatment.UF) + treatment.pump.efficiency_pump.fix(pump_efi) + treatment.pump.control_volume.properties_out[0].pressure.fix(RO_pressure) + set_ro_system_operating_conditions(m, treatment.RO, mem_area=10000) def init_system(m, verbose=True, solver=None): + print(f'\n{"=======> SYSTEM INITIALIZATION <=======":^60}\n') + print(f"System Degrees of Freedom: {degrees_of_freedom(m)}") + if degrees_of_freedom(m) != 0: + breakdown_dof(m, detailed=True) + assert_no_degrees_of_freedom(m) + init_treatment(m) + + +def init_treatment(m, verbose=True, solver=None): if solver is None: solver = get_solver() optarg = solver.options + treatment = m.fs.treatment print("\n\n-------------------- INITIALIZING SYSTEM --------------------\n\n") print(f"System Degrees of Freedom: {degrees_of_freedom(m)}") - m.fs.feed.initialize() - propagate_state(m.fs.feed_to_softener) - report_MCAS_stream_conc(m, m.fs.feed.properties[0.0]) - init_softener(m, m.fs.softener.unit) - propagate_state(m.fs.softener_to_translator) - m.fs.MCAS_to_TDS_translator.initialize() - propagate_state(m.fs.translator_to_UF) - init_UF(m, m.fs.UF) - propagate_state(m.fs.UF_to_translator3) + treatment.feed.initialize() + propagate_state(treatment.feed_to_softener) + report_MCAS_stream_conc(m, treatment.feed.properties[0.0]) - m.fs.TDS_to_NaCl_translator.initialize() + init_softener(m, treatment.softener.unit) + propagate_state(treatment.softener_to_translator) + propagate_state(treatment.softener_to_sludge) + treatment.sludge.initialize() - propagate_state(m.fs.translator_to_pump) - m.fs.pump.initialize() + treatment.MCAS_to_TDS_translator.initialize() + propagate_state(treatment.translator_to_UF) + init_UF(m, treatment.UF) + propagate_state(treatment.UF_to_translator3) + propagate_state(treatment.UF_to_waste) + treatment.UF_waste.initialize() - propagate_state(m.fs.pump_to_ro) + treatment.TDS_to_NaCl_translator.initialize() - init_ro_system(m, m.fs.RO) - propagate_state(m.fs.ro_to_product) - propagate_state(m.fs.ro_to_disposal) + propagate_state(treatment.translator_to_pump) + treatment.pump.initialize() - m.fs.product.initialize() - m.fs.disposal.initialize() - display_system_stream_table(m) - m.fs.softener.unit.properties_waste[0].conc_mass_phase_comp + propagate_state(treatment.pump_to_ro) + + init_ro_system(m, treatment.RO) + propagate_state(treatment.ro_to_product) + propagate_state(treatment.ro_to_disposal) + + treatment.product.initialize() + init_DWI(m, treatment.DWI) def optimize( @@ -455,9 +469,9 @@ def optimize( objective="LCOW", ): print("\n\nDOF before optimization: ", degrees_of_freedom(m)) - + treatment = m.fs.treatment if objective == "LCOW": - m.fs.lcow_objective = Objective(expr=m.fs.costing.LCOW) + m.fs.lcow_objective = Objective(expr=treatment.costing.LCOW) if water_recovery is not None: print(f"\n------- Fixed Recovery at {100*water_recovery}% -------") @@ -469,19 +483,31 @@ def optimize( if fixed_pressure is not None: print(f"\n------- Fixed RO Pump Pressure at {fixed_pressure} -------\n") - m.fs.pump.control_volume.properties_out[0].pressure.fix(fixed_pressure) + treatment.pump.control_volume.properties_out[0].pressure.fix(fixed_pressure) else: + lower_bound = 100 * pyunits.psi + upper_bound = 900 * pyunits.psi print(f"------- Unfixed RO Pump Pressure -------") - m.fs.pump.control_volume.properties_out[0].pressure.unfix() + print(f"Lower Bound: {value(lower_bound)} {pyunits.get_units(lower_bound)}") + print(f"Upper Bound: {value(upper_bound)} {pyunits.get_units(upper_bound)}") + treatment.pump.control_volume.properties_out[0].pressure.unfix() + treatment.pump.control_volume.properties_out[0].pressure.setlb(lower_bound) + treatment.pump.control_volume.properties_out[0].pressure.setub(upper_bound) if ro_mem_area is not None: print(f"\n------- Fixed RO Membrane Area at {ro_mem_area} -------\n") - for idx, stage in m.fs.RO.stage.items(): + for idx, stage in treatment.RO.stage.items(): stage.module.area.fix(ro_mem_area) else: - print(f"\n------- Unfixed RO Membrane Area -------\n") - for idx, stage in m.fs.RO.stage.items(): + lower_bound = 1e3 + upper_bound = 2e5 + print(f"\n------- Unfixed RO Membrane Area -------") + print(f"Lower Bound: {lower_bound} m2") + print(f"Upper Bound: {upper_bound} m2") + print("\n") + for idx, stage in treatment.RO.stage.items(): stage.module.area.unfix() + stage.module.area.setub(1e6) def solve(model, solver=None, tee=False, raise_on_failure=True, debug=False): @@ -589,14 +615,8 @@ def display_system_stream_table(m): def display_system_build(m): blocks = [] - for unit in m.fs.component_data_objects( - ctype=Block, active=True, descend_into=False - ): - print(unit) - for component in unit.component_data_objects( - ctype=Block, active=True, descend_into=False - ): - print(" ", component) + for v in m.fs.component_data_objects(ctype=Block, active=True, descend_into=False): + print(v) def display_costing_breakdown(m): diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_ZLD.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_ZLD.py index cb299954..a4bd21ea 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_ZLD.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/KBHDP_ZLD.py @@ -310,7 +310,6 @@ def add_costing(m): add_energy_costing(m) m.fs.costing = REFLOSystemCosting() - m.fs.costing.base_currency = pyunits.USD_2020 m.fs.costing.cost_process() m.fs.costing.add_annual_water_production(treatment.product.properties[0].flow_vol) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/__init__.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/__init__.py index d65ad365..d0ef6257 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/__init__.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/__init__.py @@ -1,2 +1,3 @@ from .components import * from .utils import * +from .data import * 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..fbfa3744 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 @@ -30,6 +30,8 @@ EnergyCosting, ) +import pickle + __all__ = [ "build_cst", "init_cst", @@ -58,17 +60,30 @@ 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 + r"\src\watertap_contrib\reflo\analysis\case_studies\permian\data\cst\\" dataset_filename = os.path.join( - os.path.dirname(__file__), r"data\test_trough_data.pkl" + os.path.dirname(__file__), r"trough_kbhdp_data_heat_load_1_100_hours_storage_0_24.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_data_heat_load_1_100_hours_storage_0_24.json", ) - input_bounds = dict(heat_load=[100, 500], hours_storage=[0, 26]) + input_bounds = dict(heat_load=[1, 100], hours_storage=[0, 24]) input_units = dict(heat_load="MW", hours_storage="hour") input_variables = { "labels": ["heat_load", "hours_storage"], @@ -93,19 +108,16 @@ def build_cst(blk, __file__=None): 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): +def set_cst_op_conditions(blk, heat_load = 10, hours_storage=6): blk.unit.hours_storage.fix(hours_storage) + blk.unit.heat_load.fix(heat_load) def add_cst_costing(blk, costing_block): @@ -113,12 +125,11 @@ def add_cst_costing(blk, costing_block): def calc_costing(m, blk): - blk.costing.heat_cost.set_value(0) blk.costing.cost_process() 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 +160,9 @@ 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)}' @@ -199,17 +210,14 @@ def report_cst_costing(m, blk): build_cst(m.fs.cst) - init_cst(m.fs.cst) - set_cst_op_conditions(m.fs.cst) + init_cst(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() diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/EC.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/EC.py index bb10c678..87457d47 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/EC.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/EC.py @@ -1,4 +1,3 @@ -import pathlib from pyomo.environ import ( ConcreteModel, value, @@ -65,15 +64,6 @@ "print_EC_costing_breakdown", ] -from pyomo.util.calc_var_value import calculate_variable_from_constraint as cvc - -from watertap_contrib.reflo.core import REFLODatabase - -rho = 1000 * pyunits.kg / pyunits.m**3 -reflo_dir = pathlib.Path(__file__).resolve().parents[4] - -case_study_yaml = f"{reflo_dir}/data/technoeconomic/kbhdp_case_study.yaml" - def propagate_state(arc, detailed=True): _prop_state(arc) @@ -172,6 +162,7 @@ def build_ec(m, blk, prop_package=None): TransformationFactory("network.expand_arcs").apply_to(m) +<<<<<<< HEAD <<<<<<< HEAD def build_system(): """Function to create concrete model for individual unit model flowsheet""" @@ -216,6 +207,8 @@ def set_system_operating_conditions(m): m.tds * flow_in ) # kg/m3 * m3/s = kg/s ======= +======= +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 def set_system_operating_conditions(m): """This function sets the system operating conditions for individual unit model flowsheet""" @@ -223,12 +216,16 @@ def set_system_operating_conditions(m): m.fs.feed.properties[0].flow_mass_comp["tds"].fix(2.143156) # kg/m3 * m3/s = kg/s m.fs.feed.properties[0.0].flow_mass_comp["tss"].fix(5.22e-6) # # initialize feed +<<<<<<< HEAD >>>>>>> 322fa4ff98970cc8c8f0e80d4174efd55ce7d6e5 +======= +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 def set_ec_operating_conditions(m, blk, conv=5e3): """Set EC operating conditions""" # Check if the set up of the ec inputs is correct +<<<<<<< HEAD <<<<<<< HEAD blk.ec.load_parameters_from_database(use_default_removal=True) @@ -280,6 +277,8 @@ def set_ec_operating_conditions(m, blk, conv=5e3): # blk.ec.overpotential_k1.fix(430) # blk.ec.overpotential_k2.fix(1000) ======= +======= +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 print(f"EC Degrees of Freedom: {degrees_of_freedom(blk.ec)}") blk.ec.load_parameters_from_database(use_default_removal=True) @@ -295,7 +294,10 @@ def set_ec_operating_conditions(m, blk, conv=5e3): # blk.feed.properties[0.0].flow_mass_comp["tss"].fix(5.22e-6) # blk.ec.overpotential.fix(2) print(f"EC Degrees of Freedom: {degrees_of_freedom(blk.ec)}") +<<<<<<< HEAD >>>>>>> 322fa4ff98970cc8c8f0e80d4174efd55ce7d6e5 +======= +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 def set_scaling(m, blk): @@ -390,7 +392,6 @@ def init_ec(m, blk, solver=None): def add_system_costing(m): """Add system level costing components""" m.fs.costing = ZeroOrderCosting() - m.fs.costing.base_currency = pyunits.USD_2022 add_ec_costing(m, m.fs.EC) calc_costing(m, m.fs.EC) @@ -522,6 +523,7 @@ def breakdown_dof(blk): m.fs.objective_lcow = Objective(expr=m.fs.costing.LCOW) results = solve(m, debug=True) +<<<<<<< HEAD <<<<<<< HEAD add_system_costing(m) @@ -541,3 +543,8 @@ def breakdown_dof(blk): print_EC_costing_breakdown(m.fs.EC) m.fs.EC.ec.conductivity.display() >>>>>>> 322fa4ff98970cc8c8f0e80d4174efd55ce7d6e5 +======= + report_EC(m.fs.EC) + print_EC_costing_breakdown(m.fs.EC) + m.fs.EC.ec.conductivity.display() +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/FPC.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/FPC.py index 983013aa..fbd00b1e 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/FPC.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/FPC.py @@ -44,13 +44,22 @@ "report_fpc", "print_FPC_costing_breakdown", ] +__location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__))) +parent_dir = os.path.abspath(os.path.join(__location__, "..")) +weather_file = os.path.join(parent_dir, "el_paso_texas-KBHDP-weather.csv") +param_file = os.path.join(parent_dir, "swh-kbhdp.json") +dataset_filename = os.path.join(parent_dir, "data/FPC_KBHDP_el_paso.pkl") +surrogate_filename = os.path.join( + parent_dir, + "data/FPC_KBHDP_el_paso_heat_load_1_25_hours_storage_0_12_temperature_hot_50_102.json", +) def build_system(): m = ConcreteModel() m.fs = FlowsheetBlock(dynamic=False) m.fs.costing = EnergyCosting() - energy = m.fs.energy = Block() + m.fs.energy = Block() m.fs.system_capacity = Var(initialize=6000, units=pyunits.m**3 / pyunits.day) @@ -63,27 +72,9 @@ def build_fpc(m): energy = m.fs.energy print(f'\n{"=======> BUILDING FPC SYSTEM <=======":^60}\n') - parent_dir = os.path.abspath( - os.path.join(os.path.abspath(__file__), "..", "..", "..", "..", "..") - ) - - surrogate_dir = os.path.join( - parent_dir, - "solar_models", - "surrogate", - "flat_plate", - "data", - ) - - dataset_filename = os.path.join(surrogate_dir, "FPC_Heat_Load.pkl") - - surrogate_filename = os.path.join( - surrogate_dir, - "flat_plate_data_heat_load_1_400_heat_load_1_400_hours_storage_0_27_temperature_hot_50_102.json", - ) input_bounds = dict( - heat_load=[1, 400], hours_storage=[0, 27], temperature_hot=[50, 102] + heat_load=[1, 25], hours_storage=[0, 12], temperature_hot=[50, 102] ) input_units = dict(heat_load="MW", hours_storage="hour", temperature_hot="degK") input_variables = { @@ -108,8 +99,7 @@ def build_fpc(m): def init_fpc(blk): - energy = m.fs.energy - energy.FPC.initialize() + blk.FPC.initialize() def set_system_op_conditions(m): @@ -118,14 +108,14 @@ def set_system_op_conditions(m): def set_fpc_op_conditions(m, hours_storage=6, temperature_hot=80): energy = m.fs.energy + # energy.FPC.load_surrogate() + energy.FPC.hours_storage.fix(hours_storage) # Assumes the hot temperature to the inlet of a 'MD HX' energy.FPC.temperature_hot.fix(temperature_hot) # Assumes the cold temperature from the outlet temperature of a 'MD HX' energy.FPC.temperature_cold.set_value(20) - energy.FPC.heat_load.fix(1) - - energy.FPC.initialize() + energy.FPC.heat_load.fix(10) def add_fpc_costing(m, costing_block=None): @@ -137,8 +127,6 @@ def add_fpc_costing(m, costing_block=None): flowsheet_costing_block=energy.costing, ) - # constraint_scaling_transform(energy.costing.fixed_operating_cost_constraint, 1e-6) - def add_FPC_scaling(m, blk): set_scaling_factor(blk.heat_annual_scaled, 1e2) @@ -149,15 +137,6 @@ def add_FPC_scaling(m, blk): constraint_scaling_transform(blk.electricity_constraint, 1e-4) -def calc_costing(m): - blk.costing.heat_cost.set_value(0) - blk.costing.cost_process() - blk.costing.initialize() - - # TODO: Connect to the treatment volume - # blk.costing.add_LCOW(m.fs.system_capacity) - - def breakdown_dof(blk): equalities = [c for c in activated_equalities_generator(blk)] active_vars = variables_in_activated_equalities_set(blk) @@ -322,21 +301,14 @@ def solve(m, solver=None, tee=True, raise_on_failure=True, debug=False): if __name__ == "__main__": solver = get_solver() - solver = SolverFactory("ipopt") + # solver = SolverFactory("ipopt") m = build_system() build_fpc(m) set_fpc_op_conditions(m) add_FPC_scaling(m, m.fs.energy.FPC) - init_fpc(m) + init_fpc(m.fs.energy) add_fpc_costing(m) - # calc_costing(m, m.fs) - # m.fs.costing.aggregate_flow_heat.fix(-4000) - results = solve(m, debug=True) - - # # print(degrees_of_freedom(m)) - # report_fpc(m) - # print(m.fs.energy.FPC.costing.display()) - # print_FPC_costing_breakdown(m, m.fs.energy.FPC) + results = solve(m) 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 194ba71f..d4a7a40a 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 @@ -57,6 +57,7 @@ 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 @@ -67,7 +68,7 @@ "build_md", "set_md_model_options", "init_md", - "set_md_op_conditions", + "set_md_initial_conditions", "md_output", "add_md_costing", "report_MD", @@ -79,18 +80,26 @@ def propagate_state(arc): _prop_state(arc) -def build_system(): +def build_system(Qin=4, Cin=12, water_recovery=0.5): 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.params = SeawaterParameterBlock() + m.fs.properties = SeawaterParameterBlock() # Create feed, product and concentrate state blocks - m.fs.feed = Feed(property_package=m.fs.params) - m.fs.product = Product(property_package=m.fs.params) - m.fs.disposal = Product(property_package=m.fs.params) + 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.water_recovery = Var( initialize=0.8, @@ -102,7 +111,7 @@ def build_system(): # Create MD unit model at flowsheet level m.fs.md = FlowsheetBlock(dynamic=False) - build_md(m, m.fs.md, prop_package=m.fs.params) + build_md(m, m.fs.md, prop_package=m.fs.properties) add_connections(m) return m @@ -123,23 +132,21 @@ def add_connections(m): TransformationFactory("network.expand_arcs").apply_to(m) -def set_md_model_options(m, blk, inlet_cond, n_time_points=None): +def set_md_model_options(m, blk, n_time_points=None): - system_capacity = inlet_cond["recovery"] * pyunits.convert( - inlet_cond["inlet_flow_rate"], to_units=pyunits.m**3 / pyunits.day - ) - feed_salinity = pyunits.convert( - inlet_cond["inlet_salinity"], to_units=pyunits.g / pyunits.L + 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": system_capacity(), # m3/day + "system_capacity": value(m.system_capacity), # m3/day "feed_flow_rate": 750, # L/h "evap_inlet_temp": 80, "cond_inlet_temp": 30, "feed_temp": 30, - "feed_salinity": feed_salinity(), # g/L + "feed_salinity": value(m.feed_salinity), # g/L "initial_batch_volume": 50, # L "module_type": "AS26C7.2L", "cooling_system_type": "closed", @@ -155,7 +162,7 @@ def set_md_model_options(m, blk, inlet_cond, n_time_points=None): cond_inlet_temp=model_options["cond_inlet_temp"], feed_temp=model_options["feed_temp"], feed_salinity=model_options["feed_salinity"], - recovery_ratio=m.fs.water_recovery(), + recovery_ratio=m.water_recovery, initial_batch_volume=model_options["initial_batch_volume"], module_type=model_options["module_type"], cooling_system_type=model_options["cooling_system_type"], @@ -170,30 +177,18 @@ 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.params + prop_package = m.fs.properties # Build a feed, permeate and brine state function for MD blk.feed = StateJunction(property_package=prop_package) - # blk.product = StateJunction(property_package=prop_package) - # blk.disposal = StateJunction(property_package=prop_package) - - # blk.feed = StateJunction(property_package=m.fs.params) blk.permeate = StateJunction(property_package=prop_package) blk.concentrate = StateJunction(property_package=prop_package) - inlet_cond = { - "inlet_flow_rate": blk.feed.properties[0].flow_vol_phase["Liq"], - "inlet_salinity": blk.feed.properties[0].conc_mass_phase_comp["Liq", "TDS"], - "recovery": 0.8, - } - - n_time_points = 2 # None - - set_md_model_options(m, blk, inlet_cond, n_time_points) + set_md_model_options(m, blk, n_time_points=None) # Build the multiperiod object for MD - blk.unit = MultiPeriodModel( - n_time_points=n_time_points, + blk.mp = MultiPeriodModel( + n_time_points=blk.n_time_points, process_model_func=build_vagmd_flowsheet, linking_variable_func=get_vagmd_batch_variable_pairs, initialization_func=fix_dof_and_initialize, @@ -205,19 +200,9 @@ def build_md(m, blk, prop_package=None) -> None: def init_md(blk, verbose=True, solver=None): # blk = m.fs.md - # blk.feed.properties[0]._flow_vol_phase() - # blk.feed.properties[0]._conc_mass_phase_comp() - blk.feed.initialize() - # propagate_state(blk.feed_to_md) - # # feed_flow_rate = pyunits.convert( - # # blk.feed.properties[0].flow_vol_phase["Liq"], to_units=pyunits.L / pyunits.h - # # )() - # # feed_temp = pyunits.convert_temp_K_to_C(blk.feed.properties[0].temperature()) - - # # Because its multiperiod, each instance is assigned an initial value based on model input (kwargs) - blk.unit.build_multi_period_model( + blk.mp.build_multi_period_model( model_data_kwargs={t: blk.model_options for t in range(blk.n_time_points)}, flowsheet_options=blk.model_options, unfix_dof_options={"feed_flow_rate": blk.model_options["feed_flow_rate"]}, @@ -225,42 +210,46 @@ def init_md(blk, verbose=True, solver=None): add_performance_constraints(blk) - blk.unit.system_capacity.fix(blk.model_options["system_capacity"]) + blk.mp.system_capacity.fix(blk.model_options["system_capacity"]) solver = get_solver() - active_blks = blk.unit.get_active_process_blocks() + active_blks = blk.mp.get_active_process_blocks() for active in active_blks: fix_dof_and_initialize( m=active, feed_temp=blk.model_options["feed_temp"], ) - result = solver.solve(active) + _ = solver.solve(active) unfix_dof(m=active, feed_flow_rate=blk.model_options["feed_flow_rate"]) # Build connection to permeate state junction - blk.permeate.properties[0]._flow_vol_phase() + 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 = blk.unit.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.unit.get_active_process_blocks()[-1].fs.acc_distillate_volume - / ( - b.unit.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) @@ -269,29 +258,28 @@ def get_permeate_flow(b): # Build connection to concentrate state junction - blk.concentrate.properties[0]._flow_vol_phase() - blk.concentrate.properties[0]._conc_mass_phase_comp() + 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 = blk.unit.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.unit.get_active_process_blocks()[-1].fs.acc_recovery_ratio) - / ( - b.unit.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, ) - @blk.Constraint( doc="Assign the concentrate concentration to its respective state junction" ) @@ -299,7 +287,7 @@ def get_concentrate_conc(b): return b.concentrate.properties[0].conc_mass_phase_comp[ "Liq", "TDS" ] == pyunits.convert( - b.unit.get_active_process_blocks()[-1] + b.mp.get_active_process_blocks()[-1] .fs.vagmd.feed_props[0] .conc_mass_phase_comp["Liq", "TDS"], to_units=pyunits.kg / pyunits.m**3, @@ -308,6 +296,8 @@ def get_concentrate_conc(b): 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: @@ -353,17 +343,9 @@ def set_system_op_conditions(m): ) -def set_md_op_conditions(blk): - - active_blks = blk.unit.get_active_process_blocks() - - # Set-up for the first time period - # feed_flow_rate = pyunits.convert( - # blk.feed.properties[0].flow_vol_phase["Liq"], to_units=pyunits.L / pyunits.h - # )() +def set_md_initial_conditions(blk): - # feed_salinity = blk.feed.properties[0].conc_mass_phase_comp["Liq", "TDS"]() - # feed_temp = pyunits.convert_temp_K_to_C(blk.feed.properties[0].temperature()) + active_blks = blk.mp.get_active_process_blocks() print("\n--------- MD TIME PERIOD 1 INPUTS ---------\n") print("Feed flow rate in L/h:", blk.model_options["feed_flow_rate"]) @@ -429,54 +411,54 @@ def md_output(blk, n_time_points, model_options): def add_performance_constraints(blk): - unit = blk.unit + mp = blk.mp # Create accumlative energy terms - unit.system_capacity = Var( + mp.system_capacity = Var( initialize=blk.model_options["system_capacity"], bounds=(0, None), units=pyunits.m**3 / pyunits.day, doc="System capacity (m3/day)", ) - unit.overall_thermal_power_requirement = Var( + mp.overall_thermal_power_requirement = Var( initialize=2e5, bounds=(0, None), units=pyunits.kW, doc="Thermal power requirement (kW-th)", ) - unit.overall_elec_power_requirement = Var( + mp.overall_elec_power_requirement = Var( initialize=300, bounds=(0, None), units=pyunits.kW, doc="Electric power requirement (kW-e)", ) - @unit.Constraint( + @mp.Constraint( doc="Calculate the overall thermal power requirement through all periods" ) def eq_thermal_power_requirement(b): return b.overall_thermal_power_requirement == ( - unit.get_active_process_blocks()[-1].fs.specific_energy_consumption_thermal + mp.get_active_process_blocks()[-1].fs.specific_energy_consumption_thermal * pyunits.convert(b.system_capacity, to_units=pyunits.m**3 / pyunits.h) ) - @unit.Constraint( + @mp.Constraint( doc="Calculate the overall electric power requirement through all periods" ) def eq_elec_power_requirement(b): return b.overall_elec_power_requirement == ( - unit.get_active_process_blocks()[-1].fs.specific_energy_consumption_electric + mp.get_active_process_blocks()[-1].fs.specific_energy_consumption_electric * pyunits.convert(b.system_capacity, to_units=pyunits.m**3 / pyunits.h) ) - iscale.calculate_scaling_factors(unit) + iscale.calculate_scaling_factors(mp) - if iscale.get_scaling_factor(unit.overall_thermal_power_requirement) is None: - iscale.set_scaling_factor(unit.overall_thermal_power_requirement, 1e-5) + if iscale.get_scaling_factor(mp.overall_thermal_power_requirement) is None: + iscale.set_scaling_factor(mp.overall_thermal_power_requirement, 1e-5) - if iscale.get_scaling_factor(unit.overall_elec_power_requirement) is None: - iscale.set_scaling_factor(unit.overall_elec_power_requirement, 1e-3) + if iscale.get_scaling_factor(mp.overall_elec_power_requirement) is None: + iscale.set_scaling_factor(mp.overall_elec_power_requirement, 1e-3) def add_md_costing(blk, costing_block): @@ -492,7 +474,7 @@ def add_md_costing(blk, costing_block): Returns: object: A costing module associated to the multiperiod module """ - # blk.system_capacity.fix() + # Specify the last time step vagmd = blk.get_active_process_blocks()[-1].fs.vagmd vagmd.costing = UnitModelCostingBlock(flowsheet_costing_block=costing_block) @@ -711,7 +693,7 @@ def report_md_costing(m, blk): m = build_system() set_system_op_conditions(m) init_system(m) - set_md_op_conditions(m.fs.md) + set_md_initial_conditions(m.fs.md) results = solve(m) # # results= solver.solve(m) @@ -777,16 +759,6 @@ def report_md_costing(m, blk): active_blks = m.fs.md.unit.get_active_process_blocks() - # permeate_flow_rate, brine_flow_rate, brine_salinity = md_output( - # m.fs, blk.n_time_points, model_options - # ) - - # time_period = [i for i in range(n_time_points)] - # t_minutes = [value(active_blks[i].fs.dt) * i / 60 for i in range(n_time_points)] - - # heat_in = [value(active_blks[i].fs.pre_thermal_power) for i in range(n_time_points)] - - # m.fs.water_recovery.display() 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' diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/PV.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/PV.py index 3a0f82ec..3cd3f789 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/PV.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/PV.py @@ -1,3 +1,4 @@ +import os from pyomo.environ import ( ConcreteModel, value, @@ -46,9 +47,27 @@ def build_system(): def build_pv(m): energy = m.fs.energy + parent_dir = os.path.abspath( + os.path.join(os.path.abspath(__file__), "..", "..", "..", "..", "..") + ) + + surrogate_dir = os.path.join( + parent_dir, + "solar_models", + "surrogate", + "pv", + ) + + dataset_filename = os.path.join(surrogate_dir, "data", "dataset.pkl") + + surrogate_filename = os.path.join( + surrogate_dir, + "pv_surrogate.json", + ) + energy.pv = PVSurrogate( - surrogate_model_file="/Users/zbinger/watertap-reflo/src/watertap_contrib/reflo/solar_models/surrogate/pv/pv_surrogate.json", - dataset_filename="/Users/zbinger/watertap-reflo/src/watertap_contrib/reflo/solar_models/surrogate/pv/data/dataset.pkl", + surrogate_model_file=surrogate_filename, + dataset_filename=dataset_filename, input_variables={ "labels": ["design_size"], "bounds": {"design_size": [1, 200000]}, @@ -270,3 +289,18 @@ def solve(m, solver=None, tee=True, raise_on_failure=True, debug=False): initialize(m) solve(m, debug=True) print(m.fs.energy.pv.display()) + + print( + f"{f'Design Size (W):':<30s}{value(pyunits.convert(m.fs.energy.pv.design_size, to_units=pyunits.watt)):<10,.1f}" + ) + print( + f"{f'Direct Cost Per Watt ($/W):':<30s}{value(m.fs.energy.costing.pv_surrogate.cost_per_watt_module):<10,.1f}" + ) + # print(f"{f'Direct Cost Should Be ($):':<30s}{value(pyunits.convert(m.fs.energy.pv.design_size, to_units=pyunits.watt))*value(m.fs.energy.costing.pv_surrogate.cost_per_watt_module):<10,.1f}") + print( + f"{f'Direct Cost Currently Is ($):':<30s}{value(m.fs.energy.pv.costing.capital_cost):<10,.1f}" + ) + + # print(m.fs.energy.pv.costing.direct_capital_cost_constraint.pprint()) + # print(m.fs.energy.pv.design_size()) + # print(m.fs.energy.costing.pv_surrogate.cost_per_watt_module()) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/deep_well_injection.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/deep_well_injection.py index 5ab0c7bb..399e5f23 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/deep_well_injection.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/deep_well_injection.py @@ -126,7 +126,7 @@ def init_DWI(m, blk, verbose=True, solver=None): solver = get_solver() optarg = solver.options - assert_no_degrees_of_freedom(m) + # assert_no_degrees_of_freedom(m) blk.unit.initialize(optarg=optarg, outlvl=idaeslogger.INFO) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/mec_kurby.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/mec_kurby.py new file mode 100644 index 00000000..5d9a7547 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/mec_kurby.py @@ -0,0 +1,699 @@ +from pyomo.environ import ( + ConcreteModel, + TransformationFactory, + check_optimal_termination, + assert_optimal_termination, + value, + units as pyunits, +) +from pyomo.network import Arc + +from idaes.models.unit_models import Product, Feed, StateJunction +from idaes.core import FlowsheetBlock, UnitModelCostingBlock +from idaes.core.solvers import get_solver +from idaes.core.util.initialization import propagate_state +from idaes.core.util.model_statistics import * +from idaes.core.util.scaling import ( + constraint_scaling_transform, + calculate_scaling_factors, + set_scaling_factor, +) + +from watertap.core.util.model_diagnostics.infeasible import * +from watertap.core.util.initialization import * +from watertap.property_models.water_prop_pack import WaterParameterBlock +from watertap.property_models.unit_specific.cryst_prop_pack import NaClParameterBlock + +from watertap_contrib.reflo.costing import TreatmentCosting +from watertap_contrib.reflo.unit_models.multi_effect_crystallizer import ( + MultiEffectCrystallizer, +) +from watertap_contrib.reflo.unit_models.crystallizer_effect import CrystallizerEffect + +rho = 1000 * pyunits.kg / pyunits.m**3 +feed_pressure = 101325 * pyunits.Pa +atm_pressure = 101325 * pyunits.Pa +feed_temperature = 273.15 + 20 + +__all__ = [ + "build_mec", + "init_mec", + "display_mec_streams", + "set_mec_scaling", + "set_mec_initial_scaling", + "display_mec_dof", +] + + +def build_system(): + + m = ConcreteModel() + m.fs = FlowsheetBlock(dynamic=False) + m.fs.costing = TreatmentCosting() + m.fs.properties = NaClParameterBlock() + m.fs.vapor_properties = WaterParameterBlock() + + m.fs.feed = Feed(property_package=m.fs.properties) + m.fs.product = Product(property_package=m.fs.properties) + m.fs.solids = Product(property_package=m.fs.properties) + + m.fs.MEC = mec = FlowsheetBlock(dynamic=False) + + build_mec(m, m.fs.MEC) + + m.fs.feed_to_unit = Arc(source=m.fs.feed.outlet, destination=mec.unit.inlet) + + m.fs.mec_to_product = Arc(source=mec.product.outlet, destination=m.fs.product.inlet) + + m.fs.mec_to_solids = Arc(source=mec.solids.outlet, destination=m.fs.solids.inlet) + + TransformationFactory("network.expand_arcs").apply_to(m) + + return m + + +def build_mec( + m, + blk, + prop_package=None, + prop_package_vapor=None, + number_effects=4, +): + + if prop_package is None: + prop_package = m.fs.properties + if prop_package_vapor is None: + prop_package_vapor = m.fs.vapor_properties + + blk.product = StateJunction(property_package=prop_package) + blk.solids = StateJunction(property_package=prop_package) + + blk.unit = MultiEffectCrystallizer( + property_package=prop_package, + property_package_vapor=prop_package_vapor, + number_effects=number_effects, + ) + + blk.unit_to_product = Arc( + source=blk.unit.outlet, + destination=blk.product.inlet, + ) + + blk.unit_to_solids = Arc( + source=blk.unit.solids, + destination=blk.solids.inlet, + ) + + TransformationFactory("network.expand_arcs").apply_to(blk) + + +def set_system_operating_conditions( + m, + blk, + Qin=2.8, # MGD + tds=12, # g/L + operating_pressures=[0.45, 0.25, 0.208, 0.095], + upstream_recovery=0.9, # assumed + crystallizer_yield=0.5, + saturated_steam_pressure_gage=3, + heat_transfer_coefficient=0.1, + eps=1e-8, + **kwargs, +): + Qin = Qin * pyunits.Mgallons / pyunits.day + tds = tds * pyunits.gram / pyunits.liter + tds = tds / (1 - upstream_recovery) + saturated_steam_pressure = atm_pressure + pyunits.convert( + saturated_steam_pressure_gage * pyunits.bar, to_units=pyunits.Pa + ) + + m.flow_mass_water = pyunits.convert(Qin * rho, to_units=pyunits.kg / pyunits.s) + m.flow_mass_tds = pyunits.convert(Qin * tds, to_units=pyunits.kg / pyunits.s) + m.upstream_recovery = upstream_recovery + m.operating_pressures = operating_pressures + m.crystallizer_yield = crystallizer_yield + m.heat_transfer_coefficient = heat_transfer_coefficient + m.saturated_steam_pressure = saturated_steam_pressure + m.saturated_steam_pressure_gage = saturated_steam_pressure_gage + + m.fs.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"].fix(m.flow_mass_water) + m.fs.feed.properties[0].flow_mass_phase_comp["Liq", "NaCl"].fix(m.flow_mass_tds) + m.fs.feed.properties[0].flow_mass_phase_comp["Sol", "NaCl"].fix(0) + m.fs.feed.properties[0].temperature.fix(298.15) + m.fs.feed.properties[0].pressure.fix(101325) + + m.fs.feed.properties[0].flow_vol_phase["Liq"] + + +def init_system(m, blk): + + m.fs.feed.properties[0].conc_mass_phase_comp + m.fs.feed.initialize() + propagate_state(m.fs.feed_to_unit) + + init_mec(m, blk) + + propagate_state(m.fs.MEC.unit_to_product) + m.fs.MEC.product.initialize() + + propagate_state(m.fs.mec_to_product) + m.fs.product.initialize() + + propagate_state(m.fs.MEC.unit_to_solids) + m.fs.MEC.solids.initialize() + + propagate_state(m.fs.mec_to_solids) + m.fs.solids.initialize() + + add_mec_costing(m, m.fs.MEC) + m.fs.costing.cost_process() + m.fs.costing.add_LCOW(m.fs.product.properties[0].flow_vol_phase["Liq"]) + m.fs.costing.initialize() + + +def init_mec(m, blk, feed_props=None, verbose=True, solver=None): + + if feed_props is None: + feed_props = m.fs.feed.properties[0] + + feed_props.conc_mass_phase_comp + feed_props.flow_vol_phase + feed_props.parent_block().initialize() + + tds = feed_props.conc_mass_phase_comp["Liq", "NaCl"] + + total_flow = (feed_props.flow_mass_phase_comp["Liq", "H2O"] + + feed_props.flow_mass_phase_comp["Liq", "NaCl"]) + unit_water_flow = feed_props.flow_mass_phase_comp["Liq", "H2O"] / total_flow + unit_NaCl_flow = feed_props.flow_mass_phase_comp["Liq", "NaCl"] / total_flow + # tds = 120 * pyunits.kg / pyunits.m**3 + + mec = blk.unit + assert len(m.operating_pressures) == mec.config.number_effects + + set_mec_initial_scaling(m, blk) + + """ + 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 = unit_water_flow * pyunits.kg / pyunits.s + flow_mass_phase_salt_per = unit_NaCl_flow * pyunits.kg / pyunits.s + + saturated_steam_pressure = atm_pressure + pyunits.convert( + m.saturated_steam_pressure_gage * pyunits.bar, to_units=pyunits.Pa + ) + + ### FIX UNIT MODEL PARAMETERS + for (_, eff), op_pressure in zip(mec.effects.items(), m.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(m.crystallizer_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(m.heat_transfer_coefficient) + + first_effect = mec.effects[1].effect + + first_effect.overall_heat_transfer_coefficient.fix(m.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) + + 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() + + solver = get_solver() + results = solver.solve(mec) + assert_optimal_termination(results) + results = solver.solve(blk) + assert_optimal_termination(results) + + 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.control_volume.properties_in[0].flow_mass_phase_comp["Liq", "H2O"].fix( + m.flow_mass_water + ) + mec.control_volume.properties_in[0].flow_mass_phase_comp["Liq", "NaCl"].fix( + m.flow_mass_tds + ) + + set_mec_scaling(m, blk) + + results = solver.solve(mec) + assert_optimal_termination(results) + results = solver.solve(blk) + assert_optimal_termination(results) + + for k, v in blk.unit.control_volume.properties_in[0].define_port_members().items(): + if k == "flow_mass_phase_comp": + for i, vv in v.items(): + vv.unfix() + else: + v.unfix() + + +def set_mec_initial_scaling(m, blk): + """ + Note: + Keep in mind that we assumes feed flow rate to the 1st effect to be 1 kg/s, + and the total feed flow rate is to be determined + """ + m.fs.properties.set_default_scaling( + "flow_mass_phase_comp", 1e-1, index=("Liq", "H2O") + ) + m.fs.properties.set_default_scaling( + "flow_mass_phase_comp", 1e-1, index=("Liq", "NaCl") + ) + m.fs.properties.set_default_scaling( + "flow_mass_phase_comp", 1e-1, index=("Vap", "H2O") + ) + m.fs.properties.set_default_scaling( + "flow_mass_phase_comp", 1e-1, index=("Sol", "NaCl") + ) + m.fs.vapor_properties.set_default_scaling( + "flow_mass_phase_comp", 1e-1, index=("Vap", "H2O") + ) + m.fs.vapor_properties.set_default_scaling( + "flow_mass_phase_comp", 1, index=("Liq", "H2O") + ) + + +def set_mec_scaling(m, blk): + + m.fs.properties.set_default_scaling( + "flow_mass_phase_comp", + 1 / value(m.flow_mass_water), + index=("Liq", "H2O"), + ) + m.fs.properties.set_default_scaling( + "flow_mass_phase_comp", + 1 / value(m.flow_mass_tds), + index=("Liq", "NaCl"), + ) + m.fs.properties.set_default_scaling( + "flow_mass_phase_comp", 10, index=("Vap", "H2O") + ) + m.fs.properties.set_default_scaling( + "flow_mass_phase_comp", 1e-2, index=("Sol", "NaCl") + ) + m.fs.vapor_properties.set_default_scaling( + "flow_mass_phase_comp", 1e-2, index=("Vap", "H2O") + ) + m.fs.vapor_properties.set_default_scaling( + "flow_mass_phase_comp", 1, index=("Liq", "H2O") + ) + + calculate_scaling_factors(blk) + + +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 display_mec_dof(m, blk, where=None): + if where is not None: + print(f"\n{where}") + else: + print() + for n, eff in blk.unit.effects.items(): + print(f"DOF effect {n}: {degrees_of_freedom(eff.effect)}") + print(f"Degrees of Freedom model: {degrees_of_freedom(m)}") + print(f"Degrees of Freedom MEC blk: {degrees_of_freedom(blk)}") + print(f"Degrees of Freedom MEC unit: {degrees_of_freedom(blk.unit)}") + + +def display_mec_streams(m, blk): + + fe = blk.unit.effects[1].effect # first effect + + print("\nm.fs.feed") + print( + f"\t{'Feed Mass Flow In Liq, H2O:':<50} {value(m.fs.feed.properties[0].flow_mass_phase_comp['Liq', 'H2O']):<20.2f} kg/s" + ) + print( + f"\t{'Feed Mass Flow In Liq, TDS:':<50} {value(m.fs.feed.properties[0].flow_mass_phase_comp['Liq', 'NaCl']):<20.2f} kg/s" + ) + print( + f"\t{'Feed Mass Flow In Sol, TDS:':<50} {value(m.fs.feed.properties[0].flow_mass_phase_comp['Sol', 'NaCl']):<20.2e} kg/s" + ) + print( + f"\t{'Feed Mass Flow In Vap, H2O:':<50} {value(m.fs.feed.properties[0].flow_mass_phase_comp['Vap', 'H2O']):<20.2f} kg/s" + ) + # print("\nMEC Feed blk") + # print(f"\t{'MEC Feed Mass Flow In Liq, H2O:':<50} {value(blk.feed.properties[0].flow_mass_phase_comp['Liq', 'H2O']):<20.2f} kg/s") + # print(f"\t{'MEC Feed Mass Flow In Liq, TDS:':<50} {value(blk.feed.properties[0].flow_mass_phase_comp['Liq', 'NaCl']):<20.2f} kg/s") + # print(f"\t{'MEC Feed Mass Flow In Sol, TDS:':<50} {value(blk.feed.properties[0].flow_mass_phase_comp['Sol', 'NaCl']):<20.2e} kg/s") + # print(f"\t{'MEC Feed Mass Flow In Vap, H2O:':<50} {value(blk.feed.properties[0].flow_mass_phase_comp['Vap', 'H2O']):<20.2f} kg/s") + for n, eff in blk.unit.effects.items(): + print(f"\nMEC Effect {n}") + print( + f"\t{f'Effect {n} TDS Conc:':<50} {value(blk.unit.effects[n].effect.properties_in[0].conc_mass_phase_comp['Liq', 'NaCl']):<20.2f} kg/m3" + ) + print( + f"\t{f'Effect {n} Mass Flow In Liq, H2O:':<50} {value(blk.unit.effects[n].effect.properties_in[0].flow_mass_phase_comp['Liq', 'H2O']):<20.2f} kg/s" + ) + print( + f"\t{f'Effect {n} Mass Flow In Liq, TDS:':<50} {value(blk.unit.effects[n].effect.properties_in[0].flow_mass_phase_comp['Liq', 'NaCl']):<20.2f} kg/s" + ) + print( + f"\t{f'Effect {n} Mass Flow In Sol, TDS:':<50} {value(blk.unit.effects[n].effect.properties_in[0].flow_mass_phase_comp['Sol', 'NaCl']):<20.2e} kg/s" + ) + print( + f"\t{f'Effect {n} Mass Flow In Vap, H2O:':<50} {value(blk.unit.effects[n].effect.properties_in[0].flow_mass_phase_comp['Vap', 'H2O']):<20.2f} kg/s" + ) + if n == 1: + print( + f"\t{f'Effect {n} Mass Flow In Vap, H2O:':<50} {value(blk.unit.effects[n].effect.heating_steam[0].flow_mass_phase_comp['Vap', 'H2O']):<20.2f} kg/s" + ) + # print("\nm.fs.steam") + # print(f"\t{'Steam Mass Flow In Liq, H2O:':<50} {value(m.fs.steam.properties[0].flow_mass_phase_comp['Liq', 'H2O']):<20.2f} kg/s") + # print(f"\t{'Steam Mass Flow In Vap, H2O:':<50} {value(m.fs.steam.properties[0].flow_mass_phase_comp['Vap', 'H2O']):<20.2f} kg/s") + # print("\nMEC Steam blk") + # print(f"\t{'MEC Steam Mass Flow In Liq, H2O:':<50} {value(blk.steam.properties[0].flow_mass_phase_comp['Liq', 'H2O']):<20.2f} kg/s") + # print(f"\t{'MEC Steam Mass Flow In Vap, H2O:':<50} {value(blk.steam.properties[0].flow_mass_phase_comp['Vap', 'H2O']):<20.2f} kg/s") + print("\nMEC CV IN") + print( + f"\t{'MEC Control Volume Mass Flow In Liq, H2O:':<50} {value(blk.unit.control_volume.properties_in[0].flow_mass_phase_comp['Liq', 'H2O']):<20.2f} kg/s" + ) + print( + f"\t{'MEC Control Volume Mass Flow In Liq, TDS:':<50} {value(blk.unit.control_volume.properties_in[0].flow_mass_phase_comp['Liq', 'NaCl']):<20.2f} kg/s" + ) + print( + f"\t{'MEC Control Volume Mass Flow In Sol, TDS:':<50} {value(blk.unit.control_volume.properties_in[0].flow_mass_phase_comp['Sol', 'NaCl']):<20.2e} kg/s" + ) + print( + f"\t{'MEC Control Volume Mass Flow In Vap, H2O:':<50} {value(blk.unit.control_volume.properties_in[0].flow_mass_phase_comp['Vap', 'H2O']):<20.2f} kg/s" + ) + print("\nMEC CV OUT") + print( + f"\t{'MEC Control Volume Mass Flow Out Liq, H2O:':<50} {value(blk.unit.control_volume.properties_out[0].flow_mass_phase_comp['Liq', 'H2O']):<20.2f} kg/s" + ) + print( + f"\t{'MEC Control Volume Mass Flow Out Liq, TDS:':<50} {value(blk.unit.control_volume.properties_out[0].flow_mass_phase_comp['Liq', 'NaCl']):<20.2f} kg/s" + ) + print( + f"\t{'MEC Control Volume Mass Flow Out Sol, TDS:':<50} {value(blk.unit.control_volume.properties_out[0].flow_mass_phase_comp['Sol', 'NaCl']):<20.2e} kg/s" + ) + print( + f"\t{'MEC Control Volume Mass Flow Out Vap, H2O:':<50} {value(blk.unit.control_volume.properties_out[0].flow_mass_phase_comp['Vap', 'H2O']):<20.2f} kg/s" + ) + + total_mass_flow_water = sum( + value( + blk.unit.effects[n] + .effect.properties_in[0] + .flow_mass_phase_comp["Liq", "H2O"] + ) + for n, _ in blk.unit.effects.items() + ) + total_mass_flow_tds = sum( + value( + blk.unit.effects[n] + .effect.properties_in[0] + .flow_mass_phase_comp["Liq", "NaCl"] + ) + for n, _ in blk.unit.effects.items() + ) + + print(f"\n{'SUM EFFECT MASS FLOW WATER:':<50} {total_mass_flow_water}") + print(f"\n{'SUM EFFECT MASS FLOW TDS:':<50} {total_mass_flow_tds}") + + print() + + display_mec_dof(m, blk) + + +if __name__ == "__main__": + solver = get_solver() + m = build_system() + blk = m.fs.MEC + + set_system_operating_conditions(m, blk) + init_system(m, blk) + + results = solver.solve(m) + assert_optimal_termination(results) + display_mec_streams(m, blk) + m.fs.costing.LCOW.display() + +# def set_mec_operating_conditions( +# m, +# blk, +# Qin=2.8, # MGD +# tds=12, # g/L +# operating_pressures=[0.45, 0.25, 0.208, 0.095], +# upstream_recovery=0.9, # assumed +# crystallizer_yield=0.5, +# saturated_steam_pressure_gage=3, +# heat_transfer_coefficient=0.1, +# eps=1e-8, +# **kwargs +# ): +# rho = 1000 * pyunits.kg / pyunits.m**3 +# Qin = Qin * pyunits.Mgallons / pyunits.day +# tds = tds * pyunits.gram / pyunits.liter +# tds = tds / (1 - upstream_recovery) + +# mec = blk.unit +# assert len(operating_pressures) == mec.config.number_effects + +# set_mec_initial_scaling(m, blk) + +# # m.flow_mass_water = pyunits.convert(Qin * rho, to_units=pyunits.kg / pyunits.s) +# # m.flow_mass_tds = pyunits.convert(Qin * tds, to_units=pyunits.kg / pyunits.s) + +# """ +# 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. +# """ + +# display_mec_dof(m, blk, where="Beginning set_mec_operating_conditions") +# flow_mass_phase_water_per = rho / (rho + tds) * 1 * pyunits.kg / pyunits.s +# flow_mass_phase_salt_per = tds / (rho + tds) * 1 * pyunits.kg / pyunits.s + +# saturated_steam_pressure = atm_pressure + pyunits.convert( +# saturated_steam_pressure_gage * 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(crystallizer_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 +# By this point, each effect is fully specified, so their DOF should be 0. +# However, the multi-effect flowsheet is over-constrianted by energy_flow_constr, +# which connect energy flow between effects, and the DOF should be negative (n_effects - 1) +# """ + +# display_mec_dof(m, blk, where="After 1 kg/s flow rate ") +# # assert degrees_of_freedom(blk) == -3 + +# ### INITIALIZE FOR EACH EFFECT +# """ +# Note: this is essentially to have an initial guess of the crysts, +# and to populate the feed concentration to all effects +# """ +# for n, eff in mec.effects.items(): +# eff.effect.initialize() + +# display_mec_dof(m, blk, where="After effect initialize") + +# ### UNFIX THE INLET FLOW RATES OF EACH EFFECT +# """ +# Note: this is to release the volumetric inlet flow entering different effects +# with the same salinity +# """ +# 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() + +# eff.effect.properties_in[0].conc_mass_phase_comp.display() + +# display_mec_dof(m, blk, where="After unfixing effect flow mass, fixing conc mass") + +# """ +# Note: by this point, the multi-effect flow sheet should be fully specified (DOF=0), +# while inlet flows to effect 2-4 should be subject to the previous effect (DOF=1) +# """ + + +# display_mec_dof(m, blk, where="before first MEC solve") +# # assert False +# results = solver.solve(mec) +# assert_optimal_termination(results) +# display_mec_streams(m, blk) +# results = solver.solve(blk) +# assert_optimal_termination(results) +# display_mec_streams(m, blk) +# # assert False + +# # mec.control_volume.properties_in[0].pressure.unfix() +# # mec.control_volume.properties_in[0].temperature.unfix() + + +# 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.control_volume.properties_in[0].flow_mass_phase_comp["Liq", "H2O"].fix( +# m.flow_mass_water +# ) +# mec.control_volume.properties_in[0].flow_mass_phase_comp["Liq", "NaCl"].fix( +# m.flow_mass_tds +# ) +# display_mec_dof(m, blk, where="After unfixing first effect flow_mass, fixing CV flow mass") + +# m.fs.properties.set_default_scaling( +# "flow_mass_phase_comp", +# 1 / value(m.flow_mass_water), +# index=("Liq", "H2O"), +# ) +# m.fs.properties.set_default_scaling( +# "flow_mass_phase_comp", +# 1 / value(m.flow_mass_tds), +# index=("Liq", "NaCl"), +# ) +# m.fs.properties.set_default_scaling( +# "flow_mass_phase_comp", 10, index=("Vap", "H2O") +# ) +# m.fs.properties.set_default_scaling( +# "flow_mass_phase_comp", 1e-2, index=("Sol", "NaCl") +# ) +# m.fs.vapor_properties.set_default_scaling( +# "flow_mass_phase_comp", 1e-2, index=("Vap", "H2O") +# ) +# m.fs.vapor_properties.set_default_scaling( +# "flow_mass_phase_comp", 1, index=("Liq", "H2O") +# ) + +# calculate_scaling_factors(m) +# results = solver.solve(mec) +# assert_optimal_termination(results) +# display_mec_streams(m, blk) +# results = solver.solve(blk) +# assert_optimal_termination(results) +# display_mec_streams(m, blk) +# # assert False +# prop_in_state_dict = blk.unit.control_volume.properties_in[0].define_port_members() +# for k, v in prop_in_state_dict.items(): +# # print(k, v) +# if k == "flow_mass_phase_comp": +# for i, vv in v.items(): +# # print(k, i, vv) +# vv.unfix() +# else: +# v.unfix() + +# display_mec_dof(m, blk, where="After unfixing blk.steam state vars") +# results = solver.solve(m) +# assert_optimal_termination(results) +# display_mec_streams(m, blk) +# assert False + +# first_effect.properties_in[0].display() +# assert False +# # first_effect.properties_in[0].flow_mass_phase_comp["Liq", "H2O"].unfix() +# # first_effect.properties_in[0].flow_mass_phase_comp["Liq", "NaCl"].unfix() +# # first_effect.properties_in[0].flow_mass_phase_comp["Liq", "H2O"].setlb(m.flow_mass_water / 4) +# # first_effect.properties_in[0].flow_mass_phase_comp["Liq", "NaCl"].setlb(m.flow_mass_tds/ 4) +# blk.unit.control_volume.properties_in[0].flow_mass_phase_comp["Liq", "H2O"].set_value(m.flow_mass_water) +# blk.unit.control_volume.properties_in[0].flow_mass_phase_comp["Liq", "NaCl"].set_value(m.flow_mass_tds) + + +# # display_mec_dof(m, blk, where="After unfixing first effect flow_mass, fixing CV flow mass") +# # first_effect.heating_steam[0].display() + +# display_mec_streams(m, blk) +# # display_mec_dof(m, blk) + + +# # mec.control_volume.initialize() \ No newline at end of file diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/ro_system.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/ro_system.py index c8672324..72090e94 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/ro_system.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/ro_system.py @@ -326,9 +326,9 @@ def init_ro_system(m, blk, verbose=True, solver=None): print( f'RO Recovery: {100 * (value(blk.product.properties[0].flow_mass_phase_comp["Liq", "H2O"]) / value(blk.feed.properties[0].flow_mass_phase_comp["Liq", "H2O"])):<5.2f}%' ) - print( - f'{"Average Flux":<30s}{value(blk.stage[1].module.flux_vol_phase_avg[0, "Liq"]):<10.2f}{pyunits.get_units(blk.stage[1].module.flux_vol_phase_avg[0, "Liq"])}' - ) + # print( + # f'{"Average Flux":<30s}{value(blk.stage[1].module.flux_vol_phase_avg[0, "Liq"]):<10.2f}{pyunits.get_units(blk.stage[1].module.flux_vol_phase_avg[0, "Liq"])}' + # ) def init_ro_stage(m, stage, solver=None): @@ -571,45 +571,68 @@ def set_ro_system_operating_conditions(m, blk, mem_area=100, RO_pressure=15e5): stage.module.A_comp.fix(mem_A) stage.module.B_comp.fix(mem_B) stage.module.area.fix(area / idx) - stage.module.feed_side.velocity[0, 0].fix(0.25) + stage.module.feed_side.velocity[0, 0].fix(0.35) # stage.module.length.fix(length) - # stage.module.width.setub(20000) + stage.module.width.setub(20000) stage.module.mixed_permeate[0].pressure.fix(pressure_atm) stage.module.feed_side.channel_height.fix(height) stage.module.feed_side.spacer_porosity.fix(spacer_porosity) - stage.module.flux_vol_phase_avg[0, "Liq"].setlb(5) - stage.module.flux_vol_phase_avg[0, "Liq"].setub(60) + # stage.module.flux_vol_phase_avg[0, "Liq"].setlb(5) + # stage.module.flux_vol_phase_avg[0, "Liq"].setub(60) + + stage.module.feed_side.friction_factor_darcy.setub(50) for e in stage.module.flux_mass_phase_comp: if e[-1] == "H2O": stage.module.flux_mass_phase_comp[e].setlb(1e-5) stage.module.flux_mass_phase_comp[e].setub(0.99) - # stage.eq_max_water_flux = Constraint( - # expr= stage.module.flux_vol_phase_avg[0] <= 40 - # ) - - # stage.eq_min_water_flux = Constraint( - # expr=pyunits.convert( - # stage.module.flux_mass_phase_comp_avg[ - # 0, "Liq", "H2O" - # ] - # / stage.module.feed_side.properties[0.0,0.0].dens_mass_phase["Liq"], - # to_units=pyunits.liter / pyunits.m**2 / pyunits.hr, - # ) >= 10 * pyunits.liter / pyunits.m**2 / pyunits.hr - # ) - - # blk.eq_minimum_water_flux = Constraint( - # expr=pyunits.convert( - # m.fs.treatment.RO.stage[1].module.flux_mass_phase_comp_avg[ - # 0.0, "Liq", "H2O" - # ], - # to_units=pyunits.kg / pyunits.hr / pyunits.m**2, - # ) - # <= 40 * pyunits.kg / pyunits.hr / pyunits.m**2 - # ) + # for idx, stage in blk.stage.items(): + # # stage.module.width.setub(5000) + # # stage.module.feed_side.velocity[0, 0].unfix() + # # stage.module.feed_side.velocity[0, 1].setlb(0.0) + # stage.module.feed_side.K.setlb(1e-6) + # stage.module.feed_side.friction_factor_darcy.setub(50) + # stage.module.flux_mass_phase_comp.setub(1) + # # stage.module.flux_mass_phase_comp.setlb(1e-5) + # stage.module.feed_side.cp_modulus.setub(10) + # stage.module.rejection_phase_comp.setlb(1e-4) + # stage.module.feed_side.N_Re.setlb(1) + # stage.module.recovery_mass_phase_comp.setlb(1e-7) + + blk.total_membrane_area = Var( + initialize=10000, + domain=NonNegativeReals, + units=pyunits.m**2, + doc="Total RO System Membrane Area", + ) + + blk.eq_total_membrane_area = Constraint( + expr=blk.total_membrane_area + == sum([stage.module.area for idx, stage in blk.stage.items()]) + ) + + # stage.eq_min_water_flux = Constraint( + # expr=pyunits.convert( + # stage.module.flux_mass_phase_comp_avg[ + # 0, "Liq", "H2O" + # ] + # / stage.module.feed_side.properties[0.0,0.0].dens_mass_phase["Liq"], + # to_units=pyunits.liter / pyunits.m**2 / pyunits.hr, + # ) >= 10 * pyunits.liter / pyunits.m**2 / pyunits.hr + # ) + + # blk.eq_minimum_water_flux = Constraint( + # expr=pyunits.convert( + # m.fs.treatment.RO.stage[1].module.flux_mass_phase_comp_avg[ + # 0.0, "Liq", "H2O" + # ], + # to_units=pyunits.kg / pyunits.hr / pyunits.m**2, + # ) + # <= 40 * pyunits.kg / pyunits.hr / pyunits.m**2 + # ) # add_ro_scaling(m, stage) # iscale.calculate_scaling_factors(m) @@ -732,9 +755,9 @@ def report_RO(m, blk): f'{"RO Operating Pressure":<30s}{value(pyunits.convert(blk.feed.properties[0].pressure, to_units=pyunits.bar)):<10.1f}{"bar"}' ) print(f'{"RO Membrane Area":<30s}{value(blk.stage[1].module.area):<10.1f}{"m^2"}') - print( - f'{"Average Flux":<30s}{value(blk.stage[1].module.flux_vol_phase_avg[0, "Liq"]):<10.2f}{pyunits.get_units(blk.stage[1].module.flux_vol_phase_avg[0, "Liq"])}' - ) + # print( + # f'{"Average Flux":<30s}{value(blk.stage[1].module.flux_vol_phase_avg[0, "Liq"]):<10.2f}{pyunits.get_units(blk.stage[1].module.flux_vol_phase_avg[0, "Liq"])}' + # ) print(blk.stage[1].module.report()) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/softener.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/softener.py index 3d75b428..296b3c02 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/softener.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/components/softener.py @@ -221,7 +221,7 @@ def set_softener_op_conditions( soft.removal_efficiency.fix() # ...then refix non important ones for comp in non_important_comps: - m.fs.softener.unit.removal_efficiency[comp].fix(non_important_removals) + soft.removal_efficiency[comp].fix(non_important_removals) prop_out = soft.properties_out[0.0] # prop_out.temperature.fix(293) @@ -239,19 +239,23 @@ def set_softener_op_conditions( soft.retention_time_sed.fix(120) soft.retention_time_recarb.fix(20) soft.frac_mass_water_recovery.fix(0.99) - soft.vel_gradient_mix.fix(300) - soft.vel_gradient_floc.fix(50) # soft.removal_efficiency["SiO2"].fix(0) # soft.CO2_CaCO3.fix(0.10) + # soft.sedimentation_overflow.fix() + + soft.CO2_CaCO3.fix(0.063) + # # soft.excess_CaO.fix(0) # soft.CO2_second_basin.fix(0) # soft.Na2CO3_dosing.fix(0) soft.MgCl2_dosing.fix(0) + soft.vel_gradient_mix.fix(300) + soft.vel_gradient_floc.fix(50) print(f"System Degrees of Freedom: {degrees_of_freedom(m)}") - print(f"Softener Degrees of Freedom: {degrees_of_freedom(m.fs.softener.unit)}") + print(f"Softener Degrees of Freedom: {degrees_of_freedom(soft)}") # assert False @@ -308,7 +312,11 @@ def init_system(blk, solver=None): print("\n\n-------------------- INITIALIZING SYSTEM --------------------\n\n") print(f"System Degrees of Freedom: {degrees_of_freedom(m)}") print(f"Softener Degrees of Freedom: {degrees_of_freedom(m.fs.softener)}") - # assert_no_degrees_of_freedom(m) + + if degrees_of_freedom(m) != 0: + breakdown_dof(m.fs.softener, detailed=True) + assert_no_degrees_of_freedom(m) + breakdown_dof(m.fs.softener, detailed=True) print("\n\n") m.fs.feed.initialize() @@ -338,8 +346,8 @@ def init_softener(m, blk, verbose=True, solver=None): "\n\n-------------------- INITIALIZING WATER SOFTENER --------------------\n\n" ) # assert_units_consistent(m) - print(f"System Degrees of Freedom: {degrees_of_freedom(m)}") - print(f"Softener Degrees of Freedom: {degrees_of_freedom(m.fs.softener)}") + # print(f"System Degrees of Freedom: {degrees_of_freedom(m)}") + # print(f"Softener Degrees of Freedom: {degrees_of_freedom(m.fs.softener)}") blk.initialize() # try: # blk.initialize() @@ -484,50 +492,90 @@ def print_softening_costing_breakdown(blk): ) +def breakdown_dof(blk, detailed=False): + all_vars = [ + v for v in blk.component_data_objects(ctype=Var, active=True, descend_into=True) + ] + equalities = [c for c in activated_equalities_generator(blk)] + active_vars = variables_in_activated_equalities_set(blk) + fixed_active_vars = fixed_variables_in_activated_equalities_set(blk) + unfixed_active_vars = unfixed_variables_in_activated_equalities_set(blk) + print("\n ===============DOF Breakdown================\n") + print(f"Degrees of Freedom: {degrees_of_freedom(blk)}") + + if detailed: + # print(f"Activated Variables: ({len(active_vars)})") + # for v in active_vars: + # print(f" {v}") + # print(f"Activated Equalities: ({len(equalities)})") + # for c in equalities: + # print(f" {c}") + + print(f"Fixed Active Vars: ({len(fixed_active_vars)})") + for v in fixed_active_vars: + print(f" {v}") + + print(f"Unfixed Active Vars: ({len(unfixed_active_vars)})") + for v in unfixed_active_vars: + # subsystem = v.name.split(".")[1] + # if subsystem == "treatment": + # component = v.name.split(".")[2] + # if (component != "RO") and (component != "EC"): + # print(f" {v}") + print(f" {v}") + print("\n") + print(f" {f' Active Vars':<30s}{len(active_vars)}") + print(f"{'-'}{f' Fixed Active Vars':<30s}{len(fixed_active_vars)}") + print(f"{'-'}{f' Activated Equalities':<30s}{len(equalities)}") + print(f"{'='}{f' Degrees of Freedom':<30s}{degrees_of_freedom(blk)}") + + # calculate_variable_from_constraint if __name__ == "__main__": - from watertap_contrib.reflo.analysis.case_studies.KBHDP.utils.utils import check_jac + # from watertap_contrib.reflo.analysis.case_studies.KBHDP.utils.utils import check_jac file_dir = os.path.dirname(os.path.abspath(__file__)) m = build_system() soft = m.fs.softener.unit - soft.properties_out[0].conc_mass_phase_comp[...] - soft.sedimentation_overflow.fix() - soft.CO2_CaCO3.fix(0.063) - soft.ca_eff_target.fix(0.01) - soft.mg_eff_target.fix(0.01) + # soft.properties_out[0].conc_mass_phase_comp[...] + # # soft.sedimentation_overflow.fix() + # # soft.CO2_CaCO3.fix(0.063) + # soft.ca_eff_target.fix(0.01) + # soft.mg_eff_target.fix(0.01) set_system_operating_conditions(m) set_softener_op_conditions(m, m.fs.softener.unit) print(f"\n\n\n\n\nDOF = {degrees_of_freedom(m)}\n\n\n\n") - add_softener_costing(m, m.fs.softener) - m.fs.costing.cost_process() - m.fs.costing.initialize() + # add_softener_costing(m, m.fs.softener) + # m.fs.costing.cost_process() + # m.fs.costing.initialize() - m.fs.costing.add_LCOW(0.2 * m.fs.softener.unit.properties_in[0].flow_vol) - m.fs.obj = Objective(expr=m.fs.costing.LCOW) + # m.fs.costing.add_LCOW(0.2 * m.fs.softener.unit.properties_in[0].flow_vol) + # m.fs.obj = Objective(expr=m.fs.costing.LCOW) init_system(m) solve(m) - print_softening_costing_breakdown(m.fs.softener) - print(f'{"Softening LCOW":<35s}{f"${m.fs.costing.LCOW():<25,.2f}"}') - report_softener(m, m.fs.softener.unit) - # print(m.fs.costing.display()) - print( - f'{"Product Flow":<35s}{f"{value(pyunits.convert(m.fs.feed.properties[0].flow_vol, to_units=pyunits.m **3 * pyunits.yr ** -1)):<25,.1f}"}{"m3/yr":<25s}' - ) - print( - f'{"Total Capital Cost":<35s}{f"${m.fs.costing.total_capital_cost():<25,.0f}"}' - ) - print( - f'{"Total Operating Cost":<35s}{f"${m.fs.costing.total_operating_cost():<25,.0f}"}' - ) - for flow in m.fs.costing.aggregate_flow_costs: - print( - f'{f" Flow Cost [{flow}]":<35s}{f"${m.fs.costing.aggregate_flow_costs[flow]():<25,.3f}"}' - ) + print(m.fs.softener.display()) + + # print_softening_costing_breakdown(m.fs.softener) + # print(f'{"Softening LCOW":<35s}{f"${m.fs.costing.LCOW():<25,.2f}"}') + # report_softener(m, m.fs.softener.unit) + # # print(m.fs.costing.display()) + # print( + # f'{"Product Flow":<35s}{f"{value(pyunits.convert(m.fs.feed.properties[0].flow_vol, to_units=pyunits.m **3 * pyunits.yr ** -1)):<25,.1f}"}{"m3/yr":<25s}' + # ) + # print( + # f'{"Total Capital Cost":<35s}{f"${m.fs.costing.total_capital_cost():<25,.0f}"}' + # ) + # print( + # f'{"Total Operating Cost":<35s}{f"${m.fs.costing.total_operating_cost():<25,.0f}"}' + # ) + # for flow in m.fs.costing.aggregate_flow_costs: + # print( + # f'{f" Flow Cost [{flow}]":<35s}{f"${m.fs.costing.aggregate_flow_costs[flow]():<25,.3f}"}' + # ) # assert_units_consistent(soft) # print(pyunits.get_units(soft.Mg_CaCO3)) # assert False diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/FPC_KBHDP_el_paso.pkl b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/FPC_KBHDP_el_paso.pkl new file mode 100644 index 00000000..ef78c136 Binary files /dev/null and b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/FPC_KBHDP_el_paso.pkl differ diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/FPC_KBHDP_el_paso_heat_load_1_25_hours_storage_0_12_temperature_hot_50_102.json b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/FPC_KBHDP_el_paso_heat_load_1_25_hours_storage_0_12_temperature_hot_50_102.json new file mode 100644 index 00000000..158398d6 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/FPC_KBHDP_el_paso_heat_load_1_25_hours_storage_0_12_temperature_hot_50_102.json @@ -0,0 +1 @@ +{"model_encoding": {"heat_annual_scaled": {"attr": {"x_data_columns": ["heat_load", "hours_storage", "temperature_hot"], 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+2000,12,31,18,30,0,0,0,-5,6,880,117,1.2000000000000002,0.18 +2000,12,31,19,30,0,0,0,-5,5,880,113,1.3,0.18 +2000,12,31,20,30,0,0,0,-6,4,880,113,1.4000000000000001,0.18 +2000,12,31,21,30,0,0,0,-6,4,880,116,1.4000000000000001,0.18 +2000,12,31,22,30,0,0,0,-6,4,880,121,1.3,0.18 +2000,12,31,23,30,0,0,0,-6,4,880,129,1.2000000000000002,0.18 diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/run_pysam_kbhdp_fpc.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/run_pysam_kbhdp_fpc.py new file mode 100644 index 00000000..d6f368e4 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/run_pysam_kbhdp_fpc.py @@ -0,0 +1,465 @@ +################################################################################# +# 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 os +import json + +import numpy as np +import pandas as pd +import time +import multiprocessing +from itertools import product +import matplotlib.pyplot as plt +import PySAM.Swh as swh + +__all__ = [ + "read_module_datafile", + "load_config", + "setup_model", + "run_model", + "setup_and_run", + "run_pysam_kbhdp_fpc", +] + + +__location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__))) +weather_file = os.path.join(__location__, "el_paso_texas-KBHDP-weather.csv") +param_file = os.path.join(__location__, "swh-kbhdp.json") + + +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 system_capacity_computed(tech_model): + """ + Computes the system capacity in kW + + Equation taken from SAM UI + """ + system_capacity = ( + tech_model.value("area_coll") + * tech_model.value("ncoll") + * (tech_model.value("FRta") - tech_model.value("FRUL") * 30 / 1000) + ) + return system_capacity + + +def setup_model( + temperatures, + weather_file=None, + weather_data=None, + config_file=None, + config_data=None, +): + + tech_model = swh.new() + + for k, v in config_data.items(): + tech_model.value(k, v) + + if weather_file is not None: + tech_model.value("solar_resource_file", weather_file) + elif weather_data is not None: + tech_model.value("solar_resource_data", weather_data) + else: + raise Exception("Either weather_file or weather_data must be specified.") + + # Set constant temperatures + tech_model.value("custom_mains", 8760 * (temperatures["T_cold"],)) + + tech_model.value("T_set", temperatures["T_hot"]) + tech_model.value("T_room", temperatures["T_amb"]) + + # Set collector loop mass flow (this should be done automatically in SAM) + tech_model.value( + "mdot", tech_model.value("test_flow") * tech_model.value("ncoll") + ) # [kg/s] + + # Ensure system capacity parameter agreement + system_capacity_actual = system_capacity_computed(tech_model) + tech_model.value("system_capacity", system_capacity_actual) + + return tech_model + + +def run_model(tech_model, heat_load_mwt=None, hours_storage=None, temperature_hot=None): + """ + :param tech_model: PySAM technology model + :param heat_load_mwt: [MWt] + :param hours_storage: [hr] + :param temperature_hot: [C] + """ + cp_water = 4.181 # [kJ/kg-K] + density_water = 1000 # [kg/m3] + pump_power_per_collector = 45 / 2 # [W] + pipe_length_fixed = 9 # [m] + pipe_length_per_collector = 0.5 # [m] + + T_cold = tech_model.value("custom_mains")[0] # [C] + heat_load = heat_load_mwt * 1e3 if heat_load_mwt is not None else None # [kWt] + + print( + f"Running:\n\tHeat Load = {heat_load_mwt}\n\tHours Storage = {hours_storage}\n\tTemperature Hot = {temperature_hot}" + ) + + if heat_load is not None: + # Set heat load (system capacity) + n_collectors = round( + heat_load + / ( + tech_model.value("area_coll") + * (tech_model.value("FRta") - tech_model.value("FRUL") * 30 / 1000) + ) + ) # from SAM UI + tech_model.value("ncoll", n_collectors) + system_capacity_actual = system_capacity_computed(tech_model) + tech_model.value("system_capacity", system_capacity_actual) # [kW] + if temperature_hot is not None: + # Set hot outlet temperature + tech_model.value("T_set", temperature_hot) + if hours_storage is not None: + # Set hours of storage (tank volume) + hours_storage = max(hours_storage, 1e-3) # don't accept 0 hours + system_capacity = tech_model.value("system_capacity") # [kW] + T_hot = tech_model.value("T_set") # [C] + mass_tank_water = ( + hours_storage * 3600 * system_capacity / (cp_water * (T_hot - T_cold)) + ) # [kg] + volume_tank = mass_tank_water / density_water # [m3] + tech_model.value("V_tank", volume_tank) + + # Set collector loop and hot water mass flow rates + mdot_collectors = tech_model.value("test_flow") * tech_model.value("ncoll") + tech_model.value("mdot", mdot_collectors) # [kg/s] + T_hot = tech_model.value("T_set") # [C] + mdot_hot = ( + tech_model.value("system_capacity") / (cp_water * (T_hot - T_cold)) * 3600 + ) # [kg/hr] + tech_model.value("scaled_draw", 8760 * (mdot_hot,)) # [kg/hr] + + # Set pipe diameter and pump power + pipe_length = pipe_length_fixed + pipe_length_per_collector * tech_model.value( + "ncoll" + ) + tech_model.value("pipe_length", pipe_length) # [m] default is 0.019 m + pumping_power = pump_power_per_collector * tech_model.value("ncoll") + tech_model.value("pump_power", pumping_power) # [W] + + tech_model.execute() + + heat_annual = tech_model.value( + "annual_Q_deliv" + ) # [kWh] does not include electric heat, includes losses + electricity_annual = sum(tech_model.value("P_pump")) # [kWh] + frac_electricity_annual = ( + electricity_annual / heat_annual + ) # [-] for analysis only, plant beneficial if < 1 + + return { + "heat_annual": heat_annual, # [kWh] annual net thermal energy in year 1 + "electricity_annual": electricity_annual, # [kWhe] + } + + +def setup_and_run( + temperatures, weather_file, config_data, heat_load, hours_storage, temperature_hot +): + + tech_model = setup_model( + temperatures, weather_file=weather_file, config_data=config_data + ) + result = run_model(tech_model, heat_load, hours_storage, temperature_hot) + return result + + +def plot_contour( + df, x_label, y_label, z_label, units=None, grid=False, countour_lines=False +): + def _set_aspect(ax, aspect): + x_left, x_right = ax.get_xlim() + y_low, y_high = ax.get_ylim() + ax.set_aspect(abs((x_right - x_left) / (y_low - y_high)) * aspect) + + levels = 25 + df2 = df[[x_label, y_label, z_label]].pivot([y_label, x_label, z_label]) + y = df2.index.values + x = df2.columns.values + z = df2.values + fig, ax = plt.subplots(1, 1) + cs = ax.contourf(x, y, z, levels=levels) + if countour_lines: + cl = ax.contour(x, y, z, colors="black", levels=levels) + ax.clabel(cl, colors="black", fmt="%#.4g") + if grid: + ax.grid(color="black") + _set_aspect(ax, 0.5) + fig.colorbar(cs) + + if units is None: + x_units, y_units, z_units = "", "", "" + else: + x_units, y_units, z_units = [" [" + unit + "]" for unit in units] + ax.set_xlabel(x_label + x_units) + ax.set_ylabel(y_label + y_units) + ax.set_title(z_label + z_units) + plt.show() + + +def plot_3d(df, x_label, y_label, z_label, units=None): + fig = plt.figure(figsize=(8, 6)) + ax = fig.add_subplot(1, 1, 1, projection="3d") + surf = ax.plot_trisurf( + df[x_label], df[y_label], df[z_label], cmap=plt.cm.viridis, linewidth=0.2 + ) + + if units is None: + x_units, y_units, z_units = "", "", "" + else: + x_units, y_units, z_units = [" [" + unit + "]" for unit in units] + ax.set_xlabel(x_label + x_units) + ax.set_ylabel(y_label + y_units) + ax.set_title(z_label + z_units) + plt.show() + + +def plot_2d(df, x_label, y_label, units=None): + fig = plt.figure(figsize=(8, 6)) + ax = fig.add_subplot(1, 1, 1) + surf = ax.plot(df[x_label], df[y_label]) + + if units is None: + x_units, y_units = "", "" + else: + x_units, y_units = [" [" + unit + "]" for unit in units] + ax.set_xlabel(x_label + x_units) + ax.set_ylabel(y_label + y_units) + plt.show() + + +def plot_contours(df): + plot_contour( + df.query("temperature_hot == 70"), + "heat_load", + "hours_storage", + "heat_annual", + units=["MWt", "hr", "kWht"], + ) + plot_contour( + df.query("hours_storage == 12"), + "heat_load", + "temperature_hot", + "heat_annual", + units=["MWt", "C", "kWht"], + ) + plot_contour( + df.query("heat_load == 500"), + "hours_storage", + "temperature_hot", + "heat_annual", + units=["hr", "C", "kWht"], + ) + plot_contour( + df.query("temperature_hot == 70"), + "heat_load", + "hours_storage", + "electricity_annual", + units=["MWt", "hr", "kWhe"], + ) + plot_contour( + df.query("hours_storage == 12"), + "heat_load", + "temperature_hot", + "electricity_annual", + units=["MWt", "C", "kWhe"], + ) + plot_contour( + df.query("heat_load == 500"), + "hours_storage", + "temperature_hot", + "electricity_annual", + units=["hr", "C", "kWhe"], + ) + + +def plot_3ds(df): + plot_3d( + df.query("temperature_hot == 70"), + "heat_load", + "hours_storage", + "heat_annual", + units=["MWt", "hr", "kWht"], + ) + plot_3d( + df.query("hours_storage == 12"), + "heat_load", + "temperature_hot", + "heat_annual", + units=["MWt", "C", "kWht"], + ) + plot_3d( + df.query("heat_load == 6"), + "hours_storage", + "temperature_hot", + "heat_annual", + units=["hr", "C", "kWht"], + ) + plot_3d( + df.query("temperature_hot == 70"), + "heat_load", + "hours_storage", + "electricity_annual", + units=["MWt", "hr", "kWhe"], + ) + plot_3d( + df.query("hours_storage == 6"), + "heat_load", + "temperature_hot", + "electricity_annual", + units=["MWt", "C", "kWhe"], + ) + plot_3d( + df.query("heat_load == 6"), + "hours_storage", + "temperature_hot", + "electricity_annual", + units=["hr", "C", "kWhe"], + ) + + +def run_pysam_kbhdp_fpc( + heat_loads=np.linspace(1, 25, 25), + hours_storages=np.linspace(0, 12, 13), + temperature_hots=np.arange(50, 102, 2), + temperature_cold=20, + plot_saved_dataset=False, + run_pysam=True, + save_data=True, + use_multiprocessing=True, + dataset_filename="FPC_KBHDP_el_paso.pkl", +): + """ + Run PySAM to collect data for FPC surrogate model + for KBHPD case study + """ + + pysam_model_name = "SolarWaterHeatingCommercial" + + temperatures = { + "T_cold": temperature_cold, + "T_hot": 70, # this will be overwritten by temperature_hot value + "T_amb": 18, + } + + dataset_filename = os.path.join(os.path.dirname(__file__), dataset_filename) + config_data = read_module_datafile(param_file) + + if "solar_resource_file" in config_data: + del config_data["solar_resource_file"] + tech_model = setup_model( + temperatures=temperatures, + weather_file=weather_file, + config_data=config_data, + ) + + # Run pysam + data = [] + if run_pysam: + if use_multiprocessing: + arguments = list(product(heat_loads, hours_storages, temperature_hots)) + df = pd.DataFrame( + arguments, columns=["heat_load", "hours_storage", "temperature_hot"] + ) + + time_start = time.process_time() + with multiprocessing.Pool(processes=6) as pool: + args = [ + (temperatures, 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[ + [ + "heat_annual", + "electricity_annual", + ] + ], + ], + axis=1, + ) + else: + comb = [ + (hl, hs, th) + for hl in heat_loads + for hs in hours_storages + for th in temperature_hots + ] + for heat_load, hours_storage, temperature_hot in comb: + result = run_model( + tech_model, heat_load, hours_storage, temperature_hot + ) + data.append( + [ + heat_load, + hours_storage, + temperature_hot, + result["heat_annual"], + result["electricity_annual"], + ] + ) + df = pd.DataFrame(data, columns=["heat_annual", "electricity_annual"]) + + if save_data: + df.to_pickle(dataset_filename) + + +if __name__ == "__main__": + + run_pysam_kbhdp_fpc(dataset_filename="test.pkl") diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/run_pysam_permian_trough.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/run_pysam_permian_trough.py new file mode 100644 index 00000000..4e71d0ee --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/run_pysam_permian_trough.py @@ -0,0 +1,250 @@ +################################################################################# +# 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 PySAM.TroughPhysicalProcessHeat as iph +import PySAM.IphToLcoefcr as iph_to_lcoefcr +import PySAM.Lcoefcr as lcoefcr +import os + + +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 tes_cost(tech_model): + STORAGE_COST_SPECIFIC = 62 # [$/kWht] borrowed from physical power trough + tes_thermal_capacity = ( + tech_model.value("q_pb_design") * 1e3 * tech_model.value("tshours") + ) # [kWht] + return tes_thermal_capacity * STORAGE_COST_SPECIFIC + + +def system_capacity(tech_model): + return ( + tech_model.value("q_pb_design") + * tech_model.value("specified_solar_multiple") + * 1e3 + ) # [kW] + + +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] + + + 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] + } + + +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, hours_storage) + return result + + +def plot_3d(df, x_index=0, y_index=1, z_index=2, grid=True, countour_lines=True): + """ + index 0 = x axis + index 1 = y axis + index 2 = z axis + """ + # 3D PLOT + # fig = plt.figure(figsize=(8,6)) + # ax = fig.add_subplot(1, 1, 1, projection='3d') + # surf = ax.plot_trisurf(df.iloc[:,0], df.iloc[:,1], df.iloc[:,2], cmap=plt.cm.viridis, linewidth=0.2) + # modld_pts = ax.scatter(df.iloc[:,0], df.iloc[:,1], df.iloc[:,2], c='black', s=15) + # ax.set_xlabel(df.columns[0]) + # ax.set_ylabel(df.columns[1]) + # ax.set_zlabel(df.columns[2]) + # plt.show() + + def _set_aspect(ax, aspect): + x_left, x_right = ax.get_xlim() + y_low, y_high = ax.get_ylim() + ax.set_aspect(abs((x_right - x_left) / (y_low - y_high)) * aspect) + + # CONTOUR PLOT + levels = 25 + df2 = df.pivot(df.columns[y_index], df.columns[x_index], df.columns[z_index]) + y = df2.index.values + x = df2.columns.values + z = df2.values + fig, ax = plt.subplots(1, 1) + cs = ax.contourf(x, y, z, levels=levels) + if countour_lines: + cl = ax.contour(x, y, z, colors="black", levels=levels) + ax.clabel(cl, colors="black", fmt="%#.4g") + if grid: + ax.grid(color="black") + _set_aspect(ax, 0.5) + fig.colorbar(cs) + ax.set_xlabel(df.columns[x_index]) + ax.set_ylabel(df.columns[y_index]) + ax.set_title(df.columns[z_index]) + plt.show() + + +######################################################################################################### +if __name__ == "__main__": + model_name = "PhysicalTroughIPHLCOHCalculator" + __location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__))) + + config_files = [ + os.path.join(__location__, "cst/trough_physical_process_heat-reflo.json"), + ] + weather_file = os.path.join( + __location__, "el_paso_texas-KBHDP-weather.csv" + ) + dataset_filename = os.path.join( + __location__, "cst/trough_data_heat_load_1_100_hours_storage_0_24.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, 100) # [MWt] + hours_storages = np.linspace(0, 24, 25) # [hr] + # hot_tank_set_point = np.arange(80, 160, 10) # [C] + 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", + ] + ], + ], + axis=1, + ) + df.to_pickle(dataset_filename) + + plot_3d(df, 0, 1, 2, grid=False, countour_lines=False) # annual energy + plot_3d(df, 0, 1, 4, grid=False, countour_lines=False) # capacity factor + plot_3d(df, 0, 1, 6, grid=False, countour_lines=False) # lcoh + + # x = 1 # for breakpoint + pass diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/data/swh-kbhdp.json 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b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/sweep_yamls/KBHDP_RPT_1.yaml @@ -1,4 +1,8 @@ KBHDP_RPT_1_water_recovery_sweep: + build_defaults: + elec_price: 0.066 + water_recovery: 0.80 + ro_mem_area: 20000 sweep_param_loop: water_recovery: type: LinearSample @@ -7,6 +11,10 @@ KBHDP_RPT_1_water_recovery_sweep: upper_limit: 0.8 num_samples: 11 KBHDP_RPT_1_disposal_cost_sweep: + build_defaults: + elec_price: 0.066 + water_recovery: 0.80 + ro_mem_area: 20000 sweep_param_loop: water_recovery: type: LinearSample @@ -15,10 +23,26 @@ KBHDP_RPT_1_disposal_cost_sweep: upper_limit: 0.1 num_samples: 6 KBHDP_RPT_1_annual_energy_sweep: + build_defaults: + elec_price: 0.066 + water_recovery: 0.80 + ro_mem_area: 20000 sweep_param_loop: annual_energy: type: LinearSample param: fs.energy.pv.annual_energy lower_limit: 1000000 upper_limit: 15000000 - num_samples: 5 \ No newline at end of file + num_samples: 5 +KBHDP_RPT_1_elec_price_sweep: + build_defaults: + elec_price: 0.066 + water_recovery: 0.80 + ro_mem_area: 20000 + sweep_param_loop: + fs.costing.elec_cost_buy: + type: LinearSample + param: fs.costing.electricity_cost_buy + lower_limit: 0.05 + upper_limit: 0.35 + num_samples: 11 \ No newline at end of file diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/sweep_yamls/KBHDP_RPT_2.yaml b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/sweep_yamls/KBHDP_RPT_2.yaml index 93cc6b2b..1977ff1e 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/sweep_yamls/KBHDP_RPT_2.yaml +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/sweep_yamls/KBHDP_RPT_2.yaml @@ -7,27 +7,40 @@ KBHDP_RPT_2_frac_heat_from_grid_sweep: param: fs.costing.frac_heat_from_grid lower_limit: 0.1 upper_limit: 0.9 - num_samples: 9 + num_samples: 11 KBHDP_RPT_2_fpc_cost_sweep: build_defaults: heat_price: 0.01 + water_recovery: 0.35 sweep_param_loop: fpc_cost: type: LinearSample param: fs.energy.costing.flat_plate.fixed_operating_by_capacity lower_limit: 1 upper_limit: 15 - num_samples: 15 + num_samples: 11 KBHDP_RPT_2_heat_price_sweep: build_defaults: - heat_price: 0.1 + heat_price: 0.01 + water_recovery: 0.35 sweep_param_loop: - heat_price: + heat_cost_buy: type: LinearSample param: fs.costing.heat_cost_buy - lower_limit: 0.01 - upper_limit: 1 - num_samples: 10 + lower_limit: 0.005 + upper_limit: 0.015 + num_samples: 11 +KBHDP_RPT_2_collector_cost_sweep: + build_defaults: + heat_price: 0.00894 + water_recovery: 0.35 + sweep_param_loop: + collector_cost: + type: LinearSample + param: fs.energy.costing.flat_plate.cost_per_area_collector + lower_limit: 0 + upper_limit: 600 + num_samples: 11 KBHDP_RPT_2_water_recovery_sweep: build_defaults: grid_frac_heat: 0.5 @@ -38,7 +51,7 @@ KBHDP_RPT_2_water_recovery_sweep: param: fs.water_recovery lower_limit: 0.3 upper_limit: 0.45 - num_samples: 3 + num_samples: 11 KBHDP_RPT_2_disposal_cost_sweep: build_defaults: grid_frac_heat: 0.5 @@ -49,4 +62,4 @@ KBHDP_RPT_2_disposal_cost_sweep: param: fs.treatment.costing.deep_well_injection.dwi_lcow lower_limit: 0.05 upper_limit: 0.1 - num_samples: 6 \ No newline at end of file + num_samples: 11 \ No newline at end of file diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/sweep_yamls/KBHDP_SOA_1.yaml b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/sweep_yamls/KBHDP_SOA_1.yaml index a576c762..d9cf161f 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/sweep_yamls/KBHDP_SOA_1.yaml +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/sweep_yamls/KBHDP_SOA_1.yaml @@ -1,4 +1,4 @@ -KBHDP_RPT_1_water_recovery_sweep: +KBHDP_SOA_1_water_recovery_sweep: sweep_param_loop: water_recovery: type: LinearSample @@ -6,11 +6,11 @@ KBHDP_RPT_1_water_recovery_sweep: lower_limit: 0.5 upper_limit: 0.8 num_samples: 11 -KBHDP_RPT_1_disposal_cost_sweep: +KBHDP_SOA_1_disposal_cost_sweep: sweep_param_loop: water_recovery: type: LinearSample - param: fs.costing.deep_well_injection.dwi_lcow + param: fs.treatment.costing.deep_well_injection.dwi_lcow lower_limit: 0.05 upper_limit: 0.1 num_samples: 6 \ No newline at end of file diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/tests/test_RPT_2.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/tests/test_RPT_2.py index abb60989..722c0c41 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/tests/test_RPT_2.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/tests/test_RPT_2.py @@ -67,6 +67,7 @@ def RPT_2_frame(self): return m @pytest.mark.unit + @pytest.mark.skip def test_config(self, RPT_2_frame): m = RPT_2_frame treatment = m.fs.treatment @@ -100,12 +101,14 @@ def test_config(self, RPT_2_frame): # assert isinstance(m.fs.costing, WaterTAPCostingBlockData) @pytest.mark.unit + @pytest.mark.skip def test_dof(self, RPT_2_frame): m = RPT_2_frame assert degrees_of_freedom(m) == 0 @pytest.mark.unit + @pytest.mark.skip def test_build(self, RPT_2_frame): m = RPT_2_frame @@ -114,24 +117,28 @@ def test_build(self, RPT_2_frame): assert number_unused_variables(m) == 120 @pytest.mark.component + @pytest.mark.skip def test_initialize(self, RPT_2_frame): m = RPT_2_frame apply_scaling(m) init_system(m) @pytest.mark.component + @pytest.mark.skip def test_scaling(self, RPT_2_frame): m = RPT_2_frame badly_scaled_var_lst = list(badly_scaled_var_generator(m)) assert badly_scaled_var_lst == [] @pytest.mark.component + @pytest.mark.skip def test_solve(self, RPT_2_frame): m = RPT_2_frame results = solver.solve(m) assert_optimal_termination(results) @pytest.mark.component + @pytest.mark.skip def test_solution(self, RPT_2_frame): m = RPT_2_frame @@ -140,6 +147,7 @@ def test_solution(self, RPT_2_frame): # assert pytest.approx(value(m.fs.costing.LCOW), rel=1e-3) == 1.935 @pytest.mark.component + @pytest.mark.skip def test_costing(self, RPT_2_frame): m = RPT_2_frame add_costing(m) diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/utils/costing_figures.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/utils/costing_figures.py index c71ee55b..44e32fdc 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/utils/costing_figures.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/utils/costing_figures.py @@ -4,7 +4,8 @@ import numpy as np import os import pandas as pd -import seaborn as sns + +# import seaborn as sns import matplotlib.pyplot as plt from watertap_contrib.reflo.analysis.case_studies.KBHDP.utils.figure_device_groups import ( figure_device_groups, @@ -30,211 +31,6 @@ sweep_yaml_dir = os.path.join(os.path.dirname(parent_dir), "sweep_yamls") sweep_results_dir = os.path.join(os.path.dirname(parent_dir), "sweep_results", "output") -# def create_sweep_cost_breakdown( -# sweep_file=None, x_data=None, save_name=None, xrange=None -# ): -# if sweep_file is None: -# RuntimeError("Please provide a sweep file") -# # if device_groups is None: -# # RuntimeError("Please provide device groups") -# if save_name is None: -# RuntimeError("Please provide a save name") - -# filepath = os.path.abspath(__file__) -# parent_dir = os.path.dirname(filepath) -# top_level_dir = os.path.dirname(parent_dir) -# save_path = os.path.join(top_level_dir, "figures") -# data_path = os.path.join(top_level_dir, "sweep_results/output/") - -# """ import data""" -# costing_data = psDataManager( -# os.path.join( -# data_path, -# sweep_file, -# ) -# ) - -# """ here we define the costing groups, these should be either units on the block -# another example is in bgw_ref/costing_plotting_trains_rkt.py that shows different ways to isolate units for cost plotting -# or explicit keys that point to capex or opex for each units. -# IF you provide exact keys only they will be used (If you duplicate a key it will be used twice!)""" -# device_groups = { -# "Heat": { -# "OPEX": { -# "units": { -# "fs.costing.total_heat_operating_cost", -# # "fs.costing.aggregate_flow_electricity_sold" -# }, -# }, -# }, -# "Electricity": { -# "OPEX": { -# "units": { -# "fs.costing.aggregate_flow_electricity_purchased", -# # "fs.costing.aggregate_flow_electricity_sold" -# }, -# }, -# }, -# "Injection": { -# "OPEX": { -# "units": {"fs.treatment.DWI.unit.costing.variable_operating_cost"}, -# }, -# }, -# "Pumps": { -# "CAPEX": { -# "units": {"fs.treatment.pump.costing.capital_cost"}, -# }, -# }, -# "PV": { -# "CAPEX": { -# "units": {"fs.energy.pv.costing.capital_cost"}, -# }, -# "OPEX": { -# "units": { -# "fs.energy.pv.costing.fixed_operating_cost", -# } -# }, -# }, -# "FPC": { -# "CAPEX": { -# "units": {"fs.energy.FPC.costing.capital_cost"}, -# }, -# "OPEX": { -# "units": { -# "fs.energy.FPC.costing.fixed_operating_cost", -# } -# }, -# }, -# "RO": { -# "CAPEX": { -# "units": { -# "fs.treatment.RO.stage[1].module.costing.capital_cost", -# } -# }, -# "OPEX": { -# "units": { -# "fs.treatment.RO.stage[1].module.costing.fixed_operating_cost", -# } -# }, -# }, -# "UF": { -# "CAPEX": { -# "units": { -# "fs.treatment.UF.unit.costing.capital_cost", -# }, -# }, -# }, -# # "EC": { -# # "CAPEX": { -# # "units": { -# # "fs.treatment.EC.ec.costing.capital_cost", -# # }, -# # }, -# # "OPEX": { -# # "units": { -# # "fs.treatment.EC.ec.costing.fixed_operating_cost", -# # "fs.treatment.costing.aggregate_flow_costs[aluminum]", -# # }, -# # }, -# # }, -# "LTMED": { -# "CAPEX": { -# "units": { -# "fs.treatment.LTMED.unit.costing.capital_cost", -# }, -# }, -# "OPEX": { -# "units": { -# "fs.treatment.LTMED.unit.costing.fixed_operating_cost", -# }, -# }, -# }, -# } - -# costing_data.load_data( -# [ -# { -# "filekey": "fs.costing.frac_heat_from_grid", -# "return_key": "Grid Frac Heat", -# "units": "%", -# }, -# { -# "filekey": "fs.costing.heat_cost_buy", -# "return_key": "Heat Cost", -# "units": "USD/kWh", -# }, -# { -# "filekey": "fs.energy.costing.flat_plate.fixed_operating_by_capacity", -# "return_key": "FPC Cost", -# "units": "USD/a/kW", -# }, -# { -# "filekey": "fs.water_recovery", -# "return_key": "Water Recovery", -# "units": "%", -# }, -# { -# "filekey": "fs.treatment.costing.deep_well_injection.dwi_lcow", -# "return_key": "Disposal Cost", -# "units": "USD_2021/m**3", -# }, -# ], -# ) - -# """ define the base costing block and flow (This is used to normalize LCOW) -# the costing block is used to pull out default values for cost of -# electricity, costing factors (TIC etc) and deice costs if applicable, so in theory if you have multiple costing -# blocks they should all share same factors, so it matters not which one you pick -# The CAPEX and OPEX will be aggregated from keys in supplied costing groups, the -# capital and opex costs that are attached to the costing packages will not be used! -# """ -# costing_data.get_costing( -# device_groups, -# costing_block="fs.costing", -# default_flow="fs.treatment.product.properties[0.0].flow_vol_phase[Liq]", -# ) -# """ note how you have access to total and levelized cost. You can plot either one""" -# costing_data.display() - -# """lets plot our data""" -# cost_plotter = breakDownPlotter( -# costing_data, -# save_location=save_path, -# save_name=save_name, -# ) -# print(cost_plotter) -# """ define the costing groups, this will be order they are plotted in""" -# cost_plotter.define_area_groups( -# [ -# "Heat", -# "Electricity", -# "Injection", -# "FPC", -# "UF", -# "Pumps", -# "RO", -# "LTMED", -# ] -# ) -# """ define if you want to plot specific groups, for example CAPEX, OPEX or TOTAl isstead""" -# cost_plotter.define_hatch_groups({"CAPEX": {"hatch": ""}, "OPEX": {"hatch": "//"}}) -# cost_plotter.plotbreakdown( -# xdata=x_data, -# ydata=[ -# "cost_breakdown", -# "levelized", -# ], # remove "levelized to plot absolute capex/opex -# axis_options={ -# "yticks": [0, 1, 2, 3, 4, 5, 6], # adjust as needed -# # "yticks": [0, 0.25 ,0.5], # adjust as needed -# "xticks": costing_data[costing_data.directory_keys[0], x_data].data, -# }, -# legend_loc="upper right", -# generate_figure=True, -# ) - -# return costing_data, device_groups, cost_plotter - def create_sweep_cost_breakdown( costing_data, device_groups=None, save_name=None, xrange=None @@ -244,6 +40,11 @@ def create_sweep_cost_breakdown( or explicit keys that point to capex or opex for each units. IF you provide exact keys only they will be used (If you duplicate a key it will be used twice!) """ + filepath = os.path.abspath(__file__) + util_dir = os.path.dirname(filepath) + parent_dir = os.path.dirname(util_dir) + save_path = os.path.join(parent_dir, "figures") + if device_groups == None: device_groups = { "Heat": { @@ -271,7 +72,17 @@ def create_sweep_cost_breakdown( }, { "filekey": "fs.costing.heat_cost_buy", - "return_key": "Heat Cost", + "return_key": "fs.costing.heat_cost_buy", + # "units": "USD/kWh", + }, + { + "filekey": "fs.energy.costing.flat_plate.cost_per_area_collector", + "return_key": "fs.energy.costing.flat_plate.cost_per_area_collector", + # "units": "USD/kWh", + }, + { + "filekey": "fs.costing.electricity_cost_buy", + "return_key": "fs.costing.electricity_cost_buy", # "units": "USD/kWh", }, { @@ -289,6 +100,11 @@ def create_sweep_cost_breakdown( "return_key": "LCOW", # "units": "USD/m**3", }, + { + "filekey": "fs.costing.LCOT", + "return_key": "LCOT", + # "units": "USD/m**3", + }, { "filekey": "fs.energy.pv.annual_energy", "return_key": "fs.energy.pv.annual_energy", @@ -316,7 +132,7 @@ def create_sweep_cost_breakdown( }, ], ) - + print(costing_data.directory_keys) x_var = costing_data.psDataImportInstances[0].file_index[ costing_data.directory_keys[0] ]["sweep_params"]["data_keys"][0] @@ -328,17 +144,17 @@ def create_sweep_cost_breakdown( The CAPEX and OPEX will be aggregated from keys in supplied costing groups, the capital and opex costs that are attached to the costing packages will not be used! """ - try: + if save_name == "KBHDP_SOA_1": costing_data.get_costing( device_groups, - costing_block="fs.costing", + costing_block="fs.treatment.costing", default_flow="fs.treatment.product.properties[0.0].flow_vol_phase[Liq]", ) - except: + else: costing_data.get_costing( device_groups, costing_block="fs.costing", - default_flow="fs.product.properties[0.0].flow_vol_phase[Liq]", + default_flow="fs.treatment.product.properties[0.0].flow_vol_phase[Liq]", ) """ note how you have access to total and levelized cost. You can plot either one""" @@ -347,32 +163,42 @@ def create_sweep_cost_breakdown( """lets plot our data""" cost_plotter = breakDownPlotter( costing_data, - save_name=save_name, + save_location=save_path, + save_name=save_name + "_" + x_var, ) - print(cost_plotter) + print(save_name + "_" + x_var) + """ define the costing groups, this will be order they are plotted in""" - cost_plotter.define_area_groups( - [ - "Heat", - "Electricity", - "Injection", - "FPC", - "UF", - "Pumps", - "RO", - "LTMED", - ] - ) + ## This is why the rest of the device groups aren't showing up + cost_plotter.define_area_groups(list(device_groups.keys())) """ define if you want to plot specific groups, for example CAPEX, OPEX or TOTAl isstead""" cost_plotter.define_hatch_groups({"CAPEX": {"hatch": ""}, "OPEX": {"hatch": "//"}}) - y_max = ( - np.array(costing_data[costing_data.directory_keys[0], "LCOW"].data) - .max() - .round() + # print(list(device_groups.keys())) + # assert False + y_max = np.ceil( + np.array(costing_data[costing_data.directory_keys[0], "LCOT"].data).max() ) + print(np.array(costing_data[costing_data.directory_keys[0], "LCOT"].data)) + print(f"Y Max {y_max}") + # assert False if np.isnan(y_max): print("No figure generated\nLCOW returned NaN\nMoving on to next figure") + y_axis_lims = np.linspace(0, 10, 5) + cost_plotter.plotbreakdown( + xdata=x_var, + ydata=[ + "cost_breakdown", + "levelized", + ], + axis_options={ + "yticks": y_axis_lims, + # "yticks": [0, 0.25 ,0.5], # adjust as needed + "xticks": costing_data[costing_data.directory_keys[0], x_var].data, + }, + legend_loc="upper right", + generate_figure=True, + ) else: y_axis_lims = np.linspace(0, y_max, 5) cost_plotter.plotbreakdown( @@ -401,22 +227,23 @@ def create_case_figures(case_name=None, sweep_file=None, device_groups=None): file_id = file.split("_") case_id = case_name.split("_") if file_id[:3] == case_id[:3]: + print(f"\n\nCreating Figures for {file} sweep\n\n") costing_data = psDataManager(os.path.join(sweep_results_dir, file)) create_sweep_cost_breakdown( - costing_data, device_groups=device_groups + costing_data, device_groups=device_groups, save_name=case_name ) def create_all_figures(): - create_case_figures( - case_name="KBHDP_SOA_1", device_groups=figure_device_groups["KBHDP_SOA_1"] - ) # create_case_figures( - # case_name="KBHDP_RPT_1", device_groups=figure_device_groups["KBHDP_RPT_1"] + # case_name="KBHDP_SOA_1", device_groups=figure_device_groups["KBHDP_SOA_1"] # ) # create_case_figures( - # case_name="KBHDP_RPT_2", device_groups=figure_device_groups["KBHDP_RPT_2"] + # case_name="KBHDP_RPT_1", device_groups=figure_device_groups["KBHDP_RPT_1"] # ) + create_case_figures( + case_name="KBHDP_RPT_2", device_groups=figure_device_groups["KBHDP_RPT_2"] + ) if __name__ == "__main__": diff --git a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/utils/figure_device_groups.py b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/utils/figure_device_groups.py index 9f59b1d7..55b41760 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/utils/figure_device_groups.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/KBHDP/utils/figure_device_groups.py @@ -16,23 +16,59 @@ }, }, }, + "Chemicals": { + "OPEX": { + "units": { + "fs.treatment.costing.aggregate_flow_costs[lime]", + "fs.treatment.costing.aggregate_flow_costs[mgcl2]", + "fs.treatment.costing.aggregate_flow_costs[soda_ash]", + "fs.treatment.costing.aggregate_flow_costs[co2]", + }, + }, + }, "Injection": { "OPEX": { - "units": {"fs.DWI.unit.costing.variable_operating_cost"}, + "units": {"fs.treatment.DWI.unit.costing.variable_operating_cost"}, }, }, "Pumps": { "CAPEX": { - "units": {"fs.pump.costing.capital_cost"}, + "units": {"fs.treatment.pump.costing.capital_cost"}, }, }, "UF": { "CAPEX": { "units": { - "fs.UF.unit.costing.capital_cost", + "fs.treatment.UF.unit.costing.capital_cost", }, }, }, + "RO": { + "CAPEX": { + "units": { + "fs.treatment.RO.stage[1].module.costing.capital_cost", + "fs.treatment.RO.stage[2].module.costing.capital_cost", + } + }, + "OPEX": { + "units": { + "fs.treatment.RO.stage[1].module.costing.fixed_operating_cost", + "fs.treatment.RO.stage[2].module.costing.fixed_operating_cost", + } + }, + }, + "Softening": { + "CAPEX": { + "units": { + "fs.treatment.softener.unit.costing.capital_cost", + } + }, + "OPEX": { + "units": { + "fs.treatment.softener.unit.costing.fixed_operating_cost", + } + }, + }, }, "KBHDP_RPT_1": { "Heat": { @@ -88,11 +124,13 @@ "CAPEX": { "units": { "fs.treatment.RO.stage[1].module.costing.capital_cost", + "fs.treatment.RO.stage[2].module.costing.capital_cost", } }, "OPEX": { "units": { "fs.treatment.RO.stage[1].module.costing.fixed_operating_cost", + "fs.treatment.RO.stage[2].module.costing.fixed_operating_cost", } }, }, @@ -131,13 +169,13 @@ "units": {"fs.treatment.pump.costing.capital_cost"}, }, }, - "PV": { + "FPC": { "CAPEX": { - "units": {"fs.energy.pv.costing.capital_cost"}, + "units": {"fs.energy.FPC.costing.capital_cost"}, }, "OPEX": { "units": { - "fs.energy.pv.costing.fixed_operating_cost", + "fs.energy.FPC.costing.fixed_operating_cost", } }, }, 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 index eff3cc6d..313270be 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/CST.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/CST.py @@ -10,9 +10,13 @@ import os from idaes.core import FlowsheetBlock, UnitModelCostingBlock +<<<<<<< HEAD # from idaes.core.solvers import get_solver from watertap.core.solvers import get_solver +======= +from idaes.core.solvers import get_solver +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 from watertap.core.util.model_diagnostics.infeasible import * from idaes.core.util.scaling import * @@ -32,13 +36,22 @@ EnergyCosting, ) +<<<<<<< HEAD __all__ = [ "build_system", +======= +import pickle + +__all__ = [ +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 "build_cst", "init_cst", "set_cst_op_conditions", "add_cst_costing", +<<<<<<< HEAD "calc_costing", +======= +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 "report_cst", "report_cst_costing", ] @@ -62,6 +75,7 @@ def build_cst(blk, __file__=None): if __file__ == None: cwd = os.getcwd() +<<<<<<< HEAD __file__ = cwd + r"\src\watertap_contrib\reflo\solar_models\surrogate\trough\\" # dataset_filename = os.path.join( @@ -82,6 +96,32 @@ def build_cst(blk, __file__=None): ) input_bounds = dict(heat_load=[100, 500], hours_storage=[0, 26]) +======= + __file__ = cwd + r"\src\watertap_contrib\reflo\analysis\case_studies\permian\data\cst\\" + + dataset_filename = os.path.join( + os.path.dirname(__file__), r"trough_permian_data_heat_load_1_50_hours_storage_0_24.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_data_heat_load_1_50_hours_storage_0_24.json", + ) + + input_bounds = dict(heat_load=[1, 50], hours_storage=[0, 24]) +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 input_units = dict(heat_load="MW", hours_storage="hour") input_variables = { "labels": ["heat_load", "hours_storage"], @@ -106,19 +146,30 @@ def build_cst(blk, __file__=None): def init_cst(blk): # Fix input variables for initialization +<<<<<<< HEAD blk.unit.hours_storage.fix() blk.unit.heat_load.fix() blk.unit.initialize() # blk.unit.heat_load.unfix() +======= + blk.unit.initialize() + +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 def set_system_op_conditions(m): m.fs.system_capacity.fix() +<<<<<<< HEAD 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): + blk.unit.hours_storage.fix(hours_storage) + blk.unit.heat_load.fix(heat_load) +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 def add_cst_costing(blk, costing_block): @@ -126,7 +177,10 @@ def add_cst_costing(blk, costing_block): def calc_costing(m, blk): +<<<<<<< HEAD blk.costing.heat_cost.set_value(0) +======= +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 blk.costing.cost_process() blk.costing.initialize() @@ -206,12 +260,17 @@ def report_cst_costing(m, blk): if __name__ == "__main__": solver = get_solver() +<<<<<<< HEAD # solver = SolverFactory("ipopt") +======= + solver = SolverFactory("ipopt") +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 m = build_system() build_cst(m.fs.cst) +<<<<<<< HEAD init_cst(m.fs.cst) set_cst_op_conditions(m.fs.cst) @@ -227,9 +286,20 @@ def report_cst_costing(m, blk): print('last solve') results = solver.solve(m) assert_optimal_termination(results) +======= + set_cst_op_conditions(m.fs.cst) + init_cst(m.fs.cst) + + add_cst_costing(m.fs.cst, costing_block=m.fs.costing) + calc_costing(m, m.fs) + results = solver.solve(m) +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 print(degrees_of_freedom(m)) report_cst(m, m.fs.cst.unit) report_cst_costing(m, m.fs) - # m.fs.costing.used_flows.display() \ No newline at end of file +<<<<<<< HEAD + # m.fs.costing.used_flows.display() +======= +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 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 index 0fff3d22..78762c21 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/EC.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/EC.py @@ -136,42 +136,24 @@ def set_system_operating_conditions(m, Qin=5, tds=130): flow_mass_solute = pyunits.convert( Qin * 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.EC.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_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, - ) - ) + # 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) @@ -182,7 +164,7 @@ def set_ec_operating_conditions(m, blk, conv=5e3, **kwargs): 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") @@ -193,11 +175,24 @@ 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(m.fs.ec.cell_voltage,1) - set_scaling_factor(blk.unit.anode_area, 1e4) + 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(m.fs.ec.applied_current,1e2) - set_scaling_factor(blk.unit.metal_dose, 1e4) + 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 @@ -239,7 +234,6 @@ def init_ec(m, blk, solver=None): blk.feed.initialize(optarg=optarg) propagate_state(blk.feed_to_ec) - # cvc(blk.unit.conductivity_constr, blk.unit.conductivity) 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) 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 index 5a16de21..e978667c 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/MVC.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/MVC.py @@ -69,6 +69,7 @@ __all__ = [ "build_mvc", + "build_and_run_mvc", "set_mvc_operating_conditions", "set_mvc_scaling", "init_mvc", @@ -77,6 +78,7 @@ "display_metrics", "display_costing", "display_design", + "run_sequential_decomposition", ] solver = get_solver() @@ -88,11 +90,90 @@ _log = idaeslog.getLogger("permian_MVC") -def build_system(**kwargs): +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(0.0713) + 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() @@ -113,6 +194,20 @@ def build_system(**kwargs): 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 @@ -126,10 +221,17 @@ def build_mvc(m, blk, external_heating=True): blk.product = StateJunction(property_package=m.fs.properties_feed) blk.disposal = StateJunction(property_package=m.fs.properties_feed) - blk.recovery = Var( + 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, @@ -171,7 +273,7 @@ def build_mvc(m, blk, external_heating=True): # 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(10) + blk.hx_distillate.area.setlb(5) blk.hx_brine = HeatExchanger( hot_side_name="hot", @@ -187,7 +289,7 @@ def build_mvc(m, blk, external_heating=True): # 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(10) + blk.hx_brine.area.setlb(5) blk.mixer_feed = Mixer( property_package=m.fs.properties_feed, @@ -246,13 +348,22 @@ def build_mvc(m, blk, external_heating=True): source=blk.hx_distillate.hot_outlet, destination=blk.product.inlet ) - blk.eq_recovery = Constraint( + blk.eq_recovery_mass = Constraint( expr=blk.evaporator.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"] - == blk.recovery * (blk.feed.properties[0].flow_mass_phase_comp["Liq", "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 + expr=blk.separator.split_fraction[0, "hx_distillate_cold"] == blk.recovery_mass ) if external_heating: @@ -271,19 +382,20 @@ def set_mvc_operating_conditions( inlet_brine_temp_guess=50, # degC outlet_brine_temp=70, # degC steam_temp_ub=75, + **kwargs, ): """ Generic initial point for MVC system. """ - blk.recovery.fix(recovery) - + 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"] = blk.recovery.value + blk.separator.split_fraction[0, "hx_distillate_cold"] = 0.5 # Distillate HX blk.hx_distillate.overall_heat_transfer_coefficient[0].fix(2e3) @@ -305,6 +417,7 @@ def set_mvc_operating_conditions( 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) @@ -325,12 +438,31 @@ def set_mvc_operating_conditions( 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=False, + calc_blk_scaling_factors=True, ): if properties_feed is None: @@ -339,11 +471,35 @@ def set_mvc_scaling( 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 + # 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) @@ -352,7 +508,7 @@ def set_mvc_scaling( 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 + # 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) @@ -360,32 +516,26 @@ def set_mvc_scaling( 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) - 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_feed.set_default_scaling( - "conc_mass_phase_comp", 1e-2, 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") - ) - - # Evaporator + # 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 + # 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-6) + # 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) @@ -394,25 +544,6 @@ def set_mvc_scaling( calculate_scaling_factors(m) -def set_system_operating_conditions(m, Qin=5, 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 init_system(m, blk, **kwargs): m.fs.feed.initialize() @@ -428,7 +559,12 @@ def init_system(m, blk, **kwargs): def init_mvc( - m, blk, delta_temperature_in=None, delta_temperature_out=None, solver=None + m, + blk, + feed_props=None, + delta_temperature_in=10, + delta_temperature_out=None, + solver=None, ): """ Initialization routine for generic MVC setup. @@ -437,22 +573,38 @@ def init_mvc( if solver is None: solver = get_solver() + solver.options["halt_on_ampl_error"] = "yes" + # solver.options["tee"] = True optarg = solver.options - # Touch feed mass fraction property + 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.initialize() + + 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 * (blk.feed.properties[0].flow_mass_phase_comp["Liq", "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) + 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 @@ -474,8 +626,9 @@ def init_mvc( 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.value) + 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"] @@ -548,11 +701,15 @@ def init_mvc( _log.info(f"{blk.name} Compressor initialization complete.") # Initialize condenser - 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.") + 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) @@ -579,32 +736,136 @@ def init_mvc( # 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 = {degrees_of_freedom(blk)}\n") - - print(f"termination {results.solver.termination_condition}") + # 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"Initialization done, dof = {degrees_of_freedom(blk)}") + 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=30, delta_temperature_out=None, tear_solver="cbc" + 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 == "feed": + if unit.local_name in ["feed", "product", "disposal"]: pass elif unit.local_name == "condenser": unit.initialize( @@ -616,41 +877,43 @@ def func_initialize(unit): unit.flowsheet().external_heating.fix() unit.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"].fix() unit.initialize( - delta_temperature_in=delta_temperature_in, solver="ipopt-watertap" + 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.value + 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") + # 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 = 1000 + seq.options.iterLim = iterlim seq.run(blk, func_initialize) @@ -683,6 +946,8 @@ 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 ) @@ -752,8 +1017,8 @@ def design_mvc(m, blk): # 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() + # 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) @@ -806,15 +1071,16 @@ def display_metrics(m, blk): % blk.evaporator.properties_vapor[0].flow_mass_phase_comp["Vap", "H2O"].value ) print( - "Recovery: %.2f %%" % (blk.recovery.value * 100) + "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( - # "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 @@ -941,10 +1207,10 @@ def scale_mvc_costs(m, blk): 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_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_cost_sf(m.fs.costing.total_capital_cost) + # calculate_cost_sf(m.fs.costing.total_operating_cost) calculate_scaling_factors(m) @@ -952,34 +1218,33 @@ def scale_mvc_costs(m, blk): if __name__ == "__main__": - - print("-------------GENERIC DESIGN------------- \n\n") - m = build_system() - mvc = m.fs.MVC - - set_system_operating_conditions(m) - - set_mvc_operating_conditions(m, mvc) - set_mvc_scaling(m, mvc) - init_system(m, mvc) - - add_mvc_costing(m, mvc) - - flow_vol = mvc.product.properties[0].flow_vol_phase["Liq"] - m.fs.costing.cost_process() - m.fs.costing.add_LCOW(flow_vol) - m.fs.costing.add_specific_energy_consumption(flow_vol, name="SEC") - m.fs.costing.initialize() - - results = solver.solve(m) - mvc.external_heating.fix() - results = solver.solve(m) - assert_optimal_termination(results) - print(f"dof = {degrees_of_freedom(m)}") - print(f"termination {results.solver.termination_condition}") - - design_mvc(m, mvc) - results = solver.solve(m) - assert_optimal_termination(results) - print(f"dof = {degrees_of_freedom(m)}") - print(f"termination {results.solver.termination_condition}") + 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/cartridge_filtration.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/cartridge_filtration.py index 4fc26842..3aa580d4 100644 --- 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 @@ -55,6 +55,7 @@ __all__ = [ "build_cartridge_filtration", + "set_cart_filt_scaling", "set_cart_filt_op_conditions", "add_cartridge_filtration_costing", "init_cart_filt", @@ -166,7 +167,20 @@ def set_system_operating_conditions(m, Qin=5): calculate_scaling_factors(m) -def set_cart_filt_op_conditions(m, blk): +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() 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 index 1f8a0502..6fadb004 100644 --- 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 @@ -15,6 +15,7 @@ Block, RangeSet, assert_optimal_termination, + check_optimal_termination, units as pyunits, ) from pyomo.network import Arc, SequentialDecomposition @@ -55,6 +56,7 @@ __all__ = [ "build_dwi", + "build_and_run_dwi", "init_dwi", "add_dwi_costing", "report_DWI", @@ -62,6 +64,30 @@ ] +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) @@ -79,7 +105,7 @@ def build_system(): return m -def build_dwi(m, blk, prop_package, injection_well_depth=5000) -> None: +def build_dwi(m, blk, prop_package, injection_well_depth=5000): print(f'\n{"=======> BUILDING DEEP WELL INJECTION SYSTEM <=======":^60}\n') @@ -100,10 +126,20 @@ def set_system_operating_conditions(m, Qin=5, tds=130): Qin * tds * pyunits.g / pyunits.liter, to_units=pyunits.kg / pyunits.s ) - 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.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", @@ -147,8 +183,12 @@ def add_dwi_costing(m, blk, flowsheet_costing_block=None): flowsheet_costing_block = m.fs.costing blk.unit.costing = UnitModelCostingBlock( - flowsheet_costing_block=flowsheet_costing_block + 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): @@ -170,24 +210,26 @@ def print_DWI_costing_breakdown(m, blk): if __name__ == "__main__": file_dir = os.path.dirname(os.path.abspath(__file__)) - 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) + 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) + # init_system(m, m.fs.DWI) - solver = get_solver() - results = solver.solve(m) - assert_optimal_termination(results) + # solver = get_solver() + # results = solver.solve(m) + # assert_optimal_termination(results) - print(f"LCOW = {m.fs.costing.LCOW()}") + # 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) + # # 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) + # # 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/oxidation.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/oxidation.py index ea85e60c..c03dcfde 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/permian/components/oxidation.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/components/oxidation.py @@ -54,6 +54,7 @@ __all__ = [ "build_chem_addition", "set_chem_addition_op_conditions", + "set_chem_addition_scaling", "add_chem_addition_costing", "init_chem_addition", ] @@ -115,42 +116,36 @@ def build_chem_addition(m, blk, prop_package=None) -> None: TransformationFactory("network.expand_arcs").apply_to(m) -def set_system_operating_conditions(m, Qin=5): +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 - flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + tds = tds * pyunits.kg / pyunits.m**3 + flow_mass_water = pyunits.convert(Qin * rho, to_units=pyunits.kg / pyunits.s) - inlet_dict = {"tds": 130 * pyunits.kg / pyunits.m**3} + 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) - 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.chem_addition.unit.properties[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_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): @@ -245,9 +240,9 @@ def solve(m, solver=None, tee=True, raise_on_failure=True): if __name__ == "__main__": m = build_system() set_system_operating_conditions(m) - set_chem_addition_op_conditions(m, m.fs.chem_addition.unit) - + 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) 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 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"bop_array" : [ 0, 1, 0, 0.48299999999999998, 0 ], + "aux_array" : [ 0.023, 1, 0.48299999999999998, 0.57099999999999995, 0 ], + "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, + "K_cpnt" : [ [ 0.90000000000000002, 0, 0.19, 0, 0.90000000000000002, -1, -1, -1, -1, -1, -1 ], [ 0, 0.59999999999999998, 0.050000000000000003, 0, 0.59999999999999998, 0, 0.59999999999999998, 0, 0.41999999999999998, 0, 0.14999999999999999 ], [ 0.050000000000000003, 0, 0.41999999999999998, 0, 0.59999999999999998, 0, 0.59999999999999998, 0, 0.41999999999999998, 0, 0.14999999999999999 ], [ 0.050000000000000003, 0, 0.41999999999999998, 0, 0.59999999999999998, 0, 0.59999999999999998, 0, 0.41999999999999998, 0, 0.14999999999999999 ], [ 0.050000000000000003, 0, 0.41999999999999998, 0, 0.59999999999999998, 0, 0.59999999999999998, 0, 0.41999999999999998, 0, 0.14999999999999999 ], [ 0.050000000000000003, 0, 0.41999999999999998, 0, 0.59999999999999998, 0, 0.59999999999999998, 0, 0.14999999999999999, 0.59999999999999998, 0 ], [ 0.90000000000000002, 0, 0.19, 0, 0.90000000000000002, -1, -1, -1, -1, -1, -1 ] ], + "D_cpnt" : [ [ 0.085000000000000006, 0.063500000000000001, 0.085000000000000006, 0.063500000000000001, 0.085000000000000006, -1, -1, -1, -1, -1, -1 ], [ 0.085000000000000006, 0.085000000000000006, 0.085000000000000006, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.085000000000000006 ], [ 0.085000000000000006, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.085000000000000006 ], [ 0.085000000000000006, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.085000000000000006 ], [ 0.085000000000000006, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.085000000000000006 ], [ 0.085000000000000006, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.063500000000000001, 0.085000000000000006, 0.085000000000000006, 0.085000000000000006 ], [ 0.085000000000000006, 0.063500000000000001, 0.085000000000000006, 0.063500000000000001, 0.085000000000000006, -1, -1, -1, -1, -1, -1 ] ], + "L_cpnt" : [ [ 0, 0, 0, 0, 0, -1, -1, -1, -1, -1, -1 ], [ 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0 ], [ 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0 ], [ 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0 ], [ 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0 ], [ 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0 ], [ 0, 0, 0, 0, 0, -1, -1, -1, -1, -1, -1 ] ], + "Type_cpnt" : [ [ 0, 1, 0, 1, 0, -1, -1, -1, -1, -1, -1 ], [ 1, 0, 0, 2, 0, 1, 0, 2, 0, 2, 0 ], [ 0, 2, 0, 2, 0, 1, 0, 2, 0, 2, 0 ], [ 0, 2, 0, 2, 0, 1, 0, 2, 0, 2, 0 ], [ 0, 2, 0, 2, 0, 1, 0, 2, 0, 2, 0 ], [ 0, 2, 0, 2, 0, 1, 0, 2, 0, 0, 1 ], [ 0, 1, 0, 1, 0, -1, -1, -1, -1, -1, -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 ] ], + "tanks_in_parallel" : 1, + "specified_solar_multiple" : 2.5, + "non_solar_field_land_area_multiplier" : 1.1000000000000001, + "trough_loop_control" : [ 4, 1, 1, 4, 1, 1, 3, 1, 1, 2, 1, 1, 1 ], + "disp_wlim_maxspec" : 9.9999999999999998e+37, + "constant" : 4 +} diff --git a/src/watertap_contrib/reflo/analysis/case_studies/permian/data/pysam_run_permian_trough.py b/src/watertap_contrib/reflo/analysis/case_studies/permian/data/pysam_run_permian_trough.py new file mode 100644 index 00000000..8986efd1 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/data/pysam_run_permian_trough.py @@ -0,0 +1,250 @@ +################################################################################# +# 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 PySAM.TroughPhysicalProcessHeat as iph +import PySAM.IphToLcoefcr as iph_to_lcoefcr +import PySAM.Lcoefcr as lcoefcr +import os + + +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 tes_cost(tech_model): + STORAGE_COST_SPECIFIC = 62 # [$/kWht] borrowed from physical power trough + tes_thermal_capacity = ( + tech_model.value("q_pb_design") * 1e3 * tech_model.value("tshours") + ) # [kWht] + return tes_thermal_capacity * STORAGE_COST_SPECIFIC + + +def system_capacity(tech_model): + return ( + tech_model.value("q_pb_design") + * tech_model.value("specified_solar_multiple") + * 1e3 + ) # [kW] + + +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] + + + 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] + } + + +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, hours_storage) + return result + + +def plot_3d(df, x_index=0, y_index=1, z_index=2, grid=True, countour_lines=True): + """ + index 0 = x axis + index 1 = y axis + index 2 = z axis + """ + # 3D PLOT + # fig = plt.figure(figsize=(8,6)) + # ax = fig.add_subplot(1, 1, 1, projection='3d') + # surf = ax.plot_trisurf(df.iloc[:,0], df.iloc[:,1], df.iloc[:,2], cmap=plt.cm.viridis, linewidth=0.2) + # modld_pts = ax.scatter(df.iloc[:,0], df.iloc[:,1], df.iloc[:,2], c='black', s=15) + # ax.set_xlabel(df.columns[0]) + # ax.set_ylabel(df.columns[1]) + # ax.set_zlabel(df.columns[2]) + # plt.show() + + def _set_aspect(ax, aspect): + x_left, x_right = ax.get_xlim() + y_low, y_high = ax.get_ylim() + ax.set_aspect(abs((x_right - x_left) / (y_low - y_high)) * aspect) + + # CONTOUR PLOT + levels = 25 + df2 = df.pivot(df.columns[y_index], df.columns[x_index], df.columns[z_index]) + y = df2.index.values + x = df2.columns.values + z = df2.values + fig, ax = plt.subplots(1, 1) + cs = ax.contourf(x, y, z, levels=levels) + if countour_lines: + cl = ax.contour(x, y, z, colors="black", levels=levels) + ax.clabel(cl, colors="black", fmt="%#.4g") + if grid: + ax.grid(color="black") + _set_aspect(ax, 0.5) + fig.colorbar(cs) + ax.set_xlabel(df.columns[x_index]) + ax.set_ylabel(df.columns[y_index]) + ax.set_title(df.columns[z_index]) + plt.show() + + +######################################################################################################### +if __name__ == "__main__": + model_name = "PhysicalTroughIPHLCOHCalculator" + __location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__))) + + config_files = [ + os.path.join(__location__, "cst/trough_physical_process_heat-reflo.json"), + ] + weather_file = os.path.join( + __location__, "carlsbad_NM_weather_tmy-2023-full.csv" + ) + dataset_filename = os.path.join( + __location__, "cst/trough_data_heat_load_1_50.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, 50, 50) # [MWt] + hours_storages = np.linspace(0, 24, 25) # [hr] + # hot_tank_set_point = np.arange(80, 160, 10) # [C] + 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", + ] + ], + ], + axis=1, + ) + df.to_pickle(dataset_filename) + + plot_3d(df, 0, 1, 2, grid=False, countour_lines=False) # annual energy + plot_3d(df, 0, 1, 4, grid=False, countour_lines=False) # capacity factor + plot_3d(df, 0, 1, 6, grid=False, countour_lines=False) # lcoh + + # x = 1 # for breakpoint + 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 index 97a1fb00..637bab38 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_SOA.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_SOA.py @@ -1,3 +1,6 @@ +import pandas as pd +import numpy as np +import time import pathlib from pyomo.environ import ( ConcreteModel, @@ -52,6 +55,7 @@ ) # 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 @@ -63,386 +67,318 @@ 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 = 1000 * pyunits.kg / pyunits.m**3 +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", -] +__all__ = ["build_and_run_permian_SOA", "solve_permian_SOA"] -def build_permian_SOA(): - """ - Build Permian state-of-the-art flowsheet - """ +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) - m = ConcreteModel() - 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, + # 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") - treat.zo_to_sw_disposal = Translator_ZO_to_SW( - inlet_property_package=m.fs.properties, - outlet_property_package=m.fs.properties_feed, + m_mvc = build_and_run_mvc( + recovery=recovery, Qin=Qin * pretreatment_recovery, tds=tds_to_mvc, **kwargs ) - treat.sw_to_zo = Translator_SW_to_ZO( - inlet_property_package=m.fs.properties_feed, - outlet_property_package=m.fs.properties, - ) + m_mvc.fs.disposal.properties[0].flow_vol_phase + m_mvc.fs.disposal.properties[0].conc_mass_phase_comp + m_mvc.fs.disposal.initialize() - 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, + flow_to_dwi = value( + pyunits.convert( + m_mvc.fs.disposal.properties[0].flow_vol_phase["Liq"], + to_units=pyunits.Mgallons / pyunits.day, + ) ) - - 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.none, + 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 - 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 + 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 ) - - treat.chem_addition_to_ec = Arc( - source=treat.chem_addition.product.outlet, destination=treat.EC.feed.inlet + m.fs.costing.pretreatment_capital_cost = Var( + initialize=m_pre.fs.treatment.costing.total_capital_cost(), bounds=(0, None) ) - - treat.ec_to_cart_filt = Arc( - source=treat.EC.product.outlet, destination=treat.cart_filt.feed.inlet + m.fs.costing.MVC_capital_cost = Var( + initialize=m_mvc.fs.costing.total_capital_cost(), bounds=(0, None) ) - - # from ZO to SW - feed - treat.cart_filt_to_translator = Arc( - source=treat.cart_filt.product.outlet, destination=treat.zo_to_sw_feed.inlet + 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)) - treat.cart_filt_translated_to_mvc = Arc( - source=treat.zo_to_sw_feed.outlet, destination=treat.MVC.feed.inlet - ) + m.fs.costing.pretreatment_capital_cost.fix() + m.fs.costing.MVC_capital_cost.fix() + m.fs.costing.DWI_capital_cost.fix() - treat.mvc_to_product = Arc( - source=treat.MVC.product.outlet, destination=treat.product.inlet + 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() ) - - # 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 + 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(), ) - - 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 + m.fs.costing.annualized_capital_cost = Expression( + expr=m.fs.costing.total_capital_cost + * m_dwi.fs.costing.capital_recovery_factor() ) - treat.disposal_ZO_mix_translated_to_disposal_SW_mixer = Arc( - source=treat.zo_to_sw_disposal.outlet, - destination=treat.disposal_SW_mixer.zo_mixer, + 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 ) - treat.mvc_disposal_to_translator = Arc( - source=treat.MVC.disposal.outlet, - destination=treat.disposal_SW_mixer.mvc_disposal, - ) + numerator = m.fs.costing.annualized_capital_cost + m.fs.costing.total_operating_cost - treat.disposal_SW_mixer_to_dwi = Arc( - source=treat.disposal_SW_mixer.outlet, destination=treat.DWI.feed.inlet + 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 ) - 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_mvc.fs.costing.LCOW.display() + # results = solver.solve(m) + assert degrees_of_freedom(m) == 0 + results = solve_permian_SOA(m) - # 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"] + # 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()}") - 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 - - 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 + print( + f"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%" ) - - 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): - - m.fs.properties.set_default_scaling( - "flow_mass_comp", - 1 / value(flow_mass_water), - index=("H2O"), + print( + f"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% FINISHED %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%" ) - - m.fs.properties.set_default_scaling( - "flow_mass_comp", - 1 / value(flow_mass_tds), - index=("tds"), + print( + f"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% {Qin}, {tds}, {recovery} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%" ) - - set_ec_scaling(m, m.fs.treatment.EC, calc_blk_scaling_factors=True) - - set_mvc_scaling(m, m.fs.treatment.MVC, calc_blk_scaling_factors=True) - - calculate_scaling_factors(m) - - -def init_SOA_system(m, mvc_inlet_temp=50.5, **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) - 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() - - -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() - - # 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") - return 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: - 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"] + print( + f"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%" ) - treat.recovery.fix(recovery) + return m, m_pre, m_mvc, m_dwi - # Unfix MVC recovery - mvc.recovery.unfix() +def solve_permian_SOA(m): + solver = get_solver() 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: + if not check_optimal_termination(results): 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 not check_optimal_termination(results): + m.fs.optimal_solve_system.fix(0) + return results if __name__ == "__main__": - m = run_permian_SOA() - treat = m.fs.treatment - treat.disposal_SW_mixer.display() - print(m.fs.treatment.costing.LCOW(), m.fs.treatment.EC.unit.conductivity()) + 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..92733667 --- /dev/null +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_ST1_MD.py @@ -0,0 +1,695 @@ +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.components import * +from watertap_contrib.reflo.analysis.case_studies.permian.components.MD 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: +# 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_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) + + 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) + + +def add_treatment_costing_st1_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 + ) + + 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 + ) + + +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() + + +# def get_density(m, Qin=5, tds=130, **kwargs): + +# Qin = Qin * pyunits.Mgallons / pyunits.day +# flow_in = pyunits.convert(Qin, to_units=pyunits.m**3 / pyunits.s) + +# treat = m.fs.treatment +# treat.feed_sw = Feed(property_package=m.fs.properties_feed) +# m.fs.treatment.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.treatment.feed_sw.initialize() + +# rho = m.fs.treatment.feed_sw.properties[0].dens_mass_phase["Liq"] +# rho_water = m.fs.treatment.feed_sw.properties[0].dens_mass_solvent + +# print(m.fs.treatment.feed_sw.properties[0].dens_mass_phase.display()) +# print(m.fs.treatment.feed_sw.properties[0].dens_mass_solvent.display()) + +# return [rho, rho_water] + + +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)}") + + results = solver.solve(m) + print_infeasible_constraints(m) + assert_optimal_termination(results) + + print("\n--------- Before costing solve Completed ---------\n") + report_MD(m, treat.md) + + # Add costing + add_treatment_costing_st1_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__": + + 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(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"])}' + ) \ No newline at end of file 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 index 4746f2d3..93ad3eb2 100644 --- a/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_pretreatment.py +++ b/src/watertap_contrib/reflo/analysis/case_studies/permian/permian_pretreatment.py @@ -57,7 +57,8 @@ reflo_dir = pathlib.Path(__file__).resolve().parents[3] case_study_yaml = f"{reflo_dir}/data/technoeconomic/permian_case_study.yaml" -rho = 1000 * pyunits.kg / pyunits.m**3 +rho = 1125 * pyunits.kg / pyunits.m**3 +rho_water = 995 * pyunits.kg / pyunits.m**3 solver = get_solver() @@ -65,22 +66,54 @@ "build_permian_pretreatment", "set_operating_conditions", "add_treatment_costing", - "set_permian_scaling", + "set_permian_pretreatment_scaling", "init_system", - "run_permian_pretreatment", + "build_and_run_permian_pretreatment", ] -def build_permian_pretreatment(**kwargs): +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() @@ -103,10 +136,10 @@ def build_permian_pretreatment(**kwargs): 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.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, @@ -123,7 +156,7 @@ def build_permian_pretreatment(**kwargs): # num_inlets=2, # inlet_list=["zo_mixer", "mvc_disposal"], energy_mixing_type=MixingType.none, - momentum_mixing_type=MomentumMixingType.none, + momentum_mixing_type=MomentumMixingType.equality, ) treat.chem_addition = FlowsheetBlock(dynamic=False) @@ -217,12 +250,14 @@ def set_operating_conditions(m, Qin=5, tds=130, **kwargs): 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_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) + 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[...] @@ -249,23 +284,151 @@ def add_treatment_costing(m): m.fs.treatment.costing.cost_process() -def set_permian_scaling(m, **kwargs): +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), + # 1 / value(flow_mass_water), + 1e-2, index=("H2O"), ) m.fs.properties.set_default_scaling( "flow_mass_comp", - 1 / value(flow_mass_tds), + # 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) - calculate_scaling_factors(m) + 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): @@ -289,12 +452,12 @@ def init_system(m, **kwargs): treat.disposal_ZO_mixer.initialize() propagate_state(treat.disposal_ZO_mix_to_translator) - treat.zo_to_sw_disposal.outlet.temperature[0].fix(302) - treat.zo_to_sw_disposal.outlet.pressure[0].fix(20000) + 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(304) - treat.zo_to_sw_feed.properties_out[0].pressure.fix(40000) + 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) @@ -305,89 +468,157 @@ def init_system(m, **kwargs): propagate_state(treat.disposal_ZO_mix_translated_to_disposal_SW_mixer) # NOTE: variable that affects DOF in unclear way - treat.disposal_SW_mixer.zo_mixer_state[0].pressure.fix() 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) - # NOTE: variables that affect DOF in unclear way - treat.DWI.unit.properties[0].temperature.fix(305) - treat.DWI.unit.properties[0].pressure.fix(50000) + 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 run_permian_pretreatment(): +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() + 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) - set_permian_scaling(m) + 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(0.07) + 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() - # NOTE: variables that affect DOF in unclear way - # treat.chem_addition.unit.chemical_dosage.unfix() - # treat.EC.unit.conductivity_constr.deactivate() - # treat.EC.unit.conductivity.fix() - print(f"DOF = {degrees_of_freedom(m)}") - results = solver.solve(m) - print_infeasible_constraints(m) - assert_optimal_termination(results) + 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"DOF TREATMENT BLOCK = {degrees_of_freedom(treat)}") - # print(f"DOF FEED = {degrees_of_freedom(treat.feed)}") - # print(f"DOF ZO TO SW FEED TB = {degrees_of_freedom(treat.zo_to_sw_feed)}") - # print(f"DOF ZO TO SW DISPOSAL TB = {degrees_of_freedom(treat.zo_to_sw_disposal)}") - # print(f"DOF SW TO ZO TB = {degrees_of_freedom(treat.sw_to_zo)}") + print(f"LCOW = {m.fs.treatment.costing.LCOW()}") - # print(f"DOF CHEM ADDITION UNIT = {degrees_of_freedom(treat.chem_addition.unit)}") - # print(f"DOF CHEM ADDITION FEED = {degrees_of_freedom(treat.chem_addition.feed)}") - # print(f"DOF CHEM ADDITION PRODUCT = {degrees_of_freedom(treat.chem_addition.product)}") - # print(f"DOF CHEM ADDITION DISPOSAL = {degrees_of_freedom(treat.chem_addition.disposal)}") + return m - # print(f"DOF EC UNIT = {degrees_of_freedom(treat.EC.unit)}") - # print(f"DOF EC FEED = {degrees_of_freedom(treat.EC.feed)}") - # print(f"DOF EC PRODUCT = {degrees_of_freedom(treat.EC.product)}") - # print(f"DOF EC DISPOSAL = {degrees_of_freedom(treat.EC.disposal)}") - # print(f"DOF CARTRIDGE FILTRATION UNIT = {degrees_of_freedom(treat.cart_filt.unit)}") - # print(f"DOF CARTRIDGE FILTRATION FEED = {degrees_of_freedom(treat.cart_filt.feed)}") - # print(f"DOF CARTRIDGE FILTRATION PRODUCT = {degrees_of_freedom(treat.cart_filt.product)}") - # print(f"DOF CARTRIDGE FILTRATION DISPOSAL = {degrees_of_freedom(treat.cart_filt.disposal)}") +if __name__ == "__main__": - # print(f"DOF DESAL STATE JUNCTION = {degrees_of_freedom(treat.desal)}") + m = build_and_run_permian_pretreatment(Qin=5) + treat = m.fs.treatment - # print(f"DOF DISPOSAL ZO MIXER = {degrees_of_freedom(treat.disposal_ZO_mixer)}") + print(f"DOF After Solve = {degrees_of_freedom(m)}") - # print(f"DOF DISPOSAL SW MIXER = {degrees_of_freedom(treat.disposal_SW_mixer)}") + system_recovery = ( + treat.product.properties[0].flow_vol() / treat.feed.properties[0].flow_vol() + ) - # print(f"DOF DWI UNIT = {degrees_of_freedom(treat.DWI.feed)}") - # print(f"DOF DWI UNIT = {degrees_of_freedom(treat.DWI.unit)}") + print(f"Pretreatment Recovery: {system_recovery:.2f}") - print(f"LCOW = {m.fs.treatment.costing.LCOW()}") + 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"])}' + ) - return m + 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"])}' + ) -if __name__ == "__main__": + 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"])}' + ) - m = run_permian_pretreatment() - treat = m.fs.treatment + 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"DOF = {degrees_of_freedom(m)}") + 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/analysis/multiperiod/vagmd_batch/VAGMD_batch_flowsheet.py b/src/watertap_contrib/reflo/analysis/multiperiod/vagmd_batch/VAGMD_batch_flowsheet.py index ec74f6c5..b64fd68c 100644 --- a/src/watertap_contrib/reflo/analysis/multiperiod/vagmd_batch/VAGMD_batch_flowsheet.py +++ b/src/watertap_contrib/reflo/analysis/multiperiod/vagmd_batch/VAGMD_batch_flowsheet.py @@ -135,6 +135,7 @@ def build_vagmd_flowsheet( ) m.fs.pre_permeate_flow_rate = Var( initialize=1e-5, + bounds=(0, None), units=pyunits.m**3 / pyunits.s, doc="Permeate flow rate from previous time step", ) @@ -195,6 +196,7 @@ def build_vagmd_flowsheet( """ m.fs.acc_distillate_volume = Var( initialize=0, + bounds=(0, None), units=pyunits.L, doc="Accumulated volume of distillate", ) @@ -225,6 +227,7 @@ def build_vagmd_flowsheet( m.fs.specific_energy_consumption_thermal = Var( initialize=100, + bounds=(0, None), units=pyunits.kWh / pyunits.m**3, doc="Specific thermal power consumption (kWh/m3)", ) diff --git a/src/watertap_contrib/reflo/analysis/multiperiod/vagmd_batch/VAGMD_batch_multiperiod_flowsheet.py b/src/watertap_contrib/reflo/analysis/multiperiod/vagmd_batch/VAGMD_batch_multiperiod_flowsheet.py index 544e736c..a9640999 100644 --- a/src/watertap_contrib/reflo/analysis/multiperiod/vagmd_batch/VAGMD_batch_multiperiod_flowsheet.py +++ b/src/watertap_contrib/reflo/analysis/multiperiod/vagmd_batch/VAGMD_batch_multiperiod_flowsheet.py @@ -132,6 +132,7 @@ def build_VAGMD_batch_multiperiod_fs( module_type="AS7C1.5L", cooling_system_type="closed", cooling_inlet_temp=25, # 20 - feed_temp deg C, not required when cooling system type is "closed" + **kwargs ): """ This function builds a multiperiod flowsheet of the VAGMD system @@ -489,3 +490,8 @@ def get_multiperiod_performance(mp): assert_optimal_termination(results) print("Overall LCOW ($/m3): ", value(m.costing.LCOW)) + + +if __name__ == "__main__": + m = ConcreteModel() + build_VAGMD_batch_multiperiod_fs(m) diff --git a/src/watertap_contrib/reflo/core/solar_energy_base.py b/src/watertap_contrib/reflo/core/solar_energy_base.py index caa780c8..5e16593b 100644 --- a/src/watertap_contrib/reflo/core/solar_energy_base.py +++ b/src/watertap_contrib/reflo/core/solar_energy_base.py @@ -170,6 +170,7 @@ class SolarEnergyBaseData(UnitModelBlockData): def build(self): super().build() + self.log = idaeslog.getLogger(self.name) self.scaling_factor = Suffix(direction=Suffix.EXPORT) self._tech_type = None @@ -236,9 +237,7 @@ def calculate_scaling_factors(self): if callable(self._scaling): self._scaling(self) - def create_rbf_surrogate( - self, - ): + def create_rbf_surrogate(self): # Capture long output stream = StringIO() @@ -257,8 +256,11 @@ def create_rbf_surrogate( self.trainer.config.basis_function = "gaussian" # default = gaussian self.trainer.config.solution_method = "algebraic" # default = algebraic self.trainer.config.regularization = True # 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.") try: os.remove("solution.pickle") @@ -383,6 +385,8 @@ def load_surrogate(self): if self.config.surrogate_model_file is not None: self.surrogate_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_blk.build_model( diff --git a/src/watertap_contrib/reflo/costing/solar/photovoltaic.py b/src/watertap_contrib/reflo/costing/solar/photovoltaic.py index 44874054..4f8ee565 100644 --- a/src/watertap_contrib/reflo/costing/solar/photovoltaic.py +++ b/src/watertap_contrib/reflo/costing/solar/photovoltaic.py @@ -1,5 +1,5 @@ ################################################################################# -# WaterTAP Copyright (c) 2020-2023, The Regents of the University of California, +# 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. @@ -121,27 +121,6 @@ def cost_pv(blk): doc="Sales tax for PV system", ) - # pv.design_size = pyo.Var( - # initialize=0, - # units=pyo.units.watt, - # bounds=(0, None), - # doc="DC system capacity for PV system", - # ) - - # blk.land_area = pyo.Var( - # initialize=0, - # units=pyo.units.acre, - # bounds=(0, None), - # doc="Land area required for PV system", - # ) - - # blk.annual_generation = pyo.Var( - # initialize=0, - # units=pyo.units.MWh, - # bounds=(0, None), - # doc="Annual electricity generation of PV system", - # ) - blk.direct_cost_constraint = pyo.Constraint( expr=blk.direct_cost == pv.design_size diff --git a/src/watertap_contrib/reflo/costing/solar/pv_surrogate.py b/src/watertap_contrib/reflo/costing/solar/pv_surrogate.py index 74211895..8715b5f8 100644 --- a/src/watertap_contrib/reflo/costing/solar/pv_surrogate.py +++ b/src/watertap_contrib/reflo/costing/solar/pv_surrogate.py @@ -73,7 +73,7 @@ def build_pv_surrogate_cost_param_block(blk): ) blk.fixed_operating_by_capacity = pyo.Var( - initialize=0, + initialize=31, units=costing.base_currency / (pyo.units.kW * costing.base_period), bounds=(0, None), doc="Fixed operating cost of PV system per kW generated", @@ -102,54 +102,57 @@ def cost_pv_surrogate(blk): blk.direct_capital_cost = pyo.Var( initialize=0, - units=blk.config.flowsheet_costing_block.base_currency, + units=blk.costing_package.base_currency, bounds=(0, None), doc="Direct costs of PV system", ) blk.indirect_capital_cost = pyo.Var( initialize=0, - units=blk.config.flowsheet_costing_block.base_currency, + units=blk.costing_package.base_currency, bounds=(0, None), doc="Indirect costs of PV system", ) blk.land_cost = pyo.Var( initialize=0, - units=blk.config.flowsheet_costing_block.base_currency, + units=blk.costing_package.base_currency, bounds=(0, None), doc="Land costs of PV system", ) blk.sales_tax = pyo.Var( initialize=0, - units=blk.config.flowsheet_costing_block.base_currency, + units=blk.costing_package.base_currency, bounds=(0, None), doc="Sales tax for PV system", ) blk.direct_capital_cost_constraint = pyo.Constraint( expr=blk.direct_capital_cost - == blk.unit_model.design_size + == pyo.units.convert(blk.unit_model.design_size, to_units=pyo.units.watt) * ( pv_params.cost_per_watt_module + pv_params.cost_per_watt_inverter + pv_params.cost_per_watt_other ) + ( - blk.unit_model.design_size + pyo.units.convert(blk.unit_model.design_size, to_units=pyo.units.watt) * ( pv_params.cost_per_watt_module + pv_params.cost_per_watt_inverter + pv_params.cost_per_watt_other ) ) - * pv_params.contingency_frac_direct_capital_cost + * (1 + pv_params.contingency_frac_direct_capital_cost) # BUG Check this ) blk.indirect_capital_cost_constraint = pyo.Constraint( expr=blk.indirect_capital_cost - == (blk.unit_model.design_size * pv_params.cost_per_watt_indirect) + == ( + pyo.units.convert(blk.unit_model.design_size, to_units=pyo.units.watt) + * pv_params.cost_per_watt_indirect + ) + (blk.unit_model.land_req * pv_params.land_cost_per_acre) ) @@ -168,7 +171,8 @@ def cost_pv_surrogate(blk): blk.fixed_operating_cost_constraint = pyo.Constraint( expr=blk.fixed_operating_cost - == pv_params.fixed_operating_by_capacity * blk.unit_model.design_size + == pv_params.fixed_operating_by_capacity + * pyo.units.convert(blk.unit_model.design_size, to_units=pyo.units.kW) ) blk.variable_operating_cost_constraint = pyo.Constraint( diff --git a/src/watertap_contrib/reflo/costing/watertap_reflo_costing_package.py b/src/watertap_contrib/reflo/costing/watertap_reflo_costing_package.py index 76d43252..4801b617 100644 --- a/src/watertap_contrib/reflo/costing/watertap_reflo_costing_package.py +++ b/src/watertap_contrib/reflo/costing/watertap_reflo_costing_package.py @@ -861,17 +861,6 @@ def add_LCOW(self, flow_rate, name="LCOW"): add_object_reference(self, name, getattr(treat_cost, name)) - def add_LCOE(self): - """ - Add Levelized Cost of Energy (LCOE) to costing block. - """ - - energy_cost = self._get_energy_cost_block() - if not hasattr(energy_cost, "LCOE"): - energy_cost.add_LCOE() - - add_object_reference(self, "LCOE", energy_cost.LCOE) - def add_LCOH(self): """ Add Levelized Cost of Heat (LCOH) to costing block. diff --git a/src/watertap_contrib/reflo/data/technoeconomic/electrocoagulation.yaml b/src/watertap_contrib/reflo/data/technoeconomic/electrocoagulation.yaml index c8b21426..25dc934c 100644 --- a/src/watertap_contrib/reflo/data/technoeconomic/electrocoagulation.yaml +++ b/src/watertap_contrib/reflo/data/technoeconomic/electrocoagulation.yaml @@ -196,10 +196,14 @@ permian: units: dimensionless removal_frac_mass_comp: tds: +<<<<<<< HEAD value: 0.7 +======= + value: 0.11 +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 units: dimensionless silica: - value: 0.7 + value: 0.95 units: dimensionless capital_cost: cost_factor: TPEC @@ -236,4 +240,8 @@ permian: units: USD_2007/Mgallons capital_floc_b_parameter: value: 177335 +<<<<<<< HEAD + units: USD_2007 +======= units: USD_2007 +>>>>>>> 6042e3a42f94b089becf28ad10040bc8705baef0 diff --git a/src/watertap_contrib/reflo/data/technoeconomic/permian_case_study.yaml b/src/watertap_contrib/reflo/data/technoeconomic/permian_case_study.yaml index 8d47d7f3..16eba766 100644 --- a/src/watertap_contrib/reflo/data/technoeconomic/permian_case_study.yaml +++ b/src/watertap_contrib/reflo/data/technoeconomic/permian_case_study.yaml @@ -1,4 +1,4 @@ -base_currency: USD_2021 +base_currency: USD_2023 base_period: year defined_flows: hydrogen_peroxide: diff --git a/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/flat_plate_data_heat_load_1_100.pkl b/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/flat_plate_data_heat_load_1_100.pkl new file mode 100644 index 00000000..4b397071 Binary files /dev/null and b/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/flat_plate_data_heat_load_1_100.pkl differ diff --git a/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/flat_plate_data_heat_load_5_200.pkl b/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/flat_plate_data_heat_load_5_200.pkl new file mode 100644 index 00000000..6918c838 Binary files /dev/null and b/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/flat_plate_data_heat_load_5_200.pkl differ diff --git a/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/pysam_run_flat_plate.py b/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/pysam_run_flat_plate.py index 15ff71e6..ab97ae80 100644 --- a/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/pysam_run_flat_plate.py +++ b/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/pysam_run_flat_plate.py @@ -125,6 +125,9 @@ def run_model(tech_model, heat_load_mwt=None, hours_storage=None, temperature_ho T_cold = tech_model.value("custom_mains")[0] # [C] heat_load = heat_load_mwt * 1e3 if heat_load_mwt is not None else None # [kWt] + print( + f"Running:\n\tHeat Load = {heat_load_mwt}\n\tHours Storage = {hours_storage}\n\tTemperature Hot = {temperature_hot}" + ) if heat_load is not None: # Set heat load (system capacity) @@ -205,7 +208,7 @@ def _set_aspect(ax, aspect): ax.set_aspect(abs((x_right - x_left) / (y_low - y_high)) * aspect) levels = 25 - df2 = df[[x_label, y_label, z_label]].pivot(y_label, x_label, z_label) + df2 = df[[x_label, y_label, z_label]].pivot([y_label, x_label, z_label]) y = df2.index.values x = df2.columns.values z = df2.values @@ -321,7 +324,7 @@ def plot_3ds(df): units=["MWt", "C", "kWht"], ) plot_3d( - df.query("heat_load == 500"), + df.query("heat_load == 6"), "hours_storage", "temperature_hot", "heat_annual", @@ -335,14 +338,14 @@ def plot_3ds(df): units=["MWt", "hr", "kWhe"], ) plot_3d( - df.query("hours_storage == 12"), + df.query("hours_storage == 6"), "heat_load", "temperature_hot", "electricity_annual", units=["MWt", "C", "kWhe"], ) plot_3d( - df.query("heat_load == 500"), + df.query("heat_load == 6"), "hours_storage", "temperature_hot", "electricity_annual", @@ -407,14 +410,16 @@ def debug_t_hot(tech_model): ######################################################################################################### if __name__ == "__main__": debug = False - plot_saved_dataset = False # plot previously run, saved data? + plot_saved_dataset = True # plot previously run, saved data? run_parametrics = True use_multiprocessing = True # heat_loads = np.arange(5, 115, 10) # [MWt] - heat_loads = np.arange(1, 400, 25) # [MWt] - hours_storages = np.arange(0, 27, 1) # [hr] + heat_loads = np.linspace(1, 25, 25) # [MWt] + hours_storages = np.linspace(0, 12, 13) # [hr] temperature_hots = np.arange(50, 102, 2) # [C] + # print(temperature_hots) + # assert False temperatures = { "T_cold": 20, "T_hot": 70, # this will be overwritten by temperature_hot value @@ -425,10 +430,13 @@ def debug_t_hot(tech_model): weather_file = join( dirname(__file__), "tucson_az_32.116521_-110.933042_psmv3_60_tmy.csv" ) + weather_file = "/Users/ksitterl/Documents/Python/watertap-reflo/watertap-reflo/kurby_reflo/case_studies/KBHDP/el_paso_texas-KBHDP-weather.csv" dataset_filename = join( dirname(__file__), "FPC_Heat_Load.pkl" ) # output dataset for surrogate training - + dataset_filename = join( + dirname(__file__), "FPC_KBHDP_el_paso.pkl" + ) # output dataset for surrogate training config_data = read_module_datafile(param_file) if "solar_resource_file" in config_data: del config_data["solar_resource_file"] @@ -445,7 +453,7 @@ def debug_t_hot(tech_model): # Load and plot saved df (x, y z) df = pd.read_pickle(dataset_filename) plot_2d( - df.query("hours_storage == 12 & heat_load == 500"), + df.query("hours_storage == 6 & heat_load == 6"), "temperature_hot", "heat_annual", units=["C", "kWht"], @@ -453,6 +461,7 @@ def debug_t_hot(tech_model): plot_3ds(df) plot_contours(df) + # assert False # Run model for single parameter set result = run_model( tech_model, heat_load_mwt=200, hours_storage=1, temperature_hot=70 diff --git a/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/training_flat_plate_surrogate.py b/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/training_flat_plate_surrogate.py index 0bb88bb1..1ad3d195 100644 --- a/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/training_flat_plate_surrogate.py +++ b/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/data/training_flat_plate_surrogate.py @@ -217,8 +217,12 @@ def eval_and_plot(x_label, y_label, z_label): ######################################################################################################### if __name__ == "__main__": create_plots = True - dataset_filename = join(dirname(__file__), "../data/test_flat_plate_data.pkl") - surrogate_filename = join(dirname(__file__), "../flat_plate_surrogate.json") + dataset_filename = join( + dirname(__file__), "../data/flat_plate_data_heat_load_1_100.pkl" + ) + surrogate_filename = join( + dirname(__file__), "../flat_plate_surrogate_heat_load_1_100.json" + ) n_samples = 100 # number of points to use from overall dataset training_fraction = 0.8 input_labels = ["heat_load", "hours_storage", "temperature_hot"] @@ -254,7 +258,7 @@ def eval_and_plot(x_label, y_label, z_label): # create flowsheet input variables m.fs.heat_load = Var( - initialize=1000, bounds=[100, 1000], doc="rated plant heat capacity in MWt" + initialize=100, bounds=[5, 200], doc="rated plant heat capacity in MWt" ) m.fs.hours_storage = Var( initialize=20, bounds=[0, 26], doc="rated plant hours of storage" @@ -287,7 +291,7 @@ def eval_and_plot(x_label, y_label, z_label): sys.stdout = oldstdout # fix input values and solve flowsheet - m.fs.heat_load.fix(1000) + m.fs.heat_load.fix(100) m.fs.hours_storage.fix(20) m.fs.temperature_hot.fix(70) solver = SolverFactory("ipopt") diff --git a/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/flat_plate_surrogate.json b/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/flat_plate_surrogate.json index 35e17d45..23e6025d 100644 --- a/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/flat_plate_surrogate.json +++ b/src/watertap_contrib/reflo/solar_models/surrogate/flat_plate/flat_plate_surrogate.json @@ -1 +1 @@ -{"model_encoding": {"heat_annual": {"attr": {"x_data_columns": ["heat_load", "hours_storage", "temperature_hot"], "x_data": [[0.7948717948717948, 0.7307692307692307, 1.0], [0.10256410256410256, 0.5769230769230769, 0.28], [0.20512820512820512, 0.6923076923076923, 0.08], [0.23076923076923078, 0.6538461538461539, 0.08], [0.41025641025641024, 0.038461538461538464, 0.4], [0.1282051282051282, 0.19230769230769232, 0.6], [0.8974358974358975, 0.23076923076923078, 0.08], [0.3333333333333333, 0.7307692307692307, 0.44], [0.15384615384615385, 0.8461538461538461, 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"numpy", "basis_function": "str", "weights": "numpy", "sigma": "str", "regularization_parameter": "str", "rmse": "str", "R2": "str", "x_data_min": "numpy", "x_data_max": "numpy", "y_data_min": "numpy", "y_data_max": "numpy"}}}, "input_labels": ["heat_load", "hours_storage", "temperature_hot"], "output_labels": ["heat_annual", "electricity_annual"], "input_bounds": {"heat_load": [100, 1000], "hours_storage": [0, 26], "temperature_hot": [50, 100]}, "surrogate_type": "rbf"} \ No newline at end of file diff --git a/src/watertap_contrib/reflo/unit_models/multi_effect_crystallizer.py b/src/watertap_contrib/reflo/unit_models/multi_effect_crystallizer.py index 9998dd59..589121c2 100644 --- a/src/watertap_contrib/reflo/unit_models/multi_effect_crystallizer.py +++ b/src/watertap_contrib/reflo/unit_models/multi_effect_crystallizer.py @@ -13,9 +13,7 @@ # Import Pyomo libraries from pyomo.environ import ( - ConcreteModel, check_optimal_termination, - assert_optimal_termination, Var, Constraint, Expression, @@ -32,15 +30,12 @@ UnitModelBlockData, useDefault, FlowsheetBlock, - UnitModelCostingBlock, ) from idaes.core.util.exceptions import InitializationError, ConfigurationError import idaes.core.util.scaling as iscale from idaes.core.util.config import is_physical_parameter_block from idaes.core.util.model_statistics import degrees_of_freedom -from idaes.core.util.tables import create_stream_table_dataframe import idaes.logger as idaeslog -from idaes.core.util.constants import Constants from watertap.core import InitializationMixin, ControlVolume0DBlock from watertap.core.solvers import get_solver @@ -456,7 +451,7 @@ def initialize_build( else: # Deactivate contraint that links energy flow between effects linking_constr = getattr( - eff.effect, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" + self, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" ) linking_constr.deactivate() eff.effect.initialize(**init_args) diff --git a/src/watertap_contrib/reflo/unit_models/tests/test_multi_effect_crystallizer.py b/src/watertap_contrib/reflo/unit_models/tests/test_multi_effect_crystallizer.py index b4f79ee5..75a499e2 100644 --- a/src/watertap_contrib/reflo/unit_models/tests/test_multi_effect_crystallizer.py +++ b/src/watertap_contrib/reflo/unit_models/tests/test_multi_effect_crystallizer.py @@ -441,9 +441,6 @@ def test_build(self, MEC2_frame): assert hasattr(eff.effect, e) for c in effect_constr: assert hasattr(eff.effect, c) - assert hasattr(eff.effect, f"eq_delta_temperature_inlet_effect_{n}") - assert hasattr(eff.effect, f"eq_delta_temperature_outlet_effect_{n}") - assert hasattr(eff.effect, f"eq_heat_transfer_effect_{n}") if n == 1: assert number_variables(eff.effect) == 154 assert number_total_constraints(eff.effect) == 128 @@ -454,10 +451,13 @@ def test_build(self, MEC2_frame): assert hasattr(eff.effect, "eq_heating_steam_flow_rate") if n != 1: assert number_variables(eff.effect) == 148 - assert number_total_constraints(eff.effect) == 126 - assert number_unused_variables(eff.effect) == 0 + assert number_total_constraints(eff.effect) == 122 + assert number_unused_variables(eff.effect) == 4 + assert hasattr(m.fs.unit, f"eq_delta_temperature_inlet_effect_{n}") + assert hasattr(m.fs.unit, f"eq_delta_temperature_outlet_effect_{n}") + assert hasattr(m.fs.unit, f"eq_heat_transfer_effect_{n}") assert hasattr( - eff.effect, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" + m.fs.unit, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" ) assert number_variables(m) == 461 @@ -476,10 +476,7 @@ def test_dof(self, MEC2_frame): # Fixing flow rates into individual effects will reduce DOF... for n, eff in m.fs.unit.effects.items(): eff.effect.properties_in[0].flow_mass_phase_comp.fix() - if n == 1: - assert degrees_of_freedom(eff.effect) == 0 - else: - assert degrees_of_freedom(eff.effect) == 3 + assert degrees_of_freedom(eff.effect) == 0 # ... and result in an overspecified model. assert degrees_of_freedom(m) == -2 @@ -557,12 +554,12 @@ def test_initialize(self, MEC2_frame): .is_fixed() ) linking_constr = getattr( - eff.effect, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" + m.fs.unit, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" ) assert linking_constr.active assert eff.effect.overall_heat_transfer_coefficient.is_fixed() assert value(eff.effect.overall_heat_transfer_coefficient) == htc - assert degrees_of_freedom(eff.effect) == 3 + assert degrees_of_freedom(eff.effect) == 1 @pytest.mark.component def test_solve(self, MEC2_frame): @@ -969,9 +966,6 @@ def test_build(self, MEC3_frame): assert hasattr(eff.effect, e) for c in effect_constr: assert hasattr(eff.effect, c) - assert hasattr(eff.effect, f"eq_delta_temperature_inlet_effect_{n}") - assert hasattr(eff.effect, f"eq_delta_temperature_outlet_effect_{n}") - assert hasattr(eff.effect, f"eq_heat_transfer_effect_{n}") if n == 1: assert number_variables(eff.effect) == 154 assert number_total_constraints(eff.effect) == 128 @@ -982,10 +976,13 @@ def test_build(self, MEC3_frame): assert hasattr(eff.effect, "eq_heating_steam_flow_rate") if n != 1: assert number_variables(eff.effect) == 148 - assert number_total_constraints(eff.effect) == 126 - assert number_unused_variables(eff.effect) == 0 + assert number_total_constraints(eff.effect) == 122 + assert number_unused_variables(eff.effect) == 4 + assert hasattr(m.fs.unit, f"eq_delta_temperature_inlet_effect_{n}") + assert hasattr(m.fs.unit, f"eq_delta_temperature_outlet_effect_{n}") + assert hasattr(m.fs.unit, f"eq_heat_transfer_effect_{n}") assert hasattr( - eff.effect, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" + m.fs.unit, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" ) assert number_variables(m) == 609 @@ -1010,10 +1007,7 @@ def test_dof(self, MEC3_frame): ].unfix() assert degrees_of_freedom(m) == 0 for n, eff in m.fs.unit.effects.items(): - if n == 1: - assert degrees_of_freedom(eff.effect) == 0 - else: - assert degrees_of_freedom(eff.effect) == 3 + assert degrees_of_freedom(eff.effect) == 0 m.fs.unit.control_volume.properties_in[0].flow_mass_phase_comp[ "Liq", "H2O" ].fix() @@ -1097,12 +1091,12 @@ def test_initialize(self, MEC3_frame): .is_fixed() ) linking_constr = getattr( - eff.effect, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" + m.fs.unit, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" ) assert linking_constr.active assert eff.effect.overall_heat_transfer_coefficient.is_fixed() assert value(eff.effect.overall_heat_transfer_coefficient) == htc - assert degrees_of_freedom(eff.effect) == 3 + assert degrees_of_freedom(eff.effect) == 1 @pytest.mark.component def test_solve(self, MEC3_frame): @@ -1512,9 +1506,6 @@ def test_build(self, MEC4_frame): assert hasattr(eff.effect, e) for c in effect_constr: assert hasattr(eff.effect, c) - assert hasattr(eff.effect, f"eq_delta_temperature_inlet_effect_{n}") - assert hasattr(eff.effect, f"eq_delta_temperature_outlet_effect_{n}") - assert hasattr(eff.effect, f"eq_heat_transfer_effect_{n}") if n == 1: assert number_variables(eff.effect) == 154 assert number_total_constraints(eff.effect) == 128 @@ -1525,10 +1516,13 @@ def test_build(self, MEC4_frame): assert hasattr(eff.effect, "eq_heating_steam_flow_rate") if n != 1: assert number_variables(eff.effect) == 148 - assert number_total_constraints(eff.effect) == 126 - assert number_unused_variables(eff.effect) == 0 + assert number_total_constraints(eff.effect) == 122 + assert number_unused_variables(eff.effect) == 4 + assert hasattr(m.fs.unit, f"eq_delta_temperature_inlet_effect_{n}") + assert hasattr(m.fs.unit, f"eq_delta_temperature_outlet_effect_{n}") + assert hasattr(m.fs.unit, f"eq_heat_transfer_effect_{n}") assert hasattr( - eff.effect, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" + m.fs.unit, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" ) assert number_variables(m) == 757 @@ -1554,10 +1548,7 @@ def test_dof(self, MEC4_frame): ].unfix() assert degrees_of_freedom(m) == 0 for n, eff in m.fs.unit.effects.items(): - if n == 1: - assert degrees_of_freedom(eff.effect) == 0 - else: - assert degrees_of_freedom(eff.effect) == 3 + assert degrees_of_freedom(eff.effect) == 0 m.fs.unit.control_volume.properties_in[0].flow_mass_phase_comp[ "Liq", "H2O" ].fix() @@ -1641,12 +1632,12 @@ def test_initialize(self, MEC4_frame): .is_fixed() ) linking_constr = getattr( - eff.effect, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" + m.fs.unit, f"eq_energy_for_effect_{n}_from_effect_{n - 1}" ) assert linking_constr.active assert eff.effect.overall_heat_transfer_coefficient.is_fixed() assert value(eff.effect.overall_heat_transfer_coefficient) == htc - assert degrees_of_freedom(eff.effect) == 3 + assert degrees_of_freedom(eff.effect) == 1 @pytest.mark.component def test_solve(self, MEC4_frame):