###############################################################################
# WaterTAP Copyright (c) 2021, 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/"
#
###############################################################################
'''
mutable parameters for optimization:
m.fs.system_recovery_target
m.fs.max_allowable_pressure
'''
from pyomo.environ import ConcreteModel, TransformationFactory
from idaes.core import FlowsheetBlock
from idaes.core.util.scaling import calculate_scaling_factors
from watertap.examples.flowsheets.full_treatment_train.util import (solve_with_user_scaling,
check_dof)
import watertap.examples.flowsheets.full_treatment_train.analysis.flowsheet_softening as flowsheet_softening
import watertap.examples.flowsheets.full_treatment_train.analysis.flowsheet_two_stage as flowsheet_two_stage
[docs]def build(m, **kwargs):
"""
Build a flowsheet with softening pretreatment and RO.
"""
assert kwargs['RO_base'] == 'TDS'
assert not kwargs['has_desal_feed']
flowsheet_softening.build_components(m)
flowsheet_two_stage.build_components(m, pretrt_type='softening', **kwargs)
return m
def scale(m, **kwargs):
flowsheet_softening.scale(m)
flowsheet_two_stage.scale(m, **kwargs)
def initialize(m, **kwargs):
flowsheet_softening.initialize(m)
flowsheet_two_stage.initialize(m, **kwargs)
def report(m, **kwargs):
flowsheet_softening.report(m)
flowsheet_two_stage.report(m, **kwargs)
def set_optimization_components(m, system_recovery, **kwargs):
# unfix variables
m.fs.stoich_softening_mixer_unit.lime_stream.flow_mol[0].unfix()
m.fs.stoich_softening_mixer_unit.lime_stream.flow_mol.setlb(1e-6 / 74.09e-3)
m.fs.stoich_softening_mixer_unit.lime_stream.flow_mol.setub(1 / 74.09e-3)
m.fs.stoich_softening_separator_unit.hardness.setlb(10)
m.fs.stoich_softening_separator_unit.hardness.setub(10000)
flowsheet_two_stage.set_optimization_components(m, system_recovery, **kwargs)
def set_up_optimization(m, system_recovery=0.50, **kwargs):
set_optimization_components(m, system_recovery, **kwargs)
calculate_scaling_factors(m)
check_dof(m, 7)
def optimize(m):
solve_with_user_scaling(m, tee=False, fail_flag=True, bound_push=1e-5, mu_init=1e-3)
def solve_flowsheet(**desal_kwargs):
if desal_kwargs == {}:
desal_kwargs = flowsheet_two_stage.desal_kwargs
m = ConcreteModel()
m.fs = FlowsheetBlock(default={"dynamic": False})
build(m, **desal_kwargs)
TransformationFactory("network.expand_arcs").apply_to(m)
# scale
scale(m, **desal_kwargs)
calculate_scaling_factors(m)
# initialize
initialize(m, **desal_kwargs)
check_dof(m)
solve_with_user_scaling(m, tee=False, fail_flag=True, bound_push=1e-5, mu_init=1e-3)
# report
print('==================================='
'\n Simulation ')
report(m, **desal_kwargs)
return m
def optimize_flowsheet(system_recovery=0.50, **kwargs):
m = solve_flowsheet(**kwargs)
set_up_optimization(m, system_recovery=system_recovery, **kwargs)
optimize(m)
print('==================================='
'\n Optimization ')
report(m, **flowsheet_two_stage.desal_kwargs)
return m
if __name__ == "__main__":
import sys
if len(sys.argv) == 1:
m = solve_flowsheet()
else:
desal_kwargs = flowsheet_two_stage.desal_kwargs
m = optimize_flowsheet(system_recovery=float(sys.argv[1]), **desal_kwargs)