#################################################################################
# WaterTAP Copyright (c) 2020-2024, The Regents of the University of California,
# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory,
# National Renewable Energy Laboratory, and National Energy Technology
# Laboratory (subject to receipt of any required approvals from the U.S. Dept.
# of Energy). All rights reserved.
#
# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license
# information, respectively. These files are also available online at the URL
# "https://github.com/watertap-org/watertap/"
#################################################################################
import pyomo.environ as pyo
from idaes.core.util.exceptions import ConfigurationError
from idaes.core.util.misc import StrEnum
from idaes.core.util.math import smooth_min
from ..util import (
register_costing_parameter_block,
make_capital_cost_var,
make_fixed_operating_cost_var,
)
[docs]def cost_gac(blk, contactor_type=ContactorType.pressure):
"""
3 equation capital cost estimation for GAC systems with: (i), contactor/pressure vessel cost by polynomial as a
function of individual contactor volume; (ii), initial charge of GAC adsorbent cost by exponential as a function of
required mass of GAC adsorbent; and (iii), other process costs (vessels, pipes, instrumentation, and controls)
calculated by power law as a function of total contactor(s) volume. Operating costs calculated as the required
makeup and regeneration of GAC adsorbent. Energy consumption is estimated from that required for booster, backwash,
and residual pumps as a function of total contactor(s) volume.
Args:
contactor_type: ContactorType Enum indicating whether to cost based on steel pressure vessels or concrete,
default = ContactorType.pressure
"""
# costing data parameters based on contactor type
if contactor_type == ContactorType.pressure:
cost_gac_pressure(blk)
elif contactor_type == ContactorType.gravity:
cost_gac_gravity(blk)
else:
raise ConfigurationError(
f"{blk.unit_model.name} received invalid argument for contactor_type:"
f" {contactor_type}. Argument must be a member of the ContactorType Enum."
)
def build_gac_cost_param_block_pressure(blk):
_build_gac_cost_param_block(blk, ContactorType.pressure)
def build_gac_cost_param_block_gravity(blk):
_build_gac_cost_param_block(blk, ContactorType.gravity)
[docs]@register_costing_parameter_block(
build_rule=build_gac_cost_param_block_pressure,
parameter_block_name="gac_pressure",
)
def cost_gac_pressure(blk):
"""
3 equation capital cost estimation for GAC systems with: (i), contactor/pressure vessel cost by polynomial as a
function of individual contactor volume; (ii), initial charge of GAC adsorbent cost by exponential as a function of
required mass of GAC adsorbent; and (iii), other process costs (vessels, pipes, instrumentation, and controls)
calculated by power law as a function of total contactor(s) volume. Operating costs calculated as the required
makeup and regeneration of GAC adsorbent. Energy consumption is estimated from that required for booster, backwash,
and residual pumps as a function of total contactor(s) volume.
This function costs assuming steel pressure-fed vessels.
"""
parameter_blk = blk.costing_package.gac_pressure
_cost_gac(blk, parameter_blk)
[docs]@register_costing_parameter_block(
build_rule=build_gac_cost_param_block_gravity,
parameter_block_name="gac_gravity",
)
def cost_gac_gravity(blk):
"""
3 equation capital cost estimation for GAC systems with: (i), contactor/pressure vessel cost by polynomial as a
function of individual contactor volume; (ii), initial charge of GAC adsorbent cost by exponential as a function of
required mass of GAC adsorbent; and (iii), other process costs (vessels, pipes, instrumentation, and controls)
calculated by power law as a function of total contactor(s) volume. Operating costs calculated as the required
makeup and regeneration of GAC adsorbent. Energy consumption is estimated from that required for booster, backwash,
and residual pumps as a function of total contactor(s) volume.
This function costs assuming concrete gravity-fed basins.
"""
parameter_blk = blk.costing_package.gac_gravity
_cost_gac(blk, parameter_blk)
def _build_gac_cost_param_block(blk, contactor_type):
adsorbent_unit_cost_coeff_data = {0: 4.58342, 1: -1.25311e-5}
if contactor_type == ContactorType.pressure:
contactor_cost_coeff_data = {0: 10010.9, 1: 2204.95, 2: -15.9378, 3: 0.110592}
other_cost_param_data = {0: 16660.7, 1: 0.552207}
energy_consumption_coeff_data = {0: 8.09926e-4, 1: 8.70577e-4, 2: 0}
elif contactor_type == ContactorType.gravity:
contactor_cost_coeff_data = {0: 75131.3, 1: 735.550, 2: -1.01827, 3: 0.000000}
other_cost_param_data = {0: 38846.9, 1: 0.490571}
energy_consumption_coeff_data = {0: 0.123782, 1: 0.132403, 2: -1.41512e-5}
# ---------------------------------------------------------------------
# design options
blk.num_contactors_op = pyo.Var(
initialize=1,
units=pyo.units.dimensionless,
doc="number of GAC contactors in operation in parallel",
)
blk.num_contactors_redundant = pyo.Var(
initialize=1,
units=pyo.units.dimensionless,
doc="number of off-line redundant GAC contactors in parallel",
)
blk.regen_frac = pyo.Var(
initialize=0.70,
units=pyo.units.dimensionless,
doc="fraction of spent GAC adsorbent that can be regenerated for reuse",
)
# ---------------------------------------------------------------------
# correlation reference points
blk.bed_mass_max_ref = pyo.Var(
initialize=18143.7,
units=pyo.units.kg,
doc="reference maximum value of GAC mass needed for initial charge where "
"economy of scale no longer discounts the unit price",
)
# ---------------------------------------------------------------------
# correlation parameter data
# USD_2020 embedded in equation
blk.contactor_cost_coeff = pyo.Var(
contactor_cost_coeff_data,
initialize=contactor_cost_coeff_data,
units=pyo.units.dimensionless,
doc="contactor polynomial cost coefficients",
)
# USD_2020 * kg**-1 embedded in equation adsorbent_unit_cost_constraint
blk.adsorbent_unit_cost_coeff = pyo.Var(
adsorbent_unit_cost_coeff_data,
initialize=adsorbent_unit_cost_coeff_data,
units=pyo.units.dimensionless,
doc="GAC adsorbent cost exponential function parameters",
)
# USD_2020 embedded in equation other_process_cost_constraint
blk.other_cost_param = pyo.Var(
other_cost_param_data,
initialize=other_cost_param_data,
units=pyo.units.dimensionless,
doc="other process cost power law parameters",
)
blk.regen_unit_cost = pyo.Var(
initialize=4.28352,
units=pyo.units.USD_2020 * pyo.units.kg**-1,
doc="unit cost to regenerate spent GAC adsorbent by an offsite regeneration facility",
)
blk.makeup_unit_cost = pyo.Var(
initialize=4.58223,
units=pyo.units.USD_2020 * pyo.units.kg**-1,
doc="unit cost to makeup spent GAC adsorbent with fresh adsorbent",
)
# kW embedded in equation energy_consumption_constraint
blk.energy_consumption_coeff = pyo.Var(
energy_consumption_coeff_data,
initialize=energy_consumption_coeff_data,
units=pyo.units.dimensionless,
doc="energy consumption polynomial coefficients",
)
def _cost_gac(blk, parameter_blk):
"""
3 equation capital cost estimation for GAC systems with: (i), contactor/pressure vessel cost by polynomial as a
function of individual contactor volume; (ii), initial charge of GAC adsorbent cost by exponential as a function of
required mass of GAC adsorbent; and (iii), other process costs (vessels, pipes, instrumentation, and controls)
calculated by power law as a function of total contactor(s) volume. Operating costs calculated as the required
makeup and regeneration of GAC adsorbent. Energy consumption is estimated from that required for booster, backwash,
and residual pumps as a function of total contactor(s) volume.
Args:
parameter_blk: the block containing the global-level parameters utilized to cost GAC
"""
# ---------------------------------------------------------------------
make_capital_cost_var(blk)
blk.contactor_cost = pyo.Var(
initialize=1e5,
domain=pyo.NonNegativeReals,
units=blk.costing_package.base_currency,
doc="Unit contactor(s) capital cost",
)
blk.bed_mass_gac_ref = pyo.Var(
initialize=4,
domain=pyo.NonNegativeReals,
units=pyo.units.kg,
doc="Reference value of GAC mass needed for initial charge where "
"economy of scale no longer discounts the unit price",
)
blk.adsorbent_unit_cost = pyo.Var(
initialize=2,
domain=pyo.NonNegativeReals,
units=blk.costing_package.base_currency * pyo.units.kg**-1,
doc="GAC adsorbent cost per unit mass",
)
blk.adsorbent_cost = pyo.Var(
initialize=1e5,
domain=pyo.NonNegativeReals,
units=blk.costing_package.base_currency,
doc="Unit adsorbent capital cost",
)
blk.other_process_cost = pyo.Var(
initialize=1e5,
domain=pyo.NonNegativeReals,
units=blk.costing_package.base_currency,
doc="Unit other process capital cost",
)
blk.energy_consumption = pyo.Var(
initialize=100,
domain=pyo.NonNegativeReals,
units=pyo.units.kW,
doc="Approximate GAC system energy consumption",
)
# intermediate variables to shorten constraint code
num_contactors = (
parameter_blk.num_contactors_op + parameter_blk.num_contactors_redundant
)
unit_contactor_volume = blk.unit_model.bed_volume / parameter_blk.num_contactors_op
total_bed_volume = num_contactors * unit_contactor_volume
blk.contactor_cost_constraint = pyo.Constraint(
expr=blk.contactor_cost
== num_contactors
* pyo.units.convert(
(
parameter_blk.contactor_cost_coeff[3]
* (pyo.units.m**3) ** -3
* unit_contactor_volume**3
+ parameter_blk.contactor_cost_coeff[2]
* (pyo.units.m**3) ** -2
* unit_contactor_volume**2
+ parameter_blk.contactor_cost_coeff[1]
* (pyo.units.m**3) ** -1
* unit_contactor_volume**1
+ parameter_blk.contactor_cost_coeff[0]
)
* pyo.units.USD_2020,
to_units=blk.costing_package.base_currency,
)
)
blk.bed_mass_gac_ref_constraint = pyo.Constraint(
expr=blk.bed_mass_gac_ref
== smooth_min(
parameter_blk.bed_mass_max_ref / pyo.units.kg,
pyo.units.convert(blk.unit_model.bed_mass_gac, to_units=pyo.units.kg)
/ pyo.units.kg,
)
* pyo.units.kg
)
blk.adsorbent_unit_cost_constraint = pyo.Constraint(
expr=blk.adsorbent_unit_cost
== pyo.units.convert(
parameter_blk.adsorbent_unit_cost_coeff[0]
* pyo.exp(
blk.bed_mass_gac_ref
* pyo.units.kg**-1
* parameter_blk.adsorbent_unit_cost_coeff[1]
)
* pyo.units.USD_2020
* pyo.units.kg**-1,
to_units=blk.costing_package.base_currency * pyo.units.kg**-1,
)
)
blk.adsorbent_cost_constraint = pyo.Constraint(
expr=blk.adsorbent_cost == blk.adsorbent_unit_cost * blk.unit_model.bed_mass_gac
)
blk.other_process_cost_constraint = pyo.Constraint(
expr=blk.other_process_cost
== pyo.units.convert(
(
parameter_blk.other_cost_param[0]
* (total_bed_volume * pyo.units.m**-3)
** parameter_blk.other_cost_param[1]
)
* pyo.units.USD_2020,
to_units=blk.costing_package.base_currency,
)
)
blk.costing_package.add_cost_factor(blk, "TIC")
blk.capital_cost_constraint = pyo.Constraint(
expr=blk.capital_cost
== blk.cost_factor
* (blk.contactor_cost + blk.adsorbent_cost + blk.other_process_cost)
)
make_fixed_operating_cost_var(blk)
blk.gac_regen_cost = pyo.Var(
initialize=1e5,
domain=pyo.NonNegativeReals,
units=blk.costing_package.base_currency / blk.costing_package.base_period,
doc="Cost to regenerate spent GAC adsorbent by an offsite regeneration facility",
)
blk.gac_makeup_cost = pyo.Var(
initialize=1e5,
domain=pyo.NonNegativeReals,
units=blk.costing_package.base_currency / blk.costing_package.base_period,
doc="Cost to makeup spent GAC adsorbent with fresh adsorbent",
)
blk.gac_regen_cost_constraint = pyo.Constraint(
expr=blk.gac_regen_cost
== pyo.units.convert(
(
parameter_blk.regen_unit_cost
* (parameter_blk.regen_frac * blk.unit_model.gac_usage_rate)
),
to_units=blk.costing_package.base_currency
/ blk.costing_package.base_period,
)
)
blk.gac_makeup_cost_constraint = pyo.Constraint(
expr=blk.gac_makeup_cost
== pyo.units.convert(
(
parameter_blk.makeup_unit_cost
* ((1 - parameter_blk.regen_frac) * blk.unit_model.gac_usage_rate)
),
to_units=blk.costing_package.base_currency
/ blk.costing_package.base_period,
)
)
blk.fixed_operating_cost_constraint = pyo.Constraint(
expr=blk.fixed_operating_cost == blk.gac_regen_cost + blk.gac_makeup_cost
)
blk.energy_consumption_constraint = pyo.Constraint(
expr=pyo.units.convert(blk.energy_consumption, to_units=pyo.units.kW)
== pyo.units.kW
* (
parameter_blk.energy_consumption_coeff[2]
* total_bed_volume**2
* (pyo.units.m**3) ** -2
+ parameter_blk.energy_consumption_coeff[1]
* total_bed_volume
* (pyo.units.m**3) ** -1
+ parameter_blk.energy_consumption_coeff[0]
)
)
blk.costing_package.cost_flow(
pyo.units.convert(blk.energy_consumption, to_units=pyo.units.kW),
"electricity",
)