Source code for watertap.unit_models.zero_order.nanofiltration_zo

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# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory,
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# of Energy). All rights reserved.
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# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license
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"""
This module contains a zero-order representation of a nanofiltration unit
operation.
"""

import pyomo.environ as pyo
from idaes.core import declare_process_block_class
from pyomo.environ import Var, units as pyunits
from watertap.core import build_sido, constant_intensity, ZeroOrderBaseData

# Some more information about this module
__author__ = "Andrew Lee, Adam Atia"


[docs]@declare_process_block_class("NanofiltrationZO") class NanofiltrationZOData(ZeroOrderBaseData): """ Zero-Order model for a Nanofiltration unit operation. """ CONFIG = ZeroOrderBaseData.CONFIG()
[docs] def build(self): super().build() self._tech_type = "nanofiltration" build_sido(self) if ( self.config.process_subtype == "default" or self.config.process_subtype is None ): constant_intensity(self) else: self.rejection_comp = Var( self.flowsheet().time, self.config.property_package.config.solute_list, units=pyunits.dimensionless, doc="Component rejection", ) self.water_permeability_coefficient = Var( self.flowsheet().time, units=pyunits.L / pyunits.m**2 / pyunits.hour / pyunits.bar, doc="Membrane water permeability coefficient, A", ) self.applied_pressure = Var( self.flowsheet().time, units=pyunits.bar, doc="Net driving pressure across membrane", ) self.area = Var(units=pyunits.m**2, doc="Membrane area") self._fixed_perf_vars.append(self.applied_pressure) self._fixed_perf_vars.append(self.water_permeability_coefficient) @self.Constraint(self.flowsheet().time, doc="Water permeance constraint") def water_permeance_constraint(b, t): return b.properties_treated[t].flow_vol == pyunits.convert( b.water_permeability_coefficient[t] * b.area * b.applied_pressure[t], to_units=pyunits.m**3 / pyunits.s, ) @self.Constraint( self.flowsheet().time, self.config.property_package.config.solute_list, doc="Solute [observed] rejection constraint", ) def rejection_constraint(b, t, j): return ( b.rejection_comp[t, j] == 1 - b.properties_treated[t].conc_mass_comp[j] / b.properties_in[t].conc_mass_comp[j] ) self._perf_var_dict["Membrane Area (m^2)"] = self.area self._perf_var_dict["Net Driving Pressure (bar)"] = self.applied_pressure self._perf_var_dict["Water Permeability Coefficient (LMH/bar)"] = ( self.water_permeability_coefficient ) self._perf_var_dict[f"Rejection"] = self.rejection_comp
@property def default_costing_method(self): return self.cost_nanofiltration
[docs] @staticmethod def cost_nanofiltration(blk, number_of_parallel_units=1): """ General method for costing nanofiltration. Costing is carried out using either the general_power_law form or the standard form which computes membrane cost and replacement rate. Args: number_of_parallel_units (int, optional) - cost this unit as number_of_parallel_units parallel units (default: 1) """ # Get cost method for this technology cost_method = blk.unit_model._get_unit_cost_method(blk) valid_methods = ["cost_power_law_flow", "cost_membrane"] if cost_method == "cost_power_law_flow": blk.unit_model.cost_power_law_flow(blk, number_of_parallel_units) elif cost_method == "cost_membrane": # NOTE: number of units does not matter for cost_membrane # as its a linear function of membrane area blk.unit_model.cost_membrane(blk) else: raise KeyError( f"{cost_method} is not a relevant cost method for " f"{blk.unit_model._tech_type}. Specify one of the following " f"cost methods in the unit's YAML file: {valid_methods}" )
[docs] @staticmethod def cost_membrane(blk): """ Get membrane cost based on membrane area and unit membrane costs as well as fixed operating cost for membrane replacement. """ t0 = blk.flowsheet().time.first() # Get parameter dict from database parameter_dict = blk.unit_model.config.database.get_unit_operation_parameters( blk.unit_model._tech_type, subtype=blk.unit_model.config.process_subtype ) # Get costing parameter sub-block for this technology mem_cost, rep_rate = blk.unit_model._get_tech_parameters( blk, parameter_dict, blk.unit_model.config.process_subtype, ["membrane_cost", "membrane_replacement_rate"], ) # Add cost variable and constraint blk.capital_cost = pyo.Var( initialize=1, units=blk.config.flowsheet_costing_block.base_currency, bounds=(0, None), doc="Capital cost of unit operation", ) blk.variable_operating_cost = pyo.Var( initialize=1, units=blk.config.flowsheet_costing_block.base_currency / blk.config.flowsheet_costing_block.base_period, bounds=(0, None), doc="Fixed operating cost of unit operation", ) capex_expr = pyo.units.convert( mem_cost * pyo.units.convert(blk.unit_model.area, to_units=pyo.units.m**2), to_units=blk.config.flowsheet_costing_block.base_currency, ) # Determine if a costing factor is required blk.costing_package.add_cost_factor( blk, parameter_dict["capital_cost"]["cost_factor"] ) blk.capital_cost_constraint = pyo.Constraint( expr=blk.capital_cost == blk.cost_factor * capex_expr ) blk.variable_operating_cost_constraint = pyo.Constraint( expr=blk.variable_operating_cost == pyo.units.convert( rep_rate * mem_cost * pyo.units.convert(blk.unit_model.area, to_units=pyo.units.m**2), to_units=blk.config.flowsheet_costing_block.base_currency / blk.config.flowsheet_costing_block.base_period, ) )