Source code for watertap.unit_models.zero_order.chemical_addition_zo

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# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory,
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"""
This module contains a zero-order representation of a chemical addition unit
operation.
"""
import pyomo.environ as pyo

from idaes.core import declare_process_block_class
from idaes.core.util.exceptions import ConfigurationError

from watertap.core import build_pt, pump_electricity, ZeroOrderBaseData

# Some more inforation about this module
__author__ = "Andrew Lee"


[docs]@declare_process_block_class("ChemicalAdditionZO") class ChemicalAdditionZOData(ZeroOrderBaseData): """ Zero-Order model for a chemical addition unit operation. """ CONFIG = ZeroOrderBaseData.CONFIG()
[docs] def build(self): super().build() self._tech_type = "chemical_addition" if self.config.process_subtype is None: raise ConfigurationError( f"{self.name} - zero-order chemical addition operations " "require the process_subtype configuration argument to be set" ) build_pt(self) self.chemical_dosage = pyo.Var( self.flowsheet().time, units=pyo.units.mg / pyo.units.L, bounds=(0, None), doc="Dosing rate of chemical", ) self.solution_density = pyo.Var( bounds=(0, None), units=pyo.units.kg / pyo.units.m**3, doc="Mass density of chemical solution", ) self.ratio_in_solution = pyo.Var( bounds=(0, 1), units=pyo.units.dimensionless, doc="Mass fraction of chemical in solution", ) self.chemical_flow_vol = pyo.Var( self.flowsheet().time, units=pyo.units.m**3 / pyo.units.s, bounds=(0, None), doc="Volumetric flow rate of chemical solution", ) self._fixed_perf_vars.append(self.chemical_dosage) self._fixed_perf_vars.append(self.solution_density) self._fixed_perf_vars.append(self.ratio_in_solution) self._perf_var_dict["Chemical Dosage"] = self.chemical_dosage self._perf_var_dict["Chemical Flow"] = self.chemical_flow_vol def rule_chem_flow(blk, t): return blk.chemical_flow_vol[t] == pyo.units.convert( blk.chemical_dosage[t] * blk.properties[t].flow_vol / (blk.solution_density * blk.ratio_in_solution), to_units=pyo.units.m**3 / pyo.units.s, ) self.chemical_flow_constraint = pyo.Constraint( self.flowsheet().time, rule=rule_chem_flow ) pump_electricity(self, self.chemical_flow_vol)
@property def default_costing_method(self): return self.cost_chemical_addition
[docs] @staticmethod def cost_chemical_addition(blk, number_of_parallel_units=1): """ General method for costing chemical addition processes. Capital cost is based on the mass flow rate of chemical added. This method also registers the chemical flow and electricity demand as costed flows. Args: number_of_parallel_units (int, optional) - cost this unit as number_of_parallel_units parallel units (default: 1) """ chem_name = blk.unit_model.config.process_subtype t0 = blk.flowsheet().time.first() chem_flow_mass = ( blk.unit_model.chemical_dosage[t0] * blk.unit_model.properties[t0].flow_vol / blk.unit_model.ratio_in_solution ) sizing_term = blk.unit_model.chemical_flow_vol[t0] / ( pyo.units.gal / pyo.units.day ) # 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 A, B = blk.unit_model._get_tech_parameters( blk, parameter_dict, blk.unit_model.config.process_subtype, ["capital_a_parameter", "capital_b_parameter"], ) # Determine if a costing factor is required factor = parameter_dict["capital_cost"]["cost_factor"] # Call general power law costing method blk.unit_model._general_power_law_form( blk, A, B, sizing_term, factor, number_of_parallel_units ) # Register flows blk.config.flowsheet_costing_block.cost_flow( blk.unit_model.electricity[t0], "electricity" ) blk.config.flowsheet_costing_block.cost_flow(chem_flow_mass, chem_name)