Source code for watertap.unit_models.dewatering

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# 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/"
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"""
Dewatering unit model for BSM2 and plant-wide wastewater treatment modeling. 
This unit inherits from the IDAES separator unit.

Model based on

J. Alex, L. Benedetti, J.B. Copp, K.V. Gernaey, U. Jeppsson,
I. Nopens, M.N. Pons, C. Rosen, J.P. Steyer and
P. A. Vanrolleghem
Benchmark Simulation Model no. 2 (BSM2)

Modifications made to TSS formulation based on ASM type.
"""
from enum import Enum, auto

# Import IDAES cores
from idaes.core import (
    declare_process_block_class,
)
from idaes.models.unit_models.separator import SeparatorData, SplittingType

from idaes.core.util.tables import create_stream_table_dataframe
import idaes.logger as idaeslog

from pyomo.environ import (
    Param,
    units as pyunits,
    Var,
    NonNegativeReals,
)
from pyomo.common.config import ConfigValue, In

from idaes.core.util.exceptions import (
    ConfigurationError,
)
from watertap.costing.unit_models.dewatering import cost_dewatering

__author__ = "Alejandro Garciadiego, Adam Atia"


# Set up logger
_log = idaeslog.getLogger(__name__)


[docs]class ActivatedSludgeModelType(Enum): """ ASM1: ASM1 model ASM2D: ASM2D model modified_ASM2D: modified ASM2D model for ADM1 compatibility """ ASM1 = auto() ASM2D = auto() modified_ASM2D = auto()
[docs]@declare_process_block_class("DewateringUnit") class DewateringData(SeparatorData): """ Dewatering unit block for BSM2 """ CONFIG = SeparatorData.CONFIG() CONFIG.outlet_list = ["underflow", "overflow"] CONFIG.split_basis = SplittingType.componentFlow CONFIG.declare( "activated_sludge_model", ConfigValue( default=ActivatedSludgeModelType.ASM1, domain=In(ActivatedSludgeModelType), description="Activated Sludge Model used with unit", doc=""" Options to account for version of activated sludge model property package. **default** - ``ActivatedSludgeModelType.ASM1`` .. csv-table:: :header: "Configuration Options", "Description" "``ActivatedSludgeModelType.ASM1``", "ASM1 model" "``ActivatedSludgeModelType.ASM2D``", "ASM2D model" "``ActivatedSludgeModelType.modified_ASM2D``", "modified ASM2D model for ADM1 compatibility" """, ), )
[docs] def build(self): """ Begin building model. Args: None Returns: None """ # Call UnitModel.build to set up dynamics super(DewateringData, self).build() if "underflow" and "overflow" not in self.config.outlet_list: raise ConfigurationError( "{} encountered unrecognised " "outlet_list. This should not " "occur - please use overflow " "and underflow as outlets.".format(self.name) ) self.p_dewat = Param( initialize=0.28, units=pyunits.dimensionless, mutable=True, doc="Percentage of suspended solids in the underflow", ) self.TSS_rem = Param( initialize=0.98, units=pyunits.dimensionless, mutable=True, doc="Percentage of suspended solids removed", ) self.electricity_consumption = Var( self.flowsheet().time, units=pyunits.kW, bounds=(0, None), doc="Electricity consumption of unit", ) # 0.026 kWh/m3 average between averages of belt and screw presses & centrifuge in relation to flow capacity self.energy_electric_flow_vol_inlet = Param( self.flowsheet().time, units=pyunits.kWh / (pyunits.m**3), initialize=0.026, mutable=True, doc="Specific electricity intensity of unit", ) @self.Constraint(self.flowsheet().time, doc="Electricity consumption equation") def eq_electricity_consumption(blk, t): return blk.electricity_consumption[t] == pyunits.convert( blk.energy_electric_flow_vol_inlet[t] * blk.inlet.flow_vol[t], to_units=pyunits.kW, ) self.hydraulic_retention_time = Var( self.flowsheet().time, initialize=1800, domain=NonNegativeReals, units=pyunits.s, doc="Hydraulic retention time", ) self.volume = Var( self.flowsheet().time, initialize=1800, domain=NonNegativeReals, units=pyunits.m**3, doc="Hydraulic retention time", ) @self.Constraint(self.flowsheet().time, doc="Hydraulic retention time equation") def eq_hydraulic_retention(blk, t): return ( self.hydraulic_retention_time[t] == self.volume[t] / self.inlet.flow_vol[t] ) @self.Expression(self.flowsheet().time, doc="Suspended solid concentration") def TSS_in(blk, t): if blk.config.activated_sludge_model == ActivatedSludgeModelType.ASM1: return 0.75 * ( sum( blk.inlet.conc_mass_comp[t, i] for i in blk.config.property_package.tss_component_set ) ) elif blk.config.activated_sludge_model == ActivatedSludgeModelType.ASM2D: return blk.inlet.conc_mass_comp[ t, blk.config.property_package.tss_component_set.first() ] elif ( blk.config.activated_sludge_model == ActivatedSludgeModelType.modified_ASM2D ): return blk.mixed_state[t].TSS else: raise ConfigurationError( "The activated_sludge_model was not specified properly in configuration options." ) @self.Expression(self.flowsheet().time, doc="Dewatering factor") def f_dewat(blk, t): return blk.p_dewat * (10 / (blk.TSS_in[t])) @self.Expression(self.flowsheet().time, doc="Remove factor") def f_q_du(blk, t): return blk.TSS_rem / (pyunits.kg / pyunits.m**3) / 100 / blk.f_dewat[t] @self.Constraint( self.flowsheet().time, self.config.property_package.particulate_component_set, doc="particulate fraction", ) def overflow_particulate_fraction(blk, t, i): return blk.split_fraction[t, "overflow", i] == 1 - blk.TSS_rem @self.Constraint( self.flowsheet().time, self.config.property_package.non_particulate_component_set, doc="soluble fraction", ) def non_particulate_components(blk, t, i): return blk.split_fraction[t, "overflow", i] == 1 - blk.f_q_du[t]
def _get_performance_contents(self, time_point=0): var_dict = {} param_dict = {} for k in self.split_fraction.keys(): if k[0] == time_point: var_dict[f"Split Fraction [{str(k[1:])}]"] = self.split_fraction[k] var_dict["Electricity consumption"] = self.electricity_consumption[time_point] param_dict["Specific electricity consumption"] = ( self.energy_electric_flow_vol_inlet[time_point] ) var_dict["Unit Volume"] = self.volume[time_point] var_dict["Hydraulic Retention Time"] = self.hydraulic_retention_time[time_point] return {"vars": var_dict, "params": param_dict} def _get_stream_table_contents(self, time_point=0): outlet_list = self.create_outlet_list() io_dict = {} if self.config.mixed_state_block is None: io_dict["Inlet"] = self.mixed_state else: io_dict["Inlet"] = self.config.mixed_state_block for o in outlet_list: io_dict[o] = getattr(self, o + "_state") return create_stream_table_dataframe(io_dict, time_point=time_point) @property def default_costing_method(self): return cost_dewatering