#################################################################################
# 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/"
#################################################################################
"""
This module contains a zero-order representation of a deep well injection unit.
"""
import pyomo.environ as pyo
from pyomo.environ import Reference, units as pyunits, Var
from idaes.core import declare_process_block_class
from watertap.core import build_pt, pump_electricity, ZeroOrderBaseData
# Some more information about this module
__author__ = "Chenyu Wang"
[docs]@declare_process_block_class("DeepWellInjectionZO")
class DeepWellInjectionZOData(ZeroOrderBaseData):
"""
Zero-Order model for a deep well injection unit operation.
"""
CONFIG = ZeroOrderBaseData.CONFIG()
[docs] def build(self):
super().build()
self._tech_type = "deep_well_injection"
build_pt(self)
self._Q = Reference(self.properties[:].flow_vol)
pump_electricity(self, self._Q)
self.pipe_distance = Var(
self.flowsheet().config.time, units=pyunits.miles, doc="Piping distance"
)
self.pipe_diameter = Var(
self.flowsheet().config.time, units=pyunits.inches, doc="Pipe diameter"
)
self.flow_basis = Var(
self.flowsheet().time, units=pyunits.m**3 / pyunits.hour, doc="flow basis"
)
self._fixed_perf_vars.append(self.pipe_distance)
self._fixed_perf_vars.append(self.pipe_diameter)
self._fixed_perf_vars.append(self.flow_basis)
self._perf_var_dict["Pipe Distance (miles)"] = self.pipe_distance
self._perf_var_dict["Pipe Diameter (inches)"] = self.pipe_diameter
@property
def default_costing_method(self):
return self.cost_deep_well_injection
[docs] @staticmethod
def cost_deep_well_injection(blk, number_of_parallel_units=1):
"""
General method for costing deep well injection processes. Capital cost
is based on the cost of pump and pipe.
This method also registers the electricity demand as a costed flow.
Args:
number_of_parallel_units (int, optional) - cost this unit as
number_of_parallel_units parallel units (default: 1)
"""
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
A, B, C = blk.unit_model._get_tech_parameters(
blk,
parameter_dict,
blk.unit_model.config.process_subtype,
["well_pump_cost", "pipe_cost_basis", "flow_exponent"],
)
# 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",
)
cost_well_pump = A
cost_pipe = (
B * blk.unit_model.pipe_distance[t0] * blk.unit_model.pipe_diameter[t0]
)
cost_total = pyo.units.convert(
cost_well_pump + cost_pipe,
to_units=blk.config.flowsheet_costing_block.base_currency,
)
Q = pyo.units.convert(
blk.unit_model.properties[t0].flow_vol,
to_units=pyo.units.m**3 / pyo.units.hour,
)
sizing_term = Q / blk.unit_model.flow_basis[t0]
# 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,
cost_total,
C,
sizing_term,
factor,
number_of_parallel_units,
)
# Register flows
blk.config.flowsheet_costing_block.cost_flow(
blk.unit_model.electricity[t0], "electricity"
)