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Extended BSM2 Flowsheet Costing #1405

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merged 6 commits into from
May 24, 2024
Merged

Extended BSM2 Flowsheet Costing #1405

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153c3c2
Add costing to BSM2_P_extension flowsheet
MarcusHolly May 22, 2024
5773dda
Add costing to Extended BSM2 GUI
MarcusHolly May 22, 2024
f1e4d60
Add costing tests
MarcusHolly May 23, 2024
8ada67b
Address Adam's comments
MarcusHolly May 23, 2024
4fcb5e8
Skip costing tests on Mac
MarcusHolly May 24, 2024
bee9985
Merge branch 'main' into bsm2_minor_refinements
MarcusHolly May 24, 2024
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106 changes: 54 additions & 52 deletions watertap/examples/flowsheets/case_studies/full_water_resource_recovery_facility/BSM2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -98,6 +98,7 @@
print("\n\n=============OPTIMIZATION RESULTS=============\n\n")
# display_results(m)
display_costing(m)
display_performance_metrics(m)

Check warning on line 101 in watertap/examples/flowsheets/case_studies/full_water_resource_recovery_facility/BSM2.py

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watertap/examples/flowsheets/case_studies/full_water_resource_recovery_facility/BSM2.py#L101 

Added line #L101 was not covered by tests

return m, results

Expand Down Expand Up @@ -485,7 +486,6 @@

# process costing and add system level metrics
m.fs.costing.cost_process()
m.fs.costing.add_electricity_intensity(m.fs.FeedWater.properties[0].flow_vol)
m.fs.costing.add_annual_water_production(m.fs.Treated.properties[0].flow_vol)
m.fs.costing.add_LCOW(m.fs.FeedWater.properties[0].flow_vol)
m.fs.costing.add_specific_energy_consumption(m.fs.FeedWater.properties[0].flow_vol)
Expand Down Expand Up @@ -622,6 +622,59 @@
"Total annualized cost: %.2f $/yr"
% pyo.value(m.fs.costing.total_annualized_cost)
)
print(
"capital cost R1",
pyo.value(m.fs.R1.costing.capital_cost),
pyo.units.get_units(m.fs.R1.costing.capital_cost),
)
print(
"capital cost R2",
pyo.value(m.fs.R2.costing.capital_cost),
pyo.units.get_units(m.fs.R2.costing.capital_cost),
)
print(
"capital cost R3",
pyo.value(m.fs.R3.costing.capital_cost),
pyo.units.get_units(m.fs.R3.costing.capital_cost),
)
print(
"capital cost R4",
pyo.value(m.fs.R4.costing.capital_cost),
pyo.units.get_units(m.fs.R4.costing.capital_cost),
)
print(
"capital cost R5",
pyo.value(m.fs.R5.costing.capital_cost),
pyo.units.get_units(m.fs.R5.costing.capital_cost),
)
print(
"capital cost primary clarifier",
pyo.value(m.fs.CL.costing.capital_cost),
pyo.units.get_units(m.fs.CL.costing.capital_cost),
)
print(
"capital cost secondary clarifier",
pyo.value(m.fs.CL1.costing.capital_cost),
pyo.units.get_units(m.fs.CL1.costing.capital_cost),
)
print(
"capital cost AD",
pyo.value(m.fs.RADM.costing.capital_cost),
pyo.units.get_units(m.fs.RADM.costing.capital_cost),
)
print(
"capital cost dewatering Unit",
pyo.value(m.fs.DU.costing.capital_cost),
pyo.units.get_units(m.fs.DU.costing.capital_cost),
)
print(
"capital cost thickener unit",
pyo.value(m.fs.TU.costing.capital_cost),
pyo.units.get_units(m.fs.TU.costing.capital_cost),
)


def display_performance_metrics(m):
print(
"Specific energy consumption with respect to influent flowrate: %.1f kWh/m3"
% pyo.value(m.fs.costing.specific_energy_consumption)
Expand Down Expand Up @@ -683,57 +736,6 @@
pyo.units.get_units(m.fs.RADM.liquid_phase.properties_in[0].flow_vol),
)

print(
"capital cost R1",
pyo.value(m.fs.R1.costing.capital_cost),
pyo.units.get_units(m.fs.R1.costing.capital_cost),
)
print(
"capital cost R2",
pyo.value(m.fs.R2.costing.capital_cost),
pyo.units.get_units(m.fs.R2.costing.capital_cost),
)
print(
"capital cost R3",
pyo.value(m.fs.R3.costing.capital_cost),
pyo.units.get_units(m.fs.R3.costing.capital_cost),
)
print(
"capital cost R4",
pyo.value(m.fs.R4.costing.capital_cost),
pyo.units.get_units(m.fs.R4.costing.capital_cost),
)
print(
"capital cost R5",
pyo.value(m.fs.R5.costing.capital_cost),
pyo.units.get_units(m.fs.R5.costing.capital_cost),
)
print(
"capital cost primary clarifier",
pyo.value(m.fs.CL.costing.capital_cost),
pyo.units.get_units(m.fs.CL.costing.capital_cost),
)
print(
"capital cost secondary clarifier",
pyo.value(m.fs.CL1.costing.capital_cost),
pyo.units.get_units(m.fs.CL1.costing.capital_cost),
)
print(
"capital cost AD",
pyo.value(m.fs.RADM.costing.capital_cost),
pyo.units.get_units(m.fs.RADM.costing.capital_cost),
)
print(
"capital cost dewatering Unit",
pyo.value(m.fs.DU.costing.capital_cost),
pyo.units.get_units(m.fs.DU.costing.capital_cost),
)
print(
"capital cost thickener unit",
pyo.value(m.fs.TU.costing.capital_cost),
pyo.units.get_units(m.fs.TU.costing.capital_cost),
)


if __name__ == "__main__":
m, results = main()
203 changes: 202 additions & 1 deletion ...xamples/flowsheets/case_studies/full_water_resource_recovery_facility/BSM2_P_extension.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,7 @@

from idaes.core import (
FlowsheetBlock,
UnitModelCostingBlock,
)
from idaes.models.unit_models import (
CSTR,
Expand Down Expand Up @@ -74,7 +75,14 @@
Thickener,
ActivatedSludgeModelType as thickener_type,
)
from watertap.core.util.initialization import check_solve

from watertap.core.util.initialization import check_solve, assert_degrees_of_freedom
from watertap.costing import WaterTAPCosting
from watertap.costing.unit_models.clarifier import (
cost_circular_clarifier,
cost_primary_clarifier,
)


# Set up logger
_log = idaeslog.getLogger(__name__)
Expand Down Expand Up @@ -116,6 +124,17 @@ def main(bio_P=True):
fail_flag=True,
)

add_costing(m)
m.fs.costing.initialize()

assert_degrees_of_freedom(m, 0)

results = solve(m)
pyo.assert_optimal_termination(results)

display_costing(m)
display_performance_metrics(m)

return m, results


Expand Down Expand Up @@ -471,6 +490,8 @@ def set_operating_conditions(m):
m.fs.CL2.split_fraction[0, "effluent", "X_PP"].fix(0.00187)
m.fs.CL2.split_fraction[0, "effluent", "X_S"].fix(0.00187)

m.fs.CL2.surface_area.fix(1500 * pyo.units.m**2)

# Sludge purge separator
m.fs.SP2.split_fraction[:, "recycle"].fix(0.985)

Expand Down Expand Up @@ -658,6 +679,186 @@ def solve(m, solver=None):
return results


def add_costing(m):
m.fs.costing = WaterTAPCosting()
m.fs.costing.base_currency = pyo.units.USD_2020
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Is this what we use on the conventional BSM2? I think we should avoid 2020 as the base currency because of the pandemic's impact.

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Conventional also used 2020... should I switch both to 2018 or 2019?

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Good question. I'm not sure that we've selected a standard year that we want to go by. I think I can recall using 2018 for a few of the IEDO models previously. I suppose we can put a pin it this for now if we'd rather settle on a year.

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But perhaps the best route is to go with the latest year that we have the CEPCI index for

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The latest year in IDAES is 2022, but it appears that hasn't made it's way into WaterTAP yet. I tried 2021 as well, but the solver failed to return an optimal solution... not sure why that would happen.


# Costing Blocks
m.fs.R1.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)
m.fs.R2.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)
m.fs.R3.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)
m.fs.R4.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)
m.fs.R5.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)
m.fs.R6.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)
m.fs.R7.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)
m.fs.CL.costing = UnitModelCostingBlock(
flowsheet_costing_block=m.fs.costing,
costing_method=cost_primary_clarifier,
)

m.fs.CL2.costing = UnitModelCostingBlock(
flowsheet_costing_block=m.fs.costing,
costing_method=cost_circular_clarifier,
)

m.fs.AD.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)
m.fs.dewater.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)
m.fs.thickener.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)

# TODO: Leaving out mixer costs; consider including later

# process costing and add system level metrics
m.fs.costing.cost_process()
m.fs.costing.add_annual_water_production(m.fs.Treated.properties[0].flow_vol)
m.fs.costing.add_LCOW(m.fs.FeedWater.properties[0].flow_vol)
m.fs.costing.add_specific_energy_consumption(m.fs.FeedWater.properties[0].flow_vol)

m.fs.objective = pyo.Objective(expr=m.fs.costing.LCOW)
iscale.set_scaling_factor(m.fs.costing.LCOW, 1e3)
iscale.set_scaling_factor(m.fs.costing.total_capital_cost, 1e-7)
iscale.set_scaling_factor(m.fs.costing.total_capital_cost, 1e-5)

iscale.calculate_scaling_factors(m.fs)


def display_costing(m):
print("Levelized cost of water: %.2f $/m3" % pyo.value(m.fs.costing.LCOW))

print(
"Total operating cost: %.2f $/yr" % pyo.value(m.fs.costing.total_operating_cost)
)
print("Total capital cost: %.2f $" % pyo.value(m.fs.costing.total_capital_cost))

print(
"Total annualized cost: %.2f $/yr"
% pyo.value(m.fs.costing.total_annualized_cost)
)

print(
"capital cost R1",
pyo.value(m.fs.R1.costing.capital_cost),
pyo.units.get_units(m.fs.R1.costing.capital_cost),
)
print(
"capital cost R2",
pyo.value(m.fs.R2.costing.capital_cost),
pyo.units.get_units(m.fs.R2.costing.capital_cost),
)
print(
"capital cost R3",
pyo.value(m.fs.R3.costing.capital_cost),
pyo.units.get_units(m.fs.R3.costing.capital_cost),
)
print(
"capital cost R4",
pyo.value(m.fs.R4.costing.capital_cost),
pyo.units.get_units(m.fs.R4.costing.capital_cost),
)
print(
"capital cost R5",
pyo.value(m.fs.R5.costing.capital_cost),
pyo.units.get_units(m.fs.R5.costing.capital_cost),
)
print(
"capital cost R6",
pyo.value(m.fs.R6.costing.capital_cost),
pyo.units.get_units(m.fs.R6.costing.capital_cost),
)
print(
"capital cost R7",
pyo.value(m.fs.R7.costing.capital_cost),
pyo.units.get_units(m.fs.R7.costing.capital_cost),
)
print(
"capital cost primary clarifier",
pyo.value(m.fs.CL.costing.capital_cost),
pyo.units.get_units(m.fs.CL.costing.capital_cost),
)
print(
"capital cost secondary clarifier",
pyo.value(m.fs.CL2.costing.capital_cost),
pyo.units.get_units(m.fs.CL2.costing.capital_cost),
)
print(
"capital cost AD",
pyo.value(m.fs.AD.costing.capital_cost),
pyo.units.get_units(m.fs.AD.costing.capital_cost),
)
print(
"capital cost dewatering Unit",
pyo.value(m.fs.dewater.costing.capital_cost),
pyo.units.get_units(m.fs.dewater.costing.capital_cost),
)
print(
"capital cost thickener unit",
pyo.value(m.fs.thickener.costing.capital_cost),
pyo.units.get_units(m.fs.thickener.costing.capital_cost),
)


def display_performance_metrics(m):
print(
"Specific energy consumption with respect to influent flowrate: %.1f kWh/m3"
% pyo.value(m.fs.costing.specific_energy_consumption)
)

print(
"electricity consumption R5",
pyo.value(m.fs.R5.electricity_consumption[0]),
pyo.units.get_units(m.fs.R5.electricity_consumption[0]),
)
print(
"electricity consumption R6",
pyo.value(m.fs.R6.electricity_consumption[0]),
pyo.units.get_units(m.fs.R6.electricity_consumption[0]),
)
print(
"electricity consumption R7",
pyo.value(m.fs.R7.electricity_consumption[0]),
pyo.units.get_units(m.fs.R7.electricity_consumption[0]),
)
print(
"electricity consumption primary clarifier",
pyo.value(m.fs.CL.electricity_consumption[0]),
pyo.units.get_units(m.fs.CL.electricity_consumption[0]),
)
print(
"electricity consumption secondary clarifier",
pyo.value(m.fs.CL2.electricity_consumption[0]),
pyo.units.get_units(m.fs.CL2.electricity_consumption[0]),
)
print(
"electricity consumption AD",
pyo.value(m.fs.AD.electricity_consumption[0]),
pyo.units.get_units(m.fs.AD.electricity_consumption[0]),
)
print(
"electricity consumption dewatering Unit",
pyo.value(m.fs.dewater.electricity_consumption[0]),
pyo.units.get_units(m.fs.dewater.electricity_consumption[0]),
)
print(
"electricity consumption thickening Unit",
pyo.value(m.fs.thickener.electricity_consumption[0]),
pyo.units.get_units(m.fs.thickener.electricity_consumption[0]),
)
print(
"Influent flow",
pyo.value(m.fs.FeedWater.flow_vol[0]),
pyo.units.get_units(m.fs.FeedWater.flow_vol[0]),
)
print(
"flow into R3",
pyo.value(m.fs.R3.control_volume.properties_in[0].flow_vol),
pyo.units.get_units(m.fs.R3.control_volume.properties_in[0].flow_vol),
)
print(
"flow into RADM",
pyo.value(m.fs.AD.liquid_phase.properties_in[0].flow_vol),
pyo.units.get_units(m.fs.AD.liquid_phase.properties_in[0].flow_vol),
)


if __name__ == "__main__":
# This method builds and runs a steady state activated sludge flowsheet.
m, results = main()
Expand Down
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