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merged 5 commits into from
Jul 25, 2025
Merged

Redundant class cleanup #86

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bbea18f
Remove redundant parameter declarations from SUTRAEconomics
softwareengineerprogrammer Jul 24, 2025
b36c453
Use Peaking Boiler Cost per KW in SUTRAEconomics (follow-up from http…
softwareengineerprogrammer Jul 24, 2025
7d1f8b5
SBTEconomics - remove commented code, call calculate_field_gathering_…
softwareengineerprogrammer Jul 24, 2025
87e89b3
SBTEconomics - call calculate_plant_costs
softwareengineerprogrammer Jul 24, 2025
e9ab8a2
fix oversight in 7d1f8b54f8dbdc8b0c1f607825e9c21d2cf063df (remove mis…
softwareengineerprogrammer Jul 24, 2025
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329 changes: 2 additions & 327 deletions src/geophires_x/SBTEconomics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -101,67 +101,7 @@ def __init__(self, model: Model):
sclass = str(__class__).replace("<class \'", "")
self.MyClass = sclass.replace("\'>", "")
self.MyPath = os.path.abspath(__file__)
#self.Electricity_rate = None
#self.Discount_rate = None
#self.error = 0
#self.AverageOPEX_Plant = 0
#self.OPEX_Plant = 0
#self.TotalCAPEX = 0
#self.CAPEX_Surface_Plant = 0
#self.CAPEX_Drilling = 0

# Set up all the Parameters that will be predefined by this class using the different types of parameter classes.
# Setting up includes giving it a name, a default value, The Unit Type (length, volume, temperature, etc.)
# and Unit Name of that value, sets it as required (or not), sets allowable range,
# the error message if that range is exceeded, the ToolTip Text, and the name of the class that created it.
# This includes setting up temporary variables that will be available to all the class but noy read in by user,
# or used for Output
# This also includes all Parameters that are calculated and then published using the Printouts function.
# If you choose to subclass this master class, you can do so before or after you create your own parameters.
# If you do, you can also choose to call this method from you class, which will effectively add
# and set all these parameters to your class.
# NB: inputs we already have ("already have it") need to be set at ReadParameter time so values
# are set at the last possible time

"""
self.O_and_M_cost_plant = self.ParameterDict[self.O_and_M_cost_plant.Name] = floatParameter(
"Operation & Maintenance Cost of Surface Plant",
DefaultValue=0.015,
Min=0.0,
Max=0.2,
UnitType=Units.PERCENT,
PreferredUnits=PercentUnit.TENTH,
CurrentUnits=PercentUnit.TENTH,
Required=True,
ErrMessage="assume default Operation & Maintenance cost of surface plant expressed as fraction of total surface plant capital cost (0.015)"
)
self.Direct_use_heat_cost_per_kWth = self.ParameterDict[
self.Direct_use_heat_cost_per_kWth.Name] = floatParameter(
"Capital Cost for Surface Plant for Direct-use System",
DefaultValue=100.0,
Min=0.0,
Max=10000.0,
UnitType=Units.ENERGYCOST,
PreferredUnits=EnergyCostUnit.DOLLARSPERKW,
CurrentUnits=EnergyCostUnit.DOLLARSPERKW,
Required=False,
ErrMessage="assume default Capital cost for surface plant for direct-use system (100 $/kWth)"
)
self.Power_plant_cost_per_kWe = self.ParameterDict[self.Power_plant_cost_per_kWe.Name] = floatParameter(
"Capital Cost for Power Plant for Electricity Generation",
DefaultValue=3000.0,
Min=0.0,
Max=10000.0,
UnitType=Units.ENERGYCOST,
PreferredUnits=EnergyCostUnit.DOLLARSPERKW,
CurrentUnits=EnergyCostUnit.DOLLARSPERKW,
Required=True,
ErrMessage="assume default Power plant capital cost per kWe (3000 USD/kWe)"
)

# results are stored here and in the parent ProducedTemperature array

"""
model.logger.info(f'complete {__class__!s}: {sys._getframe().f_code.co_name}')

def __str__(self):
Expand All @@ -183,10 +123,6 @@ def read_parameters(self, model: Model) -> None:
# because the call to the super.readparameters will set all the variables,
# including the ones that are specific to this class

# inputs we already have - needs to be set at ReadParameter time so values set at the latest possible time
# self.Discount_rate = model.economics.discountrate.value # same units are GEOPHIRES
# self.Electricity_rate = model.surfaceplant.electricity_cost_to_buy.value # same units are GEOPHIRES

model.logger.info(f'complete {__class__!s}: {sys._getframe().f_code.co_name}')

def Calculate(self, model: Model) -> None:
Expand Down Expand Up @@ -280,269 +216,8 @@ def Calculate(self, model: Model) -> None:
self.cost_lateral_section.value + self.cost_to_junction_section.value)

self.Cstim.value = self.calculate_stimulation_costs(model).to(self.Cstim.CurrentUnits).magnitude

# field gathering system costs (M$)
if self.ccgathfixed.Valid:
self.Cgath.value = self.ccgathfixed.value
else:
self.Cgath.value = self.ccgathadjfactor.value * 50 - 6 * np.max(
model.surfaceplant.HeatExtracted.value) * 1000. # (GEOPHIRES v1 correlation)
if model.wellbores.impedancemodelused.value:
pumphp = np.max(model.wellbores.PumpingPower.value) * 1341
numberofpumps = np.ceil(pumphp / 2000) # pump can be maximum 2,000 hp
if numberofpumps == 0:
self.Cpumps = 0.0
else:
pumphpcorrected = pumphp / numberofpumps
self.Cpumps = numberofpumps * 1.5 * (
(1750 * pumphpcorrected ** 0.7) * 3 * pumphpcorrected ** (-0.11))
else:
if model.wellbores.productionwellpumping.value:
prodpumphp = np.max(model.wellbores.PumpingPowerProd.value) / model.wellbores.nprod.value * 1341
Cpumpsprod = model.wellbores.nprod.value * 1.5 * (1750 * prodpumphp ** 0.7 + 5750 *
prodpumphp ** 0.2 + 10000 + np.max(
model.wellbores.pumpdepth.value) * 50 * 3.281) # see page 46 in user's manual assuming rental of rig for 1 day.
else:
Cpumpsprod = 0

injpumphp = np.max(model.wellbores.PumpingPowerInj.value) * 1341
numberofinjpumps = np.ceil(injpumphp / 2000) # pump can be maximum 2,000 hp
if numberofinjpumps == 0:
Cpumpsinj = 0
else:
injpumphpcorrected = injpumphp / numberofinjpumps
Cpumpsinj = numberofinjpumps * 1.5 * (
1750 * injpumphpcorrected ** 0.7) * 3 * injpumphpcorrected ** (-0.11)
self.Cpumps = Cpumpsinj + Cpumpsprod

# Based on GETEM 2016 #1.15 for 15% contingency
self.Cgath.value = 1.15 * self.ccgathadjfactor.value * self._indirect_cost_factor * (
(model.wellbores.nprod.value + model.wellbores.ninj.value) * 750 * 500. + self.Cpumps) / 1E6

# plant costs
if (model.surfaceplant.enduse_option.value == EndUseOptions.HEAT
and model.surfaceplant.plant_type.value not in [PlantType.ABSORPTION_CHILLER, PlantType.HEAT_PUMP, PlantType.DISTRICT_HEATING]): # direct-use
if self.ccplantfixed.Valid:
self.Cplant.value = self.ccplantfixed.value
else:
self.Cplant.value = self._indirect_cost_factor * 1.15 * self.ccplantadjfactor.value * 250E-6 * np.max(
model.surfaceplant.HeatExtracted.value) * 1000. # 1.15 for 15% contingency

# absorption chiller
elif model.surfaceplant.enduse_option.value == EndUseOptions.HEAT and model.surfaceplant.plant_type.value == PlantType.ABSORPTION_CHILLER: # absorption chiller
if self.ccplantfixed.Valid:
self.Cplant.value = self.ccplantfixed.value
else:
# this is for the direct-use part all the way up to the absorption chiller
self.Cplant.value = self._indirect_cost_factor * 1.15 * self.ccplantadjfactor.value * 250E-6 * np.max(
model.surfaceplant.HeatExtracted.value) * 1000. # 1.15 for 15% contingency
if self.chillercapex.value == -1: # no value provided by user, use built-in correlation ($2500/ton)
self.chillercapex.value = self._indirect_cost_factor * 1.15 * np.max(
model.surfaceplant.cooling_produced.value) * 1000 / 3.517 * 2500 / 1e6 # $2,500/ton of cooling. 1.15 for 15% contingency

# now add chiller cost to surface plant cost
self.Cplant.value += self.chillercapex.value

# heat pump
elif model.surfaceplant.enduse_option.value == EndUseOptions.HEAT and model.surfaceplant.plant_type.value == PlantType.HEAT_PUMP:
if self.ccplantfixed.Valid:
self.Cplant.value = self.ccplantfixed.value
else:
# this is for the direct-use part all the way up to the heat pump
self.Cplant.value = self._indirect_cost_factor * 1.15 * self.ccplantadjfactor.value * 250E-6 * np.max(
model.surfaceplant.HeatExtracted.value) * 1000. # 1.15 for 15% contingency
if self.heatpumpcapex.value == -1: # no value provided by user, use built-in correlation ($150/kWth)
self.heatpumpcapex.value = self._indirect_cost_factor * 1.15 * np.max(
model.surfaceplant.HeatProduced.value) * 1000 * 150 / 1e6 # $150/kW. 1.15 for 15% contingency

# now add heat pump cost to surface plant cost
self.Cplant.value += self.heatpumpcapex.value

# district heating
elif model.surfaceplant.enduse_option.value == EndUseOptions.HEAT and model.surfaceplant.plant_type.value == PlantType.DISTRICT_HEATING:
if self.ccplantfixed.Valid:
self.Cplant.value = self.ccplantfixed.value
else:
self.Cplant.value = self._indirect_cost_factor * 1.15 * self.ccplantadjfactor.value * 250E-6 * np.max(
model.surfaceplant.HeatExtracted.value) * 1000. # 1.15 for 15% contingency

self.peakingboilercost.value = (self.peaking_boiler_cost_per_kW.quantity()
.to('USD / kilowatt').magnitude
* model.surfaceplant.max_peaking_boiler_demand.value
/ 1000)

self.Cplant.value += self.peakingboilercost.value # add peaking boiler cost to surface plant cost


else: # all other options have power plant
if model.surfaceplant.plant_type.value == PlantType.SUB_CRITICAL_ORC:
MaxProducedTemperature = np.max(model.surfaceplant.TenteringPP.value)
if MaxProducedTemperature < 150.:
C3 = -1.458333E-3
C2 = 7.6875E-1
C1 = -1.347917E2
C0 = 1.0075E4
CCAPP1 = C3 * MaxProducedTemperature ** 3 + C2 * MaxProducedTemperature ** 2 + C1 * MaxProducedTemperature + C0
else:
CCAPP1 = 2231 - 2 * (MaxProducedTemperature - 150.)
x = np.max(model.surfaceplant.ElectricityProduced.value)
y = np.max(model.surfaceplant.ElectricityProduced.value)
if y == 0.0:
y = 15.0
z = math.pow(y / 15., -0.06)
self.Cplantcorrelation = CCAPP1 * z * x * 1000. / 1E6

elif model.surfaceplant.plant_type.value == PlantType.SUPER_CRITICAL_ORC:
MaxProducedTemperature = np.max(model.surfaceplant.TenteringPP.value)
if MaxProducedTemperature < 150.:
C3 = -1.458333E-3
C2 = 7.6875E-1
C1 = -1.347917E2
C0 = 1.0075E4
CCAPP1 = C3 * MaxProducedTemperature ** 3 + C2 * MaxProducedTemperature ** 2 + C1 * MaxProducedTemperature + C0
else:
CCAPP1 = 2231 - 2 * (MaxProducedTemperature - 150.)
# factor 1.1 to make supercritical 10% more expansive than subcritical
self.Cplantcorrelation = 1.1 * CCAPP1 * math.pow(
np.max(model.surfaceplant.ElectricityProduced.value) / 15., -0.06) * np.max(
model.surfaceplant.ElectricityProduced.value) * 1000. / 1E6

elif model.surfaceplant.plant_type.value == PlantType.SINGLE_FLASH:
if np.max(model.surfaceplant.ElectricityProduced.value) < 10.:
C2 = 4.8472E-2
C1 = -35.2186
C0 = 8.4474E3
D2 = 4.0604E-2
D1 = -29.3817
D0 = 6.9911E3
PLL = 5.
PRL = 10.
elif np.max(model.surfaceplant.ElectricityProduced.value) < 25.:
C2 = 4.0604E-2
C1 = -29.3817
C0 = 6.9911E3
D2 = 3.2773E-2
D1 = -23.5519
D0 = 5.5263E3
PLL = 10.
PRL = 25.
elif np.max(model.surfaceplant.ElectricityProduced.value) < 50.:
C2 = 3.2773E-2
C1 = -23.5519
C0 = 5.5263E3
D2 = 3.4716E-2
D1 = -23.8139
D0 = 5.1787E3
PLL = 25.
PRL = 50.
elif np.max(model.surfaceplant.ElectricityProduced.value) < 75.:
C2 = 3.4716E-2
C1 = -23.8139
C0 = 5.1787E3
D2 = 3.5271E-2
D1 = -24.3962
D0 = 5.1972E3
PLL = 50.
PRL = 75.
else:
C2 = 3.5271E-2
C1 = -24.3962
C0 = 5.1972E3
D2 = 3.3908E-2
D1 = -23.4890
D0 = 5.0238E3
PLL = 75.
PRL = 100.
maxProdTemp = np.max(model.surfaceplant.TenteringPP.value)
CCAPPLL = C2 * maxProdTemp ** 2 + C1 * maxProdTemp + C0
CCAPPRL = D2 * maxProdTemp ** 2 + D1 * maxProdTemp + D0
b = math.log(CCAPPRL / CCAPPLL) / math.log(PRL / PLL)
a = CCAPPRL / PRL ** b
# factor 0.75 to make double flash 25% more expansive than single flash
self.Cplantcorrelation = (0.8 * a * math.pow(np.max(model.surfaceplant.ElectricityProduced.value), b) *
np.max(model.surfaceplant.ElectricityProduced.value) * 1000. / 1E6)

elif model.surfaceplant.plant_type.value == PlantType.DOUBLE_FLASH:
if np.max(model.surfaceplant.ElectricityProduced.value) < 10.:
C2 = 4.8472E-2
C1 = -35.2186
C0 = 8.4474E3
D2 = 4.0604E-2
D1 = -29.3817
D0 = 6.9911E3
PLL = 5.
PRL = 10.
elif np.max(model.surfaceplant.ElectricityProduced.value) < 25.:
C2 = 4.0604E-2
C1 = -29.3817
C0 = 6.9911E3
D2 = 3.2773E-2
D1 = -23.5519
D0 = 5.5263E3
PLL = 10.
PRL = 25.
elif np.max(model.surfaceplant.ElectricityProduced.value) < 50.:
C2 = 3.2773E-2
C1 = -23.5519
C0 = 5.5263E3
D2 = 3.4716E-2
D1 = -23.8139
D0 = 5.1787E3
PLL = 25.
PRL = 50.
elif np.max(model.surfaceplant.ElectricityProduced.value) < 75.:
C2 = 3.4716E-2
C1 = -23.8139
C0 = 5.1787E3
D2 = 3.5271E-2
D1 = -24.3962
D0 = 5.1972E3
PLL = 50.
PRL = 75.
else:
C2 = 3.5271E-2
C1 = -24.3962
C0 = 5.1972E3
D2 = 3.3908E-2
D1 = -23.4890
D0 = 5.0238E3
PLL = 75.
PRL = 100.
maxProdTemp = np.max(model.surfaceplant.TenteringPP.value)
CCAPPLL = C2 * maxProdTemp ** 2 + C1 * maxProdTemp + C0
CCAPPRL = D2 * maxProdTemp ** 2 + D1 * maxProdTemp + D0
b = math.log(CCAPPRL / CCAPPLL) / math.log(PRL / PLL)
a = CCAPPRL / PRL ** b
self.Cplantcorrelation = (a * math.pow(np.max(model.surfaceplant.ElectricityProduced.value), b) *
np.max(model.surfaceplant.ElectricityProduced.value) * 1000. / 1E6)

if self.ccplantfixed.Valid:
self.Cplant.value = self.ccplantfixed.value
self.CAPEX_cost_electricity_plant = self.Cplant.value * self.CAPEX_heat_electricity_plant_ratio.value
self.CAPEX_cost_heat_plant = self.Cplant.value * (1.0 - self.CAPEX_heat_electricity_plant_ratio.value)
else:
# 1.02 to convert cost from 2012 to 2016 #factor 1.15 for 15% contingency and factor 1.10 to convert from 2016 to 2022
self.Cplant.value = self._indirect_cost_factor * 1.15 * self.ccplantadjfactor.value * self.Cplantcorrelation * 1.02 * 1.10
self.CAPEX_cost_electricity_plant = self.Cplant.value

# add direct-use plant cost of co-gen system to Cplant (only of no total Cplant was provided)
if not self.ccplantfixed.Valid: # 1.15 below for contingency
if model.surfaceplant.enduse_option.value in [EndUseOptions.COGENERATION_TOPPING_EXTRA_ELECTRICITY,
EndUseOptions.COGENERATION_TOPPING_EXTRA_HEAT]: # enduse_option = 3: cogen topping cycle
self.CAPEX_cost_heat_plant = self._indirect_cost_factor * 1.15 * self.ccplantadjfactor.value * 250E-6 * np.max(
model.surfaceplant.HeatProduced.value / model.surfaceplant.enduse_efficiency_factor.value) * 1000.
elif model.surfaceplant.enduse_option.value in [EndUseOptions.COGENERATION_BOTTOMING_EXTRA_HEAT,
EndUseOptions.COGENERATION_BOTTOMING_EXTRA_ELECTRICITY]: # enduse_option = 4: cogen bottoming cycle
self.CAPEX_cost_heat_plant = self._indirect_cost_factor * 1.15 * self.ccplantadjfactor.value * 250E-6 * np.max(
model.surfaceplant.HeatProduced.value / model.surfaceplant.enduse_efficiency_factor.value) * 1000.
elif model.surfaceplant.enduse_option.value in [EndUseOptions.COGENERATION_PARALLEL_EXTRA_ELECTRICITY,
EndUseOptions.COGENERATION_PARALLEL_EXTRA_HEAT]: # cogen parallel cycle
self.CAPEX_cost_heat_plant = self._indirect_cost_factor * 1.15 * self.ccplantadjfactor.value * 250E-6 * np.max(
model.surfaceplant.HeatProduced.value / model.surfaceplant.enduse_efficiency_factor.value) * 1000.

self.Cplant.value = self.Cplant.value + self.CAPEX_cost_heat_plant
if not self.CAPEX_heat_electricity_plant_ratio.Provided:
self.CAPEX_heat_electricity_plant_ratio.value = self.CAPEX_cost_electricity_plant/self.Cplant.value
self.calculate_field_gathering_costs(model)
self.calculate_plant_costs(model)

if not self.totalcapcost.Valid:
# exploration costs (same as in Geophires v1.2) (M$)
Expand Down
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