Merge pull request #16 from softwareengineerprogrammer/econo_cash_flow-4

Revenue & Cashflow Profile

Author: softwareengineerprogrammer

src/geophires_monte_carlo/MC_GeoPHIRES3.py

@@ -130,6 +130,12 @@ def work_package(pass_list: list):
             HipRaInputParameters(from_file_path=Path(tmp_input_file))
         )
         shutil.copyfile(result.output_file_path, tmp_output_file)
+    elif args.Code_File.endswith('HIP_RA_x.py'):
+        hip_ra_x_client: HipRaXClient = HipRaXClient()
+        result: HipRaResult = hip_ra_x_client.get_hip_ra_result(
+            HipRaInputParameters(from_file_path=Path(tmp_input_file))
+        )
+        shutil.copyfile(result.output_file_path, tmp_output_file)
     else:
         log.warning(
             f'Code file from args ({args.Code_File}) is not a known program, '
@@ -311,7 +317,7 @@ def main(command_line_args=None):
 
     args = []
     for _ in range(iterations):
-        args.append(pass_list)  # we need to make Iterations number of copies of this list fr the map
+        args.append(pass_list)  # we need to make Iterations number of copies of this list for the map
     args = tuple(args)  # convert to a tuple
 
     # Now run the executor with the map - that will run it Iterations number of times
@@ -335,6 +341,7 @@ def main(command_line_args=None):
             if len(line) > 3:
                 # FIXME TODO doesn't work for HIP RA results
                 line, sep, tail = line.partition(', (')  # strip off the Input Variable Values
+                line = line.replace('(', '').replace(')', '')  # strip off the ()
                 results.append([float(y) for y in line.split(',')])
         else:
             logger.warning(f'-9999.0 or space found in line {result_count!s}')

src/geophires_x/AGSWellBores.py

@@ -1054,7 +1054,7 @@ def Calculate(self, model: Model) -> None:
                     DowngoingPumpingPower, ppp2, dppw, ppwh = ProdPressureDropAndPumpingPowerUsingIndexes(
                         model, self.productionwellpumping.value,
                         self.usebuiltinppwellheadcorrelation,
-                        model.reserv.Trock.value, model.reserv.depth.value,
+                        model.reserv.Trock.value, model.reserv.InputDepth.value,
                         self.ppwellhead.value, self.PI.value,
                         self.prodwellflowrate.value, f3, vprod,
                         self.injwelldiam.value, self.nprod.value, model.surfaceplant.pump_efficiency.value,

src/geophires_x/CylindricalReservoir.py

@@ -6,7 +6,7 @@
 import numpy as np
 from pint.facets.plain import PlainQuantity
 
-from geophires_x.GeoPHIRESUtils import density_water_kg_per_m3, lithostatic_pressure_MPa, quantity
+from geophires_x.GeoPHIRESUtils import density_water_kg_per_m3, static_pressure_MPa, quantity
 
 from geophires_x.GeoPHIRESUtils import heat_capacity_water_J_per_kg_per_K
 import geophires_x.Model as Model
@@ -266,5 +266,5 @@ def lithostatic_pressure(self) -> PlainQuantity:
 
         Standard reservoir implementation uses depth but CylindricalReservoir sets depth to total drilled length
         """
-        return quantity(lithostatic_pressure_MPa(self.rhorock.quantity().to('kg/m**3').magnitude,
-                                                 self.InputDepth.quantity().to('m').magnitude), 'MPa')
+        return quantity(static_pressure_MPa(self.rhorock.quantity().to('kg/m**3').magnitude,
+                                            self.InputDepth.quantity().to('m').magnitude), 'MPa')

src/geophires_x/Economics.py

@@ -128,12 +128,6 @@ def __init__(self, model: Model):
             PreferredUnits=CurrencyFrequencyUnit.MDOLLARSPERYEAR,
             CurrentUnits=CurrencyFrequencyUnit.MDOLLARSPERYEAR
         )
-        self.ProjectPaybackPeriod = self.OutputParameterDict[self.ProjectPaybackPeriod.Name] = OutputParameter(
-            "Project Payback Period",
-            UnitType=Units.TIME,
-            PreferredUnits=TimeUnit.YEAR,
-            CurrentUnits=TimeUnit.YEAR
-        )
         self.AddOnPaybackPeriod = self.OutputParameterDict[self.AddOnPaybackPeriod.Name] = OutputParameter(
             "AddOn Payback Period",
             UnitType=Units.TIME,
@@ -348,19 +342,14 @@ def Calculate(self, model: Model) -> None:
             self.ProjectIRR.value = 0.0
         self.ProjectVIR.value = 1.0 + (self.ProjectNPV.value / self.AdjustedProjectCAPEX.value)
 
-        # calculate Cummcashflows and paybacks
+        # calculate Cummcashflows and payback period
         self.ProjectCummCashFlow.value = [0.0] * len(self.ProjectCashFlow.value)
         i = 0
         for val in self.ProjectCashFlow.value:
             if i == 0:
                 self.ProjectCummCashFlow.value[i] = val
             else:
                 self.ProjectCummCashFlow.value[i] = self.ProjectCummCashFlow.value[i - 1] + val
-                if self.ProjectCummCashFlow.value[i] > 0 >= self.ProjectCummCashFlow.value[
-                    i - 1]:  # we just crossed the threshold into positive project cummcashflow, so we can calculate payback period
-                    dFullDiff = self.ProjectCummCashFlow.value[i] + math.fabs(self.ProjectCummCashFlow.value[(i - 1)])
-                    dPerc = math.fabs(self.ProjectCummCashFlow.value[(i - 1)]) / dFullDiff
-                    self.ProjectPaybackPeriod.value = i + dPerc
             i = i + 1
         i = 0
         self.AddOnCummCashFlow.value = [0.0] * len(self.AddOnCashFlow.value)
@@ -382,7 +371,7 @@ def Calculate(self, model: Model) -> None:
                     self.AdjustedProjectOPEX.value * model.surfaceplant.plant_lifetime.value))
 
         # recalculate LCOE/LCOH
-        self.LCOE.value, self.LCOH.value, LCOC = Economics.CalculateLCOELCOH(self, model)
+        self.LCOE.value, self.LCOH.value, LCOC = Economics.CalculateLCOELCOHLCOC(self, model)
 
         model.logger.info(f'complete {str(__class__)}: {sys._getframe().f_code.co_name}')
 

src/geophires_x/EconomicsAddOns.py

@@ -226,12 +226,6 @@ def __init__(self, model):
             PreferredUnits=PercentUnit.TENTH,
             CurrentUnits=PercentUnit.TENTH
         )
-        self.ProjectPaybackPeriod = self.OutputParameterDict[self.ProjectPaybackPeriod.Name] = OutputParameter(
-            "Project Payback Period",
-            UnitType=Units.TIME,
-            PreferredUnits=TimeUnit.YEAR,
-            CurrentUnits=TimeUnit.YEAR
-        )
         self.ProjectMOIC = self.OutputParameterDict[self.ProjectMOIC.Name] = OutputParameter(
             "Project Multiple of Invested Capital",
             UnitType=Units.PERCENT,
@@ -429,11 +423,6 @@ def Calculate(self, model) -> None:
                 self.ProjectCummCashFlow.value[0] = val
             else:
                 self.ProjectCummCashFlow.value[i] = self.ProjectCummCashFlow.value[i - 1] + val
-                if self.ProjectCummCashFlow.value[i] > 0 >= self.ProjectCummCashFlow.value[
-                    i - 1]:  # we just crossed the threshold into positive project cummcashflow, so we can calculate payback period
-                    dFullDiff = self.ProjectCummCashFlow.value[i] + math.fabs(self.ProjectCummCashFlow.value[(i - 1)])
-                    dPerc = math.fabs(self.ProjectCummCashFlow.value[(i - 1)]) / dFullDiff
-                    self.ProjectPaybackPeriod.value = i + dPerc
             i = i + 1
 
         # Calculate more financial values using numpy financials

src/geophires_x/EconomicsCCUS.py

@@ -43,8 +43,8 @@ def __init__(self, model: Model):
         """
         model.logger.info("Init " + str(__class__) + ": " + sys._getframe().f_code.co_name)
 
-        # These disctionaries contains a list of all the parameters set in this object, stored as "Parameter" and
-        # OutputParameter Objects.  This will alow us later to access them in a user interface and get that list,
+        # These dictionaries contains a list of all the parameters set in this object, stored as "Parameter" and
+        # OutputParameter Objects.  This will allow us later to access them in a user interface and get that list,
         # along with unit type, preferred units, etc.
         self.ParameterDict = {}
         self.OutputParameterDict = {}
@@ -593,15 +593,18 @@ def Calculate(self, model: Model) -> None:
             print(err_message + "  Exiting....")
             sys.exit()
 
-        self.CRF = self.calculate_CRF(self.wacc.value,
-                                      model.surfaceplant.plant_lifetime.value)  # Calculate initial CRF value based on default inputs
-        CAPEX = self.CAPEX.value * self.CRF  # don't change a parameters value directly - it throw off the rehydration
+        # Calculate initial CRF value based on default inputs
+        self.CRF = self.calculate_CRF(self.wacc.value, model.surfaceplant.plant_lifetime.value)
+
+        # don't change a parameters value directly - it throw off the rehydration
+        CAPEX = self.CAPEX.value * self.CRF
         CAPEX = CAPEX * self.CAPEX_mult.value
         self.OPEX.value = self.OPEX.value * self.OPEX_mult.value
         self.therm.value = self.therm.value * self.therm_index.value
         power_totalcost = self.elec.value * model.surfaceplant.electricity_cost_to_buy.value
         elec_heat_totalcost = self.therm.value * model.surfaceplant.electricity_cost_to_buy.value
-        # Convert from $/McF to $/kWh_th, but don't change a parameters value directly - it will throw off the rehydration
+
+        # Convert from $/McF to $/kWh_th, but don't change any parameters value directly - it will throw off the rehydration
         NG_price = self.NG_price.value / self.NG_EnergyDensity.value
         NG_totalcost = self.therm.value * NG_price
         self.LCOH.value, self.kWh_e_per_kWh_th.value = self.geo_therm_cost(model.surfaceplant.electricity_cost_to_buy.value,
@@ -659,7 +662,8 @@ def Calculate(self, model: Model) -> None:
         # some (all) of it to do the capture, so when they get used in the final economic calculation (below),
         # the new values reflect the impact of S-DAC-GT
         for i in range(0, model.surfaceplant.plant_lifetime.value):
-            if model.surfaceplant.enduse_option.value != EndUseOptions.HEAT:  # all these end-use options have an electricity generation component
+            if model.surfaceplant.enduse_option.value != EndUseOptions.HEAT:
+                # all these end-use options have an electricity generation component
                 model.surfaceplant.TotalkWhProduced.value[i] = model.surfaceplant.TotalkWhProduced.value[i] - (
                     self.CarbonExtractedAnnually.value[i] * self.elec.value)
                 model.surfaceplant.NetkWhProduced.value[i] = model.surfaceplant.NetkWhProduced.value[i] - (
@@ -668,8 +672,18 @@ def Calculate(self, model: Model) -> None:
                     model.surfaceplant.HeatkWhProduced.value[i] = model.surfaceplant.HeatkWhProduced.value[i] - (
                         self.CarbonExtractedAnnually.value[i] * self.therm.value)
             else:
-                model.surfaceplant.HeatkWhProduced.value[i] = model.surfaceplant.HeatkWhProduced.value[i] - (
-                    self.CarbonExtractedAnnually.value[
-                        i] * self.therm.value)  # all the end-use option of direct-use only component
-
-        model.logger.info("complete " + str(__class__) + ": " + sys._getframe().f_code.co_name)
+                # all the end-use option of direct-use only component
+                model.surfaceplant.HeatkWhProduced.value[i] = (model.surfaceplant.HeatkWhProduced.value[i] -
+                                                               (self.CarbonExtractedAnnually.value[i] * self.therm.value))
+
+        # Build a revenue generation model for the carbon capture, assuming the capture is being sequestered and that
+        # there is some sort of credit involved for doing that sequestering
+        # note that there may already be values in the CarbonRevenue array, so we need to
+        # add to them, not just set them. If there isn't values, there, the array will be filed with zeros, so adding won't be a problem
+        #total_duration = model.surfaceplant.plant_lifetime.value
+        #for i in range(0, total_duration, 1):
+        #    model.sdacgteconomics.CarbonRevenue.value[i] = (model.sdacgteconomics.CarbonRevenue.value[i] +
+        #                                              (self.CarbonExtractedAnnually.value[i] * model.economics.CarbonPrice.value[i]))
+#            if i > 0:
+#                model.economics.CarbonCummCashFlow.value[i] = model.economics.CarbonCummCashFlow.value[i - 1] + model.economics.CarbonRevenue.value[i]
+        model.logger.info("Complete " + str(__class__) + ": " + sys._getframe().f_code.co_name)

src/geophires_x/EconomicsS_DAC_GT.py

@@ -0,0 +1,67 @@
+Reservoir Model,1,                        			---Multiple, Fractures, reservoir, model
+Reservoir Depth,3.7,                     				---[km]
+Number of Segments,3,                  				---[-]
+Gradient 1,42.69972,                          			---[deg.C/km]
+Gradient 2,51.66667,                          			---[deg.C/km]
+Thickness 1,0.793,                          			---[km]
+Gradient 3,46.9697,                          			---[deg.C/km]
+Thickness 2,1.646,                          			---[km]
+Maximum Temperature,400,                  			---[deg.C]
+Number of Production Wells,2,            			---[-]
+Number of Injection Wells,2,            			---[-]
+Production Well Diameter,7,		     			---[inch]
+Injection Well Diameter,7,					---[inch]
+Ramey Production Wellbore Model,1,       			---
+Production Wellbore Temperature Drop,.5,			---[deg.C]
+Injection Wellbore Temperature Gain,0,   			---[deg.C]
+Production Flow Rate per Well,90,       			---[kg/s]
+Fracture Shape,3,                       			---[-]
+Fracture Height,900, 						---[m]
+Reservoir Volume Option,3,              			---[-]
+Reservoir Volume,1000000000000,		 			---[m^3]
+Number of Fractures,20,		  				---[-]
+Water Loss Fraction,.02,					---[-]
+Productivity Index,5,						---[kg/s/bar]
+Injectivity Index,5,						---[kg/s/bar]
+Injection Temperature,40,		 			---[deg.C]
+Maximum Drawdown,0.3,			  			---[-] no redrilling considered
+Reservoir Heat Capacity,975,		  			---[J/kg/K]
+Reservoir Density,2600,			  			---[kg/m^3]
+Reservoir Thermal Conductivity,3,	  			---[W/m/K]
+
+***SURFACE TECHNICAL PARAMETERS***
+**********************************
+End-Use Option,1,			  			---[-] Electricity
+Economic Model,1,			  			---[-] Fixed Charge Rate Model
+Power Plant Type,2,			  			---[-] Supercritcal ORC
+Circulation Pump Efficiency,.8,	  				---[-] between .1 and 1
+Utilization Factor,.9,			  			---[-] between .1 and 1
+Surface Temperature,20,		  				---[deg.C]
+Ambient Temperature,20,		 				---[deg.C]
+
+***FINANCIAL PARAMETERS***
+**************************
+Plant Lifetime,30,			  			---[years]
+Fixed Charge Rate,.05,			 			---[-] between 0 and 1
+
+Inflation Rate During Construction,0,   			---[-]
+
+Starting Electricity Sale Price, 0.10
+
+Ending Electricity Sale Price, 0.15
+
+Electricity Escalation Start Year, 5
+
+Electricity Escalation Rate Per Year, 0.01
+
+***Simulation Parameters***
+***************************
+
+Print Output to Console,1,		  			---[-] Should be 0 (don't print results) or 1 (print results)
+Time steps per year,6,		  				---[1/year]
+
+***Output unit conversions you wish to make***
+***************************
+Units:Bottom-hole temperature, degF,  ---[This is what I want the units to be for this output parameter
+Units:Exploration cost,MEUR,  ---[This is what I want the units to be for this output parameter
+Units:O&M Make-up Water costs, MEUR/yr

src/geophires_x/Examples/Border_EGS_150C_Electricity_Input.txt

@@ -53,10 +53,6 @@ def main(enable_geophires_logging_config=True):
         json_addons = jsons.dumps(model.addeconomics.OutputParameterDict, indent=4, sort_keys=True,
                                   supress_warnings=True)
         json_merged = {**json_merged, **json.loads(json_addons)}
-    if model.economics.DoCCUSCalculations.value:
-        json_ccus = jsons.dumps(model.ccuseconomics.OutputParameterDict, indent=4, sort_keys=True,
-                                supress_warnings=True)
-        json_merged = {**json_merged, **json.loads(json_ccus)}
     if model.economics.DoSDACGTCalculations.value:
         json_sdacgt = jsons.dumps(model.sdacgteconomics.OutputParameterDict, indent=4, sort_keys=True,
                                   supress_warnings=True)