Merge pull request #199 from NREL/develop

CHP class size, financial input output bugs

CHANGELOG.md

@@ -22,6 +22,18 @@ Classify the change according to the following categories:
     ### Fixed
     ### Deprecated
     ### Removed
+
+
+## v0.28
+### Changed 
+- Changed Financial **breakeven_cost_of_emissions_reduction_per_tonnes_CO2** to **breakeven_cost_of_emissions_reduction_per_tonne_CO2**
+- Changed `CHP.size_class` to start at 0 instead of 1, consistent with the API, and 0 represents the average of all `size_class`s
+- Change `CHP.max_kw` to be based on either the heuristic sizing from average heating load (if heating) or peak electric load (if no heating, aka Prime Generator in the UI)
+  - The "big_number" for `max_kw` was causing the model to take forever to solve and some erroneous behavior; this is also consistent with the API to limit max_kw to a reasonable number
+### Added 
+- Added previously missing Financial BAU outputs: **lifecycle_om_costs_before_tax**, **lifecycle_om_costs_after_tax**, **year_one_om_costs_before_tax**
+### Fixed
+- Fixed if statement to determing ElectricLoad "year" from && to ||, so that defaults to 2017 if any CRB input is used
 
 ## v0.27.0
 ### Added

Project.toml

@@ -1,7 +1,7 @@
 name = "REopt"
 uuid = "d36ad4e8-d74a-4f7a-ace1-eaea049febf6"
 authors = ["Nick Laws", "Hallie Dunham <[email protected]>", "Bill Becker <[email protected]>", "Bhavesh Rathod <[email protected]>", "Alex Zolan <[email protected]>", "Amanda Farthing <[email protected]>"]
-version = "0.27.0"
+version = "0.28.0"
 
 [deps]
 ArchGDAL = "c9ce4bd3-c3d5-55b8-8973-c0e20141b8c3"

src/core/electric_load.jl

@@ -35,7 +35,7 @@
     doe_reference_name::String = "",
     blended_doe_reference_names::Array{String, 1} = String[],
     blended_doe_reference_percents::Array{<:Real,1} = Real[],
-    year::Int = doe_reference_name ≠ nothing && blended_doe_reference_names ≠ nothing ? 2017 : 2022, # used in ElectricTariff to align rate schedule with weekdays/weekends. DOE CRB profiles must use 2017. If providing load data, specify year of data.
+    year::Int = doe_reference_name ≠ "" || blended_doe_reference_names ≠ String[] ? 2017 : 2022, # used in ElectricTariff to align rate schedule with weekdays/weekends. DOE CRB profiles must use 2017. If providing load data, specify year of data.
     city::String = "",
     annual_kwh::Union{Real, Nothing} = nothing,
     monthly_totals_kwh::Array{<:Real,1} = Real[],
@@ -117,7 +117,7 @@ mutable struct ElectricLoad  # mutable to adjust (critical_)loads_kw based off o
         doe_reference_name::String = "",
         blended_doe_reference_names::Array{String, 1} = String[],
         blended_doe_reference_percents::Array{<:Real,1} = Real[],
-        year::Int = doe_reference_name ≠ "" && blended_doe_reference_names ≠ String[] ? 2017 : 2022, # used in ElectricTariff to align rate schedule with weekdays/weekends. DOE CRB profiles must use 2017. If providing load data, specify year of data.
+        year::Int = doe_reference_name ≠ "" || blended_doe_reference_names ≠ String[] ? 2017 : 2022, # used in ElectricTariff to align rate schedule with weekdays/weekends. DOE CRB profiles must use 2017. If providing load data, specify year of data.
         city::String = "",
         annual_kwh::Union{Real, Nothing} = nothing,
         monthly_totals_kwh::Array{<:Real,1} = Real[],

src/core/scenario.jl

@@ -320,6 +320,8 @@ function Scenario(d::Dict; flex_hvac_from_json=false)
         boiler_inputs[:time_steps_per_hour] = settings.time_steps_per_hour
         if haskey(d, "ExistingBoiler")
             boiler_inputs = merge(boiler_inputs, dictkeys_tosymbols(d["ExistingBoiler"]))
+        else
+            throw(@error("Must include ExistingBoiler input with at least fuel_cost_per_mmbtu if modeling heating load"))
         end
         existing_boiler = ExistingBoiler(; boiler_inputs...)
     end
@@ -342,9 +344,11 @@ function Scenario(d::Dict; flex_hvac_from_json=false)
             avg_boiler_fuel_load_mmbtu_per_hour = sum(total_fuel_heating_load_mmbtu_per_hour) / length(total_fuel_heating_load_mmbtu_per_hour)
             chp = CHP(d["CHP"]; 
                     avg_boiler_fuel_load_mmbtu_per_hour = avg_boiler_fuel_load_mmbtu_per_hour,
-                    existing_boiler = existing_boiler)
+                    existing_boiler = existing_boiler,
+                    electric_load_series_kw = electric_load.loads_kw)
         else # Only if modeling CHP without heating_load and existing_boiler (for electric-only CHP)
-            chp = CHP(d["CHP"])
+            chp = CHP(d["CHP"],
+                    electric_load_series_kw = electric_load.loads_kw)
         end
         chp_prime_mover = chp.prime_mover
     end

src/core/steam_turbine.jl

@@ -143,7 +143,8 @@ function get_steam_turbine_defaults(size_class::Int, defaults_all::Dict)
     steam_turbine_defaults = Dict{String, Any}()
 
     for key in keys(defaults_all)
-        steam_turbine_defaults[key] = defaults_all[key][size_class]
+        # size_class is zero-based index so plus-1 for indexing Julia one-based indexed arrays
+        steam_turbine_defaults[key] = defaults_all[key][size_class+1]
     end
     defaults_all = nothing
 
@@ -227,11 +228,10 @@ function get_steam_turbine_defaults_size_class(;avg_boiler_fuel_load_mmbtu_per_h
     class_bounds = [(0.0, 25000.0), (0, 1000.0), (1000.0, 5000.0), (5000.0, 25000.0)]
     n_classes = length(class_bounds)
     if !isnothing(size_class)
-        if size_class < 1 || size_class > n_classes
-            throw(@error("Invalid size_class given for steam_turbine, must be in [1,2,3,4]"))
+        if size_class < 0 || size_class > (n_classes-1)
+            throw(@error("Invalid size_class $size_class given for steam_turbine, must be in [0,1,2,3]"))
         end
-    end
-    if !isnothing(avg_boiler_fuel_load_mmbtu_per_hour)
+    elseif !isnothing(avg_boiler_fuel_load_mmbtu_per_hour)
         if avg_boiler_fuel_load_mmbtu_per_hour <= 0
             throw(@error("avg_boiler_fuel_load_mmbtu_per_hour must be > 0.0 MMBtu/hr"))
         end
@@ -241,21 +241,22 @@ function get_steam_turbine_defaults_size_class(;avg_boiler_fuel_load_mmbtu_per_h
         # With heuristic size, find the suggested size class
         if st_elec_size_heuristic_kw < class_bounds[2][2]
             # If smaller than the upper bound of the smallest class, assign the smallest class
-            size_class = 2
+            size_class = 1
         elseif st_elec_size_heuristic_kw >= class_bounds[n_classes][1]
             # If larger than or equal to the lower bound of the largest class, assign the largest class
-            size_class = n_classes  # Size classes are zero-indexed
+            size_class = n_classes - 1  # Size classes are zero-indexed
         else
             # For middle size classes
-            for sc in 2:(n_classes-1)
+            for sc in 3:(n_classes-1)
                 if st_elec_size_heuristic_kw >= class_bounds[sc][1] &&
                     st_elec_size_heuristic_kw < class_bounds[sc][2]
-                    size_class = sc
+                    size_class = sc - 1
+                    break
                 end
             end
         end
     else
-        size_class = 1
+        size_class = 0
         st_elec_size_heuristic_kw = nothing
     end
 

src/results/financial.jl

@@ -32,7 +32,7 @@
 - `lcc` Optimal lifecycle cost
 - `lifecycle_generation_tech_capital_costs` LCC component. Net capital costs for all generation technologies, in present value, including replacement costs and incentives. This value does not include offgrid_other_capital_costs.
 - `lifecycle_storage_capital_costs` LCC component. Net capital costs for all storage technologies, in present value, including replacement costs and incentives. This value does not include offgrid_other_capital_costs.
-- `lifecycle_om_costs_after_tax` LCC component. Present value of all O&M costs, after tax.
+- `lifecycle_om_costs_after_tax` LCC component. Present value of all O&M costs, after tax. (does not include fuel costs)
 - `lifecycle_fuel_costs_after_tax` LCC component. Present value of all fuel costs over the analysis period, after tax.
 - `lifecycle_chp_standby_cost_after_tax` LCC component. Present value of all CHP standby charges, after tax.
 - `lifecycle_elecbill_after_tax` LCC component. Present value of all electric utility charges, after tax. 
@@ -57,7 +57,7 @@
 - `lifecycle_emissions_cost_health` LCC component if Settings input include_health_in_objective is true. Present value of NOx, SO2, and PM2.5 emissions cost over the analysis period.
 
 calculated in combine_results function if BAU scenario is run:
-- `breakeven_cost_of_emissions_reduction_per_tonnes_CO2`
+- `breakeven_cost_of_emissions_reduction_per_tonne_CO2`
 
 !!! note "'Series' and 'Annual' energy outputs are average annual"
 	REopt performs load balances using average annual production values for technologies that include degradation. 

src/results/results.jl

@@ -142,6 +142,9 @@ function combine_results(p::REoptInputs, bau::Dict, opt::Dict, bau_scenario::BAU
         ("Financial", "lcc"),
         ("Financial", "lifecycle_emissions_cost_climate"),
         ("Financial", "lifecycle_emissions_cost_health"),
+        ("Financial", "lifecycle_om_costs_before_tax"),
+        ("Financial", "lifecycle_om_costs_after_tax"),
+        ("Financial", "year_one_om_costs_before_tax"),
         ("ElectricTariff", "year_one_energy_cost_before_tax"),
         ("ElectricTariff", "year_one_demand_cost_before_tax"),
         ("ElectricTariff", "year_one_fixed_cost_before_tax"),
@@ -221,7 +224,6 @@ function combine_results(p::REoptInputs, bau::Dict, opt::Dict, bau_scenario::BAU
             end
         end
     end
-    opt["Financial"]["lifecycle_om_costs_before_tax_bau"] = bau["Financial"]["lifecycle_om_costs_before_tax"]
     opt["Financial"]["npv"] = round(opt["Financial"]["lcc_bau"] - opt["Financial"]["lcc"], digits=2)
 
     opt["ElectricLoad"]["bau_critical_load_met"] = bau_scenario.outage_outputs.bau_critical_load_met
@@ -247,7 +249,7 @@ function combine_results(p::REoptInputs, bau::Dict, opt::Dict, bau_scenario::BAU
             bau["Site"]["annual_emissions_from_fuelburn_tonnes_CO2"] - opt["Site"]["annual_emissions_from_fuelburn_tonnes_CO2"] 
         )
         if breakeven_cost_denominator != 0.0
-            opt["Financial"]["breakeven_cost_of_emissions_reduction_per_tonnes_CO2"] = -1 * npv_without_modeled_climate_costs / breakeven_cost_denominator
+            opt["Financial"]["breakeven_cost_of_emissions_reduction_per_tonne_CO2"] = -1 * npv_without_modeled_climate_costs / breakeven_cost_denominator
         end
     end
 

test/scenarios/re_emissions_with_thermal.json

@@ -91,7 +91,7 @@
   },
   "CHP": {
     "prime_mover": "recip_engine",
-    "size_class": 3,
+    "size_class": 2,
     "min_kw": 200.0,
     "min_allowable_kw":0.0,
     "max_kw": 200.0,
@@ -104,4 +104,4 @@
     "min_gal": 50000.0,
     "max_gal": 50000.0
   }
-}
+}

test/test_with_xpress.jl

@@ -85,7 +85,7 @@ end
         data_cost_curve = JSON.parsefile("./scenarios/chp_sizing.json")
         data_cost_curve["CHP"] = Dict()
         data_cost_curve["CHP"]["prime_mover"] = "recip_engine"
-        data_cost_curve["CHP"]["size_class"] = 2
+        data_cost_curve["CHP"]["size_class"] = 1
         data_cost_curve["CHP"]["fuel_cost_per_mmbtu"] = 8.0
         data_cost_curve["CHP"]["min_kw"] = 0
         data_cost_curve["CHP"]["min_allowable_kw"] = 555.5
@@ -876,7 +876,7 @@ end
     total_chiller_electric_consumption = sum(inputs.s.cooling_load.loads_kw_thermal) / inputs.s.existing_chiller.cop
     @test round(total_chiller_electric_consumption, digits=0) ≈ 320544.0 atol=1.0  # loads_kw is **electric**, loads_kw_thermal is **thermal**
 
-    #Test CHP defaults use average fuel load, size class 3 for recip_engine 
+    #Test CHP defaults use average fuel load, size class 2 for recip_engine 
     @test inputs.s.chp.min_allowable_kw ≈ 50.0 atol=0.01
     @test inputs.s.chp.om_cost_per_kwh ≈ 0.0225 atol=0.0001
 
@@ -893,18 +893,23 @@ end
     @test round(total_chiller_electric_consumption, digits=0) ≈ round(expected_cooling_electricity) atol=1.0
     @test round(total_chiller_electric_consumption, digits=0) ≈ 3876410 atol=1.0
 
+    # Check that without heating load or max_kw input, CHP.max_kw gets set based on peak electric load
+    @test inputs.s.chp.max_kw ≈ maximum(inputs.s.electric_load.loads_kw) atol=0.01
+
     input_data["SpaceHeatingLoad"] = Dict{Any, Any}("monthly_mmbtu" => repeat([500.0], 12))
     input_data["DomesticHotWaterLoad"] = Dict{Any, Any}("monthly_mmbtu" => repeat([500.0], 12))
     input_data["CoolingLoad"] = Dict{Any, Any}("monthly_fractions_of_electric_load" => repeat([0.1], 12))
 
     s = Scenario(input_data)
     inputs = REoptInputs(s)
-    #Test CHP defaults use average fuel load, size class changes to 4
+    #Test CHP defaults use average fuel load, size class changes to 3
     @test inputs.s.chp.min_allowable_kw ≈ 315.0 atol=0.1
     @test inputs.s.chp.om_cost_per_kwh ≈ 0.02 atol=0.0001
     #Update CHP prime_mover and test new defaults
     input_data["CHP"]["prime_mover"] = "combustion_turbine"
-    input_data["CHP"]["size_class"] = 2
+    input_data["CHP"]["size_class"] = 1
+    # Set max_kw higher than peak electric load so min_allowable_kw doesn't get assigned to max_kw
+    input_data["CHP"]["max_kw"] = 1000.0
 
     s = Scenario(input_data)
     inputs = REoptInputs(s)
@@ -1283,8 +1288,8 @@ end
         yr1_grid_emissions_tonnes_CO2_out = results["ElectricUtility"]["annual_emissions_tonnes_CO2"]
         yr1_total_emissions_calced_tonnes_CO2 = yr1_fuel_emissions_tonnes_CO2_out + yr1_grid_emissions_tonnes_CO2_out 
         @test annual_emissions_tonnes_CO2_out ≈ yr1_total_emissions_calced_tonnes_CO2 atol=1e-1
-        if haskey(results["Financial"],"breakeven_cost_of_emissions_reduction_per_tonnes_CO2")
-            @test results["Financial"]["breakeven_cost_of_emissions_reduction_per_tonnes_CO2"] >= 0.0
+        if haskey(results["Financial"],"breakeven_cost_of_emissions_reduction_per_tonne_CO2")
+            @test results["Financial"]["breakeven_cost_of_emissions_reduction_per_tonne_CO2"] >= 0.0
         end
 
         if i == 1
@@ -1300,7 +1305,7 @@ end
             @test results["Site"]["total_renewable_energy_fraction"] ≈ 0.8
             @test results["Site"]["total_renewable_energy_fraction_bau"] ≈ 0.14495 atol=1e-4
             @test results["Site"]["lifecycle_emissions_reduction_CO2_fraction"] ≈ 0.61865 atol=1e-4
-            @test results["Financial"]["breakeven_cost_of_emissions_reduction_per_tonnes_CO2"] ≈ 283.5 atol=1
+            @test results["Financial"]["breakeven_cost_of_emissions_reduction_per_tonne_CO2"] ≈ 283.5 atol=1
             @test results["Site"]["annual_emissions_tonnes_CO2"] ≈ 11.36 atol=1e-2
             @test results["Site"]["annual_emissions_tonnes_CO2_bau"] ≈ 32.16 atol=1e-2
             @test results["Site"]["annual_emissions_from_fuelburn_tonnes_CO2"] ≈ 6.96
@@ -1334,7 +1339,7 @@ end
             @test results["Site"]["total_renewable_energy_fraction_bau"] ≈ 0.1365 atol=1e-3 # 0.1354 atol=1e-3
             # CO2 emissions - totals ≈  from grid, from fuelburn, ER, $/tCO2 breakeven
             @test results["Site"]["lifecycle_emissions_reduction_CO2_fraction"] ≈ 0.8 atol=1e-3 # 0.8
-            @test results["Financial"]["breakeven_cost_of_emissions_reduction_per_tonnes_CO2"] ≈ 351.24 atol=1e-1
+            @test results["Financial"]["breakeven_cost_of_emissions_reduction_per_tonne_CO2"] ≈ 351.24 atol=1e-1
             @test results["Site"]["annual_emissions_tonnes_CO2"] ≈ 14.2 atol=1
             @test results["Site"]["annual_emissions_tonnes_CO2_bau"] ≈ 70.99 atol=1
             @test results["Site"]["annual_emissions_from_fuelburn_tonnes_CO2"] ≈ 0.0 atol=1 # 0.0
@@ -1357,13 +1362,13 @@ end
             inputs["ElectricStorage"]["max_kw"] = results["ElectricStorage"]["size_kw"]
             inputs["ElectricStorage"]["min_kwh"] = results["ElectricStorage"]["size_kwh"]
             inputs["ElectricStorage"]["max_kwh"] = results["ElectricStorage"]["size_kwh"]
-            inputs["Financial"]["CO2_cost_per_tonne"] = results["Financial"]["breakeven_cost_of_emissions_reduction_per_tonnes_CO2"]
+            inputs["Financial"]["CO2_cost_per_tonne"] = results["Financial"]["breakeven_cost_of_emissions_reduction_per_tonne_CO2"]
             inputs["Settings"]["include_climate_in_objective"] = true
             m1 = Model(optimizer_with_attributes(Xpress.Optimizer, "OUTPUTLOG" => 0))
             m2 = Model(optimizer_with_attributes(Xpress.Optimizer, "OUTPUTLOG" => 0))
             results = run_reopt([m1, m2], inputs)
             @test results["Financial"]["npv"]/expected_npv ≈ 0 atol=1e-3
-            @test results["Financial"]["breakeven_cost_of_emissions_reduction_per_tonnes_CO2"] ≈ inputs["Financial"]["CO2_cost_per_tonne"] atol=1e-1
+            @test results["Financial"]["breakeven_cost_of_emissions_reduction_per_tonne_CO2"] ≈ inputs["Financial"]["CO2_cost_per_tonne"] atol=1e-1
         elseif i == 3
             @test results["PV"]["size_kw"] ≈ 20.0 atol=1e-1
             @test !haskey(results, "Wind")
@@ -1484,7 +1489,7 @@ end
     # Add CHP 
     input_data["CHP"] = Dict{Any, Any}([
                         ("prime_mover", "recip_engine"),
-                        ("size_class", 2),
+                        ("size_class", 1),
                         ("min_kw", 250.0),
                         ("min_allowable_kw", 0.0),
                         ("max_kw", 250.0),