Add MacroEnergySystemsScaling.jl

Project.toml

@@ -15,6 +15,7 @@ HiGHS = "87dc4568-4c63-4d18-b0c0-bb2238e4078b"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
+MacroEnergySystemsScaling = "e07ba8b4-499e-4f54-a885-af58260c741f"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"

docs/src/Tutorials/Tutorial_1_configuring_settings.md

@@ -35,7 +35,6 @@ genx_settings_SNE = YAML.load(open("example_systems/1_three_zones/settings/genx_
     Dict{Any, Any} with 19 entries:
       "NetworkExpansion"                        => 1
       "ModelingToGenerateAlternativeIterations" => 3
-      "ParameterScale"                          => 1
       "EnergyShareRequirement"                  => 0
       "PrintModel"                              => 0
       "TimeDomainReduction"                     => 1

docs/src/Tutorials/Tutorial_3_K-means_time_domain_reduction.md

@@ -97,7 +97,6 @@ genx_settings_TZ = YAML.load(open((joinpath(case,"settings/genx_settings.yml")))
     Dict{Any, Any} with 19 entries:
       "NetworkExpansion"                        => 1
       "ModelingToGenerateAlternativeIterations" => 3
-      "ParameterScale"                          => 1
       "EnergyShareRequirement"                  => 0
       "PrintModel"                              => 0
       "TimeDomainReduction"                     => 1
@@ -129,7 +128,6 @@ genx_settings_TZ ## Output settings
 ```
     Dict{Any, Any} with 13 entries:
     "NetworkExpansion"       => 1
-    "ParameterScale"         => 1
     "EnergyShareRequirement" => 0
     "TimeDomainReduction"    => 0
     "Trans_Loss_Segments"    => 1

docs/src/Tutorials/Tutorial_4_model_generation.md

@@ -193,7 +193,6 @@ setup = GenX.configure_settings(genx_settings,writeoutput_settings) # Combines g
       "CO2Cap"                                  => 2
       "WriteShadowPrices"                       => 1
       "ModelingToGenerateAlternativeIterations" => 3
-      "ParameterScale"                          => 1
       "EnergyShareRequirement"                  => 1
       "PrintModel"                              => 0
       "TimeDomainReduction"                     => 1

docs/src/Tutorials/Tutorial_7_setup.md

@@ -65,7 +65,6 @@ setup = GenX.configure_settings(genx_settings,writeoutput_settings)
       "CO2Cap"                             => 2
       "WriteShadowPrices"                  => 1
       "OperationalReserves"                => 0
-      "ParameterScale"                     => 1
       "EnergyShareRequirement"             => 0
       "PrintModel"                         => 0
       "TimeDomainReduction"                => 1

docs/src/User_Guide/model_configuration.md

@@ -42,7 +42,7 @@ The following tables summarize the model settings parameters and their default/p
 
 |**Parameter** | **Description**|
 | :------------ | :-----------|
-|ParameterScale | Flag to turn on parameter scaling wherein demand, capacity and power variables defined in GW rather than MW. This flag aides in improving the computational performance of the model. |
+|AutoScaling | Flag to turn on constraint scaling wherein demand. This feature usually aides in improving the computational performance of the model. It does not affect the units of the inputs or results. The scaling can be adjusted by using the additional settings detailed [here](https://macroenergy.github.io/MacroEnergySystemsScaling.jl/stable/scaling_settings/)|
 ||1 = Scaling is activated. |
 ||0 = Scaling is not activated. |
 |ObjScale| Parameter value to scale the objective function during optimization.|

example_systems/1_three_zones/settings/genx_settings.yml

@@ -6,8 +6,8 @@ CO2Cap: 2 # CO2 emissions cap; 0 = not active (no CO2 emission limit); 1 = mass-
 StorageLosses: 1 # Energy Share Requirement and CO2 constraints account for energy lost; 0 = not active (DO NOT account for energy lost); 1 = active systemwide (DO account for energy lost)
 MinCapReq: 1  # Activate minimum technology carveout constraints; 0 = not active; 1 = active
 MaxCapReq: 0  # Activate maximum technology carveout constraints; 0 = not active; 1 = active
-ParameterScale: 1 # Turn on parameter scaling wherein demand, capacity and power variables are defined in GW rather than MW. 0 = not active; 1 = active systemwide
 WriteShadowPrices: 1 # Write shadow prices of LP or relaxed MILP; 0 = not active; 1 = active
 UCommit: 2 # Unit committment of thermal power plants; 0 = not active; 1 = active using integer clestering; 2 = active using linearized clustering
 TimeDomainReduction: 1 # Time domain reduce (i.e. cluster) inputs based on Demand_data.csv, Generators_variability.csv, and Fuels_data.csv; 0 = not active (use input data as provided); 0 = active (cluster input data, or use data that has already been clustered)
-OutputFullTimeSeries: 1
+OutputFullTimeSeries: 1
+AutoScaling : 1

example_systems/2_three_zones_w_electrolyzer/settings/genx_settings.yml

@@ -2,7 +2,6 @@ Trans_Loss_Segments: 1 # Number of segments used in piecewise linear approximati
 UCommit: 2 # Unit committment of thermal power plants; 0 = not active; 1 = active using integer clestering; 2 = active using linearized clustering
 StorageLosses: 1 # Energy Share Requirement and CO2 constraints account for energy lost; 0 = not active (DO NOT account for energy lost); 1 = active systemwide (DO account for energy lost)
 HydrogenHourlyMatching: 1 # Hydrogen electrolyzer contribution to hourly supply matching required
-ParameterScale: 1 # Turn on parameter scaling wherein demand, capacity and power variables are defined in GW rather than MW. 0 = not active; 1 = active systemwide
 TimeDomainReduction: 1 # Time domain reduce (i.e. cluster) inputs based on Demand_data.csv, Generators_variability.csv, and Fuels_data.csv; 0 = not active (use input data as provided); 0 = active (cluster input data, or use data that has already been clustered)
 WriteShadowPrices: 1 # Write shadow prices of LP or relaxed MILP; 0 = not active; 1 = active
 HydrogenMinimumProduction: 1 # Hydrogen production requirement; 0 = not active; 1 = active, meet regional level H2 production requirements

example_systems/3_three_zones_w_co2_capture/settings/genx_settings.yml

@@ -6,7 +6,6 @@ CO2Cap: 2 # CO2 emissions cap; 0 = not active (no CO2 emission limit); 1 = mass-
 StorageLosses: 1 # Energy Share Requirement and CO2 constraints account for energy lost; 0 = not active (DO NOT account for energy lost); 1 = active systemwide (DO account for energy lost)
 MinCapReq: 1  # Activate minimum technology carveout constraints; 0 = not active; 1 = active
 MaxCapReq: 0  # Activate maximum technology carveout constraints; 0 = not active; 1 = active
-ParameterScale: 1 # Turn on parameter scaling wherein demand, capacity and power variables are defined in GW rather than MW. 0 = not active; 1 = active systemwide
 WriteShadowPrices: 1 # Write shadow prices of LP or relaxed MILP; 0 = not active; 1 = active
 UCommit: 2 # Unit committment of thermal power plants; 0 = not active; 1 = active using integer clestering; 2 = active using linearized clustering
 TimeDomainReduction: 1 # Time domain reduce (i.e. cluster) inputs based on Demand_data.csv, Generators_variability.csv, and Fuels_data.csv; 0 = not active (use input data as provided); 0 = active (cluster input data, or use data that has already been clustered) 

example_systems/4_three_zones_w_policies_slack/settings/genx_settings.yml

@@ -6,7 +6,6 @@ CO2Cap: 2 # CO2 emissions cap; 0 = not active (no CO2 emission limit); 1 = mass-
 StorageLosses: 1 # Energy Share Requirement and CO2 constraints account for energy lost; 0 = not active (DO NOT account for energy lost); 1 = active systemwide (DO account for energy lost)
 MinCapReq: 1  # Activate minimum technology carveout constraints; 0 = not active; 1 = active
 MaxCapReq: 1  # Activate maximum technology carveout constraints; 0 = not active; 1 = active
-ParameterScale: 1 # Turn on parameter scaling wherein demand, capacity and power variables are defined in GW rather than MW. 0 = not active; 1 = active systemwide
 WriteShadowPrices: 1 # Write shadow prices of LP or relaxed MILP; 0 = not active; 1 = active
 UCommit: 2 # Unit committment of thermal power plants; 0 = not active; 1 = active using integer clestering; 2 = active using linearized clustering
 TimeDomainReduction: 1 # Time domain reduce (i.e. cluster) inputs based on Demand_data.csv, Generators_variability.csv, and Fuels_data.csv; 0 = not active (use input data as provided); 0 = active (cluster input data, or use data that has already been clustered)

example_systems/5_three_zones_w_piecewise_fuel/settings/genx_settings.yml

@@ -7,7 +7,6 @@ CO2Cap: 2 # CO2 emissions cap; 0 = not active (no CO2 emission limit); 1 = mass-
 StorageLosses: 1 # Energy Share Requirement and CO2 constraints account for energy lost; 0 = not active (DO NOT account for energy lost); 1 = active systemwide (DO account for energy lost)
 MinCapReq: 1  # Activate minimum technology carveout constraints; 0 = not active; 1 = active
 MaxCapReq: 0  # Activate maximum technology carveout constraints; 0 = not active; 1 = active
-ParameterScale: 1 # Turn on parameter scaling wherein demand, capacity and power variables are defined in GW rather than MW. 0 = not active; 1 = active systemwide
 WriteShadowPrices: 1 # Write shadow prices of LP or relaxed MILP; 0 = not active; 1 = active
 UCommit: 2 # Unit committment of thermal power plants; 0 = not active; 1 = active using integer clestering; 2 = active using linearized clustering
 TimeDomainReduction: 1 # Time domain reduce (i.e. cluster) inputs based on Demand_data.csv, Generators_variability.csv, and Fuels_data.csv; 0 = not active (use input data as provided); 0 = active (cluster input data, or use data that has already been clustered)

example_systems/6_three_zones_w_multistage/settings/genx_settings.yml

@@ -6,7 +6,6 @@ CO2Cap: 2 # CO2 emissions cap; 0 = not active (no CO2 emission limit); 1 = mass-
 StorageLosses: 1 # Energy Share Requirement and CO2 constraints account for energy lost; 0 = not active (DO NOT account for energy lost); 1 = active systemwide (DO account for energy lost)
 MinCapReq: 0  # Activate minimum technology carveout constraints; 0 = not active; 1 = active
 MaxCapReq: 0  # Activate maximum technology carveout constraints; 0 = not active; 1 = active
-ParameterScale: 1 # Turn on parameter scaling wherein demand, capacity and power variables are defined in GW rather than MW. 0 = not active; 1 = active systemwide
 UCommit: 2 # Unit committment of thermal power plants; 0 = not active; 1 = active using integer clestering; 2 = active using linearized clustering
 TimeDomainReduction: 1 # Time domain reduce (i.e. cluster) inputs based on Demand_data.csv, Generators_variability.csv, and Fuels_data.csv; 0 = not active (use input data as provided); 0 = active (cluster input data, or use data that has already been clustered)
 MultiStage: 1 # 0 = Single-stage GenX, 1 = Multi-stage GenX

example_systems/7_three_zones_w_colocated_VRE_storage/settings/genx_settings.yml

@@ -1,4 +1,3 @@
-ParameterScale: 1
 NetworkExpansion: 1
 Trans_Loss_Segments: 1
 UCommit: 2

example_systems/8_three_zones_w_colocated_VRE_storage_electrolyzers/settings/genx_settings.yml

@@ -2,7 +2,6 @@ Trans_Loss_Segments: 1 # Number of segments used in piecewise linear approximati
 UCommit: 2 # Unit committment of thermal power plants; 0 = not active; 1 = active using integer clestering; 2 = active using linearized clustering
 StorageLosses: 1 # Energy Share Requirement and CO2 constraints account for energy lost; 0 = not active (DO NOT account for energy lost); 1 = active systemwide (DO account for energy lost)
 HydrogenHourlyMatching: 0 # Hydrogen electrolyzer hourly supply matching required
-ParameterScale: 0 # Turn on parameter scaling wherein demand, capacity and power variables are defined in GW rather than MW. 0 = not active; 1 = active systemwide
 TimeDomainReduction: 0 # Time domain reduce (i.e. cluster) inputs based on Demand_data.csv, Generators_variability.csv, and Fuels_data.csv; 0 = not active (use input data as provided); 0 = active (cluster input data, or use data that has already been clustered)
 WriteShadowPrices: 1 # Write shadow prices of LP or relaxed MILP; 0 = not active; 1 = active
 HydrogenMinimumProduction: 1  # Hydrogen production requirement; 0 = not active; 1 = active, meet regional level H2 production requirements

example_systems/9_three_zones_w_retrofit/settings/genx_settings.yml

@@ -6,7 +6,6 @@ CO2Cap: 2 # CO2 emissions cap; 0 = not active (no CO2 emission limit); 1 = mass-
 StorageLosses: 1 # Energy Share Requirement and CO2 constraints account for energy lost; 0 = not active (DO NOT account for energy lost); 1 = active systemwide (DO account for energy lost)
 MinCapReq: 1  # Activate minimum technology carveout constraints; 0 = not active; 1 = active
 MaxCapReq: 0  # Activate maximum technology carveout constraints; 0 = not active; 1 = active
-ParameterScale: 1 # Turn on parameter scaling wherein demand, capacity and power variables are defined in GW rather than MW. 0 = not active; 1 = active systemwide
 WriteShadowPrices: 1 # Write shadow prices of LP or relaxed MILP; 0 = not active; 1 = active
 UCommit: 2 # Unit committment of thermal power plants; 0 = not active; 1 = active using integer clestering; 2 = active using linearized clustering
 TimeDomainReduction: 1 # Time domain reduce (i.e. cluster) inputs based on Demand_data.csv, Generators_variability.csv, and Fuels_data.csv; 0 = not active (use input data as provided); 0 = active (cluster input data, or use data that has already been clustered)

precompile/case/settings/genx_settings.yml

@@ -3,7 +3,6 @@ Trans_Loss_Segments: 1
 CO2Cap: 2
 StorageLosses: 1
 MinCapReq: 1 
-ParameterScale: 1
 WriteShadowPrices: 1
 UCommit: 2
 OverwriteResults: 1

src/GenX.jl

@@ -37,16 +37,10 @@ using RecursiveArrayTools
 using Statistics
 using HiGHS
 using Logging
+using MacroEnergySystemsScaling
 
 using PrecompileTools: @compile_workload
 
-# Global scaling factor used when ParameterScale is on to shift values from MW to GW
-# DO NOT CHANGE THIS (Unless you do so very carefully)
-# To translate MW to GW, divide by ModelScalingFactor
-# To translate $ to $M, multiply by ModelScalingFactor^2
-# To translate $/MWh to $M/GWh, multiply by ModelScalingFactor
-const ModelScalingFactor = 1e+3
-
 """
 An abstract type that should be subtyped for users creating GenX resources.
 """

src/case_runners/case_runner.jl

@@ -79,6 +79,11 @@ function run_genx_case_simple!(case::AbstractString, mysetup::Dict, optimizer::A
     println("Time elapsed for model building is")
     println(time_elapsed)
 
+    if mysetup["AutoScaling"] == 1
+        println("Scaling Constraints")
+        scale_constraints!(EP, mysetup["ScalingSettings"])
+    end
+
     println("Solving Model")
     EP, solve_time = solve_model(EP, mysetup)
     myinputs["solve_time"] = solve_time # Store the model solve time in myinputs

src/configure_settings/configure_settings.jl

@@ -11,7 +11,6 @@ function default_settings()
         "VirtualChargeDischargeCost" => 1,  # $/MWh
         "MinCapReq" => 0,
         "MaxCapReq" => 0,
-        "ParameterScale" => 0,
         "WriteShadowPrices" => 0,
         "UCommit" => 0,
         "TimeDomainReduction" => 0,
@@ -36,7 +35,8 @@ function default_settings()
         "ResourcePoliciesFolder" => "policy_assignments",
         "SystemFolder" => "system",
         "PoliciesFolder" => "policies",
-        "ObjScale" => 1)
+        "ObjScale" => 1,
+        "AutoScaling" => 0,)
 end
 
 @doc raw"""
@@ -60,6 +60,8 @@ function configure_settings(settings_path::String, output_settings_path::String)
     settings = default_settings()
     merge!(settings, model_settings)
 
+    settings["ScalingSettings"] = get_scaling_settings(settings)
+
     output_settings = configure_writeoutput(output_settings_path, settings)
     settings["WriteOutputsSettingsDict"] = output_settings
 

src/load_inputs/load_cap_reserve_margin.jl

@@ -4,13 +4,13 @@
 Read input parameters related to planning reserve margin constraints
 """
 function load_cap_reserve_margin!(setup::Dict, path::AbstractString, inputs::Dict)
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+
 
     filename = "Capacity_reserve_margin_slack.csv"
     if isfile(joinpath(path, filename))
         df = load_dataframe(joinpath(path, filename))
         inputs["dfCapRes_slack"] = df
-        inputs["dfCapRes_slack"][!, :PriceCap] ./= scale_factor # Million $/GW if scaled, $/MW if not scaled
+
     end
 
     filename = "Capacity_reserve_margin.csv"

src/load_inputs/load_co2_cap.jl

@@ -4,13 +4,13 @@
 Read input parameters related to CO$_2$ emissions cap constraints
 """
 function load_co2_cap!(setup::Dict, path::AbstractString, inputs::Dict)
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+
 
     filename = "CO2_cap_slack.csv"
     if isfile(joinpath(path, filename))
         df = load_dataframe(joinpath(path, filename))
         inputs["dfCO2Cap_slack"] = df
-        inputs["dfCO2Cap_slack"][!, :PriceCap] ./= scale_factor # Million $/kton if scaled, $/ton if not scaled
+
     end
 
     filename = "CO2_cap.csv"
@@ -28,12 +28,11 @@ function load_co2_cap!(setup::Dict, path::AbstractString, inputs::Dict)
         # when scaled, the constraint unit is kton
         # when not scaled, the constraint unit is ton
         mat = extract_matrix_from_dataframe(df, "CO_2_Max_Mtons")
-        inputs["dfMaxCO2"] = mat * 1e6 / scale_factor
+        inputs["dfMaxCO2"] = mat * 1e6 
 
     elseif setup["CO2Cap"] == 2 || setup["CO2Cap"] == 3
         #  CO2 emissions rate applied per MWh
         mat = extract_matrix_from_dataframe(df, "CO_2_Max_tons_MWh")
-        # no scale_factor is needed since this is a ratio
         inputs["dfMaxCO2Rate"] = mat
     end
 

src/load_inputs/load_demand_data.jl

@@ -72,13 +72,13 @@ function load_demand_data!(setup::Dict, path::AbstractString, inputs::Dict)
     inputs["INTERIOR_SUBPERIODS"] = setdiff(1:T, inputs["START_SUBPERIODS"]) # set of indexes for all time periods that do not start a subperiod
 
     # Demand in MW for each zone
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+
     # Max value of non-served energy
-    inputs["Voll"] = as_vector(:Voll) / scale_factor # convert from $/MWh $ million/GWh (assuming objective is divided by 1000)
+    inputs["Voll"] = as_vector(:Voll)  # convert from $/MWh $ million/GWh (assuming objective is divided by 1000)
     # Demand in MW
     inputs["pD"] = extract_matrix_from_dataframe(demand_in,
         DEMAND_COLUMN_PREFIX()[1:(end - 1)],
-        prefixseparator = 'z') / scale_factor
+        prefixseparator = 'z') 
 
     # Cost of non-served energy/demand curtailment
     # Cost of each segment reported as a fraction of value of non-served energy - scaled implicitly

src/load_inputs/load_energy_share_requirement.jl

@@ -5,13 +5,13 @@ Read input parameters related to minimum energy share requirement constraints
 (e.g. renewable portfolio standard or clean electricity standard policies)
 """
 function load_energy_share_requirement!(setup::Dict, path::AbstractString, inputs::Dict)
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+
 
     filename = "Energy_share_requirement_slack.csv"
     if isfile(joinpath(path, filename))
         df = load_dataframe(joinpath(path, filename))
         inputs["dfESR_slack"] = df
-        inputs["dfESR_slack"][!, :PriceCap] ./= scale_factor # million $/GWh if scaled, $/MWh if not scaled
+
     end
 
     filename = "Energy_share_requirement.csv"

src/load_inputs/load_fuels_data.jl

@@ -24,11 +24,11 @@ function load_fuels_data!(setup::Dict, path::AbstractString, inputs::Dict)
     fuel_costs = Dict{AbstractString, Array{Float64}}()
     fuel_CO2 = Dict{AbstractString, Float64}()
 
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+
 
     for i in 1:length(fuels)
         # fuel cost is in $/MMBTU w/o scaling, $/Billon BTU w/ scaling
-        fuel_costs[fuels[i]] = costs[:, i] / scale_factor
+        fuel_costs[fuels[i]] = costs[:, i] 
         # No need to scale fuel_CO2, fuel_CO2 is ton/MMBTU or kton/Billion BTU 
         fuel_CO2[fuels[i]] = CO2_content[i]
     end

src/load_inputs/load_hydrogen_demand.jl

@@ -10,10 +10,10 @@ function load_hydrogen_demand!(setup::Dict, path::AbstractString, inputs::Dict)
     inputs["NumberOfH2DemandReqs"] = nrow(df)
     inputs["H2DemandReq"] = df[!, :Hydrogen_Demand_kt]
 
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1 # Million $/kton if scaled, $/ton if not scaled
+     # Million $/kton if scaled, $/ton if not scaled
 
     if "PriceCap" in names(df)
-        inputs["H2DemandPriceCap"] = df[!, :PriceCap] / scale_factor
+        inputs["H2DemandPriceCap"] = df[!, :PriceCap] 
     end
     println(filename * " Successfully Read!")
 end

src/load_inputs/load_inputs.jl

@@ -81,9 +81,7 @@ function load_inputs(setup::Dict, path::AbstractString)
     end
 
     # Virtual charge discharge cost
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
-    inputs["VirtualChargeDischargeCost"] = setup["VirtualChargeDischargeCost"] /
-                                           scale_factor
+    inputs["VirtualChargeDischargeCost"] = setup["VirtualChargeDischargeCost"]
 
     println("CSV Files Successfully Read In From $path")