From b7040cb6781b1ba13b7527df9a61181e10c95148 Mon Sep 17 00:00:00 2001
From: Ruaridh Macdonald <rmacd@mit.edu>
Date: Thu, 14 Nov 2024 04:39:23 -0500
Subject: [PATCH 01/11] Add MacroEnergySystemsScaling

---
 Project.toml | 1 +
 src/GenX.jl  | 1 +
 2 files changed, 2 insertions(+)

diff --git a/Project.toml b/Project.toml
index 60f5a42e2..46fa2393e 100644
--- a/Project.toml
+++ b/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"
diff --git a/src/GenX.jl b/src/GenX.jl
index 3a5a39980..5be926316 100644
--- a/src/GenX.jl
+++ b/src/GenX.jl
@@ -37,6 +37,7 @@ using RecursiveArrayTools
 using Statistics
 using HiGHS
 using Logging
+using MacroEnergySystemsScaling
 
 using PrecompileTools: @compile_workload
 

From 0679927c990856ef19d31db2e04b4917e0fbe1e0 Mon Sep 17 00:00:00 2001
From: Ruaridh Macdonald <rmacd@mit.edu>
Date: Thu, 14 Nov 2024 05:04:20 -0500
Subject: [PATCH 02/11] Remove scale_factor

I left scale_factor in load_resources_data.jl to allow for other scaling on loading
---
 src/load_inputs/load_cap_reserve_margin.jl    |  4 +-
 src/load_inputs/load_co2_cap.jl               |  7 ++--
 src/load_inputs/load_demand_data.jl           |  6 +--
 .../load_energy_share_requirement.jl          |  4 +-
 src/load_inputs/load_fuels_data.jl            |  4 +-
 src/load_inputs/load_hydrogen_demand.jl       |  4 +-
 src/load_inputs/load_inputs.jl                |  4 +-
 .../load_maximum_capacity_requirement.jl      |  6 +--
 src/load_inputs/load_multistage_data.jl       |  8 ++--
 src/load_inputs/load_network_data.jl          | 17 ++++----
 src/load_inputs/load_operational_reserves.jl  |  7 ++--
 src/load_inputs/load_resources_data.jl        | 41 ++++++++++---------
 src/model/resources/fusion/fusion.jl          |  4 +-
 src/model/resources/hydrogen/electrolyzer.jl  |  5 +--
 .../write_capacity_value.jl                   |  8 ++--
 .../write_reserve_margin_revenue.jl           |  4 +-
 .../write_virtual_discharge.jl                |  4 +-
 .../hydrogen/write_hourly_matching_prices.jl  |  4 +-
 .../hydrogen/write_hydrogen_prices.jl         |  4 +-
 .../write_maximum_capacity_requirement.jl     |  8 ++--
 .../write_minimum_capacity_requirement.jl     |  8 ++--
 .../write_operating_reserve_price_revenue.jl  | 13 +++---
 src/write_outputs/reserves/write_reg.jl       |  4 +-
 src/write_outputs/reserves/write_rsv.jl       |  6 +--
 src/write_outputs/write_capacityfactor.jl     | 16 ++++----
 src/write_outputs/write_charge.jl             |  4 +-
 src/write_outputs/write_charging_cost.jl      |  4 +-
 src/write_outputs/write_co2.jl                |  8 ++--
 src/write_outputs/write_curtailment.jl        |  4 +-
 src/write_outputs/write_emissions.jl          | 14 +++----
 src/write_outputs/write_nse.jl                |  4 +-
 src/write_outputs/write_power.jl              |  4 +-
 src/write_outputs/write_price.jl              |  4 +-
 src/write_outputs/write_reliability.jl        |  4 +-
 src/write_outputs/write_storage.jl            |  4 +-
 test/test_load_resource_data.jl               |  6 +--
 test/test_multistage.jl                       |  3 +-
 37 files changed, 121 insertions(+), 142 deletions(-)

diff --git a/src/load_inputs/load_cap_reserve_margin.jl b/src/load_inputs/load_cap_reserve_margin.jl
index 0a652bc78..28d57aed5 100644
--- a/src/load_inputs/load_cap_reserve_margin.jl
+++ b/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"
diff --git a/src/load_inputs/load_co2_cap.jl b/src/load_inputs/load_co2_cap.jl
index 08e6802a0..5a0138646 100644
--- a/src/load_inputs/load_co2_cap.jl
+++ b/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
 
diff --git a/src/load_inputs/load_demand_data.jl b/src/load_inputs/load_demand_data.jl
index 52c5bd7bf..70d8b9842 100644
--- a/src/load_inputs/load_demand_data.jl
+++ b/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
diff --git a/src/load_inputs/load_energy_share_requirement.jl b/src/load_inputs/load_energy_share_requirement.jl
index e3205196b..01ca4bc4f 100644
--- a/src/load_inputs/load_energy_share_requirement.jl
+++ b/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"
diff --git a/src/load_inputs/load_fuels_data.jl b/src/load_inputs/load_fuels_data.jl
index 61b0ff2f0..5a52c377a 100644
--- a/src/load_inputs/load_fuels_data.jl
+++ b/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
diff --git a/src/load_inputs/load_hydrogen_demand.jl b/src/load_inputs/load_hydrogen_demand.jl
index d7b5fc6e4..938ce9582 100644
--- a/src/load_inputs/load_hydrogen_demand.jl
+++ b/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
diff --git a/src/load_inputs/load_inputs.jl b/src/load_inputs/load_inputs.jl
index aa1ee28a0..1ec862f5b 100644
--- a/src/load_inputs/load_inputs.jl
+++ b/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")
 
diff --git a/src/load_inputs/load_maximum_capacity_requirement.jl b/src/load_inputs/load_maximum_capacity_requirement.jl
index 95b766be8..d7aaca228 100644
--- a/src/load_inputs/load_maximum_capacity_requirement.jl
+++ b/src/load_inputs/load_maximum_capacity_requirement.jl
@@ -9,11 +9,11 @@ function load_maximum_capacity_requirement!(path::AbstractString, inputs::Dict,
     inputs["NumberOfMaxCapReqs"] = nrow(df)
     inputs["MaxCapReq"] = df[!, :Max_MW]
 
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
+
 
-    inputs["MaxCapReq"] /= scale_factor
     if "PriceCap" in names(df)
-        inputs["MaxCapPriceCap"] = df[!, :PriceCap] / scale_factor
+        inputs["MaxCapPriceCap"] = df[!, :PriceCap] 
     end
     println(filename * " Successfully Read!")
 end
diff --git a/src/load_inputs/load_multistage_data.jl b/src/load_inputs/load_multistage_data.jl
index 2042ffa87..5793ed205 100644
--- a/src/load_inputs/load_multistage_data.jl
+++ b/src/load_inputs/load_multistage_data.jl
@@ -1,4 +1,4 @@
-function load_multistage_dataframe(filepath::AbstractString, scale_factor::Float64)
+function load_multistage_dataframe(filepath::AbstractString)
     if !isfile(filepath)
         error("Multistage data file not found at $filepath")
     end
@@ -6,7 +6,7 @@ function load_multistage_dataframe(filepath::AbstractString, scale_factor::Float
     multistage_in = load_dataframe(filepath)
     # rename columns lowercase for internal consistency
     rename!(multistage_in, lowercase.(names(multistage_in)))
-    scale_multistage_data!(multistage_in, scale_factor)
+    scale_multistage_data!(multistage_in)
 
     validate_multistage_data!(multistage_in)
 
@@ -24,7 +24,7 @@ function validate_multistage_data!(multistage_df::DataFrame)
     end
 end
 
-function scale_multistage_data!(multistage_in::DataFrame, scale_factor::Float64)
+function scale_multistage_data!(multistage_in::DataFrame)
     columns_to_scale = [:min_retired_cap_mw,            # to GW
         :min_retired_charge_cap_mw,     # to GW
         :min_retired_energy_cap_mw,     # to GW
@@ -37,6 +37,6 @@ function scale_multistage_data!(multistage_in::DataFrame, scale_factor::Float64)
         :min_retired_cap_discharge_dc_mw,
         :min_retired_cap_discharge_ac_mw
     ]
-    scale_columns!(multistage_in, columns_to_scale, scale_factor)
+    scale_columns!(multistage_in, columns_to_scale)
     return nothing
 end
diff --git a/src/load_inputs/load_network_data.jl b/src/load_inputs/load_network_data.jl
index ac7f2b1c8..1896b3d4c 100644
--- a/src/load_inputs/load_network_data.jl
+++ b/src/load_inputs/load_network_data.jl
@@ -4,7 +4,7 @@
 Function for reading input parameters related to the electricity transmission network
 """
 function load_network_data!(setup::Dict, path::AbstractString, inputs_nw::Dict)
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     filename = "Network.csv"
     network_var = load_dataframe(joinpath(path, filename))
@@ -23,7 +23,7 @@ function load_network_data!(setup::Dict, path::AbstractString, inputs_nw::Dict)
     inputs_nw["pNet_Map"] = load_network_map(network_var, Z, L)
 
     # Transmission capacity of the network (in MW)
-    inputs_nw["pTrans_Max"] = to_floats(:Line_Max_Flow_MW) / scale_factor  # convert to GW
+    inputs_nw["pTrans_Max"] = to_floats(:Line_Max_Flow_MW)   # convert to GW
 
     if setup["Trans_Loss_Segments"] == 1
         # Line percentage Loss - valid for case when modeling losses as a fixed percent of absolute value of power flows
@@ -50,8 +50,7 @@ function load_network_data!(setup::Dict, path::AbstractString, inputs_nw::Dict)
         inputs_nw["Line_Angle_Limit"] = to_floats(:Angle_Limit_Rad)
         # DC-OPF coefficient for each line (in MW when not scaled, in GW when scaled) 
         # MW = (kV)^2/Ohms 
-        inputs_nw["pDC_OPF_coeff"] = ((line_voltage_kV .^ 2) ./ line_reactance_Ohms) /
-                                     scale_factor
+        inputs_nw["pDC_OPF_coeff"] = ((line_voltage_kV .^ 2) ./ line_reactance_Ohms)
     end
 
     # Maximum possible flow after reinforcement for use in linear segments of piecewise approximation
@@ -59,12 +58,11 @@ function load_network_data!(setup::Dict, path::AbstractString, inputs_nw::Dict)
 
     if setup["NetworkExpansion"] == 1
         # Read between zone network reinforcement costs per peak MW of capacity added
-        inputs_nw["pC_Line_Reinforcement"] = to_floats(:Line_Reinforcement_Cost_per_MWyr) /
-                                             scale_factor # convert to million $/GW/yr with objective function in millions
+        inputs_nw["pC_Line_Reinforcement"] = to_floats(:Line_Reinforcement_Cost_per_MWyr)
         # Maximum reinforcement allowed in MW
         #NOTE: values <0 indicate no expansion possible
         inputs_nw["pMax_Line_Reinforcement"] = map(x -> max(0, x),
-            to_floats(:Line_Max_Reinforcement_MW)) / scale_factor # convert to GW
+            to_floats(:Line_Max_Reinforcement_MW))  # convert to GW
         inputs_nw["pTrans_Max_Possible"] += inputs_nw["pMax_Line_Reinforcement"]
     end
 
@@ -77,8 +75,7 @@ function load_network_data!(setup::Dict, path::AbstractString, inputs_nw::Dict)
         end
 
         # Max Flow Possible on Each Line
-        inputs_nw["pLine_Max_Flow_Possible_MW"] = to_floats(:Line_Max_Flow_Possible_MW) /
-                                                  scale_factor # Convert to GW
+        inputs_nw["pLine_Max_Flow_Possible_MW"] = to_floats(:Line_Max_Flow_Possible_MW)
     end
 
     # Transmission line (between zone) loss coefficient (resistance/voltage^2)
@@ -88,7 +85,7 @@ function load_network_data!(setup::Dict, path::AbstractString, inputs_nw::Dict)
     elseif setup["Trans_Loss_Segments"] >= 2
         # If zones are connected, loss coefficient is R/V^2 where R is resistance in Ohms and V is voltage in Volts
         inputs_nw["pTrans_Loss_Coef"] = (inputs_nw["Ohms"] / 10^6) ./
-                                        (inputs_nw["kV"] / 10^3)^2 * scale_factor # 1/GW ***
+                                        (inputs_nw["kV"] / 10^3)^2 # 1/GW ***
     end
 
     ## Sets and indices for transmission losses and expansion
diff --git a/src/load_inputs/load_operational_reserves.jl b/src/load_inputs/load_operational_reserves.jl
index 6b6d67cb7..f0ca6c723 100644
--- a/src/load_inputs/load_operational_reserves.jl
+++ b/src/load_inputs/load_operational_reserves.jl
@@ -43,12 +43,11 @@ function load_operational_reserves!(setup::Dict, path::AbstractString, inputs::D
     # Spinning up reserve requirement as a percent of hourly wind and solar generation (which is summed across all zones)
     inputs["pRsv_Req_VRE"] = float(res_in[1, :Rsv_Req_Percent_VRE])
 
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     # Penalty for not meeting hourly spinning reserve requirement
-    inputs["pC_Rsv_Penalty"] = float(res_in[1, :Unmet_Rsv_Penalty_Dollar_per_MW]) /
-                               scale_factor # convert to million $/GW with objective function in millions
-    inputs["pStatic_Contingency"] = float(res_in[1, :Static_Contingency_MW]) / scale_factor # convert to GW
+    inputs["pC_Rsv_Penalty"] = float(res_in[1, :Unmet_Rsv_Penalty_Dollar_per_MW])
+    inputs["pStatic_Contingency"] = float(res_in[1, :Static_Contingency_MW])  # convert to GW
 
     if setup["UCommit"] >= 1
         inputs["pDynamic_Contingency"] = convert(Int8, res_in[1, :Dynamic_Contingency])
diff --git a/src/load_inputs/load_resources_data.jl b/src/load_inputs/load_resources_data.jl
index 7966038a0..6049da599 100644
--- a/src/load_inputs/load_resources_data.jl
+++ b/src/load_inputs/load_resources_data.jl
@@ -72,7 +72,7 @@ function _get_summary_map()
 end
 
 """
-    scale_resources_data!(resource_in::DataFrame, scale_factor::Float64)
+    scale_resources_data!(resource_in::DataFrame, scale_factor::Float64=1.0)
 
 Scales resources attributes in-place if necessary. Generally, these scalings converts energy and power units from MW to GW  and \$/MW to \$M/GW. Both are done by dividing the values by 1000.
 See documentation for descriptions of each column being scaled.
@@ -82,7 +82,11 @@ See documentation for descriptions of each column being scaled.
 - `scale_factor` (Float64): A scaling factor for energy and currency units.
 
 """
-function scale_resources_data!(resource_in::DataFrame, scale_factor::Float64)
+function scale_resources_data!(resource_in::DataFrame, scale_factor::Float64=1.0)
+    if scale_factor == 1.0
+        return nothing
+    end
+
     columns_to_scale = [:existing_charge_cap_mw,        # to GW
         :existing_cap_mwh,              # to GWh
         :existing_cap_mw,               # to GW
@@ -115,7 +119,7 @@ function scale_resources_data!(resource_in::DataFrame, scale_factor::Float64)
 end
 
 """
-    scale_vre_stor_data!(vre_stor_in::DataFrame, scale_factor::Float64)
+    scale_vre_stor_data!(vre_stor_in::DataFrame, scale_factor::Float64=1.0)
 
 Scales vre_stor attributes in-place if necessary. Generally, these scalings converts energy and power units from MW to GW  and \$/MW to \$M/GW. Both are done by dividing the values by 1000.
 See documentation for descriptions of each column being scaled.
@@ -125,7 +129,7 @@ See documentation for descriptions of each column being scaled.
 - `scale_factor` (Float64): A scaling factor for energy and currency units.
 
 """
-function scale_vre_stor_data!(vre_stor_in::DataFrame, scale_factor::Float64)
+function scale_vre_stor_data!(vre_stor_in::DataFrame, scale_factor::Float64=1.0)
     columns_to_scale = [:existing_cap_inverter_mw,
         :existing_cap_solar_mw,
         :existing_cap_wind_mw,
@@ -185,7 +189,7 @@ function scale_vre_stor_data!(vre_stor_in::DataFrame, scale_factor::Float64)
 end
 
 """
-    scale_columns!(df::DataFrame, columns_to_scale::Vector{Symbol}, scale_factor::Float64)
+    scale_columns!(df::DataFrame, columns_to_scale::Vector{Symbol}, scale_factor::Float64=1.0)
 
 Scales in-place the columns in `columns_to_scale` of a dataframe `df` by a `scale_factor`.
 
@@ -197,7 +201,10 @@ Scales in-place the columns in `columns_to_scale` of a dataframe `df` by a `scal
 """
 function scale_columns!(df::DataFrame,
         columns_to_scale::Vector{Symbol},
-        scale_factor::Float64)
+        scale_factor::Float64=1.0)
+    if scale_factor == 1.0
+        return nothing
+    end
     for column in columns_to_scale
         if string(column) in names(df)
             df[!, column] /= scale_factor
@@ -207,20 +214,20 @@ function scale_columns!(df::DataFrame,
 end
 
 """
-    load_resource_df(path::AbstractString, scale_factor::Float64, resource_type::Type)
+    load_resource_df(path::AbstractString, scale_factor::Float64=1.0, resource_type::Type)
 
 Function to load and scale the dataframe of a given resource.
 
 # Arguments
 - `path::AbstractString`: Path to the resource dataframe.
-- `scale_factor::Float64`: Scaling factor for the resource data.
+- `scale_factor::Float64=1.0`: Scaling factor for the resource data.
 - `resource_type::Type`: GenX type of the resource.
 
 # Returns
 - `resource_in::DataFrame`: The loaded and scaled resource data.
 
 """
-function load_resource_df(path::AbstractString, scale_factor::Float64, resource_type::Type)
+function load_resource_df(path::AbstractString, scale_factor::Float64=1.0, resource_type::Type)
     resource_in = load_dataframe(path)
     # rename columns lowercase for internal consistency
     rename!(resource_in, lowercase.(names(resource_in)))
@@ -296,14 +303,14 @@ function create_resources_sametype(resource_in::DataFrame, ResourceType)
 end
 
 """
-    create_resource_array(resource_folder::AbstractString, resources_info::NamedTuple, scale_factor::Float64=1.0)
+    create_resource_array(resource_folder::AbstractString, resources_info::NamedTuple, scale_factor::Float64=1.0=1.0)
 
 Construct the array of resources from multiple files of different types located in the specified `resource_folder`. The `resources_info` NamedTuple contains the filename and GenX type for each type of resource available in GenX.
 
 # Arguments
 - `resource_folder::AbstractString`: The path to the folder containing the resource files.
 - `resources_info::NamedTuple`: A NamedTuple that maps a resource type to its filename and GenX type.
-- `scale_factor::Float64`: A scaling factor to adjust the attributes of the resources (default: 1.0).
+- `scale_factor::Float64=1.0`: A scaling factor to adjust the attributes of the resources (default: 1.0).
 
 # Returns
 - `Vector{<:AbstractResource}`: An array of GenX resources.
@@ -314,7 +321,7 @@ Construct the array of resources from multiple files of different types located
 """
 function create_resource_array(resource_folder::AbstractString,
         resources_info::NamedTuple,
-        scale_factor::Float64 = 1.0)
+        scale_factor::Float64=1.0)
     resource_id_offset = 0
     resources = []
     # loop over available types and load all resources in resource_folder
@@ -590,13 +597,11 @@ Function that loads and scales resources data from folder specified in resources
 
 """
 function create_resource_array(setup::Dict, resources_path::AbstractString)
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1.0
-
     # get filename and GenX type for each type of resources available in GenX
     resources_info = _get_resource_info()
 
     # load each resource type, scale data and return array of resources
-    resources = create_resource_array(resources_path, resources_info, scale_factor)
+    resources = create_resource_array(resources_path, resources_info)
     # validate input before returning resources
     validate_resources(setup, resources)
     return resources
@@ -800,7 +805,6 @@ Reads module dataframes, loops over files and adds columns as new attributes to
 function add_modules_to_resources!(resources::Vector{<:AbstractResource},
         setup::Dict,
         resources_path::AbstractString)
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1.0
 
     modules = Vector{DataFrame}()
 
@@ -808,7 +812,7 @@ function add_modules_to_resources!(resources::Vector{<:AbstractResource},
     # Add multistage if multistage is activated
     if setup["MultiStage"] == 1
         filename = joinpath(resources_path, "Resource_multistage_data.csv")
-        multistage_in = load_multistage_dataframe(filename, scale_factor)
+        multistage_in = load_multistage_dataframe(filename)
         push!(modules, multistage_in)
         @info "Multistage data successfully read."
     end
@@ -944,9 +948,6 @@ function process_piecewisefuelusage!(setup::Dict,
         sort!(slope_cols, by = x -> parse(Int, split(string(x), "_")[end]))
         slope_df = DataFrame(heat_rate_mat, Symbol.(slope_cols))
         PWFU_data = hcat(slope_df, intercept_df)
-        # no need to scale sclope, but intercept should be scaled when parameterscale is on (MMBTU -> billion BTU)
-        scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
-        PWFU_data[!, intercept_cols] ./= scale_factor
 
         inputs["slope_cols"] = slope_cols
         inputs["intercept_cols"] = intercept_cols
diff --git a/src/model/resources/fusion/fusion.jl b/src/model/resources/fusion/fusion.jl
index 2b62f1d20..c4e2fb3f8 100644
--- a/src/model/resources/fusion/fusion.jl
+++ b/src/model/resources/fusion/fusion.jl
@@ -483,11 +483,11 @@ end
 function thermal_fusion_annual_parasitic_power(
         EP::Model, inputs::Dict, setup::Dict)::Vector{Float64}
     gen = inputs["RESOURCES"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
     FUSION = ids_with(gen, fusion)
 
     resource_component = resource_name.(gen[FUSION])
 
     expr = fusion_annual_parasitic_power.(Ref(EP), Ref(inputs), resource_component)
-    return scale_factor * value.(expr)
+    return value.(expr)
 end
diff --git a/src/model/resources/hydrogen/electrolyzer.jl b/src/model/resources/hydrogen/electrolyzer.jl
index bd132321b..aaab9835c 100644
--- a/src/model/resources/hydrogen/electrolyzer.jl
+++ b/src/model/resources/hydrogen/electrolyzer.jl
@@ -172,14 +172,13 @@ function electrolyzer!(EP::Model, inputs::Dict, setup::Dict)
 
     ### Objective Function ###
     # Subtract hydrogen revenue from objective function
-    scale_factor = setup["ParameterScale"] == 1 ? 10^6 : 1  # If ParameterScale==1, costs are in millions of $
     @expression(EP, eHydrogenValue[y in ELECTROLYZERS, t in 1:T],
         omega[t] * EP[:vUSE][y, t] / hydrogen_mwh_per_tonne(gen[y]) *
-        hydrogen_price_per_tonne(gen[y])/scale_factor)
+        hydrogen_price_per_tonne(gen[y]))
     if !isempty(VS_ELEC)
         @expression(EP, eHydrogenValue_vs[y in VS_ELEC, t in 1:T],
             omega[t] * EP[:vP_ELEC][y, t] / hydrogen_mwh_per_tonne_elec(gen[y]) *
-            hydrogen_price_per_tonne_elec(gen[y])/scale_factor)
+            hydrogen_price_per_tonne_elec(gen[y]))
     end
     @expression(EP, eTotalHydrogenValueT[t in 1:T],
         if !isempty(VS_ELEC)
diff --git a/src/write_outputs/capacity_reserve_margin/write_capacity_value.jl b/src/write_outputs/capacity_reserve_margin/write_capacity_value.jl
index b1aa431bb..52b84fe8b 100644
--- a/src/write_outputs/capacity_reserve_margin/write_capacity_value.jl
+++ b/src/write_outputs/capacity_reserve_margin/write_capacity_value.jl
@@ -29,11 +29,11 @@ function write_capacity_value(path::AbstractString, inputs::Dict, setup::Dict, E
     MUST_RUN = inputs["MUST_RUN"]
     VRE_STOR = inputs["VRE_STOR"]
 
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
     eTotalCap = value.(EP[:eTotalCap])
 
     minimum_plant_size = 1 # MW
-    large_plants = findall(>=(minimum_plant_size), eTotalCap * scale_factor)
+    large_plants = findall(>=(minimum_plant_size), eTotalCap )
 
     THERM_ALL_EX = intersect(THERM_ALL, large_plants)
     VRE_EX = intersect(VRE, large_plants)
@@ -165,6 +165,6 @@ function capacity_reserve_margin_price(EP::Model,
         setup::Dict,
         capres_zone::Int)::Vector{Float64}
     ω = inputs["omega"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
-    return dual.(EP[:cCapacityResMargin][capres_zone, :]) ./ ω * scale_factor
+    
+    return dual.(EP[:cCapacityResMargin][capres_zone, :]) ./ ω 
 end
diff --git a/src/write_outputs/capacity_reserve_margin/write_reserve_margin_revenue.jl b/src/write_outputs/capacity_reserve_margin/write_reserve_margin_revenue.jl
index 418b14eea..2dedcd035 100644
--- a/src/write_outputs/capacity_reserve_margin/write_reserve_margin_revenue.jl
+++ b/src/write_outputs/capacity_reserve_margin/write_reserve_margin_revenue.jl
@@ -12,7 +12,7 @@ function write_reserve_margin_revenue(path::AbstractString,
         inputs::Dict,
         setup::Dict,
         EP::Model)
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     gen = inputs["RESOURCES"]
     regions = region.(gen)
@@ -86,7 +86,7 @@ function write_reserve_margin_revenue(path::AbstractString,
             tempresrev[AC_CHARGE] .-= derating_factor.(gen[AC_CHARGE], tag = i) .* 
                                           ((value.(EP[:vCAPRES_AC_CHARGE][AC_CHARGE, :]).data) * weighted_price)
         end
-        tempresrev *= scale_factor
+
         annual_sum .+= tempresrev
         dfResRevenue = hcat(dfResRevenue, DataFrame([tempresrev], [Symbol("CapRes_$i")]))
     end
diff --git a/src/write_outputs/capacity_reserve_margin/write_virtual_discharge.jl b/src/write_outputs/capacity_reserve_margin/write_virtual_discharge.jl
index 1aa52623d..89e481209 100644
--- a/src/write_outputs/capacity_reserve_margin/write_virtual_discharge.jl
+++ b/src/write_outputs/capacity_reserve_margin/write_virtual_discharge.jl
@@ -9,12 +9,12 @@ function write_virtual_discharge(path::AbstractString, inputs::Dict, setup::Dict
     T = inputs["T"]     # Number of time steps (hours)
     STOR_ALL = inputs["STOR_ALL"]
 
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     resources = inputs["RESOURCE_NAMES"][STOR_ALL]
     zones = inputs["R_ZONES"][STOR_ALL]
     virtual_discharge = (value.(EP[:vCAPRES_discharge][STOR_ALL, :].data) -
-                         value.(EP[:vCAPRES_charge][STOR_ALL, :].data)) * scale_factor
+                         value.(EP[:vCAPRES_charge][STOR_ALL, :].data)) 
 
     dfVirtualDischarge = DataFrame(Resource = resources, Zone = zones)
     dfVirtualDischarge.AnnualSum .= virtual_discharge * inputs["omega"]
diff --git a/src/write_outputs/hydrogen/write_hourly_matching_prices.jl b/src/write_outputs/hydrogen/write_hourly_matching_prices.jl
index 92fe82c0b..4ce5fd142 100644
--- a/src/write_outputs/hydrogen/write_hourly_matching_prices.jl
+++ b/src/write_outputs/hydrogen/write_hourly_matching_prices.jl
@@ -4,12 +4,12 @@ function write_hourly_matching_prices(path::AbstractString,
         EP::Model)
     T = inputs["T"]     # Number of time steps (hours)
     Z = inputs["Z"]     # Number of zones
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     ## Extract dual variables of constraints
     dfHourlyMatchPrices = DataFrame(Zone = 1:Z) # The unit is $/MWh
     # Dividing dual variable for each hour with corresponding hourly weight to retrieve marginal cost of the constraint
-    price = dual.(EP[:cHourlyMatching]) ./ inputs["omega"] * scale_factor
+    price = dual.(EP[:cHourlyMatching]) ./ inputs["omega"] 
     dfHourlyMatchPrices = hcat(dfHourlyMatchPrices,
         DataFrame(transpose(price), :auto))
 
diff --git a/src/write_outputs/hydrogen/write_hydrogen_prices.jl b/src/write_outputs/hydrogen/write_hydrogen_prices.jl
index 670193196..b552d6012 100644
--- a/src/write_outputs/hydrogen/write_hydrogen_prices.jl
+++ b/src/write_outputs/hydrogen/write_hydrogen_prices.jl
@@ -1,11 +1,9 @@
 function write_hydrogen_prices(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor^2 : 1  # If ParameterScale==1, costs are in millions of $
-
     NumberOfH2DemandReqs = inputs["NumberOfH2DemandReqs"]
     dfHydrogenPrice = DataFrame(
         H2_Demand = [Symbol("H2_Demand_$h2demand") for h2demand in 1:NumberOfH2DemandReqs],
         Hydrogen_Price_Per_Tonne = convert(
-            Array{Float64}, dual.(EP[:cZoneH2DemandReq]) * scale_factor))
+            Array{Float64}, dual.(EP[:cZoneH2DemandReq]) ))
     CSV.write(joinpath(path, "hydrogen_prices.csv"), dfHydrogenPrice)
 
     return nothing
diff --git a/src/write_outputs/min_max_capacity_requirement/write_maximum_capacity_requirement.jl b/src/write_outputs/min_max_capacity_requirement/write_maximum_capacity_requirement.jl
index 8d1b3450e..ea6c3a0ce 100644
--- a/src/write_outputs/min_max_capacity_requirement/write_maximum_capacity_requirement.jl
+++ b/src/write_outputs/min_max_capacity_requirement/write_maximum_capacity_requirement.jl
@@ -8,15 +8,15 @@ function write_maximum_capacity_requirement(path::AbstractString,
                       for maxcap in 1:NumberOfMaxCapReqs],
         Price = -dual.(EP[:cZoneMaxCapReq]))
 
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
+
 
-    dfMaxCapPrice.Price *= scale_factor
 
     if haskey(inputs, "MaxCapPriceCap")
         dfMaxCapPrice[!, :Slack] = convert(Array{Float64}, value.(EP[:vMaxCap_slack]))
         dfMaxCapPrice[!, :Penalty] = convert(Array{Float64}, value.(EP[:eCMaxCap_slack]))
-        dfMaxCapPrice.Slack *= scale_factor # Convert GW to MW
-        dfMaxCapPrice.Penalty *= scale_factor^2 # Convert Million $ to $
+
+
     end
     CSV.write(joinpath(path, "MaxCapReq_prices_and_penalties.csv"), dfMaxCapPrice)
 end
diff --git a/src/write_outputs/min_max_capacity_requirement/write_minimum_capacity_requirement.jl b/src/write_outputs/min_max_capacity_requirement/write_minimum_capacity_requirement.jl
index bae7d17ee..9923fc2e3 100644
--- a/src/write_outputs/min_max_capacity_requirement/write_minimum_capacity_requirement.jl
+++ b/src/write_outputs/min_max_capacity_requirement/write_minimum_capacity_requirement.jl
@@ -8,15 +8,15 @@ function write_minimum_capacity_requirement(path::AbstractString,
                       for mincap in 1:NumberOfMinCapReqs],
         Price = dual.(EP[:cZoneMinCapReq]))
 
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
+
 
-    dfMinCapPrice.Price *= scale_factor # Convert Million $/GW to $/MW
 
     if haskey(inputs, "MinCapPriceCap")
         dfMinCapPrice[!, :Slack] = convert(Array{Float64}, value.(EP[:vMinCap_slack]))
         dfMinCapPrice[!, :Penalty] = convert(Array{Float64}, value.(EP[:eCMinCap_slack]))
-        dfMinCapPrice.Slack *= scale_factor # Convert GW to MW
-        dfMinCapPrice.Penalty *= scale_factor^2 # Convert Million $ to $
+
+
     end
     CSV.write(joinpath(path, "MinCapReq_prices_and_penalties.csv"), dfMinCapPrice)
 end
diff --git a/src/write_outputs/reserves/write_operating_reserve_price_revenue.jl b/src/write_outputs/reserves/write_operating_reserve_price_revenue.jl
index 79ab9b8cb..9851fb94e 100644
--- a/src/write_outputs/reserves/write_operating_reserve_price_revenue.jl
+++ b/src/write_outputs/reserves/write_operating_reserve_price_revenue.jl
@@ -11,7 +11,7 @@ function write_operating_reserve_regulation_revenue(path::AbstractString,
         inputs::Dict,
         setup::Dict,
         EP::Model)
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     gen = inputs["RESOURCES"]
     RSV = inputs["RSV"]
@@ -39,9 +39,6 @@ function write_operating_reserve_regulation_revenue(path::AbstractString,
     rsvrevenue = value.(EP[:vRSV][RSV, :].data) .* transpose(weighted_rsv_price)
     regrevenue = value.(EP[:vREG][REG, :].data) .* transpose(weighted_reg_price)
 
-    rsvrevenue *= scale_factor
-    regrevenue *= scale_factor
-
     dfOpRsvRevenue.AnnualSum .= rsvrevenue * inputs["omega"]
     dfOpRegRevenue.AnnualSum .= regrevenue * inputs["omega"]
 
@@ -63,8 +60,8 @@ This is equal to the dual variable of the regulation requirement constraint.
 
 function operating_regulation_price(EP::Model, inputs::Dict, setup::Dict)::Vector{Float64}
     ω = inputs["omega"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
-    return dual.(EP[:cReg]) ./ ω * scale_factor
+    
+    return dual.(EP[:cReg]) ./ ω 
 end
 
 @doc raw"""
@@ -80,6 +77,6 @@ This is equal to the dual variable of the reserve requirement constraint.
 
 function operating_reserve_price(EP::Model, inputs::Dict, setup::Dict)::Vector{Float64}
     ω = inputs["omega"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
-    return dual.(EP[:cRsvReq]) ./ ω * scale_factor
+    
+    return dual.(EP[:cRsvReq]) ./ ω 
 end
diff --git a/src/write_outputs/reserves/write_reg.jl b/src/write_outputs/reserves/write_reg.jl
index 7d7ca1efd..2fc0c17bb 100644
--- a/src/write_outputs/reserves/write_reg.jl
+++ b/src/write_outputs/reserves/write_reg.jl
@@ -1,11 +1,11 @@
 function write_reg(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
     REG = inputs["REG"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     resources = inputs["RESOURCE_NAMES"][REG]
     zones = inputs["R_ZONES"][REG]
     # Regulation contributions for each resource in each time step
-    reg = value.(EP[:vREG][REG, :].data) * scale_factor
+    reg = value.(EP[:vREG][REG, :].data) 
 
     dfReg = DataFrame(Resource = resources, Zone = zones)
     dfReg.AnnualSum = reg * inputs["omega"]
diff --git a/src/write_outputs/reserves/write_rsv.jl b/src/write_outputs/reserves/write_rsv.jl
index ba38ccb72..6686a2f26 100644
--- a/src/write_outputs/reserves/write_rsv.jl
+++ b/src/write_outputs/reserves/write_rsv.jl
@@ -1,11 +1,11 @@
 function write_rsv(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
     T = inputs["T"]     # Number of time steps (hours)
     RSV = inputs["RSV"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     resources = inputs["RESOURCE_NAMES"][RSV]
     zones = inputs["R_ZONES"][RSV]
-    rsv = value.(EP[:vRSV][RSV, :].data) * scale_factor
+    rsv = value.(EP[:vRSV][RSV, :].data) 
 
     dfRsv = DataFrame(Resource = resources, Zone = zones)
 
@@ -14,7 +14,7 @@ function write_rsv(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
     if setup["WriteOutputs"] == "annual"
         write_annual(joinpath(path, "reg_dn.csv"), dfRsv)
     else # setup["WriteOutputs"] == "full"
-        unmet_vec = value.(EP[:vUNMET_RSV]) * scale_factor
+        unmet_vec = value.(EP[:vUNMET_RSV]) 
         total_unmet = sum(unmet_vec)
         dfRsv = hcat(dfRsv, DataFrame(rsv, :auto))
         auxNew_Names = [Symbol("Resource");
diff --git a/src/write_outputs/write_capacityfactor.jl b/src/write_outputs/write_capacityfactor.jl
index d7e5f13c6..0d9c829b7 100644
--- a/src/write_outputs/write_capacityfactor.jl
+++ b/src/write_outputs/write_capacityfactor.jl
@@ -21,14 +21,14 @@ function write_capacityfactor(path::AbstractString, inputs::Dict, setup::Dict, E
         AnnualSum = zeros(G),
         Capacity = zeros(G),
         CapacityFactor = zeros(G))
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
-    df.AnnualSum .= value.(EP[:vP]) * weight * scale_factor
-    df.Capacity .= value.(EP[:eTotalCap]) * scale_factor
+    
+    df.AnnualSum .= value.(EP[:vP]) * weight 
+    df.Capacity .= value.(EP[:eTotalCap]) 
 
     # The .data only works on DenseAxisArray variables or expressions
     # In contrast vP and eTotalCap are whole vectors / matrices
-    energy_sum(sym, set) = value.(EP[sym][set, :]).data * weight * scale_factor
-    capacity(sym, set) = value.(EP[sym][set]).data * scale_factor
+    energy_sum(sym, set) = value.(EP[sym][set, :]).data * weight 
+    capacity(sym, set) = value.(EP[sym][set]).data 
 
     if !isempty(VRE_STOR)
         VS_SOLAR = inputs["VS_SOLAR"]
@@ -94,7 +94,7 @@ function write_fusion_net_capacity_factor(path::AbstractString, inputs::Dict, se
     G_fusion = length(gen_fusion)
 
     ω = inputs["omega"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     df = DataFrame(Resource = resource_names,
         Zone = zone_id.(gen_fusion),
@@ -105,10 +105,10 @@ function write_fusion_net_capacity_factor(path::AbstractString, inputs::Dict, se
     reactor = FusionReactorData.(gen_fusion)
     avg_power_factor = average_net_power_factor.(reactor)
 
-    gross_power = value.(EP[:vP][FUSION, :]) * ω * scale_factor
+    gross_power = value.(EP[:vP][FUSION, :]) * ω 
     parasitic_power = thermal_fusion_annual_parasitic_power(EP, inputs, setup)
     df.NetOutput .= gross_power - parasitic_power
-    df.NetCapacity .= value.(EP[:eTotalCap][FUSION]) * scale_factor .* avg_power_factor
+    df.NetCapacity .= value.(EP[:eTotalCap][FUSION])  .* avg_power_factor
 
     # We only calcualte the resulted capacity factor with total capacity > 1MW and total generation > 1MWh
     enough_power = findall(x -> x >= 1, df.NetOutput)
diff --git a/src/write_outputs/write_charge.jl b/src/write_outputs/write_charge.jl
index 89d95fbb2..193938e55 100644
--- a/src/write_outputs/write_charge.jl
+++ b/src/write_outputs/write_charge.jl
@@ -17,7 +17,7 @@ function write_charge(path::AbstractString, inputs::Dict, setup::Dict, EP::Model
     FUSION = ids_with(gen, :fusion)
 
     weight = inputs["omega"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     charge = Matrix[]
     charge_ids = Vector{Int}[]
@@ -45,8 +45,6 @@ function write_charge(path::AbstractString, inputs::Dict, setup::Dict, EP::Model
     charge = reduce(vcat, charge, init = zeros(0, T))
     charge_ids = reduce(vcat, charge_ids, init = Int[])
 
-    charge *= scale_factor
-
     df = DataFrame(Resource = resources[charge_ids],
         Zone = zones[charge_ids])
     df.AnnualSum = charge * weight
diff --git a/src/write_outputs/write_charging_cost.jl b/src/write_outputs/write_charging_cost.jl
index cabc4db13..2f7d7f1d9 100644
--- a/src/write_outputs/write_charging_cost.jl
+++ b/src/write_outputs/write_charging_cost.jl
@@ -16,7 +16,7 @@ function write_charging_cost(path::AbstractString, inputs::Dict, setup::Dict, EP
     FUSION = ids_with(gen, :fusion)
 
     weight = inputs["omega"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     price = locational_marginal_price(EP, inputs, setup)
 
@@ -41,8 +41,6 @@ function write_charging_cost(path::AbstractString, inputs::Dict, setup::Dict, EP
         _, mat = prepare_fusion_parasitic_power(EP, inputs)
         chargecost[FUSION, :] = mat
     end
-    chargecost *= scale_factor
-
     dfChargingcost = DataFrame(Region = regions,
         Resource = resources,
         Zone = zones,
diff --git a/src/write_outputs/write_co2.jl b/src/write_outputs/write_co2.jl
index 5a2860d19..3211492d2 100644
--- a/src/write_outputs/write_co2.jl
+++ b/src/write_outputs/write_co2.jl
@@ -21,10 +21,10 @@ function write_co2_emissions_plant(path::AbstractString,
     G = inputs["G"]     # Number of resources (generators, storage, DR, and DERs)
 
     weight = inputs["omega"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     emissions_plant = value.(EP[:eEmissionsByPlant])
-    emissions_plant *= scale_factor
+
 
     df = DataFrame(Resource = resources,
         Zone = zones,
@@ -43,14 +43,14 @@ function write_co2_capture_plant(path::AbstractString, inputs::Dict, setup::Dict
     zones = zone_id.(gen[CCS])
 
     weight = inputs["omega"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     df = DataFrame(Resource = resources,
         Zone = zones,
         AnnualSum = zeros(length(CCS)))
     if !isempty(CCS)
         emissions_captured_plant = value.(EP[:eEmissionsCaptureByPlant]).data
-        emissions_captured_plant *= scale_factor
+
 
         df.AnnualSum .= emissions_captured_plant * weight
 
diff --git a/src/write_outputs/write_curtailment.jl b/src/write_outputs/write_curtailment.jl
index 4d4128975..43d4cc959 100644
--- a/src/write_outputs/write_curtailment.jl
+++ b/src/write_outputs/write_curtailment.jl
@@ -15,7 +15,7 @@ function write_curtailment(path::AbstractString, inputs::Dict, setup::Dict, EP::
     VRE_STOR = inputs["VRE_STOR"]
 
     weight = inputs["omega"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     curtailment = zeros(G, T)
     curtailment[VRE, :] = (value.(EP[:eTotalCap][VRE]) .* inputs["pP_Max"][VRE, :] .-
@@ -48,7 +48,7 @@ function write_curtailment(path::AbstractString, inputs::Dict, setup::Dict, EP::
         end
     end
 
-    curtailment *= scale_factor
+
 
     df = DataFrame(Resource = resources,
         Zone = zones,
diff --git a/src/write_outputs/write_emissions.jl b/src/write_outputs/write_emissions.jl
index 2e0c011f6..e5f0c5737 100644
--- a/src/write_outputs/write_emissions.jl
+++ b/src/write_outputs/write_emissions.jl
@@ -8,7 +8,7 @@ function write_emissions(path::AbstractString, inputs::Dict, setup::Dict, EP::Mo
     T = inputs["T"]     # Number of time steps (hours)
     Z = inputs["Z"]     # Number of zones
 
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     if (setup["WriteShadowPrices"] == 1 || setup["UCommit"] == 0 ||
         (setup["UCommit"] == 2 && (setup["OperationalReserves"] == 0 ||
@@ -24,7 +24,7 @@ function write_emissions(path::AbstractString, inputs::Dict, setup::Dict, EP::Mo
                         tempCO2Price[z, cap] = (-1) *
                                                dual.(EP[:cCO2Emissions_systemwide])[cap]
                         # when scaled, The objective function is in unit of Million US$/kton, thus k$/ton, to get $/ton, multiply 1000
-                        tempCO2Price[z, cap] *= scale_factor
+
                     end
                 end
             end
@@ -41,8 +41,7 @@ function write_emissions(path::AbstractString, inputs::Dict, setup::Dict, EP::Mo
 
         emissions_by_zone = value.(EP[:eEmissionsByZone])
         for i in 1:Z
-            dfEmissions[i, :AnnualSum] = sum(inputs["omega"] .* emissions_by_zone[i, :]) *
-                                         scale_factor
+            dfEmissions[i, :AnnualSum] = sum(inputs["omega"] .* emissions_by_zone[i, :])
         end
 
         if setup["WriteOutputs"] == "annual"
@@ -58,7 +57,7 @@ function write_emissions(path::AbstractString, inputs::Dict, setup::Dict, EP::Mo
             CSV.write(joinpath(path, "emissions.csv"), dfEmissions)
         else# setup["WriteOutputs"] == "full"
             dfEmissions = hcat(dfEmissions,
-                DataFrame(emissions_by_zone * scale_factor, :auto))
+                DataFrame(emissions_by_zone , :auto))
             if setup["CO2Cap"] >= 1
                 auxNew_Names = [Symbol("Zone");
                                 [Symbol("CO2_Price_$cap") for cap in 1:inputs["NCO2Cap"]];
@@ -99,8 +98,7 @@ function write_emissions(path::AbstractString, inputs::Dict, setup::Dict, EP::Mo
         dfEmissions = hcat(DataFrame(Zone = 1:Z),
             DataFrame(AnnualSum = Array{Float64}(undef, Z)))
         for i in 1:Z
-            dfEmissions[i, :AnnualSum] = sum(inputs["omega"] .* emissions_by_zone[i, :]) *
-                                         scale_factor
+            dfEmissions[i, :AnnualSum] = sum(inputs["omega"] .* emissions_by_zone[i, :])
         end
 
         if setup["WriteOutputs"] == "annual"
@@ -109,7 +107,7 @@ function write_emissions(path::AbstractString, inputs::Dict, setup::Dict, EP::Mo
             CSV.write(joinpath(path, "emissions.csv"), dfEmissions)
         else# setup["WriteOutputs"] == "full"
             dfEmissions = hcat(dfEmissions,
-                DataFrame(emissions_by_zone * scale_factor, :auto))
+                DataFrame(emissions_by_zone , :auto))
             auxNew_Names = [Symbol("Zone");
                             Symbol("AnnualSum");
                             [Symbol("t$t") for t in 1:T]]
diff --git a/src/write_outputs/write_nse.jl b/src/write_outputs/write_nse.jl
index 9d1c73e83..649013801 100644
--- a/src/write_outputs/write_nse.jl
+++ b/src/write_outputs/write_nse.jl
@@ -12,9 +12,9 @@ function write_nse(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
         Zone = repeat(1:Z, inner = SEG),
         AnnualSum = zeros(SEG * Z))
     nse = zeros(SEG * Z, T)
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
     for z in 1:Z
-        nse[((z - 1) * SEG + 1):(z * SEG), :] = value.(EP[:vNSE])[:, :, z] * scale_factor
+        nse[((z - 1) * SEG + 1):(z * SEG), :] = value.(EP[:vNSE])[:, :, z] 
     end
     dfNse.AnnualSum .= nse * inputs["omega"]
 
diff --git a/src/write_outputs/write_power.jl b/src/write_outputs/write_power.jl
index 995a2d941..b7789f7b1 100644
--- a/src/write_outputs/write_power.jl
+++ b/src/write_outputs/write_power.jl
@@ -12,11 +12,11 @@ function write_power(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
     T = inputs["T"]     # Number of time steps (hours)
     
     weight = inputs["omega"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     # Power injected by each resource in each time step
     power = value.(EP[:vP])
-    power *= scale_factor
+
 
     df = DataFrame(Resource = resources,
         Zone = zones,
diff --git a/src/write_outputs/write_price.jl b/src/write_outputs/write_price.jl
index 79afb5b42..611eab4b4 100644
--- a/src/write_outputs/write_price.jl
+++ b/src/write_outputs/write_price.jl
@@ -43,6 +43,6 @@ be calculated only if `WriteShadowPrices` is activated.
 """
 function locational_marginal_price(EP::Model, inputs::Dict, setup::Dict)::Matrix{Float64}
     ω = inputs["omega"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
-    return dual.(EP[:cPowerBalance]) ./ ω * scale_factor
+    
+    return dual.(EP[:cPowerBalance]) ./ ω 
 end
diff --git a/src/write_outputs/write_reliability.jl b/src/write_outputs/write_reliability.jl
index afb3a3284..b0330a914 100644
--- a/src/write_outputs/write_reliability.jl
+++ b/src/write_outputs/write_reliability.jl
@@ -10,9 +10,9 @@ function write_reliability(path::AbstractString, inputs::Dict, setup::Dict, EP::
     # reliability: Dual variable of maximum NSE constraint = shadow value of reliability constraint
     dfReliability = DataFrame(Zone = 1:Z)
     # Dividing dual variable for each hour with corresponding hourly weight to retrieve marginal cost of generation
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
     dfReliability = hcat(dfReliability,
-        DataFrame(transpose(dual.(EP[:cMaxNSE]) ./ inputs["omega"] * scale_factor), :auto))
+        DataFrame(transpose(dual.(EP[:cMaxNSE]) ./ inputs["omega"] ), :auto))
 
     auxNew_Names = [Symbol("Zone"); [Symbol("t$t") for t in 1:T]]
     rename!(dfReliability, auxNew_Names)
diff --git a/src/write_outputs/write_storage.jl b/src/write_outputs/write_storage.jl
index 4e64c0f9b..1420bf1a6 100644
--- a/src/write_outputs/write_storage.jl
+++ b/src/write_outputs/write_storage.jl
@@ -17,7 +17,7 @@ function write_storage(path::AbstractString, inputs::Dict, setup::Dict, EP::Mode
     VS_STOR = !isempty(VRE_STOR) ? inputs["VS_STOR"] : []
 
     weight = inputs["omega"]
-    scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
+    
 
     stored = Matrix[]
     if !isempty(STOR_ALL)
@@ -33,7 +33,7 @@ function write_storage(path::AbstractString, inputs::Dict, setup::Dict, EP::Mode
         push!(stored, value.(EP[:vS_VRE_STOR]))
     end
     stored = reduce(vcat, stored, init = zeros(0, T))
-    stored *= scale_factor
+
 
     stored_ids = convert(Vector{Int}, vcat(STOR_ALL, HYDRO_RES, FLEX, VS_STOR))
     df = DataFrame(Resource = resources[stored_ids],
diff --git a/test/test_load_resource_data.jl b/test/test_load_resource_data.jl
index 00d979b19..5ae72f7dc 100644
--- a/test/test_load_resource_data.jl
+++ b/test/test_load_resource_data.jl
@@ -34,9 +34,8 @@ function prepare_inputs_true(test_path::AbstractString,
     gen_filename = in_filenames.gen_filename
     inputs_filename = in_filenames.inputs_filename
     dfGen = GenX.load_dataframe(joinpath(test_path, gen_filename))
-    scale_factor = setup["ParameterScale"] == 1 ? GenX.ModelScalingFactor : 1.0
     GenX.rename!(dfGen, lowercase.(names(dfGen)))
-    GenX.scale_resources_data!(dfGen, scale_factor)
+    GenX.scale_resources_data!(dfGen)
     dfGen[!, :r_id] = 1:size(dfGen, 1)
     inputs_true = load(joinpath(test_path, inputs_filename))
     return dfGen, inputs_true
@@ -308,8 +307,7 @@ function test_load_VRE_STOR_data()
 
     dfVRE_STOR = GenX.load_dataframe(joinpath(test_path, "Vre_and_stor_data.csv"))
     dfVRE_STOR = GenX.rename!(dfVRE_STOR, lowercase.(names(dfVRE_STOR)))
-    scale_factor = settings["ParameterScale"] == 1 ? GenX.ModelScalingFactor : 1.0
-    GenX.scale_vre_stor_data!(dfVRE_STOR, scale_factor)
+    GenX.scale_vre_stor_data!(dfVRE_STOR)
 
     resources_path = joinpath(test_path, settings["ResourcesFolder"])
     gen = GenX.create_resource_array(settings, resources_path)
diff --git a/test/test_multistage.jl b/test/test_multistage.jl
index eba9201a1..d593e41d1 100644
--- a/test/test_multistage.jl
+++ b/test/test_multistage.jl
@@ -109,7 +109,6 @@ function test_update_cumulative_min_ret!()
         inputs_dict = Dict()
         true_min_retirements = Dict()
 
-        scale_factor = settings["ParameterScale"] == 1 ? GenX.ModelScalingFactor : 1.0
         redirect_stdout(devnull) do
             warnerror_logger = ConsoleLogger(stderr, Logging.Warn)
             with_logger(warnerror_logger) do
@@ -123,7 +122,7 @@ function test_update_cumulative_min_ret!()
                         DataFrame)
                     rename!(true_min_retirements[t],
                         lowercase.(names(true_min_retirements[t])))
-                    GenX.scale_multistage_data!(true_min_retirements[t], scale_factor)
+                    GenX.scale_multistage_data!(true_min_retirements[t])
 
                     inputs_dict[t] = Dict()
                     inputs_dict[t]["Z"] = 1

From c7ae2a02721b43d54c5064b6770b0b4684d843b0 Mon Sep 17 00:00:00 2001
From: Ruaridh Macdonald <rmacd@mit.edu>
Date: Thu, 14 Nov 2024 05:36:56 -0500
Subject: [PATCH 03/11] Swap load_resource_df arg order to allow default
 scale_factor

---
 src/load_inputs/load_resources_data.jl | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/src/load_inputs/load_resources_data.jl b/src/load_inputs/load_resources_data.jl
index 6049da599..86188e45a 100644
--- a/src/load_inputs/load_resources_data.jl
+++ b/src/load_inputs/load_resources_data.jl
@@ -214,20 +214,20 @@ function scale_columns!(df::DataFrame,
 end
 
 """
-    load_resource_df(path::AbstractString, scale_factor::Float64=1.0, resource_type::Type)
+    load_resource_df(path::AbstractString, resource_type::Type, scale_factor::Float64=1.0)
 
 Function to load and scale the dataframe of a given resource.
 
 # Arguments
 - `path::AbstractString`: Path to the resource dataframe.
-- `scale_factor::Float64=1.0`: Scaling factor for the resource data.
 - `resource_type::Type`: GenX type of the resource.
+- `scale_factor::Float64=1.0`: Scaling factor for the resource data.
 
 # Returns
 - `resource_in::DataFrame`: The loaded and scaled resource data.
 
 """
-function load_resource_df(path::AbstractString, scale_factor::Float64=1.0, resource_type::Type)
+function load_resource_df(path::AbstractString, resource_type::Type, scale_factor::Float64=1.0)
     resource_in = load_dataframe(path)
     # rename columns lowercase for internal consistency
     rename!(resource_in, lowercase.(names(resource_in)))
@@ -303,7 +303,7 @@ function create_resources_sametype(resource_in::DataFrame, ResourceType)
 end
 
 """
-    create_resource_array(resource_folder::AbstractString, resources_info::NamedTuple, scale_factor::Float64=1.0=1.0)
+    create_resource_array(resource_folder::AbstractString, resources_info::NamedTuple, scale_factor::Float64=1.0)
 
 Construct the array of resources from multiple files of different types located in the specified `resource_folder`. The `resources_info` NamedTuple contains the filename and GenX type for each type of resource available in GenX.
 
@@ -329,7 +329,7 @@ function create_resource_array(resource_folder::AbstractString,
         df_path = joinpath(resource_folder, filename)
         # if file exists, load resources of a single resource_type
         if isfile(df_path)
-            resource_in = load_resource_df(df_path, scale_factor, resource_type)
+            resource_in = load_resource_df(df_path, resource_type, scale_factor)
             # compute indices for resources of a given type and add them to dataframe
             resources_indices = compute_resource_indices(resource_in, resource_id_offset)
             add_id_to_resource_df!(resource_in, resources_indices)

From 6ff2d353ef27d5b517845803cb88a523fb6953f9 Mon Sep 17 00:00:00 2001
From: Ruaridh Macdonald <rmacd@mit.edu>
Date: Thu, 14 Nov 2024 05:48:07 -0500
Subject: [PATCH 04/11] Remove ParameterScale

---
 .../Tutorial_1_configuring_settings.md        |  1 -
 ...utorial_3_K-means_time_domain_reduction.md |  2 -
 .../Tutorials/Tutorial_4_model_generation.md  |  1 -
 docs/src/Tutorials/Tutorial_7_setup.md        |  1 -
 docs/src/User_Guide/model_configuration.md    |  2 +-
 .../1_three_zones/settings/genx_settings.yml  |  4 +-
 .../settings/genx_settings.yml                |  1 -
 .../settings/genx_settings.yml                |  1 -
 .../settings/genx_settings.yml                |  1 -
 .../settings/genx_settings.yml                |  1 -
 .../settings/genx_settings.yml                |  1 -
 .../settings/genx_settings.yml                |  1 -
 .../settings/genx_settings.yml                |  1 -
 .../settings/genx_settings.yml                |  1 -
 precompile/case/settings/genx_settings.yml    |  1 -
 src/GenX.jl                                   |  7 --
 .../load_minimum_capacity_requirement.jl      |  6 --
 .../write_reserve_margin.jl                   |  3 -
 .../write_reserve_margin_slack.jl             |  8 ---
 .../write_reserve_margin_w.jl                 |  3 -
 src/write_outputs/co2_cap/write_co2_cap.jl    |  7 --
 .../write_esr_prices.jl                       |  7 --
 .../write_opwrap_lds_dstor.jl                 |  3 -
 .../write_opwrap_lds_stor_init.jl             |  3 -
 .../transmission/write_nw_expansion.jl        |  5 --
 .../transmission/write_transmission_flows.jl  |  3 -
 .../transmission/write_transmission_losses.jl |  3 -
 src/write_outputs/write_capacity.jl           | 16 -----
 src/write_outputs/write_costs.jl              | 25 +------
 src/write_outputs/write_energy_revenue.jl     |  3 -
 src/write_outputs/write_fuel_consumption.jl   | 15 ----
 src/write_outputs/write_net_revenue.jl        | 26 -------
 src/write_outputs/write_power_balance.jl      |  3 -
 src/write_outputs/write_storagedual.jl        |  4 --
 src/write_outputs/write_subsidy_revenue.jl    |  5 --
 src/write_outputs/write_vre_stor.jl           | 70 +------------------
 .../settings/genx_settings.yml                |  1 -
 .../settings/genx_settings.yml                |  1 -
 test/test_VRE_storage.jl                      |  3 +-
 test/test_electrolyzer.jl                     |  1 -
 test/test_fusion.jl                           |  4 +-
 test/test_load_resource_data.jl               |  4 +-
 test/test_multifuels.jl                       |  1 -
 test/test_multistage.jl                       |  5 +-
 test/test_piecewisefuel.jl                    |  6 +-
 test/test_retrofit.jl                         |  4 +-
 test/test_threezones.jl                       |  1 -
 47 files changed, 19 insertions(+), 257 deletions(-)

diff --git a/docs/src/Tutorials/Tutorial_1_configuring_settings.md b/docs/src/Tutorials/Tutorial_1_configuring_settings.md
index c7d8c7f08..cb5603dcf 100644
--- a/docs/src/Tutorials/Tutorial_1_configuring_settings.md
+++ b/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
diff --git a/docs/src/Tutorials/Tutorial_3_K-means_time_domain_reduction.md b/docs/src/Tutorials/Tutorial_3_K-means_time_domain_reduction.md
index 5d56315d4..37507a98b 100644
--- a/docs/src/Tutorials/Tutorial_3_K-means_time_domain_reduction.md
+++ b/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
diff --git a/docs/src/Tutorials/Tutorial_4_model_generation.md b/docs/src/Tutorials/Tutorial_4_model_generation.md
index 0d50bab76..96911a056 100644
--- a/docs/src/Tutorials/Tutorial_4_model_generation.md
+++ b/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
diff --git a/docs/src/Tutorials/Tutorial_7_setup.md b/docs/src/Tutorials/Tutorial_7_setup.md
index 53dfe6ea6..d0a9c0e28 100644
--- a/docs/src/Tutorials/Tutorial_7_setup.md
+++ b/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
diff --git a/docs/src/User_Guide/model_configuration.md b/docs/src/User_Guide/model_configuration.md
index a1526b3ea..8fb4fe5dc 100644
--- a/docs/src/User_Guide/model_configuration.md
+++ b/docs/src/User_Guide/model_configuration.md
@@ -45,7 +45,7 @@ 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.|
diff --git a/example_systems/1_three_zones/settings/genx_settings.yml b/example_systems/1_three_zones/settings/genx_settings.yml
index d48032b1d..1acd7a883 100644
--- a/example_systems/1_three_zones/settings/genx_settings.yml
+++ b/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
\ No newline at end of file
+OutputFullTimeSeries: 1
+AutoScaling : 1
\ No newline at end of file
diff --git a/example_systems/2_three_zones_w_electrolyzer/settings/genx_settings.yml b/example_systems/2_three_zones_w_electrolyzer/settings/genx_settings.yml
index 3c3f4d572..b6d6ff6e0 100644
--- a/example_systems/2_three_zones_w_electrolyzer/settings/genx_settings.yml
+++ b/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
diff --git a/example_systems/3_three_zones_w_co2_capture/settings/genx_settings.yml b/example_systems/3_three_zones_w_co2_capture/settings/genx_settings.yml
index 27f3eef52..72647ea81 100644
--- a/example_systems/3_three_zones_w_co2_capture/settings/genx_settings.yml
+++ b/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) 
diff --git a/example_systems/4_three_zones_w_policies_slack/settings/genx_settings.yml b/example_systems/4_three_zones_w_policies_slack/settings/genx_settings.yml
index 2aeabd9a6..9febaf6f6 100644
--- a/example_systems/4_three_zones_w_policies_slack/settings/genx_settings.yml
+++ b/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)
diff --git a/example_systems/5_three_zones_w_piecewise_fuel/settings/genx_settings.yml b/example_systems/5_three_zones_w_piecewise_fuel/settings/genx_settings.yml
index fdd18b230..8139d00a3 100644
--- a/example_systems/5_three_zones_w_piecewise_fuel/settings/genx_settings.yml
+++ b/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)
diff --git a/example_systems/6_three_zones_w_multistage/settings/genx_settings.yml b/example_systems/6_three_zones_w_multistage/settings/genx_settings.yml
index e9599523c..36e7fa1f9 100644
--- a/example_systems/6_three_zones_w_multistage/settings/genx_settings.yml
+++ b/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
diff --git a/example_systems/7_three_zones_w_colocated_VRE_storage/settings/genx_settings.yml b/example_systems/7_three_zones_w_colocated_VRE_storage/settings/genx_settings.yml
index a4039ad2e..7230a35a0 100644
--- a/example_systems/7_three_zones_w_colocated_VRE_storage/settings/genx_settings.yml
+++ b/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
diff --git a/example_systems/8_three_zones_w_colocated_VRE_storage_electrolyzers/settings/genx_settings.yml b/example_systems/8_three_zones_w_colocated_VRE_storage_electrolyzers/settings/genx_settings.yml
index c53bd4b62..717ef8f2a 100644
--- a/example_systems/8_three_zones_w_colocated_VRE_storage_electrolyzers/settings/genx_settings.yml
+++ b/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
\ No newline at end of file
diff --git a/example_systems/9_three_zones_w_retrofit/settings/genx_settings.yml b/example_systems/9_three_zones_w_retrofit/settings/genx_settings.yml
index 96854d022..772ff0663 100644
--- a/example_systems/9_three_zones_w_retrofit/settings/genx_settings.yml
+++ b/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)
\ No newline at end of file
diff --git a/precompile/case/settings/genx_settings.yml b/precompile/case/settings/genx_settings.yml
index 2d6600608..a72528fbe 100644
--- a/precompile/case/settings/genx_settings.yml
+++ b/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
\ No newline at end of file
diff --git a/src/GenX.jl b/src/GenX.jl
index 5be926316..54a6f842c 100644
--- a/src/GenX.jl
+++ b/src/GenX.jl
@@ -41,13 +41,6 @@ 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.
 """
diff --git a/src/load_inputs/load_minimum_capacity_requirement.jl b/src/load_inputs/load_minimum_capacity_requirement.jl
index e0561b126..1ab6fd695 100644
--- a/src/load_inputs/load_minimum_capacity_requirement.jl
+++ b/src/load_inputs/load_minimum_capacity_requirement.jl
@@ -9,14 +9,8 @@ function load_minimum_capacity_requirement!(path::AbstractString, inputs::Dict,
     NumberOfMinCapReqs = length(df[!, :MinCapReqConstraint])
     inputs["NumberOfMinCapReqs"] = NumberOfMinCapReqs
     inputs["MinCapReq"] = df[!, :Min_MW]
-    if setup["ParameterScale"] == 1
-        inputs["MinCapReq"] /= ModelScalingFactor # Convert to GW
-    end
     if "PriceCap" in names(df)
         inputs["MinCapPriceCap"] = df[!, :PriceCap]
-        if setup["ParameterScale"] == 1
-            inputs["MinCapPriceCap"] /= ModelScalingFactor # Convert to million $/GW
-        end
     end
     println(filename * " Successfully Read!")
 end
diff --git a/src/write_outputs/capacity_reserve_margin/write_reserve_margin.jl b/src/write_outputs/capacity_reserve_margin/write_reserve_margin.jl
index 1eeca0ef0..107ae72a2 100644
--- a/src/write_outputs/capacity_reserve_margin/write_reserve_margin.jl
+++ b/src/write_outputs/capacity_reserve_margin/write_reserve_margin.jl
@@ -1,8 +1,5 @@
 function write_reserve_margin(path::AbstractString, setup::Dict, EP::Model)
     temp_ResMar = dual.(EP[:cCapacityResMargin])
-    if setup["ParameterScale"] == 1
-        temp_ResMar = temp_ResMar * ModelScalingFactor # Convert from MillionUS$/GWh to US$/MWh
-    end
     dfResMar = DataFrame(temp_ResMar, :auto)
     CSV.write(joinpath(path, "ReserveMargin.csv"), dfResMar)
     return nothing
diff --git a/src/write_outputs/capacity_reserve_margin/write_reserve_margin_slack.jl b/src/write_outputs/capacity_reserve_margin/write_reserve_margin_slack.jl
index f6d71e4fb..9ab0d126c 100644
--- a/src/write_outputs/capacity_reserve_margin/write_reserve_margin_slack.jl
+++ b/src/write_outputs/capacity_reserve_margin/write_reserve_margin_slack.jl
@@ -8,18 +8,10 @@ function write_reserve_margin_slack(path::AbstractString,
         AnnualSum = value.(EP[:eCapResSlack_Year]),
         Penalty = value.(EP[:eCCapResSlack]))
 
-    if setup["ParameterScale"] == 1
-        dfResMar_slack.AnnualSum .*= ModelScalingFactor # Convert GW to MW
-        dfResMar_slack.Penalty .*= ModelScalingFactor^2 # Convert Million $ to $
-    end
-
     if setup["WriteOutputs"] == "annual"
         CSV.write(joinpath(path, "ReserveMargin_prices_and_penalties.csv"), dfResMar_slack)
     else     # setup["WriteOutputs"] == "full"
         temp_ResMar_slack = value.(EP[:vCapResSlack])
-        if setup["ParameterScale"] == 1
-            temp_ResMar_slack .*= ModelScalingFactor # Convert GW to MW
-        end
         dfResMar_slack = hcat(dfResMar_slack,
             DataFrame(temp_ResMar_slack, [Symbol("t$t") for t in 1:T]))
         CSV.write(joinpath(path, "ReserveMargin_prices_and_penalties.csv"),
diff --git a/src/write_outputs/capacity_reserve_margin/write_reserve_margin_w.jl b/src/write_outputs/capacity_reserve_margin/write_reserve_margin_w.jl
index 74b4efa7f..5299ce072 100644
--- a/src/write_outputs/capacity_reserve_margin/write_reserve_margin_w.jl
+++ b/src/write_outputs/capacity_reserve_margin/write_reserve_margin_w.jl
@@ -3,9 +3,6 @@ function write_reserve_margin_w(path::AbstractString, inputs::Dict, setup::Dict,
     #dfResMar dataframe with weights included for calculations
     dfResMar_w = DataFrame(Constraint = [Symbol("t$t") for t in 1:T])
     temp_ResMar_w = transpose(dual.(EP[:cCapacityResMargin])) ./ inputs["omega"]
-    if setup["ParameterScale"] == 1
-        temp_ResMar_w = temp_ResMar_w * ModelScalingFactor # Convert from MillionUS$/GWh to US$/MWh
-    end
     dfResMar_w = hcat(dfResMar_w, DataFrame(temp_ResMar_w, :auto))
     auxNew_Names_res = [Symbol("Constraint");
                         [Symbol("CapRes_$i") for i in 1:inputs["NCapacityReserveMargin"]]]
diff --git a/src/write_outputs/co2_cap/write_co2_cap.jl b/src/write_outputs/co2_cap/write_co2_cap.jl
index 19cba87d7..8b486a977 100644
--- a/src/write_outputs/co2_cap/write_co2_cap.jl
+++ b/src/write_outputs/co2_cap/write_co2_cap.jl
@@ -8,16 +8,9 @@ function write_co2_cap(path::AbstractString, inputs::Dict, setup::Dict, EP::Mode
     dfCO2Price = DataFrame(
         CO2_Cap = [Symbol("CO2_Cap_$cap") for cap in 1:inputs["NCO2Cap"]],
         CO2_Price = (-1) * (dual.(EP[:cCO2Emissions_systemwide])))
-    if setup["ParameterScale"] == 1
-        dfCO2Price.CO2_Price .*= ModelScalingFactor # Convert Million$/kton to $/ton
-    end
     if haskey(inputs, "dfCO2Cap_slack")
         dfCO2Price[!, :CO2_Mass_Slack] = convert(Array{Float64}, value.(EP[:vCO2Cap_slack]))
         dfCO2Price[!, :CO2_Penalty] = convert(Array{Float64}, value.(EP[:eCCO2Cap_slack]))
-        if setup["ParameterScale"] == 1
-            dfCO2Price.CO2_Mass_Slack .*= ModelScalingFactor # Convert ktons to tons
-            dfCO2Price.CO2_Penalty .*= ModelScalingFactor^2 # Convert Million$ to $
-        end
     end
 
     CSV.write(joinpath(path, "CO2_prices_and_penalties.csv"), dfCO2Price)
diff --git a/src/write_outputs/energy_share_requirement/write_esr_prices.jl b/src/write_outputs/energy_share_requirement/write_esr_prices.jl
index e9cccc46a..0fe94e566 100644
--- a/src/write_outputs/energy_share_requirement/write_esr_prices.jl
+++ b/src/write_outputs/energy_share_requirement/write_esr_prices.jl
@@ -1,16 +1,9 @@
 function write_esr_prices(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
     dfESR = DataFrame(ESR_Price = convert(Array{Float64}, dual.(EP[:cESRShare])))
-    if setup["ParameterScale"] == 1
-        dfESR[!, :ESR_Price] = dfESR[!, :ESR_Price] * ModelScalingFactor # Converting MillionUS$/GWh to US$/MWh
-    end
 
     if haskey(inputs, "dfESR_slack")
         dfESR[!, :ESR_AnnualSlack] = convert(Array{Float64}, value.(EP[:vESR_slack]))
         dfESR[!, :ESR_AnnualPenalty] = convert(Array{Float64}, value.(EP[:eCESRSlack]))
-        if setup["ParameterScale"] == 1
-            dfESR[!, :ESR_AnnualSlack] *= ModelScalingFactor # Converting GWh to MWh
-            dfESR[!, :ESR_AnnualPenalty] *= (ModelScalingFactor^2) # Converting MillionUSD to USD
-        end
     end
     CSV.write(joinpath(path, "ESR_prices_and_penalties.csv"), dfESR)
     return dfESR
diff --git a/src/write_outputs/long_duration_storage/write_opwrap_lds_dstor.jl b/src/write_outputs/long_duration_storage/write_opwrap_lds_dstor.jl
index 875d8e6f8..a318fa3e6 100644
--- a/src/write_outputs/long_duration_storage/write_opwrap_lds_dstor.jl
+++ b/src/write_outputs/long_duration_storage/write_opwrap_lds_dstor.jl
@@ -19,9 +19,6 @@ function write_opwrap_lds_dstor(path::AbstractString, inputs::Dict, setup::Dict,
             end
         end
     end
-    if setup["ParameterScale"] == 1
-        dsoc *= ModelScalingFactor
-    end
 
     dfdStorage = hcat(dfdStorage, DataFrame(dsoc, :auto))
     auxNew_Names = [Symbol("Resource"); Symbol("Zone"); [Symbol("w$t") for t in 1:W]]
diff --git a/src/write_outputs/long_duration_storage/write_opwrap_lds_stor_init.jl b/src/write_outputs/long_duration_storage/write_opwrap_lds_stor_init.jl
index e0a731d17..bdcba9e9b 100644
--- a/src/write_outputs/long_duration_storage/write_opwrap_lds_stor_init.jl
+++ b/src/write_outputs/long_duration_storage/write_opwrap_lds_stor_init.jl
@@ -22,9 +22,6 @@ function write_opwrap_lds_stor_init(path::AbstractString,
             end
         end
     end
-    if setup["ParameterScale"] == 1
-        socw *= ModelScalingFactor
-    end
 
     dfStorageInit = hcat(dfStorageInit, DataFrame(socw, :auto))
     auxNew_Names = [Symbol("Resource"); Symbol("Zone"); [Symbol("n$t") for t in 1:NPeriods]]
diff --git a/src/write_outputs/transmission/write_nw_expansion.jl b/src/write_outputs/transmission/write_nw_expansion.jl
index f89e1bfe1..6ec1ceeb6 100644
--- a/src/write_outputs/transmission/write_nw_expansion.jl
+++ b/src/write_outputs/transmission/write_nw_expansion.jl
@@ -14,10 +14,5 @@ function write_nw_expansion(path::AbstractString, inputs::Dict, setup::Dict, EP:
         Cost_Trans_Capacity = convert(Array{Float64},
             transcap .* inputs["pC_Line_Reinforcement"]))
 
-    if setup["ParameterScale"] == 1
-        dfTransCap.New_Trans_Capacity *= ModelScalingFactor  # GW to MW
-        dfTransCap.Cost_Trans_Capacity *= ModelScalingFactor^2  # MUSD to USD
-    end
-
     CSV.write(joinpath(path, "network_expansion.csv"), dfTransCap)
 end
diff --git a/src/write_outputs/transmission/write_transmission_flows.jl b/src/write_outputs/transmission/write_transmission_flows.jl
index 5290d71af..e13179f6e 100644
--- a/src/write_outputs/transmission/write_transmission_flows.jl
+++ b/src/write_outputs/transmission/write_transmission_flows.jl
@@ -8,9 +8,6 @@ function write_transmission_flows(path::AbstractString,
     # Power flows on transmission lines at each time step
     dfFlow = DataFrame(Line = 1:L)
     flow = value.(EP[:vFLOW])
-    if setup["ParameterScale"] == 1
-        flow *= ModelScalingFactor
-    end
 
     filepath = joinpath(path, "flow.csv")
     if setup["WriteOutputs"] == "annual"
diff --git a/src/write_outputs/transmission/write_transmission_losses.jl b/src/write_outputs/transmission/write_transmission_losses.jl
index a76bca118..d5ef53809 100644
--- a/src/write_outputs/transmission/write_transmission_losses.jl
+++ b/src/write_outputs/transmission/write_transmission_losses.jl
@@ -9,9 +9,6 @@ function write_transmission_losses(path::AbstractString,
     dfTLosses = DataFrame(Line = 1:L)
     tlosses = zeros(L, T)
     tlosses[LOSS_LINES, :] = value.(EP[:vTLOSS][LOSS_LINES, :])
-    if setup["ParameterScale"] == 1
-        tlosses[LOSS_LINES, :] *= ModelScalingFactor
-    end
 
     dfTLosses.AnnualSum = tlosses * inputs["omega"]
 
diff --git a/src/write_outputs/write_capacity.jl b/src/write_outputs/write_capacity.jl
index 99e4797ec..b00b5c76c 100755
--- a/src/write_outputs/write_capacity.jl
+++ b/src/write_outputs/write_capacity.jl
@@ -96,22 +96,6 @@ function write_capacity(path::AbstractString, inputs::Dict, setup::Dict, EP::Mod
         RetChargeCap = retcapcharge[:],
         NewChargeCap = capcharge[:],
         EndChargeCap = existingcapcharge[:] - retcapcharge[:] + capcharge[:])
-    if setup["ParameterScale"] == 1
-        dfCap.StartCap = dfCap.StartCap * ModelScalingFactor
-        dfCap.RetCap = dfCap.RetCap * ModelScalingFactor
-        dfCap.RetroCap = dfCap.RetroCap * ModelScalingFactor
-        dfCap.NewCap = dfCap.NewCap * ModelScalingFactor
-        dfCap.EndCap = dfCap.EndCap * ModelScalingFactor
-        dfCap.CapacityConstraintDual = dfCap.CapacityConstraintDual * ModelScalingFactor
-        dfCap.StartEnergyCap = dfCap.StartEnergyCap * ModelScalingFactor
-        dfCap.RetEnergyCap = dfCap.RetEnergyCap * ModelScalingFactor
-        dfCap.NewEnergyCap = dfCap.NewEnergyCap * ModelScalingFactor
-        dfCap.EndEnergyCap = dfCap.EndEnergyCap * ModelScalingFactor
-        dfCap.StartChargeCap = dfCap.StartChargeCap * ModelScalingFactor
-        dfCap.RetChargeCap = dfCap.RetChargeCap * ModelScalingFactor
-        dfCap.NewChargeCap = dfCap.NewChargeCap * ModelScalingFactor
-        dfCap.EndChargeCap = dfCap.EndChargeCap * ModelScalingFactor
-    end
     total = DataFrame(Resource = "Total", Zone = "n/a", Retrofit_Id = "n/a",
         StartCap = sum(dfCap[!, :StartCap]), RetCap = sum(dfCap[!, :RetCap]),
         NewCap = sum(dfCap[!, :NewCap]), EndCap = sum(dfCap[!, :EndCap]),
diff --git a/src/write_outputs/write_costs.jl b/src/write_outputs/write_costs.jl
index 919386591..e3b228e0b 100644
--- a/src/write_outputs/write_costs.jl
+++ b/src/write_outputs/write_costs.jl
@@ -95,10 +95,6 @@ function write_costs(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
 
     dfCost[!, Symbol("Total")] = total_cost
 
-    if setup["ParameterScale"] == 1
-        dfCost.Total *= ModelScalingFactor^2
-    end
-
     if setup["UCommit"] >= 1
         dfCost[6, 2] = value(EP[:eTotalCStart]) + value(EP[:eTotalCFuelStart])
     end
@@ -136,22 +132,13 @@ function write_costs(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
     end
 
     if !isempty(VRE_STOR)
-        dfCost[!, 2][11] = value(EP[:eTotalCGrid]) *
-                           (setup["ParameterScale"] == 1 ? ModelScalingFactor^2 : 1)
+        dfCost[!, 2][11] = value(EP[:eTotalCGrid])
     end
 
     if any(co2_capture_fraction.(gen) .!= 0)
         dfCost[10, 2] += value(EP[:eTotaleCCO2Sequestration])
     end
 
-    if setup["ParameterScale"] == 1
-        dfCost[6, 2] *= ModelScalingFactor^2
-        dfCost[7, 2] *= ModelScalingFactor^2
-        dfCost[8, 2] *= ModelScalingFactor^2
-        dfCost[9, 2] *= ModelScalingFactor^2
-        dfCost[10, 2] *= ModelScalingFactor^2
-    end
-
     for z in 1:Z
         tempCTotal = 0.0
         tempCFix = 0.0
@@ -297,16 +284,6 @@ function write_costs(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
             tempCTotal += tempCCO2
         end
 
-        if setup["ParameterScale"] == 1
-            tempCTotal *= ModelScalingFactor^2
-            tempCFix *= ModelScalingFactor^2
-            tempCVar *= ModelScalingFactor^2
-            tempCFuel *= ModelScalingFactor^2
-            tempCNSE *= ModelScalingFactor^2
-            tempCStart *= ModelScalingFactor^2
-            tempHydrogenValue *= ModelScalingFactor^2
-            tempCCO2 *= ModelScalingFactor^2
-        end
         temp_cost_list = [
             tempCTotal,
             tempCFix,
diff --git a/src/write_outputs/write_energy_revenue.jl b/src/write_outputs/write_energy_revenue.jl
index 3e0834bd1..60f502b24 100644
--- a/src/write_outputs/write_energy_revenue.jl
+++ b/src/write_outputs/write_energy_revenue.jl
@@ -26,9 +26,6 @@ function write_energy_revenue(path::AbstractString, inputs::Dict, setup::Dict, E
         energyrevenue[FLEX, :] = value.(EP[:vCHARGE_FLEX][FLEX, :]).data .*
                                  transpose(price)[zone_id.(gen[FLEX]), :]
     end
-    if setup["ParameterScale"] == 1
-        energyrevenue *= ModelScalingFactor
-    end
     dfEnergyRevenue.AnnualSum .= energyrevenue * inputs["omega"]
     write_simple_csv(joinpath(path, "EnergyRevenue.csv"), dfEnergyRevenue)
     return dfEnergyRevenue
diff --git a/src/write_outputs/write_fuel_consumption.jl b/src/write_outputs/write_fuel_consumption.jl
index 8385e3e5c..662fdb948 100644
--- a/src/write_outputs/write_fuel_consumption.jl
+++ b/src/write_outputs/write_fuel_consumption.jl
@@ -46,12 +46,6 @@ function write_fuel_consumption_plant(path::AbstractString,
                 tempannualsum_fuel_heat_multi_total[findfirst(x -> x == g, HAS_FUEL)] = value.(EP[:ePlantFuelConsumptionYear_multi][g,i])
                 tempannualsum_fuel_cost_multi[findfirst(x -> x == g, HAS_FUEL)] = value.(EP[:ePlantCFuelOut_multi][g,i]) + value.(EP[:ePlantCFuelOut_multi_start][g,i])
             end
-            if setup["ParameterScale"] == 1
-                tempannualsum_fuel_heat_multi_generation *= ModelScalingFactor
-                tempannualsum_fuel_heat_multi_start *= ModelScalingFactor
-                tempannualsum_fuel_heat_multi_total *= ModelScalingFactor
-                tempannualsum_fuel_cost_multi *= ModelScalingFactor^2
-            end
 
             dfPlantFuel[!, fuel_cols_num[i]] = fuel_cols.(gen[HAS_FUEL], tag = i)
             dfPlantFuel[!, Symbol(string(fuel_cols_num[i], "_AnnualSum_Fuel_HeatInput_Generation_MMBtu"))] = tempannualsum_fuel_heat_multi_generation
@@ -61,9 +55,6 @@ function write_fuel_consumption_plant(path::AbstractString,
         end
     end
 
-    if setup["ParameterScale"] == 1
-        tempannualsum *= ModelScalingFactor^2 # 
-    end
     dfPlantFuel.AnnualSumCosts .+= tempannualsum
     CSV.write(joinpath(path, "Fuel_cost_plant.csv"), dfPlantFuel)
 end
@@ -78,9 +69,6 @@ function write_fuel_consumption_ts(path::AbstractString,
     # Fuel consumption by each resource per time step, unit is MMBTU
     dfPlantFuel_TS = DataFrame(Resource = inputs["RESOURCE_NAMES"][HAS_FUEL])
     tempts = value.(EP[:ePlantFuel_generation] + EP[:ePlantFuel_start])[HAS_FUEL, :]
-    if setup["ParameterScale"] == 1
-        tempts *= ModelScalingFactor # kMMBTU to MMBTU
-    end
     dfPlantFuel_TS = hcat(dfPlantFuel_TS,
         DataFrame(tempts, [Symbol("t$t") for t in 1:T]))
     CSV.write(joinpath(path, "FuelConsumption_plant_MMBTU.csv"),
@@ -103,9 +91,6 @@ function write_fuel_consumption_tot(path::AbstractString,
     dfFuel = DataFrame(Fuel = fuel_types,
         AnnualSum = zeros(fuel_number))
     tempannualsum = value.(EP[:eFuelConsumptionYear])
-    if setup["ParameterScale"] == 1
-        tempannualsum *= ModelScalingFactor # billion MMBTU to MMBTU
-    end
     dfFuel.AnnualSum .+= tempannualsum
     CSV.write(joinpath(path, "FuelConsumption_total_MMBTU.csv"), dfFuel)
 end
diff --git a/src/write_outputs/write_net_revenue.jl b/src/write_outputs/write_net_revenue.jl
index 2311c8d1a..216b45401 100644
--- a/src/write_outputs/write_net_revenue.jl
+++ b/src/write_outputs/write_net_revenue.jl
@@ -75,11 +75,6 @@ function write_net_revenue(path::AbstractString,
                                                   dfVreStor[1:VRE_STOR_LENGTH, :NewCapWind]
         end
     end
-    if setup["ParameterScale"] == 1
-        dfNetRevenue.Inv_cost_MWh *= ModelScalingFactor # converting Million US$ to US$
-        dfNetRevenue.Inv_cost_MW *= ModelScalingFactor # converting Million US$ to US$
-        dfNetRevenue.Inv_cost_charge_MW *= ModelScalingFactor # converting Million US$ to US$
-    end
 
     # Add operations and maintenance cost to the dataframe
     dfNetRevenue.Fixed_OM_cost_MW = fixed_om_cost_per_mwyr.(gen) .* dfCap[1:G, :EndCap]
@@ -121,18 +116,9 @@ function write_net_revenue(path::AbstractString,
                                                           (value.(EP[:vP_AC_DISCHARGE][AC_DISCHARGE,:]).data * inputs["omega"])
         end
     end
-    if setup["ParameterScale"] == 1
-        dfNetRevenue.Fixed_OM_cost_MW *= ModelScalingFactor # converting Million US$ to US$
-        dfNetRevenue.Fixed_OM_cost_MWh *= ModelScalingFactor # converting Million US$ to US$
-        dfNetRevenue.Fixed_OM_cost_charge_MW *= ModelScalingFactor # converting Million US$ to US$
-        dfNetRevenue.Var_OM_cost_out *= ModelScalingFactor # converting Million US$ to US$
-    end
 
     # Add fuel cost to the dataframe
     dfNetRevenue.Fuel_cost = sum(value.(EP[:ePlantCFuelOut]), dims = 2)
-    if setup["ParameterScale"] == 1
-        dfNetRevenue.Fuel_cost *= ModelScalingFactor^2 # converting Million US$ to US$
-    end
 
     # Add storage cost to the dataframe
     dfNetRevenue.Var_OM_cost_in = zeros(nrow(dfNetRevenue))
@@ -154,9 +140,6 @@ function write_net_revenue(path::AbstractString,
         end
     end
 
-    if setup["ParameterScale"] == 1
-        dfNetRevenue.Var_OM_cost_in *= ModelScalingFactor^2 # converting Million US$ to US$
-    end
     # Add start-up cost to the dataframe
     dfNetRevenue.StartCost = zeros(nrow(dfNetRevenue))
     if setup["UCommit"] >= 1 && !isempty(COMMIT)
@@ -164,9 +147,6 @@ function write_net_revenue(path::AbstractString,
         start_fuel_costs = vec(value.(EP[:ePlantCFuelStart][COMMIT]))
         dfNetRevenue.StartCost[COMMIT] .= start_costs + start_fuel_costs
     end
-    if setup["ParameterScale"] == 1
-        dfNetRevenue.StartCost *= ModelScalingFactor^2 # converting Million US$ to US$
-    end
     # Add charge cost to the dataframe
     dfNetRevenue.Charge_cost = zeros(nrow(dfNetRevenue))
     if has_duals(EP)
@@ -179,9 +159,6 @@ function write_net_revenue(path::AbstractString,
         dfNetRevenue.CO2SequestrationCost = zeros(G)
         dfNetRevenue[CCS, :CO2SequestrationCost] = value.(EP[:ePlantCCO2Sequestration]).data
     end
-    if setup["ParameterScale"] == 1
-        dfNetRevenue.CO2SequestrationCost *= ModelScalingFactor^2 # converting Million US$ to US$
-    end
 
     # Add energy and subsidy revenue to the dataframe
     dfNetRevenue.EnergyRevenue = zeros(nrow(dfNetRevenue))
@@ -236,9 +213,6 @@ function write_net_revenue(path::AbstractString,
                 dfNetRevenue.EmissionsCost[Y] += -co2_cap_dual * temp_vec
             end
         end
-        if setup["ParameterScale"] == 1
-            dfNetRevenue.EmissionsCost *= ModelScalingFactor^2 # converting Million US$ to US$
-        end
     end
 
     # Add regional technology subsidy revenue to the dataframe
diff --git a/src/write_outputs/write_power_balance.jl b/src/write_outputs/write_power_balance.jl
index 72bfee22d..61d2cc59a 100644
--- a/src/write_outputs/write_power_balance.jl
+++ b/src/write_outputs/write_power_balance.jl
@@ -97,9 +97,6 @@ function write_power_balance(path::AbstractString, inputs::Dict, setup::Dict, EP
                 EP, inputs, z)
         end
     end
-    if setup["ParameterScale"] == 1
-        powerbalance *= ModelScalingFactor
-    end
     dfPowerBalance.AnnualSum .= powerbalance * inputs["omega"]
 
     if setup["WriteOutputs"] == "annual"
diff --git a/src/write_outputs/write_storagedual.jl b/src/write_outputs/write_storagedual.jl
index 90eae94ff..1af5fed23 100644
--- a/src/write_outputs/write_storagedual.jl
+++ b/src/write_outputs/write_storagedual.jl
@@ -68,10 +68,6 @@ function write_storagedual(path::AbstractString, inputs::Dict, setup::Dict, EP::
         end
     end
 
-    if setup["ParameterScale"] == 1
-        dual_values *= ModelScalingFactor
-    end
-
     dfStorageDual = hcat(dfStorageDual, DataFrame(dual_values, :auto))
     rename!(dfStorageDual,
         [Symbol("Resource"); Symbol("Zone"); [Symbol("t$t") for t in 1:T]])
diff --git a/src/write_outputs/write_subsidy_revenue.jl b/src/write_outputs/write_subsidy_revenue.jl
index 3262ec94d..97cc98045 100644
--- a/src/write_outputs/write_subsidy_revenue.jl
+++ b/src/write_outputs/write_subsidy_revenue.jl
@@ -93,11 +93,6 @@ function write_subsidy_revenue(path::AbstractString, inputs::Dict, setup::Dict,
         end
     end
 
-    if setup["ParameterScale"] == 1
-        dfSubRevenue.SubsidyRevenue *= ModelScalingFactor^2 #convert from Million US$ to US$
-        dfRegSubRevenue.SubsidyRevenue *= ModelScalingFactor^2 #convert from Million US$ to US$
-    end
-
     CSV.write(joinpath(path, "SubsidyRevenue.csv"), dfSubRevenue)
     CSV.write(joinpath(path, "RegSubsidyRevenue.csv"), dfRegSubRevenue)
     return dfSubRevenue, dfRegSubRevenue
diff --git a/src/write_outputs/write_vre_stor.jl b/src/write_outputs/write_vre_stor.jl
index a50687c95..f6ca98907 100644
--- a/src/write_outputs/write_vre_stor.jl
+++ b/src/write_outputs/write_vre_stor.jl
@@ -247,52 +247,6 @@ function write_vre_stor_capacity(path::AbstractString, inputs::Dict, setup::Dict
         EndDischargeACCap = existingcapdischargeac[:] - retcapdischargeac[:] +
                             capdischargeac[:])
 
-    if setup["ParameterScale"] == 1
-        columns_to_scale = [
-            :StartCapSolar,
-            :RetCapSolar,
-            :NewCapSolar,
-            :EndCapSolar,
-            :StartCapWind,
-            :RetCapWind,
-            :NewCapWind,
-            :EndCapWind,
-            :StartCapElec,
-            :RetCapElec,
-            :NewCapElec,
-            :EndCapElec,
-            :StartCapDC,
-            :RetCapDC,
-            :NewCapDC,
-            :EndCapDC,
-            :StartCapGrid,
-            :RetCapGrid,
-            :NewCapGrid,
-            :EndCapGrid,
-            :StartEnergyCap,
-            :RetEnergyCap,
-            :NewEnergyCap,
-            :EndEnergyCap,
-            :StartChargeACCap,
-            :RetChargeACCap,
-            :NewChargeACCap,
-            :EndChargeACCap,
-            :StartChargeDCCap,
-            :RetChargeDCCap,
-            :NewChargeDCCap,
-            :EndChargeDCCap,
-            :StartDischargeDCCap,
-            :RetDischargeDCCap,
-            :NewDischargeDCCap,
-            :EndDischargeDCCap,
-            :StartDischargeACCap,
-            :RetDischargeACCap,
-            :NewDischargeACCap,
-            :EndDischargeACCap
-        ]
-        dfCap[!, columns_to_scale] .*= ModelScalingFactor
-    end
-
     total = DataFrame(Resource = "Total", Zone = "n/a", Resource_Type = "Total",
         Cluster = "n/a",
         StartCapSolar = sum(dfCap[!, :StartCapSolar]),
@@ -354,8 +308,7 @@ function write_vre_stor_charge(path::AbstractString, inputs::Dict, setup::Dict,
             AnnualSum = Array{Union{Missing, Float32}}(undef, size(DC_CHARGE)[1]))
         charge_dc = zeros(size(DC_CHARGE)[1], T)
         charge_dc = value.(EP[:vP_DC_CHARGE]).data ./
-                    etainverter.(gen[DC_CHARGE]) *
-                    (setup["ParameterScale"] == 1 ? ModelScalingFactor : 1)
+                    etainverter.(gen[DC_CHARGE])
         dfCharge_DC.AnnualSum .= charge_dc * inputs["omega"]
 
         filepath = joinpath(path, "vre_stor_dc_charge.csv")
@@ -372,8 +325,7 @@ function write_vre_stor_charge(path::AbstractString, inputs::Dict, setup::Dict,
             Zone = inputs["ZONES_AC_CHARGE"],
             AnnualSum = Array{Union{Missing, Float32}}(undef, size(AC_CHARGE)[1]))
         charge_ac = zeros(size(AC_CHARGE)[1], T)
-        charge_ac = value.(EP[:vP_AC_CHARGE]).data *
-                    (setup["ParameterScale"] == 1 ? ModelScalingFactor : 1)
+        charge_ac = value.(EP[:vP_AC_CHARGE]).data
         dfCharge_AC.AnnualSum .= charge_ac * inputs["omega"]
 
         filepath = joinpath(path, "vre_stor_ac_charge.csv")
@@ -411,9 +363,6 @@ function write_vre_stor_discharge(path::AbstractString,
             AnnualSum = Array{Union{Missing, Float32}}(undef, size(DC_DISCHARGE)[1]))
         power_vre_stor = value.(EP[:vP_DC_DISCHARGE]).data .*
                          etainverter.(gen[DC_DISCHARGE])
-        if setup["ParameterScale"] == 1
-            power_vre_stor *= ModelScalingFactor
-        end
         dfDischarge_DC.AnnualSum .= power_vre_stor * inputs["omega"]
 
         filepath = joinpath(path, "vre_stor_dc_discharge.csv")
@@ -430,9 +379,6 @@ function write_vre_stor_discharge(path::AbstractString,
             Zone = inputs["ZONES_AC_DISCHARGE"],
             AnnualSum = Array{Union{Missing, Float32}}(undef, size(AC_DISCHARGE)[1]))
         power_vre_stor = value.(EP[:vP_AC_DISCHARGE]).data
-        if setup["ParameterScale"] == 1
-            power_vre_stor *= ModelScalingFactor
-        end
         dfDischarge_AC.AnnualSum .= power_vre_stor * inputs["omega"]
 
         filepath = joinpath(path, "vre_stor_ac_discharge.csv")
@@ -449,9 +395,6 @@ function write_vre_stor_discharge(path::AbstractString,
             Zone = inputs["ZONES_WIND"],
             AnnualSum = Array{Union{Missing, Float32}}(undef, size(WIND)[1]))
         vre_vre_stor = value.(EP[:vP_WIND]).data
-        if setup["ParameterScale"] == 1
-            vre_vre_stor *= ModelScalingFactor
-        end
         dfVP_VRE_STOR.AnnualSum .= vre_vre_stor * inputs["omega"]
 
         filepath = joinpath(path, "vre_stor_wind_power.csv")
@@ -468,9 +411,6 @@ function write_vre_stor_discharge(path::AbstractString,
             Zone = inputs["ZONES_ELEC"],
             AnnualSum = Array{Union{Missing, Float32}}(undef, size(ELEC)[1]))
         elec_vre_stor = value.(EP[:vP_ELEC]).data
-        if setup["ParameterScale"] == 1
-            elec_vre_stor *= ModelScalingFactor
-        end
         dfVP_VRE_STOR.AnnualSum .= elec_vre_stor * inputs["omega"]
 
         filepath = joinpath(path, "vre_stor_elec_power_consumption.csv")
@@ -485,11 +425,7 @@ function write_vre_stor_discharge(path::AbstractString,
         dfVP_VRE_STOR = DataFrame(Resource = inputs["RESOURCE_NAMES_SOLAR"],
             Zone = inputs["ZONES_SOLAR"],
             AnnualSum = Array{Union{Missing, Float32}}(undef, size(SOLAR)[1]))
-        vre_vre_stor = value.(EP[:vP_SOLAR]).data .*
-                       etainverter.(gen[SOLAR])
-        if setup["ParameterScale"] == 1
-            vre_vre_stor *= ModelScalingFactor
-        end
+        vre_vre_stor = value.(EP[:vP_SOLAR]).data .* etainverter.(gen[SOLAR])
         dfVP_VRE_STOR.AnnualSum .= vre_vre_stor * inputs["omega"]
 
         filepath = joinpath(path, "vre_stor_solar_power.csv")
diff --git a/test/load_resources/test_gen_non_colocated/settings/genx_settings.yml b/test/load_resources/test_gen_non_colocated/settings/genx_settings.yml
index 4c1c974d2..958c5e2c4 100644
--- a/test/load_resources/test_gen_non_colocated/settings/genx_settings.yml
+++ b/test/load_resources/test_gen_non_colocated/settings/genx_settings.yml
@@ -1,5 +1,4 @@
 NetworkExpansion: 1
-ParameterScale: 1
 EnergyShareRequirement: 1
 Trans_Loss_Segments: 1
 CapacityReserveMargin: 1
diff --git a/test/load_resources/test_gen_vre_stor/settings/genx_settings.yml b/test/load_resources/test_gen_vre_stor/settings/genx_settings.yml
index 4c1c974d2..958c5e2c4 100644
--- a/test/load_resources/test_gen_vre_stor/settings/genx_settings.yml
+++ b/test/load_resources/test_gen_vre_stor/settings/genx_settings.yml
@@ -1,5 +1,4 @@
 NetworkExpansion: 1
-ParameterScale: 1
 EnergyShareRequirement: 1
 Trans_Loss_Segments: 1
 CapacityReserveMargin: 1
diff --git a/test/test_VRE_storage.jl b/test/test_VRE_storage.jl
index ddf8a604c..a0dd6e52d 100644
--- a/test/test_VRE_storage.jl
+++ b/test/test_VRE_storage.jl
@@ -37,8 +37,7 @@ genx_setup = Dict("NetworkExpansion" => 1,
     "CO2Cap" => 1,
     "StorageLosses" => 1,
     "VirtualChargeDischargeCost" => 1,
-    "ParameterScale" => 1)
-
+)
 # Run test cases
 for (test_path, obj_true) in test_cases
     test_case(test_path, obj_true, genx_setup)
diff --git a/test/test_electrolyzer.jl b/test/test_electrolyzer.jl
index 58685beb8..4b0bf47f7 100644
--- a/test/test_electrolyzer.jl
+++ b/test/test_electrolyzer.jl
@@ -11,7 +11,6 @@ test_path = "electrolyzer"
 genx_setup = Dict("Trans_Loss_Segments" => 1,
     "UCommit" => 2,
     "StorageLosses" => 1,
-    "ParameterScale" => 1,
     "HourlyMatching" => 1,
     "HydrogenHourlyMatching" => 1,
     "HydrogenMinimumProduction" => 1
diff --git a/test/test_fusion.jl b/test/test_fusion.jl
index 105b6b703..b3bb81281 100644
--- a/test/test_fusion.jl
+++ b/test/test_fusion.jl
@@ -8,8 +8,8 @@ obj_true = 300.5962608 # see fusion_pulse_every_hour/README.md
 test_path = "fusion_pulse_every_hour"
 
 # Define test inputs
-genx_setup = Dict("UCommit" => 2,
-    "ParameterScale" => 1,
+genx_setup = Dict(
+    "UCommit" => 2,
 )
 settings = GenX.default_settings()
 merge!(settings, genx_setup)
diff --git a/test/test_load_resource_data.jl b/test/test_load_resource_data.jl
index 5ae72f7dc..f19347d23 100644
--- a/test/test_load_resource_data.jl
+++ b/test/test_load_resource_data.jl
@@ -242,7 +242,7 @@ function test_resource_specific_attributes(gen, dfGen, inputs)
 end
 
 function test_load_resources_data()
-    setup = Dict("ParameterScale" => 0,
+    setup = Dict(
         "OperationalReserves" => 1,
         "UCommit" => 2,
         "MultiStage" => 1)
@@ -292,7 +292,7 @@ function test_load_resources_data()
 end
 
 function test_load_VRE_STOR_data()
-    setup = Dict("ParameterScale" => 0,
+    setup = Dict(
         "OperationalReserves" => 1,
         "UCommit" => 2,
         "MultiStage" => 0)
diff --git a/test/test_multifuels.jl b/test/test_multifuels.jl
index ff1a0efda..23d6cc1e9 100644
--- a/test/test_multifuels.jl
+++ b/test/test_multifuels.jl
@@ -14,7 +14,6 @@ genx_setup = Dict("Trans_Loss_Segments" => 1,
     "StorageLosses" => 1,
     "MinCapReq" => 1,
     "MaxCapReq" => 1,
-    "ParameterScale" => 1,
     "WriteShadowPrices" => 1,
     "UCommit" => 2)
 
diff --git a/test/test_multistage.jl b/test/test_multistage.jl
index d593e41d1..cf4b0af67 100644
--- a/test/test_multistage.jl
+++ b/test/test_multistage.jl
@@ -19,7 +19,6 @@ genx_setup = Dict("Trans_Loss_Segments" => 1,
     "OperationalReserves" => 1,
     "CO2Cap" => 2,
     "StorageLosses" => 1,
-    "ParameterScale" => 1,
     "UCommit" => 2,
     "MultiStage" => 1,
     "MultiStageSettingsDict" => multistage_setup)
@@ -102,8 +101,8 @@ function test_update_cumulative_min_ret!()
     # Merge the genx_setup with the default settings
     settings = GenX.default_settings()
 
-    for ParameterScale in [0, 1]
-        genx_setup["ParameterScale"] = ParameterScale
+    for AutoScale in [0, 1]
+        genx_setup["AutoScaling"] = AutoScale
         merge!(settings, genx_setup)
 
         inputs_dict = Dict()
diff --git a/test/test_piecewisefuel.jl b/test/test_piecewisefuel.jl
index db52aaf0d..122a05940 100644
--- a/test/test_piecewisefuel.jl
+++ b/test/test_piecewisefuel.jl
@@ -7,10 +7,10 @@ obj_true = 2341.82308
 test_path = "piecewise_fuel"
 
 # Define test inputs
-genx_setup = Dict("UCommit" => 2,
+genx_setup = Dict(
+    "UCommit" => 2,
     "CO2Cap" => 1,
-    "ParameterScale" => 1)
-
+)
 # Run the case and get the objective value and tolerance
 EP, _, _ = redirect_stdout(devnull) do
     run_genx_case_testing(test_path, genx_setup)
diff --git a/test/test_retrofit.jl b/test/test_retrofit.jl
index 54ae82ad5..590894697 100644
--- a/test/test_retrofit.jl
+++ b/test/test_retrofit.jl
@@ -8,11 +8,11 @@ obj_true = 3179.6244
 test_path = "retrofit"
 
 # Define test inputs
-genx_setup = Dict("CO2Cap" => 2,
+genx_setup = Dict(
+    "CO2Cap" => 2,
     "StorageLosses" => 1,
     "MinCapReq" => 1,
     "MaxCapReq" => 1,
-    "ParameterScale" => 1,
     "UCommit" => 2,
     "EnergyShareRequirement" => 1,
     "CapacityReserveMargin" => 1,
diff --git a/test/test_threezones.jl b/test/test_threezones.jl
index 5d608e0f9..bc7f53dff 100644
--- a/test/test_threezones.jl
+++ b/test/test_threezones.jl
@@ -13,7 +13,6 @@ genx_setup = Dict("NetworkExpansion" => 1,
     "CO2Cap" => 2,
     "StorageLosses" => 1,
     "MinCapReq" => 1,
-    "ParameterScale" => 1,
     "UCommit" => 2)
 
 # Run the case and get the objective value and tolerance

From 90cce6c3795141831cfb633ff3df3f21bd371ab0 Mon Sep 17 00:00:00 2001
From: Ruaridh Macdonald <rmacd@mit.edu>
Date: Thu, 14 Nov 2024 05:48:22 -0500
Subject: [PATCH 05/11] Add AutoScaling to single stage case

---
 src/case_runners/case_runner.jl              | 5 +++++
 src/configure_settings/configure_settings.jl | 6 ++++--
 2 files changed, 9 insertions(+), 2 deletions(-)

diff --git a/src/case_runners/case_runner.jl b/src/case_runners/case_runner.jl
index afea227f2..827829a95 100644
--- a/src/case_runners/case_runner.jl
+++ b/src/case_runners/case_runner.jl
@@ -80,6 +80,11 @@ 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)
+    end
+
     println("Solving Model")
     EP, solve_time = solve_model(EP, mysetup)
     myinputs["solve_time"] = solve_time # Store the model solve time in myinputs
diff --git a/src/configure_settings/configure_settings.jl b/src/configure_settings/configure_settings.jl
index 9df418e33..dce8e5ddb 100644
--- a/src/configure_settings/configure_settings.jl
+++ b/src/configure_settings/configure_settings.jl
@@ -12,7 +12,6 @@ function default_settings()
         "VirtualChargeDischargeCost" => 1,  # $/MWh
         "MinCapReq" => 0,
         "MaxCapReq" => 0,
-        "ParameterScale" => 0,
         "WriteShadowPrices" => 0,
         "UCommit" => 0,
         "TimeDomainReduction" => 0,
@@ -37,7 +36,8 @@ function default_settings()
         "ResourcePoliciesFolder" => "policy_assignments",
         "SystemFolder" => "system",
         "PoliciesFolder" => "policies",
-        "ObjScale" => 1)
+        "ObjScale" => 1,
+        "AutoScaling" => 0,)
 end
 
 @doc raw"""
@@ -61,6 +61,8 @@ 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
 

From 3630c7f401e67061d56462f76508c47016a6352b Mon Sep 17 00:00:00 2001
From: Ruaridh Macdonald <rmacd@mit.edu>
Date: Thu, 14 Nov 2024 06:36:19 -0500
Subject: [PATCH 06/11] Add ScalingSettings to scale_constraints!

---
 src/case_runners/case_runner.jl | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/case_runners/case_runner.jl b/src/case_runners/case_runner.jl
index 827829a95..905f4e211 100644
--- a/src/case_runners/case_runner.jl
+++ b/src/case_runners/case_runner.jl
@@ -82,7 +82,7 @@ function run_genx_case_simple!(case::AbstractString, mysetup::Dict, optimizer::A
 
     if mysetup["AutoScaling"] == 1
         println("Scaling Constraints")
-        scale_constraints!(EP)
+        scale_constraints!(EP, mysetup["ScalingSettings"])
     end
 
     println("Solving Model")

From 8dccfdfd88784765075299446127939fab074ee3 Mon Sep 17 00:00:00 2001
From: lbonaldo <bonaldo.luca12@gmail.com>
Date: Thu, 16 Jan 2025 14:51:15 -0500
Subject: [PATCH 07/11] Remove scaling in tests

---
 src/model/resources/maintenance.jl | 2 +-
 test/test_VRE_storage.jl           | 6 +++---
 test/test_electrolyzer.jl          | 2 +-
 test/test_fusion.jl                | 2 +-
 test/test_multifuels.jl            | 2 +-
 test/test_multistage.jl            | 2 +-
 test/test_piecewisefuel.jl         | 2 +-
 test/test_retrofit.jl              | 2 +-
 test/test_threezones.jl            | 2 +-
 9 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/src/model/resources/maintenance.jl b/src/model/resources/maintenance.jl
index 1a9bda5f0..4f6f1469e 100644
--- a/src/model/resources/maintenance.jl
+++ b/src/model/resources/maintenance.jl
@@ -108,7 +108,7 @@ function maintenance_formulation!(EP::Model,
         maint_begin_cadence::Int,
         maint_dur::Int,
         maint_freq_years::Int,
-        cap::Float64,
+        cap::Union{Float64, Int64},
         vcommit::Symbol,
         ecap::Symbol,
         integer_operational_unit_commitment::Bool)
diff --git a/test/test_VRE_storage.jl b/test/test_VRE_storage.jl
index a0dd6e52d..72bfd11ee 100644
--- a/test/test_VRE_storage.jl
+++ b/test/test_VRE_storage.jl
@@ -24,9 +24,9 @@ function test_case(test_path, obj_true, genx_setup)
 end
 
 # Test cases (format: (test_path, obj_true))
-test_cases = [("VRE_storage/solar_wind", 92376.060123),
-    ("VRE_storage/solar", 106798.88706),
-    ("VRE_storage/wind", 92376.275543)]
+test_cases = [("VRE_storage/solar_wind", 9.23762755432138e10),
+    ("VRE_storage/solar", 1.0679888706409656e11),
+    ("VRE_storage/wind", 9.23762755432139e10)]
 
 # Define test setup
 genx_setup = Dict("NetworkExpansion" => 1,
diff --git a/test/test_electrolyzer.jl b/test/test_electrolyzer.jl
index 4b0bf47f7..31191fd68 100644
--- a/test/test_electrolyzer.jl
+++ b/test/test_electrolyzer.jl
@@ -4,7 +4,7 @@ using Test
 
 include(joinpath(@__DIR__, "utilities.jl"))
 
-obj_true = 34275.8599
+obj_true = 3.427501887037163e10
 test_path = "electrolyzer"
 
 # Define test inputs
diff --git a/test/test_fusion.jl b/test/test_fusion.jl
index b3bb81281..92c4c51c8 100644
--- a/test/test_fusion.jl
+++ b/test/test_fusion.jl
@@ -4,7 +4,7 @@ using Test
 
 include(joinpath(@__DIR__, "utilities.jl"))
 
-obj_true = 300.5962608 # see fusion_pulse_every_hour/README.md
+obj_true = 3.005962608299133e8 # see fusion_pulse_every_hour/README.md
 test_path = "fusion_pulse_every_hour"
 
 # Define test inputs
diff --git a/test/test_multifuels.jl b/test/test_multifuels.jl
index 23d6cc1e9..3d3c7ae45 100644
--- a/test/test_multifuels.jl
+++ b/test/test_multifuels.jl
@@ -4,7 +4,7 @@ using Test
 
 include(joinpath(@__DIR__, "utilities.jl"))
 
-obj_true = 5494.7919354
+obj_true = 5.4950570610364895e9
 test_path = "multi_fuels"
 
 # Define test inputs
diff --git a/test/test_multistage.jl b/test/test_multistage.jl
index cf4b0af67..ef500f503 100644
--- a/test/test_multistage.jl
+++ b/test/test_multistage.jl
@@ -4,7 +4,7 @@ using Test
 
 include(joinpath(@__DIR__, "utilities.jl"))
 
-obj_true = [79734.80032, 41630.03494, 27855.20631]
+obj_true = [7.973480032e10, 4.163003494e10, 2.785520631e10]
 test_path = joinpath(@__DIR__, "multi_stage")
 
 # Define test inputs
diff --git a/test/test_piecewisefuel.jl b/test/test_piecewisefuel.jl
index 122a05940..77ce4e24d 100644
--- a/test/test_piecewisefuel.jl
+++ b/test/test_piecewisefuel.jl
@@ -3,7 +3,7 @@ module TestPiecewiseFuelCO2
 using Test
 include(joinpath(@__DIR__, "utilities.jl"))
 
-obj_true = 2341.82308
+obj_true = 2.3418230753008084e9
 test_path = "piecewise_fuel"
 
 # Define test inputs
diff --git a/test/test_retrofit.jl b/test/test_retrofit.jl
index 590894697..807eb4640 100644
--- a/test/test_retrofit.jl
+++ b/test/test_retrofit.jl
@@ -4,7 +4,7 @@ using Test
 
 include(joinpath(@__DIR__, "utilities.jl"))
 
-obj_true = 3179.6244
+obj_true = 3.1796243889649606e9
 test_path = "retrofit"
 
 # Define test inputs
diff --git a/test/test_threezones.jl b/test/test_threezones.jl
index bc7f53dff..bc093fc7e 100644
--- a/test/test_threezones.jl
+++ b/test/test_threezones.jl
@@ -4,7 +4,7 @@ using Test
 
 include(joinpath(@__DIR__, "utilities.jl"))
 
-obj_true = 6960.20855
+obj_true = 6.960208549907064e9
 test_path = "three_zones"
 
 # Define test inputs

From 30ac181bcc9bdab1537f6d51157b00c69405f637 Mon Sep 17 00:00:00 2001
From: lbonaldo <bonaldo.luca12@gmail.com>
Date: Thu, 16 Jan 2025 14:51:40 -0500
Subject: [PATCH 08/11] Update CHANGELOG.md

---
 CHANGELOG.md | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 909f8a14c..73d8c5b91 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -7,6 +7,14 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## Unreleased
 
+### Changed
+- Automatic problem scaling is now available using the `MacroEnergySystemsScaling.jl` 
+package. The new `AutoScaling` setting has been introduced to replace the 
+`ParameterScale` setting and enable this feature.
+
+### Removed
+- Removed the `ParameterScale` setting. 
+
 ## [0.4.2] - 2024-12-23
 
 ### Added

From 96b50e289351d03cd1dc5490af6786aecc0aa8dc Mon Sep 17 00:00:00 2001
From: lbonaldo <bonaldo.luca12@gmail.com>
Date: Thu, 16 Jan 2025 16:29:01 -0500
Subject: [PATCH 09/11] Clean up

---
 src/load_inputs/load_cap_reserve_margin.jl                | 3 ---
 src/load_inputs/load_co2_cap.jl                           | 8 ++------
 src/load_inputs/load_demand_data.jl                       | 6 ++----
 src/load_inputs/load_energy_share_requirement.jl          | 3 ---
 src/load_inputs/load_fuels_data.jl                        | 6 ++----
 src/load_inputs/load_hydrogen_demand.jl                   | 4 +---
 src/load_inputs/load_maximum_capacity_requirement.jl      | 5 +----
 src/load_inputs/load_network_data.jl                      | 4 +---
 src/load_inputs/load_operational_reserves.jl              | 4 +---
 .../capacity_reserve_margin/write_capacity_value.jl       | 4 +---
 .../write_reserve_margin_revenue.jl                       | 1 -
 .../capacity_reserve_margin/write_virtual_discharge.jl    | 4 +---
 .../hydrogen/write_hourly_matching_prices.jl              | 3 +--
 .../write_maximum_capacity_requirement.jl                 | 6 ------
 .../write_minimum_capacity_requirement.jl                 | 6 ------
 .../reserves/write_operating_reserve_price_revenue.jl     | 4 +---
 src/write_outputs/reserves/write_reg.jl                   | 3 +--
 src/write_outputs/reserves/write_rsv.jl                   | 5 ++---
 src/write_outputs/write_capacityfactor.jl                 | 5 ++---
 src/write_outputs/write_charge.jl                         | 1 -
 src/write_outputs/write_charging_cost.jl                  | 1 -
 src/write_outputs/write_co2.jl                            | 4 ----
 src/write_outputs/write_curtailment.jl                    | 3 ---
 src/write_outputs/write_emissions.jl                      | 6 +-----
 src/write_outputs/write_nse.jl                            | 3 +--
 src/write_outputs/write_power.jl                          | 2 --
 src/write_outputs/write_price.jl                          | 3 +--
 src/write_outputs/write_reliability.jl                    | 3 +--
 src/write_outputs/write_storage.jl                        | 2 --
 29 files changed, 23 insertions(+), 89 deletions(-)

diff --git a/src/load_inputs/load_cap_reserve_margin.jl b/src/load_inputs/load_cap_reserve_margin.jl
index 28d57aed5..338c17aac 100644
--- a/src/load_inputs/load_cap_reserve_margin.jl
+++ b/src/load_inputs/load_cap_reserve_margin.jl
@@ -4,13 +4,10 @@
 Read input parameters related to planning reserve margin constraints
 """
 function load_cap_reserve_margin!(setup::Dict, path::AbstractString, inputs::Dict)
-    
-
     filename = "Capacity_reserve_margin_slack.csv"
     if isfile(joinpath(path, filename))
         df = load_dataframe(joinpath(path, filename))
         inputs["dfCapRes_slack"] = df
-
     end
 
     filename = "Capacity_reserve_margin.csv"
diff --git a/src/load_inputs/load_co2_cap.jl b/src/load_inputs/load_co2_cap.jl
index 5a0138646..2660ac093 100644
--- a/src/load_inputs/load_co2_cap.jl
+++ b/src/load_inputs/load_co2_cap.jl
@@ -4,13 +4,10 @@
 Read input parameters related to CO$_2$ emissions cap constraints
 """
 function load_co2_cap!(setup::Dict, path::AbstractString, inputs::Dict)
-    
-
     filename = "CO2_cap_slack.csv"
     if isfile(joinpath(path, filename))
         df = load_dataframe(joinpath(path, filename))
         inputs["dfCO2Cap_slack"] = df
-
     end
 
     filename = "CO2_cap.csv"
@@ -23,12 +20,11 @@ function load_co2_cap!(setup::Dict, path::AbstractString, inputs::Dict)
 
     # Emission limits
     if setup["CO2Cap"] == 1
-        #  CO2 emissions cap in mass
+        # CO2 emissions cap in mass
         # note the default inputs is in million tons
-        # 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 
+        inputs["dfMaxCO2"] = mat * 1e6
 
     elseif setup["CO2Cap"] == 2 || setup["CO2Cap"] == 3
         #  CO2 emissions rate applied per MWh
diff --git a/src/load_inputs/load_demand_data.jl b/src/load_inputs/load_demand_data.jl
index 70d8b9842..512275b70 100644
--- a/src/load_inputs/load_demand_data.jl
+++ b/src/load_inputs/load_demand_data.jl
@@ -71,14 +71,12 @@ function load_demand_data!(setup::Dict, path::AbstractString, inputs::Dict)
     inputs["START_SUBPERIODS"] = 1:hours_per_subperiod:T # set of indexes for all time periods that start a subperiod (e.g. sample day/week)
     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
-    
     # Max value of non-served energy
-    inputs["Voll"] = as_vector(:Voll)  # convert from $/MWh $ million/GWh (assuming objective is divided by 1000)
+    inputs["Voll"] = as_vector(:Voll)
     # Demand in MW
     inputs["pD"] = extract_matrix_from_dataframe(demand_in,
         DEMAND_COLUMN_PREFIX()[1:(end - 1)],
-        prefixseparator = 'z') 
+        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
diff --git a/src/load_inputs/load_energy_share_requirement.jl b/src/load_inputs/load_energy_share_requirement.jl
index 01ca4bc4f..0d1a9d5a9 100644
--- a/src/load_inputs/load_energy_share_requirement.jl
+++ b/src/load_inputs/load_energy_share_requirement.jl
@@ -5,13 +5,10 @@ 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)
-    
-
     filename = "Energy_share_requirement_slack.csv"
     if isfile(joinpath(path, filename))
         df = load_dataframe(joinpath(path, filename))
         inputs["dfESR_slack"] = df
-
     end
 
     filename = "Energy_share_requirement.csv"
diff --git a/src/load_inputs/load_fuels_data.jl b/src/load_inputs/load_fuels_data.jl
index 5a52c377a..2b1d89f11 100644
--- a/src/load_inputs/load_fuels_data.jl
+++ b/src/load_inputs/load_fuels_data.jl
@@ -24,11 +24,9 @@ function load_fuels_data!(setup::Dict, path::AbstractString, inputs::Dict)
     fuel_costs = Dict{AbstractString, Array{Float64}}()
     fuel_CO2 = Dict{AbstractString, Float64}()
 
-    
-
     for i in 1:length(fuels)
-        # fuel cost is in $/MMBTU w/o scaling, $/Billon BTU w/ scaling
-        fuel_costs[fuels[i]] = costs[:, i] 
+        # fuel cost is in $/MMBTU w/o scaling
+        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
diff --git a/src/load_inputs/load_hydrogen_demand.jl b/src/load_inputs/load_hydrogen_demand.jl
index 938ce9582..d78be7e73 100644
--- a/src/load_inputs/load_hydrogen_demand.jl
+++ b/src/load_inputs/load_hydrogen_demand.jl
@@ -10,10 +10,8 @@ function load_hydrogen_demand!(setup::Dict, path::AbstractString, inputs::Dict)
     inputs["NumberOfH2DemandReqs"] = nrow(df)
     inputs["H2DemandReq"] = df[!, :Hydrogen_Demand_kt]
 
-     # Million $/kton if scaled, $/ton if not scaled
-
     if "PriceCap" in names(df)
-        inputs["H2DemandPriceCap"] = df[!, :PriceCap] 
+        inputs["H2DemandPriceCap"] = df[!, :PriceCap]
     end
     println(filename * " Successfully Read!")
 end
diff --git a/src/load_inputs/load_maximum_capacity_requirement.jl b/src/load_inputs/load_maximum_capacity_requirement.jl
index d7aaca228..d242a33da 100644
--- a/src/load_inputs/load_maximum_capacity_requirement.jl
+++ b/src/load_inputs/load_maximum_capacity_requirement.jl
@@ -9,11 +9,8 @@ function load_maximum_capacity_requirement!(path::AbstractString, inputs::Dict,
     inputs["NumberOfMaxCapReqs"] = nrow(df)
     inputs["MaxCapReq"] = df[!, :Max_MW]
 
-    
-
-
     if "PriceCap" in names(df)
-        inputs["MaxCapPriceCap"] = df[!, :PriceCap] 
+        inputs["MaxCapPriceCap"] = df[!, :PriceCap]
     end
     println(filename * " Successfully Read!")
 end
diff --git a/src/load_inputs/load_network_data.jl b/src/load_inputs/load_network_data.jl
index 1896b3d4c..3cd06da8e 100644
--- a/src/load_inputs/load_network_data.jl
+++ b/src/load_inputs/load_network_data.jl
@@ -4,8 +4,6 @@
 Function for reading input parameters related to the electricity transmission network
 """
 function load_network_data!(setup::Dict, path::AbstractString, inputs_nw::Dict)
-    
-
     filename = "Network.csv"
     network_var = load_dataframe(joinpath(path, filename))
 
@@ -23,7 +21,7 @@ function load_network_data!(setup::Dict, path::AbstractString, inputs_nw::Dict)
     inputs_nw["pNet_Map"] = load_network_map(network_var, Z, L)
 
     # Transmission capacity of the network (in MW)
-    inputs_nw["pTrans_Max"] = to_floats(:Line_Max_Flow_MW)   # convert to GW
+    inputs_nw["pTrans_Max"] = to_floats(:Line_Max_Flow_MW)
 
     if setup["Trans_Loss_Segments"] == 1
         # Line percentage Loss - valid for case when modeling losses as a fixed percent of absolute value of power flows
diff --git a/src/load_inputs/load_operational_reserves.jl b/src/load_inputs/load_operational_reserves.jl
index f0ca6c723..91cd836a6 100644
--- a/src/load_inputs/load_operational_reserves.jl
+++ b/src/load_inputs/load_operational_reserves.jl
@@ -43,11 +43,9 @@ function load_operational_reserves!(setup::Dict, path::AbstractString, inputs::D
     # Spinning up reserve requirement as a percent of hourly wind and solar generation (which is summed across all zones)
     inputs["pRsv_Req_VRE"] = float(res_in[1, :Rsv_Req_Percent_VRE])
 
-    
-
     # Penalty for not meeting hourly spinning reserve requirement
     inputs["pC_Rsv_Penalty"] = float(res_in[1, :Unmet_Rsv_Penalty_Dollar_per_MW])
-    inputs["pStatic_Contingency"] = float(res_in[1, :Static_Contingency_MW])  # convert to GW
+    inputs["pStatic_Contingency"] = float(res_in[1, :Static_Contingency_MW])
 
     if setup["UCommit"] >= 1
         inputs["pDynamic_Contingency"] = convert(Int8, res_in[1, :Dynamic_Contingency])
diff --git a/src/write_outputs/capacity_reserve_margin/write_capacity_value.jl b/src/write_outputs/capacity_reserve_margin/write_capacity_value.jl
index 52b84fe8b..50ef9e7ae 100644
--- a/src/write_outputs/capacity_reserve_margin/write_capacity_value.jl
+++ b/src/write_outputs/capacity_reserve_margin/write_capacity_value.jl
@@ -29,7 +29,6 @@ function write_capacity_value(path::AbstractString, inputs::Dict, setup::Dict, E
     MUST_RUN = inputs["MUST_RUN"]
     VRE_STOR = inputs["VRE_STOR"]
 
-    
     eTotalCap = value.(EP[:eTotalCap])
 
     minimum_plant_size = 1 # MW
@@ -165,6 +164,5 @@ function capacity_reserve_margin_price(EP::Model,
         setup::Dict,
         capres_zone::Int)::Vector{Float64}
     ω = inputs["omega"]
-    
-    return dual.(EP[:cCapacityResMargin][capres_zone, :]) ./ ω 
+    return dual.(EP[:cCapacityResMargin][capres_zone, :]) ./ ω
 end
diff --git a/src/write_outputs/capacity_reserve_margin/write_reserve_margin_revenue.jl b/src/write_outputs/capacity_reserve_margin/write_reserve_margin_revenue.jl
index 2dedcd035..32b5930a6 100644
--- a/src/write_outputs/capacity_reserve_margin/write_reserve_margin_revenue.jl
+++ b/src/write_outputs/capacity_reserve_margin/write_reserve_margin_revenue.jl
@@ -13,7 +13,6 @@ function write_reserve_margin_revenue(path::AbstractString,
         setup::Dict,
         EP::Model)
     
-
     gen = inputs["RESOURCES"]
     regions = region.(gen)
     clusters = cluster.(gen)
diff --git a/src/write_outputs/capacity_reserve_margin/write_virtual_discharge.jl b/src/write_outputs/capacity_reserve_margin/write_virtual_discharge.jl
index 89e481209..fe9be7150 100644
--- a/src/write_outputs/capacity_reserve_margin/write_virtual_discharge.jl
+++ b/src/write_outputs/capacity_reserve_margin/write_virtual_discharge.jl
@@ -9,12 +9,10 @@ function write_virtual_discharge(path::AbstractString, inputs::Dict, setup::Dict
     T = inputs["T"]     # Number of time steps (hours)
     STOR_ALL = inputs["STOR_ALL"]
 
-    
-
     resources = inputs["RESOURCE_NAMES"][STOR_ALL]
     zones = inputs["R_ZONES"][STOR_ALL]
     virtual_discharge = (value.(EP[:vCAPRES_discharge][STOR_ALL, :].data) -
-                         value.(EP[:vCAPRES_charge][STOR_ALL, :].data)) 
+                         value.(EP[:vCAPRES_charge][STOR_ALL, :].data))
 
     dfVirtualDischarge = DataFrame(Resource = resources, Zone = zones)
     dfVirtualDischarge.AnnualSum .= virtual_discharge * inputs["omega"]
diff --git a/src/write_outputs/hydrogen/write_hourly_matching_prices.jl b/src/write_outputs/hydrogen/write_hourly_matching_prices.jl
index 4ce5fd142..6dda03f2d 100644
--- a/src/write_outputs/hydrogen/write_hourly_matching_prices.jl
+++ b/src/write_outputs/hydrogen/write_hourly_matching_prices.jl
@@ -5,11 +5,10 @@ function write_hourly_matching_prices(path::AbstractString,
     T = inputs["T"]     # Number of time steps (hours)
     Z = inputs["Z"]     # Number of zones
     
-
     ## Extract dual variables of constraints
     dfHourlyMatchPrices = DataFrame(Zone = 1:Z) # The unit is $/MWh
     # Dividing dual variable for each hour with corresponding hourly weight to retrieve marginal cost of the constraint
-    price = dual.(EP[:cHourlyMatching]) ./ inputs["omega"] 
+    price = dual.(EP[:cHourlyMatching]) ./ inputs["omega"]
     dfHourlyMatchPrices = hcat(dfHourlyMatchPrices,
         DataFrame(transpose(price), :auto))
 
diff --git a/src/write_outputs/min_max_capacity_requirement/write_maximum_capacity_requirement.jl b/src/write_outputs/min_max_capacity_requirement/write_maximum_capacity_requirement.jl
index ea6c3a0ce..fda5d3c9d 100644
--- a/src/write_outputs/min_max_capacity_requirement/write_maximum_capacity_requirement.jl
+++ b/src/write_outputs/min_max_capacity_requirement/write_maximum_capacity_requirement.jl
@@ -8,15 +8,9 @@ function write_maximum_capacity_requirement(path::AbstractString,
                       for maxcap in 1:NumberOfMaxCapReqs],
         Price = -dual.(EP[:cZoneMaxCapReq]))
 
-    
-
-
-
     if haskey(inputs, "MaxCapPriceCap")
         dfMaxCapPrice[!, :Slack] = convert(Array{Float64}, value.(EP[:vMaxCap_slack]))
         dfMaxCapPrice[!, :Penalty] = convert(Array{Float64}, value.(EP[:eCMaxCap_slack]))
-
-
     end
     CSV.write(joinpath(path, "MaxCapReq_prices_and_penalties.csv"), dfMaxCapPrice)
 end
diff --git a/src/write_outputs/min_max_capacity_requirement/write_minimum_capacity_requirement.jl b/src/write_outputs/min_max_capacity_requirement/write_minimum_capacity_requirement.jl
index 9923fc2e3..d1210ce9a 100644
--- a/src/write_outputs/min_max_capacity_requirement/write_minimum_capacity_requirement.jl
+++ b/src/write_outputs/min_max_capacity_requirement/write_minimum_capacity_requirement.jl
@@ -8,15 +8,9 @@ function write_minimum_capacity_requirement(path::AbstractString,
                       for mincap in 1:NumberOfMinCapReqs],
         Price = dual.(EP[:cZoneMinCapReq]))
 
-    
-
-
-
     if haskey(inputs, "MinCapPriceCap")
         dfMinCapPrice[!, :Slack] = convert(Array{Float64}, value.(EP[:vMinCap_slack]))
         dfMinCapPrice[!, :Penalty] = convert(Array{Float64}, value.(EP[:eCMinCap_slack]))
-
-
     end
     CSV.write(joinpath(path, "MinCapReq_prices_and_penalties.csv"), dfMinCapPrice)
 end
diff --git a/src/write_outputs/reserves/write_operating_reserve_price_revenue.jl b/src/write_outputs/reserves/write_operating_reserve_price_revenue.jl
index 9851fb94e..8c87aaf68 100644
--- a/src/write_outputs/reserves/write_operating_reserve_price_revenue.jl
+++ b/src/write_outputs/reserves/write_operating_reserve_price_revenue.jl
@@ -12,7 +12,6 @@ function write_operating_reserve_regulation_revenue(path::AbstractString,
         setup::Dict,
         EP::Model)
     
-
     gen = inputs["RESOURCES"]
     RSV = inputs["RSV"]
     REG = inputs["REG"]
@@ -60,8 +59,7 @@ This is equal to the dual variable of the regulation requirement constraint.
 
 function operating_regulation_price(EP::Model, inputs::Dict, setup::Dict)::Vector{Float64}
     ω = inputs["omega"]
-    
-    return dual.(EP[:cReg]) ./ ω 
+    return dual.(EP[:cReg]) ./ ω
 end
 
 @doc raw"""
diff --git a/src/write_outputs/reserves/write_reg.jl b/src/write_outputs/reserves/write_reg.jl
index 2fc0c17bb..86afbc0a5 100644
--- a/src/write_outputs/reserves/write_reg.jl
+++ b/src/write_outputs/reserves/write_reg.jl
@@ -1,11 +1,10 @@
 function write_reg(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
     REG = inputs["REG"]
     
-
     resources = inputs["RESOURCE_NAMES"][REG]
     zones = inputs["R_ZONES"][REG]
     # Regulation contributions for each resource in each time step
-    reg = value.(EP[:vREG][REG, :].data) 
+    reg = value.(EP[:vREG][REG, :].data)
 
     dfReg = DataFrame(Resource = resources, Zone = zones)
     dfReg.AnnualSum = reg * inputs["omega"]
diff --git a/src/write_outputs/reserves/write_rsv.jl b/src/write_outputs/reserves/write_rsv.jl
index 6686a2f26..d91c35341 100644
--- a/src/write_outputs/reserves/write_rsv.jl
+++ b/src/write_outputs/reserves/write_rsv.jl
@@ -2,10 +2,9 @@ function write_rsv(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
     T = inputs["T"]     # Number of time steps (hours)
     RSV = inputs["RSV"]
     
-
     resources = inputs["RESOURCE_NAMES"][RSV]
     zones = inputs["R_ZONES"][RSV]
-    rsv = value.(EP[:vRSV][RSV, :].data) 
+    rsv = value.(EP[:vRSV][RSV, :].data)
 
     dfRsv = DataFrame(Resource = resources, Zone = zones)
 
@@ -14,7 +13,7 @@ function write_rsv(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
     if setup["WriteOutputs"] == "annual"
         write_annual(joinpath(path, "reg_dn.csv"), dfRsv)
     else # setup["WriteOutputs"] == "full"
-        unmet_vec = value.(EP[:vUNMET_RSV]) 
+        unmet_vec = value.(EP[:vUNMET_RSV])
         total_unmet = sum(unmet_vec)
         dfRsv = hcat(dfRsv, DataFrame(rsv, :auto))
         auxNew_Names = [Symbol("Resource");
diff --git a/src/write_outputs/write_capacityfactor.jl b/src/write_outputs/write_capacityfactor.jl
index 0d9c829b7..c8637d610 100644
--- a/src/write_outputs/write_capacityfactor.jl
+++ b/src/write_outputs/write_capacityfactor.jl
@@ -94,7 +94,6 @@ function write_fusion_net_capacity_factor(path::AbstractString, inputs::Dict, se
     G_fusion = length(gen_fusion)
 
     ω = inputs["omega"]
-    
 
     df = DataFrame(Resource = resource_names,
         Zone = zone_id.(gen_fusion),
@@ -105,10 +104,10 @@ function write_fusion_net_capacity_factor(path::AbstractString, inputs::Dict, se
     reactor = FusionReactorData.(gen_fusion)
     avg_power_factor = average_net_power_factor.(reactor)
 
-    gross_power = value.(EP[:vP][FUSION, :]) * ω 
+    gross_power = value.(EP[:vP][FUSION, :]) * ω
     parasitic_power = thermal_fusion_annual_parasitic_power(EP, inputs, setup)
     df.NetOutput .= gross_power - parasitic_power
-    df.NetCapacity .= value.(EP[:eTotalCap][FUSION])  .* avg_power_factor
+    df.NetCapacity .= value.(EP[:eTotalCap][FUSION]) .* avg_power_factor
 
     # We only calcualte the resulted capacity factor with total capacity > 1MW and total generation > 1MWh
     enough_power = findall(x -> x >= 1, df.NetOutput)
diff --git a/src/write_outputs/write_charge.jl b/src/write_outputs/write_charge.jl
index 193938e55..496479224 100644
--- a/src/write_outputs/write_charge.jl
+++ b/src/write_outputs/write_charge.jl
@@ -18,7 +18,6 @@ function write_charge(path::AbstractString, inputs::Dict, setup::Dict, EP::Model
 
     weight = inputs["omega"]
     
-
     charge = Matrix[]
     charge_ids = Vector{Int}[]
     if !isempty(STOR_ALL)
diff --git a/src/write_outputs/write_charging_cost.jl b/src/write_outputs/write_charging_cost.jl
index 2f7d7f1d9..a850b0b6a 100644
--- a/src/write_outputs/write_charging_cost.jl
+++ b/src/write_outputs/write_charging_cost.jl
@@ -17,7 +17,6 @@ function write_charging_cost(path::AbstractString, inputs::Dict, setup::Dict, EP
 
     weight = inputs["omega"]
     
-
     price = locational_marginal_price(EP, inputs, setup)
 
     chargecost = zeros(G, T)
diff --git a/src/write_outputs/write_co2.jl b/src/write_outputs/write_co2.jl
index 3211492d2..c5fa1d3a1 100644
--- a/src/write_outputs/write_co2.jl
+++ b/src/write_outputs/write_co2.jl
@@ -22,10 +22,8 @@ function write_co2_emissions_plant(path::AbstractString,
 
     weight = inputs["omega"]
     
-
     emissions_plant = value.(EP[:eEmissionsByPlant])
 
-
     df = DataFrame(Resource = resources,
         Zone = zones,
         AnnualSum = zeros(G))
@@ -43,7 +41,6 @@ function write_co2_capture_plant(path::AbstractString, inputs::Dict, setup::Dict
     zones = zone_id.(gen[CCS])
 
     weight = inputs["omega"]
-    
 
     df = DataFrame(Resource = resources,
         Zone = zones,
@@ -51,7 +48,6 @@ function write_co2_capture_plant(path::AbstractString, inputs::Dict, setup::Dict
     if !isempty(CCS)
         emissions_captured_plant = value.(EP[:eEmissionsCaptureByPlant]).data
 
-
         df.AnnualSum .= emissions_captured_plant * weight
 
         write_temporal_data(
diff --git a/src/write_outputs/write_curtailment.jl b/src/write_outputs/write_curtailment.jl
index 43d4cc959..414d6596c 100644
--- a/src/write_outputs/write_curtailment.jl
+++ b/src/write_outputs/write_curtailment.jl
@@ -16,7 +16,6 @@ function write_curtailment(path::AbstractString, inputs::Dict, setup::Dict, EP::
 
     weight = inputs["omega"]
     
-
     curtailment = zeros(G, T)
     curtailment[VRE, :] = (value.(EP[:eTotalCap][VRE]) .* inputs["pP_Max"][VRE, :] .-
                            value.(EP[:vP][VRE, :]))
@@ -48,8 +47,6 @@ function write_curtailment(path::AbstractString, inputs::Dict, setup::Dict, EP::
         end
     end
 
-
-
     df = DataFrame(Resource = resources,
         Zone = zones,
         AnnualSum = zeros(G))
diff --git a/src/write_outputs/write_emissions.jl b/src/write_outputs/write_emissions.jl
index e5f0c5737..1b85848e1 100644
--- a/src/write_outputs/write_emissions.jl
+++ b/src/write_outputs/write_emissions.jl
@@ -8,8 +8,6 @@ function write_emissions(path::AbstractString, inputs::Dict, setup::Dict, EP::Mo
     T = inputs["T"]     # Number of time steps (hours)
     Z = inputs["Z"]     # Number of zones
 
-    
-
     if (setup["WriteShadowPrices"] == 1 || setup["UCommit"] == 0 ||
         (setup["UCommit"] == 2 && (setup["OperationalReserves"] == 0 ||
           (setup["OperationalReserves"] > 0 && inputs["pDynamic_Contingency"] == 0)))) # fully linear model
@@ -23,8 +21,6 @@ function write_emissions(path::AbstractString, inputs::Dict, setup::Dict, EP::Mo
                     for z in findall(x -> x == 1, inputs["dfCO2CapZones"][:, cap])
                         tempCO2Price[z, cap] = (-1) *
                                                dual.(EP[:cCO2Emissions_systemwide])[cap]
-                        # when scaled, The objective function is in unit of Million US$/kton, thus k$/ton, to get $/ton, multiply 1000
-
                     end
                 end
             end
@@ -107,7 +103,7 @@ function write_emissions(path::AbstractString, inputs::Dict, setup::Dict, EP::Mo
             CSV.write(joinpath(path, "emissions.csv"), dfEmissions)
         else# setup["WriteOutputs"] == "full"
             dfEmissions = hcat(dfEmissions,
-                DataFrame(emissions_by_zone , :auto))
+                DataFrame(emissions_by_zone, :auto))
             auxNew_Names = [Symbol("Zone");
                             Symbol("AnnualSum");
                             [Symbol("t$t") for t in 1:T]]
diff --git a/src/write_outputs/write_nse.jl b/src/write_outputs/write_nse.jl
index 649013801..8838c7527 100644
--- a/src/write_outputs/write_nse.jl
+++ b/src/write_outputs/write_nse.jl
@@ -12,9 +12,8 @@ function write_nse(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
         Zone = repeat(1:Z, inner = SEG),
         AnnualSum = zeros(SEG * Z))
     nse = zeros(SEG * Z, T)
-    
     for z in 1:Z
-        nse[((z - 1) * SEG + 1):(z * SEG), :] = value.(EP[:vNSE])[:, :, z] 
+        nse[((z - 1) * SEG + 1):(z * SEG), :] = value.(EP[:vNSE])[:, :, z]
     end
     dfNse.AnnualSum .= nse * inputs["omega"]
 
diff --git a/src/write_outputs/write_power.jl b/src/write_outputs/write_power.jl
index b7789f7b1..6b6cff045 100644
--- a/src/write_outputs/write_power.jl
+++ b/src/write_outputs/write_power.jl
@@ -13,11 +13,9 @@ function write_power(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
     
     weight = inputs["omega"]
     
-
     # Power injected by each resource in each time step
     power = value.(EP[:vP])
 
-
     df = DataFrame(Resource = resources,
         Zone = zones,
         AnnualSum = zeros(G))
diff --git a/src/write_outputs/write_price.jl b/src/write_outputs/write_price.jl
index 611eab4b4..10e658d47 100644
--- a/src/write_outputs/write_price.jl
+++ b/src/write_outputs/write_price.jl
@@ -43,6 +43,5 @@ be calculated only if `WriteShadowPrices` is activated.
 """
 function locational_marginal_price(EP::Model, inputs::Dict, setup::Dict)::Matrix{Float64}
     ω = inputs["omega"]
-    
-    return dual.(EP[:cPowerBalance]) ./ ω 
+    return dual.(EP[:cPowerBalance]) ./ ω
 end
diff --git a/src/write_outputs/write_reliability.jl b/src/write_outputs/write_reliability.jl
index b0330a914..36c83a8d7 100644
--- a/src/write_outputs/write_reliability.jl
+++ b/src/write_outputs/write_reliability.jl
@@ -10,9 +10,8 @@ function write_reliability(path::AbstractString, inputs::Dict, setup::Dict, EP::
     # reliability: Dual variable of maximum NSE constraint = shadow value of reliability constraint
     dfReliability = DataFrame(Zone = 1:Z)
     # Dividing dual variable for each hour with corresponding hourly weight to retrieve marginal cost of generation
-    
     dfReliability = hcat(dfReliability,
-        DataFrame(transpose(dual.(EP[:cMaxNSE]) ./ inputs["omega"] ), :auto))
+        DataFrame(transpose(dual.(EP[:cMaxNSE]) ./ inputs["omega"]), :auto))
 
     auxNew_Names = [Symbol("Zone"); [Symbol("t$t") for t in 1:T]]
     rename!(dfReliability, auxNew_Names)
diff --git a/src/write_outputs/write_storage.jl b/src/write_outputs/write_storage.jl
index 1420bf1a6..53ac2c546 100644
--- a/src/write_outputs/write_storage.jl
+++ b/src/write_outputs/write_storage.jl
@@ -18,7 +18,6 @@ function write_storage(path::AbstractString, inputs::Dict, setup::Dict, EP::Mode
 
     weight = inputs["omega"]
     
-
     stored = Matrix[]
     if !isempty(STOR_ALL)
         push!(stored, value.(EP[:vS]))
@@ -34,7 +33,6 @@ function write_storage(path::AbstractString, inputs::Dict, setup::Dict, EP::Mode
     end
     stored = reduce(vcat, stored, init = zeros(0, T))
 
-
     stored_ids = convert(Vector{Int}, vcat(STOR_ALL, HYDRO_RES, FLEX, VS_STOR))
     df = DataFrame(Resource = resources[stored_ids],
         Zone = zones[stored_ids])

From 7abfca3a2bec4ba7fe7471e809c6585a1b4a171e Mon Sep 17 00:00:00 2001
From: lbonaldo <bonaldo.luca12@gmail.com>
Date: Thu, 16 Jan 2025 16:57:10 -0500
Subject: [PATCH 10/11] Remove `ParameterScale` in `write_opwrap_lds_stor_init`

---
 .../long_duration_storage/write_opwrap_lds_stor_init.jl       | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/src/write_outputs/long_duration_storage/write_opwrap_lds_stor_init.jl b/src/write_outputs/long_duration_storage/write_opwrap_lds_stor_init.jl
index bdcba9e9b..6bc831f97 100644
--- a/src/write_outputs/long_duration_storage/write_opwrap_lds_stor_init.jl
+++ b/src/write_outputs/long_duration_storage/write_opwrap_lds_stor_init.jl
@@ -42,10 +42,6 @@ function write_opwrap_lds_stor_init(path::AbstractString,
     e_total_cap = value.(EP[:eTotalCap])
     v_charge = value.(EP[:vCHARGE])
     v_P = value.(EP[:vP])
-    if setup["ParameterScale"] == 1
-        v_charge *= ModelScalingFactor
-        v_P *= ModelScalingFactor
-    end
     if !isempty(stor_hydro_long_duration)
         v_spill = value.(EP[:vSPILL])
     end

From ed9bbfb8945d736979c5196ecdd2d74fa9a3b782 Mon Sep 17 00:00:00 2001
From: lbonaldo <bonaldo.luca12@gmail.com>
Date: Thu, 16 Jan 2025 16:59:02 -0500
Subject: [PATCH 11/11] Remove `ParameterScale` from TDR

---
 src/time_domain_reduction/time_domain_reduction.jl | 8 +-------
 1 file changed, 1 insertion(+), 7 deletions(-)

diff --git a/src/time_domain_reduction/time_domain_reduction.jl b/src/time_domain_reduction/time_domain_reduction.jl
index 36aa7ecb6..7d08ac560 100644
--- a/src/time_domain_reduction/time_domain_reduction.jl
+++ b/src/time_domain_reduction/time_domain_reduction.jl
@@ -683,16 +683,10 @@ function cluster_inputs(inpath,
     PMap_Outfile = joinpath(TimeDomainReductionFolder, "Period_map.csv")
     YAML_Outfile = joinpath(TimeDomainReductionFolder, "time_domain_reduction_settings.yml")
 
-    # Define a local version of the setup so that you can modify the mysetup["ParameterScale"] value to be zero in case it is 1
-    mysetup_local = copy(mysetup)
-    # If ParameterScale =1 then make it zero, since clustered inputs will be scaled prior to generating model
-    mysetup_local["ParameterScale"] = 0  # Performing cluster and report outputs in user-provided units
-
     # Define another local version of setup such that Multi-Stage Non-Concatentation TDR can iteratively read in the raw data
     mysetup_MS = copy(mysetup)
     mysetup_MS["TimeDomainReduction"] = 0
     mysetup_MS["DoNotReadPeriodMap"] = 1
-    mysetup_MS["ParameterScale"] = 0
 
     if MultiStage == 1
         model_dict = Dict()
@@ -749,7 +743,7 @@ function cluster_inputs(inpath,
         if v
             println("Not MultiStage")
         end
-        myinputs = load_inputs(mysetup_local, inpath)
+        myinputs = load_inputs(mysetup, inpath)
         RESOURCE_ZONES = myinputs["RESOURCE_ZONES"]
         RESOURCES = myinputs["RESOURCE_NAMES"]
         ZONES = myinputs["R_ZONES"]