Add method to calculate locational marginal prices (GenXProject#582)

src/write_outputs/write_charging_cost.jl

@@ -7,25 +7,27 @@ function write_charging_cost(path::AbstractString, inputs::Dict, setup::Dict, EP
 	ELECTROLYZER = inputs["ELECTROLYZER"]
 	VRE_STOR = inputs["VRE_STOR"]
 	VS_STOR = !isempty(VRE_STOR) ? inputs["VS_STOR"] : []
-
+
+    price = locational_marginal_price(EP, inputs, setup)
+
 	dfChargingcost = DataFrame(Region = dfGen[!, :region], Resource = inputs["RESOURCES"], Zone = dfGen[!, :Zone], Cluster = dfGen[!, :cluster], AnnualSum = Array{Float64}(undef, G),)
 	chargecost = zeros(G, T)
 	if !isempty(STOR_ALL)
-	    chargecost[STOR_ALL, :] .= (value.(EP[:vCHARGE][STOR_ALL, :]).data) .* transpose(dual.(EP[:cPowerBalance]) ./ inputs["omega"])[dfGen[STOR_ALL, :Zone], :]
+	    chargecost[STOR_ALL, :] .= (value.(EP[:vCHARGE][STOR_ALL, :]).data) .* transpose(price)[dfGen[STOR_ALL, :Zone], :]
 	end
 	if !isempty(FLEX)
-	    chargecost[FLEX, :] .= value.(EP[:vP][FLEX, :]) .* transpose(dual.(EP[:cPowerBalance]) ./ inputs["omega"])[dfGen[FLEX, :Zone], :]
+	    chargecost[FLEX, :] .= value.(EP[:vP][FLEX, :]) .* transpose(price)[dfGen[FLEX, :Zone], :]
 	end
 	if !isempty(ELECTROLYZER)
-		chargecost[ELECTROLYZER, :] .= (value.(EP[:vUSE][ELECTROLYZER, :]).data) .* transpose(dual.(EP[:cPowerBalance]) ./ inputs["omega"])[dfGen[ELECTROLYZER, :Zone], :]
+		chargecost[ELECTROLYZER, :] .= (value.(EP[:vUSE][ELECTROLYZER, :]).data) .* transpose(price)[dfGen[ELECTROLYZER, :Zone], :]
 	end
 	if !isempty(VS_STOR)
-		chargecost[VS_STOR, :] .= value.(EP[:vCHARGE_VRE_STOR][VS_STOR, :].data) .* transpose(dual.(EP[:cPowerBalance]) ./ inputs["omega"])[dfGen[VS_STOR, :Zone], :]
+		chargecost[VS_STOR, :] .= value.(EP[:vCHARGE_VRE_STOR][VS_STOR, :].data) .* transpose(price)[dfGen[VS_STOR, :Zone], :]
 	end
 	if setup["ParameterScale"] == 1
-	    chargecost *= ModelScalingFactor^2
+	    chargecost *= ModelScalingFactor
 	end
 	dfChargingcost.AnnualSum .= chargecost * inputs["omega"]
-	CSV.write(joinpath(path, "ChargingCost.csv"), dfChargingcost)
+	write_simple_csv(joinpath(path, "ChargingCost.csv"), dfChargingcost)
 	return dfChargingcost
 end

src/write_outputs/write_energy_revenue.jl

@@ -11,14 +11,15 @@ function write_energy_revenue(path::AbstractString, inputs::Dict, setup::Dict, E
 	NONFLEX = setdiff(collect(1:G), FLEX)
 	dfEnergyRevenue = DataFrame(Region = dfGen.region, Resource = inputs["RESOURCES"], Zone = dfGen.Zone, Cluster = dfGen.cluster, AnnualSum = Array{Float64}(undef, G),)
 	energyrevenue = zeros(G, T)
-	energyrevenue[NONFLEX, :] = value.(EP[:vP][NONFLEX, :]) .* transpose(dual.(EP[:cPowerBalance]) ./ inputs["omega"])[dfGen[NONFLEX, :Zone], :]
+    price = locational_marginal_price(EP, inputs, setup)
+    energyrevenue[NONFLEX, :] = value.(EP[:vP][NONFLEX, :]) .* transpose(price)[dfGen[NONFLEX, :Zone], :]
 	if !isempty(FLEX)
-		energyrevenue[FLEX, :] = value.(EP[:vCHARGE_FLEX][FLEX, :]).data .* transpose(dual.(EP[:cPowerBalance]) ./ inputs["omega"])[dfGen[FLEX, :Zone], :]
+		energyrevenue[FLEX, :] = value.(EP[:vCHARGE_FLEX][FLEX, :]).data .* transpose(price)[dfGen[FLEX, :Zone], :]
 	end
 	if setup["ParameterScale"] == 1
-		energyrevenue *= ModelScalingFactor^2
+		energyrevenue *= ModelScalingFactor
 	end
 	dfEnergyRevenue.AnnualSum .= energyrevenue * inputs["omega"]
-	CSV.write(joinpath(path, "EnergyRevenue.csv"), dfEnergyRevenue)
+	write_simple_csv(joinpath(path, "EnergyRevenue.csv"), dfEnergyRevenue)
 	return dfEnergyRevenue
 end

src/write_outputs/write_price.jl

@@ -10,9 +10,9 @@ function write_price(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
 	## Extract dual variables of constraints
 	# Electricity price: Dual variable of hourly power balance constraint = hourly price
 	dfPrice = DataFrame(Zone = 1:Z) # The unit is $/MWh
-	scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1
 	# Dividing dual variable for each hour with corresponding hourly weight to retrieve marginal cost of generation
-	dfPrice = hcat(dfPrice, DataFrame(transpose(dual.(EP[:cPowerBalance])./inputs["omega"]*scale_factor), :auto))
+    price = locational_marginal_price(EP, inputs, setup)
+	dfPrice = hcat(dfPrice, DataFrame(transpose(price), :auto))
 
 	auxNew_Names=[Symbol("Zone");[Symbol("t$t") for t in 1:T]]
 	rename!(dfPrice,auxNew_Names)
@@ -21,3 +21,21 @@ function write_price(path::AbstractString, inputs::Dict, setup::Dict, EP::Model)
 	CSV.write(joinpath(path, "prices.csv"), dftranspose(dfPrice, false), writeheader=false)
 	return dfPrice
 end
+
+@doc raw"""
+	locational_marginal_price(EP::Model, inputs::Dict, setup::Dict)
+
+Marginal electricity price for each model zone and time step.
+This is equal to the dual variable of the power balance constraint.
+When solving a linear program (i.e. linearized unit commitment or economic dispatch)
+this output is always available; when solving a mixed integer linear program, this can
+be calculated only if `WriteShadowPrices` is activated.
+
+    Returns a matrix of size (T, Z).
+    Values have units of $/MWh
+"""
+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
+end