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This commit adds the option of deciding which files to write and which ones to skip. Also, among the time-series files, it gives users the option to choose between writing the hourly outputs versus annual values. It does so by adding a new settings parameter called "WriteOutputs" that can be set to annual or full and also introducing a new YAML file called output_settings.yml --------- Co-authored-by: Chakrabarti, Sambuddha (Sam) <[email protected]>
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Example_Systems/RealSystemExample/ISONE_Singlezone/Settings/output_settings.yml
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WriteCosts: false | ||
WriteCapacity: false | ||
WriteCapacityValue: false | ||
WriteCapacityFactor: false | ||
WriteCharge: false | ||
WriteChargingCost: false | ||
WriteCO2: false | ||
WriteCO2Cap: false | ||
WriteCommit: false | ||
WriteCurtailment: false | ||
WriteEmissions: false | ||
WriteEnergyRevenue: false | ||
WriteESRPrices: false | ||
WriteESRRevenue: false | ||
WriteFuelConsumption: false | ||
WriteHourlyMatchingPrices: false | ||
WriteHydrogenPrices: false | ||
WriteMaintenance: false | ||
WriteMaxCapReq: false | ||
WriteMinCapReq: false | ||
WriteNetRevenue: false | ||
WriteNSE: false | ||
WriteNWExpansion: false | ||
WriteTransmissionFlows: false | ||
WriteTransmissionLosses: false | ||
WriteVirtualDischarge: false | ||
WriteVREStor: false |
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Original file line number | Diff line number | Diff line change |
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@@ -1,23 +1,20 @@ | ||
function write_reg(path::AbstractString, inputs::Dict, setup::Dict, EP::Model) | ||
gen = inputs["RESOURCES"] | ||
zones = zone_id.(gen) | ||
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G = inputs["G"] # Number of resources (generators, storage, DR, and DERs) | ||
T = inputs["T"] # Number of time steps (hours) | ||
REG = inputs["REG"] | ||
scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1 | ||
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resources = inputs["RESOURCE_NAMES"][REG] | ||
zones = inputs["R_ZONES"][REG] | ||
# Regulation contributions for each resource in each time step | ||
dfReg = DataFrame(Resource = inputs["RESOURCE_NAMES"], Zone = zones) | ||
reg = zeros(G,T) | ||
reg[REG, :] = value.(EP[:vREG][REG, :]) | ||
dfReg.AnnualSum = (reg*scale_factor) * inputs["omega"] | ||
dfReg = hcat(dfReg, DataFrame(reg*scale_factor, :auto)) | ||
auxNew_Names=[Symbol("Resource");Symbol("Zone");Symbol("AnnualSum");[Symbol("t$t") for t in 1:T]] | ||
rename!(dfReg,auxNew_Names) | ||
reg = value.(EP[:vREG][REG, :].data) * scale_factor | ||
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dfReg = DataFrame(Resource = resources, Zone = zones) | ||
dfReg.AnnualSum = reg * inputs["omega"] | ||
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total = DataFrame(["Total" 0 sum(dfReg.AnnualSum) fill(0.0, (1,T))], :auto) | ||
total[!, 4:T+3] .= sum(reg, dims = 1) | ||
rename!(total,auxNew_Names) | ||
dfReg = vcat(dfReg, total) | ||
CSV.write(joinpath(path, "reg.csv"), dftranspose(dfReg, false), header=false) | ||
filepath = joinpath(path, "reg.csv") | ||
if setup["WriteOutputs"] == "annual" | ||
write_annual(filepath, dfReg) | ||
else # setup["WriteOutputs"] == "full" | ||
write_fulltimeseries(filepath, reg, dfReg) | ||
end | ||
return nothing | ||
end |
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@@ -1,28 +1,31 @@ | ||
function write_rsv(path::AbstractString, inputs::Dict, setup::Dict, EP::Model) | ||
gen = inputs["RESOURCES"] | ||
zones = zone_id.(gen) | ||
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G = inputs["G"] # Number of resources (generators, storage, DR, and DERs) | ||
T = inputs["T"] # Number of time steps (hours) | ||
RSV = inputs["RSV"] | ||
scale_factor = setup["ParameterScale"] == 1 ? ModelScalingFactor : 1 | ||
dfRsv = DataFrame(Resource = inputs["RESOURCE_NAMES"], Zone = zones) | ||
rsv = zeros(G,T) | ||
unmet_vec = zeros(T) | ||
rsv[RSV, :] = value.(EP[:vRSV][RSV, :]) * scale_factor | ||
unmet_vec = value.(EP[:vUNMET_RSV]) * scale_factor | ||
total_unmet = sum(unmet_vec) | ||
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resources = inputs["RESOURCE_NAMES"][RSV] | ||
zones = inputs["R_ZONES"][RSV] | ||
rsv = value.(EP[:vRSV][RSV, :].data) * scale_factor | ||
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dfRsv = DataFrame(Resource = resources, Zone = zones) | ||
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dfRsv.AnnualSum = rsv * inputs["omega"] | ||
dfRsv = hcat(dfRsv, DataFrame(rsv, :auto)) | ||
auxNew_Names=[Symbol("Resource");Symbol("Zone");Symbol("AnnualSum");[Symbol("t$t") for t in 1:T]] | ||
rename!(dfRsv,auxNew_Names) | ||
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total = DataFrame(["Total" 0 sum(dfRsv.AnnualSum) zeros(1, T)], :auto) | ||
unmet = DataFrame(["unmet" 0 total_unmet zeros(1, T)], :auto) | ||
total[!, 4:T+3] .= sum(rsv, dims = 1) | ||
unmet[!, 4:T+3] .= transpose(unmet_vec) | ||
rename!(total,auxNew_Names) | ||
rename!(unmet,auxNew_Names) | ||
dfRsv = vcat(dfRsv, unmet, total) | ||
CSV.write(joinpath(path, "reg_dn.csv"), dftranspose(dfRsv, false), header=false) | ||
if setup["WriteOutputs"] == "annual" | ||
write_annual(joinpath(path, "reg_dn.csv"), dfRsv) | ||
else # setup["WriteOutputs"] == "full" | ||
unmet_vec = value.(EP[:vUNMET_RSV]) * scale_factor | ||
total_unmet = sum(unmet_vec) | ||
dfRsv = hcat(dfRsv, DataFrame(rsv, :auto)) | ||
auxNew_Names=[Symbol("Resource");Symbol("Zone");Symbol("AnnualSum");[Symbol("t$t") for t in 1:T]] | ||
rename!(dfRsv,auxNew_Names) | ||
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total = DataFrame(["Total" 0 sum(dfRsv.AnnualSum) zeros(1, T)], :auto) | ||
unmet = DataFrame(["unmet" 0 total_unmet zeros(1, T)], :auto) | ||
total[!, 4:T+3] .= sum(rsv, dims = 1) | ||
unmet[!, 4:T+3] .= transpose(unmet_vec) | ||
rename!(total,auxNew_Names) | ||
rename!(unmet,auxNew_Names) | ||
dfRsv = vcat(dfRsv, unmet, total) | ||
CSV.write(joinpath(path, "reg_dn.csv"), dftranspose(dfRsv, false), writeheader=false) | ||
end | ||
end |
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