Thermal Module Empty Collection Reduction
AlannLiu opened this issue · comments
Hello. When I try to run GenX, the code stops at the thermal module.
This is my error message:
ERROR: LoadError: MethodError: reducing over an empty collection is not allowed; consider supplying init to the reducer
Stacktrace:
[1] reduce_empty(op::Base.MappingRF{JuMP.Containers.var"#47#48"{typeof(identity)}, Base.BottomRF{typeof(Base.add_sum)}}, #unused#::Type{JuMP.VariableRef})
@ Base .\reduce.jl:356
[2] reduce_empty_iter
@ .\reduce.jl:379 [inlined]
[3] reduce_empty_iter
@ .\reduce.jl:378 [inlined]
[4] foldl_impl
@ .\reduce.jl:49 [inlined]
[5] mapfoldl_impl
@ .\reduce.jl:44 [inlined]
[6] #mapfoldl#288
@ .\reduce.jl:170 [inlined]
[7] mapfoldl
@ .\reduce.jl:170 [inlined]
[8] #mapreduce#292
@ .\reduce.jl:302 [inlined]
[9] mapreduce
@ .\reduce.jl:302 [inlined]
[10] #sum#295
@ .\reduce.jl:530 [inlined]
[11] sum
@ .\reduce.jl:530 [inlined]
[12] #sum#296
@ .\reduce.jl:559 [inlined]
[13] sum
@ .\reduce.jl:559 [inlined]
[14] #sum#46
@ C:\Users\alanl.julia\packages\JuMP\jZvaU\src\Containers\DenseAxisArray.jl:831 [inlined]
[15] sum
@ C:\Users\alanl.julia\packages\JuMP\jZvaU\src\Containers\DenseAxisArray.jl:825 [inlined]
[16] #sum#49
@ C:\Users\alanl.julia\packages\JuMP\jZvaU\src\Containers\DenseAxisArray.jl:841 [inlined]
[17] sum(x::JuMP.Containers.DenseAxisArray{JuMP.VariableRef, 1, Tuple{Vector{Int64}}, Tuple{JuMP.Containers._AxisLookup{Dict{Int64, Int64}}}})
@ JuMP.Containers C:\Users\alanl.julia\packages\JuMP\jZvaU\src\Containers\DenseAxisArray.jl:840
[18] macro expansion
@ C:\Users\alanl.julia\packages\MutableArithmetics\h0wjj\src\rewrite.jl:322 [inlined]
[19] macro expansion
@ C:\Users\alanl.julia\packages\JuMP\jZvaU\src\macros.jl:1071 [inlined]
[20] (::GenX.var"#687#702"{JuMP.Model, Vector{Int64}, Int64})(y::Int64, t::Int64)
@ GenX C:\Users\alanl.julia\packages\JuMP\jZvaU\src\Containers\macro.jl:301
[21] #87
@ C:\Users\alanl.julia\packages\JuMP\jZvaU\src\Containers\container.jl:124 [inlined]
[22] iterate
@ .\generator.jl:47 [inlined]
[23] collect(itr::Base.Generator{JuMP.Containers.VectorizedProductIterator{Tuple{Vector{Int64}, Base.OneTo{Int64}}}, JuMP.Containers.var"#87#89"{GenX.var"#687#702"{JuMP.Model, Vector{Int64}, Int64}}})
@ Base .\array.jl:782
[24] map(f::Function, A::JuMP.Containers.VectorizedProductIterator{Tuple{Vector{Int64}, Base.OneTo{Int64}}})
@ Base .\abstractarray.jl:3289
[25] container(f::Function, indices::JuMP.Containers.VectorizedProductIterator{Tuple{Vector{Int64}, Base.OneTo{Int64}}}, ::Type{JuMP.Containers.DenseAxisArray}, names::Vector{Any})
@ JuMP.Containers C:\Users\alanl.julia\packages\JuMP\jZvaU\src\Containers\container.jl:123
[26] container(f::Function, indices::JuMP.Containers.VectorizedProductIterator{Tuple{Vector{Int64}, Base.OneTo{Int64}}}, #unused#::Type{JuMP.Containers.AutoContainerType}, names::Vector{Any})
@ JuMP.Containers C:\Users\alanl.julia\packages\JuMP\jZvaU\src\Containers\container.jl:75
[27] thermal_commit!(EP::JuMP.Model, inputs::Dict{Any, Any}, setup::Dict{Any, Any})
@ GenX .\Users\alanl\OneDrive\Desktop\GenX\src\model\resources\thermal\thermal_commit.jl:214
[28] thermal!(EP::JuMP.Model, inputs::Dict{Any, Any}, setup::Dict{Any, Any})
@ GenX .\Users\alanl\OneDrive\Desktop\GenX\src\model\resources\thermal\thermal.jl:19
[29] generate_model(setup::Dict{Any, Any}, inputs::Dict{Any, Any}, OPTIMIZER::MathOptInterface.OptimizerWithAttributes)
@ GenX .\Users\alanl\OneDrive\Desktop\GenX\src\model\generate_model.jl:173
[30] macro expansion
@ .\timing.jl:393 [inlined]
[31] run_genx_case_simple!(case::String, mysetup::Dict{Any, Any})
@ GenX .\Users\alanl\OneDrive\Desktop\GenX\src\case_runners\case_runner.jl:62
[32] run_genx_case!(case::String)
@ GenX .\Users\alanl\OneDrive\Desktop\GenX\src\case_runners\case_runner.jl:21
[33] top-level scope
@ C:\Users\alanl\OneDrive\Desktop\GenX\Example_Systems\RealSystemExample\ISONE_Singlezone\Cases\case_20\Run.jl:3
[34] include
@ .\client.jl:478 [inlined]
[35] run_job_sequential(i::Int64)
@ Main C:\Users\alanl\OneDrive\Desktop\GenX\Example_Systems\RealSystemExample\ISONE_Singlezone\caserunner.jl:42
[36] run_job(i::Int64)
@ Main C:\Users\alanl\OneDrive\Desktop\GenX\Example_Systems\RealSystemExample\ISONE_Singlezone\caserunner.jl:32
[37] launch_new_case(i::Int64, df::DataFrame, files_with_keys::Vector{String})
@ Main C:\Users\alanl\OneDrive\Desktop\GenX\Example_Systems\RealSystemExample\ISONE_Singlezone\caserunner.jl:379
[38] launch_new_cases()
@ Main C:\Users\alanl\OneDrive\Desktop\GenX\Example_Systems\RealSystemExample\ISONE_Singlezone\caserunner.jl:394
[39] top-level scope
@ C:\Users\alanl\OneDrive\Desktop\GenX\Example_Systems\RealSystemExample\ISONE_Singlezone\caserunner.jl:399
[40] include(fname::String)
@ Base.MainInclude .\client.jl:478
[41] top-level scope
@ REPL[8]:1
in expression starting at C:\Users\alanl\OneDrive\Desktop\GenX\Example_Systems\RealSystemExample\ISONE_Singlezone\Cases\case_20\Run.jl:3
in expression starting at C:\Users\alanl\OneDrive\Desktop\GenX\Example_Systems\RealSystemExample\ISONE_Singlezone\caserunner.jl:399
This are my packages:
Project GenX v0.3.5
Status C:\Users\alanl\OneDrive\Desktop\GenX\Project.toml
[336ed68f] CSV v0.10.11
[9961bab8] Cbc v1.1.1
[e2554f3b] Clp v1.0.3
[aaaa29a8] Clustering v0.15.4
[861a8166] Combinatorics v1.0.2
[a93c6f00] DataFrames v1.6.1
[864edb3b] DataStructures v0.18.14
[b4f34e82] Distances v0.10.9
[2e9cd046] Gurobi v1.0.1
[87dc4568] HiGHS v1.5.2
[4076af6c] JuMP v1.13.0
[b8f27783] MathOptInterface v1.18.0
[731186ca] RecursiveArrayTools v2.38.7
[2913bbd2] StatsBase v0.34.0
[ddb6d928] YAML v0.4.9
[d7ed1dd3] MUMPS_seq_jll v500.600.100+0
[ade2ca70] Dates
[37e2e46d] LinearAlgebra
[9a3f8284] Random
[10745b16] Statistics v1.9.0
I am using Julia 1.9.1
Hi Alann,
This issue was fixed in GenX v0.3.6, and is due to changes made in JuMP v1.13; I believe we had previously been using v1.11. We'd recommend that you update to v0.3.6.
If for some reason you cannot update GenX, but you can modify your installation, make the changes as seen in the commit here: 7c85cc7
I believe this issue is caused when some thermal generators have Up_Time or Down_Time of 0.
We were able to fix this issue with your recommendation. Thank you.
Glad to hear it.