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39 lines
1.2 KiB
39 lines
1.2 KiB
# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
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# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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using UnitCommitment, Cbc, HiGHS, JuMP
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import UnitCommitment:
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AELMP
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@testset "aelmp" begin
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path = "$FIXTURES/aelmp_simple.json.gz"
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# model has to be solved first
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instance = UnitCommitment.read(path)
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model = UnitCommitment.build_model(
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instance=instance,
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optimizer=Cbc.Optimizer,
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variable_names = true,
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)
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JuMP.set_silent(model)
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UnitCommitment.optimize!(model)
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# policy 1: allow offlines; consider startups
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aelmp_1 = UnitCommitment.compute_lmp(
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model,
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AELMP.Method(),
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optimizer=HiGHS.Optimizer
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)
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@test aelmp_1["B1", 1] ≈ 231.7 atol = 0.1
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# policy 2: do not allow offlines; but consider startups
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aelmp_2 = UnitCommitment.compute_lmp(
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model,
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AELMP.Method(
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allow_offline_participation=false,
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consider_startup_costs=true
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),
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optimizer=HiGHS.Optimizer
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)
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@test aelmp_2["B1", 1] ≈ 274.3 atol = 0.1
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end |