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UnitCommitment.jl
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Make test/ a standalone project

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new-tests
Alinson S. Xavier 2 years ago
parent 6db2ca76e8
commit 1afd71b97b
Signed by: isoron
GPG Key ID: 0DA8E4B9E1109DCA
36 changed files with 1070 additions and 1097 deletions
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33
.github/workflows/test.yml vendored
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name: Tests
name: Build & Test
on:
push:
pull_request:
@ -6,19 +6,30 @@ on:
- cron: '45 10 * * *'
jobs:
test:
name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }}
runs-on: ${{ matrix.os }}
strategy:
matrix:
julia-version: ['1.6', '1.7']
julia-arch: [x64]
os: [ubuntu-latest, windows-latest, macOS-latest]
exclude:
- os: macOS-latest
julia-arch: x86
version: ['1.6', '1.7', '1.8', '1.9']
os:
- ubuntu-latest
arch:
- x64
steps:
- uses: actions/checkout@v2
- uses: julia-actions/setup-julia@latest
- uses: julia-actions/setup-julia@v1
with:
version: ${{ matrix.julia-version }}
- uses: julia-actions/julia-buildpkg@latest
- uses: julia-actions/julia-runtest@latest
version: ${{ matrix.version }}
arch: ${{ matrix.arch }}
- name: Run tests
shell: julia --color=yes --project=test {0}
run: |
using Pkg
Pkg.develop(path=".")
Pkg.update()
using UnitCommitmentT
try
runtests()
catch
exit(1)
end

14
Makefile
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VERSION := 0.3
clean:
rm -rfv build Manifest.toml test/Manifest.toml deps/formatter/build deps/formatter/Manifest.toml
docs:
cd docs; julia --project=. make.jl; cd ..
rsync -avP --delete-after docs/build/ ../docs/$(VERSION)/
format:
cd deps/formatter; ../../juliaw format.jl
test: test/Manifest.toml
./juliaw test/runtests.jl
test/Manifest.toml: test/Project.toml
julia --project=test -e "using Pkg; Pkg.instantiate()"
.PHONY: docs test format install-deps
.PHONY: docs

5
deps/formatter/Project.toml vendored
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[deps]
JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
[compat]
JuliaFormatter = "0.14.4"

9
deps/formatter/format.jl vendored
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using JuliaFormatter
format(
[
"../../src",
"../../test",
"../../benchmark/run.jl",
],
verbose=true,
)

75
juliaw
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#!/bin/bash
# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
if [ ! -e Project.toml ]; then
echo "juliaw: Project.toml not found"
exit 1
fi
if [ ! -e Manifest.toml ]; then
julia --project=. -e 'using Pkg; Pkg.instantiate()' || exit 1
fi
if [ ! -e build/sysimage.so -o Project.toml -nt build/sysimage.so ]; then
echo "juliaw: rebuilding system image..."
# Generate temporary project folder
rm -rf $HOME/.juliaw
mkdir -p $HOME/.juliaw/src
cp Project.toml Manifest.toml $HOME/.juliaw
NAME=$(julia -e 'using TOML; toml = TOML.parsefile("Project.toml"); "name" in keys(toml) && print(toml["name"])')
if [ ! -z $NAME ]; then
cat > $HOME/.juliaw/src/$NAME.jl << EOF
module $NAME
end
EOF
fi
# Add PackageCompiler dependencies to temporary project
julia --project=$HOME/.juliaw -e 'using Pkg; Pkg.add(["PackageCompiler", "TOML", "Logging"])'
# Generate system image scripts
cat > $HOME/.juliaw/sysimage.jl << EOF
using PackageCompiler
using TOML
using Logging
Logging.disable_logging(Logging.Info)
mkpath("$PWD/build")
println("juliaw: generating precompilation statements...")
run(\`julia --project="$PWD" --trace-compile="$PWD"/build/precompile.jl \$(ARGS)\`)
println("juliaw: finding dependencies...")
project = TOML.parsefile("Project.toml")
manifest = TOML.parsefile("Manifest.toml")
deps = Symbol[]
for dep in keys(project["deps"])
if dep in keys(manifest)
# Up to Julia 1.6
dep_entry = manifest[dep][1]
else
# Julia 1.7+
dep_entry = manifest["deps"][dep][1]
end
if "path" in keys(dep_entry)
println(" - \$(dep) [skip]")
else
println(" - \$(dep)")
push!(deps, Symbol(dep))
end
end
println("juliaw: building system image...")
create_sysimage(
deps,
precompile_statements_file = "$PWD/build/precompile.jl",
sysimage_path = "$PWD/build/sysimage.so",
)
EOF
julia --project=$HOME/.juliaw $HOME/.juliaw/sysimage.jl $*
else
julia --project=. --sysimage build/sysimage.so $*
fi

22
test/Project.toml
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name = "UnitCommitmentT"
uuid = "a3b7a17a-ab64-45e4-a924-cd5ae7dc644e"
authors = ["Alinson S. Xavier <git@axavier.org>"]
version = "0.1.0"
[deps]
Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
@ -6,21 +11,10 @@ GZip = "92fee26a-97fe-5a0c-ad85-20a5f3185b63"
HiGHS = "87dc4568-4c63-4d18-b0c0-bb2238e4078b"
JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
PackageCompiler = "9b87118b-4619-50d2-8e1e-99f35a4d4d9d"
Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
[compat]
DataStructures = "0.18"
Distributions = "0.25"
GZip = "0.5"
JSON = "0.21"
JuMP = "1"
MathOptInterface = "1"
PackageCompiler = "1"
julia = "1"
UnitCommitment = "64606440-39ea-11e9-0f29-3303a1d3d877"

21
test/import/egret_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment
@testset "read_egret_solution" begin
solution =
UnitCommitment.read_egret_solution("$FIXTURES/egret_output.json.gz")
for attr in
["Is on", "Thermal production (MW)", "Thermal production cost (\$)"]
@test attr in keys(solution)
@test "115_STEAM_1" in keys(solution[attr])
@test length(solution[attr]["115_STEAM_1"]) == 48
end
@test solution["Thermal production cost (\$)"]["315_CT_6"][15:20] ==
[0.0, 0.0, 884.44, 1470.71, 1470.71, 884.44]
@test solution["Startup cost (\$)"]["315_CT_6"][15:20] ==
[0.0, 0.0, 5665.23, 0.0, 0.0, 0.0]
@test length(keys(solution["Is on"])) == 154
end

22
test/instance/migrate_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
@testset "read v0.2" begin
instance = UnitCommitment.read("$FIXTURES/ucjl-0.2.json.gz")
@test length(instance.scenarios) == 1
sc = instance.scenarios[1]
@test length(sc.reserves_by_name["r1"].amount) == 4
@test sc.thermal_units_by_name["g2"].reserves[1].name == "r1"
end
@testset "read v0.3" begin
instance = UnitCommitment.read("$FIXTURES/ucjl-0.3.json.gz")
@test length(instance.scenarios) == 1
sc = instance.scenarios[1]
@test length(sc.thermal_units) == 6
@test length(sc.buses) == 14
@test length(sc.lines) == 20
end

166
test/instance/read_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
@testset "read_benchmark" begin
instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
@test repr(instance) == (
"UnitCommitmentInstance(1 scenarios, 6 thermal units, 0 profiled units, 14 buses, " *
"20 lines, 19 contingencies, 1 price sensitive loads, 4 time steps)"
)
@test length(instance.scenarios) == 1
sc = instance.scenarios[1]
@test length(sc.lines) == 20
@test length(sc.buses) == 14
@test length(sc.thermal_units) == 6
@test length(sc.contingencies) == 19
@test length(sc.price_sensitive_loads) == 1
@test instance.time == 4
@test sc.lines[5].name == "l5"
@test sc.lines[5].source.name == "b2"
@test sc.lines[5].target.name == "b5"
@test sc.lines[5].reactance ≈ 0.17388
@test sc.lines[5].susceptance ≈ 10.037550333
@test sc.lines[5].normal_flow_limit == [1e8 for t in 1:4]
@test sc.lines[5].emergency_flow_limit == [1e8 for t in 1:4]
@test sc.lines[5].flow_limit_penalty == [5e3 for t in 1:4]
@test sc.lines_by_name["l5"].name == "l5"
@test sc.lines[1].name == "l1"
@test sc.lines[1].source.name == "b1"
@test sc.lines[1].target.name == "b2"
@test sc.lines[1].reactance ≈ 0.059170
@test sc.lines[1].susceptance ≈ 29.496860773945
@test sc.lines[1].normal_flow_limit == [300.0 for t in 1:4]
@test sc.lines[1].emergency_flow_limit == [400.0 for t in 1:4]
@test sc.lines[1].flow_limit_penalty == [1e3 for t in 1:4]
@test sc.buses[9].name == "b9"
@test sc.buses[9].load == [35.36638, 33.25495, 31.67138, 31.14353]
@test sc.buses_by_name["b9"].name == "b9"
@test sc.reserves[1].name == "r1"
@test sc.reserves[1].type == "spinning"
@test sc.reserves[1].amount == [100.0, 100.0, 100.0, 100.0]
@test sc.reserves_by_name["r1"].name == "r1"
unit = sc.thermal_units[1]
@test unit.name == "g1"
@test unit.bus.name == "b1"
@test unit.ramp_up_limit == 1e6
@test unit.ramp_down_limit == 1e6
@test unit.startup_limit == 1e6
@test unit.shutdown_limit == 1e6
@test unit.must_run == [false for t in 1:4]
@test unit.min_power_cost == [1400.0 for t in 1:4]
@test unit.min_uptime == 1
@test unit.min_downtime == 1
for t in 1:1
@test unit.cost_segments[1].mw[t] == 10.0
@test unit.cost_segments[2].mw[t] == 20.0
@test unit.cost_segments[3].mw[t] == 5.0
@test unit.cost_segments[1].cost[t] ≈ 20.0
@test unit.cost_segments[2].cost[t] ≈ 30.0
@test unit.cost_segments[3].cost[t] ≈ 40.0
end
@test length(unit.startup_categories) == 3
@test unit.startup_categories[1].delay == 1
@test unit.startup_categories[2].delay == 2
@test unit.startup_categories[3].delay == 3
@test unit.startup_categories[1].cost == 1000.0
@test unit.startup_categories[2].cost == 1500.0
@test unit.startup_categories[3].cost == 2000.0
@test length(unit.reserves) == 0
@test sc.thermal_units_by_name["g1"].name == "g1"
unit = sc.thermal_units[2]
@test unit.name == "g2"
@test unit.must_run == [false for t in 1:4]
@test length(unit.reserves) == 1
unit = sc.thermal_units[3]
@test unit.name == "g3"
@test unit.bus.name == "b3"
@test unit.ramp_up_limit == 70.0
@test unit.ramp_down_limit == 70.0
@test unit.startup_limit == 70.0
@test unit.shutdown_limit == 70.0
@test unit.must_run == [true for t in 1:4]
@test unit.min_power_cost == [0.0 for t in 1:4]
@test unit.min_uptime == 1
@test unit.min_downtime == 1
for t in 1:4
@test unit.cost_segments[1].mw[t] ≈ 33
@test unit.cost_segments[2].mw[t] ≈ 33
@test unit.cost_segments[3].mw[t] ≈ 34
@test unit.cost_segments[1].cost[t] ≈ 33.75
@test unit.cost_segments[2].cost[t] ≈ 38.04
@test unit.cost_segments[3].cost[t] ≈ 44.77853
end
@test length(unit.reserves) == 1
@test unit.reserves[1].name == "r1"
@test sc.contingencies[1].lines == [sc.lines[1]]
@test sc.contingencies[1].thermal_units == []
@test sc.contingencies[1].name == "c1"
@test sc.contingencies_by_name["c1"].name == "c1"
load = sc.price_sensitive_loads[1]
@test load.name == "ps1"
@test load.bus.name == "b3"
@test load.revenue == [100.0 for t in 1:4]
@test load.demand == [50.0 for t in 1:4]
@test sc.price_sensitive_loads_by_name["ps1"].name == "ps1"
end
@testset "read_benchmark sub-hourly" begin
instance = UnitCommitment.read("$FIXTURES/case14-sub-hourly.json.gz")
@test instance.time == 4
unit = instance.scenarios[1].thermal_units[1]
@test unit.name == "g1"
@test unit.min_uptime == 2
@test unit.min_downtime == 2
@test length(unit.startup_categories) == 3
@test unit.startup_categories[1].delay == 2
@test unit.startup_categories[2].delay == 4
@test unit.startup_categories[3].delay == 6
@test unit.initial_status == -200
end
@testset "read_benchmark profiled-units" begin
instance = UnitCommitment.read("$FIXTURES/case14-profiled.json.gz")
sc = instance.scenarios[1]
@test length(sc.profiled_units) == 2
first_pu = sc.profiled_units[1]
@test first_pu.name == "g7"
@test first_pu.bus.name == "b4"
@test first_pu.cost == [100.0 for t in 1:4]
@test first_pu.min_power == [60.0 for t in 1:4]
@test first_pu.max_power == [100.0 for t in 1:4]
@test sc.profiled_units_by_name["g7"].name == "g7"
second_pu = sc.profiled_units[2]
@test second_pu.name == "g8"
@test second_pu.bus.name == "b5"
@test second_pu.cost == [50.0 for t in 1:4]
@test second_pu.min_power == [0.0 for t in 1:4]
@test second_pu.max_power == [120.0 for t in 1:4]
@test sc.profiled_units_by_name["g8"].name == "g8"
end
@testset "read_benchmark commitmemt-status" begin
instance = UnitCommitment.read("$FIXTURES/case14-fixed-status.json.gz")
sc = instance.scenarios[1]
@test sc.thermal_units[1].commitment_status == [nothing for t in 1:4]
@test sc.thermal_units[2].commitment_status == [true for t in 1:4]
@test sc.thermal_units[4].commitment_status == [false for t in 1:4]
@test sc.thermal_units[6].commitment_status ==
[false, nothing, true, nothing]
end

35
test/lmp/aelmp_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Cbc, HiGHS, JuMP
import UnitCommitment: AELMP
@testset "aelmp" begin
path = "$FIXTURES/aelmp_simple.json.gz"
# model has to be solved first
instance = UnitCommitment.read(path)
model = UnitCommitment.build_model(
instance = instance,
optimizer = Cbc.Optimizer,
variable_names = true,
)
JuMP.set_silent(model)
UnitCommitment.optimize!(model)
# policy 1: allow offlines; consider startups
aelmp_1 =
UnitCommitment.compute_lmp(model, AELMP(), optimizer = HiGHS.Optimizer)
@test aelmp_1["s1", "B1", 1] ≈ 231.7 atol = 0.1
# policy 2: do not allow offlines; but consider startups
aelmp_2 = UnitCommitment.compute_lmp(
model,
AELMP(
allow_offline_participation = false,
consider_startup_costs = true,
),
optimizer = HiGHS.Optimizer,
)
@test aelmp_2["s1", "B1", 1] ≈ 274.3 atol = 0.1
end

51
test/lmp/conventional_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Cbc, HiGHS, JuMP
import UnitCommitment: ConventionalLMP
function solve_conventional_testcase(path::String)
instance = UnitCommitment.read(path)
model = UnitCommitment.build_model(
instance = instance,
optimizer = Cbc.Optimizer,
variable_names = true,
)
JuMP.set_silent(model)
UnitCommitment.optimize!(model)
lmp = UnitCommitment.compute_lmp(
model,
ConventionalLMP(),
optimizer = HiGHS.Optimizer,
)
return lmp
end
@testset "conventional" begin
# instance 1
path = "$FIXTURES/lmp_simple_test_1.json.gz"
lmp = solve_conventional_testcase(path)
@test lmp["s1", "A", 1] == 50.0
@test lmp["s1", "B", 1] == 50.0
# instance 2
path = "$FIXTURES/lmp_simple_test_2.json.gz"
lmp = solve_conventional_testcase(path)
@test lmp["s1", "A", 1] == 50.0
@test lmp["s1", "B", 1] == 60.0
# instance 3
path = "$FIXTURES/lmp_simple_test_3.json.gz"
lmp = solve_conventional_testcase(path)
@test lmp["s1", "A", 1] == 50.0
@test lmp["s1", "B", 1] == 70.0
@test lmp["s1", "C", 1] == 100.0
# instance 4
path = "$FIXTURES/lmp_simple_test_4.json.gz"
lmp = solve_conventional_testcase(path)
@test lmp["s1", "A", 1] == 50.0
@test lmp["s1", "B", 1] == 70.0
@test lmp["s1", "C", 1] == 90.0
end

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test/model/formulations_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment
using JuMP
using Cbc
using JSON
import UnitCommitment:
ArrCon2000,
CarArr2006,
DamKucRajAta2016,
Formulation,
Gar1962,
KnuOstWat2018,
MorLatRam2013,
PanGua2016,
XavQiuWanThi2019,
WanHob2016
function _test(
formulation::Formulation;
instances = ["case14"],
dump::Bool = false,
)::Nothing
for instance_name in instances
instance = UnitCommitment.read("$(FIXTURES)/$(instance_name).json.gz")
model = UnitCommitment.build_model(
instance = instance,
formulation = formulation,
optimizer = Cbc.Optimizer,
variable_names = true,
)
set_silent(model)
UnitCommitment.optimize!(model)
solution = UnitCommitment.solution(model)
if dump
open("/tmp/ucjl.json", "w") do f
return write(f, JSON.json(solution, 2))
end
write_to_file(model, "/tmp/ucjl.lp")
end
@test UnitCommitment.validate(instance, solution)
end
return
end
@testset "formulations" begin
@testset "default" begin
_test(Formulation())
end
@testset "ArrCon2000" begin
_test(Formulation(ramping = ArrCon2000.Ramping()))
end
@testset "DamKucRajAta2016" begin
_test(Formulation(ramping = DamKucRajAta2016.Ramping()))
end
@testset "MorLatRam2013" begin
_test(
Formulation(
ramping = MorLatRam2013.Ramping(),
startup_costs = MorLatRam2013.StartupCosts(),
),
)
end
@testset "PanGua2016" begin
_test(Formulation(ramping = PanGua2016.Ramping()))
end
@testset "Gar1962" begin
_test(Formulation(pwl_costs = Gar1962.PwlCosts()))
end
@testset "CarArr2006" begin
_test(Formulation(pwl_costs = CarArr2006.PwlCosts()))
end
@testset "KnuOstWat2018" begin
_test(Formulation(pwl_costs = KnuOstWat2018.PwlCosts()))
end
@testset "WanHob2016" begin
_test(
Formulation(ramping = WanHob2016.Ramping()),
instances = ["case14-flex"],
)
end
end

46
test/runtests.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using Test
using UnitCommitment
push!(Base.LOAD_PATH, @__DIR__)
UnitCommitment._setup_logger(level = Base.CoreLogging.Error)
FIXTURES = "$(@__DIR__)/fixtures"
@testset "UnitCommitment" begin
include("usage.jl")
@testset "import" begin
include("import/egret_test.jl")
end
@testset "instance" begin
include("instance/read_test.jl")
include("instance/migrate_test.jl")
end
@testset "model" begin
include("model/formulations_test.jl")
end
@testset "solution" begin
@testset "XavQiuWanThi19" begin
include("solution/methods/XavQiuWanThi19/filter_test.jl")
include("solution/methods/XavQiuWanThi19/find_test.jl")
include("solution/methods/XavQiuWanThi19/sensitivity_test.jl")
end
end
@testset "transform" begin
include("transform/initcond_test.jl")
include("transform/slice_test.jl")
@testset "randomize" begin
include("transform/randomize/XavQiuAhm2021_test.jl")
end
end
@testset "validation" begin
include("validation/repair_test.jl")
end
@testset "lmp" begin
include("lmp/conventional_test.jl")
include("lmp/aelmp_test.jl")
end
end

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test/solution/methods/XavQiuWanThi19/filter_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Test, LinearAlgebra
import UnitCommitment: _Violation, _offer, _query
@testset "_ViolationFilter" begin
instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
sc = instance.scenarios[1]
filter = UnitCommitment._ViolationFilter(max_per_line = 1, max_total = 2)
_offer(
filter,
_Violation(
time = 1,
monitored_line = sc.lines[1],
outage_line = nothing,
amount = 100.0,
),
)
_offer(
filter,
_Violation(
time = 1,
monitored_line = sc.lines[1],
outage_line = sc.lines[1],
amount = 300.0,
),
)
_offer(
filter,
_Violation(
time = 1,
monitored_line = sc.lines[1],
outage_line = sc.lines[5],
amount = 500.0,
),
)
_offer(
filter,
_Violation(
time = 1,
monitored_line = sc.lines[1],
outage_line = sc.lines[4],
amount = 400.0,
),
)
_offer(
filter,
_Violation(
time = 1,
monitored_line = sc.lines[2],
outage_line = sc.lines[1],
amount = 200.0,
),
)
_offer(
filter,
_Violation(
time = 1,
monitored_line = sc.lines[2],
outage_line = sc.lines[8],
amount = 100.0,
),
)
actual = _query(filter)
expected = [
_Violation(
time = 1,
monitored_line = sc.lines[2],
outage_line = sc.lines[1],
amount = 200.0,
),
_Violation(
time = 1,
monitored_line = sc.lines[1],
outage_line = sc.lines[5],
amount = 500.0,
),
]
@test actual == expected
end

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test/solution/methods/XavQiuWanThi19/find_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Test, LinearAlgebra
import UnitCommitment: _Violation, _offer, _query
@testset "find_violations" begin
instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
sc = instance.scenarios[1]
for line in sc.lines, t in 1:instance.time
line.normal_flow_limit[t] = 1.0
line.emergency_flow_limit[t] = 1.0
end
isf = UnitCommitment._injection_shift_factors(
lines = sc.lines,
buses = sc.buses,
)
lodf = UnitCommitment._line_outage_factors(
lines = sc.lines,
buses = sc.buses,
isf = isf,
)
inj = [1000.0 for b in 1:13, t in 1:instance.time]
overflow = [0.0 for l in sc.lines, t in 1:instance.time]
violations = UnitCommitment._find_violations(
instance = instance,
sc = sc,
net_injections = inj,
overflow = overflow,
isf = isf,
lodf = lodf,
max_per_line = 1,
max_per_period = 5,
)
@test length(violations) == 20
end

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test/solution/methods/XavQiuWanThi19/sensitivity_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Test, LinearAlgebra
@testset "_susceptance_matrix" begin
instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
sc = instance.scenarios[1]
actual = UnitCommitment._susceptance_matrix(sc.lines)
@test size(actual) == (20, 20)
expected = Diagonal([
29.5,
7.83,
8.82,
9.9,
10.04,
10.2,
41.45,
8.35,
3.14,
6.93,
8.77,
6.82,
13.4,
9.91,
15.87,
20.65,
6.46,
9.09,
8.73,
5.02,
])
@test round.(actual, digits = 2) == expected
end
@testset "_reduced_incidence_matrix" begin
instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
sc = instance.scenarios[1]
actual = UnitCommitment._reduced_incidence_matrix(
lines = sc.lines,
buses = sc.buses,
)
@test size(actual) == (20, 13)
@test actual[1, 1] == -1.0
@test actual[3, 1] == 1.0
@test actual[4, 1] == 1.0
@test actual[5, 1] == 1.0
@test actual[3, 2] == -1.0
@test actual[6, 2] == 1.0
@test actual[4, 3] == -1.0
@test actual[6, 3] == -1.0
@test actual[7, 3] == 1.0
@test actual[8, 3] == 1.0
@test actual[9, 3] == 1.0
@test actual[2, 4] == -1.0
@test actual[5, 4] == -1.0
@test actual[7, 4] == -1.0
@test actual[10, 4] == 1.0
@test actual[10, 5] == -1.0
@test actual[11, 5] == 1.0
@test actual[12, 5] == 1.0
@test actual[13, 5] == 1.0
@test actual[8, 6] == -1.0
@test actual[14, 6] == 1.0
@test actual[15, 6] == 1.0
@test actual[14, 7] == -1.0
@test actual[9, 8] == -1.0
@test actual[15, 8] == -1.0
@test actual[16, 8] == 1.0
@test actual[17, 8] == 1.0
@test actual[16, 9] == -1.0
@test actual[18, 9] == 1.0
@test actual[11, 10] == -1.0
@test actual[18, 10] == -1.0
@test actual[12, 11] == -1.0
@test actual[19, 11] == 1.0
@test actual[13, 12] == -1.0
@test actual[19, 12] == -1.0
@test actual[20, 12] == 1.0
@test actual[17, 13] == -1.0
@test actual[20, 13] == -1.0
end
@testset "_injection_shift_factors" begin
instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
sc = instance.scenarios[1]
actual = UnitCommitment._injection_shift_factors(
lines = sc.lines,
buses = sc.buses,
)
@test size(actual) == (20, 13)
@test round.(actual, digits = 2) == [
-0.84 -0.75 -0.67 -0.61 -0.63 -0.66 -0.66 -0.65 -0.65 -0.64 -0.63 -0.63 -0.64
-0.16 -0.25 -0.33 -0.39 -0.37 -0.34 -0.34 -0.35 -0.35 -0.36 -0.37 -0.37 -0.36
0.03 -0.53 -0.15 -0.1 -0.12 -0.14 -0.14 -0.14 -0.13 -0.13 -0.12 -0.12 -0.13
0.06 -0.14 -0.32 -0.22 -0.25 -0.3 -0.3 -0.29 -0.28 -0.27 -0.25 -0.26 -0.27
0.08 -0.07 -0.2 -0.29 -0.26 -0.22 -0.22 -0.22 -0.23 -0.25 -0.26 -0.26 -0.24
0.03 0.47 -0.15 -0.1 -0.12 -0.14 -0.14 -0.14 -0.13 -0.13 -0.12 -0.12 -0.13
0.08 0.31 0.5 -0.3 -0.03 0.36 0.36 0.28 0.23 0.1 -0.0 0.02 0.17
0.0 0.01 0.02 -0.01 -0.22 -0.63 -0.63 -0.45 -0.41 -0.32 -0.24 -0.25 -0.36
0.0 0.01 0.01 -0.01 -0.12 -0.17 -0.17 -0.26 -0.24 -0.18 -0.14 -0.14 -0.21
-0.0 -0.02 -0.03 0.02 -0.66 -0.2 -0.2 -0.29 -0.36 -0.5 -0.63 -0.61 -0.43
-0.0 -0.01 -0.02 0.01 0.21 -0.12 -0.12 -0.17 -0.28 -0.53 0.18 0.15 -0.03
-0.0 -0.0 -0.0 0.0 0.03 -0.02 -0.02 -0.03 -0.02 0.01 -0.52 -0.17 -0.09
-0.0 -0.01 -0.01 0.01 0.11 -0.06 -0.06 -0.09 -0.05 0.02 -0.28 -0.59 -0.31
-0.0 -0.0 -0.0 -0.0 -0.0 -0.0 -1.0 -0.0 -0.0 -0.0 -0.0 -0.0 0.0
0.0 0.01 0.02 -0.01 -0.22 0.37 0.37 -0.45 -0.41 -0.32 -0.24 -0.25 -0.36
0.0 0.01 0.02 -0.01 -0.21 0.12 0.12 0.17 -0.72 -0.47 -0.18 -0.15 0.03
0.0 0.01 0.01 -0.01 -0.14 0.08 0.08 0.12 0.07 -0.03 -0.2 -0.24 -0.6
0.0 0.01 0.02 -0.01 -0.21 0.12 0.12 0.17 0.28 -0.47 -0.18 -0.15 0.03
-0.0 -0.0 -0.0 0.0 0.03 -0.02 -0.02 -0.03 -0.02 0.01 0.48 -0.17 -0.09
-0.0 -0.01 -0.01 0.01 0.14 -0.08 -0.08 -0.12 -0.07 0.03 0.2 0.24 -0.4
]
end
@testset "_line_outage_factors" begin
instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
sc = instance.scenarios[1]
isf_before = UnitCommitment._injection_shift_factors(
lines = sc.lines,
buses = sc.buses,
)
lodf = UnitCommitment._line_outage_factors(
lines = sc.lines,
buses = sc.buses,
isf = isf_before,
)
for contingency in sc.contingencies
for lc in contingency.lines
prev_susceptance = lc.susceptance
lc.susceptance = 0.0
isf_after = UnitCommitment._injection_shift_factors(
lines = sc.lines,
buses = sc.buses,
)
lc.susceptance = prev_susceptance
for lm in sc.lines
expected = isf_after[lm.offset, :]
actual =
isf_before[lm.offset, :] +
lodf[lm.offset, lc.offset] * isf_before[lc.offset, :]
@test norm(expected - actual) < 1e-6
end
end
end
end

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test/src/UnitCommitmentT.jl
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module UnitCommitmentT
using JuliaFormatter
using UnitCommitment
using Test
include("usage.jl")
include("import/egret_test.jl")
include("instance/read_test.jl")
include("instance/migrate_test.jl")
include("model/formulations_test.jl")
include("solution/methods/XavQiuWanThi19/filter_test.jl")
include("solution/methods/XavQiuWanThi19/find_test.jl")
include("solution/methods/XavQiuWanThi19/sensitivity_test.jl")
include("transform/initcond_test.jl")
include("transform/slice_test.jl")
include("transform/randomize/XavQiuAhm2021_test.jl")
include("validation/repair_test.jl")
include("lmp/conventional_test.jl")
include("lmp/aelmp_test.jl")
basedir = dirname(@__FILE__)
function fixture(path::String)::String
return "$basedir/../fixtures/$path"
end
function runtests()
println("Running tests...")
UnitCommitment._setup_logger(level = Base.CoreLogging.Error)
@testset "UnitCommitment" begin
usage_test()
import_egret_test()
instance_read_test()
instance_migrate_test()
model_formulations_test()
solution_methods_XavQiuWanThi19_filter_test()
solution_methods_XavQiuWanThi19_find_test()
solution_methods_XavQiuWanThi19_sensitivity_test()
transform_initcond_test()
transform_slice_test()
transform_randomize_XavQiuAhm2021_test()
validation_repair_test()
lmp_conventional_test()
lmp_aelmp_test()
end
return
end
function format()
JuliaFormatter.format(basedir, verbose = true)
JuliaFormatter.format("$basedir/../../src", verbose = true)
return
end
export runtests, format
end # module UnitCommitmentT

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test/src/import/egret_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment
function import_egret_test()
@testset "read_egret_solution" begin
solution =
UnitCommitment.read_egret_solution(fixture("egret_output.json.gz"))
for attr in
["Is on", "Thermal production (MW)", "Thermal production cost (\$)"]
@test attr in keys(solution)
@test "115_STEAM_1" in keys(solution[attr])
@test length(solution[attr]["115_STEAM_1"]) == 48
end
@test solution["Thermal production cost (\$)"]["315_CT_6"][15:20] ==
[0.0, 0.0, 884.44, 1470.71, 1470.71, 884.44]
@test solution["Startup cost (\$)"]["315_CT_6"][15:20] ==
[0.0, 0.0, 5665.23, 0.0, 0.0, 0.0]
@test length(keys(solution["Is on"])) == 154
end
end

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test/src/instance/migrate_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
function instance_migrate_test()
@testset "read v0.2" begin
instance = UnitCommitment.read(fixture("/ucjl-0.2.json.gz"))
@test length(instance.scenarios) == 1
sc = instance.scenarios[1]
@test length(sc.reserves_by_name["r1"].amount) == 4
@test sc.thermal_units_by_name["g2"].reserves[1].name == "r1"
end
@testset "read v0.3" begin
instance = UnitCommitment.read(fixture("/ucjl-0.3.json.gz"))
@test length(instance.scenarios) == 1
sc = instance.scenarios[1]
@test length(sc.thermal_units) == 6
@test length(sc.buses) == 14
@test length(sc.lines) == 20
end
end

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test/src/instance/read_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
function instance_read_test()
@testset "read_benchmark" begin
instance = UnitCommitment.read(fixture("case14.json.gz"))
@test repr(instance) == (
"UnitCommitmentInstance(1 scenarios, 6 thermal units, 0 profiled units, 14 buses, " *
"20 lines, 19 contingencies, 1 price sensitive loads, 4 time steps)"
)
@test length(instance.scenarios) == 1
sc = instance.scenarios[1]
@test length(sc.lines) == 20
@test length(sc.buses) == 14
@test length(sc.thermal_units) == 6
@test length(sc.contingencies) == 19
@test length(sc.price_sensitive_loads) == 1
@test instance.time == 4
@test sc.lines[5].name == "l5"
@test sc.lines[5].source.name == "b2"
@test sc.lines[5].target.name == "b5"
@test sc.lines[5].reactance ≈ 0.17388
@test sc.lines[5].susceptance ≈ 10.037550333
@test sc.lines[5].normal_flow_limit == [1e8 for t in 1:4]
@test sc.lines[5].emergency_flow_limit == [1e8 for t in 1:4]
@test sc.lines[5].flow_limit_penalty == [5e3 for t in 1:4]
@test sc.lines_by_name["l5"].name == "l5"
@test sc.lines[1].name == "l1"
@test sc.lines[1].source.name == "b1"
@test sc.lines[1].target.name == "b2"
@test sc.lines[1].reactance ≈ 0.059170
@test sc.lines[1].susceptance ≈ 29.496860773945
@test sc.lines[1].normal_flow_limit == [300.0 for t in 1:4]
@test sc.lines[1].emergency_flow_limit == [400.0 for t in 1:4]
@test sc.lines[1].flow_limit_penalty == [1e3 for t in 1:4]
@test sc.buses[9].name == "b9"
@test sc.buses[9].load == [35.36638, 33.25495, 31.67138, 31.14353]
@test sc.buses_by_name["b9"].name == "b9"
@test sc.reserves[1].name == "r1"
@test sc.reserves[1].type == "spinning"
@test sc.reserves[1].amount == [100.0, 100.0, 100.0, 100.0]
@test sc.reserves_by_name["r1"].name == "r1"
unit = sc.thermal_units[1]
@test unit.name == "g1"
@test unit.bus.name == "b1"
@test unit.ramp_up_limit == 1e6
@test unit.ramp_down_limit == 1e6
@test unit.startup_limit == 1e6
@test unit.shutdown_limit == 1e6
@test unit.must_run == [false for t in 1:4]
@test unit.min_power_cost == [1400.0 for t in 1:4]
@test unit.min_uptime == 1
@test unit.min_downtime == 1
for t in 1:1
@test unit.cost_segments[1].mw[t] == 10.0
@test unit.cost_segments[2].mw[t] == 20.0
@test unit.cost_segments[3].mw[t] == 5.0
@test unit.cost_segments[1].cost[t] ≈ 20.0
@test unit.cost_segments[2].cost[t] ≈ 30.0
@test unit.cost_segments[3].cost[t] ≈ 40.0
end
@test length(unit.startup_categories) == 3
@test unit.startup_categories[1].delay == 1
@test unit.startup_categories[2].delay == 2
@test unit.startup_categories[3].delay == 3
@test unit.startup_categories[1].cost == 1000.0
@test unit.startup_categories[2].cost == 1500.0
@test unit.startup_categories[3].cost == 2000.0
@test length(unit.reserves) == 0
@test sc.thermal_units_by_name["g1"].name == "g1"
unit = sc.thermal_units[2]
@test unit.name == "g2"
@test unit.must_run == [false for t in 1:4]
@test length(unit.reserves) == 1
unit = sc.thermal_units[3]
@test unit.name == "g3"
@test unit.bus.name == "b3"
@test unit.ramp_up_limit == 70.0
@test unit.ramp_down_limit == 70.0
@test unit.startup_limit == 70.0
@test unit.shutdown_limit == 70.0
@test unit.must_run == [true for t in 1:4]
@test unit.min_power_cost == [0.0 for t in 1:4]
@test unit.min_uptime == 1
@test unit.min_downtime == 1
for t in 1:4
@test unit.cost_segments[1].mw[t] ≈ 33
@test unit.cost_segments[2].mw[t] ≈ 33
@test unit.cost_segments[3].mw[t] ≈ 34
@test unit.cost_segments[1].cost[t] ≈ 33.75
@test unit.cost_segments[2].cost[t] ≈ 38.04
@test unit.cost_segments[3].cost[t] ≈ 44.77853
end
@test length(unit.reserves) == 1
@test unit.reserves[1].name == "r1"
@test sc.contingencies[1].lines == [sc.lines[1]]
@test sc.contingencies[1].thermal_units == []
@test sc.contingencies[1].name == "c1"
@test sc.contingencies_by_name["c1"].name == "c1"
load = sc.price_sensitive_loads[1]
@test load.name == "ps1"
@test load.bus.name == "b3"
@test load.revenue == [100.0 for t in 1:4]
@test load.demand == [50.0 for t in 1:4]
@test sc.price_sensitive_loads_by_name["ps1"].name == "ps1"
end
@testset "read_benchmark sub-hourly" begin
instance = UnitCommitment.read(fixture("case14-sub-hourly.json.gz"))
@test instance.time == 4
unit = instance.scenarios[1].thermal_units[1]
@test unit.name == "g1"
@test unit.min_uptime == 2
@test unit.min_downtime == 2
@test length(unit.startup_categories) == 3
@test unit.startup_categories[1].delay == 2
@test unit.startup_categories[2].delay == 4
@test unit.startup_categories[3].delay == 6
@test unit.initial_status == -200
end
@testset "read_benchmark profiled-units" begin
instance = UnitCommitment.read(fixture("case14-profiled.json.gz"))
sc = instance.scenarios[1]
@test length(sc.profiled_units) == 2
first_pu = sc.profiled_units[1]
@test first_pu.name == "g7"
@test first_pu.bus.name == "b4"
@test first_pu.cost == [100.0 for t in 1:4]
@test first_pu.min_power == [60.0 for t in 1:4]
@test first_pu.max_power == [100.0 for t in 1:4]
@test sc.profiled_units_by_name["g7"].name == "g7"
second_pu = sc.profiled_units[2]
@test second_pu.name == "g8"
@test second_pu.bus.name == "b5"
@test second_pu.cost == [50.0 for t in 1:4]
@test second_pu.min_power == [0.0 for t in 1:4]
@test second_pu.max_power == [120.0 for t in 1:4]
@test sc.profiled_units_by_name["g8"].name == "g8"
end
@testset "read_benchmark commitmemt-status" begin
instance = UnitCommitment.read(fixture("case14-fixed-status.json.gz"))
sc = instance.scenarios[1]
@test sc.thermal_units[1].commitment_status == [nothing for t in 1:4]
@test sc.thermal_units[2].commitment_status == [true for t in 1:4]
@test sc.thermal_units[4].commitment_status == [false for t in 1:4]
@test sc.thermal_units[6].commitment_status ==
[false, nothing, true, nothing]
end
end

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test/src/lmp/aelmp_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Cbc, HiGHS, JuMP
import UnitCommitment: AELMP
function lmp_aelmp_test()
@testset "aelmp" begin
path = fixture("aelmp_simple.json.gz")
# model has to be solved first
instance = UnitCommitment.read(path)
model = UnitCommitment.build_model(
instance = instance,
optimizer = Cbc.Optimizer,
variable_names = true,
)
JuMP.set_silent(model)
UnitCommitment.optimize!(model)
# policy 1: allow offlines; consider startups
aelmp_1 = UnitCommitment.compute_lmp(
model,
AELMP(),
optimizer = HiGHS.Optimizer,
)
@test aelmp_1["s1", "B1", 1] ≈ 231.7 atol = 0.1
# policy 2: do not allow offlines; but consider startups
aelmp_2 = UnitCommitment.compute_lmp(
model,
AELMP(
allow_offline_participation = false,
consider_startup_costs = true,
),
optimizer = HiGHS.Optimizer,
)
@test aelmp_2["s1", "B1", 1] ≈ 274.3 atol = 0.1
end
end

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test/src/lmp/conventional_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Cbc, HiGHS, JuMP
import UnitCommitment: ConventionalLMP
function solve_conventional_testcase(path::String)
instance = UnitCommitment.read(path)
model = UnitCommitment.build_model(
instance = instance,
optimizer = Cbc.Optimizer,
variable_names = true,
)
JuMP.set_silent(model)
UnitCommitment.optimize!(model)
lmp = UnitCommitment.compute_lmp(
model,
ConventionalLMP(),
optimizer = HiGHS.Optimizer,
)
return lmp
end
function lmp_conventional_test()
@testset "conventional" begin
# instance 1
path = fixture("lmp_simple_test_1.json.gz")
lmp = solve_conventional_testcase(path)
@test lmp["s1", "A", 1] == 50.0
@test lmp["s1", "B", 1] == 50.0
# instance 2
path = fixture("lmp_simple_test_2.json.gz")
lmp = solve_conventional_testcase(path)
@test lmp["s1", "A", 1] == 50.0
@test lmp["s1", "B", 1] == 60.0
# instance 3
path = fixture("lmp_simple_test_3.json.gz")
lmp = solve_conventional_testcase(path)
@test lmp["s1", "A", 1] == 50.0
@test lmp["s1", "B", 1] == 70.0
@test lmp["s1", "C", 1] == 100.0
# instance 4
path = fixture("lmp_simple_test_4.json.gz")
lmp = solve_conventional_testcase(path)
@test lmp["s1", "A", 1] == 50.0
@test lmp["s1", "B", 1] == 70.0
@test lmp["s1", "C", 1] == 90.0
end
end

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test/src/model/formulations_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment
using JuMP
using Cbc
using JSON
import UnitCommitment:
ArrCon2000,
CarArr2006,
DamKucRajAta2016,
Formulation,
Gar1962,
KnuOstWat2018,
MorLatRam2013,
PanGua2016,
XavQiuWanThi2019,
WanHob2016
function _test(
formulation::Formulation;
instances = ["case14"],
dump::Bool = false,
)::Nothing
for instance_name in instances
instance = UnitCommitment.read(fixture("$(instance_name).json.gz"))
model = UnitCommitment.build_model(
instance = instance,
formulation = formulation,
optimizer = Cbc.Optimizer,
variable_names = true,
)
set_silent(model)
UnitCommitment.optimize!(model)
solution = UnitCommitment.solution(model)
if dump
open("/tmp/ucjl.json", "w") do f
return write(f, JSON.json(solution, 2))
end
write_to_file(model, "/tmp/ucjl.lp")
end
@test UnitCommitment.validate(instance, solution)
end
return
end
function model_formulations_test()
@testset "formulations" begin
@testset "default" begin
_test(Formulation())
end
@testset "ArrCon2000" begin
_test(Formulation(ramping = ArrCon2000.Ramping()))
end
@testset "DamKucRajAta2016" begin
_test(Formulation(ramping = DamKucRajAta2016.Ramping()))
end
@testset "MorLatRam2013" begin
_test(
Formulation(
ramping = MorLatRam2013.Ramping(),
startup_costs = MorLatRam2013.StartupCosts(),
),
)
end
@testset "PanGua2016" begin
_test(Formulation(ramping = PanGua2016.Ramping()))
end
@testset "Gar1962" begin
_test(Formulation(pwl_costs = Gar1962.PwlCosts()))
end
@testset "CarArr2006" begin
_test(Formulation(pwl_costs = CarArr2006.PwlCosts()))
end
@testset "KnuOstWat2018" begin
_test(Formulation(pwl_costs = KnuOstWat2018.PwlCosts()))
end
@testset "WanHob2016" begin
_test(
Formulation(ramping = WanHob2016.Ramping()),
instances = ["case14-flex"],
)
end
end
end

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test/src/solution/methods/XavQiuWanThi19/filter_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Test, LinearAlgebra
import UnitCommitment: _Violation, _offer, _query
function solution_methods_XavQiuWanThi19_filter_test()
@testset "_ViolationFilter" begin
instance = UnitCommitment.read(fixture("case14.json.gz"))
sc = instance.scenarios[1]
filter =
UnitCommitment._ViolationFilter(max_per_line = 1, max_total = 2)
_offer(
filter,
_Violation(
time = 1,
monitored_line = sc.lines[1],
outage_line = nothing,
amount = 100.0,
),
)
_offer(
filter,
_Violation(
time = 1,
monitored_line = sc.lines[1],
outage_line = sc.lines[1],
amount = 300.0,
),
)
_offer(
filter,
_Violation(
time = 1,
monitored_line = sc.lines[1],
outage_line = sc.lines[5],
amount = 500.0,
),
)
_offer(
filter,
_Violation(
time = 1,
monitored_line = sc.lines[1],
outage_line = sc.lines[4],
amount = 400.0,
),
)
_offer(
filter,
_Violation(
time = 1,
monitored_line = sc.lines[2],
outage_line = sc.lines[1],
amount = 200.0,
),
)
_offer(
filter,
_Violation(
time = 1,
monitored_line = sc.lines[2],
outage_line = sc.lines[8],
amount = 100.0,
),
)
actual = _query(filter)
expected = [
_Violation(
time = 1,
monitored_line = sc.lines[2],
outage_line = sc.lines[1],
amount = 200.0,
),
_Violation(
time = 1,
monitored_line = sc.lines[1],
outage_line = sc.lines[5],
amount = 500.0,
),
]
@test actual == expected
end
end

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test/src/solution/methods/XavQiuWanThi19/find_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Test, LinearAlgebra
import UnitCommitment: _Violation, _offer, _query
function solution_methods_XavQiuWanThi19_find_test()
@testset "find_violations" begin
instance = UnitCommitment.read(fixture("case14.json.gz"))
sc = instance.scenarios[1]
for line in sc.lines, t in 1:instance.time
line.normal_flow_limit[t] = 1.0
line.emergency_flow_limit[t] = 1.0
end
isf = UnitCommitment._injection_shift_factors(
lines = sc.lines,
buses = sc.buses,
)
lodf = UnitCommitment._line_outage_factors(
lines = sc.lines,
buses = sc.buses,
isf = isf,
)
inj = [1000.0 for b in 1:13, t in 1:instance.time]
overflow = [0.0 for l in sc.lines, t in 1:instance.time]
violations = UnitCommitment._find_violations(
instance = instance,
sc = sc,
net_injections = inj,
overflow = overflow,
isf = isf,
lodf = lodf,
max_per_line = 1,
max_per_period = 5,
)
@test length(violations) == 20
end
end

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test/src/solution/methods/XavQiuWanThi19/sensitivity_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Test, LinearAlgebra
function solution_methods_XavQiuWanThi19_sensitivity_test()
@testset "_susceptance_matrix" begin
instance = UnitCommitment.read(fixture("/case14.json.gz"))
sc = instance.scenarios[1]
actual = UnitCommitment._susceptance_matrix(sc.lines)
@test size(actual) == (20, 20)
expected = Diagonal([
29.5,
7.83,
8.82,
9.9,
10.04,
10.2,
41.45,
8.35,
3.14,
6.93,
8.77,
6.82,
13.4,
9.91,
15.87,
20.65,
6.46,
9.09,
8.73,
5.02,
])
@test round.(actual, digits = 2) == expected
end
@testset "_reduced_incidence_matrix" begin
instance = UnitCommitment.read(fixture("/case14.json.gz"))
sc = instance.scenarios[1]
actual = UnitCommitment._reduced_incidence_matrix(
lines = sc.lines,
buses = sc.buses,
)
@test size(actual) == (20, 13)
@test actual[1, 1] == -1.0
@test actual[3, 1] == 1.0
@test actual[4, 1] == 1.0
@test actual[5, 1] == 1.0
@test actual[3, 2] == -1.0
@test actual[6, 2] == 1.0
@test actual[4, 3] == -1.0
@test actual[6, 3] == -1.0
@test actual[7, 3] == 1.0
@test actual[8, 3] == 1.0
@test actual[9, 3] == 1.0
@test actual[2, 4] == -1.0
@test actual[5, 4] == -1.0
@test actual[7, 4] == -1.0
@test actual[10, 4] == 1.0
@test actual[10, 5] == -1.0
@test actual[11, 5] == 1.0
@test actual[12, 5] == 1.0
@test actual[13, 5] == 1.0
@test actual[8, 6] == -1.0
@test actual[14, 6] == 1.0
@test actual[15, 6] == 1.0
@test actual[14, 7] == -1.0
@test actual[9, 8] == -1.0
@test actual[15, 8] == -1.0
@test actual[16, 8] == 1.0
@test actual[17, 8] == 1.0
@test actual[16, 9] == -1.0
@test actual[18, 9] == 1.0
@test actual[11, 10] == -1.0
@test actual[18, 10] == -1.0
@test actual[12, 11] == -1.0
@test actual[19, 11] == 1.0
@test actual[13, 12] == -1.0
@test actual[19, 12] == -1.0
@test actual[20, 12] == 1.0
@test actual[17, 13] == -1.0
@test actual[20, 13] == -1.0
end
@testset "_injection_shift_factors" begin
instance = UnitCommitment.read(fixture("/case14.json.gz"))
sc = instance.scenarios[1]
actual = UnitCommitment._injection_shift_factors(
lines = sc.lines,
buses = sc.buses,
)
@test size(actual) == (20, 13)
@test round.(actual, digits = 2) == [
-0.84 -0.75 -0.67 -0.61 -0.63 -0.66 -0.66 -0.65 -0.65 -0.64 -0.63 -0.63 -0.64
-0.16 -0.25 -0.33 -0.39 -0.37 -0.34 -0.34 -0.35 -0.35 -0.36 -0.37 -0.37 -0.36
0.03 -0.53 -0.15 -0.1 -0.12 -0.14 -0.14 -0.14 -0.13 -0.13 -0.12 -0.12 -0.13
0.06 -0.14 -0.32 -0.22 -0.25 -0.3 -0.3 -0.29 -0.28 -0.27 -0.25 -0.26 -0.27
0.08 -0.07 -0.2 -0.29 -0.26 -0.22 -0.22 -0.22 -0.23 -0.25 -0.26 -0.26 -0.24
0.03 0.47 -0.15 -0.1 -0.12 -0.14 -0.14 -0.14 -0.13 -0.13 -0.12 -0.12 -0.13
0.08 0.31 0.5 -0.3 -0.03 0.36 0.36 0.28 0.23 0.1 -0.0 0.02 0.17
0.0 0.01 0.02 -0.01 -0.22 -0.63 -0.63 -0.45 -0.41 -0.32 -0.24 -0.25 -0.36
0.0 0.01 0.01 -0.01 -0.12 -0.17 -0.17 -0.26 -0.24 -0.18 -0.14 -0.14 -0.21
-0.0 -0.02 -0.03 0.02 -0.66 -0.2 -0.2 -0.29 -0.36 -0.5 -0.63 -0.61 -0.43
-0.0 -0.01 -0.02 0.01 0.21 -0.12 -0.12 -0.17 -0.28 -0.53 0.18 0.15 -0.03
-0.0 -0.0 -0.0 0.0 0.03 -0.02 -0.02 -0.03 -0.02 0.01 -0.52 -0.17 -0.09
-0.0 -0.01 -0.01 0.01 0.11 -0.06 -0.06 -0.09 -0.05 0.02 -0.28 -0.59 -0.31
-0.0 -0.0 -0.0 -0.0 -0.0 -0.0 -1.0 -0.0 -0.0 -0.0 -0.0 -0.0 0.0
0.0 0.01 0.02 -0.01 -0.22 0.37 0.37 -0.45 -0.41 -0.32 -0.24 -0.25 -0.36
0.0 0.01 0.02 -0.01 -0.21 0.12 0.12 0.17 -0.72 -0.47 -0.18 -0.15 0.03
0.0 0.01 0.01 -0.01 -0.14 0.08 0.08 0.12 0.07 -0.03 -0.2 -0.24 -0.6
0.0 0.01 0.02 -0.01 -0.21 0.12 0.12 0.17 0.28 -0.47 -0.18 -0.15 0.03
-0.0 -0.0 -0.0 0.0 0.03 -0.02 -0.02 -0.03 -0.02 0.01 0.48 -0.17 -0.09
-0.0 -0.01 -0.01 0.01 0.14 -0.08 -0.08 -0.12 -0.07 0.03 0.2 0.24 -0.4
]
end
@testset "_line_outage_factors" begin
instance = UnitCommitment.read(fixture("/case14.json.gz"))
sc = instance.scenarios[1]
isf_before = UnitCommitment._injection_shift_factors(
lines = sc.lines,
buses = sc.buses,
)
lodf = UnitCommitment._line_outage_factors(
lines = sc.lines,
buses = sc.buses,
isf = isf_before,
)
for contingency in sc.contingencies
for lc in contingency.lines
prev_susceptance = lc.susceptance
lc.susceptance = 0.0
isf_after = UnitCommitment._injection_shift_factors(
lines = sc.lines,
buses = sc.buses,
)
lc.susceptance = prev_susceptance
for lm in sc.lines
expected = isf_after[lm.offset, :]
actual =
isf_before[lm.offset, :] +
lodf[lm.offset, lc.offset] * isf_before[lc.offset, :]
@test norm(expected - actual) < 1e-6
end
end
end
end
end

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test/src/transform/initcond_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Cbc, JuMP
function transform_initcond_test()
@testset "generate_initial_conditions!" begin
# Load instance
instance = UnitCommitment.read(fixture("case118-initcond.json.gz"))
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
sc = instance.scenarios[1]
# All units should have unknown initial conditions
for g in sc.thermal_units
@test g.initial_power === nothing
@test g.initial_status === nothing
end
# Generate initial conditions
UnitCommitment.generate_initial_conditions!(sc, optimizer)
# All units should now have known initial conditions
for g in sc.thermal_units
@test g.initial_power !== nothing
@test g.initial_status !== nothing
end
# TODO: Check that initial conditions are feasible
end
end

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test/src/transform/randomize/XavQiuAhm2021_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
import Random
import UnitCommitment: XavQiuAhm2021
using Distributions
using Random
using UnitCommitment, Cbc, JuMP
function get_scenario()
return UnitCommitment.read_benchmark(
"matpower/case118/2017-02-01",
).scenarios[1]
end
system_load(sc) = sum(b.load for b in sc.buses)
test_approx(x, y) = @test isapprox(x, y, atol = 1e-3)
function transform_randomize_XavQiuAhm2021_test()
@testset "XavQiuAhm2021" begin
@testset "cost and load share" begin
sc = get_scenario()
# Check original costs
unit = sc.thermal_units[10]
test_approx(unit.min_power_cost[1], 825.023)
test_approx(unit.cost_segments[1].cost[1], 36.659)
test_approx(unit.startup_categories[1].cost[1], 7570.42)
# Check original load share
bus = sc.buses[1]
prev_system_load = system_load(sc)
test_approx(bus.load[1] / prev_system_load[1], 0.012)
randomize!(
sc,
XavQiuAhm2021.Randomization(randomize_load_profile = false),
rng = MersenneTwister(42),
)
# Check randomized costs
test_approx(unit.min_power_cost[1], 831.977)
test_approx(unit.cost_segments[1].cost[1], 36.968)
test_approx(unit.startup_categories[1].cost[1], 7634.226)
# Check randomized load share
curr_system_load = system_load(sc)
test_approx(bus.load[1] / curr_system_load[1], 0.013)
# System load should not change
@test prev_system_load ≈ curr_system_load
end
@testset "load profile" begin
sc = get_scenario()
# Check original load profile
@test round.(system_load(sc), digits = 1)[1:8] ≈ [
3059.5,
2983.2,
2937.5,
2953.9,
3073.1,
3356.4,
4068.5,
4018.8,
]
randomize!(
sc,
XavQiuAhm2021.Randomization();
rng = MersenneTwister(42),
)
# Check randomized load profile
@test round.(system_load(sc), digits = 1)[1:8] ≈ [
4854.7,
4849.2,
4732.7,
4848.2,
4948.4,
5231.1,
5874.8,
5934.8,
]
end
@testset "profiled unit cost" begin
sc = UnitCommitment.read(
fixture("case14-profiled.json.gz"),
).scenarios[1]
# Check original costs
pu1 = sc.profiled_units[1]
pu2 = sc.profiled_units[2]
test_approx(pu1.cost[1], 100.0)
test_approx(pu2.cost[1], 50.0)
randomize!(
sc,
XavQiuAhm2021.Randomization(randomize_load_profile = false),
rng = MersenneTwister(42),
)
# Check randomized costs
test_approx(pu1.cost[1], 98.039)
test_approx(pu2.cost[1], 48.385)
end
end
end

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test/src/transform/slice_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
function transform_slice_test()
@testset "slice" begin
instance = UnitCommitment.read(fixture("case14.json.gz"))
modified = UnitCommitment.slice(instance, 1:2)
sc = modified.scenarios[1]
# Should update all time-dependent fields
@test modified.time == 2
@test length(sc.power_balance_penalty) == 2
@test length(sc.reserves_by_name["r1"].amount) == 2
for u in sc.thermal_units
@test length(u.max_power) == 2
@test length(u.min_power) == 2
@test length(u.must_run) == 2
@test length(u.min_power_cost) == 2
for s in u.cost_segments
@test length(s.mw) == 2
@test length(s.cost) == 2
end
end
for b in sc.buses
@test length(b.load) == 2
end
for l in sc.lines
@test length(l.normal_flow_limit) == 2
@test length(l.emergency_flow_limit) == 2
@test length(l.flow_limit_penalty) == 2
end
for ps in sc.price_sensitive_loads
@test length(ps.demand) == 2
@test length(ps.revenue) == 2
end
# Should be able to build model without errors
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
model = UnitCommitment.build_model(
instance = modified,
optimizer = optimizer,
variable_names = true,
)
end
@testset "slice profiled units" begin
instance = UnitCommitment.read(fixture("case14-profiled.json.gz"))
modified = UnitCommitment.slice(instance, 1:2)
sc = modified.scenarios[1]
# Should update all time-dependent fields
for pu in sc.profiled_units
@test length(pu.max_power) == 2
@test length(pu.min_power) == 2
end
# Should be able to build model without errors
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
model = UnitCommitment.build_model(
instance = modified,
optimizer = optimizer,
variable_names = true,
)
end
end

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test/src/usage.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON
function _set_flow_limits!(instance)
for sc in instance.scenarios
sc.power_balance_penalty = [100_000 for _ in 1:instance.time]
for line in sc.lines, t in 1:4
line.normal_flow_limit[t] = 10.0
end
end
end
function usage_test()
@testset "usage" begin
@testset "deterministic" begin
instance = UnitCommitment.read(fixture("case14.json.gz"))
_set_flow_limits!(instance)
optimizer =
optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
model = UnitCommitment.build_model(
instance = instance,
optimizer = optimizer,
variable_names = true,
)
@test name(model[:is_on]["g1", 1]) == "is_on[g1,1]"
# Optimize and retrieve solution
UnitCommitment.optimize!(model)
solution = UnitCommitment.solution(model)
# Write solution to a file
filename = tempname()
UnitCommitment.write(filename, solution)
loaded = JSON.parsefile(filename)
@test length(loaded["Is on"]) == 6
# Verify solution
@test UnitCommitment.validate(instance, solution)
# Reoptimize with fixed solution
UnitCommitment.fix!(model, solution)
UnitCommitment.optimize!(model)
@test UnitCommitment.validate(instance, solution)
end
@testset "stochastic" begin
instance = UnitCommitment.read([
fixture("case14.json.gz"),
fixture("case14.json.gz"),
])
_set_flow_limits!(instance)
@test length(instance.scenarios) == 2
optimizer =
optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
model = UnitCommitment.build_model(
instance = instance,
optimizer = optimizer,
)
UnitCommitment.optimize!(model)
solution = UnitCommitment.solution(model)
end
end
end

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test/src/validation/repair_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, JSON, GZip, DataStructures
function parse_case14()
return JSON.parse(
GZip.gzopen(fixture("case14.json.gz")),
dicttype = () -> DefaultOrderedDict(nothing),
)
end
function validation_repair_test()
@testset "repair!" begin
@testset "Cost curve should be convex" begin
json = parse_case14()
json["Generators"]["g1"]["Production cost curve (MW)"] =
[100, 150, 200]
json["Generators"]["g1"]["Production cost curve (\$)"] =
[10, 25, 30]
sc = UnitCommitment._from_json(json, repair = false)
@test UnitCommitment.repair!(sc) == 4
end
@testset "Startup limit must be greater than Pmin" begin
json = parse_case14()
json["Generators"]["g1"]["Production cost curve (MW)"] = [100, 150]
json["Generators"]["g1"]["Production cost curve (\$)"] = [100, 150]
json["Generators"]["g1"]["Startup limit (MW)"] = 80
sc = UnitCommitment._from_json(json, repair = false)
@test UnitCommitment.repair!(sc) == 1
end
@testset "Startup costs and delays must be increasing" begin
json = parse_case14()
json["Generators"]["g1"]["Startup costs (\$)"] = [300, 200, 100]
json["Generators"]["g1"]["Startup delays (h)"] = [8, 4, 2]
sc = UnitCommitment._from_json(json, repair = false)
@test UnitCommitment.repair!(sc) == 4
end
end
end

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test/transform/initcond_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Cbc, JuMP
@testset "generate_initial_conditions!" begin
# Load instance
instance = UnitCommitment.read("$FIXTURES/case118-initcond.json.gz")
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
sc = instance.scenarios[1]
# All units should have unknown initial conditions
for g in sc.thermal_units
@test g.initial_power === nothing
@test g.initial_status === nothing
end
# Generate initial conditions
UnitCommitment.generate_initial_conditions!(sc, optimizer)
# All units should now have known initial conditions
for g in sc.thermal_units
@test g.initial_power !== nothing
@test g.initial_status !== nothing
end
# TODO: Check that initial conditions are feasible
end

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test/transform/randomize/XavQiuAhm2021_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
import Random
import UnitCommitment: XavQiuAhm2021
using Distributions
using Random
using UnitCommitment, Cbc, JuMP
function get_scenario()
return UnitCommitment.read_benchmark(
"matpower/case118/2017-02-01",
).scenarios[1]
end
system_load(sc) = sum(b.load for b in sc.buses)
test_approx(x, y) = @test isapprox(x, y, atol = 1e-3)
@testset "XavQiuAhm2021" begin
@testset "cost and load share" begin
sc = get_scenario()
# Check original costs
unit = sc.thermal_units[10]
test_approx(unit.min_power_cost[1], 825.023)
test_approx(unit.cost_segments[1].cost[1], 36.659)
test_approx(unit.startup_categories[1].cost[1], 7570.42)
# Check original load share
bus = sc.buses[1]
prev_system_load = system_load(sc)
test_approx(bus.load[1] / prev_system_load[1], 0.012)
randomize!(
sc,
XavQiuAhm2021.Randomization(randomize_load_profile = false),
rng = MersenneTwister(42),
)
# Check randomized costs
test_approx(unit.min_power_cost[1], 831.977)
test_approx(unit.cost_segments[1].cost[1], 36.968)
test_approx(unit.startup_categories[1].cost[1], 7634.226)
# Check randomized load share
curr_system_load = system_load(sc)
test_approx(bus.load[1] / curr_system_load[1], 0.013)
# System load should not change
@test prev_system_load ≈ curr_system_load
end
@testset "load profile" begin
sc = get_scenario()
# Check original load profile
@test round.(system_load(sc), digits = 1)[1:8] ≈
[3059.5, 2983.2, 2937.5, 2953.9, 3073.1, 3356.4, 4068.5, 4018.8]
randomize!(sc, XavQiuAhm2021.Randomization(); rng = MersenneTwister(42))
# Check randomized load profile
@test round.(system_load(sc), digits = 1)[1:8] ≈
[4854.7, 4849.2, 4732.7, 4848.2, 4948.4, 5231.1, 5874.8, 5934.8]
end
@testset "profiled unit cost" begin
sc =
UnitCommitment.read("$FIXTURES/case14-profiled.json.gz").scenarios[1]
# Check original costs
pu1 = sc.profiled_units[1]
pu2 = sc.profiled_units[2]
test_approx(pu1.cost[1], 100.0)
test_approx(pu2.cost[1], 50.0)
randomize!(
sc,
XavQiuAhm2021.Randomization(randomize_load_profile = false),
rng = MersenneTwister(42),
)
# Check randomized costs
test_approx(pu1.cost[1], 98.039)
test_approx(pu2.cost[1], 48.385)
end
end

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test/transform/slice_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
@testset "slice" begin
instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
modified = UnitCommitment.slice(instance, 1:2)
sc = modified.scenarios[1]
# Should update all time-dependent fields
@test modified.time == 2
@test length(sc.power_balance_penalty) == 2
@test length(sc.reserves_by_name["r1"].amount) == 2
for u in sc.thermal_units
@test length(u.max_power) == 2
@test length(u.min_power) == 2
@test length(u.must_run) == 2
@test length(u.min_power_cost) == 2
for s in u.cost_segments
@test length(s.mw) == 2
@test length(s.cost) == 2
end
end
for b in sc.buses
@test length(b.load) == 2
end
for l in sc.lines
@test length(l.normal_flow_limit) == 2
@test length(l.emergency_flow_limit) == 2
@test length(l.flow_limit_penalty) == 2
end
for ps in sc.price_sensitive_loads
@test length(ps.demand) == 2
@test length(ps.revenue) == 2
end
# Should be able to build model without errors
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
model = UnitCommitment.build_model(
instance = modified,
optimizer = optimizer,
variable_names = true,
)
end
@testset "slice profiled units" begin
instance = UnitCommitment.read("$FIXTURES/case14-profiled.json.gz")
modified = UnitCommitment.slice(instance, 1:2)
sc = modified.scenarios[1]
# Should update all time-dependent fields
for pu in sc.profiled_units
@test length(pu.max_power) == 2
@test length(pu.min_power) == 2
end
# Should be able to build model without errors
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
model = UnitCommitment.build_model(
instance = modified,
optimizer = optimizer,
variable_names = true,
)
end

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test/usage.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON
function _set_flow_limits!(instance)
for sc in instance.scenarios
sc.power_balance_penalty = [100_000 for _ in 1:instance.time]
for line in sc.lines, t in 1:4
line.normal_flow_limit[t] = 10.0
end
end
end
@testset "usage" begin
@testset "deterministic" begin
instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
_set_flow_limits!(instance)
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
model = UnitCommitment.build_model(
instance = instance,
optimizer = optimizer,
variable_names = true,
)
@test name(model[:is_on]["g1", 1]) == "is_on[g1,1]"
# Optimize and retrieve solution
UnitCommitment.optimize!(model)
solution = UnitCommitment.solution(model)
# Write solution to a file
filename = tempname()
UnitCommitment.write(filename, solution)
loaded = JSON.parsefile(filename)
@test length(loaded["Is on"]) == 6
# Verify solution
@test UnitCommitment.validate(instance, solution)
# Reoptimize with fixed solution
UnitCommitment.fix!(model, solution)
UnitCommitment.optimize!(model)
@test UnitCommitment.validate(instance, solution)
end
@testset "stochastic" begin
instance = UnitCommitment.read([
"$FIXTURES/case14.json.gz",
"$FIXTURES/case14.json.gz",
])
_set_flow_limits!(instance)
@test length(instance.scenarios) == 2
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
model = UnitCommitment.build_model(
instance = instance,
optimizer = optimizer,
)
UnitCommitment.optimize!(model)
solution = UnitCommitment.solution(model)
end
end

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test/validation/repair_test.jl
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# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, JSON, GZip, DataStructures
function parse_case14()
return JSON.parse(
GZip.gzopen("$FIXTURES/case14.json.gz"),
dicttype = () -> DefaultOrderedDict(nothing),
)
end
@testset "repair!" begin
@testset "Cost curve should be convex" begin
json = parse_case14()
json["Generators"]["g1"]["Production cost curve (MW)"] = [100, 150, 200]
json["Generators"]["g1"]["Production cost curve (\$)"] = [10, 25, 30]
sc = UnitCommitment._from_json(json, repair = false)
@test UnitCommitment.repair!(sc) == 4
end
@testset "Startup limit must be greater than Pmin" begin
json = parse_case14()
json["Generators"]["g1"]["Production cost curve (MW)"] = [100, 150]
json["Generators"]["g1"]["Production cost curve (\$)"] = [100, 150]
json["Generators"]["g1"]["Startup limit (MW)"] = 80
sc = UnitCommitment._from_json(json, repair = false)
@test UnitCommitment.repair!(sc) == 1
end
@testset "Startup costs and delays must be increasing" begin
json = parse_case14()
json["Generators"]["g1"]["Startup costs (\$)"] = [300, 200, 100]
json["Generators"]["g1"]["Startup delays (h)"] = [8, 4, 2]
sc = UnitCommitment._from_json(json, repair = false)
@test UnitCommitment.repair!(sc) == 4
end
end
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