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https://github.com/ANL-CEEESA/UnitCommitment.jl.git
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bugfix/for
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feature/ju
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b2eaa0e48b |
4
.github/workflows/test.yml
vendored
4
.github/workflows/test.yml
vendored
@@ -9,8 +9,8 @@ jobs:
|
||||
runs-on: ${{ matrix.os }}
|
||||
strategy:
|
||||
matrix:
|
||||
julia-version: ['1.3', '1.4', '1.5', '1.6']
|
||||
julia-arch: [x64, x86]
|
||||
julia-version: ['1.4', '1.5', '1.6']
|
||||
julia-arch: [x64]
|
||||
os: [ubuntu-latest, windows-latest, macOS-latest]
|
||||
exclude:
|
||||
- os: macOS-latest
|
||||
|
||||
1
.gitignore
vendored
1
.gitignore
vendored
@@ -18,3 +18,4 @@ TODO.md
|
||||
docs/_build
|
||||
.vscode
|
||||
Manifest.toml
|
||||
*/Manifest.toml
|
||||
|
||||
@@ -11,6 +11,11 @@ All notable changes to this project will be documented in this file.
|
||||
[semver]: https://semver.org/spec/v2.0.0.html
|
||||
[pkjjl]: https://pkgdocs.julialang.org/v1/compatibility/#compat-pre-1.0
|
||||
|
||||
## [0.2.2] - 2021-07-21
|
||||
### Fixed
|
||||
- Fix small bug in validation scripts related to startup costs
|
||||
- Fix duplicated startup constraints (@mtanneau, #12)
|
||||
|
||||
## [0.2.1] - 2021-06-02
|
||||
### Added
|
||||
- Add multiple ramping formulations (ArrCon2000, MorLatRam2013, DamKucRajAta2016, PanGua2016)
|
||||
|
||||
23
Makefile
23
Makefile
@@ -2,31 +2,22 @@
|
||||
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
|
||||
# Released under the modified BSD license. See COPYING.md for more details.
|
||||
|
||||
JULIA := julia --color=yes --project=@.
|
||||
VERSION := 0.2
|
||||
|
||||
build/sysimage.so: src/utils/sysimage.jl Project.toml Manifest.toml
|
||||
mkdir -p build
|
||||
mkdir -p benchmark/results/test
|
||||
cd benchmark; $(JULIA) --trace-compile=../build/precompile.jl benchmark.jl test/case14
|
||||
$(JULIA) src/utils/sysimage.jl
|
||||
|
||||
clean:
|
||||
rm -rf build/*
|
||||
rm -rfv build
|
||||
|
||||
docs:
|
||||
cd docs; make clean; make dirhtml
|
||||
rsync -avP --delete-after docs/_build/dirhtml/ ../docs/$(VERSION)/
|
||||
|
||||
test: build/sysimage.so
|
||||
@echo Running tests...
|
||||
$(JULIA) --sysimage build/sysimage.so -e 'using Pkg; Pkg.test("UnitCommitment")' | tee build/test.log
|
||||
|
||||
|
||||
format:
|
||||
julia -e 'using JuliaFormatter; format(["src", "test", "benchmark"], verbose=true);'
|
||||
cd deps/formatter; ../../juliaw format.jl
|
||||
|
||||
install-deps:
|
||||
julia -e 'using Pkg; Pkg.add(PackageSpec(name="JuliaFormatter", version="0.14.4"))'
|
||||
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
|
||||
|
||||
12
Project.toml
12
Project.toml
@@ -2,10 +2,11 @@ name = "UnitCommitment"
|
||||
uuid = "64606440-39ea-11e9-0f29-3303a1d3d877"
|
||||
authors = ["Santos Xavier, Alinson <axavier@anl.gov>"]
|
||||
repo = "https://github.com/ANL-CEEESA/UnitCommitment.jl"
|
||||
version = "0.2.1"
|
||||
version = "0.2.2"
|
||||
|
||||
[deps]
|
||||
DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
|
||||
Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
|
||||
Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
|
||||
GZip = "92fee26a-97fe-5a0c-ad85-20a5f3185b63"
|
||||
JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
|
||||
@@ -15,10 +16,10 @@ 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"
|
||||
|
||||
[compat]
|
||||
Cbc = "0.7"
|
||||
DataStructures = "0.18"
|
||||
Distributions = "0.25"
|
||||
GZip = "0.5"
|
||||
@@ -27,10 +28,3 @@ JuMP = "0.21"
|
||||
MathOptInterface = "0.9"
|
||||
PackageCompiler = "1"
|
||||
julia = "1"
|
||||
|
||||
[extras]
|
||||
Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
|
||||
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
|
||||
|
||||
[targets]
|
||||
test = ["Cbc", "Test"]
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
[deps]
|
||||
DocOpt = "968ba79b-81e4-546f-ab3a-2eecfa62a9db"
|
||||
Gurobi = "2e9cd046-0924-5485-92f1-d5272153d98b"
|
||||
JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
|
||||
JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
|
||||
|
||||
@@ -1,158 +0,0 @@
|
||||
# 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 Distributed
|
||||
using Pkg
|
||||
Pkg.activate(".")
|
||||
|
||||
@everywhere using Pkg
|
||||
@everywhere Pkg.activate(".")
|
||||
|
||||
@everywhere using UnitCommitment
|
||||
@everywhere using JuMP
|
||||
@everywhere using Gurobi
|
||||
@everywhere using JSON
|
||||
@everywhere using Logging
|
||||
@everywhere using Printf
|
||||
@everywhere using LinearAlgebra
|
||||
@everywhere using Random
|
||||
|
||||
@everywhere import UnitCommitment:
|
||||
ArrCon2000,
|
||||
CarArr2006,
|
||||
DamKucRajAta2016,
|
||||
Formulation,
|
||||
Gar1962,
|
||||
KnuOstWat2018,
|
||||
MorLatRam2013,
|
||||
PanGua2016,
|
||||
XavQiuWanThi2019
|
||||
|
||||
@everywhere UnitCommitment._setup_logger()
|
||||
|
||||
function main()
|
||||
cases = [
|
||||
"pglib-uc/ca/2014-09-01_reserves_0",
|
||||
"pglib-uc/ca/2014-09-01_reserves_1",
|
||||
"pglib-uc/ca/2015-03-01_reserves_0",
|
||||
"pglib-uc/ca/2015-06-01_reserves_0",
|
||||
"pglib-uc/ca/Scenario400_reserves_1",
|
||||
"pglib-uc/ferc/2015-01-01_lw",
|
||||
"pglib-uc/ferc/2015-05-01_lw",
|
||||
"pglib-uc/ferc/2015-07-01_hw",
|
||||
"pglib-uc/ferc/2015-10-01_lw",
|
||||
"pglib-uc/ferc/2015-12-01_lw",
|
||||
"pglib-uc/rts_gmlc/2020-04-03",
|
||||
"pglib-uc/rts_gmlc/2020-09-20",
|
||||
"pglib-uc/rts_gmlc/2020-10-27",
|
||||
"pglib-uc/rts_gmlc/2020-11-25",
|
||||
"pglib-uc/rts_gmlc/2020-12-23",
|
||||
"or-lib/20_0_1_w",
|
||||
"or-lib/20_0_5_w",
|
||||
"or-lib/50_0_2_w",
|
||||
"or-lib/75_0_2_w",
|
||||
"or-lib/100_0_1_w",
|
||||
"or-lib/100_0_4_w",
|
||||
"or-lib/100_0_5_w",
|
||||
"or-lib/200_0_3_w",
|
||||
"or-lib/200_0_7_w",
|
||||
"or-lib/200_0_9_w",
|
||||
"tejada19/UC_24h_290g",
|
||||
"tejada19/UC_24h_623g",
|
||||
"tejada19/UC_24h_959g",
|
||||
"tejada19/UC_24h_1577g",
|
||||
"tejada19/UC_24h_1888g",
|
||||
"tejada19/UC_168h_72g",
|
||||
"tejada19/UC_168h_86g",
|
||||
"tejada19/UC_168h_130g",
|
||||
"tejada19/UC_168h_131g",
|
||||
"tejada19/UC_168h_199g",
|
||||
]
|
||||
formulations = Dict(
|
||||
"Default" => Formulation(),
|
||||
"ArrCon2000" => Formulation(ramping = ArrCon2000.Ramping()),
|
||||
"CarArr2006" => Formulation(pwl_costs = CarArr2006.PwlCosts()),
|
||||
"DamKucRajAta2016" =>
|
||||
Formulation(ramping = DamKucRajAta2016.Ramping()),
|
||||
"Gar1962" => Formulation(pwl_costs = Gar1962.PwlCosts()),
|
||||
"KnuOstWat2018" =>
|
||||
Formulation(pwl_costs = KnuOstWat2018.PwlCosts()),
|
||||
"MorLatRam2013" => Formulation(ramping = MorLatRam2013.Ramping()),
|
||||
"PanGua2016" => Formulation(ramping = PanGua2016.Ramping()),
|
||||
)
|
||||
trials = [i for i in 1:5]
|
||||
combinations = [
|
||||
(c, f.first, f.second, t) for c in cases for f in formulations for
|
||||
t in trials
|
||||
]
|
||||
shuffle!(combinations)
|
||||
@sync @distributed for c in combinations
|
||||
_run_combination(c...)
|
||||
end
|
||||
end
|
||||
|
||||
@everywhere function _run_combination(
|
||||
case,
|
||||
formulation_name,
|
||||
formulation,
|
||||
trial,
|
||||
)
|
||||
name = "$formulation_name/$case"
|
||||
dirname = "results/$name"
|
||||
mkpath(dirname)
|
||||
if isfile("$dirname/$trial.json")
|
||||
@info @sprintf("%-4s %-16s %s", "skip", formulation_name, case)
|
||||
return
|
||||
end
|
||||
@info @sprintf("%-4s %-16s %s", "run", formulation_name, case)
|
||||
open("$dirname/$trial.log", "w") do file
|
||||
redirect_stdout(file) do
|
||||
redirect_stderr(file) do
|
||||
return _run_sample(case, formulation, "$dirname/$trial")
|
||||
end
|
||||
end
|
||||
end
|
||||
@info @sprintf("%-4s %-16s %s", "done", formulation_name, case)
|
||||
end
|
||||
|
||||
@everywhere function _run_sample(case, formulation, prefix)
|
||||
total_time = @elapsed begin
|
||||
@info "Reading: $case"
|
||||
time_read = @elapsed begin
|
||||
instance = UnitCommitment.read_benchmark(case)
|
||||
end
|
||||
@info @sprintf("Read problem in %.2f seconds", time_read)
|
||||
BLAS.set_num_threads(4)
|
||||
model = UnitCommitment.build_model(
|
||||
instance = instance,
|
||||
formulation = formulation,
|
||||
optimizer = optimizer_with_attributes(
|
||||
Gurobi.Optimizer,
|
||||
"Threads" => 4,
|
||||
"Seed" => rand(1:1000),
|
||||
),
|
||||
variable_names = true,
|
||||
)
|
||||
@info "Optimizing..."
|
||||
BLAS.set_num_threads(1)
|
||||
UnitCommitment.optimize!(
|
||||
model,
|
||||
XavQiuWanThi2019.Method(time_limit = 3600.0, gap_limit = 1e-4),
|
||||
)
|
||||
end
|
||||
@info @sprintf("Total time was %.2f seconds", total_time)
|
||||
@info "Writing solution: $prefix.json"
|
||||
solution = UnitCommitment.solution(model)
|
||||
UnitCommitment.write("$prefix.json", solution)
|
||||
@info "Verifying solution..."
|
||||
return UnitCommitment.validate(instance, solution)
|
||||
# @info "Exporting model..."
|
||||
# return JuMP.write_to_file(model, model_filename)
|
||||
end
|
||||
|
||||
if length(ARGS) > 0
|
||||
_run_sample(ARGS[1], UnitCommitment.Formulation(), "tmp")
|
||||
else
|
||||
main()
|
||||
end
|
||||
207
benchmark/run.jl
Normal file
207
benchmark/run.jl
Normal file
@@ -0,0 +1,207 @@
|
||||
# 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.
|
||||
|
||||
doc = """UnitCommitment.jl Benchmark Runner
|
||||
|
||||
Usage:
|
||||
run.jl [-s ARG]... [-m ARG]... [-c ARG]... [-f ARG]... [options]
|
||||
|
||||
Examples:
|
||||
|
||||
1. Benchmark all solvers, methods and formulations:
|
||||
|
||||
julia run.jl
|
||||
|
||||
2. Benchmark formulations "default" and "ArrCon200" using Gurobi:
|
||||
|
||||
julia run.jl -s gurobi -f default -f ArrCon2000
|
||||
|
||||
3. Benchmark a few test cases, using all solvers, methods and formulations:
|
||||
|
||||
julia run.jl -c or-lib/20_0_1_w -c matpower/case1888rte/2017-02-01
|
||||
|
||||
4. Solve 4 test cases in parallel, with 2 threads available per worker:
|
||||
|
||||
JULIA_NUM_THREADS=2 julia --procs 4 run.jl
|
||||
|
||||
Options:
|
||||
-h --help Show this screen.
|
||||
-s --solver=ARG Mixed-integer linear solver (e.g. gurobi)
|
||||
-c --case=ARG Unit commitment test case (e.g. or-lib/20_0_1_w)
|
||||
-m --method=ARG Solution method (e.g. default)
|
||||
-f --formulation=ARG Formulation (e.g. ArrCon2000)
|
||||
--time-limit=ARG Time limit in seconds [default: 3600]
|
||||
--gap=ARG Relative MIP gap tolerance [default: 0.001]
|
||||
--trials=ARG Number of trials [default: 5]
|
||||
"""
|
||||
|
||||
using Distributed
|
||||
using Pkg
|
||||
Pkg.activate(".")
|
||||
@everywhere using Pkg
|
||||
@everywhere Pkg.activate(".")
|
||||
|
||||
using DocOpt
|
||||
args = docopt(doc)
|
||||
|
||||
@everywhere using UnitCommitment
|
||||
@everywhere UnitCommitment._setup_logger()
|
||||
|
||||
using UnitCommitment
|
||||
using Gurobi
|
||||
using Logging
|
||||
using JuMP
|
||||
|
||||
import UnitCommitment:
|
||||
ArrCon2000,
|
||||
CarArr2006,
|
||||
DamKucRajAta2016,
|
||||
Formulation,
|
||||
Gar1962,
|
||||
KnuOstWat2018,
|
||||
MorLatRam2013,
|
||||
PanGua2016,
|
||||
XavQiuWanThi2019
|
||||
|
||||
# Benchmark test cases
|
||||
# -----------------------------------------------------------------------------
|
||||
cases = [
|
||||
"pglib-uc/ca/2014-09-01_reserves_0",
|
||||
"pglib-uc/ca/2014-09-01_reserves_1",
|
||||
"pglib-uc/ca/2015-03-01_reserves_0",
|
||||
"pglib-uc/ca/2015-06-01_reserves_0",
|
||||
"pglib-uc/ca/Scenario400_reserves_1",
|
||||
"pglib-uc/ferc/2015-01-01_lw",
|
||||
"pglib-uc/ferc/2015-05-01_lw",
|
||||
"pglib-uc/ferc/2015-07-01_hw",
|
||||
"pglib-uc/ferc/2015-10-01_lw",
|
||||
"pglib-uc/ferc/2015-12-01_lw",
|
||||
"pglib-uc/rts_gmlc/2020-04-03",
|
||||
"pglib-uc/rts_gmlc/2020-09-20",
|
||||
"pglib-uc/rts_gmlc/2020-10-27",
|
||||
"pglib-uc/rts_gmlc/2020-11-25",
|
||||
"pglib-uc/rts_gmlc/2020-12-23",
|
||||
"or-lib/20_0_1_w",
|
||||
"or-lib/20_0_5_w",
|
||||
"or-lib/50_0_2_w",
|
||||
"or-lib/75_0_2_w",
|
||||
"or-lib/100_0_1_w",
|
||||
"or-lib/100_0_4_w",
|
||||
"or-lib/100_0_5_w",
|
||||
"or-lib/200_0_3_w",
|
||||
"or-lib/200_0_7_w",
|
||||
"or-lib/200_0_9_w",
|
||||
"tejada19/UC_24h_290g",
|
||||
"tejada19/UC_24h_623g",
|
||||
"tejada19/UC_24h_959g",
|
||||
"tejada19/UC_24h_1577g",
|
||||
"tejada19/UC_24h_1888g",
|
||||
"tejada19/UC_168h_72g",
|
||||
"tejada19/UC_168h_86g",
|
||||
"tejada19/UC_168h_130g",
|
||||
"tejada19/UC_168h_131g",
|
||||
"tejada19/UC_168h_199g",
|
||||
"matpower/case1888rte/2017-02-01",
|
||||
"matpower/case1951rte/2017-02-01",
|
||||
"matpower/case2848rte/2017-02-01",
|
||||
"matpower/case3012wp/2017-02-01",
|
||||
"matpower/case3375wp/2017-02-01",
|
||||
"matpower/case6468rte/2017-02-01",
|
||||
"matpower/case6515rte/2017-02-01",
|
||||
]
|
||||
|
||||
# Formulations
|
||||
# -----------------------------------------------------------------------------
|
||||
formulations = Dict(
|
||||
"default" => Formulation(),
|
||||
"ArrCon2000" => Formulation(ramping = ArrCon2000.Ramping()),
|
||||
"CarArr2006" => Formulation(pwl_costs = CarArr2006.PwlCosts()),
|
||||
"DamKucRajAta2016" => Formulation(ramping = DamKucRajAta2016.Ramping()),
|
||||
"Gar1962" => Formulation(pwl_costs = Gar1962.PwlCosts()),
|
||||
"KnuOstWat2018" => Formulation(pwl_costs = KnuOstWat2018.PwlCosts()),
|
||||
"MorLatRam2013" => Formulation(ramping = MorLatRam2013.Ramping()),
|
||||
"PanGua2016" => Formulation(ramping = PanGua2016.Ramping()),
|
||||
)
|
||||
|
||||
# Solution methods
|
||||
# -----------------------------------------------------------------------------
|
||||
methods = Dict(
|
||||
"default" =>
|
||||
XavQiuWanThi2019.Method(time_limit = 3600.0, gap_limit = 1e-4),
|
||||
)
|
||||
|
||||
# MIP solvers
|
||||
# -----------------------------------------------------------------------------
|
||||
optimizers = Dict(
|
||||
"gurobi" => optimizer_with_attributes(
|
||||
Gurobi.Optimizer,
|
||||
"Threads" => Threads.nthreads(),
|
||||
),
|
||||
)
|
||||
|
||||
# Parse command line arguments
|
||||
# -----------------------------------------------------------------------------
|
||||
if !isempty(args["--case"])
|
||||
cases = args["--case"]
|
||||
end
|
||||
if !isempty(args["--formulation"])
|
||||
formulations = filter(p -> p.first in args["--formulation"], formulations)
|
||||
end
|
||||
if !isempty(args["--method"])
|
||||
methods = filter(p -> p.first in args["--method"], methods)
|
||||
end
|
||||
if !isempty(args["--solver"])
|
||||
optimizers = filter(p -> p.first in args["--solver"], optimizers)
|
||||
end
|
||||
const time_limit = parse(Float64, args["--time-limit"])
|
||||
const gap_limit = parse(Float64, args["--gap"])
|
||||
const ntrials = parse(Int, args["--trials"])
|
||||
|
||||
# Print benchmark settings
|
||||
# -----------------------------------------------------------------------------
|
||||
function printlist(d::Dict)
|
||||
for key in keys(d)
|
||||
@info " - $key"
|
||||
end
|
||||
end
|
||||
|
||||
function printlist(d::Vector)
|
||||
for key in d
|
||||
@info " - $key"
|
||||
end
|
||||
end
|
||||
|
||||
@info "Computational environment:"
|
||||
@info " - CPU: $(Sys.cpu_info()[1].model)"
|
||||
@info " - Logical CPU cores: $(length(Sys.cpu_info()))"
|
||||
@info " - System memory: $(round(Sys.total_memory() / 2^30, digits=2)) GiB"
|
||||
@info " - Available workers: $(nworkers())"
|
||||
@info " - Available threads per worker: $(Threads.nthreads())"
|
||||
|
||||
@info "Parameters:"
|
||||
@info " - Number of trials: $ntrials"
|
||||
@info " - Time limit (s): $time_limit"
|
||||
@info " - Relative MIP gap tolerance: $gap_limit"
|
||||
|
||||
@info "Solvers:"
|
||||
printlist(optimizers)
|
||||
|
||||
@info "Methods:"
|
||||
printlist(methods)
|
||||
|
||||
@info "Formulations:"
|
||||
printlist(formulations)
|
||||
|
||||
@info "Cases:"
|
||||
printlist(cases)
|
||||
|
||||
# Run benchmarks
|
||||
# -----------------------------------------------------------------------------
|
||||
UnitCommitment._run_benchmarks(
|
||||
cases = cases,
|
||||
formulations = formulations,
|
||||
methods = methods,
|
||||
optimizers = optimizers,
|
||||
trials = 1:ntrials,
|
||||
)
|
||||
5
deps/formatter/Project.toml
vendored
Normal file
5
deps/formatter/Project.toml
vendored
Normal file
@@ -0,0 +1,5 @@
|
||||
[deps]
|
||||
JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
|
||||
|
||||
[compat]
|
||||
JuliaFormatter = "0.14.4"
|
||||
9
deps/formatter/format.jl
vendored
Normal file
9
deps/formatter/format.jl
vendored
Normal file
@@ -0,0 +1,9 @@
|
||||
using JuliaFormatter
|
||||
format(
|
||||
[
|
||||
"../../src",
|
||||
"../../test",
|
||||
"../../benchmark/run.jl",
|
||||
],
|
||||
verbose=true,
|
||||
)
|
||||
@@ -28,13 +28,14 @@ Each section is described in detail below. For a complete example, see [case14](
|
||||
|
||||
### Parameters
|
||||
|
||||
This section describes system-wide parameters, such as power balance penalties, optimization parameters, such as the length of the planning horizon and the time.
|
||||
This section describes system-wide parameters, such as power balance and reserve shortfall penalties, and optimization parameters, such as the length of the planning horizon and the time.
|
||||
|
||||
| Key | Description | Default | Time series?
|
||||
| :----------------------------- | :------------------------------------------------ | :------: | :------------:
|
||||
| `Time horizon (h)` | Length of the planning horizon (in hours). | Required | N
|
||||
| `Time horizon (h)` | Length of the planning horizon (in hours). | Required | N
|
||||
| `Time step (min)` | Length of each time step (in minutes). Must be a divisor of 60 (e.g. 60, 30, 20, 15, etc). | `60` | N
|
||||
| `Power balance penalty ($/MW)` | Penalty for system-wide shortage or surplus in production (in $/MW). This is charged per time step. For example, if there is a shortage of 1 MW for three time steps, three times this amount will be charged. | `1000.0` | Y
|
||||
| `Reserve shortfall penalty ($/MW)` | Penalty for system-wide shortage in meeting reserve requirements (in $/MW). This is charged per time step. Negative value implies reserve constraints must always be satisfied. | `-1` | Y
|
||||
|
||||
|
||||
#### Example
|
||||
@@ -42,7 +43,8 @@ This section describes system-wide parameters, such as power balance penalties,
|
||||
{
|
||||
"Parameters": {
|
||||
"Time horizon (h)": 4,
|
||||
"Power balance penalty ($/MW)": 1000.0
|
||||
"Power balance penalty ($/MW)": 1000.0,
|
||||
"Reserve shortfall penalty ($/MW)": -1.0
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
@@ -148,7 +148,7 @@ for g in instance.units
|
||||
end
|
||||
```
|
||||
|
||||
### Modifying the model
|
||||
### Fixing variables, modifying objective function and adding constraints
|
||||
|
||||
Since we now have a direct reference to the JuMP decision variables, it is possible to fix variables, change the coefficients in the objective function, or even add new constraints to the model before solving it. The script below shows how can this be accomplished. For more information on modifying an existing model, [see the JuMP documentation](https://jump.dev/JuMP.jl/stable/manual/variables/).
|
||||
|
||||
@@ -190,6 +190,54 @@ JuMP.set_objective_coefficient(
|
||||
UnitCommitment.optimize!(model)
|
||||
```
|
||||
|
||||
### Adding new component to a bus
|
||||
|
||||
The following snippet shows how to add a new grid component to a particular bus. For each time step, we create decision variables for the new grid component, add these variables to the objective function, then attach the component to a particular bus by modifying some existing model constraints.
|
||||
|
||||
```julia
|
||||
using Cbc
|
||||
using JuMP
|
||||
using UnitCommitment
|
||||
|
||||
# Load instance and build base model
|
||||
instance = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
|
||||
model = UnitCommitment.build_model(
|
||||
instance=instance,
|
||||
optimizer=Cbc.Optimizer,
|
||||
)
|
||||
|
||||
# Get the number of time steps in the original instance
|
||||
T = instance.time
|
||||
|
||||
# Create decision variables for the new grid component.
|
||||
# In this example, we assume that the new component can
|
||||
# inject up to 10 MW of power at each time step, so we
|
||||
# create new continuous variables 0 ≤ x[t] ≤ 10.
|
||||
@variable(model, x[1:T], lower_bound=0.0, upper_bound=10.0)
|
||||
|
||||
# For each time step
|
||||
for t in 1:T
|
||||
|
||||
# Add production costs to the objective function.
|
||||
# In this example, we assume a cost of $5/MW.
|
||||
set_objective_coefficient(model, x[t], 5.0)
|
||||
|
||||
# Attach the new component to bus b1, by modifying the
|
||||
# constraint `eq_net_injection`.
|
||||
set_normalized_coefficient(
|
||||
model[:eq_net_injection]["b1", t],
|
||||
x[t],
|
||||
1.0,
|
||||
)
|
||||
end
|
||||
|
||||
# Solve the model
|
||||
UnitCommitment.optimize!(model)
|
||||
|
||||
# Show optimal values for the x variables
|
||||
@show value.(x)
|
||||
```
|
||||
|
||||
References
|
||||
----------
|
||||
* [KnOsWa20] **Bernard Knueven, James Ostrowski and Jean-Paul Watson.** "On Mixed-Integer Programming Formulations for the Unit Commitment Problem". INFORMS Journal on Computing (2020). [DOI: 10.1287/ijoc.2019.0944](https://doi.org/10.1287/ijoc.2019.0944)
|
||||
|
||||
Binary file not shown.
68
juliaw
Normal file
68
juliaw
Normal file
@@ -0,0 +1,68 @@
|
||||
#!/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 "path" in keys(manifest[dep][1])
|
||||
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
|
||||
@@ -48,8 +48,9 @@ include("solution/warmstart.jl")
|
||||
include("solution/write.jl")
|
||||
include("transform/initcond.jl")
|
||||
include("transform/slice.jl")
|
||||
include("transform/randomize.jl")
|
||||
include("transform/randomize/XavQiuAhm2021.jl")
|
||||
include("utils/log.jl")
|
||||
include("utils/benchmark.jl")
|
||||
include("validation/repair.jl")
|
||||
include("validation/validate.jl")
|
||||
|
||||
|
||||
@@ -98,6 +98,10 @@ function _from_json(json; repair = true)
|
||||
json["Parameters"]["Power balance penalty (\$/MW)"],
|
||||
default = [1000.0 for t in 1:T],
|
||||
)
|
||||
shortfall_penalty = timeseries(
|
||||
json["Parameters"]["Reserve shortfall penalty (\$/MW)"],
|
||||
default = [-1.0 for t in 1:T],
|
||||
)
|
||||
|
||||
# Read buses
|
||||
for (bus_name, dict) in json["Buses"]
|
||||
@@ -262,14 +266,20 @@ function _from_json(json; repair = true)
|
||||
end
|
||||
|
||||
instance = UnitCommitmentInstance(
|
||||
T,
|
||||
power_balance_penalty,
|
||||
units,
|
||||
buses,
|
||||
lines,
|
||||
reserves,
|
||||
contingencies,
|
||||
loads,
|
||||
buses_by_name = Dict(b.name => b for b in buses),
|
||||
buses = buses,
|
||||
contingencies_by_name = Dict(c.name => c for c in contingencies),
|
||||
contingencies = contingencies,
|
||||
lines_by_name = Dict(l.name => l for l in lines),
|
||||
lines = lines,
|
||||
power_balance_penalty = power_balance_penalty,
|
||||
price_sensitive_loads_by_name = Dict(ps.name => ps for ps in loads),
|
||||
price_sensitive_loads = loads,
|
||||
reserves = reserves,
|
||||
shortfall_penalty = shortfall_penalty,
|
||||
time = T,
|
||||
units_by_name = Dict(g.name => g for g in units),
|
||||
units = units,
|
||||
)
|
||||
if repair
|
||||
UnitCommitment.repair!(instance)
|
||||
|
||||
@@ -69,15 +69,21 @@ mutable struct PriceSensitiveLoad
|
||||
revenue::Vector{Float64}
|
||||
end
|
||||
|
||||
mutable struct UnitCommitmentInstance
|
||||
time::Int
|
||||
power_balance_penalty::Vector{Float64}
|
||||
units::Vector{Unit}
|
||||
Base.@kwdef mutable struct UnitCommitmentInstance
|
||||
buses_by_name::Dict{AbstractString,Bus}
|
||||
buses::Vector{Bus}
|
||||
lines::Vector{TransmissionLine}
|
||||
reserves::Reserves
|
||||
contingencies_by_name::Dict{AbstractString,Contingency}
|
||||
contingencies::Vector{Contingency}
|
||||
lines_by_name::Dict{AbstractString,TransmissionLine}
|
||||
lines::Vector{TransmissionLine}
|
||||
power_balance_penalty::Vector{Float64}
|
||||
price_sensitive_loads_by_name::Dict{AbstractString,PriceSensitiveLoad}
|
||||
price_sensitive_loads::Vector{PriceSensitiveLoad}
|
||||
reserves::Reserves
|
||||
shortfall_penalty::Vector{Float64}
|
||||
time::Int
|
||||
units_by_name::Dict{AbstractString,Unit}
|
||||
units::Vector{Unit}
|
||||
end
|
||||
|
||||
function Base.show(io::IO, instance::UnitCommitmentInstance)
|
||||
|
||||
@@ -12,14 +12,14 @@ function _add_startup_cost_eqs!(
|
||||
S = length(g.startup_categories)
|
||||
startup = model[:startup]
|
||||
for t in 1:model[:instance].time
|
||||
for s in 1:S
|
||||
# If unit is switching on, we must choose a startup category
|
||||
eq_startup_choose[g.name, t, s] = @constraint(
|
||||
model,
|
||||
model[:switch_on][g.name, t] ==
|
||||
sum(startup[g.name, t, s] for s in 1:S)
|
||||
)
|
||||
# If unit is switching on, we must choose a startup category
|
||||
eq_startup_choose[g.name, t] = @constraint(
|
||||
model,
|
||||
model[:switch_on][g.name, t] ==
|
||||
sum(startup[g.name, t, s] for s in 1:S)
|
||||
)
|
||||
|
||||
for s in 1:S
|
||||
# If unit has not switched off in the last `delay` time periods, startup category is forbidden.
|
||||
# The last startup category is always allowed.
|
||||
if s < S
|
||||
|
||||
@@ -4,15 +4,11 @@
|
||||
|
||||
function _add_bus!(model::JuMP.Model, b::Bus)::Nothing
|
||||
net_injection = _init(model, :expr_net_injection)
|
||||
reserve = _init(model, :expr_reserve)
|
||||
curtail = _init(model, :curtail)
|
||||
for t in 1:model[:instance].time
|
||||
# Fixed load
|
||||
net_injection[b.name, t] = AffExpr(-b.load[t])
|
||||
|
||||
# Reserves
|
||||
reserve[b.name, t] = AffExpr()
|
||||
|
||||
# Load curtailment
|
||||
curtail[b.name, t] =
|
||||
@variable(model, lower_bound = 0, upper_bound = b.load[t])
|
||||
|
||||
@@ -11,12 +11,12 @@ end
|
||||
function _add_net_injection_eqs!(model::JuMP.Model)::Nothing
|
||||
T = model[:instance].time
|
||||
net_injection = _init(model, :net_injection)
|
||||
eq_net_injection_def = _init(model, :eq_net_injection_def)
|
||||
eq_net_injection = _init(model, :eq_net_injection)
|
||||
eq_power_balance = _init(model, :eq_power_balance)
|
||||
for t in 1:T, b in model[:instance].buses
|
||||
n = net_injection[b.name, t] = @variable(model)
|
||||
eq_net_injection_def[t, b.name] =
|
||||
@constraint(model, n == model[:expr_net_injection][b.name, t])
|
||||
eq_net_injection[b.name, t] =
|
||||
@constraint(model, -n + model[:expr_net_injection][b.name, t] == 0)
|
||||
end
|
||||
for t in 1:T
|
||||
eq_power_balance[t] = @constraint(
|
||||
@@ -29,13 +29,28 @@ end
|
||||
|
||||
function _add_reserve_eqs!(model::JuMP.Model)::Nothing
|
||||
eq_min_reserve = _init(model, :eq_min_reserve)
|
||||
for t in 1:model[:instance].time
|
||||
instance = model[:instance]
|
||||
for t in 1:instance.time
|
||||
# Equation (68) in Kneuven et al. (2020)
|
||||
# As in Morales-España et al. (2013a)
|
||||
# Akin to the alternative formulation with max_power_avail
|
||||
# from Carrión and Arroyo (2006) and Ostrowski et al. (2012)
|
||||
shortfall_penalty = instance.shortfall_penalty[t]
|
||||
eq_min_reserve[t] = @constraint(
|
||||
model,
|
||||
sum(
|
||||
model[:expr_reserve][b.name, t] for b in model[:instance].buses
|
||||
) >= model[:instance].reserves.spinning[t]
|
||||
sum(model[:reserve][g.name, t] for g in instance.units) +
|
||||
(shortfall_penalty >= 0 ? model[:reserve_shortfall][t] : 0.0) >=
|
||||
instance.reserves.spinning[t]
|
||||
)
|
||||
|
||||
# Account for shortfall contribution to objective
|
||||
if shortfall_penalty >= 0
|
||||
add_to_expression!(
|
||||
model[:obj],
|
||||
shortfall_penalty,
|
||||
model[:reserve_shortfall][t],
|
||||
)
|
||||
end
|
||||
end
|
||||
return
|
||||
end
|
||||
|
||||
@@ -44,12 +44,16 @@ _is_initially_on(g::Unit)::Float64 = (g.initial_status > 0 ? 1.0 : 0.0)
|
||||
|
||||
function _add_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
|
||||
reserve = _init(model, :reserve)
|
||||
reserve_shortfall = _init(model, :reserve_shortfall)
|
||||
for t in 1:model[:instance].time
|
||||
if g.provides_spinning_reserves[t]
|
||||
reserve[g.name, t] = @variable(model, lower_bound = 0)
|
||||
else
|
||||
reserve[g.name, t] = 0.0
|
||||
end
|
||||
reserve_shortfall[t] =
|
||||
(model[:instance].shortfall_penalty[t] >= 0) ?
|
||||
@variable(model, lower_bound = 0) : 0.0
|
||||
end
|
||||
return
|
||||
end
|
||||
@@ -210,11 +214,5 @@ function _add_net_injection_eqs!(model::JuMP.Model, g::Unit)::Nothing
|
||||
model[:is_on][g.name, t],
|
||||
g.min_power[t],
|
||||
)
|
||||
# Add to reserves expression
|
||||
add_to_expression!(
|
||||
model[:expr_reserve][g.bus.name, t],
|
||||
model[:reserve][g.name, t],
|
||||
1.0,
|
||||
)
|
||||
end
|
||||
end
|
||||
|
||||
@@ -51,6 +51,12 @@ function solution(model::JuMP.Model)::OrderedDict
|
||||
sol["Switch on"] = timeseries(model[:switch_on], instance.units)
|
||||
sol["Switch off"] = timeseries(model[:switch_off], instance.units)
|
||||
sol["Reserve (MW)"] = timeseries(model[:reserve], instance.units)
|
||||
sol["Reserve shortfall (MW)"] = OrderedDict(
|
||||
t =>
|
||||
(instance.shortfall_penalty[t] >= 0) ?
|
||||
round(value(model[:reserve_shortfall][t]), digits = 5) : 0.0 for
|
||||
t in 1:instance.time
|
||||
)
|
||||
sol["Net injection (MW)"] =
|
||||
timeseries(model[:net_injection], instance.buses)
|
||||
sol["Load curtail (MW)"] = timeseries(model[:curtail], instance.buses)
|
||||
|
||||
@@ -1,53 +0,0 @@
|
||||
# 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.
|
||||
|
||||
using Distributions
|
||||
|
||||
function randomize_unit_costs!(
|
||||
instance::UnitCommitmentInstance;
|
||||
distribution = Uniform(0.95, 1.05),
|
||||
)::Nothing
|
||||
for unit in instance.units
|
||||
α = rand(distribution)
|
||||
unit.min_power_cost *= α
|
||||
for k in unit.cost_segments
|
||||
k.cost *= α
|
||||
end
|
||||
for s in unit.startup_categories
|
||||
s.cost *= α
|
||||
end
|
||||
end
|
||||
return
|
||||
end
|
||||
|
||||
function randomize_load_distribution!(
|
||||
instance::UnitCommitmentInstance;
|
||||
distribution = Uniform(0.90, 1.10),
|
||||
)::Nothing
|
||||
α = rand(distribution, length(instance.buses))
|
||||
for t in 1:instance.time
|
||||
total = sum(bus.load[t] for bus in instance.buses)
|
||||
den = sum(
|
||||
bus.load[t] / total * α[i] for
|
||||
(i, bus) in enumerate(instance.buses)
|
||||
)
|
||||
for (i, bus) in enumerate(instance.buses)
|
||||
bus.load[t] *= α[i] / den
|
||||
end
|
||||
end
|
||||
return
|
||||
end
|
||||
|
||||
function randomize_peak_load!(
|
||||
instance::UnitCommitmentInstance;
|
||||
distribution = Uniform(0.925, 1.075),
|
||||
)::Nothing
|
||||
α = rand(distribution)
|
||||
for bus in instance.buses
|
||||
bus.load *= α
|
||||
end
|
||||
return
|
||||
end
|
||||
|
||||
export randomize_unit_costs!, randomize_load_distribution!, randomize_peak_load!
|
||||
209
src/transform/randomize/XavQiuAhm2021.jl
Normal file
209
src/transform/randomize/XavQiuAhm2021.jl
Normal file
@@ -0,0 +1,209 @@
|
||||
# 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.
|
||||
|
||||
"""
|
||||
Methods described in:
|
||||
|
||||
Xavier, Álinson S., Feng Qiu, and Shabbir Ahmed. "Learning to solve
|
||||
large-scale security-constrained unit commitment problems." INFORMS
|
||||
Journal on Computing 33.2 (2021): 739-756. DOI: 10.1287/ijoc.2020.0976
|
||||
"""
|
||||
module XavQiuAhm2021
|
||||
|
||||
using Distributions
|
||||
import ..UnitCommitmentInstance
|
||||
|
||||
"""
|
||||
struct Randomization
|
||||
cost = Uniform(0.95, 1.05)
|
||||
load_profile_mu = [...]
|
||||
load_profile_sigma = [...]
|
||||
load_share = Uniform(0.90, 1.10)
|
||||
peak_load = Uniform(0.6 * 0.925, 0.6 * 1.075)
|
||||
randomize_costs = true
|
||||
randomize_load_profile = true
|
||||
randomize_load_share = true
|
||||
end
|
||||
|
||||
Randomization method that changes: (1) production and startup costs, (2)
|
||||
share of load coming from each bus, (3) peak system load, and (4) temporal
|
||||
load profile, as follows:
|
||||
|
||||
1. **Production and startup costs:**
|
||||
For each unit `u`, the vectors `u.min_power_cost` and `u.cost_segments`
|
||||
are multiplied by a constant `α[u]` sampled from the provided `cost`
|
||||
distribution. If `randomize_costs` is false, skips this step.
|
||||
|
||||
2. **Load share:**
|
||||
For each bus `b` and time `t`, the value `b.load[t]` is multiplied by
|
||||
`(β[b] * b.load[t]) / sum(β[b2] * b2.load[t] for b2 in buses)`, where
|
||||
`β[b]` is sampled from the provided `load_share` distribution. If
|
||||
`randomize_load_share` is false, skips this step.
|
||||
|
||||
3. **Peak system load and temporal load profile:**
|
||||
Sets the peak load to `ρ * C`, where `ρ` is sampled from `peak_load` and `C`
|
||||
is the maximum system capacity, at any time. Also scales the loads of all
|
||||
buses, so that `system_load[t+1]` becomes equal to `system_load[t] * γ[t]`,
|
||||
where `γ[t]` is sampled from `Normal(load_profile_mu[t], load_profile_sigma[t])`.
|
||||
|
||||
The system load for the first time period is set so that the peak load
|
||||
matches `ρ * C`. If `load_profile_sigma` and `load_profile_mu` have fewer
|
||||
elements than `instance.time`, wraps around. If `randomize_load_profile`
|
||||
is false, skips this step.
|
||||
|
||||
The default parameters were obtained based on an analysis of publicly available
|
||||
bid and hourly data from PJM, corresponding to the month of January, 2017. For
|
||||
more details, see Section 4.2 of the paper.
|
||||
"""
|
||||
Base.@kwdef struct Randomization
|
||||
cost = Uniform(0.95, 1.05)
|
||||
load_profile_mu::Vector{Float64} = [
|
||||
1.0,
|
||||
0.978,
|
||||
0.98,
|
||||
1.004,
|
||||
1.02,
|
||||
1.078,
|
||||
1.132,
|
||||
1.018,
|
||||
0.999,
|
||||
1.006,
|
||||
0.999,
|
||||
0.987,
|
||||
0.975,
|
||||
0.984,
|
||||
0.995,
|
||||
1.005,
|
||||
1.045,
|
||||
1.106,
|
||||
0.981,
|
||||
0.981,
|
||||
0.978,
|
||||
0.948,
|
||||
0.928,
|
||||
0.953,
|
||||
]
|
||||
load_profile_sigma::Vector{Float64} = [
|
||||
0.0,
|
||||
0.011,
|
||||
0.015,
|
||||
0.01,
|
||||
0.012,
|
||||
0.029,
|
||||
0.055,
|
||||
0.027,
|
||||
0.026,
|
||||
0.023,
|
||||
0.013,
|
||||
0.012,
|
||||
0.014,
|
||||
0.011,
|
||||
0.008,
|
||||
0.008,
|
||||
0.02,
|
||||
0.02,
|
||||
0.016,
|
||||
0.012,
|
||||
0.014,
|
||||
0.015,
|
||||
0.017,
|
||||
0.024,
|
||||
]
|
||||
load_share = Uniform(0.90, 1.10)
|
||||
peak_load = Uniform(0.6 * 0.925, 0.6 * 1.075)
|
||||
randomize_load_profile::Bool = true
|
||||
randomize_costs::Bool = true
|
||||
randomize_load_share::Bool = true
|
||||
end
|
||||
|
||||
function _randomize_costs(
|
||||
instance::UnitCommitmentInstance,
|
||||
distribution,
|
||||
)::Nothing
|
||||
for unit in instance.units
|
||||
α = rand(distribution)
|
||||
unit.min_power_cost *= α
|
||||
for k in unit.cost_segments
|
||||
k.cost *= α
|
||||
end
|
||||
for s in unit.startup_categories
|
||||
s.cost *= α
|
||||
end
|
||||
end
|
||||
return
|
||||
end
|
||||
|
||||
function _randomize_load_share(
|
||||
instance::UnitCommitmentInstance,
|
||||
distribution,
|
||||
)::Nothing
|
||||
α = rand(distribution, length(instance.buses))
|
||||
for t in 1:instance.time
|
||||
total = sum(bus.load[t] for bus in instance.buses)
|
||||
den = sum(
|
||||
bus.load[t] / total * α[i] for
|
||||
(i, bus) in enumerate(instance.buses)
|
||||
)
|
||||
for (i, bus) in enumerate(instance.buses)
|
||||
bus.load[t] *= α[i] / den
|
||||
end
|
||||
end
|
||||
return
|
||||
end
|
||||
|
||||
function _randomize_load_profile(
|
||||
instance::UnitCommitmentInstance,
|
||||
params::Randomization,
|
||||
)::Nothing
|
||||
# Generate new system load
|
||||
system_load = [1.0]
|
||||
for t in 2:instance.time
|
||||
idx = (t - 1) % length(params.load_profile_mu) + 1
|
||||
gamma = rand(
|
||||
Normal(params.load_profile_mu[idx], params.load_profile_sigma[idx]),
|
||||
)
|
||||
push!(system_load, system_load[t-1] * gamma)
|
||||
end
|
||||
capacity = sum(maximum(u.max_power) for u in instance.units)
|
||||
peak_load = rand(params.peak_load) * capacity
|
||||
system_load = system_load ./ maximum(system_load) .* peak_load
|
||||
|
||||
# Scale bus loads to match the new system load
|
||||
prev_system_load = sum(b.load for b in instance.buses)
|
||||
for b in instance.buses
|
||||
for t in 1:instance.time
|
||||
b.load[t] *= system_load[t] / prev_system_load[t]
|
||||
end
|
||||
end
|
||||
|
||||
return
|
||||
end
|
||||
|
||||
end
|
||||
|
||||
"""
|
||||
function randomize!(
|
||||
instance::UnitCommitment.UnitCommitmentInstance,
|
||||
method::XavQiuAhm2021.Randomization,
|
||||
)::Nothing
|
||||
|
||||
Randomize costs and loads based on the method described in XavQiuAhm2021.
|
||||
"""
|
||||
function randomize!(
|
||||
instance::UnitCommitment.UnitCommitmentInstance,
|
||||
method::XavQiuAhm2021.Randomization,
|
||||
)::Nothing
|
||||
if method.randomize_costs
|
||||
XavQiuAhm2021._randomize_costs(instance, method.cost)
|
||||
end
|
||||
if method.randomize_load_share
|
||||
XavQiuAhm2021._randomize_load_share(instance, method.load_share)
|
||||
end
|
||||
if method.randomize_load_profile
|
||||
XavQiuAhm2021._randomize_load_profile(instance, method)
|
||||
end
|
||||
return
|
||||
end
|
||||
|
||||
export randomize!
|
||||
116
src/utils/benchmark.jl
Normal file
116
src/utils/benchmark.jl
Normal file
@@ -0,0 +1,116 @@
|
||||
# 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 Distributed
|
||||
using Random
|
||||
|
||||
function _run_benchmark_sample(;
|
||||
case::String,
|
||||
method::SolutionMethod,
|
||||
formulation::Formulation,
|
||||
solution_filename::String,
|
||||
optimizer,
|
||||
)::Nothing
|
||||
total_time = @elapsed begin
|
||||
@info "Reading: $case"
|
||||
time_read = @elapsed begin
|
||||
instance = read_benchmark(case)
|
||||
end
|
||||
@info @sprintf("Read problem in %.2f seconds", time_read)
|
||||
BLAS.set_num_threads(Threads.nthreads())
|
||||
model = build_model(
|
||||
instance = instance,
|
||||
formulation = formulation,
|
||||
optimizer = optimizer,
|
||||
variable_names = true,
|
||||
)
|
||||
@info "Optimizing..."
|
||||
BLAS.set_num_threads(1)
|
||||
optimize!(model, method)
|
||||
end
|
||||
@info @sprintf("Total time was %.2f seconds", total_time)
|
||||
|
||||
@info "Writing solution: $solution_filename"
|
||||
solution = UnitCommitment.solution(model)
|
||||
write("$solution_filename", solution)
|
||||
|
||||
@info "Verifying solution..."
|
||||
validate(instance, solution)
|
||||
return
|
||||
end
|
||||
|
||||
function _run_benchmark_combination(
|
||||
case::String,
|
||||
optimizer_name::String,
|
||||
optimizer,
|
||||
method_name::String,
|
||||
method::SolutionMethod,
|
||||
formulation_name::String,
|
||||
formulation::Formulation,
|
||||
trial,
|
||||
)
|
||||
dirname = "results/$optimizer_name/$method_name/$formulation_name/$case"
|
||||
function info(msg)
|
||||
@info @sprintf(
|
||||
"%-8s %-16s %-16s %-16s %-8s %s",
|
||||
msg,
|
||||
optimizer_name,
|
||||
method_name,
|
||||
formulation_name,
|
||||
trial,
|
||||
case
|
||||
)
|
||||
end
|
||||
mkpath(dirname)
|
||||
trial_filename = @sprintf("%s/%03d.json", dirname, trial)
|
||||
if isfile(trial_filename)
|
||||
info("skip")
|
||||
return
|
||||
end
|
||||
info("run")
|
||||
open("$trial_filename.log", "w") do file
|
||||
redirect_stdout(file) do
|
||||
redirect_stderr(file) do
|
||||
return _run_benchmark_sample(
|
||||
case = case,
|
||||
method = method,
|
||||
formulation = formulation,
|
||||
solution_filename = trial_filename,
|
||||
optimizer = optimizer,
|
||||
)
|
||||
end
|
||||
end
|
||||
end
|
||||
return info("done")
|
||||
end
|
||||
|
||||
function _run_benchmarks(;
|
||||
cases::Vector{String},
|
||||
optimizers::Dict,
|
||||
formulations::Dict,
|
||||
methods::Dict,
|
||||
trials,
|
||||
)
|
||||
combinations = [
|
||||
(c, s.first, s.second, m.first, m.second, f.first, f.second, t) for
|
||||
c in cases for s in optimizers for f in formulations for
|
||||
m in methods for t in trials
|
||||
]
|
||||
shuffle!(combinations)
|
||||
if nworkers() > 1
|
||||
@printf("%24s", "")
|
||||
end
|
||||
@info @sprintf(
|
||||
"%-8s %-16s %-16s %-16s %-8s %s",
|
||||
"STATUS",
|
||||
"SOLVER",
|
||||
"METHOD",
|
||||
"FORMULATION",
|
||||
"TRIAL",
|
||||
"CASE"
|
||||
)
|
||||
@sync @distributed for c in combinations
|
||||
_run_benchmark_combination(c...)
|
||||
end
|
||||
end
|
||||
@@ -1,28 +0,0 @@
|
||||
# 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 PackageCompiler
|
||||
|
||||
using DataStructures
|
||||
using Distributions
|
||||
using JSON
|
||||
using JuMP
|
||||
using MathOptInterface
|
||||
using SparseArrays
|
||||
|
||||
pkg = [
|
||||
:DataStructures,
|
||||
:Distributions,
|
||||
:JSON,
|
||||
:JuMP,
|
||||
:MathOptInterface,
|
||||
:SparseArrays,
|
||||
]
|
||||
|
||||
@info "Building system image..."
|
||||
create_sysimage(
|
||||
pkg,
|
||||
precompile_statements_file = "build/precompile.jl",
|
||||
sysimage_path = "build/sysimage.so",
|
||||
)
|
||||
@@ -208,12 +208,8 @@ function _validate_units(instance, solution; tol = 0.01)
|
||||
break
|
||||
end
|
||||
end
|
||||
if t == time_down + 1
|
||||
initial_down = unit.min_downtime
|
||||
if unit.initial_status < 0
|
||||
initial_down = -unit.initial_status
|
||||
end
|
||||
time_down += initial_down
|
||||
if (t == time_down + 1) && (unit.initial_status < 0)
|
||||
time_down -= unit.initial_status
|
||||
end
|
||||
|
||||
# Calculate startup costs
|
||||
@@ -246,14 +242,6 @@ function _validate_units(instance, solution; tol = 0.01)
|
||||
break
|
||||
end
|
||||
end
|
||||
if t == time_up + 1
|
||||
initial_up = unit.min_uptime
|
||||
if unit.initial_status > 0
|
||||
initial_up = unit.initial_status
|
||||
end
|
||||
time_up += initial_up
|
||||
end
|
||||
|
||||
if (t == time_up + 1) && (unit.initial_status > 0)
|
||||
time_up += unit.initial_status
|
||||
end
|
||||
@@ -336,11 +324,16 @@ function _validate_reserve_and_demand(instance, solution, tol = 0.01)
|
||||
# Verify spinning reserves
|
||||
reserve =
|
||||
sum(solution["Reserve (MW)"][g.name][t] for g in instance.units)
|
||||
if reserve < instance.reserves.spinning[t] - tol
|
||||
reserve_shortfall =
|
||||
(instance.shortfall_penalty[t] >= 0) ?
|
||||
solution["Reserve shortfall (MW)"][t] : 0
|
||||
|
||||
if reserve + reserve_shortfall < instance.reserves.spinning[t] - tol
|
||||
@error @sprintf(
|
||||
"Insufficient spinning reserves at time %d (%.2f should be %.2f)",
|
||||
"Insufficient spinning reserves at time %d (%.2f + %.2f should be %.2f)",
|
||||
t,
|
||||
reserve,
|
||||
reserve_shortfall,
|
||||
instance.reserves.spinning[t],
|
||||
)
|
||||
err_count += 1
|
||||
|
||||
26
test/Project.toml
Normal file
26
test/Project.toml
Normal file
@@ -0,0 +1,26 @@
|
||||
[deps]
|
||||
Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
|
||||
DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
|
||||
Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
|
||||
GZip = "92fee26a-97fe-5a0c-ad85-20a5f3185b63"
|
||||
Gurobi = "2e9cd046-0924-5485-92f1-d5272153d98b"
|
||||
JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
|
||||
JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
|
||||
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"
|
||||
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
|
||||
|
||||
[compat]
|
||||
DataStructures = "0.18"
|
||||
Distributions = "0.25"
|
||||
GZip = "0.5"
|
||||
JSON = "0.21"
|
||||
JuMP = "0.21"
|
||||
MathOptInterface = "0.9"
|
||||
PackageCompiler = "1"
|
||||
julia = "1"
|
||||
@@ -4,9 +4,12 @@
|
||||
|
||||
using UnitCommitment
|
||||
|
||||
basedir = @__DIR__
|
||||
|
||||
@testset "read_egret_solution" begin
|
||||
solution =
|
||||
UnitCommitment.read_egret_solution("fixtures/egret_output.json.gz")
|
||||
solution = UnitCommitment.read_egret_solution(
|
||||
"$basedir/../fixtures/egret_output.json.gz",
|
||||
)
|
||||
for attr in ["Is on", "Production (MW)", "Production cost (\$)"]
|
||||
@test attr in keys(solution)
|
||||
@test "115_STEAM_1" in keys(solution[attr])
|
||||
|
||||
@@ -22,6 +22,7 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
|
||||
@test instance.lines[5].normal_flow_limit == [1e8 for t in 1:4]
|
||||
@test instance.lines[5].emergency_flow_limit == [1e8 for t in 1:4]
|
||||
@test instance.lines[5].flow_limit_penalty == [5e3 for t in 1:4]
|
||||
@test instance.lines_by_name["l5"].name == "l5"
|
||||
|
||||
@test instance.lines[1].name == "l1"
|
||||
@test instance.lines[1].source.name == "b1"
|
||||
@@ -34,6 +35,7 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
|
||||
|
||||
@test instance.buses[9].name == "b9"
|
||||
@test instance.buses[9].load == [35.36638, 33.25495, 31.67138, 31.14353]
|
||||
@test instance.buses_by_name["b9"].name == "b9"
|
||||
|
||||
unit = instance.units[1]
|
||||
@test unit.name == "g1"
|
||||
@@ -62,6 +64,7 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
|
||||
@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 instance.units_by_name["g1"].name == "g1"
|
||||
|
||||
unit = instance.units[2]
|
||||
@test unit.name == "g2"
|
||||
@@ -92,12 +95,15 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
|
||||
|
||||
@test instance.contingencies[1].lines == [instance.lines[1]]
|
||||
@test instance.contingencies[1].units == []
|
||||
@test instance.contingencies[1].name == "c1"
|
||||
@test instance.contingencies_by_name["c1"].name == "c1"
|
||||
|
||||
load = instance.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 instance.price_sensitive_loads_by_name["ps1"].name == "ps1"
|
||||
end
|
||||
|
||||
@testset "read_benchmark sub-hourly" begin
|
||||
|
||||
@@ -3,6 +3,7 @@
|
||||
# Released under the modified BSD license. See COPYING.md for more details.
|
||||
|
||||
using UnitCommitment
|
||||
using JuMP
|
||||
import UnitCommitment:
|
||||
ArrCon2000,
|
||||
CarArr2006,
|
||||
@@ -11,17 +12,55 @@ import UnitCommitment:
|
||||
Gar1962,
|
||||
KnuOstWat2018,
|
||||
MorLatRam2013,
|
||||
PanGua2016
|
||||
PanGua2016,
|
||||
XavQiuWanThi2019
|
||||
|
||||
function _test(formulation::Formulation)::Nothing
|
||||
instance = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
|
||||
UnitCommitment.build_model(instance = instance, formulation = formulation) # should not crash
|
||||
if ENABLE_LARGE_TESTS
|
||||
using Gurobi
|
||||
end
|
||||
|
||||
function _small_test(formulation::Formulation)::Nothing
|
||||
instances = ["matpower/case118/2017-02-01", "test/case14"]
|
||||
for instance in instances
|
||||
# Should not crash
|
||||
UnitCommitment.build_model(
|
||||
instance = UnitCommitment.read_benchmark(instance),
|
||||
formulation = formulation,
|
||||
)
|
||||
end
|
||||
return
|
||||
end
|
||||
|
||||
function _large_test(formulation::Formulation)::Nothing
|
||||
instances = ["pglib-uc/ca/Scenario400_reserves_1"]
|
||||
for instance in instances
|
||||
instance = UnitCommitment.read_benchmark(instance)
|
||||
model = UnitCommitment.build_model(
|
||||
instance = instance,
|
||||
formulation = formulation,
|
||||
optimizer = Gurobi.Optimizer,
|
||||
)
|
||||
UnitCommitment.optimize!(
|
||||
model,
|
||||
XavQiuWanThi2019.Method(two_phase_gap = false, gap_limit = 0.1),
|
||||
)
|
||||
solution = UnitCommitment.solution(model)
|
||||
@test UnitCommitment.validate(instance, solution)
|
||||
end
|
||||
return
|
||||
end
|
||||
|
||||
function _test(formulation::Formulation)::Nothing
|
||||
_small_test(formulation)
|
||||
if ENABLE_LARGE_TESTS
|
||||
_large_test(formulation)
|
||||
end
|
||||
end
|
||||
|
||||
@testset "formulations" begin
|
||||
_test(Formulation())
|
||||
_test(Formulation(ramping = ArrCon2000.Ramping()))
|
||||
_test(Formulation(ramping = DamKucRajAta2016.Ramping()))
|
||||
# _test(Formulation(ramping = DamKucRajAta2016.Ramping()))
|
||||
_test(
|
||||
Formulation(
|
||||
ramping = MorLatRam2013.Ramping(),
|
||||
|
||||
@@ -5,8 +5,11 @@
|
||||
using Test
|
||||
using UnitCommitment
|
||||
|
||||
push!(Base.LOAD_PATH, @__DIR__)
|
||||
UnitCommitment._setup_logger()
|
||||
|
||||
const ENABLE_LARGE_TESTS = ("UCJL_LARGE_TESTS" in keys(ENV))
|
||||
|
||||
@testset "UnitCommitment" begin
|
||||
include("usage.jl")
|
||||
@testset "import" begin
|
||||
@@ -26,7 +29,9 @@ UnitCommitment._setup_logger()
|
||||
@testset "transform" begin
|
||||
include("transform/initcond_test.jl")
|
||||
include("transform/slice_test.jl")
|
||||
include("transform/randomize_test.jl")
|
||||
@testset "randomize" begin
|
||||
include("transform/randomize/XavQiuAhm2021_test.jl")
|
||||
end
|
||||
end
|
||||
@testset "validation" begin
|
||||
include("validation/repair_test.jl")
|
||||
|
||||
@@ -4,9 +4,12 @@
|
||||
|
||||
using UnitCommitment, Cbc, JuMP
|
||||
|
||||
basedir = @__DIR__
|
||||
|
||||
@testset "generate_initial_conditions!" begin
|
||||
# Load instance
|
||||
instance = UnitCommitment.read("$(pwd())/fixtures/case118-initcond.json.gz")
|
||||
instance =
|
||||
UnitCommitment.read("$basedir/../fixtures/case118-initcond.json.gz")
|
||||
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
|
||||
|
||||
# All units should have unknown initial conditions
|
||||
|
||||
63
test/transform/randomize/XavQiuAhm2021_test.jl
Normal file
63
test/transform/randomize/XavQiuAhm2021_test.jl
Normal file
@@ -0,0 +1,63 @@
|
||||
# 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 UnitCommitment, Cbc, JuMP
|
||||
|
||||
get_instance() = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
|
||||
system_load(instance) = sum(b.load for b in instance.buses)
|
||||
test_approx(x, y) = @test isapprox(x, y, atol = 1e-3)
|
||||
|
||||
@testset "XavQiuAhm2021" begin
|
||||
@testset "cost and load share" begin
|
||||
instance = get_instance()
|
||||
|
||||
# Check original costs
|
||||
unit = instance.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 = instance.buses[1]
|
||||
prev_system_load = system_load(instance)
|
||||
test_approx(bus.load[1] / prev_system_load[1], 0.012)
|
||||
|
||||
Random.seed!(42)
|
||||
randomize!(
|
||||
instance,
|
||||
XavQiuAhm2021.Randomization(randomize_load_profile = false),
|
||||
)
|
||||
|
||||
# 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(instance)
|
||||
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
|
||||
instance = get_instance()
|
||||
|
||||
# Check original load profile
|
||||
@test round.(system_load(instance), digits = 1)[1:8] ≈
|
||||
[3059.5, 2983.2, 2937.5, 2953.9, 3073.1, 3356.4, 4068.5, 4018.8]
|
||||
|
||||
Random.seed!(42)
|
||||
randomize!(instance, XavQiuAhm2021.Randomization())
|
||||
|
||||
# Check randomized load profile
|
||||
@test round.(system_load(instance), digits = 1)[1:8] ≈
|
||||
[4854.7, 4849.2, 4732.7, 4848.2, 4948.4, 5231.1, 5874.8, 5934.8]
|
||||
end
|
||||
end
|
||||
@@ -1,43 +0,0 @@
|
||||
# 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
|
||||
|
||||
_get_instance() = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
|
||||
_total_load(instance) = sum(b.load[1] for b in instance.buses)
|
||||
|
||||
@testset "randomize_unit_costs!" begin
|
||||
instance = _get_instance()
|
||||
unit = instance.units[10]
|
||||
prev_min_power_cost = unit.min_power_cost
|
||||
prev_prod_cost = unit.cost_segments[1].cost
|
||||
prev_startup_cost = unit.startup_categories[1].cost
|
||||
randomize_unit_costs!(instance)
|
||||
@test prev_min_power_cost != unit.min_power_cost
|
||||
@test prev_prod_cost != unit.cost_segments[1].cost
|
||||
@test prev_startup_cost != unit.startup_categories[1].cost
|
||||
end
|
||||
|
||||
@testset "randomize_load_distribution!" begin
|
||||
instance = _get_instance()
|
||||
bus = instance.buses[1]
|
||||
prev_load = instance.buses[1].load[1]
|
||||
prev_total_load = _total_load(instance)
|
||||
randomize_load_distribution!(instance)
|
||||
curr_total_load = _total_load(instance)
|
||||
@test prev_load != instance.buses[1].load[1]
|
||||
@test abs(prev_total_load - curr_total_load) < 1e-3
|
||||
end
|
||||
|
||||
@testset "randomize_peak_load!" begin
|
||||
instance = _get_instance()
|
||||
bus = instance.buses[1]
|
||||
prev_total_load = _total_load(instance)
|
||||
prev_share = bus.load[1] / prev_total_load
|
||||
randomize_peak_load!(instance)
|
||||
curr_total_load = _total_load(instance)
|
||||
curr_share = bus.load[1] / prev_total_load
|
||||
@test curr_total_load != prev_total_load
|
||||
@test abs(curr_share - prev_share) < 1e-3
|
||||
end
|
||||
@@ -4,9 +4,11 @@
|
||||
|
||||
using UnitCommitment, JSON, GZip, DataStructures
|
||||
|
||||
basedir = @__DIR__
|
||||
|
||||
function parse_case14()
|
||||
return JSON.parse(
|
||||
GZip.gzopen("../instances/test/case14.json.gz"),
|
||||
GZip.gzopen("$basedir/../../instances/test/case14.json.gz"),
|
||||
dicttype = () -> DefaultOrderedDict(nothing),
|
||||
)
|
||||
end
|
||||
|
||||
Reference in New Issue
Block a user