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15 Commits

Author SHA1 Message Date
Aleksandr Kazachkov
2b429bc664 Fix failing test due to wrong solution.jl input of reserve shortfall 2021-07-23 23:29:58 -04:00
Aleksandr Kazachkov
2d48c84f1a Ran JuliaFormatter 2021-07-23 22:57:16 -04:00
Aleksandr Kazachkov
718d6af96b Properly handle reserve_shortfall when variable not present. 2021-07-23 22:53:02 -04:00
Aleksandr Kazachkov
56c9e28495 Added missing reference to objective. 2021-07-23 19:23:13 -04:00
Aleksandr Kazachkov
3d252c55a3 Merge branch 'feature/reserve-shortfall' of github.com:ANL-CEEESA/UnitCommitment.jl into feature/reserve-shortfall 2021-07-23 18:48:11 -04:00
Aleksandr Kazachkov
f44d7bcfdf Fix _validate_reserve_and_demand 2021-07-23 18:48:03 -04:00
c64b76d6d1 Minor fixes to docs 2021-07-23 17:33:53 -05:00
f514ace560 Add test for reserve shortfall penalty 2021-07-23 17:23:42 -05:00
Aleksandr Kazachkov
97b8611fcc Added reserve_shortfall variable 2021-07-23 18:17:53 -04:00
209c3a72e9 Reformat code 2021-07-23 17:11:01 -05:00
fe3066f2b5 Remove commented out code 2021-07-23 17:09:16 -05:00
Aleksandr Kazachkov
92221bcaa4 Use shortfall penalty only when val is nonnegative 2021-07-23 16:54:51 -04:00
Aleksandr Kazachkov
2cdf8874fb Replace no penalty text with corrected documentation that reserve constraints must be satisfied. 2021-07-23 16:52:24 -04:00
Aleksandr Kazachkov
ea35c3ffcc Added docs for shortfall and set default to -1, indicating no penalty. 2021-07-23 16:50:04 -04:00
Aleksandr Kazachkov
7a03f4bbb0 Add reserve shortfall penalty 2021-07-23 11:23:16 -05:00
18 changed files with 157 additions and 380 deletions

View File

@@ -9,8 +9,8 @@ jobs:
runs-on: ${{ matrix.os }}
strategy:
matrix:
julia-version: ['1.4', '1.5', '1.6']
julia-arch: [x64]
julia-version: ['1.3', '1.4', '1.5', '1.6']
julia-arch: [x64, x86]
os: [ubuntu-latest, windows-latest, macOS-latest]
exclude:
- os: macOS-latest

1
.gitignore vendored
View File

@@ -18,4 +18,3 @@ TODO.md
docs/_build
.vscode
Manifest.toml
*/Manifest.toml

View File

@@ -5,20 +5,23 @@
JULIA := julia --color=yes --project=@.
VERSION := 0.2
build/sysimage.so: src/utils/sysimage.jl Project.toml
julia --project=. -e "using Pkg; Pkg.instantiate()"
julia --project=test -e "using Pkg; Pkg.instantiate()"
$(JULIA) src/utils/sysimage.jl test/runtests.jl
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
$(JULIA) src/utils/sysimage.jl
clean:
rm -rfv build
rm -rf build/*
docs:
cd docs; make clean; make dirhtml
rsync -avP --delete-after docs/_build/dirhtml/ ../docs/$(VERSION)/
test: build/sysimage.so
$(JULIA) --sysimage build/sysimage.so test/runtests.jl
@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);'

View File

@@ -2,7 +2,7 @@ name = "UnitCommitment"
uuid = "64606440-39ea-11e9-0f29-3303a1d3d877"
authors = ["Santos Xavier, Alinson <axavier@anl.gov>"]
repo = "https://github.com/ANL-CEEESA/UnitCommitment.jl"
version = "0.2.2"
version = "0.2.3"
[deps]
DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
@@ -15,10 +15,10 @@ 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"
@@ -27,3 +27,11 @@ JuMP = "0.21"
MathOptInterface = "0.9"
PackageCompiler = "1"
julia = "1"
[extras]
Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
Gurobi = "2e9cd046-0924-5485-92f1-d5272153d98b"
[targets]
test = ["Cbc", "Test", "Gurobi"]

View File

@@ -48,7 +48,7 @@ include("solution/warmstart.jl")
include("solution/write.jl")
include("transform/initcond.jl")
include("transform/slice.jl")
include("transform/randomize/XavQiuAhm2021.jl")
include("transform/randomize.jl")
include("utils/log.jl")
include("validation/repair.jl")
include("validation/validate.jl")

View File

@@ -266,20 +266,15 @@ function _from_json(json; repair = true)
end
instance = UnitCommitmentInstance(
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,
T,
power_balance_penalty,
shortfall_penalty,
units,
buses,
lines,
reserves,
contingencies,
loads,
)
if repair
UnitCommitment.repair!(instance)

View File

@@ -69,21 +69,17 @@ mutable struct PriceSensitiveLoad
revenue::Vector{Float64}
end
Base.@kwdef mutable struct UnitCommitmentInstance
buses_by_name::Dict{AbstractString,Bus}
buses::Vector{Bus}
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}
mutable struct UnitCommitmentInstance
time::Int
units_by_name::Dict{AbstractString,Unit}
power_balance_penalty::Vector{Float64}
"Penalty for failing to meet reserve requirement."
shortfall_penalty::Vector{Float64}
units::Vector{Unit}
buses::Vector{Bus}
lines::Vector{TransmissionLine}
reserves::Reserves
contingencies::Vector{Contingency}
price_sensitive_loads::Vector{PriceSensitiveLoad}
end
function Base.show(io::IO, instance::UnitCommitmentInstance)

View File

@@ -0,0 +1,53 @@
# 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!

View File

@@ -1,209 +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.
"""
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!

View File

@@ -3,31 +3,26 @@
# Released under the modified BSD license. See COPYING.md for more details.
using PackageCompiler
using TOML
using Logging
Logging.disable_logging(Logging.Info)
mkpath("build")
using DataStructures
using Distributions
using JSON
using JuMP
using MathOptInterface
using SparseArrays
println("Generating precompilation statements...")
run(`julia --project=. --trace-compile=build/precompile.jl $(ARGS)`)
pkg = [
:DataStructures,
:Distributions,
:JSON,
:JuMP,
:MathOptInterface,
:SparseArrays,
]
println("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("Building system image...")
@info "Building system image..."
create_sysimage(
deps,
pkg,
precompile_statements_file = "build/precompile.jl",
sysimage_path = "build/sysimage.so",
)

View File

@@ -1,26 +0,0 @@
[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"

View File

@@ -4,12 +4,9 @@
using UnitCommitment
basedir = @__DIR__
@testset "read_egret_solution" begin
solution = UnitCommitment.read_egret_solution(
"$basedir/../fixtures/egret_output.json.gz",
)
solution =
UnitCommitment.read_egret_solution("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])

View File

@@ -22,7 +22,6 @@ 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"
@@ -35,7 +34,6 @@ 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"
@@ -64,7 +62,6 @@ 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"
@@ -95,15 +92,12 @@ 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

View File

@@ -5,7 +5,6 @@
using Test
using UnitCommitment
push!(Base.LOAD_PATH, @__DIR__)
UnitCommitment._setup_logger()
const ENABLE_LARGE_TESTS = ("UCJL_LARGE_TESTS" in keys(ENV))
@@ -29,9 +28,7 @@ const ENABLE_LARGE_TESTS = ("UCJL_LARGE_TESTS" in keys(ENV))
@testset "transform" begin
include("transform/initcond_test.jl")
include("transform/slice_test.jl")
@testset "randomize" begin
include("transform/randomize/XavQiuAhm2021_test.jl")
end
include("transform/randomize_test.jl")
end
@testset "validation" begin
include("validation/repair_test.jl")

View File

@@ -4,12 +4,9 @@
using UnitCommitment, Cbc, JuMP
basedir = @__DIR__
@testset "generate_initial_conditions!" begin
# Load instance
instance =
UnitCommitment.read("$basedir/../fixtures/case118-initcond.json.gz")
instance = UnitCommitment.read("$(pwd())/fixtures/case118-initcond.json.gz")
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
# All units should have unknown initial conditions

View File

@@ -1,63 +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.
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

View File

@@ -0,0 +1,43 @@
# 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

View File

@@ -4,11 +4,9 @@
using UnitCommitment, JSON, GZip, DataStructures
basedir = @__DIR__
function parse_case14()
return JSON.parse(
GZip.gzopen("$basedir/../../instances/test/case14.json.gz"),
GZip.gzopen("../instances/test/case14.json.gz"),
dicttype = () -> DefaultOrderedDict(nothing),
)
end