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3 Commits

20 changed files with 378 additions and 360 deletions

1
.gitignore vendored
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@@ -18,3 +18,4 @@ TODO.md
docs/_build
.vscode
Manifest.toml
*/Manifest.toml

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@@ -5,23 +5,20 @@
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
build/sysimage.so: src/utils/sysimage.jl Project.toml
julia --project=. -e "using Pkg; Pkg.instantiate()"
julia --project=test -e "using Pkg; Pkg.instantiate()"
$(JULIA) src/utils/sysimage.jl test/runtests.jl
clean:
rm -rf build/*
rm -rfv build
docs:
cd docs; make clean; make dirhtml
rsync -avP --delete-after docs/_build/dirhtml/ ../docs/$(VERSION)/
test: build/sysimage.so
@echo Running tests...
$(JULIA) --sysimage build/sysimage.so -e 'using Pkg; Pkg.test("UnitCommitment")' | tee build/test.log
$(JULIA) --sysimage build/sysimage.so test/runtests.jl
format:
julia -e 'using JuliaFormatter; format(["src", "test", "benchmark"], verbose=true);'

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@@ -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"
@@ -27,11 +27,3 @@ 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"]

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@@ -48,7 +48,7 @@ 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("validation/repair.jl")
include("validation/validate.jl")

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@@ -266,15 +266,20 @@ function _from_json(json; repair = true)
end
instance = UnitCommitmentInstance(
T,
power_balance_penalty,
shortfall_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)

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@@ -69,17 +69,21 @@ mutable struct PriceSensitiveLoad
revenue::Vector{Float64}
end
mutable struct UnitCommitmentInstance
time::Int
power_balance_penalty::Vector{Float64}
"Penalty for failing to meet reserve requirement."
shortfall_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)

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@@ -1,96 +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.
"""
_add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::Nothing
Startup and shutdown limits from Gentile et al. (2017).
Eqns. (20), (23a), and (23b) in Knueven et al. (2020).
Creates constraints `eq_startstop_limit`, `eq_startup_limit`, and `eq_shutdown_limit`
using variables `Gar1962.StatusVars`, `prod_above` from `Gar1962.ProdVars`, and `reserve`.
Constraints
---
* `eq_startstop_limit`
* `eq_startup_limit`
* `eq_shutdown_limit`
"""
function _add_startup_shutdown_limit_eqs!(
model::JuMP.Model,
g::Unit,
formulation_prod_vars::Gar1962.ProdVars,
formulation_status_vars::Gar1962.StatusVars,
)::Nothing
# TODO: Move upper case constants to model[:instance]
RESERVES_WHEN_START_UP = true
RESERVES_WHEN_RAMP_UP = true
RESERVES_WHEN_RAMP_DOWN = true
RESERVES_WHEN_SHUT_DOWN = true
eq_startstop_limit = _init(model, :eq_startstop_limit)
eq_shutdown_limit = _init(model, :eq_shutdown_limit)
eq_startup_limit = _init(model, :eq_startup_limit)
is_on = model[:is_on]
prod_above = model[:prod_above]
reserve = model[:reserve]
switch_off = model[:switch_off]
switch_on = model[:switch_on]
T = model[:instance].time
gi = g.name
if g.initial_power > g.shutdown_limit
eqs.shutdown_limit[gi, 0] =
@constraint(mip, vars.switch_off[gi, 1] <= 0)
end
for t in 1:T
## 2020-10-09 amk: added eqn (20) and check of g.min_uptime
# Not present in (23) in Kneueven et al.
if g.min_uptime > 1
# Equation (20) in Knueven et al. (2020)
eqs.startstop_limit[gi, t] = @constraint(
model,
prod_above[gi, t] + reserve[gi, t] <=
(g.max_power[t] - g.min_power[t]) * is_on[gi, t] -
max(0, g.max_power[t] - g.startup_limit) * switch_on[gi, t] - (
t < T ?
max(0, g.max_power[t] - g.shutdown_limit) *
switch_off[gi, t+1] : 0.0
)
)
else
## Startup limits
# Equation (23a) in Knueven et al. (2020)
eqs.startup_limit[gi, t] = @constraint(
model,
prod_above[gi, t] + reserve[gi, t] <=
(g.max_power[t] - g.min_power[t]) * is_on[gi, t] -
max(0, g.max_power[t] - g.startup_limit) * switch_on[gi, t] - (
t < T ?
max(0, g.startup_limit - g.shutdown_limit) *
switch_off[gi, t+1] : 0.0
)
)
## Shutdown limits
if t < T
# Equation (23b) in Knueven et al. (2020)
eqs.shutdown_limit[gi, t] = @constraint(
model,
prod_above[gi, t] + reserve[gi, t] <=
(g.max_power[t] - g.min_power[t]) * xis_on[gi, t] - (
t < T ?
max(0, g.max_power[t] - g.shutdown_limit) *
switch_off[gi, t+1] : 0.0
) -
max(0, g.shutdown_limit - g.startup_limit) *
switch_on[gi, t]
)
end
end
end
end

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@@ -1,89 +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.
"""
_add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::Nothing
Startup and shutdown limits from Morales-España et al. (2013a).
Eqns. (20), (21a), and (21b) in Knueven et al. (2020).
Uses variable `prod_above` from `Gar1962.ProdVars`, the variables in `Gar1962.StatusVars`, and `reserve`
to generate constraints below.
Constraints
---
* :eq_startstop_limit
* :eq_startup_limit
* :eq_shutdown_limit
"""
function _add_startup_shutdown_limit_eqs!(
model::JuMP.Model,
g::Unit,
formulation_prod_vars::Gar1962.ProdVars,
formulation_status_vars::Gar1962.StatusVars,
)::Nothing
# TODO: Move upper case constants to model[:instance]
RESERVES_WHEN_START_UP = true
RESERVES_WHEN_RAMP_UP = true
RESERVES_WHEN_RAMP_DOWN = true
RESERVES_WHEN_SHUT_DOWN = true
eq_startstop_limit = _init(model, :eq_startstop_limit)
eq_shutdown_limit = _init(model, :eq_shutdown_limit)
eq_startup_limit = _init(model, :eq_startup_limit)
is_on = model[:is_on]
prod_above = model[:prod_above]
reserve = model[:reserve]
switch_off = model[:switch_off]
switch_on = model[:switch_on]
T = model[:instance].time
gi = g.name
for t in 1:T
## 2020-10-09 amk: added eqn (20) and check of g.min_uptime
if g.min_uptime > 1 && t < T
# Equation (20) in Knueven et al. (2020)
# UT > 1 required, to guarantee that vars.switch_on[gi, t] and vars.switch_off[gi, t+1] are not both = 1 at the same time
eq_startstop_limit[gi, t] = @constraint(
model,
prod_above[gi, t] + reserve[gi, t] <=
(g.max_power[t] - g.min_power[t]) * is_on[gi, t] -
max(0, g.max_power[t] - g.startup_limit) * switch_on[gi, t] -
max(0, g.max_power[t] - g.shutdown_limit) * switch_off[gi, t+1]
)
else
## Startup limits
# Equation (21a) in Knueven et al. (2020)
# Proposed by Morales-España et al. (2013a)
eqs_startup_limit[gi, t] = @constraint(
model,
prod_above[gi, t] + reserve[gi, t] <=
(g.max_power[t] - g.min_power[t]) * is_on[gi, t] -
max(0, g.max_power[t] - g.startup_limit) * switch_on[gi, t]
)
## Shutdown limits
if t < T
# Equation (21b) in Knueven et al. (2020)
# TODO different from what was in previous model, due to reserve variable
# ax: ideally should have reserve_up and reserve_down variables
# i.e., the generator should be able to increase/decrease production as specified
# (this is a heuristic for a "robust" solution,
# in case there is an outage or a surge, and flow has to be redirected)
# amk: if shutdown_limit is the max prod of generator in time period before shutting down,
# then it makes sense to count reserves, because otherwise, if reserves ≠ 0,
# then the generator will actually produce more than the limit
eqs.shutdown_limit[gi, t] = @constraint(
model,
prod_above[gi, t] +
(RESERVES_WHEN_SHUT_DOWN ? reserve[gi, t] : 0.0) <=
(g.max_power[t] - g.min_power[t]) * is_on[gi, t] -
max(0, g.max_power[t] - g.shutdown_limit) *
switch_off[gi, t+1]
)
end
end
end
end

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@@ -35,12 +35,7 @@ function _add_unit!(model::JuMP.Model, g::Unit, formulation::Formulation)
formulation.status_vars,
)
_add_startup_cost_eqs!(model, g, formulation.startup_costs)
_add_startup_shutdown_limit_eqs!(
model,
g,
formulation.prod_vars,
formulation.status_vars,
)
_add_startup_shutdown_limit_eqs!(model, g)
_add_status_eqs!(model, g, formulation.status_vars)
return
end
@@ -81,22 +76,7 @@ function _add_startup_shutdown_vars!(model::JuMP.Model, g::Unit)::Nothing
return
end
"""
_add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::Nothing
Creates startup/shutdown limit constraints below based on variables `Gar1962.StatusVars`, `prod_above` from `Gar1962.ProdVars`, and `reserve`.
Constraints
---
* :eq_startup_limit
* :eq_shutdown_limit
"""
function _add_startup_shutdown_limit_eqs!(
model::JuMP.Model,
g::Unit,
formulation_prod_vars::Gar1962.ProdVars,
formulation_status_vars::Gar1962.StatusVars,
)::Nothing
function _add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::Nothing
eq_shutdown_limit = _init(model, :eq_shutdown_limit)
eq_startup_limit = _init(model, :eq_startup_limit)
is_on = model[:is_on]

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@@ -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!

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@@ -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!

View File

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

26
test/Project.toml Normal file
View 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"

View File

@@ -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])

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@@ -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

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@@ -5,6 +5,7 @@
using Test
using UnitCommitment
push!(Base.LOAD_PATH, @__DIR__)
UnitCommitment._setup_logger()
const ENABLE_LARGE_TESTS = ("UCJL_LARGE_TESTS" in keys(ENV))
@@ -28,7 +29,9 @@ const ENABLE_LARGE_TESTS = ("UCJL_LARGE_TESTS" in keys(ENV))
@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")

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@@ -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

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@@ -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

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@@ -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

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@@ -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