Ran JuliaFormatter

.gitignore

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

Makefile

@@ -2,22 +2,31 @@
 # 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 -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
+	@echo Running tests...
+	$(JULIA) --sysimage build/sysimage.so -e 'using Pkg; Pkg.test("UnitCommitment")' | tee build/test.log
+
+
 format:
-	cd deps/formatter; ../../juliaw format.jl
+	julia -e 'using JuliaFormatter; format(["src", "test", "benchmark"], verbose=true);'
 
-test: test/Manifest.toml
+install-deps:
-	./juliaw test/runtests.jl
+	julia -e 'using Pkg; Pkg.add(PackageSpec(name="JuliaFormatter", version="0.14.4"))'
-
-test/Manifest.toml: test/Project.toml
-	julia --project=test -e "using Pkg; Pkg.instantiate()"
 
 .PHONY: docs test format install-deps

Project.toml

@@ -6,7 +6,6 @@ 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"
@@ -16,10 +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"
@@ -28,3 +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"]

benchmark/Project.toml

@@ -1,5 +1,4 @@
 [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"

benchmark/benchmark.jl

@@ -0,0 +1,158 @@
+# 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

benchmark/run.jl

@@ -1,207 +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.
-
-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,
-)

deps/formatter/Project.toml

@@ -1,5 +0,0 @@
-[deps]
-JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
-
-[compat]
-JuliaFormatter = "0.14.4"

deps/formatter/format.jl

@@ -1,9 +0,0 @@
-using JuliaFormatter
-format(
-    [
-        "../../src", 
-        "../../test",
-        "../../benchmark/run.jl",
-    ],
-    verbose=true,
-)

juliaw

@@ -1,68 +0,0 @@
-#!/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

src/UnitCommitment.jl

@@ -48,9 +48,8 @@ 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("utils/benchmark.jl")
 include("validation/repair.jl")
 include("validation/validate.jl")
 

src/instance/read.jl

@@ -266,20 +266,15 @@ function _from_json(json; repair = true)
     end
 
     instance = UnitCommitmentInstance(
-        buses_by_name = Dict(b.name => b for b in buses),
+        T,
-        buses = buses,
+        power_balance_penalty,
-        contingencies_by_name = Dict(c.name => c for c in contingencies),
+        shortfall_penalty,
-        contingencies = contingencies,
+        units,
-        lines_by_name = Dict(l.name => l for l in lines),
+        buses,
-        lines = lines,
+        lines,
-        power_balance_penalty = power_balance_penalty,
+        reserves,
-        price_sensitive_loads_by_name = Dict(ps.name => ps for ps in loads),
+        contingencies,
-        price_sensitive_loads = 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)

src/instance/structs.jl

@@ -69,21 +69,17 @@ mutable struct PriceSensitiveLoad
     revenue::Vector{Float64}
 end
 
-Base.@kwdef mutable struct UnitCommitmentInstance
+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}
     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)

src/model/build.jl

@@ -21,6 +21,8 @@ Arguments
 - `optimizer`:
     the optimizer factory that should be attached to this model (e.g. Cbc.Optimizer).
     If not provided, no optimizer will be attached.
+- `formulation`:
+    the details of which constraints, variables, etc. to use
 - `variable_names`: 
     If true, set variable and constraint names. Important if the model is going
     to be exported to an MPS file. For large models, this can take significant

src/model/formulations/ArrCon2000/ramp.jl

@@ -2,6 +2,15 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_ramp_eqs!(model, unit, formulation_prod_vars, formulation_ramping, formulation_status_vars)::Nothing
+
+Ensure constraints on ramping are met.
+Based on Arroyo and Conejo (2000).
+Eqns. (24), (25) in Knueven et al. (2020).
+
+Adds constraints identified by `ArrCon200.Ramping` to `model` using variables `Gar1962.ProdVars` and `is_on` from `Gar1962.StatusVars`.
+"""
 function _add_ramp_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -22,7 +31,6 @@ function _add_ramp_eqs!(
     reserve = model[:reserve]
     eq_ramp_down = _init(model, :eq_ramp_down)
     eq_ramp_up = _init(model, :eq_ramp_up)
-    is_initially_on = (g.initial_status > 0)
 
     # Gar1962.ProdVars
     prod_above = model[:prod_above]
@@ -32,6 +40,8 @@ function _add_ramp_eqs!(
     switch_off = model[:switch_off]
     switch_on = model[:switch_on]
 
+    is_initially_on = _is_initially_on(g) > 0
+
     for t in 1:model[:instance].time
         # Ramp up limit
         if t == 1
@@ -56,7 +66,7 @@ function _add_ramp_eqs!(
             min_prod_last_period =
                 g.min_power[t-1] * is_on[gn, t-1] + prod_above[gn, t-1]
 
-            # Equation (24) in Kneuven et al. (2020)
+            # Equation (24) in Knueven et al. (2020)
             eq_ramp_up[gn, t] = @constraint(
                 model,
                 max_prod_this_period - min_prod_last_period <=
@@ -87,7 +97,7 @@ function _add_ramp_eqs!(
             min_prod_this_period =
                 g.min_power[t] * is_on[gn, t] + prod_above[gn, t]
 
-            # Equation (25) in Kneuven et al. (2020)
+            # Equation (25) in Knueven et al. (2020)
             eq_ramp_down[gn, t] = @constraint(
                 model,
                 max_prod_last_period - min_prod_this_period <=

src/model/formulations/ArrCon2000/structs.jl

@@ -13,6 +13,12 @@ module ArrCon2000
 
 import ..RampingFormulation
 
+"""
+Constraints
+---
+* `eq_ramp_up`: Equation (24) in Knueven et al. (2020)
+* `eq_ramp_down`: Equation (25) in Knueven et al. (2020)
+"""
 struct Ramping <: RampingFormulation end
 
 end

src/model/formulations/CarArr2006/pwlcosts.jl

@@ -2,6 +2,12 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_production_piecewise_linear_eqs!
+
+Ensure respect of production limits along each segment.
+Creates constraints `CarArr2006.PwlCosts` using variables `Gar1962.StatusVars`
+"""
 function _add_production_piecewise_linear_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -21,7 +27,7 @@ function _add_production_piecewise_linear_eqs!(
     for t in 1:model[:instance].time
         gn = g.name
         for k in 1:K
-            # Equation (45) in Kneuven et al. (2020)
+            # Equation (45) in Knueven et al. (2020)
             # NB: when reading instance, UnitCommitment.jl already calculates
             #     difference between max power for segments k and k-1 so the
             #     value of cost_segments[k].mw[t] is the max production *for
@@ -36,14 +42,14 @@ function _add_production_piecewise_linear_eqs!(
             set_upper_bound(segprod[gn, t, k], g.cost_segments[k].mw[t])
 
             # Definition of production
-            # Equation (43) in Kneuven et al. (2020)
+            # Equation (43) in Knueven et al. (2020)
             eq_prod_above_def[gn, t] = @constraint(
                 model,
                 prod_above[gn, t] == sum(segprod[gn, t, k] for k in 1:K)
             )
 
             # Objective function
-            # Equation (44) in Kneuven et al. (2020)
+            # Equation (44) in Knueven et al. (2020)
             add_to_expression!(
                 model[:obj],
                 segprod[gn, t, k],

src/model/formulations/CarArr2006/structs.jl

@@ -14,6 +14,16 @@ module CarArr2006
 
 import ..PiecewiseLinearCostsFormulation
 
+"""
+Based on Garver (1962) and Carrión and Arryo (2006),
+which replaces (42) in Knueven et al. (2020) with a weaker version missing the on/off variable.
+Equations (45), (43), (44) in Knueven et al. (2020).
+
+Constraints
+---
+* `eq_prod_above_def`: Equation (43) in Knueven et al. (2020)
+* `eq_segprod_limit`: Equation (45) in Knueven et al. (2020)
+"""
 struct PwlCosts <: PiecewiseLinearCostsFormulation end
 
 end

src/model/formulations/DamKucRajAta2016/ramp.jl

@@ -2,6 +2,26 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_ramp_eqs!
+
+Ensure constraints on ramping are met.
+Based on Damcı-Kurt et al. (2016).
+Eqns. (35), (36) in Knueven et al. (2020).
+
+Variables
+---
+* :prod_above
+* :reserve
+* :is_on
+* :switch_on
+* :switch_off],
+
+Constraints
+---
+* :eq_str_ramp_up
+* :eq_str_ramp_down
+"""
 function _add_ramp_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -14,12 +34,14 @@ function _add_ramp_eqs!(
     RESERVES_WHEN_RAMP_UP = true
     RESERVES_WHEN_RAMP_DOWN = true
     RESERVES_WHEN_SHUT_DOWN = true
-    known_initial_conditions = true
+    is_initially_on = _is_initially_on(g)
-    is_initially_on = (g.initial_status > 0)
+
-    SU = g.startup_limit
+    # The following are the same for generator g across all time periods
-    SD = g.shutdown_limit
+    SU = g.startup_limit   # startup rate
-    RU = g.ramp_up_limit
+    SD = g.shutdown_limit  # shutdown rate
-    RD = g.ramp_down_limit
+    RU = g.ramp_up_limit   # ramp up rate
+    RD = g.ramp_down_limit # ramp down rate
+
     gn = g.name
     eq_str_ramp_down = _init(model, :eq_str_ramp_down)
     eq_str_ramp_up = _init(model, :eq_str_ramp_up)
@@ -56,7 +78,7 @@ function _add_ramp_eqs!(
         if t > 1 && time_invariant
             min_prod_last_period = prod_above[gn, t-1]
 
-            # Equation (35) in Kneuven et al. (2020)
+            # Equation (35) in Knueven et al. (2020)
             # Sparser version of (24)
             eq_str_ramp_up[gn, t] = @constraint(
                 model,
@@ -76,7 +98,7 @@ function _add_ramp_eqs!(
             # (instead of using the amount above minimum, as min prod for t < 1 is unknown)
             max_prod_this_period += g.min_power[t] * is_on[gn, t]
 
-            # Modified version of equation (35) in Kneuven et al. (2020)
+            # Modified version of equation (35) in Knueven et al. (2020)
             # Equivalent to (24)
             eq_str_ramp_up[gn, t] = @constraint(
                 model,
@@ -94,12 +116,12 @@ function _add_ramp_eqs!(
         on_last_period = 0.0
         if t > 1
             on_last_period = is_on[gn, t-1]
-        elseif (known_initial_conditions && g.initial_status > 0)
+        elseif is_initially_on
             on_last_period = 1.0
         end
 
         if t > 1 && time_invariant
-            # Equation (36) in Kneuven et al. (2020)
+            # Equation (36) in Knueven et al. (2020)
             eq_str_ramp_down[gn, t] = @constraint(
                 model,
                 max_prod_last_period - min_prod_this_period <=
@@ -110,7 +132,7 @@ function _add_ramp_eqs!(
             # Add back in min power
             min_prod_this_period += g.min_power[t] * is_on[gn, t]
 
-            # Modified version of equation (36) in Kneuven et al. (2020)
+            # Modified version of equation (36) in Knueven et al. (2020)
             # Equivalent to (25)
             eq_str_ramp_down[gn, t] = @constraint(
                 model,

src/model/formulations/Gar1962/prod.jl

@@ -2,6 +2,11 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_production_vars!(model, unit, formulation_prod_vars)
+
+Adds symbols identified by `Gar1962.ProdVars` to `model`.
+"""
 function _add_production_vars!(
     model::JuMP.Model,
     g::Unit,
@@ -18,6 +23,23 @@ function _add_production_vars!(
     return
 end
 
+"""
+    _add_production_limit_eqs!(model, unit, formulation_prod_vars)
+
+Ensure production limit constraints are met.
+Based on Garver (1962) and Morales-España et al. (2013).
+Eqns. (18), part of (69) in Knueven et al. (2020).
+
+===
+Variables
+* :is_on
+* :prod_above
+* :reserve
+
+===
+Constraints
+* :eq_prod_limit
+"""
 function _add_production_limit_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -30,13 +52,13 @@ function _add_production_limit_eqs!(
     gn = g.name
     for t in 1:model[:instance].time
         # Objective function terms for production costs
-        # Part of (69) of Kneuven et al. (2020) as C^R_g * u_g(t) term
+        # Part of (69) of Knueven et al. (2020) as C^R_g * u_g(t) term
         add_to_expression!(model[:obj], is_on[gn, t], g.min_power_cost[t])
 
         # Production limit
-        # Equation (18) in Kneuven et al. (2020)
+        # Equation (18) in Knueven et al. (2020)
         #   as \bar{p}_g(t) \le \bar{P}_g u_g(t)
-        # amk: this is a weaker version of (20) and (21) in Kneuven et al. (2020)
+        # amk: this is a weaker version of (20) and (21) in Knueven et al. (2020)
         #      but keeping it here in case those are not present
         power_diff = max(g.max_power[t], 0.0) - max(g.min_power[t], 0.0)
         if power_diff < 1e-7

src/model/formulations/Gar1962/pwlcosts.jl

@@ -2,6 +2,28 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_production_piecewise_linear_eqs!
+
+Ensure respect of production limits along each segment.
+Based on Garver (1962).
+Equations (42), (43), (44) in Knueven et al. (2020).
+NB: when reading instance, UnitCommitment.jl already calculates difference between max power for segments k and k-1,
+so the value of cost_segments[k].mw[t] is the max production *for that segment*.
+
+Added to `model`: `:eq_prod_above_def` and `:eq_segprod_limit`.
+
+===
+Variables
+* :segprod
+* :is_on
+* :prod_above
+
+===
+Constraints
+* :eq_prod_above_def
+* :eq_segprod_limit
+"""
 function _add_production_piecewise_linear_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -23,14 +45,14 @@ function _add_production_piecewise_linear_eqs!(
     K = length(g.cost_segments)
     for t in 1:model[:instance].time
         # Definition of production
-        # Equation (43) in Kneuven et al. (2020)
+        # Equation (43) in Knueven et al. (2020)
         eq_prod_above_def[gn, t] = @constraint(
             model,
             prod_above[gn, t] == sum(segprod[gn, t, k] for k in 1:K)
         )
 
         for k in 1:K
-            # Equation (42) in Kneuven et al. (2020)
+            # Equation (42) in Knueven et al. (2020)
             # Without this, solvers will add a lot of implied bound cuts to
             # have this same effect.
             # NB: when reading instance, UnitCommitment.jl already calculates
@@ -47,7 +69,7 @@ function _add_production_piecewise_linear_eqs!(
             set_upper_bound(segprod[gn, t, k], g.cost_segments[k].mw[t])
 
             # Objective function
-            # Equation (44) in Kneuven et al. (2020)
+            # Equation (44) in Knueven et al. (2020)
             add_to_expression!(
                 model[:obj],
                 segprod[gn, t, k],

src/model/formulations/Gar1962/status.jl

@@ -2,6 +2,12 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_status_vars!
+
+Adds symbols identified by `Gar1962.StatusVars` to `model`.
+Fix variables if a certain generator _must_ run or based on initial conditions.
+"""
 function _add_status_vars!(
     model::JuMP.Model,
     g::Unit,
@@ -10,20 +16,108 @@ function _add_status_vars!(
     is_on = _init(model, :is_on)
     switch_on = _init(model, :switch_on)
     switch_off = _init(model, :switch_off)
+    FIX_VARS = !formulation_status_vars.fix_vars_via_constraint
+    is_initially_on = _is_initially_on(g) > 0
     for t in 1:model[:instance].time
-        if g.must_run[t]
-            is_on[g.name, t] = 1.0
-            switch_on[g.name, t] = (t == 1 ? 1.0 - _is_initially_on(g) : 0.0)
-            switch_off[g.name, t] = 0.0
-        else
         is_on[g.name, t] = @variable(model, binary = true)
         switch_on[g.name, t] = @variable(model, binary = true)
         switch_off[g.name, t] = @variable(model, binary = true)
+
+        # Use initial conditions and whether a unit must run to fix variables
+        if FIX_VARS
+            # Fix variables using fix function
+            if g.must_run[t]
+                # If the generator _must_ run, then it is obviously on and cannot be switched off
+                # In the first time period, force unit to switch on if was off before
+                # Otherwise, unit is on, and will never turn off, so will never need to turn on
+                fix(is_on[g.name, t], 1.0; force = true)
+                fix(
+                    switch_on[g.name, t],
+                    (t == 1 ? 1.0 - _is_initially_on(g) : 0.0);
+                    force = true,
+                )
+                fix(switch_off[g.name, t], 0.0; force = true)
+            elseif t == 1
+                if is_initially_on
+                    # Generator was on (for g.initial_status time periods),
+                    # so cannot be more switched on until the period after the first time it can be turned off
+                    fix(switch_on[g.name, 1], 0.0; force = true)
+                else
+                    # Generator is initially off (for -g.initial_status time periods)
+                    # Cannot be switched off more
+                    fix(switch_off[g.name, 1], 0.0; force = true)
+                end
+            end
+        else
+            # Add explicit constraint if !FIX_VARS
+            if g.must_run[t]
+                is_on[g.name, t] = 1.0
+                switch_on[g.name, t] =
+                    (t == 1 ? 1.0 - _is_initially_on(g) : 0.0)
+                switch_off[g.name, t] = 0.0
+            elseif t == 1
+                if is_initially_on
+                    switch_on[g.name, t] = 0.0
+                else
+                    switch_off[g.name, t] = 0.0
+                end
+            end
+        end
+
+        # Use initial conditions and whether a unit must run to fix variables
+        if FIX_VARS
+            # Fix variables using fix function
+            if g.must_run[t]
+                # If the generator _must_ run, then it is obviously on and cannot be switched off
+                # In the first time period, force unit to switch on if was off before
+                # Otherwise, unit is on, and will never turn off, so will never need to turn on
+                fix(is_on[g.name, t], 1.0; force = true)
+                fix(
+                    switch_on[g.name, t],
+                    (t == 1 ? 1.0 - _is_initially_on(g) : 0.0);
+                    force = true,
+                )
+                fix(switch_off[g.name, t], 0.0; force = true)
+            elseif t == 1
+                if is_initially_on
+                    # Generator was on (for g.initial_status time periods),
+                    # so cannot be more switched on until the period after the first time it can be turned off
+                    fix(switch_on[g.name, 1], 0.0; force = true)
+                else
+                    # Generator is initially off (for -g.initial_status time periods)
+                    # Cannot be switched off more
+                    fix(switch_off[g.name, 1], 0.0; force = true)
+                end
+            end
+        else
+            # Add explicit constraint if !FIX_VARS
+            if g.must_run[t]
+                is_on[g.name, t] = 1.0
+                switch_on[g.name, t] =
+                    (t == 1 ? 1.0 - _is_initially_on(g) : 0.0)
+                switch_off[g.name, t] = 0.0
+            elseif t == 1
+                if is_initially_on
+                    switch_on[g.name, t] = 0.0
+                else
+                    switch_off[g.name, t] = 0.0
+                end
+            end
         end
     end
     return
 end
 
+"""
+    _add_status_eqs!
+
+Creates constraints `eq_binary_link` and `eq_switch_on_off` using variables in `Gar1962.StatusVars`.
+
+Constraints
+---
+* `eq_binary_link`
+* `eq_switch_on_off`
+"""
 function _add_status_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -35,8 +129,12 @@ function _add_status_eqs!(
     switch_off = model[:switch_off]
     switch_on = model[:switch_on]
     for t in 1:model[:instance].time
-        if !g.must_run[t]
+        if g.must_run[t]
+            continue
+        end
+
         # Link binary variables
+        # Equation (2) in Knueven et al. (2020), originally from Garver (1962)
         if t == 1
             eq_binary_link[g.name, t] = @constraint(
                 model,
@@ -50,12 +148,13 @@ function _add_status_eqs!(
                 switch_on[g.name, t] - switch_off[g.name, t]
             )
         end
+
         # Cannot switch on and off at the same time
+        # amk: I am not sure this is in Knueven et al. (2020)
         eq_switch_on_off[g.name, t] = @constraint(
             model,
             switch_on[g.name, t] + switch_off[g.name, t] <= 1
         )
     end
-    end
     return
 end

src/model/formulations/Gar1962/structs.jl

@@ -17,8 +17,53 @@ import ..PiecewiseLinearCostsFormulation
 import ..ProductionVarsFormulation
 import ..StatusVarsFormulation
 
+"""
+Variables
+---
+* `prod_above`:
+        [gen, t];
+        *production above minimum required level*;
+        lb: 0, ub: Inf.
+        KnuOstWat2020: `p'_g(t)`
+* `segprod`:
+        [gen, segment, t];
+        *how much generator produces on cost segment in time t*;
+        lb: 0, ub: Inf.
+        KnuOstWat2020: `p_g^l(t)`
+"""
 struct ProdVars <: ProductionVarsFormulation end
+
 struct PwlCosts <: PiecewiseLinearCostsFormulation end
-struct StatusVars <: StatusVarsFormulation end
+
+"""
+Variables
+---
+* `is_on`:
+        [gen, t];
+        *is generator on at time t?*
+        lb: 0, ub: 1, binary.
+        KnuOstWat2020: `u_g(t)`
+* `switch_on`:
+        [gen, t];
+        *indicator that generator will be turned on at t*;
+        lb: 0, ub: 1, binary.
+        KnuOstWat2020: `v_g(t)`
+* `switch_off`: binary;
+        [gen, t];
+        *indicator that generator will be turned off at t*;
+        lb: 0, ub: 1, binary.
+        KnuOstWat2020: `w_g(t)`
+
+Arguments
+---
+* `fix_vars_via_constraint`:
+        indicator for whether to set vars to a constant using `fix` or by adding an explicit constraint
+        (particulary useful for debugging purposes).
+"""
+struct StatusVars <: StatusVarsFormulation
+    fix_vars_via_constraint::Bool
+
+    StatusVars() = new(false)
+end
 
 end

src/model/formulations/GenMorRam2017/startstop.jl

@@ -0,0 +1,100 @@
+# 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_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)
+        if formulation_status_vars.always_create_vars
+            fix(switch_off[gi, 1], 0.0; force = true)
+            @constraint(mip, vars.switch_off[gi, 1] <= 0)
+        else
+            switch_off[gi, 1] = 0.0
+        end
+    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

src/model/formulations/KnuOstWat2018/pwlcosts.jl

@@ -2,6 +2,30 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_production_piecewise_linear_eqs!
+
+Ensure respect of production limits along each segment.
+Based on Knueven et al. (2018b).
+Eqns. (43), (44), (46), (48) in Knueven et al. (2020).
+NB: when reading instance, UnitCommitment.jl already calculates difference between max power for segments k and k-1
+so the value of cost_segments[k].mw[t] is the max production *for that segment*.
+
+===
+Variables
+* :segprod
+* :is_on
+* :switch_on
+* :switch_off
+* :prod_above
+
+===
+Constraints
+* :eq_prod_above_def
+* :eq_segprod_limit_a
+* :eq_segprod_limit_b
+* :eq_segprod_limit_c
+"""
 function _add_production_piecewise_linear_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -57,7 +81,7 @@ function _add_production_piecewise_linear_eqs!(
             end
 
             if g.min_uptime > 1
-                # Equation (46) in Kneuven et al. (2020)
+                # Equation (46) in Knueven et al. (2020)
                 eq_segprod_limit_a[gn, t, k] = @constraint(
                     model,
                     segprod[gn, t, k] <=
@@ -66,7 +90,7 @@ function _add_production_piecewise_linear_eqs!(
                     (t < T ? Cw * switch_off[gn, t+1] : 0.0)
                 )
             else
-                # Equation (47a)/(48a) in Kneuven et al. (2020)
+                # Equation (47a)/(48a) in Knueven et al. (2020)
                 eq_segprod_limit_b[gn, t, k] = @constraint(
                     model,
                     segprod[gn, t, k] <=
@@ -75,7 +99,7 @@ function _add_production_piecewise_linear_eqs!(
                     (t < T ? max(0, Cv - Cw) * switch_off[gn, t+1] : 0.0)
                 )
 
-                # Equation (47b)/(48b) in Kneuven et al. (2020)
+                # Equation (47b)/(48b) in Knueven et al. (2020)
                 eq_segprod_limit_c[gn, t, k] = @constraint(
                     model,
                     segprod[gn, t, k] <=
@@ -86,14 +110,14 @@ function _add_production_piecewise_linear_eqs!(
             end
 
             # Definition of production
-            # Equation (43) in Kneuven et al. (2020)
+            # Equation (43) in Knueven et al. (2020)
             eq_prod_above_def[gn, t] = @constraint(
                 model,
                 prod_above[gn, t] == sum(segprod[gn, t, k] for k in 1:K)
             )
 
             # Objective function
-            # Equation (44) in Kneuven et al. (2020)
+            # Equation (44) in Knueven et al. (2020)
             add_to_expression!(
                 model[:obj],
                 segprod[gn, t, k],

src/model/formulations/KnuOstWat2018/scosts.jl

@@ -0,0 +1,123 @@
+# 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_cost_eqs!
+
+Extended formulation of startup costs using indicator variables
+based on Knueven, Ostrowski, and Watson, 2020
+--- equations (59), (60), (61).
+
+Variables
+---
+* switch_on
+* switch_off
+* downtime_arc
+
+Constraints
+---
+* eq_startup_at_t
+* eq_shutdown_at_t
+"""
+function _add_startup_cost_eqs!(
+    model::JuMP.Model,
+    g::Unit,
+    formulation::MorLatRam2013.StartupCosts,
+)::Nothing
+    S = length(g.startup_categories)
+    if S == 0
+        return
+    end
+    gn = g.name
+
+    _init(model, eq_startup_at_t)
+    _init(model, eq_shutdown_at_t)
+
+    switch_on = model[:switch_on]
+    switch_off = model[:switch_off]
+    downtime_arc = model[:downtime_arc]
+
+    DT = g.min_downtime # minimum time offline
+    TC = g.startup_categories[S].delay # time offline until totally cold
+
+    # If initial_status < 0, then this is the amount of time the generator has been off
+    initial_time_shutdown = (g.initial_status < 0 ? -g.initial_status : 0)
+
+    for t in 1:model[:instance].time
+        # Fix to zero values of downtime_arc outside the feasible time pairs
+        # Specifically, x(t,t') = 0 if t' does not belong to 𝒢 = [t+DT, t+TC-1]
+        # This is because DT is the minimum downtime, so there is no way x(t,t')=1 for t'<t+DT
+        # and TC is the "time until cold" => if the generator starts afterwards, always has max cost
+        #start_time = min(t + DT, T)
+        #end_time = min(t + TC - 1, T)
+        #for tmp_t in t+1:start_time
+        #  fix(vars.downtime_arc[gn, t, tmp_t], 0.; force = true)
+        #end
+        #for tmp_t in end_time+1:T
+        #  fix(vars.downtime_arc[gn, t, tmp_t], 0.; force = true)
+        #end
+
+        # Equation (59) in Knueven et al. (2020)
+        # Relate downtime_arc with switch_on
+        # "switch_on[g,t] >= x_g(t',t) for all t' \in [t-TC+1, t-DT]"
+        eq_startup_at_t[gn, t] = @constraint(
+            model,
+            switch_on[gn, t] >= sum(
+                downtime_arc[gn, tmp_t, t] for
+                tmp_t in t-TC+1:t-DT if tmp_t >= 1
+            )
+        )
+
+        # Equation (60) in Knueven et al. (2020)
+        # "switch_off[g,t] >= x_g(t,t') for all t' \in [t+DT, t+TC-1]"
+        eqs.shutdown_at_t[gn, t] = @constraint(
+            model,
+            switch_off[gn, t] >= sum(
+                downtime_arc[gn, t, tmp_t] for
+                tmp_t in t+DT:t+TC-1 if tmp_t <= T
+            )
+        )
+
+        # Objective function terms for start-up costs
+        # Equation (61) in Knueven et al. (2020)
+        default_category = S
+        if initial_time_shutdown > 0 && t + initial_time_shutdown - 1 < TC
+            for s in 1:S-1
+                # If off for x periods before, then belongs to category s
+                # if -x+1 in [t-delay[s+1]+1,t-delay[s]]
+                # or, equivalently, if total time off in [delay[s], delay[s+1]-1]
+                # where total time off = t - 1 + initial_time_shutdown
+                # (the -1 because not off for current time period)
+                if t + initial_time_shutdown - 1 <
+                   g.startup_categories[s+1].delay
+                    default_category = s
+                    break # does not go into next category
+                end
+            end
+        end
+        add_to_expression!(
+            model[:obj],
+            switch_on[gn, t],
+            g.startup_categories[default_category].cost,
+        )
+
+        for s in 1:S-1
+            # Objective function terms for start-up costs
+            # Equation (61) in Knueven et al. (2020)
+            # Says to replace the cost of last category with cost of category s
+            start_range = max((t - g.startup_categories[s+1].delay + 1), 1)
+            end_range = min((t - g.startup_categories[s].delay), T - 1)
+            for tmp_t in start_range:end_range
+                if (t < tmp_t + DT) || (t >= tmp_t + TC) # the second clause should never be true for s < S
+                    continue
+                end
+                add_to_expression!(
+                    model[:obj],
+                    downtime_arc[gn, tmp_t, t],
+                    g.startup_categories[s].cost - g.startup_categories[S].cost,
+                )
+            end
+        end # iterate over startup categories
+    end # iterate over time
+end # add_startup_costs_KneOstWat20

src/model/formulations/MorLatRam2013/ramp.jl

@@ -2,6 +2,27 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_ramp_eqs!
+
+Ensure constraints on ramping are met.
+Needs to be used in combination with shutdown rate constraints, e.g., (21b) in Knueven et al. (2020).
+Based on Morales-España, Latorre, and Ramos, 2013.
+Eqns. (26)+(27) [replaced by (24)+(25) if time-varying min demand] in Knueven et al. (2020).
+
+Variables
+---
+* :is_on
+* :switch_off
+* :switch_on
+* :prod_above
+* :reserve
+
+Constraints
+---
+* :eq_ramp_up
+* :eq_ramp_down
+"""
 function _add_ramp_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -15,10 +36,10 @@ function _add_ramp_eqs!(
     RESERVES_WHEN_RAMP_DOWN = true
     RESERVES_WHEN_SHUT_DOWN = true
     is_initially_on = (g.initial_status > 0)
-    SU = g.startup_limit
+    SU = g.startup_limit   # startup rate
-    SD = g.shutdown_limit
+    SD = g.shutdown_limit  # shutdown rate
-    RU = g.ramp_up_limit
+    RU = g.ramp_up_limit   # ramp up rate
-    RD = g.ramp_down_limit
+    RD = g.ramp_down_limit # ramp down rate
     gn = g.name
     eq_ramp_down = _init(model, :eq_ramp_down)
     eq_ramp_up = _init(model, :eq_str_ramp_up)
@@ -71,7 +92,7 @@ function _add_ramp_eqs!(
                     RU * is_on[gn, t-1] + SU * switch_on[gn, t]
                 )
             else
-                # Equation (26) in Kneuven et al. (2020)
+                # Equation (26) in Knueven et al. (2020)
                 # TODO: what if RU < SU? places too stringent upper bound
                 # prod_above[gn, t] when starting up, and creates diff with (24).
                 eq_ramp_up[gn, t] = @constraint(
@@ -115,7 +136,7 @@ function _add_ramp_eqs!(
                     RD * is_on[gn, t] + SD * switch_off[gn, t]
                 )
             else
-                # Equation (27) in Kneuven et al. (2020)
+                # Equation (27) in Knueven et al. (2020)
                 # TODO: Similar to above, what to do if shutting down in time t
                 # and RD < SD? There is a difference with (25).
                 eq_ramp_down[gn, t] = @constraint(

src/model/formulations/MorLatRam2013/scosts.jl

@@ -2,21 +2,56 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_startup_cost_eqs!
+
+Extended formulation of startup costs using indicator variables
+based on Muckstadt and Wilson, 1968;
+this version by Morales-España, Latorre, and Ramos, 2013.
+Eqns. (54), (55), and (56) in Knueven et al. (2020).
+Note that the last 'constraint' is actually setting the objective.
+
+\tstartup[gi,s,t] ≤ sum_{i=s.delay}^{(s+1).delay-1} switch_off[gi,t-i]
+\tswitch_on[gi,t] = sum_{s=1}^{length(startup_categories)} startup[gi,s,t]
+\tstartup_cost[gi,t] = sum_{s=1}^{length(startup_categories)} cost_segments[s].cost * startup[gi,s,t]
+
+Variables
+---
+* startup
+* switch_on
+* switch_off
+
+Constraints
+---
+* eq_startup_choose
+* eq_startup_restrict
+"""
 function _add_startup_cost_eqs!(
     model::JuMP.Model,
     g::Unit,
     formulation::MorLatRam2013.StartupCosts,
 )::Nothing
+    S = length(g.startup_categories)
+    if S == 0
+        return
+    end
+
+    # Constraints created
     eq_startup_choose = _init(model, :eq_startup_choose)
     eq_startup_restrict = _init(model, :eq_startup_restrict)
-    S = length(g.startup_categories)
+
+    # Variables needed
     startup = model[:startup]
+    switch_on = model[:switch_on]
+    switch_off = model[:switch_off]
+
+    gn = g.name
     for t in 1:model[:instance].time
         # If unit is switching on, we must choose a startup category
-        eq_startup_choose[g.name, t] = @constraint(
+        # Equation (55) in Knueven et al. (2020)
+        eq_startup_choose[gn, t] = @constraint(
             model,
-            model[:switch_on][g.name, t] ==
+            switch_on[gn, t] == sum(startup[gn, t, s] for s in 1:S)
-            sum(startup[g.name, t, s] for s in 1:S)
         )
 
         for s in 1:S
@@ -26,25 +61,28 @@ function _add_startup_cost_eqs!(
                 range_start = t - g.startup_categories[s+1].delay + 1
                 range_end = t - g.startup_categories[s].delay
                 range = (range_start:range_end)
+                # If initial_status < 0, then this is the amount of time the generator has been off
                 initial_sum = (
                     g.initial_status < 0 && (g.initial_status + 1 in range) ? 1.0 : 0.0
                 )
-                eq_startup_restrict[g.name, t, s] = @constraint(
+                # Change of index version of equation (54) in Knueven et al. (2020):
+                #   startup[gi,s,t] ≤ sum_{i=s.delay}^{(s+1).delay-1} switch_off[gi,t-i]
+                eq_startup_restrict[gn, t, s] = @constraint(
                     model,
-                    startup[g.name, t, s] <=
+                    startup[gn, t, s] <=
-                    initial_sum + sum(
+                    initial_sum +
-                        model[:switch_off][g.name, i] for i in range if i >= 1
+                    sum(switch_off[gn, i] for i in range if i >= 1)
                 )
-                )
+            end # if s < S (not the last category)
-            end
 
             # Objective function terms for start-up costs
+            # Equation (56) in Knueven et al. (2020)
             add_to_expression!(
                 model[:obj],
-                startup[g.name, t, s],
+                startup[gn, t, s],
                 g.startup_categories[s].cost,
             )
-        end
+        end # iterate over startup categories
-    end
+    end # iterate over time
     return
 end

src/model/formulations/MorLatRam2013/startstop.jl

@@ -0,0 +1,89 @@
+# 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).
+
+Variables
+---
+* :is_on
+* :prod_above
+* :reserve
+* :switch_on
+* :switch_off
+
+Constraints
+---
+* :eq_startstop_limit
+* :eq_startup_limit
+* :eq_shutdown_limit
+"""
+function _add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::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 # check if g.min_uptime > 1
+    end # loop over time
+end # _add_startup_shutdown_limit_eqs!

src/model/formulations/NowRom2000/scosts.jl

@@ -0,0 +1,20 @@
+# 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_cost_eqs!
+
+Based on Nowak and Römisch, 2000.
+Introduces auxiliary startup cost variable, c_g^SU(t) for each time period,
+and uses startup status variable, u_g(t);
+there are exponentially many facets in this space,
+but there is a linear-time separation algorithm (Brandenburg et al., 2017).
+"""
+function _add_startup_cost_eqs!(
+    model::JuMP.Model,
+    g::Unit,
+    formulation::MorLatRam2013.StartupCosts,
+)::Nothing
+    return error("Not implemented.")
+end

src/model/formulations/OstAnjVan2012/ramp.jl

@@ -0,0 +1,85 @@
+# 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_ramp_eqs!
+
+Ensure constraints on ramping are met.
+Based on Ostrowski, Anjos, Vannelli (2012).
+Eqn (37) in Knueven et al. (2020).
+
+Variables
+---
+* :is_on
+* :prod_above
+* :reserve
+
+Constraints
+---
+* :eq_str_prod_limit
+"""
+function _add_ramp_eqs!(
+    model::JuMP.Model,
+    g::Unit,
+    formulation_prod_vars::Gar1962.ProdVars,
+    formulation_ramping::MorLatRam2013.Ramping,
+    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
+    is_initially_on = _is_initially_on(g)
+
+    gn = g.name
+    eq_str_prod_limit = _init(model, :eq_str_prod_limit)
+
+    # Variables that we need
+    reserve = model[:reserve]
+
+    # Gar1962.ProdVars
+    prod_above = model[:prod_above]
+
+    # Gar1962.StatusVars
+    is_on = model[:is_on]
+    switch_off = model[:switch_off]
+
+    # The following are the same for generator g across all time periods
+    UT = g.min_uptime
+
+    SU = g.startup_limit   # startup rate
+    SD = g.shutdown_limit  # shutdown rate
+    RU = g.ramp_up_limit   # ramp up rate
+    RD = g.ramp_down_limit # ramp down rate
+
+    # TODO check initial conditions, but maybe okay as long as (35) and (36) are also used
+    for t in 1:model[:instance].time
+        Pbar = g.max_power[t]
+
+        #TRD = floor((Pbar - SU)/RD)
+        # TODO check amk changed TRD wrt Knueven et al.
+        TRD = ceil((Pbar - SD) / RD) # ramp down time
+
+        if Pbar < 1e-7
+            # Skip this time period if max power = 0
+            continue
+        end
+
+        if UT >= 1
+            # Equation (37) in Knueven et al. (2020)
+            KSD = min(TRD, UT - 1, T - t - 1)
+            eq_str_prod_limit[gn, t] = @constraint(
+                model,
+                prod_above[gn, t] +
+                g.min_power[t] * is_on[gn, t] +
+                (RESERVES_WHEN_RAMP_DOWN ? reserve[gn, t] : 0.0) <=
+                Pbar * is_on[gi, t] - sum(
+                    (Pbar - (SD + i * RD)) * switch_off[gi, t+1+i] for
+                    i in 0:KSD
+                )
+            )
+        end # check UT >= 1
+    end # loop over time
+end

src/model/formulations/PanGua2016/ramp.jl

@@ -2,6 +2,28 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_ramp_eqs!
+
+Add tighter upper bounds on production based on ramp-down trajectory.
+Based on (28) in Pan and Guan (2016).
+But there is an extra time period covered using (40) of Knueven et al. (2020).
+Eqns. (38), (40), (41) in Knueven et al. (2020).
+
+Variables
+---
+* :prod_above
+* :reserve
+* :is_on
+* :switch_on
+* :switch_off
+
+Constraints
+---
+* :str_prod_limit
+* :prod_limit_ramp_up_extra_period
+* :prod_limit_shutdown_trajectory
+"""
 function _add_ramp_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -41,14 +63,14 @@ function _add_ramp_eqs!(
         end
 
         #TRD = floor((Pbar - SU) / RD) # ramp down time
-        # TODO check amk changed TRD wrt Kneuven et al.
+        # TODO check amk changed TRD wrt Knueven et al.
         TRD = ceil((Pbar - SD) / RD)  # ramp down time
         TRU = floor((Pbar - SU) / RU) # ramp up time, can be negative if Pbar < SU
 
         # TODO check initial time periods: what if generator has been running for x periods?
         # But maybe ok as long as (35) and (36) are also used...
         if UT > 1
-            # Equation (38) in Kneuven et al. (2020)
+            # Equation (38) in Knueven et al. (2020)
             # Generalization of (20)
             # Necessary that if any of the switch_on = 1 in the sum,
             # then switch_off[gn, t+1] = 0
@@ -65,7 +87,7 @@ function _add_ramp_eqs!(
             )
 
             if UT - 2 < TRU
-                # Equation (40) in Kneuven et al. (2020)
+                # Equation (40) in Knueven et al. (2020)
                 # Covers an additional time period of the ramp-up trajectory, compared to (38)
                 eq_prod_limit_ramp_up_extra_period[gn, t] = @constraint(
                     model,
@@ -83,7 +105,7 @@ function _add_ramp_eqs!(
             KSD = min(TRD, UT - 1, T - t - 1)
             if KSD > 0
                 KSU = min(TRU, UT - 2 - KSD, t - 1)
-                # Equation (41) in Kneuven et al. (2020)
+                # Equation (41) in Knueven et al. (2020)
                 eq_prod_limit_shutdown_trajectory[gn, t] = @constraint(
                     model,
                     prod_above[gn, t] +

src/model/formulations/base/bus.jl

@@ -2,6 +2,11 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_bus!(model::JuMP.Model, b::Bus)::Nothing
+
+Creates `expr_net_injection` and adds `curtail` variable to `model`.
+"""
 function _add_bus!(model::JuMP.Model, b::Bus)::Nothing
     net_injection = _init(model, :expr_net_injection)
     curtail = _init(model, :curtail)

src/model/formulations/base/psload.jl

@@ -2,6 +2,9 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_price_sensitive_load!(model::JuMP.Model, ps::PriceSensitiveLoad)
+"""
 function _add_price_sensitive_load!(
     model::JuMP.Model,
     ps::PriceSensitiveLoad,

src/model/formulations/base/sensitivity.jl

@@ -18,7 +18,7 @@ function _injection_shift_factors(;
     lines::Array{TransmissionLine},
 )
     susceptance = _susceptance_matrix(lines)
-    incidence = _reduced_incidence_matrix(lines = lines, buses = buses)
+    incidence = _reduced_incidence_matrix(buses = buses, lines = lines)
     laplacian = transpose(incidence) * susceptance * incidence
     isf = susceptance * incidence * inv(Array(laplacian))
     return isf

src/model/formulations/base/structs.jl

@@ -9,6 +9,15 @@ abstract type StartupCostsFormulation end
 abstract type StatusVarsFormulation end
 abstract type ProductionVarsFormulation end
 
+"""
+    struct Formulation
+
+Every formulation has to specify components for setting production variables and limits,
+startup costs and piecewise-linear costs, ramping variables and constraints,
+status variables (on/off, starting up, shutting down), and transmission constraints.
+
+Some of these components are allowed to be empty, as long as overall validity of the formulation is maintained.
+"""
 struct Formulation
     prod_vars::ProductionVarsFormulation
     pwl_costs::PiecewiseLinearCostsFormulation

src/model/formulations/base/system.jl

@@ -2,12 +2,32 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_system_wide_eqs!(model::JuMP.Model)::Nothing
+
+Adds constraints that apply to the whole system, such as relating to net injection and reserves.
+"""
 function _add_system_wide_eqs!(model::JuMP.Model)::Nothing
     _add_net_injection_eqs!(model)
     _add_reserve_eqs!(model)
     return
 end
 
+"""
+    _add_net_injection_eqs!(model::JuMP.Model)::Nothing
+
+Adds `net_injection`, `eq_net_injection_def`, and `eq_power_balance` identifiers into `model`.
+
+Variables
+---
+* `expr_net_injection`
+* `net_injection`
+
+Constraints
+---
+* `eq_net_injection_def`
+* `eq_power_balance`
+"""
 function _add_net_injection_eqs!(model::JuMP.Model)::Nothing
     T = model[:instance].time
     net_injection = _init(model, :net_injection)
@@ -27,11 +47,30 @@ function _add_net_injection_eqs!(model::JuMP.Model)::Nothing
     return
 end
 
+"""
+    _add_reserve_eqs!(model::JuMP.Model)::Nothing
+
+Ensure constraints on reserves are met.
+Based on Morales-España et al. (2013a).
+Eqn. (68) from Knueven et al. (2020).
+
+Adds `eq_min_reserve` identifier to `model`, and corresponding constraint.
+
+Variables
+---
+* `reserve`
+* `reserve_shortfall`
+
+Constraints
+---
+* `eq_min_reserve`
+"""
 function _add_reserve_eqs!(model::JuMP.Model)::Nothing
+    instance = model[:instance]
     eq_min_reserve = _init(model, :eq_min_reserve)
     instance = model[:instance]
     for t in 1:instance.time
-        # Equation (68) in Kneuven et al. (2020)
+        # Equation (68) in Knueven 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)

src/model/formulations/base/unit.jl

@@ -2,6 +2,15 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
+"""
+    _add_unit!(model::JuMP.Model, g::Unit, formulation::Formulation)
+
+Add production, reserve, startup, shutdown, and status variables,
+and constraints for min uptime/downtime, net injection, production, ramping, startup, shutdown, and status.
+
+Fix variables if a certain generator _must_ run or if a generator provides spinning reserves.
+Also, add overflow penalty to objective for each transmission line.
+"""
 function _add_unit!(model::JuMP.Model, g::Unit, formulation::Formulation)
     if !all(g.must_run) && any(g.must_run)
         error("Partially must-run units are not currently supported")
@@ -35,22 +44,42 @@ 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)
+    _add_shutdown_cost_eqs!(model, g)
+    _add_startup_shutdown_limit_eqs!(
+        model,
+        g,
+        formulation.status_vars,
+        formulation.prod_vars,
+    )
     _add_status_eqs!(model, g, formulation.status_vars)
     return
 end
 
 _is_initially_on(g::Unit)::Float64 = (g.initial_status > 0 ? 1.0 : 0.0)
 
-function _add_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
+"""
+    _add_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
+
+Add `:reserve` variable to `model`, fixed to zero if no spinning reserves specified.
+"""
+function _add_reserve_vars!(
+    model::JuMP.Model,
+    g::Unit,
+    ALWAYS_CREATE_VARS = false,
+)::Nothing
     reserve = _init(model, :reserve)
-    reserve_shortfall = _init(model, :reserve_shortfall)
+    reserve_shortfall = _init(model, :reserve_shortfall) # for accounting for shortfall penalty in the objective
     for t in 1:model[:instance].time
         if g.provides_spinning_reserves[t]
             reserve[g.name, t] = @variable(model, lower_bound = 0)
+        else
+            if ALWAYS_CREATE_VARS
+                reserve[g.name, t] = @variable(model, lower_bound = 0)
+                fix(reserve[g.name, t], 0.0; force = true)
             else
                 reserve[g.name, t] = 0.0
             end
+        end
         reserve_shortfall[t] =
             (model[:instance].shortfall_penalty[t] >= 0) ?
             @variable(model, lower_bound = 0) : 0.0
@@ -58,14 +87,19 @@ function _add_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
     return
 end
 
+"""
+    _add_reserve_eqs!(model::JuMP.Model, g::Unit)::Nothing
+"""
 function _add_reserve_eqs!(model::JuMP.Model, g::Unit)::Nothing
-    reserve = model[:reserve]
+    # nothing to do here
-    for t in 1:model[:instance].time
-        add_to_expression!(expr_reserve[g.bus.name, t], reserve[g.name, t], 1.0)
-    end
     return
 end
 
+"""
+    _add_startup_shutdown_vars!(model::JuMP.Model, g::Unit)::Nothing
+
+Add `startup` to model.
+"""
 function _add_startup_shutdown_vars!(model::JuMP.Model, g::Unit)::Nothing
     startup = _init(model, :startup)
     for t in 1:model[:instance].time
@@ -76,14 +110,31 @@ function _add_startup_shutdown_vars!(model::JuMP.Model, g::Unit)::Nothing
     return
 end
 
-function _add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::Nothing
+"""
+    _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_status_vars::Gar1962.StatusVars,
+    formulation_prod_vars::Gar1962.ProdVars,
+)::Nothing
     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]
+    prod_above = model[:prod_above]
+    reserve = model[:reserve]
+
     T = model[:instance].time
     for t in 1:T
         # Startup limit
@@ -95,8 +146,15 @@ function _add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::Nothing
         )
         # Shutdown limit
         if g.initial_power > g.shutdown_limit
+            # TODO check what happens with these variables when exporting the model
+            # Generator producing too much to be turned off in the first time period
+            # (can a binary variable have bounds x = 0?)
+            if formulation_status_vars.fix_vars_via_constraint
                 eq_shutdown_limit[g.name, 0] =
-                @constraint(model, switch_off[g.name, 1] <= 0)
+                    @constraint(model, model[:switch_off][g.name, 1] <= 0.0)
+            else
+                fix(model[:switch_off][g.name, 1], 0.0; force = true)
+            end
         end
         if t < T
             eq_shutdown_limit[g.name, t] = @constraint(
@@ -111,6 +169,32 @@ function _add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::Nothing
     return
 end
 
+"""
+    _add_shutdown_cost_eqs!(model::JuMP.Model, g::Unit)::Nothing
+
+Variables
+---
+* `switch_off`
+"""
+function _add_shutdown_cost_eqs!(model::JuMP.Model, g::Unit)::Nothing
+    T = model[:instance].time
+    gi = g.name
+    for t in 1:T
+        shutdown_cost = 0.0
+        if shutdown_cost > 1e-7
+            # Equation (62) in Knueven et al. (2020)
+            add_to_expression!(
+                model[:obj],
+                model[:switch_off][gi, t],
+                shutdown_cost,
+            )
+        end
+    end # loop over time
+end
+
+"""
+    _add_ramp_eqs!(model, unit, formulation)
+"""
 function _add_ramp_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -157,6 +241,24 @@ function _add_ramp_eqs!(
     end
 end
 
+"""
+    _add_min_uptime_downtime_eqs!(model::JuMP.Model, g::Unit)::Nothing
+
+Ensure constraints on up/down time are met.
+Based on Garver (1962), Malkin (2003), and Rajan and Takritti (2005).
+Eqns. (3), (4), (5) in Knueven et al. (2020).
+
+Variables
+---
+* `is_on`
+* `switch_off`
+* `switch_on`
+
+Constraints
+---
+* `eq_min_uptime`
+* `eq_min_downtime`
+"""
 function _add_min_uptime_downtime_eqs!(model::JuMP.Model, g::Unit)::Nothing
     is_on = model[:is_on]
     switch_off = model[:switch_off]
@@ -166,18 +268,24 @@ function _add_min_uptime_downtime_eqs!(model::JuMP.Model, g::Unit)::Nothing
     T = model[:instance].time
     for t in 1:T
         # Minimum up-time
+        # Equation (4) in Knueven et al. (2020)
         eq_min_uptime[g.name, t] = @constraint(
             model,
             sum(switch_on[g.name, i] for i in (t-g.min_uptime+1):t if i >= 1) <= is_on[g.name, t]
         )
+
         # Minimum down-time
+        # Equation (5) in Knueven et al. (2020)
         eq_min_downtime[g.name, t] = @constraint(
             model,
             sum(
                 switch_off[g.name, i] for i in (t-g.min_downtime+1):t if i >= 1
             ) <= 1 - is_on[g.name, t]
         )
+
         # Minimum up/down-time for initial periods
+        # Equations (3a) and (3b) in Knueven et al. (2020)
+        # (using :switch_on and :switch_off instead of :is_on)
         if t == 1
             if g.initial_status > 0
                 eq_min_uptime[g.name, 0] = @constraint(
@@ -200,6 +308,9 @@ function _add_min_uptime_downtime_eqs!(model::JuMP.Model, g::Unit)::Nothing
     end
 end
 
+"""
+    _add_net_injection_eqs!(model::JuMP.Model, g::Unit)::Nothing
+"""
 function _add_net_injection_eqs!(model::JuMP.Model, g::Unit)::Nothing
     expr_net_injection = model[:expr_net_injection]
     for t in 1:model[:instance].time

src/transform/randomize.jl

@@ -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!

src/transform/randomize/XavQiuAhm2021.jl

@@ -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!

src/utils/benchmark.jl

@@ -1,116 +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 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

src/utils/sysimage.jl

@@ -0,0 +1,28 @@
+# 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",
+)

test/Project.toml

@@ -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"

test/import/egret_test.jl

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

test/instance/read_test.jl

@@ -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

test/runtests.jl

@@ -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_test.jl")
-            include("transform/randomize/XavQiuAhm2021_test.jl")
-        end
     end
     @testset "validation" begin
         include("validation/repair_test.jl")

test/transform/initcond_test.jl

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

test/transform/randomize/XavQiuAhm2021_test.jl

@@ -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

test/transform/randomize_test.jl

@@ -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

test/validation/repair_test.jl

@@ -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