Fix bug in validation script; create large tests

.github/workflows/test.yml

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

.gitignore

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

CHANGELOG.md

@@ -11,10 +11,9 @@ All notable changes to this project will be documented in this file.
 [semver]: https://semver.org/spec/v2.0.0.html
 [pkjjl]: https://pkgdocs.julialang.org/v1/compatibility/#compat-pre-1.0
 
-## [0.2.2] - 2021-07-21
+## [0.2.2] - Unreleased
 ### Fixed
 - Fix small bug in validation scripts related to startup costs
-- Fix duplicated startup constraints (@mtanneau, #12)
 
 ## [0.2.1] - 2021-06-02
 ### Added

Makefile

@@ -5,20 +5,23 @@
 JULIA := julia --color=yes --project=@.
 VERSION := 0.2
 
-build/sysimage.so: src/utils/sysimage.jl Project.toml
-	julia --project=. -e "using Pkg; Pkg.instantiate()"
-	julia --project=test -e "using Pkg; Pkg.instantiate()"
-	$(JULIA) src/utils/sysimage.jl test/runtests.jl
+build/sysimage.so: src/utils/sysimage.jl Project.toml Manifest.toml
+	mkdir -p build
+	mkdir -p benchmark/results/test
+	cd benchmark; $(JULIA) --trace-compile=../build/precompile.jl benchmark.jl test/case14
+	$(JULIA) src/utils/sysimage.jl
 
 clean:
-	rm -rfv build
+	rm -rf build/*
 
 docs:
 	cd docs; make clean; make dirhtml
 	rsync -avP --delete-after docs/_build/dirhtml/ ../docs/$(VERSION)/
 	
 test: build/sysimage.so
-	$(JULIA) --sysimage build/sysimage.so test/runtests.jl
+	@echo Running tests...
+	$(JULIA) --sysimage build/sysimage.so -e 'using Pkg; Pkg.test("UnitCommitment")' | tee build/test.log
+
 
 format:
 	julia -e 'using JuliaFormatter; format(["src", "test", "benchmark"], verbose=true);'

Project.toml

@@ -15,10 +15,10 @@ Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 PackageCompiler = "9b87118b-4619-50d2-8e1e-99f35a4d4d9d"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
-Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 
 [compat]
+Cbc = "0.7"
 DataStructures = "0.18"
 Distributions = "0.25"
 GZip = "0.5"
@@ -27,3 +27,11 @@ JuMP = "0.21"
 MathOptInterface = "0.9"
 PackageCompiler = "1"
 julia = "1"
+
+[extras]
+Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+Gurobi = "2e9cd046-0924-5485-92f1-d5272153d98b"
+
+[targets]
+test = ["Cbc", "Test", "Gurobi"]

docs/format.md

@@ -28,14 +28,13 @@ Each section is described in detail below. For a complete example, see [case14](
 
 ### Parameters
 
-This section describes system-wide parameters, such as power balance and reserve shortfall penalties, and optimization parameters, such as the length of the planning horizon and the time.
+This section describes system-wide parameters, such as power balance penalties,  optimization parameters, such as the length of the planning horizon and the time.
 
 | Key                            | Description                                       | Default  | Time series?
 | :----------------------------- | :------------------------------------------------ | :------: | :------------:
-| `Time horizon (h)` | Length of the planning horizon (in hours). | Required | N
+| `Time horizon (h)`                     | Length of the planning horizon (in hours). | Required | N
 | `Time step (min)` | Length of each time step (in minutes). Must be a divisor of 60 (e.g. 60, 30, 20, 15, etc). | `60` | N
 | `Power balance penalty ($/MW)` | Penalty for system-wide shortage or surplus in production (in $/MW). This is charged per time step. For example, if there is a shortage of 1 MW for three time steps, three times this amount will be charged. | `1000.0` | Y
-| `Reserve shortfall penalty ($/MW)` | Penalty for system-wide shortage in meeting reserve requirements (in $/MW). This is charged per time step. Negative value implies reserve constraints must always be satisfied. | `-1` | Y
 
 
 #### Example
@@ -43,8 +42,7 @@ This section describes system-wide parameters, such as power balance and reserve
 {
     "Parameters": {
         "Time horizon (h)": 4,
-        "Power balance penalty ($/MW)": 1000.0,
-        "Reserve shortfall penalty ($/MW)": -1.0
+        "Power balance penalty ($/MW)": 1000.0
     }
 }
 ```

docs/model.md

@@ -148,7 +148,7 @@ for g in instance.units
 end
 ```
 
-### Fixing variables, modifying objective function and adding constraints
+### Modifying the model
 
 Since we now have a direct reference to the JuMP decision variables, it is possible to fix variables, change the coefficients in the objective function, or even add new constraints to the model before solving it. The script below shows how can this be accomplished. For more information on modifying an existing model, [see the JuMP documentation](https://jump.dev/JuMP.jl/stable/manual/variables/).
 
@@ -190,54 +190,6 @@ JuMP.set_objective_coefficient(
 UnitCommitment.optimize!(model)
 ```
 
-### Adding new component to a bus
-
-The following snippet shows how to add a new grid component to a particular bus. For each time step, we create decision variables for the new grid component, add these variables to the objective function, then attach the component to a particular bus by modifying some existing model constraints. 
-
-```julia
-using Cbc
-using JuMP
-using UnitCommitment
-
-# Load instance and build base model
-instance = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
-model = UnitCommitment.build_model(
-    instance=instance,
-    optimizer=Cbc.Optimizer,
-)
-
-# Get the number of time steps in the original instance
-T = instance.time
-
-# Create decision variables for the new grid component.
-# In this example, we assume that the new component can
-# inject up to 10 MW of power at each time step, so we
-# create new continuous variables 0 ≤ x[t] ≤ 10.
-@variable(model, x[1:T], lower_bound=0.0, upper_bound=10.0)
-
-# For each time step
-for t in 1:T
-
-    # Add production costs to the objective function.
-    # In this example, we assume a cost of $5/MW.
-    set_objective_coefficient(model, x[t], 5.0)
-
-    # Attach the new component to bus b1, by modifying the
-    # constraint `eq_net_injection`.
-    set_normalized_coefficient(
-        model[:eq_net_injection]["b1", t],
-        x[t],
-        1.0,
-    )
-end
-
-# Solve the model
-UnitCommitment.optimize!(model)
-
-# Show optimal values for the x variables
-@show value.(x)
-```
-
 References
 ----------
 * [KnOsWa20] **Bernard Knueven, James Ostrowski and Jean-Paul Watson.** "On Mixed-Integer Programming Formulations for the Unit Commitment Problem". INFORMS Journal on Computing (2020). [DOI: 10.1287/ijoc.2019.0944](https://doi.org/10.1287/ijoc.2019.0944)

src/UnitCommitment.jl

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

src/instance/read.jl

@@ -98,10 +98,6 @@ function _from_json(json; repair = true)
         json["Parameters"]["Power balance penalty (\$/MW)"],
         default = [1000.0 for t in 1:T],
     )
-    shortfall_penalty = timeseries(
-        json["Parameters"]["Reserve shortfall penalty (\$/MW)"],
-        default = [-1.0 for t in 1:T],
-    )
 
     # Read buses
     for (bus_name, dict) in json["Buses"]
@@ -266,20 +262,14 @@ function _from_json(json; repair = true)
     end
 
     instance = UnitCommitmentInstance(
-        buses_by_name = Dict(b.name => b for b in buses),
-        buses = buses,
-        contingencies_by_name = Dict(c.name => c for c in contingencies),
-        contingencies = contingencies,
-        lines_by_name = Dict(l.name => l for l in lines),
-        lines = lines,
-        power_balance_penalty = power_balance_penalty,
-        price_sensitive_loads_by_name = Dict(ps.name => ps for ps in loads),
-        price_sensitive_loads = loads,
-        reserves = reserves,
-        shortfall_penalty = shortfall_penalty,
-        time = T,
-        units_by_name = Dict(g.name => g for g in units),
-        units = units,
+        T,
+        power_balance_penalty,
+        units,
+        buses,
+        lines,
+        reserves,
+        contingencies,
+        loads,
     )
     if repair
         UnitCommitment.repair!(instance)

src/instance/structs.jl

@@ -69,21 +69,15 @@ mutable struct PriceSensitiveLoad
     revenue::Vector{Float64}
 end
 
-Base.@kwdef mutable struct UnitCommitmentInstance
-    buses_by_name::Dict{AbstractString,Bus}
-    buses::Vector{Bus}
-    contingencies_by_name::Dict{AbstractString,Contingency}
-    contingencies::Vector{Contingency}
-    lines_by_name::Dict{AbstractString,TransmissionLine}
-    lines::Vector{TransmissionLine}
-    power_balance_penalty::Vector{Float64}
-    price_sensitive_loads_by_name::Dict{AbstractString,PriceSensitiveLoad}
-    price_sensitive_loads::Vector{PriceSensitiveLoad}
-    reserves::Reserves
-    shortfall_penalty::Vector{Float64}
+mutable struct UnitCommitmentInstance
     time::Int
-    units_by_name::Dict{AbstractString,Unit}
+    power_balance_penalty::Vector{Float64}
     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/formulations/MorLatRam2013/scosts.jl

@@ -12,14 +12,14 @@ function _add_startup_cost_eqs!(
     S = length(g.startup_categories)
     startup = model[:startup]
     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(
-            model,
-            model[:switch_on][g.name, t] ==
-            sum(startup[g.name, t, s] for s in 1:S)
-        )
-
         for s in 1:S
+            # If unit is switching on, we must choose a startup category
+            eq_startup_choose[g.name, t, s] = @constraint(
+                model,
+                model[:switch_on][g.name, t] ==
+                sum(startup[g.name, t, s] for s in 1:S)
+            )
+
             # If unit has not switched off in the last `delay` time periods, startup category is forbidden.
             # The last startup category is always allowed.
             if s < S

src/model/formulations/base/bus.jl

@@ -4,11 +4,15 @@
 
 function _add_bus!(model::JuMP.Model, b::Bus)::Nothing
     net_injection = _init(model, :expr_net_injection)
+    reserve = _init(model, :expr_reserve)
     curtail = _init(model, :curtail)
     for t in 1:model[:instance].time
         # Fixed load
         net_injection[b.name, t] = AffExpr(-b.load[t])
 
+        # Reserves
+        reserve[b.name, t] = AffExpr()
+
         # Load curtailment
         curtail[b.name, t] =
             @variable(model, lower_bound = 0, upper_bound = b.load[t])

src/model/formulations/base/system.jl

@@ -11,12 +11,12 @@ end
 function _add_net_injection_eqs!(model::JuMP.Model)::Nothing
     T = model[:instance].time
     net_injection = _init(model, :net_injection)
-    eq_net_injection = _init(model, :eq_net_injection)
+    eq_net_injection_def = _init(model, :eq_net_injection_def)
     eq_power_balance = _init(model, :eq_power_balance)
     for t in 1:T, b in model[:instance].buses
         n = net_injection[b.name, t] = @variable(model)
-        eq_net_injection[b.name, t] =
-            @constraint(model, -n + model[:expr_net_injection][b.name, t] == 0)
+        eq_net_injection_def[t, b.name] =
+            @constraint(model, n == model[:expr_net_injection][b.name, t])
     end
     for t in 1:T
         eq_power_balance[t] = @constraint(
@@ -29,28 +29,13 @@ end
 
 function _add_reserve_eqs!(model::JuMP.Model)::Nothing
     eq_min_reserve = _init(model, :eq_min_reserve)
-    instance = model[:instance]
-    for t in 1:instance.time
-        # Equation (68) in Kneuven et al. (2020)
-        # As in Morales-España et al. (2013a)
-        # Akin to the alternative formulation with max_power_avail
-        # from Carrión and Arroyo (2006) and Ostrowski et al. (2012)
-        shortfall_penalty = instance.shortfall_penalty[t]
+    for t in 1:model[:instance].time
         eq_min_reserve[t] = @constraint(
             model,
-            sum(model[:reserve][g.name, t] for g in instance.units) +
-            (shortfall_penalty >= 0 ? model[:reserve_shortfall][t] : 0.0) >=
-            instance.reserves.spinning[t]
+            sum(
+                model[:expr_reserve][b.name, t] for b in model[:instance].buses
+            ) >= model[:instance].reserves.spinning[t]
         )
-
-        # Account for shortfall contribution to objective
-        if shortfall_penalty >= 0
-            add_to_expression!(
-                model[:obj],
-                shortfall_penalty,
-                model[:reserve_shortfall][t],
-            )
-        end
     end
     return
 end

src/model/formulations/base/unit.jl

@@ -44,16 +44,12 @@ _is_initially_on(g::Unit)::Float64 = (g.initial_status > 0 ? 1.0 : 0.0)
 
 function _add_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
     reserve = _init(model, :reserve)
-    reserve_shortfall = _init(model, :reserve_shortfall)
     for t in 1:model[:instance].time
         if g.provides_spinning_reserves[t]
             reserve[g.name, t] = @variable(model, lower_bound = 0)
         else
             reserve[g.name, t] = 0.0
         end
-        reserve_shortfall[t] =
-            (model[:instance].shortfall_penalty[t] >= 0) ?
-            @variable(model, lower_bound = 0) : 0.0
     end
     return
 end
@@ -214,5 +210,11 @@ function _add_net_injection_eqs!(model::JuMP.Model, g::Unit)::Nothing
             model[:is_on][g.name, t],
             g.min_power[t],
         )
+        # Add to reserves expression
+        add_to_expression!(
+            model[:expr_reserve][g.bus.name, t],
+            model[:reserve][g.name, t],
+            1.0,
+        )
     end
 end

src/solution/solution.jl

@@ -51,12 +51,6 @@ function solution(model::JuMP.Model)::OrderedDict
     sol["Switch on"] = timeseries(model[:switch_on], instance.units)
     sol["Switch off"] = timeseries(model[:switch_off], instance.units)
     sol["Reserve (MW)"] = timeseries(model[:reserve], instance.units)
-    sol["Reserve shortfall (MW)"] = OrderedDict(
-        t =>
-            (instance.shortfall_penalty[t] >= 0) ?
-            round(value(model[:reserve_shortfall][t]), digits = 5) : 0.0 for
-        t in 1:instance.time
-    )
     sol["Net injection (MW)"] =
         timeseries(model[:net_injection], instance.buses)
     sol["Load curtail (MW)"] = timeseries(model[:curtail], instance.buses)

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/sysimage.jl

@@ -3,31 +3,26 @@
 # Released under the modified BSD license. See COPYING.md for more details.
 
 using PackageCompiler
-using TOML
-using Logging
 
-Logging.disable_logging(Logging.Info)
-mkpath("build")
+using DataStructures
+using Distributions
+using JSON
+using JuMP
+using MathOptInterface
+using SparseArrays
 
-println("Generating precompilation statements...")
-run(`julia --project=. --trace-compile=build/precompile.jl $(ARGS)`)
+pkg = [
+    :DataStructures,
+    :Distributions,
+    :JSON,
+    :JuMP,
+    :MathOptInterface,
+    :SparseArrays,
+]
 
-println("Finding dependencies...")
-project = TOML.parsefile("Project.toml")
-manifest = TOML.parsefile("Manifest.toml")
-deps = Symbol[]
-for dep in keys(project["deps"])
-    if "path" in keys(manifest[dep][1])
-        println("  - $(dep) [skip]")
-    else
-        println("  - $(dep)")
-        push!(deps, Symbol(dep))
-    end
-end
-
-println("Building system image...")
+@info "Building system image..."
 create_sysimage(
-    deps,
+    pkg,
     precompile_statements_file = "build/precompile.jl",
     sysimage_path = "build/sysimage.so",
 )

src/validation/validate.jl

@@ -324,16 +324,11 @@ function _validate_reserve_and_demand(instance, solution, tol = 0.01)
         # Verify spinning reserves
         reserve =
             sum(solution["Reserve (MW)"][g.name][t] for g in instance.units)
-        reserve_shortfall =
-            (instance.shortfall_penalty[t] >= 0) ?
-            solution["Reserve shortfall (MW)"][t] : 0
-
-        if reserve + reserve_shortfall < instance.reserves.spinning[t] - tol
+        if reserve < instance.reserves.spinning[t] - tol
             @error @sprintf(
-                "Insufficient spinning reserves at time %d (%.2f + %.2f should be %.2f)",
+                "Insufficient spinning reserves at time %d (%.2f should be %.2f)",
                 t,
                 reserve,
-                reserve_shortfall,
                 instance.reserves.spinning[t],
             )
             err_count += 1

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(
-        "$basedir/../fixtures/egret_output.json.gz",
-    )
+    solution =
+        UnitCommitment.read_egret_solution("fixtures/egret_output.json.gz")
     for attr in ["Is on", "Production (MW)", "Production cost (\$)"]
         @test attr in keys(solution)
         @test "115_STEAM_1" in keys(solution[attr])

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/model/formulations_test.jl

@@ -20,14 +20,8 @@ if ENABLE_LARGE_TESTS
 end
 
 function _small_test(formulation::Formulation)::Nothing
-    instances = ["matpower/case118/2017-02-01", "test/case14"]
-    for instance in instances
-        # Should not crash
-        UnitCommitment.build_model(
-            instance = UnitCommitment.read_benchmark(instance),
-            formulation = formulation,
-        )
-    end
+    instance = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
+    UnitCommitment.build_model(instance = instance, formulation = formulation)  # should not crash
     return
 end
 

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/XavQiuAhm2021_test.jl")
-        end
+        include("transform/randomize_test.jl")
     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 =
-        UnitCommitment.read("$basedir/../fixtures/case118-initcond.json.gz")
+    instance = UnitCommitment.read("$(pwd())/fixtures/case118-initcond.json.gz")
     optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
 
     # All units should have unknown initial conditions

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