Make test/ a standalone project

LMP Methods & Profiled Units

.github/workflows/test.yml

@@ -1,4 +1,4 @@
-name: Tests
+name: Build & Test
 on:
   push:
   pull_request:
@@ -6,19 +6,30 @@ on:
     - cron: '45 10 * * *'
 jobs:
   test:
+    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }}
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        julia-version: ['1.6', '1.7']
+        version: ['1.6', '1.7', '1.8', '1.9']
-        julia-arch: [x64]
+        os:
-        os: [ubuntu-latest, windows-latest, macOS-latest]
+          - ubuntu-latest
-        exclude:
+        arch:
-          - os: macOS-latest
+          - x64
-            julia-arch: x86
     steps:
       - uses: actions/checkout@v2
-      - uses: julia-actions/setup-julia@latest
+      - uses: julia-actions/setup-julia@v1
         with:
-          version: ${{ matrix.julia-version }}
+          version: ${{ matrix.version }}
-      - uses: julia-actions/julia-buildpkg@latest
+          arch: ${{ matrix.arch }}
-      - uses: julia-actions/julia-runtest@latest
+      - name: Run tests
+        shell: julia --color=yes --project=test {0}
+        run: |
+          using Pkg
+          Pkg.develop(path=".")
+          Pkg.update()
+          using UnitCommitmentT
+          try
+            runtests()
+          catch
+            exit(1)
+          end

Makefile

@@ -4,20 +4,8 @@
 
 VERSION := 0.3
 
-clean:
-	rm -rfv build Manifest.toml test/Manifest.toml deps/formatter/build deps/formatter/Manifest.toml
-
 docs:
 	cd docs; julia --project=. make.jl; cd ..
 	rsync -avP --delete-after docs/build/ ../docs/$(VERSION)/
 	
-format:
+.PHONY: docs
-	cd deps/formatter; ../../juliaw format.jl
-
-test: test/Manifest.toml
-	./juliaw test/runtests.jl
-
-test/Manifest.toml: test/Project.toml
-	julia --project=test -e "using Pkg; Pkg.instantiate()"
-
-.PHONY: docs test format install-deps

README.md

@@ -97,11 +97,12 @@ UnitCommitment.write("/tmp/output.json", solution)
 * **Alinson S. Xavier** (Argonne National Laboratory)
 * **Aleksandr M. Kazachkov** (University of Florida)
 * **Ogün Yurdakul** (Technische Universität Berlin)
+* **Jun He** (Purdue University)
 * **Feng Qiu** (Argonne National Laboratory)
 
 ## Acknowledgments
 
-* We would like to **Yonghong Chen** (Midcontinent Independent System Operator), **Feng Pan** (Pacific Northwest National Laboratory) for valuable feedback on early versions of this package.
+* We would like to thank **Yonghong Chen** (Midcontinent Independent System Operator), **Feng Pan** (Pacific Northwest National Laboratory) for valuable feedback on early versions of this package.
 
 * Based upon work supported by **Laboratory Directed Research and Development** (LDRD) funding from Argonne National Laboratory, provided by the Director, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357
 

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,
-)

docs/Project.toml

@@ -1,4 +1,5 @@
 [deps]
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
 UnitCommitment = "64606440-39ea-11e9-0f29-3303a1d3d877"

docs/make.jl

@@ -1,4 +1,4 @@
-using Documenter, UnitCommitment
+using Documenter, UnitCommitment, JuMP
 
 makedocs(
     sitename="UnitCommitment.jl",

docs/src/api.md

@@ -12,6 +12,20 @@ UnitCommitment.validate
 UnitCommitment.write
 ```
 
+## Locational Marginal Prices
+
+### Conventional LMPs
+```@docs
+UnitCommitment.compute_lmp(::JuMP.Model,::UnitCommitment.ConventionalLMP)
+```
+
+### Approximated Extended LMPs
+```@docs
+UnitCommitment.AELMP
+UnitCommitment.compute_lmp(::JuMP.Model,::UnitCommitment.AELMP)
+```
+
+
 ## Modify instance
 
 ```@docs

docs/src/format.md

@@ -70,11 +70,17 @@ This section describes the characteristics of each bus in the system.
 
 ### Generators
 
-This section describes all generators in the system, including thermal units, renewable units and virtual units.
+This section describes all generators in the system. Two types of units can be specified:
+
+- **Thermal units:** Units that produce power by converting heat into electrical energy, such as coal and oil power plants. These units use a more complex model, with binary decision variables, and various constraints to enforce ramp rates and minimum up/down time.
+- **Profiled units:** Simplified model for units that do not require the constraints mentioned above, only a maximum and minimum power output for each time period. Typically used for renewables and hydro.
+
+#### Thermal Units
 
 | Key                       | Description                                      | Default | Time series?
 | :------------------------ | :------------------------------------------------| ------- | :-----------:
 | `Bus`                     | Identifier of the bus where this generator is located (string). | Required | N
+| `Type`                     | Type of the generator (string). For thermal generators, this must be `Thermal`.  | Required | N
 | `Production cost curve (MW)` and `Production cost curve ($)` | Parameters describing the piecewise-linear production costs. See below for more details. | Required | Y
 | `Startup costs ($)` and `Startup delays (h)` | Parameters describing how much it costs to start the generator after it has been shut down for a certain amount of time. If `Startup costs ($)` and `Startup delays (h)` are set to `[300.0, 400.0]` and `[1, 4]`, for example, and the generator is shut down at time `00:00` (h:min), then it costs \$300 to start up the generator at any time between `01:00` and `03:59`, and \$400 to start the generator at time `04:00` or any time after that.  The number of startup cost points is unlimited, and may be different for each generator. Startup delays must be strictly increasing and the first entry must equal `Minimum downtime (h)`. | `[0.0]` and `[1]` | N
 | `Minimum uptime (h)`      | Minimum amount of time the generator must stay operational after starting up (in hours). For example, if the generator starts up at time `00:00` (h:min) and `Minimum uptime (h)` is set to 4, then the generator can only shut down at time `04:00`. | `1` | N
@@ -87,6 +93,17 @@ This section describes all generators in the system, including thermal units, re
 | `Initial power (MW)`  | Amount of power the generator at time step `-1`, immediately before the planning horizon starts. | Required | N
 | `Must run?`               | If `true`, the generator should be committed, even if that is not economical (Boolean). | `false` | Y
 | `Reserve eligibility` | List of reserve products this generator is eligibe to provide. By default, the generator is not eligible to provide any reserves. | `[]` | N
+| `Commitment status` | List of commitment status over the time horizon. At time `t`, if `true`, the generator must be commited at that time period; if `false`, the generator must not be commited at that time period. If `null` at time `t`, the generator's commitment status is then decided by the model. By default, the status is a list of `null` values. | `null` | Y
+
+#### Profiled Units
+
+| Key               | Description                                       | Default  | Time series?
+| :---------------- | :------------------------------------------------ | :------: | :------------:
+| `Bus`             | Identifier of the bus where this generator is located (string). | Required | N
+| `Type`            | Type of the generator (string). For profiled generators, this must be `Profiled`.  | Required | N
+| `Cost ($/MW)`     | Cost incurred for serving each MW of power by this generator. | Required | Y
+| `Minimum power (MW)` | Minimum amount of power this generator may supply. | `0.0` | Y
+| `Maximum power (MW)` | Maximum amount of power this generator may supply. | Required | Y
 
 #### Production costs and limits
 
@@ -115,6 +132,7 @@ Note that this curve also specifies the production limits. Specifically, the fir
     "Generators": {
         "gen1": {
             "Bus": "b1",
+            "Type": "Thermal",
             "Production cost curve (MW)": [100.0, 110.0, 130.0, 135.0],
             "Production cost curve ($)": [1400.0, 1600.0, 2200.0, 2400.0],
             "Startup costs ($)": [300.0, 400.0],
@@ -126,14 +144,26 @@ Note that this curve also specifies the production limits. Specifically, the fir
             "Minimum downtime (h)": 4,
             "Minimum uptime (h)": 4,
             "Initial status (h)": 12,
+            "Initial power (MW)": 115,
             "Must run?": false,
-            "Reserve eligibility": ["r1"],
+            "Reserve eligibility": ["r1"]
         },
         "gen2": {
             "Bus": "b5",
+            "Type": "Thermal",
             "Production cost curve (MW)": [0.0, [10.0, 8.0, 0.0, 3.0]],
             "Production cost curve ($)": [0.0, 0.0],
+            "Initial status (h)": -100,
+            "Initial power (MW)": 0,
             "Reserve eligibility": ["r1", "r2"],
+            "Commitment status": [true, false, null, true]
+        },
+        "gen3": {
+            "Bus": "b6",
+            "Type": "Profiled",
+            "Minimum power (MW)": 10.0,
+            "Maximum power (MW)": 120.0,
+            "Cost ($/MW)": 100.0
         }
     }
 }

docs/src/index.md

@@ -20,6 +20,7 @@ Depth = 3
 * **Alinson S. Xavier** (Argonne National Laboratory)
 * **Aleksandr M. Kazachkov** (University of Florida)
 * **Ogün Yurdakul** (Technische Universität Berlin)
+* **Jun He** (Purdue University)
 * **Feng Qiu** (Argonne National Laboratory)
 
 ## Acknowledgments

docs/src/model.md

@@ -8,6 +8,8 @@ Decision variables
 
 ### Generators
 
+#### Thermal Units
+
 Name | Symbol | Description | Unit
 :-----|:--------:|:-------------|:------:
 `is_on[g,t]` | $u_{g}(t)$ | True if generator `g` is on at time `t`. | Binary
@@ -19,6 +21,13 @@ Name | Symbol | Description | Unit
 `startup[g,t,s]` | $\delta^s_g(t)$ | True if generator `g` switches on at time `t` incurring start-up costs from start-up category `s`. | Binary
 
 
+#### Profiled Units
+
+Name | Symbol | Description | Unit
+:-----|:------:|:-------------|:------:
+`prod_profiled[s,t]` | $p^{\dagger}_{g}(t)$ | Amount of power produced by profiled unit `g` at time `t`. | MW
+
+
 ### Buses
 
 Name | Symbol | Description | Unit

docs/src/usage.md

@@ -58,10 +58,7 @@ using UnitCommitment
 instance = UnitCommitment.read_benchmark("matpower/case3375wp/2017-02-01")
 ```
 
-Advanced usage
+## Customizing the formulation
---------------
-
-### Customizing the formulation
 
 By default, `build_model` uses a formulation that combines modeling components from different publications, and that has been carefully tested, using our own benchmark scripts, to provide good performance across a wide variety of instances. This default formulation is expected to change over time, as new methods are proposed in the literature. You can, however, construct your own formulation, based on the modeling components that you choose, as shown in the next example.
 
@@ -94,7 +91,7 @@ model = UnitCommitment.build_model(
 )
 ```
 
-### Generating initial conditions
+## Generating initial conditions
 
 When creating random unit commitment instances for benchmark purposes, it is often hard to compute, in advance, sensible initial conditions for all generators. Setting initial conditions naively (for example, making all generators initially off and producing no power) can easily cause the instance to become infeasible due to excessive ramping. Initial conditions can also make it hard to modify existing instances. For example, increasing the system load without carefully modifying the initial conditions may make the problem infeasible or unrealistically challenging to solve.
 
@@ -122,7 +119,7 @@ UnitCommitment.optimize!(model)
 
     The function `generate_initial_conditions!` may return different initial conditions after each call, even if the same instance and the same optimizer is provided. The particular algorithm may also change in a future version of UC.jl. For these reasons, it is recommended that you generate initial conditions exactly once for each instance and store them for later use.
     
-### Verifying solutions
+## Verifying solutions
 
 When developing new formulations, it is very easy to introduce subtle errors in the model that result in incorrect solutions. To help with this, UC.jl includes a utility function that verifies if a given solution is feasible, and, if not, prints all the validation errors it found. The implementation of this function is completely independent from the implementation of the optimization model, and therefore can be used to validate it. The function can also be used to verify solutions produced by other optimization packages, as long as they follow the [UC.jl data format](format.md).
 
@@ -139,3 +136,91 @@ solution = JSON.parsefile("solution.json")
 # Validate solution and print validation errors
 UnitCommitment.validate(instance, solution)
 ```
+
+## Computing Locational Marginal Prices
+
+Locational marginal prices (LMPs) refer to the cost of supplying electricity at a particular location of the network. Multiple methods for computing LMPs have been proposed in the literature. UnitCommitment.jl implements two commonly-used methods: conventional LMPs and Approximated Extended LMPs (AELMPs). To compute LMPs for a given unit commitment instance, the `compute_lmp` function can be used, as shown in the examples below. The function accepts three arguments -- a solved SCUC model, an LMP method, and a linear optimizer -- and it returns a dictionary mapping `(bus_name, time)` to the marginal price.
+
+
+!!! warning
+
+    Most mixed-integer linear optimizers, such as `HiGHS`, `Gurobi` and `CPLEX` can be used with `compute_lmp`, with the notable exception of `Cbc`, which does not support dual value evaluations. If using `Cbc`, please provide `Clp` as the linear optimizer.
+
+### Conventional LMPs
+
+LMPs are conventionally computed by: (1) solving the SCUC model, (2) fixing all binary variables to their optimal values, and (3) re-solving the resulting linear programming model. In this approach, the LMPs are defined as the dual variables' values associated with the net injection constraints. The example below shows how to compute conventional LMPs for a given unit commitment instance. First, we build and optimize the SCUC model. Then, we call the `compute_lmp` function, providing as the second argument `ConventionalLMP()`.
+
+
+```julia
+using UnitCommitment
+using HiGHS
+
+import UnitCommitment: ConventionalLMP
+
+# Read benchmark instance
+instance = UnitCommitment.read_benchmark("matpower/case118/2018-01-01")
+
+# Build the model
+model = UnitCommitment.build_model(
+    instance = instance,
+    optimizer = HiGHS.Optimizer,
+)
+
+# Optimize the model
+UnitCommitment.optimize!(model)
+
+# Compute the LMPs using the conventional method
+lmp = UnitCommitment.compute_lmp(
+    model,
+    ConventionalLMP(),
+    optimizer = HiGHS.Optimizer,
+)
+
+# Access the LMPs
+# Example: "s1" is the scenario name, "b1" is the bus name, 1 is the first time slot
+@show lmp["s1","b1", 1]
+```
+
+### Approximate Extended LMPs
+
+Approximate Extended LMPs (AELMPs) are an alternative method to calculate locational marginal prices which attemps to minimize uplift payments. The method internally works by modifying the instance data in three ways: (1) it sets the minimum power output of each generator to zero, (2) it averages the start-up cost over the offer blocks for each generator, and (3) it relaxes all integrality constraints. To compute AELMPs, as shown in the example below, we call `compute_lmp` and provide `AELMP()` as the second argument.
+
+This method has two configurable parameters: `allow_offline_participation` and `consider_startup_costs`. If `allow_offline_participation = true`, then offline generators are allowed to participate in the pricing. If instead `allow_offline_participation = false`, offline generators are not allowed and therefore are excluded from the system. A solved UC model is optional if offline participation is allowed, but is required if not allowed. The method forces offline participation to be allowed if the UC model supplied by the user is not solved. For the second field, If `consider_startup_costs = true`, then start-up costs are integrated and averaged over each unit production; otherwise the production costs stay the same. By default, both fields are set to `true`.
+
+!!! warning
+
+    This approximation method is still under active research, and has several limitations. The implementation provided in the package is based on MISO Phase I only. It only supports fast start resources. More specifically, the minimum up/down time of all generators must be 1, the initial power of all generators must be 0, and the initial status of all generators must be negative. The method does not support time-varying start-up costs. The method does not support multiple scenarios. If offline participation is not allowed, AELMPs treats an asset to be  offline if it is never on throughout all time periods. 
+
+```julia
+using UnitCommitment
+using HiGHS
+
+import UnitCommitment: AELMP
+
+# Read benchmark instance
+instance = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
+
+# Build the model
+model = UnitCommitment.build_model(
+    instance = instance,
+    optimizer = HiGHS.Optimizer,
+)
+
+# Optimize the model
+UnitCommitment.optimize!(model)
+
+# Compute the AELMPs
+aelmp = UnitCommitment.compute_lmp(
+    model,
+    AELMP(
+        allow_offline_participation = false,
+        consider_startup_costs = true
+    ),
+    optimizer = HiGHS.Optimizer
+)
+
+# Access the AELMPs
+# Example: "s1" is the scenario name, "b1" is the bus name, 1 is the first time slot
+# Note: although scenario is supported, the query still keeps the scenario keys for consistency.
+@show aelmp["s1", "b1", 1]
+```

juliaw

@@ -1,75 +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 dep in keys(manifest)
-	# Up to Julia 1.6
-        dep_entry = manifest[dep][1]
-    else
-        # Julia 1.7+
-        dep_entry = manifest["deps"][dep][1]
-    end
-    if "path" in keys(dep_entry)
-        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

@@ -4,9 +4,12 @@
 
 module UnitCommitment
 
+using Base: String
+
 include("instance/structs.jl")
 include("model/formulations/base/structs.jl")
 include("solution/structs.jl")
+include("lmp/structs.jl")
 
 include("model/formulations/ArrCon2000/structs.jl")
 include("model/formulations/CarArr2006/structs.jl")
@@ -29,6 +32,7 @@ include("model/formulations/base/psload.jl")
 include("model/formulations/base/sensitivity.jl")
 include("model/formulations/base/system.jl")
 include("model/formulations/base/unit.jl")
+include("model/formulations/base/punit.jl")
 include("model/formulations/CarArr2006/pwlcosts.jl")
 include("model/formulations/DamKucRajAta2016/ramp.jl")
 include("model/formulations/Gar1962/pwlcosts.jl")
@@ -56,5 +60,7 @@ include("utils/log.jl")
 include("utils/benchmark.jl")
 include("validation/repair.jl")
 include("validation/validate.jl")
+include("lmp/conventional.jl")
+include("lmp/aelmp.jl")
 
 end

src/import/egret.jl

@@ -18,9 +18,9 @@ function read_egret_solution(path::String)::OrderedDict
 
     solution = OrderedDict()
     is_on = solution["Is on"] = OrderedDict()
-    production = solution["Production (MW)"] = OrderedDict()
+    production = solution["Thermal production (MW)"] = OrderedDict()
     reserve = solution["Reserve (MW)"] = OrderedDict()
-    production_cost = solution["Production cost (\$)"] = OrderedDict()
+    production_cost = solution["Thermal production cost (\$)"] = OrderedDict()
     startup_cost = solution["Startup cost (\$)"] = OrderedDict()
 
     for (gen_name, gen_dict) in egret["elements"]["generator"]

src/instance/migrate.jl

@@ -17,6 +17,7 @@ function _migrate(json)
     end
     version = VersionNumber(version)
     version >= v"0.3" || _migrate_to_v03(json)
+    version >= v"0.4" || _migrate_to_v04(json)
     return
 end
 
@@ -36,3 +37,14 @@ function _migrate_to_v03(json)
         end
     end
 end
+
+function _migrate_to_v04(json)
+    # Migrate thermal units
+    if json["Generators"] !== nothing
+        for (gen_name, gen) in json["Generators"]
+            if gen["Type"] === nothing
+                gen["Type"] = "Thermal"
+            end
+        end
+    end
+end

src/instance/read.jl

@@ -43,26 +43,76 @@ function read_benchmark(
     return UnitCommitment.read(filename)
 end
 
+function _repair_scenario_names_and_probabilities!(
+    scenarios::Vector{UnitCommitmentScenario},
+    path::Vector{String},
+)::Nothing
+    total_weight = sum([sc.probability for sc in scenarios])
+    for (sc_path, sc) in zip(path, scenarios)
+        sc.name !== "" ||
+            (sc.name = first(split(last(split(sc_path, "/")), ".")))
+        sc.probability = (sc.probability / total_weight)
+    end
+    return
+end
+
 """
     read(path::AbstractString)::UnitCommitmentInstance
 
-Read instance from a file. The file may be gzipped.
+Read a deterministic test case from the given file. The file may be gzipped.
 
 # Example
 
 ```julia
-instance = UnitCommitment.read("/path/to/input.json.gz")
+instance = UnitCommitment.read("s1.json.gz")
 ```
 """
-function read(path::AbstractString)::UnitCommitmentInstance
+function read(path::String)::UnitCommitmentInstance
-    if endswith(path, ".gz")
+    scenarios = Vector{UnitCommitmentScenario}()
-        return _read(gzopen(path))
+    scenario = _read_scenario(path)
-    else
+    scenario.name = "s1"
-        return _read(open(path))
+    scenario.probability = 1.0
-    end
+    scenarios = [scenario]
+    instance =
+        UnitCommitmentInstance(time = scenario.time, scenarios = scenarios)
+    return instance
 end
 
-function _read(file::IO)::UnitCommitmentInstance
+"""
+    read(path::Vector{String})::UnitCommitmentInstance
+
+Read a stochastic unit commitment instance from the given files. Each file
+describes a scenario. The files may be gzipped.
+
+# Example
+
+```julia
+instance = UnitCommitment.read(["s1.json.gz", "s2.json.gz"])
+```
+"""
+function read(paths::Vector{String})::UnitCommitmentInstance
+    scenarios = UnitCommitmentScenario[]
+    for p in paths
+        push!(scenarios, _read_scenario(p))
+    end
+    _repair_scenario_names_and_probabilities!(scenarios, paths)
+    instance =
+        UnitCommitmentInstance(time = scenarios[1].time, scenarios = scenarios)
+    return instance
+end
+
+function _read_scenario(path::String)::UnitCommitmentScenario
+    if endswith(path, ".gz")
+        scenario = _read(gzopen(path))
+    elseif endswith(path, ".json")
+        scenario = _read(open(path))
+    else
+        error("Unsupported input format")
+    end
+    return scenario
+end
+
+function _read(file::IO)::UnitCommitmentScenario
     return _from_json(
         JSON.parse(file, dicttype = () -> DefaultOrderedDict(nothing)),
     )
@@ -77,14 +127,15 @@ function _read_json(path::String)::OrderedDict
     return JSON.parse(file, dicttype = () -> DefaultOrderedDict(nothing))
 end
 
-function _from_json(json; repair = true)
+function _from_json(json; repair = true)::UnitCommitmentScenario
     _migrate(json)
-    units = Unit[]
+    thermal_units = ThermalUnit[]
     buses = Bus[]
     contingencies = Contingency[]
     lines = TransmissionLine[]
     loads = PriceSensitiveLoad[]
     reserves = Reserve[]
+    profiled_units = ProfiledUnit[]
 
     function scalar(x; default = nothing)
         x !== nothing || return default
@@ -102,9 +153,14 @@ function _from_json(json; repair = true)
     time_multiplier = 60 ÷ time_step
     T = time_horizon * time_multiplier
 
+    probability = json["Parameters"]["Scenario weight"]
+    probability !== nothing || (probability = 1)
+    scenario_name = json["Parameters"]["Scenario name"]
+    scenario_name !== nothing || (scenario_name = "")
+
     name_to_bus = Dict{String,Bus}()
     name_to_line = Dict{String,TransmissionLine}()
-    name_to_unit = Dict{String,Unit}()
+    name_to_unit = Dict{String,ThermalUnit}()
     name_to_reserve = Dict{String,Reserve}()
 
     function timeseries(x; default = nothing)
@@ -118,15 +174,6 @@ function _from_json(json; repair = true)
         json["Parameters"]["Power balance penalty (\$/MW)"],
         default = [1000.0 for t in 1:T],
     )
-    # Penalty price for shortage in meeting system-wide flexiramp requirements
-    flexiramp_shortfall_penalty = timeseries(
-        json["Parameters"]["Flexiramp penalty (\$/MW)"],
-        default = [500.0 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"]
@@ -134,8 +181,9 @@ function _from_json(json; repair = true)
             bus_name,
             length(buses),
             timeseries(dict["Load (MW)"]),
-            Unit[],
+            ThermalUnit[],
             PriceSensitiveLoad[],
+            ProfiledUnit[],
         )
         name_to_bus[bus_name] = bus
         push!(buses, bus)
@@ -148,7 +196,7 @@ function _from_json(json; repair = true)
                 name = reserve_name,
                 type = lowercase(dict["Type"]),
                 amount = timeseries(dict["Amount (MW)"]),
-                units = [],
+                thermal_units = [],
                 shortfall_penalty = scalar(
                     dict["Shortfall penalty (\$/MW)"],
                     default = -1,
@@ -161,90 +209,127 @@ function _from_json(json; repair = true)
 
     # Read units
     for (unit_name, dict) in json["Generators"]
+        # Read and validate unit type
+        unit_type = scalar(dict["Type"], default = nothing)
+        unit_type !== nothing || error("unit $unit_name has no type specified")
         bus = name_to_bus[dict["Bus"]]
 
-        # Read production cost curve
+        if lowercase(unit_type) === "thermal"
-        K = length(dict["Production cost curve (MW)"])
+            # Read production cost curve
-        curve_mw = hcat(
+            K = length(dict["Production cost curve (MW)"])
-            [timeseries(dict["Production cost curve (MW)"][k]) for k in 1:K]...,
+            curve_mw = hcat(
-        )
+                [
-        curve_cost = hcat(
+                    timeseries(dict["Production cost curve (MW)"][k]) for
-            [timeseries(dict["Production cost curve (\$)"][k]) for k in 1:K]...,
+                    k in 1:K
-        )
+                ]...,
-        min_power = curve_mw[:, 1]
-        max_power = curve_mw[:, K]
-        min_power_cost = curve_cost[:, 1]
-        segments = CostSegment[]
-        for k in 2:K
-            amount = curve_mw[:, k] - curve_mw[:, k-1]
-            cost = (curve_cost[:, k] - curve_cost[:, k-1]) ./ amount
-            replace!(cost, NaN => 0.0)
-            push!(segments, CostSegment(amount, cost))
-        end
-
-        # Read startup costs
-        startup_delays = scalar(dict["Startup delays (h)"], default = [1])
-        startup_costs = scalar(dict["Startup costs (\$)"], default = [0.0])
-        startup_categories = StartupCategory[]
-        for k in 1:length(startup_delays)
-            push!(
-                startup_categories,
-                StartupCategory(
-                    startup_delays[k] .* time_multiplier,
-                    startup_costs[k],
-                ),
             )
-        end
+            curve_cost = hcat(
-
+                [
-        # Read reserve eligibility
+                    timeseries(dict["Production cost curve (\$)"][k]) for
-        unit_reserves = Reserve[]
+                    k in 1:K
-        if "Reserve eligibility" in keys(dict)
+                ]...,
-            unit_reserves =
+            )
-                [name_to_reserve[n] for n in dict["Reserve eligibility"]]
+            min_power = curve_mw[:, 1]
-        end
+            max_power = curve_mw[:, K]
-
+            min_power_cost = curve_cost[:, 1]
-        # Read and validate initial conditions
+            segments = CostSegment[]
-        initial_power = scalar(dict["Initial power (MW)"], default = nothing)
+            for k in 2:K
-        initial_status = scalar(dict["Initial status (h)"], default = nothing)
+                amount = curve_mw[:, k] - curve_mw[:, k-1]
-        if initial_power === nothing
+                cost = (curve_cost[:, k] - curve_cost[:, k-1]) ./ amount
-            initial_status === nothing ||
+                replace!(cost, NaN => 0.0)
-                error("unit $unit_name has initial status but no initial power")
+                push!(segments, CostSegment(amount, cost))
-        else
-            initial_status !== nothing ||
-                error("unit $unit_name has initial power but no initial status")
-            initial_status != 0 ||
-                error("unit $unit_name has invalid initial status")
-            if initial_status < 0 && initial_power > 1e-3
-                error("unit $unit_name has invalid initial power")
             end
-            initial_status *= time_multiplier
-        end
 
-        unit = Unit(
+            # Read startup costs
-            unit_name,
+            startup_delays = scalar(dict["Startup delays (h)"], default = [1])
-            bus,
+            startup_costs = scalar(dict["Startup costs (\$)"], default = [0.0])
-            max_power,
+            startup_categories = StartupCategory[]
-            min_power,
+            for k in 1:length(startup_delays)
-            timeseries(dict["Must run?"], default = [false for t in 1:T]),
+                push!(
-            min_power_cost,
+                    startup_categories,
-            segments,
+                    StartupCategory(
-            scalar(dict["Minimum uptime (h)"], default = 1) * time_multiplier,
+                        startup_delays[k] .* time_multiplier,
-            scalar(dict["Minimum downtime (h)"], default = 1) * time_multiplier,
+                        startup_costs[k],
-            scalar(dict["Ramp up limit (MW)"], default = 1e6),
+                    ),
-            scalar(dict["Ramp down limit (MW)"], default = 1e6),
+                )
-            scalar(dict["Startup limit (MW)"], default = 1e6),
+            end
-            scalar(dict["Shutdown limit (MW)"], default = 1e6),
+
-            initial_status,
+            # Read reserve eligibility
-            initial_power,
+            unit_reserves = Reserve[]
-            startup_categories,
+            if "Reserve eligibility" in keys(dict)
-            unit_reserves,
+                unit_reserves =
-        )
+                    [name_to_reserve[n] for n in dict["Reserve eligibility"]]
-        push!(bus.units, unit)
+            end
-        for r in unit_reserves
+
-            push!(r.units, unit)
+            # Read and validate initial conditions
+            initial_power =
+                scalar(dict["Initial power (MW)"], default = nothing)
+            initial_status =
+                scalar(dict["Initial status (h)"], default = nothing)
+            if initial_power === nothing
+                initial_status === nothing || error(
+                    "unit $unit_name has initial status but no initial power",
+                )
+            else
+                initial_status !== nothing || error(
+                    "unit $unit_name has initial power but no initial status",
+                )
+                initial_status != 0 ||
+                    error("unit $unit_name has invalid initial status")
+                if initial_status < 0 && initial_power > 1e-3
+                    error("unit $unit_name has invalid initial power")
+                end
+                initial_status *= time_multiplier
+            end
+
+            # Read commitment status 
+            commitment_status = scalar(
+                dict["Commitment status"],
+                default = Vector{Union{Bool,Nothing}}(nothing, T),
+            )
+
+            unit = ThermalUnit(
+                unit_name,
+                bus,
+                max_power,
+                min_power,
+                timeseries(dict["Must run?"], default = [false for t in 1:T]),
+                min_power_cost,
+                segments,
+                scalar(dict["Minimum uptime (h)"], default = 1) *
+                time_multiplier,
+                scalar(dict["Minimum downtime (h)"], default = 1) *
+                time_multiplier,
+                scalar(dict["Ramp up limit (MW)"], default = 1e6),
+                scalar(dict["Ramp down limit (MW)"], default = 1e6),
+                scalar(dict["Startup limit (MW)"], default = 1e6),
+                scalar(dict["Shutdown limit (MW)"], default = 1e6),
+                initial_status,
+                initial_power,
+                startup_categories,
+                unit_reserves,
+                commitment_status,
+            )
+            push!(bus.thermal_units, unit)
+            for r in unit_reserves
+                push!(r.thermal_units, unit)
+            end
+            name_to_unit[unit_name] = unit
+            push!(thermal_units, unit)
+        elseif lowercase(unit_type) === "profiled"
+            bus = name_to_bus[dict["Bus"]]
+            pu = ProfiledUnit(
+                unit_name,
+                bus,
+                timeseries(scalar(dict["Minimum power (MW)"], default = 0.0)),
+                timeseries(dict["Maximum power (MW)"]),
+                timeseries(dict["Cost (\$/MW)"]),
+            )
+            push!(bus.profiled_units, pu)
+            push!(profiled_units, pu)
+        else
+            error("unit $unit_name has an invalid type")
         end
-        name_to_unit[unit_name] = unit
-        push!(units, unit)
     end
 
     # Read transmission lines
@@ -278,7 +363,7 @@ function _from_json(json; repair = true)
     # Read contingencies
     if "Contingencies" in keys(json)
         for (cont_name, dict) in json["Contingencies"]
-            affected_units = Unit[]
+            affected_units = ThermalUnit[]
             affected_lines = TransmissionLine[]
             if "Affected lines" in keys(dict)
                 affected_lines =
@@ -308,7 +393,9 @@ function _from_json(json; repair = true)
         end
     end
 
-    instance = UnitCommitmentInstance(
+    scenario = UnitCommitmentScenario(
+        name = scenario_name,
+        probability = probability,
         buses_by_name = Dict(b.name => b for b in buses),
         buses = buses,
         contingencies_by_name = Dict(c.name => c for c in contingencies),
@@ -320,14 +407,16 @@ function _from_json(json; repair = true)
         price_sensitive_loads = loads,
         reserves = reserves,
         reserves_by_name = name_to_reserve,
-        shortfall_penalty = shortfall_penalty,
-        flexiramp_shortfall_penalty = flexiramp_shortfall_penalty,
         time = T,
-        units_by_name = Dict(g.name => g for g in units),
+        thermal_units_by_name = Dict(g.name => g for g in thermal_units),
-        units = units,
+        thermal_units = thermal_units,
+        profiled_units_by_name = Dict(pu.name => pu for pu in profiled_units),
+        profiled_units = profiled_units,
+        isf = spzeros(Float64, length(lines), length(buses) - 1),
+        lodf = spzeros(Float64, length(lines), length(lines)),
     )
     if repair
-        UnitCommitment.repair!(instance)
+        UnitCommitment.repair!(scenario)
     end
-    return instance
+    return scenario
 end

src/instance/structs.jl

@@ -6,8 +6,9 @@ mutable struct Bus
     name::String
     offset::Int
     load::Vector{Float64}
-    units::Vector
+    thermal_units::Vector
     price_sensitive_loads::Vector
+    profiled_units::Vector
 end
 
 mutable struct CostSegment
@@ -24,11 +25,11 @@ Base.@kwdef mutable struct Reserve
     name::String
     type::String
     amount::Vector{Float64}
-    units::Vector
+    thermal_units::Vector
     shortfall_penalty::Float64
 end
 
-mutable struct Unit
+mutable struct ThermalUnit
     name::String
     bus::Bus
     max_power::Vector{Float64}
@@ -46,6 +47,7 @@ mutable struct Unit
     initial_power::Union{Float64,Nothing}
     startup_categories::Vector{StartupCategory}
     reserves::Vector{Reserve}
+    commitment_status::Vector{Union{Bool,Nothing}}
 end
 
 mutable struct TransmissionLine
@@ -63,7 +65,7 @@ end
 mutable struct Contingency
     name::String
     lines::Vector{TransmissionLine}
-    units::Vector{Unit}
+    thermal_units::Vector{ThermalUnit}
 end
 
 mutable struct PriceSensitiveLoad
@@ -73,35 +75,52 @@ mutable struct PriceSensitiveLoad
     revenue::Vector{Float64}
 end
 
-Base.@kwdef mutable struct UnitCommitmentInstance
+mutable struct ProfiledUnit
+    name::String
+    bus::Bus
+    min_power::Vector{Float64}
+    max_power::Vector{Float64}
+    cost::Vector{Float64}
+end
+
+Base.@kwdef mutable struct UnitCommitmentScenario
     buses_by_name::Dict{AbstractString,Bus}
     buses::Vector{Bus}
     contingencies_by_name::Dict{AbstractString,Contingency}
     contingencies::Vector{Contingency}
+    isf::Array{Float64,2}
     lines_by_name::Dict{AbstractString,TransmissionLine}
     lines::Vector{TransmissionLine}
+    lodf::Array{Float64,2}
+    name::String
     power_balance_penalty::Vector{Float64}
     price_sensitive_loads_by_name::Dict{AbstractString,PriceSensitiveLoad}
     price_sensitive_loads::Vector{PriceSensitiveLoad}
-    reserves::Vector{Reserve}
+    probability::Float64
+    profiled_units_by_name::Dict{AbstractString,ProfiledUnit}
+    profiled_units::Vector{ProfiledUnit}
     reserves_by_name::Dict{AbstractString,Reserve}
-    shortfall_penalty::Vector{Float64}
+    reserves::Vector{Reserve}
-    flexiramp_shortfall_penalty::Vector{Float64}
+    thermal_units_by_name::Dict{AbstractString,ThermalUnit}
+    thermal_units::Vector{ThermalUnit}
     time::Int
-    units_by_name::Dict{AbstractString,Unit}
+end
-    units::Vector{Unit}
+
+Base.@kwdef mutable struct UnitCommitmentInstance
+    time::Int
+    scenarios::Vector{UnitCommitmentScenario}
 end
 
 function Base.show(io::IO, instance::UnitCommitmentInstance)
+    sc = instance.scenarios[1]
     print(io, "UnitCommitmentInstance(")
-    print(io, "$(length(instance.units)) units, ")
+    print(io, "$(length(instance.scenarios)) scenarios, ")
-    print(io, "$(length(instance.buses)) buses, ")
+    print(io, "$(length(sc.thermal_units)) thermal units, ")
-    print(io, "$(length(instance.lines)) lines, ")
+    print(io, "$(length(sc.profiled_units)) profiled units, ")
-    print(io, "$(length(instance.contingencies)) contingencies, ")
+    print(io, "$(length(sc.buses)) buses, ")
-    print(
+    print(io, "$(length(sc.lines)) lines, ")
-        io,
+    print(io, "$(length(sc.contingencies)) contingencies, ")
-        "$(length(instance.price_sensitive_loads)) price sensitive loads, ",
+    print(io, "$(length(sc.price_sensitive_loads)) price sensitive loads, ")
-    )
     print(io, "$(instance.time) time steps")
     print(io, ")")
     return

src/lmp/aelmp.jl

@@ -0,0 +1,212 @@
+# 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 JuMP
+
+"""
+    function compute_lmp(
+        model::JuMP.Model,
+        method::AELMP;
+        optimizer,
+    )::OrderedDict{Tuple{String,Int},Float64}
+
+Calculates the approximate extended locational marginal prices of the given unit commitment instance.
+
+The AELPM does the following three things:
+
+    1. It sets the minimum power output of each generator to zero
+    2. It averages the start-up cost over the offer blocks for each generator
+    3. It relaxes all integrality constraints
+
+Returns a dictionary mapping `(bus_name, time)` to the marginal price.
+
+WARNING: This approximation method is not fully developed. The implementation is based on MISO Phase I only.
+
+1. It only supports Fast Start resources. More specifically, the minimum up/down time has to be zero.
+2. The method does NOT support time-varying start-up costs.
+3. An asset is considered offline if it is never on throughout all time periods. 
+4. The method does NOT support multiple scenarios.
+
+Arguments
+---------
+
+- `model`:
+    the UnitCommitment model, must be solved before calling this function if offline participation is not allowed.
+
+- `method`:
+    the AELMP method.
+
+- `optimizer`:
+    the optimizer for solving the LP problem.
+
+Examples
+--------
+
+```julia
+using UnitCommitment
+using HiGHS
+
+import UnitCommitment: AELMP
+
+# Read benchmark instance
+instance = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
+
+# Build the model
+model = UnitCommitment.build_model(
+    instance = instance,
+    optimizer = HiGHS.Optimizer,
+)
+
+# Optimize the model
+UnitCommitment.optimize!(model)
+
+# Compute the AELMPs
+aelmp = UnitCommitment.compute_lmp(
+    model,
+    AELMP(
+        allow_offline_participation = false,
+        consider_startup_costs = true
+    ),
+    optimizer = HiGHS.Optimizer
+)
+
+# Access the AELMPs
+# Example: "s1" is the scenario name, "b1" is the bus name, 1 is the first time slot
+# Note: although scenario is supported, the query still keeps the scenario keys for consistency.
+@show aelmp["s1", "b1", 1]
+```
+"""
+function compute_lmp(
+    model::JuMP.Model,
+    method::AELMP;
+    optimizer,
+)::OrderedDict{Tuple{String,String,Int},Float64}
+    @info "Building the approximation model..."
+    instance = deepcopy(model[:instance])
+    _aelmp_check_parameters(instance, model, method)
+    _modify_scenario!(instance.scenarios[1], model, method)
+
+    # prepare the result dictionary and solve the model 
+    elmp = OrderedDict()
+    @info "Solving the approximation model."
+    approx_model = build_model(instance = instance, variable_names = true)
+
+    # relax the binary constraint, and relax integrality
+    for v in all_variables(approx_model)
+        if is_binary(v)
+            unset_binary(v)
+        end
+    end
+    relax_integrality(approx_model)
+    set_optimizer(approx_model, optimizer)
+
+    # solve the model 
+    set_silent(approx_model)
+    optimize!(approx_model)
+
+    # access the dual values
+    @info "Getting dual values (AELMPs)."
+    for (key, val) in approx_model[:eq_net_injection]
+        elmp[key] = dual(val)
+    end
+    return elmp
+end
+
+function _aelmp_check_parameters(
+    instance::UnitCommitmentInstance,
+    model::JuMP.Model,
+    method::AELMP,
+)
+    # CHECK: model cannot have multiple scenarios
+    if length(instance.scenarios) > 1
+        error("The method does NOT support multiple scenarios.")
+    end
+    sc = instance.scenarios[1]
+    # CHECK: model must be solved if allow_offline_participation=false
+    if !method.allow_offline_participation
+        if isnothing(model) || !has_values(model)
+            error(
+                "A solved UC model is required if allow_offline_participation=false.",
+            )
+        end
+    end
+    all_units = sc.thermal_units
+    # CHECK: model cannot handle non-fast-starts (MISO Phase I: can ONLY solve fast-starts)
+    if any(u -> u.min_uptime > 1 || u.min_downtime > 1, all_units)
+        error(
+            "The minimum up/down time of all generators must be 1. AELMP only supports fast-starts.",
+        )
+    end
+    if any(u -> u.initial_power > 0, all_units)
+        error("The initial power of all generators must be 0.")
+    end
+    if any(u -> u.initial_status >= 0, all_units)
+        error("The initial status of all generators must be negative.")
+    end
+    # CHECK: model does not support startup costs (in time series)
+    if any(u -> length(u.startup_categories) > 1, all_units)
+        error("The method does NOT support time-varying start-up costs.")
+    end
+end
+
+function _modify_scenario!(
+    sc::UnitCommitmentScenario,
+    model::JuMP.Model,
+    method::AELMP,
+)
+    # this function modifies the sc units (generators)
+    if !method.allow_offline_participation
+        # 1. remove (if NOT allowing) the offline generators
+        units_to_remove = []
+        for unit in sc.thermal_units
+            # remove based on the solved UC model result
+            # remove the unit if it is never on
+            if all(t -> value(model[:is_on][unit.name, t]) == 0, sc.time)
+                # unregister from the bus 
+                filter!(x -> x.name != unit.name, unit.bus.thermal_units)
+                # unregister from the reserve
+                for r in unit.reserves
+                    filter!(x -> x.name != unit.name, r.thermal_units)
+                end
+                # append the name to the remove list
+                push!(units_to_remove, unit.name)
+            end
+        end
+        # unregister the units from the remove list
+        filter!(x -> !(x.name in units_to_remove), sc.thermal_units)
+    end
+
+    for unit in sc.thermal_units
+        # 2. set min generation requirement to 0 by adding 0 to production curve and cost 
+        # min_power & min_costs are vectors with dimension T
+        if unit.min_power[1] != 0
+            first_cost_segment = unit.cost_segments[1]
+            pushfirst!(
+                unit.cost_segments,
+                CostSegment(
+                    ones(size(first_cost_segment.mw)) * unit.min_power[1],
+                    ones(size(first_cost_segment.cost)) *
+                    unit.min_power_cost[1] / unit.min_power[1],
+                ),
+            )
+            unit.min_power = zeros(size(first_cost_segment.mw))
+            unit.min_power_cost = zeros(size(first_cost_segment.cost))
+        end
+
+        # 3. average the start-up costs (if considering)
+        # if consider_startup_costs = false, then use the current first_startup_cost
+        first_startup_cost = unit.startup_categories[1].cost
+        if method.consider_startup_costs
+            additional_unit_cost = first_startup_cost / unit.max_power[1]
+            for i in eachindex(unit.cost_segments)
+                unit.cost_segments[i].cost .+= additional_unit_cost
+            end
+            first_startup_cost = 0.0 # zero out the start up cost
+        end
+        unit.startup_categories =
+            StartupCategory[StartupCategory(0, first_startup_cost)]
+    end
+    return sc.thermal_units_by_name =
+        Dict(g.name => g for g in sc.thermal_units)
+end

src/lmp/conventional.jl

@@ -0,0 +1,92 @@
+# 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 JuMP
+
+"""
+    function compute_lmp(
+        model::JuMP.Model,
+        method::ConventionalLMP;
+        optimizer,
+    )::OrderedDict{Tuple{String,String,Int},Float64}
+
+Calculates conventional locational marginal prices of the given unit commitment
+instance. Returns a dictionary mapping `(bus_name, time)` to the marginal price.
+
+Arguments
+---------
+
+- `model`:
+    the UnitCommitment model, must be solved before calling this function.
+
+- `method`:
+    the LMP method.
+
+- `optimizer`:
+    the optimizer for solving the LP problem.
+
+Examples
+--------
+
+```julia
+using UnitCommitment
+using HiGHS
+
+import UnitCommitment: ConventionalLMP
+
+# Read benchmark instance
+instance = UnitCommitment.read_benchmark("matpower/case118/2018-01-01")
+
+# Build the model
+model = UnitCommitment.build_model(
+    instance = instance,
+    optimizer = HiGHS.Optimizer,
+)
+
+# Optimize the model
+UnitCommitment.optimize!(model)
+
+# Compute the LMPs using the conventional method
+lmp = UnitCommitment.compute_lmp(
+    model,
+    ConventionalLMP(),
+    optimizer = HiGHS.Optimizer,
+)
+
+# Access the LMPs
+# Example: "s1" is the scenario name, "b1" is the bus name, 1 is the first time slot
+@show lmp["s1", "b1", 1]
+```
+"""
+function compute_lmp(
+    model::JuMP.Model,
+    ::ConventionalLMP;
+    optimizer,
+)::OrderedDict{Tuple{String,String,Int},Float64}
+    if !has_values(model)
+        error("The UC model must be solved before calculating the LMPs.")
+    end
+    lmp = OrderedDict()
+
+    @info "Fixing binary variables and relaxing integrality..."
+    vals = Dict(v => value(v) for v in all_variables(model))
+    for v in all_variables(model)
+        if is_binary(v)
+            unset_binary(v)
+            fix(v, vals[v])
+        end
+    end
+    relax_integrality(model)
+    set_optimizer(model, optimizer)
+
+    @info "Solving the LP..."
+    JuMP.optimize!(model)
+
+    @info "Getting dual values (LMPs)..."
+    for (key, val) in model[:eq_net_injection]
+        lmp[key] = dual(val)
+    end
+
+    return lmp
+end

src/lmp/structs.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.
+
+abstract type PricingMethod end
+
+struct ConventionalLMP <: PricingMethod end
+
+"""
+    struct AELMP <: PricingMethod 
+        allow_offline_participation::Bool = true
+        consider_startup_costs::Bool = true
+    end
+
+Approximate Extended LMPs.
+
+Arguments
+---------
+
+- `allow_offline_participation`:
+    If true, offline assets are allowed to participate in pricing.
+- `consider_startup_costs`: 
+    If true, the start-up costs are averaged over each unit production; otherwise the production costs stay the same.
+"""
+Base.@kwdef struct AELMP <: PricingMethod
+    allow_offline_participation::Bool = true
+    consider_startup_costs::Bool = true
+end

src/model/build.jl

@@ -77,20 +77,30 @@ function build_model(;
         end
         model[:obj] = AffExpr()
         model[:instance] = instance
-        _setup_transmission(model, formulation.transmission)
+        for g in instance.scenarios[1].thermal_units
-        for l in instance.lines
+            _add_unit_commitment!(model, g, formulation)
-            _add_transmission_line!(model, l, formulation.transmission)
         end
-        for b in instance.buses
+        for sc in instance.scenarios
-            _add_bus!(model, b)
+            @info "Building scenario $(sc.name) with " *
+                  "probability $(sc.probability)"
+            _setup_transmission(formulation.transmission, sc)
+            for l in sc.lines
+                _add_transmission_line!(model, l, formulation.transmission, sc)
+            end
+            for b in sc.buses
+                _add_bus!(model, b, sc)
+            end
+            for ps in sc.price_sensitive_loads
+                _add_price_sensitive_load!(model, ps, sc)
+            end
+            for g in sc.thermal_units
+                _add_unit_dispatch!(model, g, formulation, sc)
+            end
+            for pu in sc.profiled_units
+                _add_profiled_unit!(model, pu, sc)
+            end
+            _add_system_wide_eqs!(model, sc)
         end
-        for g in instance.units
-            _add_unit!(model, g, formulation)
-        end
-        for ps in instance.price_sensitive_loads
-            _add_price_sensitive_load!(model, ps)
-        end
-        _add_system_wide_eqs!(model)
         @objective(model, Min, model[:obj])
     end
     @info @sprintf("Built model in %.2f seconds", time_model)

src/model/formulations/ArrCon2000/ramp.jl

@@ -4,10 +4,11 @@
 
 function _add_ramp_eqs!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation_prod_vars::Gar1962.ProdVars,
     formulation_ramping::ArrCon2000.Ramping,
     formulation_status_vars::Gar1962.StatusVars,
+    sc::UnitCommitmentScenario,
 )::Nothing
     # TODO: Move upper case constants to model[:instance]
     RESERVES_WHEN_START_UP = true
@@ -22,7 +23,7 @@ function _add_ramp_eqs!(
     eq_ramp_down = _init(model, :eq_ramp_down)
     eq_ramp_up = _init(model, :eq_ramp_up)
     is_initially_on = (g.initial_status > 0)
-    reserve = _total_reserves(model, g)
+    reserve = _total_reserves(model, g, sc)
 
     # Gar1962.ProdVars
     prod_above = model[:prod_above]
@@ -37,10 +38,10 @@ function _add_ramp_eqs!(
         if t == 1
             if is_initially_on
                 # min power is _not_ multiplied by is_on because if !is_on, then ramp up is irrelevant
-                eq_ramp_up[gn, t] = @constraint(
+                eq_ramp_up[sc.name, gn, t] = @constraint(
                     model,
                     g.min_power[t] +
-                    prod_above[gn, t] +
+                    prod_above[sc.name, gn, t] +
                     (RESERVES_WHEN_RAMP_UP ? reserve[t] : 0.0) <=
                     g.initial_power + RU
                 )
@@ -48,16 +49,16 @@ function _add_ramp_eqs!(
         else
             max_prod_this_period =
                 g.min_power[t] * is_on[gn, t] +
-                prod_above[gn, t] +
+                prod_above[sc.name, gn, t] +
                 (
                     RESERVES_WHEN_START_UP || RESERVES_WHEN_RAMP_UP ?
                     reserve[t] : 0.0
                 )
             min_prod_last_period =
-                g.min_power[t-1] * is_on[gn, t-1] + prod_above[gn, t-1]
+                g.min_power[t-1] * is_on[gn, t-1] + prod_above[sc.name, gn, t-1]
 
             # Equation (24) in Kneuven et al. (2020)
-            eq_ramp_up[gn, t] = @constraint(
+            eq_ramp_up[sc.name, gn, t] = @constraint(
                 model,
                 max_prod_this_period - min_prod_last_period <=
                 RU * is_on[gn, t-1] + SU * switch_on[gn, t]
@@ -71,24 +72,25 @@ function _add_ramp_eqs!(
                 #      min_power + RD < initial_power < SD
                 #      then the generator should be able to shut down at time t = 1,
                 #      but the constraint below will force the unit to produce power
-                eq_ramp_down[gn, t] = @constraint(
+                eq_ramp_down[sc.name, gn, t] = @constraint(
                     model,
-                    g.initial_power - (g.min_power[t] + prod_above[gn, t]) <= RD
+                    g.initial_power -
+                    (g.min_power[t] + prod_above[sc.name, gn, t]) <= RD
                 )
             end
         else
             max_prod_last_period =
                 g.min_power[t-1] * is_on[gn, t-1] +
-                prod_above[gn, t-1] +
+                prod_above[sc.name, gn, t-1] +
                 (
                     RESERVES_WHEN_SHUT_DOWN || RESERVES_WHEN_RAMP_DOWN ?
                     reserve[t-1] : 0.0
                 )
             min_prod_this_period =
-                g.min_power[t] * is_on[gn, t] + prod_above[gn, t]
+                g.min_power[t] * is_on[gn, t] + prod_above[sc.name, gn, t]
 
             # Equation (25) in Kneuven et al. (2020)
-            eq_ramp_down[gn, t] = @constraint(
+            eq_ramp_down[sc.name, gn, t] = @constraint(
                 model,
                 max_prod_last_period - min_prod_this_period <=
                 RD * is_on[gn, t] + SD * switch_off[gn, t]

src/model/formulations/CarArr2006/pwlcosts.jl

@@ -4,10 +4,11 @@
 
 function _add_production_piecewise_linear_eqs!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation_prod_vars::Gar1962.ProdVars,
     formulation_pwl_costs::CarArr2006.PwlCosts,
     formulation_status_vars::StatusVarsFormulation,
+    sc::UnitCommitmentScenario,
 )::Nothing
     eq_prod_above_def = _init(model, :eq_prod_above_def)
     eq_segprod_limit = _init(model, :eq_segprod_limit)
@@ -26,28 +27,32 @@ function _add_production_piecewise_linear_eqs!(
             #     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*
-            eq_segprod_limit[gn, t, k] = @constraint(
+            eq_segprod_limit[sc.name, gn, t, k] = @constraint(
                 model,
-                segprod[gn, t, k] <= g.cost_segments[k].mw[t]
+                segprod[sc.name, gn, t, k] <= g.cost_segments[k].mw[t]
             )
 
             # Also add this as an explicit upper bound on segprod to make the
             # solver's work a bit easier
-            set_upper_bound(segprod[gn, t, k], g.cost_segments[k].mw[t])
+            set_upper_bound(
+                segprod[sc.name, gn, t, k],
+                g.cost_segments[k].mw[t],
+            )
 
             # Definition of production
             # Equation (43) in Kneuven et al. (2020)
-            eq_prod_above_def[gn, t] = @constraint(
+            eq_prod_above_def[sc.name, gn, t] = @constraint(
                 model,
-                prod_above[gn, t] == sum(segprod[gn, t, k] for k in 1:K)
+                prod_above[sc.name, gn, t] ==
+                sum(segprod[sc.name, gn, t, k] for k in 1:K)
             )
 
             # Objective function
             # Equation (44) in Kneuven et al. (2020)
             add_to_expression!(
                 model[:obj],
-                segprod[gn, t, k],
+                segprod[sc.name, gn, t, k],
-                g.cost_segments[k].cost[t],
+                sc.probability * g.cost_segments[k].cost[t],
             )
         end
     end

src/model/formulations/DamKucRajAta2016/ramp.jl

@@ -4,10 +4,11 @@
 
 function _add_ramp_eqs!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation_prod_vars::Gar1962.ProdVars,
     formulation_ramping::DamKucRajAta2016.Ramping,
     formulation_status_vars::Gar1962.StatusVars,
+    sc::UnitCommitmentScenario,
 )::Nothing
     # TODO: Move upper case constants to model[:instance]
     RESERVES_WHEN_START_UP = true
@@ -23,7 +24,7 @@ function _add_ramp_eqs!(
     gn = g.name
     eq_str_ramp_down = _init(model, :eq_str_ramp_down)
     eq_str_ramp_up = _init(model, :eq_str_ramp_up)
-    reserve = _total_reserves(model, g)
+    reserve = _total_reserves(model, g, sc)
 
     # Gar1962.ProdVars
     prod_above = model[:prod_above]
@@ -48,15 +49,15 @@ function _add_ramp_eqs!(
         # end
 
         max_prod_this_period =
-            prod_above[gn, t] +
+            prod_above[sc.name, gn, t] +
             (RESERVES_WHEN_START_UP || RESERVES_WHEN_RAMP_UP ? reserve[t] : 0.0)
         min_prod_last_period = 0.0
         if t > 1 && time_invariant
-            min_prod_last_period = prod_above[gn, t-1]
+            min_prod_last_period = prod_above[sc.name, gn, t-1]
 
             # Equation (35) in Kneuven et al. (2020)
             # Sparser version of (24)
-            eq_str_ramp_up[gn, t] = @constraint(
+            eq_str_ramp_up[sc.name, gn, t] = @constraint(
                 model,
                 max_prod_this_period - min_prod_last_period <=
                 (SU - g.min_power[t] - RU) * switch_on[gn, t] +
@@ -65,7 +66,8 @@ function _add_ramp_eqs!(
         elseif (t == 1 && is_initially_on) || (t > 1 && !time_invariant)
             if t > 1
                 min_prod_last_period =
-                    prod_above[gn, t-1] + g.min_power[t-1] * is_on[gn, t-1]
+                    prod_above[sc.name, gn, t-1] +
+                    g.min_power[t-1] * is_on[gn, t-1]
             else
                 min_prod_last_period = max(g.initial_power, 0.0)
             end
@@ -76,7 +78,7 @@ function _add_ramp_eqs!(
 
             # Modified version of equation (35) in Kneuven et al. (2020)
             # Equivalent to (24)
-            eq_str_ramp_up[gn, t] = @constraint(
+            eq_str_ramp_up[sc.name, gn, t] = @constraint(
                 model,
                 max_prod_this_period - min_prod_last_period <=
                 (SU - RU) * switch_on[gn, t] + RU * is_on[gn, t]
@@ -88,7 +90,7 @@ function _add_ramp_eqs!(
                 t > 1 && (RESERVES_WHEN_SHUT_DOWN || RESERVES_WHEN_RAMP_DOWN) ?
                 reserve[t-1] : 0.0
             )
-        min_prod_this_period = prod_above[gn, t]
+        min_prod_this_period = prod_above[sc.name, gn, t]
         on_last_period = 0.0
         if t > 1
             on_last_period = is_on[gn, t-1]
@@ -98,7 +100,7 @@ function _add_ramp_eqs!(
 
         if t > 1 && time_invariant
             # Equation (36) in Kneuven et al. (2020)
-            eq_str_ramp_down[gn, t] = @constraint(
+            eq_str_ramp_down[sc.name, gn, t] = @constraint(
                 model,
                 max_prod_last_period - min_prod_this_period <=
                 (SD - g.min_power[t] - RD) * switch_off[gn, t] +
@@ -110,7 +112,7 @@ function _add_ramp_eqs!(
 
             # Modified version of equation (36) in Kneuven et al. (2020)
             # Equivalent to (25)
-            eq_str_ramp_down[gn, t] = @constraint(
+            eq_str_ramp_down[sc.name, gn, t] = @constraint(
                 model,
                 max_prod_last_period - min_prod_this_period <=
                 (SD - RD) * switch_off[gn, t] + RD * on_last_period

src/model/formulations/Gar1962/prod.jl

@@ -4,34 +4,35 @@
 
 function _add_production_vars!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation_prod_vars::Gar1962.ProdVars,
+    sc::UnitCommitmentScenario,
 )::Nothing
     prod_above = _init(model, :prod_above)
     segprod = _init(model, :segprod)
     for t in 1:model[:instance].time
         for k in 1:length(g.cost_segments)
-            segprod[g.name, t, k] = @variable(model, lower_bound = 0)
+            segprod[sc.name, g.name, t, k] = @variable(model, lower_bound = 0)
         end
-        prod_above[g.name, t] = @variable(model, lower_bound = 0)
+        prod_above[sc.name, g.name, t] = @variable(model, lower_bound = 0)
     end
     return
 end
 
 function _add_production_limit_eqs!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation_prod_vars::Gar1962.ProdVars,
+    sc::UnitCommitmentScenario,
 )::Nothing
     eq_prod_limit = _init(model, :eq_prod_limit)
     is_on = model[:is_on]
     prod_above = model[:prod_above]
-    reserve = _total_reserves(model, g)
+    reserve = _total_reserves(model, g, sc)
     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
-        add_to_expression!(model[:obj], is_on[gn, t], g.min_power_cost[t])
 
         # Production limit
         # Equation (18) in Kneuven et al. (2020)
@@ -42,9 +43,10 @@ function _add_production_limit_eqs!(
         if power_diff < 1e-7
             power_diff = 0.0
         end
-        eq_prod_limit[gn, t] = @constraint(
+        eq_prod_limit[sc.name, gn, t] = @constraint(
             model,
-            prod_above[gn, t] + reserve[t] <= power_diff * is_on[gn, t]
+            prod_above[sc.name, gn, t] + reserve[t] <=
+            power_diff * is_on[gn, t]
         )
     end
 end

src/model/formulations/Gar1962/pwlcosts.jl

@@ -4,10 +4,11 @@
 
 function _add_production_piecewise_linear_eqs!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation_prod_vars::Gar1962.ProdVars,
     formulation_pwl_costs::Gar1962.PwlCosts,
     formulation_status_vars::Gar1962.StatusVars,
+    sc::UnitCommitmentScenario,
 )::Nothing
     eq_prod_above_def = _init(model, :eq_prod_above_def)
     eq_segprod_limit = _init(model, :eq_segprod_limit)
@@ -24,9 +25,10 @@ function _add_production_piecewise_linear_eqs!(
     for t in 1:model[:instance].time
         # Definition of production
         # Equation (43) in Kneuven et al. (2020)
-        eq_prod_above_def[gn, t] = @constraint(
+        eq_prod_above_def[sc.name, gn, t] = @constraint(
             model,
-            prod_above[gn, t] == sum(segprod[gn, t, k] for k in 1:K)
+            prod_above[sc.name, gn, t] ==
+            sum(segprod[sc.name, gn, t, k] for k in 1:K)
         )
 
         for k in 1:K
@@ -37,21 +39,25 @@ function _add_production_piecewise_linear_eqs!(
             #     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*
-            eq_segprod_limit[gn, t, k] = @constraint(
+            eq_segprod_limit[sc.name, gn, t, k] = @constraint(
                 model,
-                segprod[gn, t, k] <= g.cost_segments[k].mw[t] * is_on[gn, t]
+                segprod[sc.name, gn, t, k] <=
+                g.cost_segments[k].mw[t] * is_on[gn, t]
             )
 
             # Also add this as an explicit upper bound on segprod to make the
             # solver's work a bit easier
-            set_upper_bound(segprod[gn, t, k], g.cost_segments[k].mw[t])
+            set_upper_bound(
+                segprod[sc.name, gn, t, k],
+                g.cost_segments[k].mw[t],
+            )
 
             # Objective function
             # Equation (44) in Kneuven et al. (2020)
             add_to_expression!(
                 model[:obj],
-                segprod[gn, t, k],
+                segprod[sc.name, gn, t, k],
-                g.cost_segments[k].cost[t],
+                sc.probability * g.cost_segments[k].cost[t],
             )
         end
     end

src/model/formulations/Gar1962/status.jl

@@ -4,7 +4,7 @@
 
 function _add_status_vars!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation_status_vars::Gar1962.StatusVars,
 )::Nothing
     is_on = _init(model, :is_on)
@@ -20,13 +20,14 @@ function _add_status_vars!(
             switch_on[g.name, t] = @variable(model, binary = true)
             switch_off[g.name, t] = @variable(model, binary = true)
         end
+        add_to_expression!(model[:obj], is_on[g.name, t], g.min_power_cost[t])
     end
     return
 end
 
 function _add_status_eqs!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation_status_vars::Gar1962.StatusVars,
 )::Nothing
     eq_binary_link = _init(model, :eq_binary_link)

src/model/formulations/KnuOstWat2018/pwlcosts.jl

@@ -4,10 +4,11 @@
 
 function _add_production_piecewise_linear_eqs!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation_prod_vars::Gar1962.ProdVars,
     formulation_pwl_costs::KnuOstWat2018.PwlCosts,
     formulation_status_vars::Gar1962.StatusVars,
+    sc::UnitCommitmentScenario,
 )::Nothing
     eq_prod_above_def = _init(model, :eq_prod_above_def)
     eq_segprod_limit_a = _init(model, :eq_segprod_limit_a)
@@ -58,27 +59,27 @@ function _add_production_piecewise_linear_eqs!(
 
             if g.min_uptime > 1
                 # Equation (46) in Kneuven et al. (2020)
-                eq_segprod_limit_a[gn, t, k] = @constraint(
+                eq_segprod_limit_a[sc.name, gn, t, k] = @constraint(
                     model,
-                    segprod[gn, t, k] <=
+                    segprod[sc.name, gn, t, k] <=
                     g.cost_segments[k].mw[t] * is_on[gn, t] -
                     Cv * switch_on[gn, t] -
                     (t < T ? Cw * switch_off[gn, t+1] : 0.0)
                 )
             else
                 # Equation (47a)/(48a) in Kneuven et al. (2020)
-                eq_segprod_limit_b[gn, t, k] = @constraint(
+                eq_segprod_limit_b[sc.name, gn, t, k] = @constraint(
                     model,
-                    segprod[gn, t, k] <=
+                    segprod[sc.name, gn, t, k] <=
                     g.cost_segments[k].mw[t] * is_on[gn, t] -
                     Cv * switch_on[gn, t] -
                     (t < T ? max(0, Cv - Cw) * switch_off[gn, t+1] : 0.0)
                 )
 
                 # Equation (47b)/(48b) in Kneuven et al. (2020)
-                eq_segprod_limit_c[gn, t, k] = @constraint(
+                eq_segprod_limit_c[sc.name, gn, t, k] = @constraint(
                     model,
-                    segprod[gn, t, k] <=
+                    segprod[sc.name, gn, t, k] <=
                     g.cost_segments[k].mw[t] * is_on[gn, t] -
                     max(0, Cw - Cv) * switch_on[gn, t] -
                     (t < T ? Cw * switch_off[gn, t+1] : 0.0)
@@ -87,22 +88,26 @@ function _add_production_piecewise_linear_eqs!(
 
             # Definition of production
             # Equation (43) in Kneuven et al. (2020)
-            eq_prod_above_def[gn, t] = @constraint(
+            eq_prod_above_def[sc.name, gn, t] = @constraint(
                 model,
-                prod_above[gn, t] == sum(segprod[gn, t, k] for k in 1:K)
+                prod_above[sc.name, gn, t] ==
+                sum(segprod[sc.name, gn, t, k] for k in 1:K)
             )
 
             # Objective function
             # Equation (44) in Kneuven et al. (2020)
             add_to_expression!(
                 model[:obj],
-                segprod[gn, t, k],
+                segprod[sc.name, gn, t, k],
                 g.cost_segments[k].cost[t],
             )
 
             # Also add an explicit upper bound on segprod to make the solver's
             # work a bit easier
-            set_upper_bound(segprod[gn, t, k], g.cost_segments[k].mw[t])
+            set_upper_bound(
+                segprod[sc.name, gn, t, k],
+                g.cost_segments[k].mw[t],
+            )
         end
     end
 end

src/model/formulations/MorLatRam2013/ramp.jl

@@ -4,10 +4,11 @@
 
 function _add_ramp_eqs!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation_prod_vars::Gar1962.ProdVars,
     formulation_ramping::MorLatRam2013.Ramping,
     formulation_status_vars::Gar1962.StatusVars,
+    sc::UnitCommitmentScenario,
 )::Nothing
     # TODO: Move upper case constants to model[:instance]
     RESERVES_WHEN_START_UP = true
@@ -22,7 +23,7 @@ function _add_ramp_eqs!(
     gn = g.name
     eq_ramp_down = _init(model, :eq_ramp_down)
     eq_ramp_up = _init(model, :eq_str_ramp_up)
-    reserve = _total_reserves(model, g)
+    reserve = _total_reserves(model, g, sc)
 
     # Gar1962.ProdVars
     prod_above = model[:prod_above]
@@ -39,10 +40,10 @@ function _add_ramp_eqs!(
         # Ramp up limit
         if t == 1
             if is_initially_on
-                eq_ramp_up[gn, t] = @constraint(
+                eq_ramp_up[sc.name, gn, t] = @constraint(
                     model,
                     g.min_power[t] +
-                    prod_above[gn, t] +
+                    prod_above[sc.name, gn, t] +
                     (RESERVES_WHEN_RAMP_UP ? reserve[t] : 0.0) <=
                     g.initial_power + RU
                 )
@@ -58,13 +59,14 @@ function _add_ramp_eqs!(
                 SU = g.startup_limit
                 max_prod_this_period =
                     g.min_power[t] * is_on[gn, t] +
-                    prod_above[gn, t] +
+                    prod_above[sc.name, gn, t] +
                     (
                         RESERVES_WHEN_START_UP || RESERVES_WHEN_RAMP_UP ?
                         reserve[t] : 0.0
                     )
                 min_prod_last_period =
-                    g.min_power[t-1] * is_on[gn, t-1] + prod_above[gn, t-1]
+                    g.min_power[t-1] * is_on[gn, t-1] +
+                    prod_above[sc.name, gn, t-1]
                 eq_ramp_up[gn, t] = @constraint(
                     model,
                     max_prod_this_period - min_prod_last_period <=
@@ -74,11 +76,11 @@ function _add_ramp_eqs!(
                 # Equation (26) in Kneuven 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(
+                eq_ramp_up[sc.name, gn, t] = @constraint(
                     model,
-                    prod_above[gn, t] +
+                    prod_above[sc.name, gn, t] +
                     (RESERVES_WHEN_RAMP_UP ? reserve[t] : 0.0) -
-                    prod_above[gn, t-1] <= RU
+                    prod_above[sc.name, gn, t-1] <= RU
                 )
             end
         end
@@ -90,9 +92,10 @@ function _add_ramp_eqs!(
                 #        min_power + RD < initial_power < SD
                 #      then the generator should be able to shut down at time t = 1,
                 #      but the constraint below will force the unit to produce power
-                eq_ramp_down[gn, t] = @constraint(
+                eq_ramp_down[sc.name, gn, t] = @constraint(
                     model,
-                    g.initial_power - (g.min_power[t] + prod_above[gn, t]) <= RD
+                    g.initial_power -
+                    (g.min_power[t] + prod_above[sc.name, gn, t]) <= RD
                 )
             end
         else
@@ -102,13 +105,13 @@ function _add_ramp_eqs!(
                 SD = g.shutdown_limit
                 max_prod_last_period =
                     g.min_power[t-1] * is_on[gn, t-1] +
-                    prod_above[gn, t-1] +
+                    prod_above[sc.name, gn, t-1] +
                     (
                         RESERVES_WHEN_SHUT_DOWN || RESERVES_WHEN_RAMP_DOWN ?
                         reserve[t-1] : 0.0
                     )
                 min_prod_this_period =
-                    g.min_power[t] * is_on[gn, t] + prod_above[gn, t]
+                    g.min_power[t] * is_on[gn, t] + prod_above[sc.name, gn, t]
                 eq_ramp_down[gn, t] = @constraint(
                     model,
                     max_prod_last_period - min_prod_this_period <=
@@ -118,11 +121,11 @@ function _add_ramp_eqs!(
                 # Equation (27) in Kneuven 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(
+                eq_ramp_down[sc.name, gn, t] = @constraint(
                     model,
-                    prod_above[gn, t-1] +
+                    prod_above[sc.name, gn, t-1] +
                     (RESERVES_WHEN_RAMP_DOWN ? reserve[t-1] : 0.0) -
-                    prod_above[gn, t] <= RD
+                    prod_above[sc.name, gn, t] <= RD
                 )
             end
         end

src/model/formulations/MorLatRam2013/scosts.jl

@@ -4,7 +4,7 @@
 
 function _add_startup_cost_eqs!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation::MorLatRam2013.StartupCosts,
 )::Nothing
     eq_startup_choose = _init(model, :eq_startup_choose)

src/model/formulations/PanGua2016/ramp.jl

@@ -4,15 +4,16 @@
 
 function _add_ramp_eqs!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation_prod_vars::Gar1962.ProdVars,
     formulation_ramping::PanGua2016.Ramping,
     formulation_status_vars::Gar1962.StatusVars,
+    sc::UnitCommitmentScenario,
 )::Nothing
     # TODO: Move upper case constants to model[:instance]
     RESERVES_WHEN_SHUT_DOWN = true
     gn = g.name
-    reserve = _total_reserves(model, g)
+    reserve = _total_reserves(model, g, sc)
     eq_str_prod_limit = _init(model, :eq_str_prod_limit)
     eq_prod_limit_ramp_up_extra_period =
         _init(model, :eq_prod_limit_ramp_up_extra_period)
@@ -52,9 +53,9 @@ function _add_ramp_eqs!(
             # Generalization of (20)
             # Necessary that if any of the switch_on = 1 in the sum,
             # then switch_off[gn, t+1] = 0
-            eq_str_prod_limit[gn, t] = @constraint(
+            eq_str_prod_limit[sc.name, gn, t] = @constraint(
                 model,
-                prod_above[gn, t] +
+                prod_above[sc.name, gn, t] +
                 g.min_power[t] * is_on[gn, t] +
                 reserve[t] <=
                 Pbar * is_on[gn, t] -
@@ -67,16 +68,17 @@ function _add_ramp_eqs!(
             if UT - 2 < TRU
                 # Equation (40) in Kneuven 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(
+                eq_prod_limit_ramp_up_extra_period[sc.name, gn, t] =
-                    model,
+                    @constraint(
-                    prod_above[gn, t] +
+                        model,
-                    g.min_power[t] * is_on[gn, t] +
+                        prod_above[sc.name, gn, t] +
-                    reserve[t] <=
+                        g.min_power[t] * is_on[gn, t] +
-                    Pbar * is_on[gn, t] - sum(
+                        reserve[t] <=
-                        (Pbar - (SU + i * RU)) * switch_on[gn, t-i] for
+                        Pbar * is_on[gn, t] - sum(
-                        i in 0:min(UT - 1, TRU, t - 1)
+                            (Pbar - (SU + i * RU)) * switch_on[gn, t-i] for
+                            i in 0:min(UT - 1, TRU, t - 1)
+                        )
                     )
-                )
             end
 
             # Add in shutdown trajectory if KSD >= 0 (else this is dominated by (38))
@@ -84,9 +86,9 @@ function _add_ramp_eqs!(
             if KSD > 0
                 KSU = min(TRU, UT - 2 - KSD, t - 1)
                 # Equation (41) in Kneuven et al. (2020)
-                eq_prod_limit_shutdown_trajectory[gn, t] = @constraint(
+                eq_prod_limit_shutdown_trajectory[sc.name, gn, t] = @constraint(
                     model,
-                    prod_above[gn, t] +
+                    prod_above[sc.name, gn, t] +
                     g.min_power[t] * is_on[gn, t] +
                     (RESERVES_WHEN_SHUT_DOWN ? reserve[t] : 0.0) <=
                     Pbar * is_on[gn, t] - sum(

src/model/formulations/WanHob2016/ramp.jl

@@ -4,10 +4,11 @@
 
 function _add_ramp_eqs!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     ::Gar1962.ProdVars,
     ::WanHob2016.Ramping,
     ::Gar1962.StatusVars,
+    sc::UnitCommitmentScenario,
 )::Nothing
     is_initially_on = (g.initial_status > 0)
     SU = g.startup_limit
@@ -38,41 +39,43 @@ function _add_ramp_eqs!(
         for t in 1:model[:instance].time
             @constraint(
                 model,
-                prod_above[gn, t] + (is_on[gn, t] * minp[t]) <= mfg[rn, gn, t]
+                prod_above[sc.name, gn, t] + (is_on[gn, t] * minp[t]) <=
+                mfg[sc.name, gn, t]
             ) # Eq. (19) in Wang & Hobbs (2016)
-            @constraint(model, mfg[rn, gn, t] <= is_on[gn, t] * maxp[t]) # Eq. (22) in Wang & Hobbs (2016)
+            @constraint(model, mfg[sc.name, gn, t] <= is_on[gn, t] * maxp[t]) # Eq. (22) in Wang & Hobbs (2016)
             if t != model[:instance].time
                 @constraint(
                     model,
                     minp[t] * (is_on[gn, t+1] + is_on[gn, t] - 1) <=
-                    prod_above[gn, t] - dwflexiramp[rn, gn, t] +
+                    prod_above[sc.name, gn, t] -
-                    (is_on[gn, t] * minp[t])
+                    dwflexiramp[sc.name, rn, gn, t] + (is_on[gn, t] * minp[t])
                 ) # first inequality of Eq. (20) in Wang & Hobbs (2016)
                 @constraint(
                     model,
-                    prod_above[gn, t] - dwflexiramp[rn, gn, t] +
+                    prod_above[sc.name, gn, t] -
+                    dwflexiramp[sc.name, rn, gn, t] +
                     (is_on[gn, t] * minp[t]) <=
-                    mfg[rn, gn, t+1] + (maxp[t] * (1 - is_on[gn, t+1]))
+                    mfg[sc.name, gn, t+1] + (maxp[t] * (1 - is_on[gn, t+1]))
                 ) # second inequality of Eq. (20) in Wang & Hobbs (2016)
                 @constraint(
                     model,
                     minp[t] * (is_on[gn, t+1] + is_on[gn, t] - 1) <=
-                    prod_above[gn, t] +
+                    prod_above[sc.name, gn, t] +
-                    upflexiramp[rn, gn, t] +
+                    upflexiramp[sc.name, rn, gn, t] +
                     (is_on[gn, t] * minp[t])
                 ) # first inequality of Eq. (21) in Wang & Hobbs (2016)
                 @constraint(
                     model,
-                    prod_above[gn, t] +
+                    prod_above[sc.name, gn, t] +
-                    upflexiramp[rn, gn, t] +
+                    upflexiramp[sc.name, rn, gn, t] +
                     (is_on[gn, t] * minp[t]) <=
-                    mfg[rn, gn, t+1] + (maxp[t] * (1 - is_on[gn, t+1]))
+                    mfg[sc.name, gn, t+1] + (maxp[t] * (1 - is_on[gn, t+1]))
                 ) # second inequality of Eq. (21) in Wang & Hobbs (2016)
                 if t != 1
                     @constraint(
                         model,
-                        mfg[rn, gn, t] <=
+                        mfg[sc.name, gn, t] <=
-                        prod_above[gn, t-1] +
+                        prod_above[sc.name, gn, t-1] +
                         (is_on[gn, t-1] * minp[t]) +
                         (RU * is_on[gn, t-1]) +
                         (SU * (is_on[gn, t] - is_on[gn, t-1])) +
@@ -80,8 +83,13 @@ function _add_ramp_eqs!(
                     ) # Eq. (23) in Wang & Hobbs (2016)
                     @constraint(
                         model,
-                        (prod_above[gn, t-1] + (is_on[gn, t-1] * minp[t])) -
+                        (
-                        (prod_above[gn, t] + (is_on[gn, t] * minp[t])) <=
+                            prod_above[sc.name, gn, t-1] +
+                            (is_on[gn, t-1] * minp[t])
+                        ) - (
+                            prod_above[sc.name, gn, t] +
+                            (is_on[gn, t] * minp[t])
+                        ) <=
                         RD * is_on[gn, t] +
                         SD * (is_on[gn, t-1] - is_on[gn, t]) +
                         maxp[t] * (1 - is_on[gn, t-1])
@@ -89,7 +97,7 @@ function _add_ramp_eqs!(
                 else
                     @constraint(
                         model,
-                        mfg[rn, gn, t] <=
+                        mfg[sc.name, gn, t] <=
                         initial_power +
                         (RU * is_initially_on) +
                         (SU * (is_on[gn, t] - is_initially_on)) +
@@ -97,8 +105,10 @@ function _add_ramp_eqs!(
                     ) # Eq. (23) in Wang & Hobbs (2016) for the first time period
                     @constraint(
                         model,
-                        initial_power -
+                        initial_power - (
-                        (prod_above[gn, t] + (is_on[gn, t] * minp[t])) <=
+                            prod_above[sc.name, gn, t] +
+                            (is_on[gn, t] * minp[t])
+                        ) <=
                         RD * is_on[gn, t] +
                         SD * (is_initially_on - is_on[gn, t]) +
                         maxp[t] * (1 - is_initially_on)
@@ -106,7 +116,7 @@ function _add_ramp_eqs!(
                 end
                 @constraint(
                     model,
-                    mfg[rn, gn, t] <=
+                    mfg[sc.name, gn, t] <=
                     (SD * (is_on[gn, t] - is_on[gn, t+1])) +
                     (maxp[t] * is_on[gn, t+1])
                 ) # Eq. (24) in Wang & Hobbs (2016)
@@ -114,11 +124,12 @@ function _add_ramp_eqs!(
                     model,
                     -RD * is_on[gn, t+1] -
                     SD * (is_on[gn, t] - is_on[gn, t+1]) -
-                    maxp[t] * (1 - is_on[gn, t]) <= upflexiramp[rn, gn, t]
+                    maxp[t] * (1 - is_on[gn, t]) <=
+                    upflexiramp[sc.name, rn, gn, t]
                 ) # first inequality of Eq. (26) in Wang & Hobbs (2016)
                 @constraint(
                     model,
-                    upflexiramp[rn, gn, t] <=
+                    upflexiramp[sc.name, rn, gn, t] <=
                     RU * is_on[gn, t] +
                     SU * (is_on[gn, t+1] - is_on[gn, t]) +
                     maxp[t] * (1 - is_on[gn, t+1])
@@ -126,11 +137,12 @@ function _add_ramp_eqs!(
                 @constraint(
                     model,
                     -RU * is_on[gn, t] - SU * (is_on[gn, t+1] - is_on[gn, t]) -
-                    maxp[t] * (1 - is_on[gn, t+1]) <= dwflexiramp[rn, gn, t]
+                    maxp[t] * (1 - is_on[gn, t+1]) <=
+                    dwflexiramp[sc.name, rn, gn, t]
                 ) # first inequality of Eq. (27) in Wang & Hobbs (2016)
                 @constraint(
                     model,
-                    dwflexiramp[rn, gn, t] <=
+                    dwflexiramp[sc.name, rn, gn, t] <=
                     RD * is_on[gn, t+1] +
                     SD * (is_on[gn, t] - is_on[gn, t+1]) +
                     maxp[t] * (1 - is_on[gn, t])
@@ -138,26 +150,27 @@ function _add_ramp_eqs!(
                 @constraint(
                     model,
                     -maxp[t] * is_on[gn, t] + minp[t] * is_on[gn, t+1] <=
-                    upflexiramp[rn, gn, t]
+                    upflexiramp[sc.name, rn, gn, t]
                 ) # first inequality of Eq. (28) in Wang & Hobbs (2016)
                 @constraint(
                     model,
-                    upflexiramp[rn, gn, t] <= maxp[t] * is_on[gn, t+1]
+                    upflexiramp[sc.name, rn, gn, t] <= maxp[t] * is_on[gn, t+1]
                 ) # second inequality of Eq. (28) in Wang & Hobbs (2016)
                 @constraint(
                     model,
-                    -maxp[t] * is_on[gn, t+1] <= dwflexiramp[rn, gn, t]
+                    -maxp[t] * is_on[gn, t+1] <=
+                    dwflexiramp[sc.name, rn, gn, t]
                 ) # first inequality of Eq. (29) in Wang & Hobbs (2016)
                 @constraint(
                     model,
-                    dwflexiramp[rn, gn, t] <=
+                    dwflexiramp[sc.name, rn, gn, t] <=
                     (maxp[t] * is_on[gn, t]) - (minp[t] * is_on[gn, t+1])
                 ) # second inequality of Eq. (29) in Wang & Hobbs (2016)
             else
                 @constraint(
                     model,
-                    mfg[rn, gn, t] <=
+                    mfg[sc.name, gn, t] <=
-                    prod_above[gn, t-1] +
+                    prod_above[sc.name, gn, t-1] +
                     (is_on[gn, t-1] * minp[t]) +
                     (RU * is_on[gn, t-1]) +
                     (SU * (is_on[gn, t] - is_on[gn, t-1])) +
@@ -165,8 +178,11 @@ function _add_ramp_eqs!(
                 ) # Eq. (23) in Wang & Hobbs (2016) for the last time period
                 @constraint(
                     model,
-                    (prod_above[gn, t-1] + (is_on[gn, t-1] * minp[t])) -
+                    (
-                    (prod_above[gn, t] + (is_on[gn, t] * minp[t])) <=
+                        prod_above[sc.name, gn, t-1] +
+                        (is_on[gn, t-1] * minp[t])
+                    ) -
+                    (prod_above[sc.name, gn, t] + (is_on[gn, t] * minp[t])) <=
                     RD * is_on[gn, t] +
                     SD * (is_on[gn, t-1] - is_on[gn, t]) +
                     maxp[t] * (1 - is_on[gn, t-1])

src/model/formulations/base/bus.jl

@@ -2,22 +2,30 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-function _add_bus!(model::JuMP.Model, b::Bus)::Nothing
+function _add_bus!(
+    model::JuMP.Model,
+    b::Bus,
+    sc::UnitCommitmentScenario,
+)::Nothing
     net_injection = _init(model, :expr_net_injection)
     curtail = _init(model, :curtail)
     for t in 1:model[:instance].time
         # Fixed load
-        net_injection[b.name, t] = AffExpr(-b.load[t])
+        net_injection[sc.name, b.name, t] = AffExpr(-b.load[t])
 
         # Load curtailment
-        curtail[b.name, t] =
+        curtail[sc.name, b.name, t] =
             @variable(model, lower_bound = 0, upper_bound = b.load[t])
 
-        add_to_expression!(net_injection[b.name, t], curtail[b.name, t], 1.0)
+        add_to_expression!(
+            net_injection[sc.name, b.name, t],
+            curtail[sc.name, b.name, t],
+            1.0,
+        )
         add_to_expression!(
             model[:obj],
-            curtail[b.name, t],
+            curtail[sc.name, b.name, t],
-            model[:instance].power_balance_penalty[t],
+            sc.power_balance_penalty[t] * sc.probability,
         )
     end
     return

src/model/formulations/base/line.jl

@@ -6,43 +6,43 @@ function _add_transmission_line!(
     model::JuMP.Model,
     lm::TransmissionLine,
     f::ShiftFactorsFormulation,
+    sc::UnitCommitmentScenario,
 )::Nothing
     overflow = _init(model, :overflow)
     for t in 1:model[:instance].time
-        overflow[lm.name, t] = @variable(model, lower_bound = 0)
+        overflow[sc.name, lm.name, t] = @variable(model, lower_bound = 0)
         add_to_expression!(
             model[:obj],
-            overflow[lm.name, t],
+            overflow[sc.name, lm.name, t],
-            lm.flow_limit_penalty[t],
+            lm.flow_limit_penalty[t] * sc.probability,
         )
     end
     return
 end
 
 function _setup_transmission(
-    model::JuMP.Model,
     formulation::ShiftFactorsFormulation,
+    sc::UnitCommitmentScenario,
 )::Nothing
-    instance = model[:instance]
     isf = formulation.precomputed_isf
     lodf = formulation.precomputed_lodf
-    if length(instance.buses) == 1
+    if length(sc.buses) == 1
         isf = zeros(0, 0)
         lodf = zeros(0, 0)
     elseif isf === nothing
         @info "Computing injection shift factors..."
         time_isf = @elapsed begin
             isf = UnitCommitment._injection_shift_factors(
-                lines = instance.lines,
+                buses = sc.buses,
-                buses = instance.buses,
+                lines = sc.lines,
             )
         end
         @info @sprintf("Computed ISF in %.2f seconds", time_isf)
         @info "Computing line outage factors..."
         time_lodf = @elapsed begin
             lodf = UnitCommitment._line_outage_factors(
-                lines = instance.lines,
+                buses = sc.buses,
-                buses = instance.buses,
+                lines = sc.lines,
                 isf = isf,
             )
         end
@@ -55,7 +55,7 @@ function _setup_transmission(
         isf[abs.(isf).<formulation.isf_cutoff] .= 0
         lodf[abs.(lodf).<formulation.lodf_cutoff] .= 0
     end
-    model[:isf] = isf
+    sc.isf = isf
-    model[:lodf] = lodf
+    sc.lodf = lodf
     return
 end

src/model/formulations/base/psload.jl

@@ -5,21 +5,26 @@
 function _add_price_sensitive_load!(
     model::JuMP.Model,
     ps::PriceSensitiveLoad,
+    sc::UnitCommitmentScenario,
 )::Nothing
     loads = _init(model, :loads)
     net_injection = _init(model, :expr_net_injection)
     for t in 1:model[:instance].time
         # Decision variable
-        loads[ps.name, t] =
+        loads[sc.name, ps.name, t] =
             @variable(model, lower_bound = 0, upper_bound = ps.demand[t])
 
         # Objective function terms
-        add_to_expression!(model[:obj], loads[ps.name, t], -ps.revenue[t])
+        add_to_expression!(
+            model[:obj],
+            loads[sc.name, ps.name, t],
+            -ps.revenue[t] * sc.probability,
+        )
 
         # Net injection
         add_to_expression!(
-            net_injection[ps.bus.name, t],
+            net_injection[sc.name, ps.bus.name, t],
-            loads[ps.name, t],
+            loads[sc.name, ps.name, t],
             -1.0,
         )
     end

src/model/formulations/base/punit.jl

@@ -0,0 +1,35 @@
+# 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.
+
+function _add_profiled_unit!(
+    model::JuMP.Model,
+    pu::ProfiledUnit,
+    sc::UnitCommitmentScenario,
+)::Nothing
+    punits = _init(model, :prod_profiled)
+    net_injection = _init(model, :expr_net_injection)
+    for t in 1:model[:instance].time
+        # Decision variable
+        punits[sc.name, pu.name, t] = @variable(
+            model,
+            lower_bound = pu.min_power[t],
+            upper_bound = pu.max_power[t]
+        )
+
+        # Objective function terms
+        add_to_expression!(
+            model[:obj],
+            punits[sc.name, pu.name, t],
+            pu.cost[t] * sc.probability,
+        )
+
+        # Net injection
+        add_to_expression!(
+            net_injection[sc.name, pu.bus.name, t],
+            punits[sc.name, pu.name, t],
+            1.0,
+        )
+    end
+    return
+end

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/system.jl

@@ -2,54 +2,68 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-function _add_system_wide_eqs!(model::JuMP.Model)::Nothing
+function _add_system_wide_eqs!(
-    _add_net_injection_eqs!(model)
+    model::JuMP.Model,
-    _add_spinning_reserve_eqs!(model)
+    sc::UnitCommitmentScenario,
-    _add_flexiramp_reserve_eqs!(model)
+)::Nothing
+    _add_net_injection_eqs!(model, sc)
+    _add_spinning_reserve_eqs!(model, sc)
+    _add_flexiramp_reserve_eqs!(model, sc)
     return
 end
 
-function _add_net_injection_eqs!(model::JuMP.Model)::Nothing
+function _add_net_injection_eqs!(
+    model::JuMP.Model,
+    sc::UnitCommitmentScenario,
+)::Nothing
     T = model[:instance].time
     net_injection = _init(model, :net_injection)
     eq_net_injection = _init(model, :eq_net_injection)
     eq_power_balance = _init(model, :eq_power_balance)
-    for t in 1:T, b in model[:instance].buses
+    for t in 1:T, b in sc.buses
-        n = net_injection[b.name, t] = @variable(model)
+        n = net_injection[sc.name, b.name, t] = @variable(model)
-        eq_net_injection[b.name, t] =
+        eq_net_injection[sc.name, b.name, t] = @constraint(
-            @constraint(model, -n + model[:expr_net_injection][b.name, t] == 0)
+            model,
+            -n + model[:expr_net_injection][sc.name, b.name, t] == 0
+        )
     end
     for t in 1:T
-        eq_power_balance[t] = @constraint(
+        eq_power_balance[sc.name, t] = @constraint(
             model,
-            sum(net_injection[b.name, t] for b in model[:instance].buses) == 0
+            sum(net_injection[sc.name, b.name, t] for b in sc.buses) == 0
         )
     end
     return
 end
 
-function _add_spinning_reserve_eqs!(model::JuMP.Model)::Nothing
+function _add_spinning_reserve_eqs!(
-    instance = model[:instance]
+    model::JuMP.Model,
+    sc::UnitCommitmentScenario,
+)::Nothing
+    T = model[:instance].time
     eq_min_spinning_reserve = _init(model, :eq_min_spinning_reserve)
-    for r in instance.reserves
+    for r in sc.reserves
         r.type == "spinning" || continue
-        for t in 1:instance.time
+        for t in 1:T
             # 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)
-            eq_min_spinning_reserve[r.name, t] = @constraint(
+            eq_min_spinning_reserve[sc.name, r.name, t] = @constraint(
                 model,
-                sum(model[:reserve][r.name, g.name, t] for g in r.units) +
+                sum(
-                model[:reserve_shortfall][r.name, t] >= r.amount[t]
+                    model[:reserve][sc.name, r.name, g.name, t] for
+                    g in r.thermal_units
+                ) + model[:reserve_shortfall][sc.name, r.name, t] >=
+                r.amount[t]
             )
 
             # Account for shortfall contribution to objective
             if r.shortfall_penalty >= 0
                 add_to_expression!(
                     model[:obj],
-                    r.shortfall_penalty,
+                    r.shortfall_penalty * sc.probability,
-                    model[:reserve_shortfall][r.name, t],
+                    model[:reserve_shortfall][sc.name, r.name, t],
                 )
             end
         end
@@ -57,7 +71,10 @@ function _add_spinning_reserve_eqs!(model::JuMP.Model)::Nothing
     return
 end
 
-function _add_flexiramp_reserve_eqs!(model::JuMP.Model)::Nothing
+function _add_flexiramp_reserve_eqs!(
+    model::JuMP.Model,
+    sc::UnitCommitmentScenario,
+)::Nothing
     # Note: The flexpramp requirements in Wang & Hobbs (2016) are imposed as hard constraints 
     #       through Eq. (17) and Eq. (18). The constraints eq_min_upflexiramp and eq_min_dwflexiramp 
     #       provided below are modified versions of Eq. (17) and Eq. (18), respectively, in that   
@@ -65,29 +82,37 @@ function _add_flexiramp_reserve_eqs!(model::JuMP.Model)::Nothing
     #       objective function.
     eq_min_upflexiramp = _init(model, :eq_min_upflexiramp)
     eq_min_dwflexiramp = _init(model, :eq_min_dwflexiramp)
-    instance = model[:instance]
+    T = model[:instance].time
-    for r in instance.reserves
+    for r in sc.reserves
         r.type == "flexiramp" || continue
-        for t in 1:instance.time
+        for t in 1:T
             # Eq. (17) in Wang & Hobbs (2016)
-            eq_min_upflexiramp[r.name, t] = @constraint(
+            eq_min_upflexiramp[sc.name, r.name, t] = @constraint(
                 model,
-                sum(model[:upflexiramp][r.name, g.name, t] for g in r.units) + model[:upflexiramp_shortfall][r.name, t] >= r.amount[t]
+                sum(
+                    model[:upflexiramp][sc.name, r.name, g.name, t] for
+                    g in r.thermal_units
+                ) + model[:upflexiramp_shortfall][sc.name, r.name, t] >=
+                r.amount[t]
             )
             # Eq. (18) in Wang & Hobbs (2016)
-            eq_min_dwflexiramp[r.name, t] = @constraint(
+            eq_min_dwflexiramp[sc.name, r.name, t] = @constraint(
                 model,
-                sum(model[:dwflexiramp][r.name, g.name, t] for g in r.units) + model[:dwflexiramp_shortfall][r.name, t] >= r.amount[t]
+                sum(
+                    model[:dwflexiramp][sc.name, r.name, g.name, t] for
+                    g in r.thermal_units
+                ) + model[:dwflexiramp_shortfall][sc.name, r.name, t] >=
+                r.amount[t]
             )
 
             # Account for flexiramp shortfall contribution to objective
             if r.shortfall_penalty >= 0
                 add_to_expression!(
                     model[:obj],
-                    r.shortfall_penalty,
+                    r.shortfall_penalty * sc.probability,
                     (
-                        model[:upflexiramp_shortfall][r.name, t] +
+                        model[:upflexiramp_shortfall][sc.name, r.name, t] +
-                        model[:dwflexiramp_shortfall][r.name, t]
+                        model[:dwflexiramp_shortfall][sc.name, r.name, t]
                     ),
                 )
             end

src/model/formulations/base/unit.jl

@@ -2,7 +2,13 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-function _add_unit!(model::JuMP.Model, g::Unit, formulation::Formulation)
+# Function for adding variables, constraints, and objective function terms
+# related to the binary commitment, startup and shutdown decisions of units
+function _add_unit_commitment!(
+    model::JuMP.Model,
+    g::ThermalUnit,
+    formulation::Formulation,
+)
     if !all(g.must_run) && any(g.must_run)
         error("Partially must-run units are not currently supported")
     end
@@ -11,22 +17,41 @@ function _add_unit!(model::JuMP.Model, g::Unit, formulation::Formulation)
     end
 
     # Variables
-    _add_production_vars!(model, g, formulation.prod_vars)
-    _add_spinning_reserve_vars!(model, g)
-    _add_flexiramp_reserve_vars!(model, g)
     _add_startup_shutdown_vars!(model, g)
     _add_status_vars!(model, g, formulation.status_vars)
 
     # Constraints and objective function
     _add_min_uptime_downtime_eqs!(model, g)
-    _add_net_injection_eqs!(model, g)
+    _add_startup_cost_eqs!(model, g, formulation.startup_costs)
-    _add_production_limit_eqs!(model, g, formulation.prod_vars)
+    _add_status_eqs!(model, g, formulation.status_vars)
+    _add_commitment_status_eqs!(model, g)
+    return
+end
+
+# Function for adding variables, constraints, and objective function terms
+# related to the continuous dispatch decisions of units
+function _add_unit_dispatch!(
+    model::JuMP.Model,
+    g::ThermalUnit,
+    formulation::Formulation,
+    sc::UnitCommitmentScenario,
+)
+
+    # Variables
+    _add_production_vars!(model, g, formulation.prod_vars, sc)
+    _add_spinning_reserve_vars!(model, g, sc)
+    _add_flexiramp_reserve_vars!(model, g, sc)
+
+    # Constraints and objective function
+    _add_net_injection_eqs!(model, g, sc)
+    _add_production_limit_eqs!(model, g, formulation.prod_vars, sc)
     _add_production_piecewise_linear_eqs!(
         model,
         g,
         formulation.prod_vars,
         formulation.pwl_costs,
         formulation.status_vars,
+        sc,
     )
     _add_ramp_eqs!(
         model,
@@ -34,26 +59,31 @@ function _add_unit!(model::JuMP.Model, g::Unit, formulation::Formulation)
         formulation.prod_vars,
         formulation.ramping,
         formulation.status_vars,
+        sc,
     )
-    _add_startup_cost_eqs!(model, g, formulation.startup_costs)
+    _add_startup_shutdown_limit_eqs!(model, g, sc)
-    _add_startup_shutdown_limit_eqs!(model, g)
-    _add_status_eqs!(model, g, formulation.status_vars)
     return
 end
 
-_is_initially_on(g::Unit)::Float64 = (g.initial_status > 0 ? 1.0 : 0.0)
+_is_initially_on(g::ThermalUnit)::Float64 = (g.initial_status > 0 ? 1.0 : 0.0)
 
-function _add_spinning_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
+function _add_spinning_reserve_vars!(
+    model::JuMP.Model,
+    g::ThermalUnit,
+    sc::UnitCommitmentScenario,
+)::Nothing
     reserve = _init(model, :reserve)
     reserve_shortfall = _init(model, :reserve_shortfall)
     for r in g.reserves
         r.type == "spinning" || continue
         for t in 1:model[:instance].time
-            reserve[r.name, g.name, t] = @variable(model, lower_bound = 0)
+            reserve[sc.name, r.name, g.name, t] =
-            if (r.name, t) ∉ keys(reserve_shortfall)
+                @variable(model, lower_bound = 0)
-                reserve_shortfall[r.name, t] = @variable(model, lower_bound = 0)
+            if (sc.name, r.name, t) ∉ keys(reserve_shortfall)
+                reserve_shortfall[sc.name, r.name, t] =
+                    @variable(model, lower_bound = 0)
                 if r.shortfall_penalty < 0
-                    set_upper_bound(reserve_shortfall[r.name, t], 0.0)
+                    set_upper_bound(reserve_shortfall[sc.name, r.name, t], 0.0)
                 end
             end
         end
@@ -61,27 +91,37 @@ function _add_spinning_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
     return
 end
 
-function _add_flexiramp_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
+function _add_flexiramp_reserve_vars!(
+    model::JuMP.Model,
+    g::ThermalUnit,
+    sc::UnitCommitmentScenario,
+)::Nothing
     upflexiramp = _init(model, :upflexiramp)
     upflexiramp_shortfall = _init(model, :upflexiramp_shortfall)
     mfg = _init(model, :mfg)
     dwflexiramp = _init(model, :dwflexiramp)
     dwflexiramp_shortfall = _init(model, :dwflexiramp_shortfall)
-    for r in g.reserves
+    for t in 1:model[:instance].time
-        r.type == "flexiramp" || continue
+        # maximum feasible generation, \bar{g_{its}} in Wang & Hobbs (2016)
-        for t in 1:model[:instance].time
+        mfg[sc.name, g.name, t] = @variable(model, lower_bound = 0)
-            # maximum feasible generation, \bar{g_{its}} in Wang & Hobbs (2016)
+        for r in g.reserves
-            mfg[r.name, g.name, t] = @variable(model, lower_bound = 0)
+            r.type == "flexiramp" || continue
-            upflexiramp[r.name, g.name, t] = @variable(model) # up-flexiramp, ur_{it} in Wang & Hobbs (2016)
+            upflexiramp[sc.name, r.name, g.name, t] = @variable(model) # up-flexiramp, ur_{it} in Wang & Hobbs (2016)
-            dwflexiramp[r.name, g.name, t] = @variable(model) # down-flexiramp, dr_{it} in Wang & Hobbs (2016)
+            dwflexiramp[sc.name, r.name, g.name, t] = @variable(model) # down-flexiramp, dr_{it} in Wang & Hobbs (2016)
-            if (r.name, t) ∉ keys(upflexiramp_shortfall)
+            if (sc.name, r.name, t) ∉ keys(upflexiramp_shortfall)
-                upflexiramp_shortfall[r.name, t] =
+                upflexiramp_shortfall[sc.name, r.name, t] =
                     @variable(model, lower_bound = 0)
-                dwflexiramp_shortfall[r.name, t] =
+                dwflexiramp_shortfall[sc.name, r.name, t] =
                     @variable(model, lower_bound = 0)
                 if r.shortfall_penalty < 0
-                    set_upper_bound(upflexiramp_shortfall[r.name, t], 0.0)
+                    set_upper_bound(
-                    set_upper_bound(dwflexiramp_shortfall[r.name, t], 0.0)
+                        upflexiramp_shortfall[sc.name, r.name, t],
+                        0.0,
+                    )
+                    set_upper_bound(
+                        dwflexiramp_shortfall[sc.name, r.name, t],
+                        0.0,
+                    )
                 end
             end
         end
@@ -89,7 +129,7 @@ function _add_flexiramp_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
     return
 end
 
-function _add_startup_shutdown_vars!(model::JuMP.Model, g::Unit)::Nothing
+function _add_startup_shutdown_vars!(model::JuMP.Model, g::ThermalUnit)::Nothing
     startup = _init(model, :startup)
     for t in 1:model[:instance].time
         for s in 1:length(g.startup_categories)
@@ -99,32 +139,36 @@ 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
+function _add_startup_shutdown_limit_eqs!(
+    model::JuMP.Model,
+    g::ThermalUnit,
+    sc::UnitCommitmentScenario,
+)::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 = _total_reserves(model, g)
+    reserve = _total_reserves(model, g, sc)
     switch_off = model[:switch_off]
     switch_on = model[:switch_on]
     T = model[:instance].time
     for t in 1:T
         # Startup limit
-        eq_startup_limit[g.name, t] = @constraint(
+        eq_startup_limit[sc.name, g.name, t] = @constraint(
             model,
-            prod_above[g.name, t] + reserve[t] <=
+            prod_above[sc.name, g.name, t] + reserve[t] <=
             (g.max_power[t] - g.min_power[t]) * is_on[g.name, t] -
             max(0, g.max_power[t] - g.startup_limit) * switch_on[g.name, t]
         )
         # Shutdown limit
         if g.initial_power > g.shutdown_limit
-            eq_shutdown_limit[g.name, 0] =
+            eq_shutdown_limit[sc.name, g.name, 0] =
                 @constraint(model, switch_off[g.name, 1] <= 0)
         end
         if t < T
-            eq_shutdown_limit[g.name, t] = @constraint(
+            eq_shutdown_limit[sc.name, g.name, t] = @constraint(
                 model,
-                prod_above[g.name, t] <=
+                prod_above[sc.name, g.name, t] <=
                 (g.max_power[t] - g.min_power[t]) * is_on[g.name, t] -
                 max(0, g.max_power[t] - g.shutdown_limit) *
                 switch_off[g.name, t+1]
@@ -136,51 +180,55 @@ end
 
 function _add_ramp_eqs!(
     model::JuMP.Model,
-    g::Unit,
+    g::ThermalUnit,
     formulation::RampingFormulation,
+    sc::UnitCommitmentScenario,
 )::Nothing
     prod_above = model[:prod_above]
-    reserve = _total_reserves(model, g)
+    reserve = _total_reserves(model, g, sc)
     eq_ramp_up = _init(model, :eq_ramp_up)
     eq_ramp_down = _init(model, :eq_ramp_down)
     for t in 1:model[:instance].time
         # Ramp up limit 
         if t == 1
             if _is_initially_on(g) == 1
-                eq_ramp_up[g.name, t] = @constraint(
+                eq_ramp_up[sc.name, g.name, t] = @constraint(
                     model,
-                    prod_above[g.name, t] + reserve[t] <=
+                    prod_above[sc.name, g.name, t] + reserve[t] <=
                     (g.initial_power - g.min_power[t]) + g.ramp_up_limit
                 )
             end
         else
-            eq_ramp_up[g.name, t] = @constraint(
+            eq_ramp_up[sc.name, g.name, t] = @constraint(
                 model,
-                prod_above[g.name, t] + reserve[t] <=
+                prod_above[sc.name, g.name, t] + reserve[t] <=
-                prod_above[g.name, t-1] + g.ramp_up_limit
+                prod_above[sc.name, g.name, t-1] + g.ramp_up_limit
             )
         end
 
         # Ramp down limit
         if t == 1
             if _is_initially_on(g) == 1
-                eq_ramp_down[g.name, t] = @constraint(
+                eq_ramp_down[sc.name, g.name, t] = @constraint(
                     model,
-                    prod_above[g.name, t] >=
+                    prod_above[sc.name, g.name, t] >=
                     (g.initial_power - g.min_power[t]) - g.ramp_down_limit
                 )
             end
         else
-            eq_ramp_down[g.name, t] = @constraint(
+            eq_ramp_down[sc.name, g.name, t] = @constraint(
                 model,
-                prod_above[g.name, t] >=
+                prod_above[sc.name, g.name, t] >=
-                prod_above[g.name, t-1] - g.ramp_down_limit
+                prod_above[sc.name, g.name, t-1] - g.ramp_down_limit
             )
         end
     end
 end
 
-function _add_min_uptime_downtime_eqs!(model::JuMP.Model, g::Unit)::Nothing
+function _add_min_uptime_downtime_eqs!(
+    model::JuMP.Model,
+    g::ThermalUnit,
+)::Nothing
     is_on = model[:is_on]
     switch_off = model[:switch_off]
     switch_on = model[:switch_on]
@@ -223,30 +271,52 @@ function _add_min_uptime_downtime_eqs!(model::JuMP.Model, g::Unit)::Nothing
     end
 end
 
-function _add_net_injection_eqs!(model::JuMP.Model, g::Unit)::Nothing
+function _add_commitment_status_eqs!(model::JuMP.Model, g::ThermalUnit)::Nothing
+    is_on = model[:is_on]
+    T = model[:instance].time
+    eq_commitment_status = _init(model, :eq_commitment_status)
+    for t in 1:T
+        if g.commitment_status[t] !== nothing
+            eq_commitment_status[g.name, t] = @constraint(
+                model,
+                is_on[g.name, t] == (g.commitment_status[t] ? 1.0 : 0.0)
+            )
+        end
+    end
+    return
+end
+
+function _add_net_injection_eqs!(
+    model::JuMP.Model,
+    g::ThermalUnit,
+    sc::UnitCommitmentScenario,
+)::Nothing
     expr_net_injection = model[:expr_net_injection]
     for t in 1:model[:instance].time
         # Add to net injection expression
         add_to_expression!(
-            expr_net_injection[g.bus.name, t],
+            expr_net_injection[sc.name, g.bus.name, t],
-            model[:prod_above][g.name, t],
+            model[:prod_above][sc.name, g.name, t],
             1.0,
         )
         add_to_expression!(
-            expr_net_injection[g.bus.name, t],
+            expr_net_injection[sc.name, g.bus.name, t],
             model[:is_on][g.name, t],
             g.min_power[t],
         )
     end
 end
 
-function _total_reserves(model, g)::Vector
+function _total_reserves(model, g, sc)::Vector
     T = model[:instance].time
     reserve = [0.0 for _ in 1:T]
     spinning_reserves = [r for r in g.reserves if r.type == "spinning"]
     if !isempty(spinning_reserves)
         reserve += [
-            sum(model[:reserve][r.name, g.name, t] for r in spinning_reserves) for t in 1:model[:instance].time
+            sum(
+                model[:reserve][sc.name, r.name, g.name, t] for
+                r in spinning_reserves
+            ) for t in 1:model[:instance].time
         ]
     end
     return reserve

src/solution/fix.jl

@@ -10,37 +10,43 @@ solution. Useful for computing LMPs.
 """
 function fix!(model::JuMP.Model, solution::AbstractDict)::Nothing
     instance, T = model[:instance], model[:instance].time
+    "Thermal production (MW)" ∈ keys(solution) ?
+    solution = Dict("s1" => solution) : nothing
     is_on = model[:is_on]
     prod_above = model[:prod_above]
     reserve = model[:reserve]
-    for g in instance.units
+    for sc in instance.scenarios
-        for t in 1:T
+        for g in sc.thermal_units
-            is_on_value = round(solution["Is on"][g.name][t])
-            prod_value =
-                round(solution["Production (MW)"][g.name][t], digits = 5)
-            JuMP.fix(is_on[g.name, t], is_on_value, force = true)
-            JuMP.fix(
-                prod_above[g.name, t],
-                prod_value - is_on_value * g.min_power[t],
-                force = true,
-            )
-        end
-    end
-    for r in instance.reserves
-        r.type == "spinning" || continue
-        for g in r.units
             for t in 1:T
-                reserve_value = round(
+                is_on_value = round(solution[sc.name]["Is on"][g.name][t])
-                    solution["Spinning reserve (MW)"][r.name][g.name][t],
+                prod_value = round(
+                    solution[sc.name]["Thermal production (MW)"][g.name][t],
                     digits = 5,
                 )
+                JuMP.fix(is_on[g.name, t], is_on_value, force = true)
                 JuMP.fix(
-                    reserve[r.name, g.name, t],
+                    prod_above[sc.name, g.name, t],
-                    reserve_value,
+                    prod_value - is_on_value * g.min_power[t],
                     force = true,
                 )
             end
         end
+        for r in sc.reserves
+            r.type == "spinning" || continue
+            for g in r.thermal_units
+                for t in 1:T
+                    reserve_value = round(
+                        solution[sc.name]["Spinning reserve (MW)"][r.name][g.name][t],
+                        digits = 5,
+                    )
+                    JuMP.fix(
+                        reserve[sc.name, r.name, g.name, t],
+                        reserve_value,
+                        force = true,
+                    )
+                end
+            end
+        end
     end
     return
 end

src/solution/methods/XavQiuWanThi2019/enforce.jl

@@ -5,13 +5,15 @@
 function _enforce_transmission(
     model::JuMP.Model,
     violations::Vector{_Violation},
+    sc::UnitCommitmentScenario,
 )::Nothing
     for v in violations
         _enforce_transmission(
             model = model,
+            sc = sc,
             violation = v,
-            isf = model[:isf],
+            isf = sc.isf,
-            lodf = model[:lodf],
+            lodf = sc.lodf,
         )
     end
     return
@@ -19,6 +21,7 @@ end
 
 function _enforce_transmission(;
     model::JuMP.Model,
+    sc::UnitCommitmentScenario,
     violation::_Violation,
     isf::Matrix{Float64},
     lodf::Matrix{Float64},
@@ -31,19 +34,21 @@ function _enforce_transmission(;
     if violation.outage_line === nothing
         limit = violation.monitored_line.normal_flow_limit[violation.time]
         @info @sprintf(
-            "    %8.3f MW overflow in %-5s time %3d (pre-contingency)",
+            "    %8.3f MW overflow in %-5s time %3d (pre-contingency, scenario %s)",
             violation.amount,
             violation.monitored_line.name,
             violation.time,
+            sc.name,
         )
     else
         limit = violation.monitored_line.emergency_flow_limit[violation.time]
         @info @sprintf(
-            "    %8.3f MW overflow in %-5s time %3d (outage: line %s)",
+            "    %8.3f MW overflow in %-5s time %3d (outage: line %s, scenario %s)",
             violation.amount,
             violation.monitored_line.name,
             violation.time,
             violation.outage_line.name,
+            sc.name,
         )
     end
 
@@ -51,7 +56,7 @@ function _enforce_transmission(;
     t = violation.time
     flow = @variable(model, base_name = "flow[$fm,$t]")
 
-    v = overflow[violation.monitored_line.name, violation.time]
+    v = overflow[sc.name, violation.monitored_line.name, violation.time]
     @constraint(model, flow <= limit + v)
     @constraint(model, -flow <= limit + v)
 
@@ -59,23 +64,23 @@ function _enforce_transmission(;
         @constraint(
             model,
             flow == sum(
-                net_injection[b.name, violation.time] *
+                net_injection[sc.name, b.name, violation.time] *
                 isf[violation.monitored_line.offset, b.offset] for
-                b in instance.buses if b.offset > 0
+                b in sc.buses if b.offset > 0
             )
         )
     else
         @constraint(
             model,
             flow == sum(
-                net_injection[b.name, violation.time] * (
+                net_injection[sc.name, b.name, violation.time] * (
                     isf[violation.monitored_line.offset, b.offset] + (
                         lodf[
                             violation.monitored_line.offset,
                             violation.outage_line.offset,
                         ] * isf[violation.outage_line.offset, b.offset]
                     )
-                ) for b in instance.buses if b.offset > 0
+                ) for b in sc.buses if b.offset > 0
             )
         )
     end

src/solution/methods/XavQiuWanThi2019/find.jl

@@ -5,39 +5,35 @@
 import Base.Threads: @threads
 
 function _find_violations(
-    model::JuMP.Model;
+    model::JuMP.Model,
+    sc::UnitCommitmentScenario;
     max_per_line::Int,
     max_per_period::Int,
 )
     instance = model[:instance]
     net_injection = model[:net_injection]
     overflow = model[:overflow]
-    length(instance.buses) > 1 || return []
+    length(sc.buses) > 1 || return []
     violations = []
-    @info "Verifying transmission limits..."
+
-    time_screening = @elapsed begin
+    non_slack_buses = [b for b in sc.buses if b.offset > 0]
-        non_slack_buses = [b for b in instance.buses if b.offset > 0]
+    net_injection_values = [
-        net_injection_values = [
+        value(net_injection[sc.name, b.name, t]) for b in non_slack_buses,
-            value(net_injection[b.name, t]) for b in non_slack_buses,
+        t in 1:instance.time
-            t in 1:instance.time
+    ]
-        ]
+    overflow_values = [
-        overflow_values = [
+        value(overflow[sc.name, lm.name, t]) for lm in sc.lines,
-            value(overflow[lm.name, t]) for lm in instance.lines,
+        t in 1:instance.time
-            t in 1:instance.time
+    ]
-        ]
+    violations = UnitCommitment._find_violations(
-        violations = UnitCommitment._find_violations(
+        instance = instance,
-            instance = instance,
+        sc = sc,
-            net_injections = net_injection_values,
+        net_injections = net_injection_values,
-            overflow = overflow_values,
+        overflow = overflow_values,
-            isf = model[:isf],
+        isf = sc.isf,
-            lodf = model[:lodf],
+        lodf = sc.lodf,
-            max_per_line = max_per_line,
+        max_per_line = max_per_line,
-            max_per_period = max_per_period,
+        max_per_period = max_per_period,
-        )
-    end
-    @info @sprintf(
-        "Verified transmission limits in %.2f seconds",
-        time_screening
     )
     return violations
 end
@@ -64,6 +60,7 @@ matrix, where L is the number of transmission lines.
 """
 function _find_violations(;
     instance::UnitCommitmentInstance,
+    sc::UnitCommitmentScenario,
     net_injections::Array{Float64,2},
     overflow::Array{Float64,2},
     isf::Array{Float64,2},
@@ -71,8 +68,8 @@ function _find_violations(;
     max_per_line::Int,
     max_per_period::Int,
 )::Array{_Violation,1}
-    B = length(instance.buses) - 1
+    B = length(sc.buses) - 1
-    L = length(instance.lines)
+    L = length(sc.lines)
     T = instance.time
     K = nthreads()
 
@@ -93,17 +90,17 @@ function _find_violations(;
     post_v::Array{Float64} = zeros(L, L, K)          # post_v[lm, lc, thread]
 
     normal_limits::Array{Float64,2} = [
-        l.normal_flow_limit[t] + overflow[l.offset, t] for
+        l.normal_flow_limit[t] + overflow[l.offset, t] for l in sc.lines,
-        l in instance.lines, t in 1:T
+        t in 1:T
     ]
 
     emergency_limits::Array{Float64,2} = [
-        l.emergency_flow_limit[t] + overflow[l.offset, t] for
+        l.emergency_flow_limit[t] + overflow[l.offset, t] for l in sc.lines,
-        l in instance.lines, t in 1:T
+        t in 1:T
     ]
 
     is_vulnerable::Array{Bool} = zeros(Bool, L)
-    for c in instance.contingencies
+    for c in sc.contingencies
         is_vulnerable[c.lines[1].offset] = true
     end
 
@@ -144,7 +141,7 @@ function _find_violations(;
                     filters[t],
                     _Violation(
                         time = t,
-                        monitored_line = instance.lines[lm],
+                        monitored_line = sc.lines[lm],
                         outage_line = nothing,
                         amount = pre_v[lm, k],
                     ),
@@ -159,8 +156,8 @@ function _find_violations(;
                     filters[t],
                     _Violation(
                         time = t,
-                        monitored_line = instance.lines[lm],
+                        monitored_line = sc.lines[lm],
-                        outage_line = instance.lines[lc],
+                        outage_line = sc.lines[lc],
                         amount = post_v[lm, lc, k],
                     ),
                 )

src/solution/methods/XavQiuWanThi2019/optimize.jl

@@ -12,10 +12,15 @@ function optimize!(model::JuMP.Model, method::XavQiuWanThi2019.Method)::Nothing
     end
     initial_time = time()
     large_gap = false
-    has_transmission = (length(model[:isf]) > 0)
+    has_transmission = false
-    if has_transmission && method.two_phase_gap
+    for sc in model[:instance].scenarios
-        set_gap(1e-2)
+        if length(sc.isf) > 0
-        large_gap = true
+            has_transmission = true
+        end
+        if has_transmission && method.two_phase_gap
+            set_gap(1e-2)
+            large_gap = true
+        end
     end
     while true
         time_elapsed = time() - initial_time
@@ -31,13 +36,41 @@ function optimize!(model::JuMP.Model, method::XavQiuWanThi2019.Method)::Nothing
         JuMP.set_time_limit_sec(model, time_remaining)
         @info "Solving MILP..."
         JuMP.optimize!(model)
+
         has_transmission || break
-        violations = _find_violations(
+
-            model,
+        @info "Verifying transmission limits..."
-            max_per_line = method.max_violations_per_line,
+        time_screening = @elapsed begin
-            max_per_period = method.max_violations_per_period,
+            violations = []
+            for sc in model[:instance].scenarios
+                push!(
+                    violations,
+                    _find_violations(
+                        model,
+                        sc,
+                        max_per_line = method.max_violations_per_line,
+                        max_per_period = method.max_violations_per_period,
+                    ),
+                )
+            end
+        end
+        @info @sprintf(
+            "Verified transmission limits in %.2f seconds",
+            time_screening
         )
-        if isempty(violations)
+
+        violations_found = false
+        for v in violations
+            if !isempty(v)
+                violations_found = true
+            end
+        end
+
+        if violations_found
+            for (i, v) in enumerate(violations)
+                _enforce_transmission(model, v, model[:instance].scenarios[i])
+            end
+        else
             @info "No violations found"
             if large_gap
                 large_gap = false
@@ -45,8 +78,6 @@ function optimize!(model::JuMP.Model, method::XavQiuWanThi2019.Method)::Nothing
             else
                 break
             end
-        else
-            _enforce_transmission(model, violations)
         end
     end
     return

src/solution/solution.jl

@@ -16,34 +16,44 @@ solution = UnitCommitment.solution(model)
 """
 function solution(model::JuMP.Model)::OrderedDict
     instance, T = model[:instance], model[:instance].time
-    function timeseries(vars, collection)
+    function timeseries(vars, collection; sc = nothing)
-        return OrderedDict(
+        if sc === nothing
-            b.name => [round(value(vars[b.name, t]), digits = 5) for t in 1:T]
+            return OrderedDict(
-            for b in collection
+                b.name =>
-        )
+                    [round(value(vars[b.name, t]), digits = 5) for t in 1:T] for
+                b in collection
+            )
+        else
+            return OrderedDict(
+                b.name => [
+                    round(value(vars[sc.name, b.name, t]), digits = 5) for
+                    t in 1:T
+                ] for b in collection
+            )
+        end
     end
-    function production_cost(g)
+    function production_cost(g, sc)
         return [
             value(model[:is_on][g.name, t]) * g.min_power_cost[t] + sum(
                 Float64[
-                    value(model[:segprod][g.name, t, k]) *
+                    value(model[:segprod][sc.name, g.name, t, k]) *
                     g.cost_segments[k].cost[t] for
                     k in 1:length(g.cost_segments)
                 ],
             ) for t in 1:T
         ]
     end
-    function production(g)
+    function production(g, sc)
         return [
             value(model[:is_on][g.name, t]) * g.min_power[t] + sum(
                 Float64[
-                    value(model[:segprod][g.name, t, k]) for
+                    value(model[:segprod][sc.name, g.name, t, k]) for
                     k in 1:length(g.cost_segments)
                 ],
             ) for t in 1:T
         ]
     end
-    function startup_cost(g)
+    function startup_cost(g, sc)
         S = length(g.startup_categories)
         return [
             sum(
@@ -53,66 +63,87 @@ function solution(model::JuMP.Model)::OrderedDict
         ]
     end
     sol = OrderedDict()
-    sol["Production (MW)"] =
+    for sc in instance.scenarios
-        OrderedDict(g.name => production(g) for g in instance.units)
+        sol[sc.name] = OrderedDict()
-    sol["Production cost (\$)"] =
+        if !isempty(sc.thermal_units)
-        OrderedDict(g.name => production_cost(g) for g in instance.units)
+            sol[sc.name]["Thermal production (MW)"] = OrderedDict(
-    sol["Startup cost (\$)"] =
+                g.name => production(g, sc) for g in sc.thermal_units
-        OrderedDict(g.name => startup_cost(g) for g in instance.units)
+            )
-    sol["Is on"] = timeseries(model[:is_on], instance.units)
+            sol[sc.name]["Thermal production cost (\$)"] = OrderedDict(
-    sol["Switch on"] = timeseries(model[:switch_on], instance.units)
+                g.name => production_cost(g, sc) for g in sc.thermal_units
-    sol["Switch off"] = timeseries(model[:switch_off], instance.units)
+            )
-    sol["Net injection (MW)"] =
+            sol[sc.name]["Startup cost (\$)"] = OrderedDict(
-        timeseries(model[:net_injection], instance.buses)
+                g.name => startup_cost(g, sc) for g in sc.thermal_units
-    sol["Load curtail (MW)"] = timeseries(model[:curtail], instance.buses)
+            )
-    if !isempty(instance.lines)
+            sol[sc.name]["Is on"] = timeseries(model[:is_on], sc.thermal_units)
-        sol["Line overflow (MW)"] = timeseries(model[:overflow], instance.lines)
+            sol[sc.name]["Switch on"] =
+                timeseries(model[:switch_on], sc.thermal_units)
+            sol[sc.name]["Switch off"] =
+                timeseries(model[:switch_off], sc.thermal_units)
+            sol[sc.name]["Net injection (MW)"] =
+                timeseries(model[:net_injection], sc.buses, sc = sc)
+            sol[sc.name]["Load curtail (MW)"] =
+                timeseries(model[:curtail], sc.buses, sc = sc)
+        end
+        if !isempty(sc.lines)
+            sol[sc.name]["Line overflow (MW)"] =
+                timeseries(model[:overflow], sc.lines, sc = sc)
+        end
+        if !isempty(sc.price_sensitive_loads)
+            sol[sc.name]["Price-sensitive loads (MW)"] =
+                timeseries(model[:loads], sc.price_sensitive_loads, sc = sc)
+        end
+        if !isempty(sc.profiled_units)
+            sol[sc.name]["Profiled production (MW)"] =
+                timeseries(model[:prod_profiled], sc.profiled_units, sc = sc)
+            sol[sc.name]["Profiled production cost (\$)"] = OrderedDict(
+                pu.name => [
+                    value(model[:prod_profiled][sc.name, pu.name, t]) *
+                    pu.cost[t] for t in 1:instance.time
+                ] for pu in sc.profiled_units
+            )
+        end
+        sol[sc.name]["Spinning reserve (MW)"] = OrderedDict(
+            r.name => OrderedDict(
+                g.name => [
+                    value(model[:reserve][sc.name, r.name, g.name, t]) for t in 1:instance.time
+                ] for g in r.thermal_units
+            ) for r in sc.reserves if r.type == "spinning"
+        )
+        sol[sc.name]["Spinning reserve shortfall (MW)"] = OrderedDict(
+            r.name => [
+                value(model[:reserve_shortfall][sc.name, r.name, t]) for
+                t in 1:instance.time
+            ] for r in sc.reserves if r.type == "spinning"
+        )
+        sol[sc.name]["Up-flexiramp (MW)"] = OrderedDict(
+            r.name => OrderedDict(
+                g.name => [
+                    value(model[:upflexiramp][sc.name, r.name, g.name, t]) for t in 1:instance.time
+                ] for g in r.thermal_units
+            ) for r in sc.reserves if r.type == "flexiramp"
+        )
+        sol[sc.name]["Up-flexiramp shortfall (MW)"] = OrderedDict(
+            r.name => [
+                value(model[:upflexiramp_shortfall][sc.name, r.name, t]) for t in 1:instance.time
+            ] for r in sc.reserves if r.type == "flexiramp"
+        )
+        sol[sc.name]["Down-flexiramp (MW)"] = OrderedDict(
+            r.name => OrderedDict(
+                g.name => [
+                    value(model[:dwflexiramp][sc.name, r.name, g.name, t]) for t in 1:instance.time
+                ] for g in r.thermal_units
+            ) for r in sc.reserves if r.type == "flexiramp"
+        )
+        sol[sc.name]["Down-flexiramp shortfall (MW)"] = OrderedDict(
+            r.name => [
+                value(model[:dwflexiramp_shortfall][sc.name, r.name, t]) for t in 1:instance.time
+            ] for r in sc.reserves if r.type == "flexiramp"
+        )
     end
-    if !isempty(instance.price_sensitive_loads)
+    if length(instance.scenarios) == 1
-        sol["Price-sensitive loads (MW)"] =
+        return first(values(sol))
-            timeseries(model[:loads], instance.price_sensitive_loads)
+    else
+        return sol
     end
-    sol["Spinning reserve (MW)"] = OrderedDict(
-        r.name => OrderedDict(
-            g.name => [
-                value(model[:reserve][r.name, g.name, t]) for
-                t in 1:instance.time
-            ] for g in r.units
-        ) for r in instance.reserves if r.type == "spinning"
-    )
-    sol["Spinning reserve shortfall (MW)"] = OrderedDict(
-        r.name => [
-            value(model[:reserve_shortfall][r.name, t]) for
-            t in 1:instance.time
-        ] for r in instance.reserves if r.type == "spinning"
-    )
-    sol["Up-flexiramp (MW)"] = OrderedDict(
-        r.name => OrderedDict(
-            g.name => [
-                value(model[:upflexiramp][r.name, g.name, t]) for
-                t in 1:instance.time
-            ] for g in r.units
-        ) for r in instance.reserves if r.type == "flexiramp"
-    )
-    sol["Up-flexiramp shortfall (MW)"] = OrderedDict(
-        r.name => [
-            value(model[:upflexiramp_shortfall][r.name, t]) for
-            t in 1:instance.time
-        ] for r in instance.reserves if r.type == "flexiramp"
-    )
-    sol["Down-flexiramp (MW)"] = OrderedDict(
-        r.name => OrderedDict(
-            g.name => [
-                value(model[:dwflexiramp][r.name, g.name, t]) for
-                t in 1:instance.time
-            ] for g in r.units
-        ) for r in instance.reserves if r.type == "flexiramp"
-    )
-    sol["Down-flexiramp shortfall (MW)"] = OrderedDict(
-        r.name => [
-            value(model[:upflexiramp_shortfall][r.name, t]) for
-            t in 1:instance.time
-        ] for r in instance.reserves if r.type == "flexiramp"
-    )
-    return sol
 end

src/solution/warmstart.jl

@@ -5,7 +5,7 @@
 function set_warm_start!(model::JuMP.Model, solution::AbstractDict)::Nothing
     instance, T = model[:instance], model[:instance].time
     is_on = model[:is_on]
-    for g in instance.units
+    for g in instance.thermal_units
         for t in 1:T
             JuMP.set_start_value(is_on[g.name, t], solution["Is on"][g.name][t])
             JuMP.set_start_value(

src/transform/initcond.jl

@@ -5,36 +5,41 @@
 using JuMP
 
 """
-    generate_initial_conditions!(instance, optimizer)
+    generate_initial_conditions!(sc, optimizer)
 
-Generates feasible initial conditions for the given instance, by constructing
+Generates feasible initial conditions for the given scenario, by constructing
 and solving a single-period mixed-integer optimization problem, using the given
-optimizer. The instance is modified in-place.
+optimizer. The scenario is modified in-place.
 """
 function generate_initial_conditions!(
-    instance::UnitCommitmentInstance,
+    sc::UnitCommitmentScenario,
     optimizer,
 )::Nothing
-    G = instance.units
+    G = sc.thermal_units
-    B = instance.buses
+    B = sc.buses
+    PU = sc.profiled_units
     t = 1
     mip = JuMP.Model(optimizer)
 
     # Decision variables
     @variable(mip, x[G], Bin)
     @variable(mip, p[G] >= 0)
+    @variable(mip, pu[PU])
 
     # Constraint: Minimum power
     @constraint(mip, min_power[g in G], p[g] >= g.min_power[t] * x[g])
+    @constraint(mip, pu_min_power[k in PU], pu[k] >= k.min_power[t])
 
     # Constraint: Maximum power
     @constraint(mip, max_power[g in G], p[g] <= g.max_power[t] * x[g])
+    @constraint(mip, pu_max_power[k in PU], pu[k] <= k.max_power[t])
 
     # Constraint: Production equals demand
     @constraint(
         mip,
         power_balance,
-        sum(b.load[t] for b in B) == sum(p[g] for g in G)
+        sum(b.load[t] for b in B) ==
+        sum(p[g] for g in G) + sum(pu[k] for k in PU)
     )
 
     # Constraint: Must run
@@ -58,7 +63,12 @@ function generate_initial_conditions!(
             return c / mw
         end
     end
-    @objective(mip, Min, sum(p[g] * cost_slope(g) for g in G))
+    @objective(
+        mip,
+        Min,
+        sum(p[g] * cost_slope(g) for g in G) +
+        sum(pu[k] * k.cost[t] for k in PU)
+    )
 
     JuMP.optimize!(mip)
 

src/transform/randomize/XavQiuAhm2021.jl

@@ -6,6 +6,7 @@ module XavQiuAhm2021
 
 using Distributions
 import ..UnitCommitmentInstance
+import ..UnitCommitmentScenario
 
 """
     struct Randomization
@@ -119,10 +120,10 @@ end
 
 function _randomize_costs(
     rng,
-    instance::UnitCommitmentInstance,
+    sc::UnitCommitmentScenario,
     distribution,
 )::Nothing
-    for unit in instance.units
+    for unit in sc.thermal_units
         α = rand(rng, distribution)
         unit.min_power_cost *= α
         for k in unit.cost_segments
@@ -132,22 +133,24 @@ function _randomize_costs(
             s.cost *= α
         end
     end
+    for pu in sc.profiled_units
+        α = rand(rng, distribution)
+        pu.cost *= α
+    end
     return
 end
 
 function _randomize_load_share(
     rng,
-    instance::UnitCommitmentInstance,
+    sc::UnitCommitmentScenario,
     distribution,
 )::Nothing
-    α = rand(rng, distribution, length(instance.buses))
+    α = rand(rng, distribution, length(sc.buses))
-    for t in 1:instance.time
+    for t in 1:sc.time
-        total = sum(bus.load[t] for bus in instance.buses)
+        total = sum(bus.load[t] for bus in sc.buses)
-        den = sum(
+        den =
-            bus.load[t] / total * α[i] for
+            sum(bus.load[t] / total * α[i] for (i, bus) in enumerate(sc.buses))
-            (i, bus) in enumerate(instance.buses)
+        for (i, bus) in enumerate(sc.buses)
-        )
-        for (i, bus) in enumerate(instance.buses)
             bus.load[t] *= α[i] / den
         end
     end
@@ -156,12 +159,12 @@ end
 
 function _randomize_load_profile(
     rng,
-    instance::UnitCommitmentInstance,
+    sc::UnitCommitmentScenario,
     params::Randomization,
 )::Nothing
     # Generate new system load
     system_load = [1.0]
-    for t in 2:instance.time
+    for t in 2:sc.time
         idx = (t - 1) % length(params.load_profile_mu) + 1
         gamma = rand(
             rng,
@@ -169,14 +172,14 @@ function _randomize_load_profile(
         )
         push!(system_load, system_load[t-1] * gamma)
     end
-    capacity = sum(maximum(u.max_power) for u in instance.units)
+    capacity = sum(maximum(u.max_power) for u in sc.thermal_units)
     peak_load = rand(rng, 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)
+    prev_system_load = sum(b.load for b in sc.buses)
-    for b in instance.buses
+    for b in sc.buses
-        for t in 1:instance.time
+        for t in 1:sc.time
             b.load[t] *= system_load[t] / prev_system_load[t]
         end
     end
@@ -199,15 +202,26 @@ function randomize!(
     instance::UnitCommitment.UnitCommitmentInstance,
     method::XavQiuAhm2021.Randomization;
     rng = MersenneTwister(),
+)::Nothing
+    for sc in instance.scenarios
+        randomize!(sc, method; rng)
+    end
+    return
+end
+
+function randomize!(
+    sc::UnitCommitment.UnitCommitmentScenario,
+    method::XavQiuAhm2021.Randomization;
+    rng = MersenneTwister(),
 )::Nothing
     if method.randomize_costs
-        XavQiuAhm2021._randomize_costs(rng, instance, method.cost)
+        XavQiuAhm2021._randomize_costs(rng, sc, method.cost)
     end
     if method.randomize_load_share
-        XavQiuAhm2021._randomize_load_share(rng, instance, method.load_share)
+        XavQiuAhm2021._randomize_load_share(rng, sc, method.load_share)
     end
     if method.randomize_load_profile
-        XavQiuAhm2021._randomize_load_profile(rng, instance, method)
+        XavQiuAhm2021._randomize_load_profile(rng, sc, method)
     end
     return
 end

src/transform/slice.jl

@@ -24,31 +24,38 @@ function slice(
 )::UnitCommitmentInstance
     modified = deepcopy(instance)
     modified.time = length(range)
-    modified.power_balance_penalty = modified.power_balance_penalty[range]
+    for sc in modified.scenarios
-    for r in modified.reserves
+        sc.power_balance_penalty = sc.power_balance_penalty[range]
-        r.amount = r.amount[range]
+        for r in sc.reserves
-    end
+            r.amount = r.amount[range]
-    for u in modified.units
+        end
-        u.max_power = u.max_power[range]
+        for u in sc.thermal_units
-        u.min_power = u.min_power[range]
+            u.max_power = u.max_power[range]
-        u.must_run = u.must_run[range]
+            u.min_power = u.min_power[range]
-        u.min_power_cost = u.min_power_cost[range]
+            u.must_run = u.must_run[range]
-        for s in u.cost_segments
+            u.min_power_cost = u.min_power_cost[range]
-            s.mw = s.mw[range]
+            for s in u.cost_segments
-            s.cost = s.cost[range]
+                s.mw = s.mw[range]
+                s.cost = s.cost[range]
+            end
+        end
+        for pu in sc.profiled_units
+            pu.max_power = pu.max_power[range]
+            pu.min_power = pu.min_power[range]
+            pu.cost = pu.cost[range]
+        end
+        for b in sc.buses
+            b.load = b.load[range]
+        end
+        for l in sc.lines
+            l.normal_flow_limit = l.normal_flow_limit[range]
+            l.emergency_flow_limit = l.emergency_flow_limit[range]
+            l.flow_limit_penalty = l.flow_limit_penalty[range]
+        end
+        for ps in sc.price_sensitive_loads
+            ps.demand = ps.demand[range]
+            ps.revenue = ps.revenue[range]
         end
-    end
-    for b in modified.buses
-        b.load = b.load[range]
-    end
-    for l in modified.lines
-        l.normal_flow_limit = l.normal_flow_limit[range]
-        l.emergency_flow_limit = l.emergency_flow_limit[range]
-        l.flow_limit_penalty = l.flow_limit_penalty[range]
-    end
-    for ps in modified.price_sensitive_loads
-        ps.demand = ps.demand[range]
-        ps.revenue = ps.revenue[range]
     end
     return modified
 end

src/validation/repair.jl

@@ -3,19 +3,19 @@
 # Released under the modified BSD license. See COPYING.md for more details.
 
 """
-    repair!(instance)
+    repair!(sc)
 
-Verifies that the given unit commitment instance is valid and automatically
+Verifies that the given unit commitment scenario is valid and automatically
 fixes some validation errors if possible, issuing a warning for each error
 found. If a validation error cannot be automatically fixed, issues an
 exception.
 
 Returns the number of validation errors found.
 """
-function repair!(instance::UnitCommitmentInstance)::Int
+function repair!(sc::UnitCommitmentScenario)::Int
     n_errors = 0
 
-    for g in instance.units
+    for g in sc.thermal_units
 
         # Startup costs and delays must be increasing
         for s in 2:length(g.startup_categories)
@@ -38,7 +38,7 @@ function repair!(instance::UnitCommitmentInstance)::Int
             end
         end
 
-        for t in 1:instance.time
+        for t in 1:sc.time
             # Production cost curve should be convex
             for k in 2:length(g.cost_segments)
                 cost = g.cost_segments[k].cost[t]

src/validation/validate.jl

@@ -28,6 +28,8 @@ function validate(
     instance::UnitCommitmentInstance,
     solution::Union{Dict,OrderedDict},
 )::Bool
+    "Thermal production (MW)" ∈ keys(solution) ?
+    solution = Dict("s1" => solution) : nothing
     err_count = 0
     err_count += _validate_units(instance, solution)
     err_count += _validate_reserve_and_demand(instance, solution)
@@ -42,358 +44,407 @@ end
 
 function _validate_units(instance::UnitCommitmentInstance, solution; tol = 0.01)
     err_count = 0
-
+    for sc in instance.scenarios
-    for unit in instance.units
+        for unit in sc.thermal_units
-        production = solution["Production (MW)"][unit.name]
+            production = solution[sc.name]["Thermal production (MW)"][unit.name]
-        reserve = [0.0 for _ in 1:instance.time]
+            reserve = [0.0 for _ in 1:instance.time]
-        spinning_reserves = [r for r in unit.reserves if r.type == "spinning"]
+            spinning_reserves =
-        if !isempty(spinning_reserves)
+                [r for r in unit.reserves if r.type == "spinning"]
-            reserve += sum(
+            if !isempty(spinning_reserves)
-                solution["Spinning reserve (MW)"][r.name][unit.name] for
+                reserve += sum(
-                r in spinning_reserves
+                    solution[sc.name]["Spinning reserve (MW)"][r.name][unit.name]
-            )
+                    for r in spinning_reserves
-        end
+                )
-        actual_production_cost = solution["Production cost (\$)"][unit.name]
-        actual_startup_cost = solution["Startup cost (\$)"][unit.name]
-        is_on = bin(solution["Is on"][unit.name])
-
-        for t in 1:instance.time
-            # Auxiliary variables
-            if t == 1
-                is_starting_up = (unit.initial_status < 0) && is_on[t]
-                is_shutting_down = (unit.initial_status > 0) && !is_on[t]
-                ramp_up =
-                    max(0, production[t] + reserve[t] - unit.initial_power)
-                ramp_down = max(0, unit.initial_power - production[t])
-            else
-                is_starting_up = !is_on[t-1] && is_on[t]
-                is_shutting_down = is_on[t-1] && !is_on[t]
-                ramp_up = max(0, production[t] + reserve[t] - production[t-1])
-                ramp_down = max(0, production[t-1] - production[t])
             end
+            actual_production_cost =
+                solution[sc.name]["Thermal production cost (\$)"][unit.name]
+            actual_startup_cost =
+                solution[sc.name]["Startup cost (\$)"][unit.name]
+            is_on = bin(solution[sc.name]["Is on"][unit.name])
 
-            # Compute production costs
+            for t in 1:instance.time
-            production_cost, startup_cost = 0, 0
+                # Auxiliary variables
-            if is_on[t]
+                if t == 1
-                production_cost += unit.min_power_cost[t]
+                    is_starting_up = (unit.initial_status < 0) && is_on[t]
-                residual = max(0, production[t] - unit.min_power[t])
+                    is_shutting_down = (unit.initial_status > 0) && !is_on[t]
-                for s in unit.cost_segments
+                    ramp_up =
-                    cleared = min(residual, s.mw[t])
+                        max(0, production[t] + reserve[t] - unit.initial_power)
-                    production_cost += cleared * s.cost[t]
+                    ramp_down = max(0, unit.initial_power - production[t])
-                    residual = max(0, residual - s.mw[t])
+                else
+                    is_starting_up = !is_on[t-1] && is_on[t]
+                    is_shutting_down = is_on[t-1] && !is_on[t]
+                    ramp_up =
+                        max(0, production[t] + reserve[t] - production[t-1])
+                    ramp_down = max(0, production[t-1] - production[t])
                 end
-            end
 
-            # Production should be non-negative
+                # Compute production costs
-            if production[t] < -tol
+                production_cost, startup_cost = 0, 0
-                @error @sprintf(
+                if is_on[t]
-                    "Unit %s produces negative amount of power at time %d (%.2f)",
+                    production_cost += unit.min_power_cost[t]
-                    unit.name,
+                    residual = max(0, production[t] - unit.min_power[t])
-                    t,
+                    for s in unit.cost_segments
-                    production[t]
+                        cleared = min(residual, s.mw[t])
-                )
+                        production_cost += cleared * s.cost[t]
-                err_count += 1
+                        residual = max(0, residual - s.mw[t])
-            end
+                    end
+                end
 
-            # Verify must-run
+                # Production should be non-negative
-            if !is_on[t] && unit.must_run[t]
+                if production[t] < -tol
-                @error @sprintf(
+                    @error @sprintf(
-                    "Must-run unit %s is offline at time %d",
+                        "Unit %s produces negative amount of power at time %d (%.2f)",
-                    unit.name,
+                        unit.name,
-                    t
+                        t,
-                )
+                        production[t]
-                err_count += 1
+                    )
-            end
+                    err_count += 1
+                end
 
-            # Verify reserve eligibility
+                # Verify must-run
-            for r in instance.reserves
+                if !is_on[t] && unit.must_run[t]
-                if r.type == "spinning"
+                    @error @sprintf(
-                    if unit ∉ r.units &&
+                        "Must-run unit %s is offline at time %d",
-                       (unit in keys(solution["Spinning reserve (MW)"][r.name]))
+                        unit.name,
+                        t
+                    )
+                    err_count += 1
+                end
+
+                # Verify reserve eligibility
+                for r in sc.reserves
+                    if r.type == "spinning"
+                        if unit ∉ r.thermal_units && (
+                            unit in keys(
+                                solution[sc.name]["Spinning reserve (MW)"][r.name],
+                            )
+                        )
+                            @error @sprintf(
+                                "Unit %s is not eligible to provide reserve %s",
+                                unit.name,
+                                r.name,
+                            )
+                            err_count += 1
+                        end
+                    end
+                end
+
+                # If unit is on, must produce at least its minimum power
+                if is_on[t] && (production[t] < unit.min_power[t] - tol)
+                    @error @sprintf(
+                        "Unit %s produces below its minimum limit at time %d (%.2f < %.2f)",
+                        unit.name,
+                        t,
+                        production[t],
+                        unit.min_power[t]
+                    )
+                    err_count += 1
+                end
+
+                # If unit is on, must produce at most its maximum power
+                if is_on[t] &&
+                   (production[t] + reserve[t] > unit.max_power[t] + tol)
+                    @error @sprintf(
+                        "Unit %s produces above its maximum limit at time %d (%.2f + %.2f> %.2f)",
+                        unit.name,
+                        t,
+                        production[t],
+                        reserve[t],
+                        unit.max_power[t]
+                    )
+                    err_count += 1
+                end
+
+                # If unit is off, must produce zero
+                if !is_on[t] && production[t] + reserve[t] > tol
+                    @error @sprintf(
+                        "Unit %s produces power at time %d while off (%.2f + %.2f > 0)",
+                        unit.name,
+                        t,
+                        production[t],
+                        reserve[t],
+                    )
+                    err_count += 1
+                end
+
+                # Startup limit
+                if is_starting_up && (ramp_up > unit.startup_limit + tol)
+                    @error @sprintf(
+                        "Unit %s exceeds startup limit at time %d (%.2f > %.2f)",
+                        unit.name,
+                        t,
+                        ramp_up,
+                        unit.startup_limit
+                    )
+                    err_count += 1
+                end
+
+                # Shutdown limit
+                if is_shutting_down && (ramp_down > unit.shutdown_limit + tol)
+                    @error @sprintf(
+                        "Unit %s exceeds shutdown limit at time %d (%.2f > %.2f)",
+                        unit.name,
+                        t,
+                        ramp_down,
+                        unit.shutdown_limit
+                    )
+                    err_count += 1
+                end
+
+                # Ramp-up limit
+                if !is_starting_up &&
+                   !is_shutting_down &&
+                   (ramp_up > unit.ramp_up_limit + tol)
+                    @error @sprintf(
+                        "Unit %s exceeds ramp up limit at time %d (%.2f > %.2f)",
+                        unit.name,
+                        t,
+                        ramp_up,
+                        unit.ramp_up_limit
+                    )
+                    err_count += 1
+                end
+
+                # Ramp-down limit
+                if !is_starting_up &&
+                   !is_shutting_down &&
+                   (ramp_down > unit.ramp_down_limit + tol)
+                    @error @sprintf(
+                        "Unit %s exceeds ramp down limit at time %d (%.2f > %.2f)",
+                        unit.name,
+                        t,
+                        ramp_down,
+                        unit.ramp_down_limit
+                    )
+                    err_count += 1
+                end
+
+                # Verify startup costs & minimum downtime
+                if is_starting_up
+
+                    # Calculate how much time the unit has been offline
+                    time_down = 0
+                    for k in 1:(t-1)
+                        if !is_on[t-k]
+                            time_down += 1
+                        else
+                            break
+                        end
+                    end
+                    if (t == time_down + 1) && (unit.initial_status < 0)
+                        time_down -= unit.initial_status
+                    end
+
+                    # Calculate startup costs
+                    for c in unit.startup_categories
+                        if time_down >= c.delay
+                            startup_cost = c.cost
+                        end
+                    end
+
+                    # Check minimum downtime
+                    if time_down < unit.min_downtime
                         @error @sprintf(
-                            "Unit %s is not eligible to provide reserve %s",
+                            "Unit %s violates minimum downtime at time %d",
                             unit.name,
-                            r.name,
+                            t
                         )
                         err_count += 1
                     end
                 end
-            end
 
-            # If unit is on, must produce at least its minimum power
+                # Verify minimum uptime
-            if is_on[t] && (production[t] < unit.min_power[t] - tol)
+                if is_shutting_down
-                @error @sprintf(
-                    "Unit %s produces below its minimum limit at time %d (%.2f < %.2f)",
-                    unit.name,
-                    t,
-                    production[t],
-                    unit.min_power[t]
-                )
-                err_count += 1
-            end
 
-            # If unit is on, must produce at most its maximum power
+                    # Calculate how much time the unit has been online
-            if is_on[t] &&
+                    time_up = 0
-               (production[t] + reserve[t] > unit.max_power[t] + tol)
+                    for k in 1:(t-1)
-                @error @sprintf(
+                        if is_on[t-k]
-                    "Unit %s produces above its maximum limit at time %d (%.2f + %.2f> %.2f)",
+                            time_up += 1
-                    unit.name,
+                        else
-                    t,
+                            break
-                    production[t],
+                        end
-                    reserve[t],
+                    end
-                    unit.max_power[t]
+                    if (t == time_up + 1) && (unit.initial_status > 0)
-                )
+                        time_up += unit.initial_status
-                err_count += 1
-            end
-
-            # If unit is off, must produce zero
-            if !is_on[t] && production[t] + reserve[t] > tol
-                @error @sprintf(
-                    "Unit %s produces power at time %d while off (%.2f + %.2f > 0)",
-                    unit.name,
-                    t,
-                    production[t],
-                    reserve[t],
-                )
-                err_count += 1
-            end
-
-            # Startup limit
-            if is_starting_up && (ramp_up > unit.startup_limit + tol)
-                @error @sprintf(
-                    "Unit %s exceeds startup limit at time %d (%.2f > %.2f)",
-                    unit.name,
-                    t,
-                    ramp_up,
-                    unit.startup_limit
-                )
-                err_count += 1
-            end
-
-            # Shutdown limit
-            if is_shutting_down && (ramp_down > unit.shutdown_limit + tol)
-                @error @sprintf(
-                    "Unit %s exceeds shutdown limit at time %d (%.2f > %.2f)",
-                    unit.name,
-                    t,
-                    ramp_down,
-                    unit.shutdown_limit
-                )
-                err_count += 1
-            end
-
-            # Ramp-up limit
-            if !is_starting_up &&
-               !is_shutting_down &&
-               (ramp_up > unit.ramp_up_limit + tol)
-                @error @sprintf(
-                    "Unit %s exceeds ramp up limit at time %d (%.2f > %.2f)",
-                    unit.name,
-                    t,
-                    ramp_up,
-                    unit.ramp_up_limit
-                )
-                err_count += 1
-            end
-
-            # Ramp-down limit
-            if !is_starting_up &&
-               !is_shutting_down &&
-               (ramp_down > unit.ramp_down_limit + tol)
-                @error @sprintf(
-                    "Unit %s exceeds ramp down limit at time %d (%.2f > %.2f)",
-                    unit.name,
-                    t,
-                    ramp_down,
-                    unit.ramp_down_limit
-                )
-                err_count += 1
-            end
-
-            # Verify startup costs & minimum downtime
-            if is_starting_up
-
-                # Calculate how much time the unit has been offline
-                time_down = 0
-                for k in 1:(t-1)
-                    if !is_on[t-k]
-                        time_down += 1
-                    else
-                        break
                     end
-                end
-                if (t == time_down + 1) && (unit.initial_status < 0)
-                    time_down -= unit.initial_status
-                end
 
-                # Calculate startup costs
+                    # Check minimum uptime
-                for c in unit.startup_categories
+                    if time_up < unit.min_uptime
-                    if time_down >= c.delay
+                        @error @sprintf(
-                        startup_cost = c.cost
+                            "Unit %s violates minimum uptime at time %d",
+                            unit.name,
+                            t
+                        )
+                        err_count += 1
                     end
                 end
 
-                # Check minimum downtime
+                # Verify production costs
-                if time_down < unit.min_downtime
+                if abs(actual_production_cost[t] - production_cost) > 1.00
                     @error @sprintf(
-                        "Unit %s violates minimum downtime at time %d",
+                        "Unit %s has unexpected production cost at time %d (%.2f should be %.2f)",
                         unit.name,
-                        t
+                        t,
+                        actual_production_cost[t],
+                        production_cost
+                    )
+                    err_count += 1
+                end
+
+                # Verify startup costs
+                if abs(actual_startup_cost[t] - startup_cost) > 1.00
+                    @error @sprintf(
+                        "Unit %s has unexpected startup cost at time %d (%.2f should be %.2f)",
+                        unit.name,
+                        t,
+                        actual_startup_cost[t],
+                        startup_cost
                     )
                     err_count += 1
                 end
             end
+        end
+        for pu in sc.profiled_units
+            production = solution[sc.name]["Profiled production (MW)"][pu.name]
 
-            # Verify minimum uptime
+            for t in 1:instance.time
-            if is_shutting_down
+                # Unit must produce at least its minimum power
-
+                if production[t] < pu.min_power[t] - tol
-                # Calculate how much time the unit has been online
-                time_up = 0
-                for k in 1:(t-1)
-                    if is_on[t-k]
-                        time_up += 1
-                    else
-                        break
-                    end
-                end
-                if (t == time_up + 1) && (unit.initial_status > 0)
-                    time_up += unit.initial_status
-                end
-
-                # Check minimum uptime
-                if time_up < unit.min_uptime
                     @error @sprintf(
-                        "Unit %s violates minimum uptime at time %d",
+                        "Profiled unit %s produces below its minimum limit at time %d (%.2f < %.2f)",
-                        unit.name,
+                        pu.name,
-                        t
+                        t,
+                        production[t],
+                        pu.min_power[t]
                     )
                     err_count += 1
                 end
-            end
 
-            # Verify production costs
+                # Unit must produce at most its maximum power
-            if abs(actual_production_cost[t] - production_cost) > 1.00
+                if production[t] > pu.max_power[t] + tol
-                @error @sprintf(
+                    @error @sprintf(
-                    "Unit %s has unexpected production cost at time %d (%.2f should be %.2f)",
+                        "Profiled unit %s produces above its maximum limit at time %d (%.2f > %.2f)",
-                    unit.name,
+                        pu.name,
-                    t,
+                        t,
-                    actual_production_cost[t],
+                        production[t],
-                    production_cost
+                        pu.max_power[t]
-                )
+                    )
-                err_count += 1
+                    err_count += 1
-            end
+                end
-
-            # Verify startup costs
-            if abs(actual_startup_cost[t] - startup_cost) > 1.00
-                @error @sprintf(
-                    "Unit %s has unexpected startup cost at time %d (%.2f should be %.2f)",
-                    unit.name,
-                    t,
-                    actual_startup_cost[t],
-                    startup_cost
-                )
-                err_count += 1
             end
         end
     end
-
     return err_count
 end
 
 function _validate_reserve_and_demand(instance, solution, tol = 0.01)
     err_count = 0
-    for t in 1:instance.time
+    for sc in instance.scenarios
-        load_curtail = 0
+        for t in 1:instance.time
-        fixed_load = sum(b.load[t] for b in instance.buses)
+            load_curtail = 0
-        ps_load = 0
+            fixed_load = sum(b.load[t] for b in sc.buses)
-        if length(instance.price_sensitive_loads) > 0
+            ps_load = 0
-            ps_load = sum(
+            production = 0
-                solution["Price-sensitive loads (MW)"][ps.name][t] for
+            if length(sc.price_sensitive_loads) > 0
-                ps in instance.price_sensitive_loads
+                ps_load = sum(
-            )
+                    solution[sc.name]["Price-sensitive loads (MW)"][ps.name][t]
-        end
+                    for ps in sc.price_sensitive_loads
-        production =
-            sum(solution["Production (MW)"][g.name][t] for g in instance.units)
-        if "Load curtail (MW)" in keys(solution)
-            load_curtail = sum(
-                solution["Load curtail (MW)"][b.name][t] for
-                b in instance.buses
-            )
-        end
-        balance = fixed_load - load_curtail - production + ps_load
-
-        # Verify that production equals demand
-        if abs(balance) > tol
-            @error @sprintf(
-                "Non-zero power balance at time %d (%.2f + %.2f - %.2f - %.2f != 0)",
-                t,
-                fixed_load,
-                ps_load,
-                load_curtail,
-                production,
-            )
-            err_count += 1
-        end
-
-        # Verify reserves
-        for r in instance.reserves
-            if r.type == "spinning"
-                provided = sum(
-                    solution["Spinning reserve (MW)"][r.name][g.name][t] for
-                    g in r.units
                 )
-                shortfall =
+            end
-                    solution["Spinning reserve shortfall (MW)"][r.name][t]
+            if length(sc.thermal_units) > 0
-                required = r.amount[t]
+                production = sum(
-
+                    solution[sc.name]["Thermal production (MW)"][g.name][t]
-                if provided + shortfall < required - tol
+                    for g in sc.thermal_units
-                    @error @sprintf(
-                        "Insufficient reserve %s at time %d (%.2f + %.2f < %.2f)",
-                        r.name,
-                        t,
-                        provided,
-                        shortfall,
-                        required,
-                    )
-                end
-            elseif r.type == "flexiramp"
-                upflexiramp = sum(
-                    solution["Up-flexiramp (MW)"][r.name][g.name][t] for
-                    g in r.units
                 )
-                upflexiramp_shortfall =
+            end
-                    solution["Up-flexiramp shortfall (MW)"][r.name][t]
+            if length(sc.profiled_units) > 0
-
+                production += sum(
-                if upflexiramp + upflexiramp_shortfall < r.amount[t] - tol
+                    solution[sc.name]["Profiled production (MW)"][pu.name][t]
-                    @error @sprintf(
+                    for pu in sc.profiled_units
-                        "Insufficient up-flexiramp at time %d (%.2f + %.2f < %.2f)",
-                        t,
-                        upflexiramp,
-                        upflexiramp_shortfall,
-                        r.amount[t],
-                    )
-                    err_count += 1
-                end
-
-                dwflexiramp = sum(
-                    solution["Down-flexiramp (MW)"][r.name][g.name][t] for
-                    g in r.units
                 )
-                dwflexiramp_shortfall =
+            end
-                    solution["Down-flexiramp shortfall (MW)"][r.name][t]
+            if "Load curtail (MW)" in keys(solution)
+                load_curtail = sum(
+                    solution[sc.name]["Load curtail (MW)"][b.name][t] for
+                    b in sc.buses
+                )
+            end
+            balance = fixed_load - load_curtail - production + ps_load
 
-                if dwflexiramp + dwflexiramp_shortfall < r.amount[t] - tol
+            # Verify that production equals demand
-                    @error @sprintf(
+            if abs(balance) > tol
-                        "Insufficient down-flexiramp at time %d (%.2f + %.2f < %.2f)",
+                @error @sprintf(
-                        t,
+                    "Non-zero power balance at time %d (%.2f + %.2f - %.2f - %.2f != 0)",
-                        dwflexiramp,
+                    t,
-                        dwflexiramp_shortfall,
+                    fixed_load,
-                        r.amount[t],
+                    ps_load,
+                    load_curtail,
+                    production,
+                )
+                err_count += 1
+            end
+
+            # Verify reserves
+            for r in sc.reserves
+                if r.type == "spinning"
+                    provided = sum(
+                        solution[sc.name]["Spinning reserve (MW)"][r.name][g.name][t]
+                        for g in r.thermal_units
                     )
-                    err_count += 1
+                    shortfall =
+                        solution[sc.name]["Spinning reserve shortfall (MW)"][r.name][t]
+                    required = r.amount[t]
+
+                    if provided + shortfall < required - tol
+                        @error @sprintf(
+                            "Insufficient reserve %s at time %d (%.2f + %.2f < %.2f)",
+                            r.name,
+                            t,
+                            provided,
+                            shortfall,
+                            required,
+                        )
+                    end
+                elseif r.type == "flexiramp"
+                    upflexiramp = sum(
+                        solution[sc.name]["Up-flexiramp (MW)"][r.name][g.name][t]
+                        for g in r.thermal_units
+                    )
+                    upflexiramp_shortfall =
+                        solution[sc.name]["Up-flexiramp shortfall (MW)"][r.name][t]
+
+                    if upflexiramp + upflexiramp_shortfall < r.amount[t] - tol
+                        @error @sprintf(
+                            "Insufficient up-flexiramp at time %d (%.2f + %.2f < %.2f)",
+                            t,
+                            upflexiramp,
+                            upflexiramp_shortfall,
+                            r.amount[t],
+                        )
+                        err_count += 1
+                    end
+
+                    dwflexiramp = sum(
+                        solution[sc.name]["Down-flexiramp (MW)"][r.name][g.name][t]
+                        for g in r.thermal_units
+                    )
+                    dwflexiramp_shortfall =
+                        solution[sc.name]["Down-flexiramp shortfall (MW)"][r.name][t]
+
+                    if dwflexiramp + dwflexiramp_shortfall < r.amount[t] - tol
+                        @error @sprintf(
+                            "Insufficient down-flexiramp at time %d (%.2f + %.2f < %.2f)",
+                            t,
+                            dwflexiramp,
+                            dwflexiramp_shortfall,
+                            r.amount[t],
+                        )
+                        err_count += 1
+                    end
+                else
+                    error("Unknown reserve type: $(r.type)")
                 end
-            else
-                error("Unknown reserve type: $(r.type)")
             end
         end
     end

test/Project.toml

@@ -1,25 +1,20 @@
+name = "UnitCommitmentT"
+uuid = "a3b7a17a-ab64-45e4-a924-cd5ae7dc644e"
+authors = ["Alinson S. Xavier <git@axavier.org>"]
+version = "0.1.0"
+
 [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"
+HiGHS = "87dc4568-4c63-4d18-b0c0-bb2238e4078b"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
+JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
 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"
+Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
-
+UnitCommitment = "64606440-39ea-11e9-0f29-3303a1d3d877"
-[compat]
-DataStructures = "0.18"
-Distributions = "0.25"
-GZip = "0.5"
-JSON = "0.21"
-JuMP = "1"
-MathOptInterface = "1"
-PackageCompiler = "1"
-julia = "1"

test/import/egret_test.jl

@@ -1,20 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using UnitCommitment
-
-@testset "read_egret_solution" begin
-    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 length(solution[attr]["115_STEAM_1"]) == 48
-    end
-    @test solution["Production cost (\$)"]["315_CT_6"][15:20] ==
-          [0.0, 0.0, 884.44, 1470.71, 1470.71, 884.44]
-    @test solution["Startup cost (\$)"]["315_CT_6"][15:20] ==
-          [0.0, 0.0, 5665.23, 0.0, 0.0, 0.0]
-    @test length(keys(solution["Is on"])) == 154
-end

test/instance/migrate_test.jl

@@ -1,18 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
-
-@testset "read v0.2" begin
-    instance = UnitCommitment.read("$FIXTURES/ucjl-0.2.json.gz")
-    @test length(instance.reserves_by_name["r1"].amount) == 4
-    @test instance.units_by_name["g2"].reserves[1].name == "r1"
-end
-
-@testset "read v0.3" begin
-    instance = UnitCommitment.read("$FIXTURES/ucjl-0.3.json.gz")
-    @test length(instance.units) == 6
-    @test length(instance.buses) == 14
-    @test length(instance.lines) == 20
-end

test/instance/read_test.jl

@@ -1,126 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
-
-@testset "read_benchmark" begin
-    instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
-
-    @test length(instance.lines) == 20
-    @test length(instance.buses) == 14
-    @test length(instance.units) == 6
-    @test length(instance.contingencies) == 19
-    @test length(instance.price_sensitive_loads) == 1
-    @test instance.time == 4
-
-    @test instance.lines[5].name == "l5"
-    @test instance.lines[5].source.name == "b2"
-    @test instance.lines[5].target.name == "b5"
-    @test instance.lines[5].reactance ≈ 0.17388
-    @test instance.lines[5].susceptance ≈ 10.037550333
-    @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"
-    @test instance.lines[1].target.name == "b2"
-    @test instance.lines[1].reactance ≈ 0.059170
-    @test instance.lines[1].susceptance ≈ 29.496860773945
-    @test instance.lines[1].normal_flow_limit == [300.0 for t in 1:4]
-    @test instance.lines[1].emergency_flow_limit == [400.0 for t in 1:4]
-    @test instance.lines[1].flow_limit_penalty == [1e3 for t in 1:4]
-
-    @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"
-
-    @test instance.reserves[1].name == "r1"
-    @test instance.reserves[1].type == "spinning"
-    @test instance.reserves[1].amount == [100.0, 100.0, 100.0, 100.0]
-    @test instance.reserves_by_name["r1"].name == "r1"
-
-    unit = instance.units[1]
-    @test unit.name == "g1"
-    @test unit.bus.name == "b1"
-    @test unit.ramp_up_limit == 1e6
-    @test unit.ramp_down_limit == 1e6
-    @test unit.startup_limit == 1e6
-    @test unit.shutdown_limit == 1e6
-    @test unit.must_run == [false for t in 1:4]
-    @test unit.min_power_cost == [1400.0 for t in 1:4]
-    @test unit.min_uptime == 1
-    @test unit.min_downtime == 1
-    for t in 1:1
-        @test unit.cost_segments[1].mw[t] == 10.0
-        @test unit.cost_segments[2].mw[t] == 20.0
-        @test unit.cost_segments[3].mw[t] == 5.0
-        @test unit.cost_segments[1].cost[t] ≈ 20.0
-        @test unit.cost_segments[2].cost[t] ≈ 30.0
-        @test unit.cost_segments[3].cost[t] ≈ 40.0
-    end
-    @test length(unit.startup_categories) == 3
-    @test unit.startup_categories[1].delay == 1
-    @test unit.startup_categories[2].delay == 2
-    @test unit.startup_categories[3].delay == 3
-    @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 length(unit.reserves) == 0
-    @test instance.units_by_name["g1"].name == "g1"
-
-    unit = instance.units[2]
-    @test unit.name == "g2"
-    @test unit.must_run == [false for t in 1:4]
-    @test length(unit.reserves) == 1
-
-    unit = instance.units[3]
-    @test unit.name == "g3"
-    @test unit.bus.name == "b3"
-    @test unit.ramp_up_limit == 70.0
-    @test unit.ramp_down_limit == 70.0
-    @test unit.startup_limit == 70.0
-    @test unit.shutdown_limit == 70.0
-    @test unit.must_run == [true for t in 1:4]
-    @test unit.min_power_cost == [0.0 for t in 1:4]
-    @test unit.min_uptime == 1
-    @test unit.min_downtime == 1
-    for t in 1:4
-        @test unit.cost_segments[1].mw[t] ≈ 33
-        @test unit.cost_segments[2].mw[t] ≈ 33
-        @test unit.cost_segments[3].mw[t] ≈ 34
-        @test unit.cost_segments[1].cost[t] ≈ 33.75
-        @test unit.cost_segments[2].cost[t] ≈ 38.04
-        @test unit.cost_segments[3].cost[t] ≈ 44.77853
-    end
-    @test length(unit.reserves) == 1
-    @test unit.reserves[1].name == "r1"
-
-    @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
-    instance = UnitCommitment.read("$FIXTURES/case14-sub-hourly.json.gz")
-    @test instance.time == 4
-    unit = instance.units[1]
-    @test unit.name == "g1"
-    @test unit.min_uptime == 2
-    @test unit.min_downtime == 2
-    @test length(unit.startup_categories) == 3
-    @test unit.startup_categories[1].delay == 2
-    @test unit.startup_categories[2].delay == 4
-    @test unit.startup_categories[3].delay == 6
-    @test unit.initial_status == -200
-end

test/model/formulations_test.jl

@@ -1,84 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using UnitCommitment
-using JuMP
-using Cbc
-using JSON
-import UnitCommitment:
-    ArrCon2000,
-    CarArr2006,
-    DamKucRajAta2016,
-    Formulation,
-    Gar1962,
-    KnuOstWat2018,
-    MorLatRam2013,
-    PanGua2016,
-    XavQiuWanThi2019,
-    WanHob2016
-
-function _test(
-    formulation::Formulation;
-    instances = ["case14"],
-    dump::Bool = false,
-)::Nothing
-    for instance_name in instances
-        instance = UnitCommitment.read("$(FIXTURES)/$(instance_name).json.gz")
-        model = UnitCommitment.build_model(
-            instance = instance,
-            formulation = formulation,
-            optimizer = Cbc.Optimizer,
-            variable_names = true,
-        )
-        set_silent(model)
-        UnitCommitment.optimize!(model)
-        solution = UnitCommitment.solution(model)
-        if dump
-            open("/tmp/ucjl.json", "w") do f
-                return write(f, JSON.json(solution, 2))
-            end
-            write_to_file(model, "/tmp/ucjl.lp")
-        end
-        @test UnitCommitment.validate(instance, solution)
-    end
-    return
-end
-
-@testset "formulations" begin
-    @testset "default" begin
-        _test(Formulation())
-    end
-    @testset "ArrCon2000" begin
-        _test(Formulation(ramping = ArrCon2000.Ramping()))
-    end
-    @testset "DamKucRajAta2016" begin
-        _test(Formulation(ramping = DamKucRajAta2016.Ramping()))
-    end
-    @testset "MorLatRam2013" begin
-        _test(
-            Formulation(
-                ramping = MorLatRam2013.Ramping(),
-                startup_costs = MorLatRam2013.StartupCosts(),
-            ),
-        )
-    end
-    @testset "PanGua2016" begin
-        _test(Formulation(ramping = PanGua2016.Ramping()))
-    end
-    @testset "Gar1962" begin
-        _test(Formulation(pwl_costs = Gar1962.PwlCosts()))
-    end
-    @testset "CarArr2006" begin
-        _test(Formulation(pwl_costs = CarArr2006.PwlCosts()))
-    end
-    @testset "KnuOstWat2018" begin
-        _test(Formulation(pwl_costs = KnuOstWat2018.PwlCosts()))
-    end
-    @testset "WanHob2016" begin
-        _test(
-            Formulation(ramping = WanHob2016.Ramping()),
-            instances = ["case14-flex"],
-        )
-    end
-end

test/runtests.jl

@@ -1,42 +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 Test
-using UnitCommitment
-
-push!(Base.LOAD_PATH, @__DIR__)
-UnitCommitment._setup_logger(level = Base.CoreLogging.Error)
-
-FIXTURES = "$(@__DIR__)/fixtures"
-
-@testset "UnitCommitment" begin
-    include("usage.jl")
-    @testset "import" begin
-        include("import/egret_test.jl")
-    end
-    @testset "instance" begin
-        include("instance/read_test.jl")
-        include("instance/migrate_test.jl")
-    end
-    @testset "model" begin
-        include("model/formulations_test.jl")
-    end
-    @testset "solution" begin
-        @testset "XavQiuWanThi19" begin
-            include("solution/methods/XavQiuWanThi19/filter_test.jl")
-            include("solution/methods/XavQiuWanThi19/find_test.jl")
-            include("solution/methods/XavQiuWanThi19/sensitivity_test.jl")
-        end
-    end
-    @testset "transform" begin
-        include("transform/initcond_test.jl")
-        include("transform/slice_test.jl")
-        @testset "randomize" begin
-            include("transform/randomize/XavQiuAhm2021_test.jl")
-        end
-    end
-    @testset "validation" begin
-        include("validation/repair_test.jl")
-    end
-end

test/solution/methods/XavQiuWanThi19/filter_test.jl

@@ -1,83 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using UnitCommitment, Test, LinearAlgebra
-import UnitCommitment: _Violation, _offer, _query
-
-@testset "_ViolationFilter" begin
-    instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
-    filter = UnitCommitment._ViolationFilter(max_per_line = 1, max_total = 2)
-
-    _offer(
-        filter,
-        _Violation(
-            time = 1,
-            monitored_line = instance.lines[1],
-            outage_line = nothing,
-            amount = 100.0,
-        ),
-    )
-    _offer(
-        filter,
-        _Violation(
-            time = 1,
-            monitored_line = instance.lines[1],
-            outage_line = instance.lines[1],
-            amount = 300.0,
-        ),
-    )
-    _offer(
-        filter,
-        _Violation(
-            time = 1,
-            monitored_line = instance.lines[1],
-            outage_line = instance.lines[5],
-            amount = 500.0,
-        ),
-    )
-    _offer(
-        filter,
-        _Violation(
-            time = 1,
-            monitored_line = instance.lines[1],
-            outage_line = instance.lines[4],
-            amount = 400.0,
-        ),
-    )
-    _offer(
-        filter,
-        _Violation(
-            time = 1,
-            monitored_line = instance.lines[2],
-            outage_line = instance.lines[1],
-            amount = 200.0,
-        ),
-    )
-    _offer(
-        filter,
-        _Violation(
-            time = 1,
-            monitored_line = instance.lines[2],
-            outage_line = instance.lines[8],
-            amount = 100.0,
-        ),
-    )
-
-    actual = _query(filter)
-    expected = [
-        _Violation(
-            time = 1,
-            monitored_line = instance.lines[2],
-            outage_line = instance.lines[1],
-            amount = 200.0,
-        ),
-        _Violation(
-            time = 1,
-            monitored_line = instance.lines[1],
-            outage_line = instance.lines[5],
-            amount = 500.0,
-        ),
-    ]
-    @test actual == expected
-end

test/solution/methods/XavQiuWanThi19/find_test.jl

@@ -1,35 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using UnitCommitment, Test, LinearAlgebra
-import UnitCommitment: _Violation, _offer, _query
-
-@testset "find_violations" begin
-    instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
-    for line in instance.lines, t in 1:instance.time
-        line.normal_flow_limit[t] = 1.0
-        line.emergency_flow_limit[t] = 1.0
-    end
-    isf = UnitCommitment._injection_shift_factors(
-        lines = instance.lines,
-        buses = instance.buses,
-    )
-    lodf = UnitCommitment._line_outage_factors(
-        lines = instance.lines,
-        buses = instance.buses,
-        isf = isf,
-    )
-    inj = [1000.0 for b in 1:13, t in 1:instance.time]
-    overflow = [0.0 for l in instance.lines, t in 1:instance.time]
-    violations = UnitCommitment._find_violations(
-        instance = instance,
-        net_injections = inj,
-        overflow = overflow,
-        isf = isf,
-        lodf = lodf,
-        max_per_line = 1,
-        max_per_period = 5,
-    )
-    @test length(violations) == 20
-end

test/solution/methods/XavQiuWanThi19/sensitivity_test.jl

@@ -1,143 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using UnitCommitment, Test, LinearAlgebra
-
-@testset "_susceptance_matrix" begin
-    instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
-    actual = UnitCommitment._susceptance_matrix(instance.lines)
-    @test size(actual) == (20, 20)
-    expected = Diagonal([
-        29.5,
-        7.83,
-        8.82,
-        9.9,
-        10.04,
-        10.2,
-        41.45,
-        8.35,
-        3.14,
-        6.93,
-        8.77,
-        6.82,
-        13.4,
-        9.91,
-        15.87,
-        20.65,
-        6.46,
-        9.09,
-        8.73,
-        5.02,
-    ])
-    @test round.(actual, digits = 2) == expected
-end
-
-@testset "_reduced_incidence_matrix" begin
-    instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
-    actual = UnitCommitment._reduced_incidence_matrix(
-        lines = instance.lines,
-        buses = instance.buses,
-    )
-    @test size(actual) == (20, 13)
-    @test actual[1, 1] == -1.0
-    @test actual[3, 1] == 1.0
-    @test actual[4, 1] == 1.0
-    @test actual[5, 1] == 1.0
-    @test actual[3, 2] == -1.0
-    @test actual[6, 2] == 1.0
-    @test actual[4, 3] == -1.0
-    @test actual[6, 3] == -1.0
-    @test actual[7, 3] == 1.0
-    @test actual[8, 3] == 1.0
-    @test actual[9, 3] == 1.0
-    @test actual[2, 4] == -1.0
-    @test actual[5, 4] == -1.0
-    @test actual[7, 4] == -1.0
-    @test actual[10, 4] == 1.0
-    @test actual[10, 5] == -1.0
-    @test actual[11, 5] == 1.0
-    @test actual[12, 5] == 1.0
-    @test actual[13, 5] == 1.0
-    @test actual[8, 6] == -1.0
-    @test actual[14, 6] == 1.0
-    @test actual[15, 6] == 1.0
-    @test actual[14, 7] == -1.0
-    @test actual[9, 8] == -1.0
-    @test actual[15, 8] == -1.0
-    @test actual[16, 8] == 1.0
-    @test actual[17, 8] == 1.0
-    @test actual[16, 9] == -1.0
-    @test actual[18, 9] == 1.0
-    @test actual[11, 10] == -1.0
-    @test actual[18, 10] == -1.0
-    @test actual[12, 11] == -1.0
-    @test actual[19, 11] == 1.0
-    @test actual[13, 12] == -1.0
-    @test actual[19, 12] == -1.0
-    @test actual[20, 12] == 1.0
-    @test actual[17, 13] == -1.0
-    @test actual[20, 13] == -1.0
-end
-
-@testset "_injection_shift_factors" begin
-    instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
-    actual = UnitCommitment._injection_shift_factors(
-        lines = instance.lines,
-        buses = instance.buses,
-    )
-    @test size(actual) == (20, 13)
-    @test round.(actual, digits = 2) == [
-        -0.84 -0.75 -0.67 -0.61 -0.63 -0.66 -0.66 -0.65 -0.65 -0.64 -0.63 -0.63 -0.64
-        -0.16 -0.25 -0.33 -0.39 -0.37 -0.34 -0.34 -0.35 -0.35 -0.36 -0.37 -0.37 -0.36
-        0.03 -0.53 -0.15 -0.1 -0.12 -0.14 -0.14 -0.14 -0.13 -0.13 -0.12 -0.12 -0.13
-        0.06 -0.14 -0.32 -0.22 -0.25 -0.3 -0.3 -0.29 -0.28 -0.27 -0.25 -0.26 -0.27
-        0.08 -0.07 -0.2 -0.29 -0.26 -0.22 -0.22 -0.22 -0.23 -0.25 -0.26 -0.26 -0.24
-        0.03 0.47 -0.15 -0.1 -0.12 -0.14 -0.14 -0.14 -0.13 -0.13 -0.12 -0.12 -0.13
-        0.08 0.31 0.5 -0.3 -0.03 0.36 0.36 0.28 0.23 0.1 -0.0 0.02 0.17
-        0.0 0.01 0.02 -0.01 -0.22 -0.63 -0.63 -0.45 -0.41 -0.32 -0.24 -0.25 -0.36
-        0.0 0.01 0.01 -0.01 -0.12 -0.17 -0.17 -0.26 -0.24 -0.18 -0.14 -0.14 -0.21
-        -0.0 -0.02 -0.03 0.02 -0.66 -0.2 -0.2 -0.29 -0.36 -0.5 -0.63 -0.61 -0.43
-        -0.0 -0.01 -0.02 0.01 0.21 -0.12 -0.12 -0.17 -0.28 -0.53 0.18 0.15 -0.03
-        -0.0 -0.0 -0.0 0.0 0.03 -0.02 -0.02 -0.03 -0.02 0.01 -0.52 -0.17 -0.09
-        -0.0 -0.01 -0.01 0.01 0.11 -0.06 -0.06 -0.09 -0.05 0.02 -0.28 -0.59 -0.31
-        -0.0 -0.0 -0.0 -0.0 -0.0 -0.0 -1.0 -0.0 -0.0 -0.0 -0.0 -0.0 0.0
-        0.0 0.01 0.02 -0.01 -0.22 0.37 0.37 -0.45 -0.41 -0.32 -0.24 -0.25 -0.36
-        0.0 0.01 0.02 -0.01 -0.21 0.12 0.12 0.17 -0.72 -0.47 -0.18 -0.15 0.03
-        0.0 0.01 0.01 -0.01 -0.14 0.08 0.08 0.12 0.07 -0.03 -0.2 -0.24 -0.6
-        0.0 0.01 0.02 -0.01 -0.21 0.12 0.12 0.17 0.28 -0.47 -0.18 -0.15 0.03
-        -0.0 -0.0 -0.0 0.0 0.03 -0.02 -0.02 -0.03 -0.02 0.01 0.48 -0.17 -0.09
-        -0.0 -0.01 -0.01 0.01 0.14 -0.08 -0.08 -0.12 -0.07 0.03 0.2 0.24 -0.4
-    ]
-end
-
-@testset "_line_outage_factors" begin
-    instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
-    isf_before = UnitCommitment._injection_shift_factors(
-        lines = instance.lines,
-        buses = instance.buses,
-    )
-    lodf = UnitCommitment._line_outage_factors(
-        lines = instance.lines,
-        buses = instance.buses,
-        isf = isf_before,
-    )
-    for contingency in instance.contingencies
-        for lc in contingency.lines
-            prev_susceptance = lc.susceptance
-            lc.susceptance = 0.0
-            isf_after = UnitCommitment._injection_shift_factors(
-                lines = instance.lines,
-                buses = instance.buses,
-            )
-            lc.susceptance = prev_susceptance
-            for lm in instance.lines
-                expected = isf_after[lm.offset, :]
-                actual =
-                    isf_before[lm.offset, :] +
-                    lodf[lm.offset, lc.offset] * isf_before[lc.offset, :]
-                @test norm(expected - actual) < 1e-6
-            end
-        end
-    end
-end

test/src/UnitCommitmentT.jl

@@ -0,0 +1,58 @@
+module UnitCommitmentT
+
+using JuliaFormatter
+using UnitCommitment
+using Test
+
+include("usage.jl")
+include("import/egret_test.jl")
+include("instance/read_test.jl")
+include("instance/migrate_test.jl")
+include("model/formulations_test.jl")
+include("solution/methods/XavQiuWanThi19/filter_test.jl")
+include("solution/methods/XavQiuWanThi19/find_test.jl")
+include("solution/methods/XavQiuWanThi19/sensitivity_test.jl")
+include("transform/initcond_test.jl")
+include("transform/slice_test.jl")
+include("transform/randomize/XavQiuAhm2021_test.jl")
+include("validation/repair_test.jl")
+include("lmp/conventional_test.jl")
+include("lmp/aelmp_test.jl")
+
+basedir = dirname(@__FILE__)
+
+function fixture(path::String)::String
+    return "$basedir/../fixtures/$path"
+end
+
+function runtests()
+    println("Running tests...")
+    UnitCommitment._setup_logger(level = Base.CoreLogging.Error)
+    @testset "UnitCommitment" begin
+        usage_test()
+        import_egret_test()
+        instance_read_test()
+        instance_migrate_test()
+        model_formulations_test()
+        solution_methods_XavQiuWanThi19_filter_test()
+        solution_methods_XavQiuWanThi19_find_test()
+        solution_methods_XavQiuWanThi19_sensitivity_test()
+        transform_initcond_test()
+        transform_slice_test()
+        transform_randomize_XavQiuAhm2021_test()
+        validation_repair_test()
+        lmp_conventional_test()
+        lmp_aelmp_test()
+    end
+    return
+end
+
+function format()
+    JuliaFormatter.format(basedir, verbose = true)
+    JuliaFormatter.format("$basedir/../../src", verbose = true)
+    return
+end
+
+export runtests, format
+
+end # module UnitCommitmentT

test/src/import/egret_test.jl

@@ -0,0 +1,23 @@
+# 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
+
+function import_egret_test()
+    @testset "read_egret_solution" begin
+        solution =
+            UnitCommitment.read_egret_solution(fixture("egret_output.json.gz"))
+        for attr in
+            ["Is on", "Thermal production (MW)", "Thermal production cost (\$)"]
+            @test attr in keys(solution)
+            @test "115_STEAM_1" in keys(solution[attr])
+            @test length(solution[attr]["115_STEAM_1"]) == 48
+        end
+        @test solution["Thermal production cost (\$)"]["315_CT_6"][15:20] ==
+              [0.0, 0.0, 884.44, 1470.71, 1470.71, 884.44]
+        @test solution["Startup cost (\$)"]["315_CT_6"][15:20] ==
+              [0.0, 0.0, 5665.23, 0.0, 0.0, 0.0]
+        @test length(keys(solution["Is on"])) == 154
+    end
+end

test/src/instance/migrate_test.jl

@@ -0,0 +1,24 @@
+# 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, LinearAlgebra, Cbc, JuMP, JSON, GZip
+
+function instance_migrate_test()
+    @testset "read v0.2" begin
+        instance = UnitCommitment.read(fixture("/ucjl-0.2.json.gz"))
+        @test length(instance.scenarios) == 1
+        sc = instance.scenarios[1]
+        @test length(sc.reserves_by_name["r1"].amount) == 4
+        @test sc.thermal_units_by_name["g2"].reserves[1].name == "r1"
+    end
+
+    @testset "read v0.3" begin
+        instance = UnitCommitment.read(fixture("/ucjl-0.3.json.gz"))
+        @test length(instance.scenarios) == 1
+        sc = instance.scenarios[1]
+        @test length(sc.thermal_units) == 6
+        @test length(sc.buses) == 14
+        @test length(sc.lines) == 20
+    end
+end

test/src/instance/read_test.jl

@@ -0,0 +1,168 @@
+# 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, LinearAlgebra, Cbc, JuMP, JSON, GZip
+
+function instance_read_test()
+    @testset "read_benchmark" begin
+        instance = UnitCommitment.read(fixture("case14.json.gz"))
+
+        @test repr(instance) == (
+            "UnitCommitmentInstance(1 scenarios, 6 thermal units, 0 profiled units, 14 buses, " *
+            "20 lines, 19 contingencies, 1 price sensitive loads, 4 time steps)"
+        )
+
+        @test length(instance.scenarios) == 1
+        sc = instance.scenarios[1]
+        @test length(sc.lines) == 20
+        @test length(sc.buses) == 14
+        @test length(sc.thermal_units) == 6
+        @test length(sc.contingencies) == 19
+        @test length(sc.price_sensitive_loads) == 1
+        @test instance.time == 4
+
+        @test sc.lines[5].name == "l5"
+        @test sc.lines[5].source.name == "b2"
+        @test sc.lines[5].target.name == "b5"
+        @test sc.lines[5].reactance ≈ 0.17388
+        @test sc.lines[5].susceptance ≈ 10.037550333
+        @test sc.lines[5].normal_flow_limit == [1e8 for t in 1:4]
+        @test sc.lines[5].emergency_flow_limit == [1e8 for t in 1:4]
+        @test sc.lines[5].flow_limit_penalty == [5e3 for t in 1:4]
+        @test sc.lines_by_name["l5"].name == "l5"
+
+        @test sc.lines[1].name == "l1"
+        @test sc.lines[1].source.name == "b1"
+        @test sc.lines[1].target.name == "b2"
+        @test sc.lines[1].reactance ≈ 0.059170
+        @test sc.lines[1].susceptance ≈ 29.496860773945
+        @test sc.lines[1].normal_flow_limit == [300.0 for t in 1:4]
+        @test sc.lines[1].emergency_flow_limit == [400.0 for t in 1:4]
+        @test sc.lines[1].flow_limit_penalty == [1e3 for t in 1:4]
+
+        @test sc.buses[9].name == "b9"
+        @test sc.buses[9].load == [35.36638, 33.25495, 31.67138, 31.14353]
+        @test sc.buses_by_name["b9"].name == "b9"
+
+        @test sc.reserves[1].name == "r1"
+        @test sc.reserves[1].type == "spinning"
+        @test sc.reserves[1].amount == [100.0, 100.0, 100.0, 100.0]
+        @test sc.reserves_by_name["r1"].name == "r1"
+
+        unit = sc.thermal_units[1]
+        @test unit.name == "g1"
+        @test unit.bus.name == "b1"
+        @test unit.ramp_up_limit == 1e6
+        @test unit.ramp_down_limit == 1e6
+        @test unit.startup_limit == 1e6
+        @test unit.shutdown_limit == 1e6
+        @test unit.must_run == [false for t in 1:4]
+        @test unit.min_power_cost == [1400.0 for t in 1:4]
+        @test unit.min_uptime == 1
+        @test unit.min_downtime == 1
+        for t in 1:1
+            @test unit.cost_segments[1].mw[t] == 10.0
+            @test unit.cost_segments[2].mw[t] == 20.0
+            @test unit.cost_segments[3].mw[t] == 5.0
+            @test unit.cost_segments[1].cost[t] ≈ 20.0
+            @test unit.cost_segments[2].cost[t] ≈ 30.0
+            @test unit.cost_segments[3].cost[t] ≈ 40.0
+        end
+        @test length(unit.startup_categories) == 3
+        @test unit.startup_categories[1].delay == 1
+        @test unit.startup_categories[2].delay == 2
+        @test unit.startup_categories[3].delay == 3
+        @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 length(unit.reserves) == 0
+        @test sc.thermal_units_by_name["g1"].name == "g1"
+
+        unit = sc.thermal_units[2]
+        @test unit.name == "g2"
+        @test unit.must_run == [false for t in 1:4]
+        @test length(unit.reserves) == 1
+
+        unit = sc.thermal_units[3]
+        @test unit.name == "g3"
+        @test unit.bus.name == "b3"
+        @test unit.ramp_up_limit == 70.0
+        @test unit.ramp_down_limit == 70.0
+        @test unit.startup_limit == 70.0
+        @test unit.shutdown_limit == 70.0
+        @test unit.must_run == [true for t in 1:4]
+        @test unit.min_power_cost == [0.0 for t in 1:4]
+        @test unit.min_uptime == 1
+        @test unit.min_downtime == 1
+        for t in 1:4
+            @test unit.cost_segments[1].mw[t] ≈ 33
+            @test unit.cost_segments[2].mw[t] ≈ 33
+            @test unit.cost_segments[3].mw[t] ≈ 34
+            @test unit.cost_segments[1].cost[t] ≈ 33.75
+            @test unit.cost_segments[2].cost[t] ≈ 38.04
+            @test unit.cost_segments[3].cost[t] ≈ 44.77853
+        end
+        @test length(unit.reserves) == 1
+        @test unit.reserves[1].name == "r1"
+
+        @test sc.contingencies[1].lines == [sc.lines[1]]
+        @test sc.contingencies[1].thermal_units == []
+        @test sc.contingencies[1].name == "c1"
+        @test sc.contingencies_by_name["c1"].name == "c1"
+
+        load = sc.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 sc.price_sensitive_loads_by_name["ps1"].name == "ps1"
+    end
+
+    @testset "read_benchmark sub-hourly" begin
+        instance = UnitCommitment.read(fixture("case14-sub-hourly.json.gz"))
+        @test instance.time == 4
+        unit = instance.scenarios[1].thermal_units[1]
+        @test unit.name == "g1"
+        @test unit.min_uptime == 2
+        @test unit.min_downtime == 2
+        @test length(unit.startup_categories) == 3
+        @test unit.startup_categories[1].delay == 2
+        @test unit.startup_categories[2].delay == 4
+        @test unit.startup_categories[3].delay == 6
+        @test unit.initial_status == -200
+    end
+
+    @testset "read_benchmark profiled-units" begin
+        instance = UnitCommitment.read(fixture("case14-profiled.json.gz"))
+        sc = instance.scenarios[1]
+        @test length(sc.profiled_units) == 2
+
+        first_pu = sc.profiled_units[1]
+        @test first_pu.name == "g7"
+        @test first_pu.bus.name == "b4"
+        @test first_pu.cost == [100.0 for t in 1:4]
+        @test first_pu.min_power == [60.0 for t in 1:4]
+        @test first_pu.max_power == [100.0 for t in 1:4]
+        @test sc.profiled_units_by_name["g7"].name == "g7"
+
+        second_pu = sc.profiled_units[2]
+        @test second_pu.name == "g8"
+        @test second_pu.bus.name == "b5"
+        @test second_pu.cost == [50.0 for t in 1:4]
+        @test second_pu.min_power == [0.0 for t in 1:4]
+        @test second_pu.max_power == [120.0 for t in 1:4]
+        @test sc.profiled_units_by_name["g8"].name == "g8"
+    end
+
+    @testset "read_benchmark commitmemt-status" begin
+        instance = UnitCommitment.read(fixture("case14-fixed-status.json.gz"))
+        sc = instance.scenarios[1]
+
+        @test sc.thermal_units[1].commitment_status == [nothing for t in 1:4]
+        @test sc.thermal_units[2].commitment_status == [true for t in 1:4]
+        @test sc.thermal_units[4].commitment_status == [false for t in 1:4]
+        @test sc.thermal_units[6].commitment_status ==
+              [false, nothing, true, nothing]
+    end
+end

test/src/lmp/aelmp_test.jl

@@ -0,0 +1,40 @@
+# 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, HiGHS, JuMP
+import UnitCommitment: AELMP
+
+function lmp_aelmp_test()
+    @testset "aelmp" begin
+        path = fixture("aelmp_simple.json.gz")
+        # model has to be solved first
+        instance = UnitCommitment.read(path)
+        model = UnitCommitment.build_model(
+            instance = instance,
+            optimizer = Cbc.Optimizer,
+            variable_names = true,
+        )
+        JuMP.set_silent(model)
+        UnitCommitment.optimize!(model)
+
+        # policy 1: allow offlines; consider startups
+        aelmp_1 = UnitCommitment.compute_lmp(
+            model,
+            AELMP(),
+            optimizer = HiGHS.Optimizer,
+        )
+        @test aelmp_1["s1", "B1", 1] ≈ 231.7 atol = 0.1
+
+        # policy 2: do not allow offlines; but consider startups
+        aelmp_2 = UnitCommitment.compute_lmp(
+            model,
+            AELMP(
+                allow_offline_participation = false,
+                consider_startup_costs = true,
+            ),
+            optimizer = HiGHS.Optimizer,
+        )
+        @test aelmp_2["s1", "B1", 1] ≈ 274.3 atol = 0.1
+    end
+end

test/src/lmp/conventional_test.jl

@@ -0,0 +1,53 @@
+# 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, HiGHS, JuMP
+import UnitCommitment: ConventionalLMP
+
+function solve_conventional_testcase(path::String)
+    instance = UnitCommitment.read(path)
+    model = UnitCommitment.build_model(
+        instance = instance,
+        optimizer = Cbc.Optimizer,
+        variable_names = true,
+    )
+    JuMP.set_silent(model)
+    UnitCommitment.optimize!(model)
+    lmp = UnitCommitment.compute_lmp(
+        model,
+        ConventionalLMP(),
+        optimizer = HiGHS.Optimizer,
+    )
+    return lmp
+end
+
+function lmp_conventional_test()
+    @testset "conventional" begin
+        # instance 1
+        path = fixture("lmp_simple_test_1.json.gz")
+        lmp = solve_conventional_testcase(path)
+        @test lmp["s1", "A", 1] == 50.0
+        @test lmp["s1", "B", 1] == 50.0
+
+        # instance 2
+        path = fixture("lmp_simple_test_2.json.gz")
+        lmp = solve_conventional_testcase(path)
+        @test lmp["s1", "A", 1] == 50.0
+        @test lmp["s1", "B", 1] == 60.0
+
+        # instance 3
+        path = fixture("lmp_simple_test_3.json.gz")
+        lmp = solve_conventional_testcase(path)
+        @test lmp["s1", "A", 1] == 50.0
+        @test lmp["s1", "B", 1] == 70.0
+        @test lmp["s1", "C", 1] == 100.0
+
+        # instance 4
+        path = fixture("lmp_simple_test_4.json.gz")
+        lmp = solve_conventional_testcase(path)
+        @test lmp["s1", "A", 1] == 50.0
+        @test lmp["s1", "B", 1] == 70.0
+        @test lmp["s1", "C", 1] == 90.0
+    end
+end

test/src/model/formulations_test.jl

@@ -0,0 +1,86 @@
+# 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
+using JuMP
+using Cbc
+using JSON
+import UnitCommitment:
+    ArrCon2000,
+    CarArr2006,
+    DamKucRajAta2016,
+    Formulation,
+    Gar1962,
+    KnuOstWat2018,
+    MorLatRam2013,
+    PanGua2016,
+    XavQiuWanThi2019,
+    WanHob2016
+
+function _test(
+    formulation::Formulation;
+    instances = ["case14"],
+    dump::Bool = false,
+)::Nothing
+    for instance_name in instances
+        instance = UnitCommitment.read(fixture("$(instance_name).json.gz"))
+        model = UnitCommitment.build_model(
+            instance = instance,
+            formulation = formulation,
+            optimizer = Cbc.Optimizer,
+            variable_names = true,
+        )
+        set_silent(model)
+        UnitCommitment.optimize!(model)
+        solution = UnitCommitment.solution(model)
+        if dump
+            open("/tmp/ucjl.json", "w") do f
+                return write(f, JSON.json(solution, 2))
+            end
+            write_to_file(model, "/tmp/ucjl.lp")
+        end
+        @test UnitCommitment.validate(instance, solution)
+    end
+    return
+end
+
+function model_formulations_test()
+    @testset "formulations" begin
+        @testset "default" begin
+            _test(Formulation())
+        end
+        @testset "ArrCon2000" begin
+            _test(Formulation(ramping = ArrCon2000.Ramping()))
+        end
+        @testset "DamKucRajAta2016" begin
+            _test(Formulation(ramping = DamKucRajAta2016.Ramping()))
+        end
+        @testset "MorLatRam2013" begin
+            _test(
+                Formulation(
+                    ramping = MorLatRam2013.Ramping(),
+                    startup_costs = MorLatRam2013.StartupCosts(),
+                ),
+            )
+        end
+        @testset "PanGua2016" begin
+            _test(Formulation(ramping = PanGua2016.Ramping()))
+        end
+        @testset "Gar1962" begin
+            _test(Formulation(pwl_costs = Gar1962.PwlCosts()))
+        end
+        @testset "CarArr2006" begin
+            _test(Formulation(pwl_costs = CarArr2006.PwlCosts()))
+        end
+        @testset "KnuOstWat2018" begin
+            _test(Formulation(pwl_costs = KnuOstWat2018.PwlCosts()))
+        end
+        @testset "WanHob2016" begin
+            _test(
+                Formulation(ramping = WanHob2016.Ramping()),
+                instances = ["case14-flex"],
+            )
+        end
+    end
+end

test/src/solution/methods/XavQiuWanThi19/filter_test.jl

@@ -0,0 +1,86 @@
+# 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, Test, LinearAlgebra
+import UnitCommitment: _Violation, _offer, _query
+
+function solution_methods_XavQiuWanThi19_filter_test()
+    @testset "_ViolationFilter" begin
+        instance = UnitCommitment.read(fixture("case14.json.gz"))
+        sc = instance.scenarios[1]
+        filter =
+            UnitCommitment._ViolationFilter(max_per_line = 1, max_total = 2)
+        _offer(
+            filter,
+            _Violation(
+                time = 1,
+                monitored_line = sc.lines[1],
+                outage_line = nothing,
+                amount = 100.0,
+            ),
+        )
+        _offer(
+            filter,
+            _Violation(
+                time = 1,
+                monitored_line = sc.lines[1],
+                outage_line = sc.lines[1],
+                amount = 300.0,
+            ),
+        )
+        _offer(
+            filter,
+            _Violation(
+                time = 1,
+                monitored_line = sc.lines[1],
+                outage_line = sc.lines[5],
+                amount = 500.0,
+            ),
+        )
+        _offer(
+            filter,
+            _Violation(
+                time = 1,
+                monitored_line = sc.lines[1],
+                outage_line = sc.lines[4],
+                amount = 400.0,
+            ),
+        )
+        _offer(
+            filter,
+            _Violation(
+                time = 1,
+                monitored_line = sc.lines[2],
+                outage_line = sc.lines[1],
+                amount = 200.0,
+            ),
+        )
+        _offer(
+            filter,
+            _Violation(
+                time = 1,
+                monitored_line = sc.lines[2],
+                outage_line = sc.lines[8],
+                amount = 100.0,
+            ),
+        )
+
+        actual = _query(filter)
+        expected = [
+            _Violation(
+                time = 1,
+                monitored_line = sc.lines[2],
+                outage_line = sc.lines[1],
+                amount = 200.0,
+            ),
+            _Violation(
+                time = 1,
+                monitored_line = sc.lines[1],
+                outage_line = sc.lines[5],
+                amount = 500.0,
+            ),
+        ]
+        @test actual == expected
+    end
+end

test/src/solution/methods/XavQiuWanThi19/find_test.jl

@@ -0,0 +1,39 @@
+# 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, Test, LinearAlgebra
+import UnitCommitment: _Violation, _offer, _query
+
+function solution_methods_XavQiuWanThi19_find_test()
+    @testset "find_violations" begin
+        instance = UnitCommitment.read(fixture("case14.json.gz"))
+        sc = instance.scenarios[1]
+        for line in sc.lines, t in 1:instance.time
+            line.normal_flow_limit[t] = 1.0
+            line.emergency_flow_limit[t] = 1.0
+        end
+        isf = UnitCommitment._injection_shift_factors(
+            lines = sc.lines,
+            buses = sc.buses,
+        )
+        lodf = UnitCommitment._line_outage_factors(
+            lines = sc.lines,
+            buses = sc.buses,
+            isf = isf,
+        )
+        inj = [1000.0 for b in 1:13, t in 1:instance.time]
+        overflow = [0.0 for l in sc.lines, t in 1:instance.time]
+        violations = UnitCommitment._find_violations(
+            instance = instance,
+            sc = sc,
+            net_injections = inj,
+            overflow = overflow,
+            isf = isf,
+            lodf = lodf,
+            max_per_line = 1,
+            max_per_period = 5,
+        )
+        @test length(violations) == 20
+    end
+end

test/src/solution/methods/XavQiuWanThi19/sensitivity_test.jl

@@ -0,0 +1,149 @@
+# 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, Test, LinearAlgebra
+
+function solution_methods_XavQiuWanThi19_sensitivity_test()
+    @testset "_susceptance_matrix" begin
+        instance = UnitCommitment.read(fixture("/case14.json.gz"))
+        sc = instance.scenarios[1]
+        actual = UnitCommitment._susceptance_matrix(sc.lines)
+        @test size(actual) == (20, 20)
+        expected = Diagonal([
+            29.5,
+            7.83,
+            8.82,
+            9.9,
+            10.04,
+            10.2,
+            41.45,
+            8.35,
+            3.14,
+            6.93,
+            8.77,
+            6.82,
+            13.4,
+            9.91,
+            15.87,
+            20.65,
+            6.46,
+            9.09,
+            8.73,
+            5.02,
+        ])
+        @test round.(actual, digits = 2) == expected
+    end
+
+    @testset "_reduced_incidence_matrix" begin
+        instance = UnitCommitment.read(fixture("/case14.json.gz"))
+        sc = instance.scenarios[1]
+        actual = UnitCommitment._reduced_incidence_matrix(
+            lines = sc.lines,
+            buses = sc.buses,
+        )
+        @test size(actual) == (20, 13)
+        @test actual[1, 1] == -1.0
+        @test actual[3, 1] == 1.0
+        @test actual[4, 1] == 1.0
+        @test actual[5, 1] == 1.0
+        @test actual[3, 2] == -1.0
+        @test actual[6, 2] == 1.0
+        @test actual[4, 3] == -1.0
+        @test actual[6, 3] == -1.0
+        @test actual[7, 3] == 1.0
+        @test actual[8, 3] == 1.0
+        @test actual[9, 3] == 1.0
+        @test actual[2, 4] == -1.0
+        @test actual[5, 4] == -1.0
+        @test actual[7, 4] == -1.0
+        @test actual[10, 4] == 1.0
+        @test actual[10, 5] == -1.0
+        @test actual[11, 5] == 1.0
+        @test actual[12, 5] == 1.0
+        @test actual[13, 5] == 1.0
+        @test actual[8, 6] == -1.0
+        @test actual[14, 6] == 1.0
+        @test actual[15, 6] == 1.0
+        @test actual[14, 7] == -1.0
+        @test actual[9, 8] == -1.0
+        @test actual[15, 8] == -1.0
+        @test actual[16, 8] == 1.0
+        @test actual[17, 8] == 1.0
+        @test actual[16, 9] == -1.0
+        @test actual[18, 9] == 1.0
+        @test actual[11, 10] == -1.0
+        @test actual[18, 10] == -1.0
+        @test actual[12, 11] == -1.0
+        @test actual[19, 11] == 1.0
+        @test actual[13, 12] == -1.0
+        @test actual[19, 12] == -1.0
+        @test actual[20, 12] == 1.0
+        @test actual[17, 13] == -1.0
+        @test actual[20, 13] == -1.0
+    end
+
+    @testset "_injection_shift_factors" begin
+        instance = UnitCommitment.read(fixture("/case14.json.gz"))
+        sc = instance.scenarios[1]
+        actual = UnitCommitment._injection_shift_factors(
+            lines = sc.lines,
+            buses = sc.buses,
+        )
+        @test size(actual) == (20, 13)
+        @test round.(actual, digits = 2) == [
+            -0.84 -0.75 -0.67 -0.61 -0.63 -0.66 -0.66 -0.65 -0.65 -0.64 -0.63 -0.63 -0.64
+            -0.16 -0.25 -0.33 -0.39 -0.37 -0.34 -0.34 -0.35 -0.35 -0.36 -0.37 -0.37 -0.36
+            0.03 -0.53 -0.15 -0.1 -0.12 -0.14 -0.14 -0.14 -0.13 -0.13 -0.12 -0.12 -0.13
+            0.06 -0.14 -0.32 -0.22 -0.25 -0.3 -0.3 -0.29 -0.28 -0.27 -0.25 -0.26 -0.27
+            0.08 -0.07 -0.2 -0.29 -0.26 -0.22 -0.22 -0.22 -0.23 -0.25 -0.26 -0.26 -0.24
+            0.03 0.47 -0.15 -0.1 -0.12 -0.14 -0.14 -0.14 -0.13 -0.13 -0.12 -0.12 -0.13
+            0.08 0.31 0.5 -0.3 -0.03 0.36 0.36 0.28 0.23 0.1 -0.0 0.02 0.17
+            0.0 0.01 0.02 -0.01 -0.22 -0.63 -0.63 -0.45 -0.41 -0.32 -0.24 -0.25 -0.36
+            0.0 0.01 0.01 -0.01 -0.12 -0.17 -0.17 -0.26 -0.24 -0.18 -0.14 -0.14 -0.21
+            -0.0 -0.02 -0.03 0.02 -0.66 -0.2 -0.2 -0.29 -0.36 -0.5 -0.63 -0.61 -0.43
+            -0.0 -0.01 -0.02 0.01 0.21 -0.12 -0.12 -0.17 -0.28 -0.53 0.18 0.15 -0.03
+            -0.0 -0.0 -0.0 0.0 0.03 -0.02 -0.02 -0.03 -0.02 0.01 -0.52 -0.17 -0.09
+            -0.0 -0.01 -0.01 0.01 0.11 -0.06 -0.06 -0.09 -0.05 0.02 -0.28 -0.59 -0.31
+            -0.0 -0.0 -0.0 -0.0 -0.0 -0.0 -1.0 -0.0 -0.0 -0.0 -0.0 -0.0 0.0
+            0.0 0.01 0.02 -0.01 -0.22 0.37 0.37 -0.45 -0.41 -0.32 -0.24 -0.25 -0.36
+            0.0 0.01 0.02 -0.01 -0.21 0.12 0.12 0.17 -0.72 -0.47 -0.18 -0.15 0.03
+            0.0 0.01 0.01 -0.01 -0.14 0.08 0.08 0.12 0.07 -0.03 -0.2 -0.24 -0.6
+            0.0 0.01 0.02 -0.01 -0.21 0.12 0.12 0.17 0.28 -0.47 -0.18 -0.15 0.03
+            -0.0 -0.0 -0.0 0.0 0.03 -0.02 -0.02 -0.03 -0.02 0.01 0.48 -0.17 -0.09
+            -0.0 -0.01 -0.01 0.01 0.14 -0.08 -0.08 -0.12 -0.07 0.03 0.2 0.24 -0.4
+        ]
+    end
+
+    @testset "_line_outage_factors" begin
+        instance = UnitCommitment.read(fixture("/case14.json.gz"))
+        sc = instance.scenarios[1]
+        isf_before = UnitCommitment._injection_shift_factors(
+            lines = sc.lines,
+            buses = sc.buses,
+        )
+        lodf = UnitCommitment._line_outage_factors(
+            lines = sc.lines,
+            buses = sc.buses,
+            isf = isf_before,
+        )
+        for contingency in sc.contingencies
+            for lc in contingency.lines
+                prev_susceptance = lc.susceptance
+                lc.susceptance = 0.0
+                isf_after = UnitCommitment._injection_shift_factors(
+                    lines = sc.lines,
+                    buses = sc.buses,
+                )
+                lc.susceptance = prev_susceptance
+                for lm in sc.lines
+                    expected = isf_after[lm.offset, :]
+                    actual =
+                        isf_before[lm.offset, :] +
+                        lodf[lm.offset, lc.offset] * isf_before[lc.offset, :]
+                    @test norm(expected - actual) < 1e-6
+                end
+            end
+        end
+    end
+end

test/src/transform/initcond_test.jl

@@ -0,0 +1,30 @@
+# 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
+
+function transform_initcond_test()
+    @testset "generate_initial_conditions!" begin
+        # Load instance
+        instance = UnitCommitment.read(fixture("case118-initcond.json.gz"))
+        optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
+        sc = instance.scenarios[1]
+        # All units should have unknown initial conditions
+        for g in sc.thermal_units
+            @test g.initial_power === nothing
+            @test g.initial_status === nothing
+        end
+
+        # Generate initial conditions
+        UnitCommitment.generate_initial_conditions!(sc, optimizer)
+
+        # All units should now have known initial conditions
+        for g in sc.thermal_units
+            @test g.initial_power !== nothing
+            @test g.initial_status !== nothing
+        end
+
+        # TODO: Check that initial conditions are feasible
+    end
+end

test/src/transform/randomize/XavQiuAhm2021_test.jl

@@ -0,0 +1,106 @@
+# 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 Random
+using UnitCommitment, Cbc, JuMP
+
+function get_scenario()
+    return UnitCommitment.read_benchmark(
+        "matpower/case118/2017-02-01",
+    ).scenarios[1]
+end
+system_load(sc) = sum(b.load for b in sc.buses)
+test_approx(x, y) = @test isapprox(x, y, atol = 1e-3)
+
+function transform_randomize_XavQiuAhm2021_test()
+    @testset "XavQiuAhm2021" begin
+        @testset "cost and load share" begin
+            sc = get_scenario()
+            # Check original costs
+            unit = sc.thermal_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 = sc.buses[1]
+            prev_system_load = system_load(sc)
+            test_approx(bus.load[1] / prev_system_load[1], 0.012)
+
+            randomize!(
+                sc,
+                XavQiuAhm2021.Randomization(randomize_load_profile = false),
+                rng = MersenneTwister(42),
+            )
+
+            # 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(sc)
+            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
+            sc = get_scenario()
+            # Check original load profile
+            @test round.(system_load(sc), digits = 1)[1:8] ≈ [
+                3059.5,
+                2983.2,
+                2937.5,
+                2953.9,
+                3073.1,
+                3356.4,
+                4068.5,
+                4018.8,
+            ]
+
+            randomize!(
+                sc,
+                XavQiuAhm2021.Randomization();
+                rng = MersenneTwister(42),
+            )
+
+            # Check randomized load profile
+            @test round.(system_load(sc), digits = 1)[1:8] ≈ [
+                4854.7,
+                4849.2,
+                4732.7,
+                4848.2,
+                4948.4,
+                5231.1,
+                5874.8,
+                5934.8,
+            ]
+        end
+
+        @testset "profiled unit cost" begin
+            sc = UnitCommitment.read(
+                fixture("case14-profiled.json.gz"),
+            ).scenarios[1]
+            # Check original costs
+            pu1 = sc.profiled_units[1]
+            pu2 = sc.profiled_units[2]
+            test_approx(pu1.cost[1], 100.0)
+            test_approx(pu2.cost[1], 50.0)
+            randomize!(
+                sc,
+                XavQiuAhm2021.Randomization(randomize_load_profile = false),
+                rng = MersenneTwister(42),
+            )
+            # Check randomized costs
+            test_approx(pu1.cost[1], 98.039)
+            test_approx(pu2.cost[1], 48.385)
+        end
+    end
+end

test/src/transform/slice_test.jl

@@ -0,0 +1,68 @@
+# 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, LinearAlgebra, Cbc, JuMP, JSON, GZip
+
+function transform_slice_test()
+    @testset "slice" begin
+        instance = UnitCommitment.read(fixture("case14.json.gz"))
+        modified = UnitCommitment.slice(instance, 1:2)
+        sc = modified.scenarios[1]
+
+        # Should update all time-dependent fields
+        @test modified.time == 2
+        @test length(sc.power_balance_penalty) == 2
+        @test length(sc.reserves_by_name["r1"].amount) == 2
+        for u in sc.thermal_units
+            @test length(u.max_power) == 2
+            @test length(u.min_power) == 2
+            @test length(u.must_run) == 2
+            @test length(u.min_power_cost) == 2
+            for s in u.cost_segments
+                @test length(s.mw) == 2
+                @test length(s.cost) == 2
+            end
+        end
+        for b in sc.buses
+            @test length(b.load) == 2
+        end
+        for l in sc.lines
+            @test length(l.normal_flow_limit) == 2
+            @test length(l.emergency_flow_limit) == 2
+            @test length(l.flow_limit_penalty) == 2
+        end
+        for ps in sc.price_sensitive_loads
+            @test length(ps.demand) == 2
+            @test length(ps.revenue) == 2
+        end
+
+        # Should be able to build model without errors
+        optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
+        model = UnitCommitment.build_model(
+            instance = modified,
+            optimizer = optimizer,
+            variable_names = true,
+        )
+    end
+
+    @testset "slice profiled units" begin
+        instance = UnitCommitment.read(fixture("case14-profiled.json.gz"))
+        modified = UnitCommitment.slice(instance, 1:2)
+        sc = modified.scenarios[1]
+
+        # Should update all time-dependent fields
+        for pu in sc.profiled_units
+            @test length(pu.max_power) == 2
+            @test length(pu.min_power) == 2
+        end
+
+        # Should be able to build model without errors
+        optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
+        model = UnitCommitment.build_model(
+            instance = modified,
+            optimizer = optimizer,
+            variable_names = true,
+        )
+    end
+end

test/src/usage.jl

@@ -0,0 +1,66 @@
+# 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, LinearAlgebra, Cbc, JuMP, JSON
+
+function _set_flow_limits!(instance)
+    for sc in instance.scenarios
+        sc.power_balance_penalty = [100_000 for _ in 1:instance.time]
+        for line in sc.lines, t in 1:4
+            line.normal_flow_limit[t] = 10.0
+        end
+    end
+end
+
+function usage_test()
+    @testset "usage" begin
+        @testset "deterministic" begin
+            instance = UnitCommitment.read(fixture("case14.json.gz"))
+            _set_flow_limits!(instance)
+            optimizer =
+                optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
+            model = UnitCommitment.build_model(
+                instance = instance,
+                optimizer = optimizer,
+                variable_names = true,
+            )
+            @test name(model[:is_on]["g1", 1]) == "is_on[g1,1]"
+
+            # Optimize and retrieve solution
+            UnitCommitment.optimize!(model)
+            solution = UnitCommitment.solution(model)
+
+            # Write solution to a file
+            filename = tempname()
+            UnitCommitment.write(filename, solution)
+            loaded = JSON.parsefile(filename)
+            @test length(loaded["Is on"]) == 6
+
+            # Verify solution
+            @test UnitCommitment.validate(instance, solution)
+
+            # Reoptimize with fixed solution
+            UnitCommitment.fix!(model, solution)
+            UnitCommitment.optimize!(model)
+            @test UnitCommitment.validate(instance, solution)
+        end
+
+        @testset "stochastic" begin
+            instance = UnitCommitment.read([
+                fixture("case14.json.gz"),
+                fixture("case14.json.gz"),
+            ])
+            _set_flow_limits!(instance)
+            @test length(instance.scenarios) == 2
+            optimizer =
+                optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
+            model = UnitCommitment.build_model(
+                instance = instance,
+                optimizer = optimizer,
+            )
+            UnitCommitment.optimize!(model)
+            solution = UnitCommitment.solution(model)
+        end
+    end
+end

test/src/validation/repair_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, JSON, GZip, DataStructures
+
+function parse_case14()
+    return JSON.parse(
+        GZip.gzopen(fixture("case14.json.gz")),
+        dicttype = () -> DefaultOrderedDict(nothing),
+    )
+end
+
+function validation_repair_test()
+    @testset "repair!" begin
+        @testset "Cost curve should be convex" begin
+            json = parse_case14()
+            json["Generators"]["g1"]["Production cost curve (MW)"] =
+                [100, 150, 200]
+            json["Generators"]["g1"]["Production cost curve (\$)"] =
+                [10, 25, 30]
+            sc = UnitCommitment._from_json(json, repair = false)
+            @test UnitCommitment.repair!(sc) == 4
+        end
+
+        @testset "Startup limit must be greater than Pmin" begin
+            json = parse_case14()
+            json["Generators"]["g1"]["Production cost curve (MW)"] = [100, 150]
+            json["Generators"]["g1"]["Production cost curve (\$)"] = [100, 150]
+            json["Generators"]["g1"]["Startup limit (MW)"] = 80
+            sc = UnitCommitment._from_json(json, repair = false)
+            @test UnitCommitment.repair!(sc) == 1
+        end
+
+        @testset "Startup costs and delays must be increasing" begin
+            json = parse_case14()
+            json["Generators"]["g1"]["Startup costs (\$)"] = [300, 200, 100]
+            json["Generators"]["g1"]["Startup delays (h)"] = [8, 4, 2]
+            sc = UnitCommitment._from_json(json, repair = false)
+            @test UnitCommitment.repair!(sc) == 4
+        end
+    end
+end

test/transform/initcond_test.jl

@@ -1,28 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using UnitCommitment, Cbc, JuMP
-
-@testset "generate_initial_conditions!" begin
-    # Load instance
-    instance = UnitCommitment.read("$FIXTURES/case118-initcond.json.gz")
-    optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
-
-    # All units should have unknown initial conditions
-    for g in instance.units
-        @test g.initial_power === nothing
-        @test g.initial_status === nothing
-    end
-
-    # Generate initial conditions
-    UnitCommitment.generate_initial_conditions!(instance, optimizer)
-
-    # All units should now have known initial conditions
-    for g in instance.units
-        @test g.initial_power !== nothing
-        @test g.initial_status !== nothing
-    end
-
-    # TODO: Check that initial conditions are feasible
-end

test/transform/randomize/XavQiuAhm2021_test.jl

@@ -1,69 +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 Random
-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)
-
-        randomize!(
-            instance,
-            method = XavQiuAhm2021.Randomization(
-                randomize_load_profile = false,
-            ),
-            rng = MersenneTwister(42),
-        )
-
-        # 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]
-
-        randomize!(
-            instance,
-            XavQiuAhm2021.Randomization(),
-            rng = MersenneTwister(42),
-        )
-
-        # 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/slice_test.jl

@@ -1,44 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
-
-@testset "slice" begin
-    instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
-    modified = UnitCommitment.slice(instance, 1:2)
-
-    # Should update all time-dependent fields
-    @test modified.time == 2
-    @test length(modified.power_balance_penalty) == 2
-    @test length(modified.reserves_by_name["r1"].amount) == 2
-    for u in modified.units
-        @test length(u.max_power) == 2
-        @test length(u.min_power) == 2
-        @test length(u.must_run) == 2
-        @test length(u.min_power_cost) == 2
-        for s in u.cost_segments
-            @test length(s.mw) == 2
-            @test length(s.cost) == 2
-        end
-    end
-    for b in modified.buses
-        @test length(b.load) == 2
-    end
-    for l in modified.lines
-        @test length(l.normal_flow_limit) == 2
-        @test length(l.emergency_flow_limit) == 2
-        @test length(l.flow_limit_penalty) == 2
-    end
-    for ps in modified.price_sensitive_loads
-        @test length(ps.demand) == 2
-        @test length(ps.revenue) == 2
-    end
-    # Should be able to build model without errors
-    optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
-    model = UnitCommitment.build_model(
-        instance = modified,
-        optimizer = optimizer,
-        variable_names = true,
-    )
-end

test/usage.jl

@@ -1,37 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON
-
-@testset "usage" begin
-    instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
-    for line in instance.lines, t in 1:4
-        line.normal_flow_limit[t] = 10.0
-    end
-    optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
-    model = UnitCommitment.build_model(
-        instance = instance,
-        optimizer = optimizer,
-        variable_names = true,
-    )
-    @test name(model[:is_on]["g1", 1]) == "is_on[g1,1]"
-
-    # Optimize and retrieve solution
-    UnitCommitment.optimize!(model)
-    solution = UnitCommitment.solution(model)
-
-    # Write solution to a file
-    filename = tempname()
-    UnitCommitment.write(filename, solution)
-    loaded = JSON.parsefile(filename)
-    @test length(loaded["Is on"]) == 6
-
-    # Verify solution
-    @test UnitCommitment.validate(instance, solution)
-
-    # Reoptimize with fixed solution
-    UnitCommitment.fix!(model, solution)
-    UnitCommitment.optimize!(model)
-    @test UnitCommitment.validate(instance, solution)
-end

test/validation/repair_test.jl

@@ -1,39 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using UnitCommitment, JSON, GZip, DataStructures
-
-function parse_case14()
-    return JSON.parse(
-        GZip.gzopen("$FIXTURES/case14.json.gz"),
-        dicttype = () -> DefaultOrderedDict(nothing),
-    )
-end
-
-@testset "repair!" begin
-    @testset "Cost curve should be convex" begin
-        json = parse_case14()
-        json["Generators"]["g1"]["Production cost curve (MW)"] = [100, 150, 200]
-        json["Generators"]["g1"]["Production cost curve (\$)"] = [10, 25, 30]
-        instance = UnitCommitment._from_json(json, repair = false)
-        @test UnitCommitment.repair!(instance) == 4
-    end
-
-    @testset "Startup limit must be greater than Pmin" begin
-        json = parse_case14()
-        json["Generators"]["g1"]["Production cost curve (MW)"] = [100, 150]
-        json["Generators"]["g1"]["Production cost curve (\$)"] = [100, 150]
-        json["Generators"]["g1"]["Startup limit (MW)"] = 80
-        instance = UnitCommitment._from_json(json, repair = false)
-        @test UnitCommitment.repair!(instance) == 1
-    end
-
-    @testset "Startup costs and delays must be increasing" begin
-        json = parse_case14()
-        json["Generators"]["g1"]["Startup costs (\$)"] = [300, 200, 100]
-        json["Generators"]["g1"]["Startup delays (h)"] = [8, 4, 2]
-        instance = UnitCommitment._from_json(json, repair = false)
-        @test UnitCommitment.repair!(instance) == 4
-    end
-end