README.md

UnitCommitment.jl

UnitCommitment.jl (UC.jl) is an optimization package for the Security-Constrained Unit Commitment Problem (SCUC), a fundamental optimization problem in power systems used, for example, to clear the day-ahead electricity markets. The package provides benchmark instances for the problem and Julia/JuMP implementations of state-of-the-art mixed-integer programming formulations.

Package Components

• Data Format: The package proposes an extensible and fully-documented JSON-based data format for SCUC, developed in collaboration with Independent System Operators (ISOs), which describes the most important aspects of the problem. The format supports the most common generator characteristics (including ramping, piecewise-linear production cost curves and time-dependent startup costs), as well as operating reserves, price-sensitive loads, transmission networks and contingencies.
• Benchmark Instances: The package provides a diverse collection of large-scale benchmark instances collected from the literature, converted into a common data format, and extended using data-driven methods to make them more challenging and realistic.
• Model Implementation: The package provides Julia/JuMP implementations of state-of-the-art formulations and solution methods for SCUC, including multiple ramping formulations (ArrCon2000, MorLatRam2013, DamKucRajAta2016, PanGua2016), multiple piecewise-linear costs formulations (Gar1962, CarArr2006, KnuOstWat2018) and contingency screening methods (XavQiuWanThi2019). Our goal is to keep these implementations up-to-date as new methods are proposed in the literature.
• Benchmark Tools: The package provides automated benchmark scripts to accurately evaluate the performance impact of proposed code changes.

Sample Usage

using Cbc
using JuMP
using UnitCommitment

import UnitCommitment:
    Formulation,
    KnuOstWat2018,
    MorLatRam2013,
    ShiftFactorsFormulation

# Read benchmark instance
instance = UnitCommitment.read_benchmark(
    "matpower/case118/2017-02-01",
)

# Construct model (using state-of-the-art defaults)
model = UnitCommitment.build_model(
    instance = instance,
    optimizer = Cbc.Optimizer,
)

# Construct model (using customized formulation)
model = UnitCommitment.build_model(
    instance = instance,
    optimizer = Cbc.Optimizer,
    formulation = Formulation(
        pwl_costs = KnuOstWat2018.PwlCosts(),
        ramping = MorLatRam2013.Ramping(),
        startup_costs = MorLatRam2013.StartupCosts(),
        transmission = ShiftFactorsFormulation(
            isf_cutoff = 0.005,
            lodf_cutoff = 0.001,
        ),
    ),
)

# Modify the model (e.g. add custom constraints)
@constraint(
    model,
    model[:is_on]["g3", 1] + model[:is_on]["g4", 1] <= 1,
)

# Solve model
UnitCommitment.optimize!(model)

# Extract solution
solution = UnitCommitment.solution(model)
UnitCommitment.write("/tmp/output.json", solution)

Documentation

See official documentation at: https://anl-ceeesa.github.io/UnitCommitment.jl/

Authors

• 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 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

• Based upon work supported by the U.S. Department of Energy Advanced Grid Modeling Program under Grant DE-OE0000875.

Citing

If you use UnitCommitment.jl in your research (instances, models or algorithms), we kindly request that you cite the package as follows:

• Alinson S. Xavier, Aleksandr M. Kazachkov, Ogün Yurdakul, Jun He, Feng Qiu. "UnitCommitment.jl: A Julia/JuMP Optimization Package for Security-Constrained Unit Commitment (Version 0.4)". Zenodo (2024). DOI: 10.5281/zenodo.4269874.

If you use the instances, we additionally request that you cite the original sources, as described in the documentation.

License

UnitCommitment.jl: A Julia/JuMP Optimization Package for Security-Constrained Unit Commitment
Copyright © 2020-2024, UChicago Argonne, LLC. All Rights Reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted
provided that the following conditions are met:

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   endorse or promote products derived from this software without specific prior written
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