LAPSE:2025.0282
Published Article
LAPSE:2025.0282
Optimization models and algorithms for the Unit Commitment problem
June 27, 2025
Abstract
The unit commitment problem determines the optimal strategy to meet the electricity demand at minimum cost by committing power generation units at each point of time. Solving the unit commitment problem gives rise to a challenging optimization problem due to its combinatorial complexity and potentially long solution time requirements. Our proposed solution approach utilizes a decomposition method in conjunction with alternative models from the EGRET library. Results of this decomposition approach tested against four benchmarking systems show that significant computational speed ups are achieved.
The unit commitment problem determines the optimal strategy to meet the electricity demand at minimum cost by committing power generation units at each point of time. Solving the unit commitment problem gives rise to a challenging optimization problem due to its combinatorial complexity and potentially long solution time requirements. Our proposed solution approach utilizes a decomposition method in conjunction with alternative models from the EGRET library. Results of this decomposition approach tested against four benchmarking systems show that significant computational speed ups are achieved.
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Suggested Citation
Vyas J, Laird C, Grossmann IE, Lima RM, Harjunkoski I, Poland J. Optimization models and algorithms for the Unit Commitment problem. Systems and Control Transactions 4:812-817 (2025) https://doi.org/10.69997/sct.113099
Author Affiliations
Vyas J: Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Laird C: Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Grossmann IE: Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Lima RM: King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia
Harjunkoski I: Hitachi Energy Research, Havellandstr. 10-14, Mannheim 68309, Germany
Poland J: Hitachi Energy Research, Segelhofstr. 7, 5405 Baden-Dättwil, Switzerland
Laird C: Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Grossmann IE: Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Lima RM: King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia
Harjunkoski I: Hitachi Energy Research, Havellandstr. 10-14, Mannheim 68309, Germany
Poland J: Hitachi Energy Research, Segelhofstr. 7, 5405 Baden-Dättwil, Switzerland
Journal Name
Systems and Control Transactions
Volume
4
First Page
812
Last Page
817
Year
2025
Publication Date
2025-07-01
Version Comments
Original Submission
Other Meta
PII: 0812-0817-1383-SCT-4-2025, Publication Type: Journal Article
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LAPSE:2025.0282
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https://doi.org/10.69997/sct.113099
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Jun 27, 2025
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References Cited
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- Harjunkoski, I., Giuntoli, M., Poland, J., & Schmitt, S. (2021, October). Matheuristics for Speeding Up the Solution of the Unit Commitment Problem. In 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe) (pp. 01-05). IEEE https://doi.org/10.1109/ISGTEurope52324.2021.9640029
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