IDEAS home Printed from https://ideas.repec.org/a/inm/orijoc/v34y2022i6p3309-3324.html
   My bibliography  Save this article

A Polyhedral Study on Fuel-Constrained Unit Commitment

Author

Listed:
  • Kai Pan

    (Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong)

  • Ming Zhao

    (Department of Business Administration, Alfred Lerner College of Business and Economics, University of Delaware, Newark, Delaware 19716)

  • Chung-Lun Li

    (Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong)

  • Feng Qiu

    (Energy Systems Division, Argonne National Laboratory, Lemont, Illinois 60439)

Abstract

The electricity production of a thermal generator is often constrained by the available fuel supply. These fuel constraints impose a maximum bound on the energy output over multiple time periods. Fuel constraints are increasingly important in electricity markets because of two main reasons. First, as more natural gas-fired generators join the deregulated market, there is often competition for natural gas supply from other sectors (e.g., residential and manufacturing heating). Second, as more environmental and emission regulations are being placed on fossil fuel-fired generators, fuel supply is becoming more limited. However, there are few studies that consider the fuel constraints in the unit commitment problem from the perspective of computational analysis. To address the challenge faced by an independent power producer with a limited fuel supply, we study a fuel-constrained self-scheduling unit commitment (FSUC) problem where the production decisions are coupled across multiple time periods. We provide a complexity analysis of the FSUC problem and conduct a comprehensive polyhedral study by deriving strong valid inequalities. We demonstrate the effectiveness of our proposed inequalities as cutting planes in solving various multistage stochastic FSUC problems.

Suggested Citation

  • Kai Pan & Ming Zhao & Chung-Lun Li & Feng Qiu, 2022. "A Polyhedral Study on Fuel-Constrained Unit Commitment," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3309-3324, November.
    • Handle: RePEc:inm:orijoc:v:34:y:2022:i:6:p:3309-3324
    DOI: 10.1287/ijoc.2022.1235
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/ijoc.2022.1235
    Download Restriction: no
    File URL: https://libkey.io/10.1287/ijoc.2022.1235?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Antonio Frangioni & Claudio Gentile, 2006. "Solving Nonlinear Single-Unit Commitment Problems with Ramping Constraints," Operations Research, INFORMS, vol. 54(4), pages 767-775, August.
    2. Samer Takriti & Benedikt Krasenbrink & Lilian S.-Y. Wu, 2000. "Incorporating Fuel Constraints and Electricity Spot Prices into the Stochastic Unit Commitment Problem," Operations Research, INFORMS, vol. 48(2), pages 268-280, April.
    3. Chao Li & Muhong Zhang & Kory Hedman, 2021. "Extreme Ray Feasibility Cuts for Unit Commitment with Uncertainty," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1037-1055, July.
    4. Melamed, Michal & Ben-Tal, Aharon & Golany, Boaz, 2018. "A multi-period unit commitment problem under a new hybrid uncertainty set for a renewable energy source," Renewable Energy, Elsevier, vol. 118(C), pages 909-917.
    5. Álinson S. Xavier & Feng Qiu & Shabbir Ahmed, 2021. "Learning to Solve Large-Scale Security-Constrained Unit Commitment Problems," INFORMS Journal on Computing, INFORMS, vol. 33(2), pages 739-756, May.
    6. Yongpei Guan & Kai Pan & Kezhuo Zhou, 2018. "Polynomial time algorithms and extended formulations for unit commitment problems," IISE Transactions, Taylor & Francis Journals, vol. 50(8), pages 735-751, August.
    7. Bernard Knueven & James Ostrowski & Jean-Paul Watson, 2020. "On Mixed-Integer Programming Formulations for the Unit Commitment Problem," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 857-876, October.
    8. Maurice QUEYRANNE & Laurence A. WOLSEY, 2017. "Tight MIP formulations for bounded up/down times and interval-dependent start-ups," LIDAM Reprints CORE 2876, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Brian Carlson & Yonghong Chen & Mingguo Hong & Roy Jones & Kevin Larson & Xingwang Ma & Peter Nieuwesteeg & Haili Song & Kimberly Sperry & Matthew Tackett & Doug Taylor & Jie Wan & Eugene Zak, 2012. "MISO Unlocks Billions in Savings Through the Application of Operations Research for Energy and Ancillary Services Markets," Interfaces, INFORMS, vol. 42(1), pages 58-73, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jianqiu Huang & Kai Pan & Yongpei Guan, 2021. "Multistage Stochastic Power Generation Scheduling Co-Optimizing Energy and Ancillary Services," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 352-369, January.
    2. Bernard Knueven & James Ostrowski & Jean-Paul Watson, 2020. "On Mixed-Integer Programming Formulations for the Unit Commitment Problem," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 857-876, October.
    3. Luis Montero & Antonio Bello & Javier Reneses, 2022. "A Review on the Unit Commitment Problem: Approaches, Techniques, and Resolution Methods," Energies, MDPI, vol. 15(4), pages 1-40, February.
    4. Skolfield, J. Kyle & Escobedo, Adolfo R., 2022. "Operations research in optimal power flow: A guide to recent and emerging methodologies and applications," European Journal of Operational Research, Elsevier, vol. 300(2), pages 387-404.
    5. O’Malley, Cormac & de Mars, Patrick & Badesa, Luis & Strbac, Goran, 2023. "Reinforcement learning and mixed-integer programming for power plant scheduling in low carbon systems: Comparison and hybridisation," Applied Energy, Elsevier, vol. 349(C).
    6. Wim Ackooij & Jérôme Malick, 2016. "Decomposition algorithm for large-scale two-stage unit-commitment," Annals of Operations Research, Springer, vol. 238(1), pages 587-613, March.
    7. Tumbalam Gooty, Radhakrishna & Ghouse, Jaffer & Le, Quang Minh & Thitakamol, Bhurisa & Rezaei, Sabereh & Obiang, Denis & Gupta, Raghubir & Zhou, James & Bhattacharyya, Debangsu & Miller, David C., 2023. "Incorporation of market signals for the optimal design of post combustion carbon capture systems," Applied Energy, Elsevier, vol. 337(C).
    8. Bismark Singh & Bernard Knueven & Jean-Paul Watson, 2020. "Modeling flexible generator operating regions via chance-constrained stochastic unit commitment," Computational Management Science, Springer, vol. 17(2), pages 309-326, June.
    9. Wim Ackooij & Jérôme Malick, 2016. "Decomposition algorithm for large-scale two-stage unit-commitment," Annals of Operations Research, Springer, vol. 238(1), pages 587-613, March.
    10. Ben Knueven & Jim Ostrowski & Jianhui Wang, 2018. "The Ramping Polytope and Cut Generation for the Unit Commitment Problem," INFORMS Journal on Computing, INFORMS, vol. 30(4), pages 739-749, November.
    11. C. Gentile & G. Morales-España & A. Ramos, 2017. "A tight MIP formulation of the unit commitment problem with start-up and shut-down constraints," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 177-201, March.
    12. Alexis Tantet & Philippe Drobinski, 2021. "A Minimal System Cost Minimization Model for Variable Renewable Energy Integration: Application to France and Comparison to Mean-Variance Analysis," Energies, MDPI, vol. 14(16), pages 1-38, August.
    13. Lukas Hümbs & Alexander Martin & Lars Schewe, 2022. "Exploiting complete linear descriptions for decentralized power market problems with integralities," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 95(3), pages 451-474, June.
    14. Frederic Murphy & Axel Pierru & Yves Smeers, 2016. "A Tutorial on Building Policy Models as Mixed-Complementarity Problems," Interfaces, INFORMS, vol. 46(6), pages 465-481, December.
    15. Aliakbari Sani, Sajad & Bahn, Olivier & Delage, Erick, 2022. "Affine decision rule approximation to address demand response uncertainty in smart Grids’ capacity planning," European Journal of Operational Research, Elsevier, vol. 303(1), pages 438-455.
    16. Guanglei Wang & Hassan Hijazi, 2018. "Mathematical programming methods for microgrid design and operations: a survey on deterministic and stochastic approaches," Computational Optimization and Applications, Springer, vol. 71(2), pages 553-608, November.
    17. Ying-Yi Hong & Gerard Francesco DG. Apolinario, 2021. "Uncertainty in Unit Commitment in Power Systems: A Review of Models, Methods, and Applications," Energies, MDPI, vol. 14(20), pages 1-47, October.
    18. Yang, Yuqi & Zhou, Jianzhong & Liu, Guangbiao & Mo, Li & Wang, Yongqiang & Jia, Benjun & He, Feifei, 2020. "Multi-plan formulation of hydropower generation considering uncertainty of wind power," Applied Energy, Elsevier, vol. 260(C).
    19. Fatma Kılınç-Karzan, 2016. "On Minimal Valid Inequalities for Mixed Integer Conic Programs," Mathematics of Operations Research, INFORMS, vol. 41(2), pages 477-510, May.
    20. Philip J. Neame & Andrew B. Philpott & Geoffrey Pritchard, 2003. "Offer Stack Optimization in Electricity Pool Markets," Operations Research, INFORMS, vol. 51(3), pages 397-408, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orijoc:v:34:y:2022:i:6:p:3309-3324. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.