IDEAS home Printed from https://ideas.repec.org/a/inm/orijoc/v29y2017i4p645-659.html
   My bibliography  Save this article

Algorithm for the N -2 Security-Constrained Unit Commitment Problem with Transmission Switching

Author

Listed:
  • Kathryn M. Schumacher

    (Operations Research, Research and Development, General Motors, Warren, Michigan 48092)

  • Amy E. M. Cohn

    (Industrial and Operations Engineering Department, University of Michigan, Ann Arbor, Michigan 48109)

  • Richard Li-Yang Chen

    (Industrial and Operations Engineering Department, University of Michigan, Ann Arbor, Michigan 48109; and Quantitative Modeling and Analysis, Sandia National Laboratories, Livermore, California 94551)

Abstract

Most power grid systems are operated to be N -1 secure, meaning that the system can withstand the failure of any one component. There is increasing interest in more stringent security standards, where the power grid must be able to survive the (nearly) simultaneous failure of k components (i.e., N - k ). However, this improved reliability criterion significantly increases the number of contingency scenarios that must be considered when solving the unit commitment problem. Additional computational complexity is introduced when taking into account transmission switching. This relatively inexpensive method of redirecting power flows in the grid has been proposed as a way of introducing flexibility to better survive failure events. We present an algorithm for solving the unit commitment problem that simultaneously addresses both the challenges of the N - k security requirement and the use of transmission switching during operation. We analyze the algorithmic performance and present computational results for the IEEE24 and RTS-96 test systems for k = 1 and 2. We also include a discussion of how this approach might be extended to solve problems with k ≥ 3.

Suggested Citation

  • Kathryn M. Schumacher & Amy E. M. Cohn & Richard Li-Yang Chen, 2017. "Algorithm for the N -2 Security-Constrained Unit Commitment Problem with Transmission Switching," INFORMS Journal on Computing, INFORMS, vol. 29(4), pages 645-659, November.
    • Handle: RePEc:inm:orijoc:v:29:y:2017:i:4:p:645-659
    DOI: 10.1287/ijoc.2017.0751
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/ijoc.2017.0751
    Download Restriction: no
    File URL: https://libkey.io/10.1287/ijoc.2017.0751?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. Jean-Paul Watson & David Woodruff, 2011. "Progressive hedging innovations for a class of stochastic mixed-integer resource allocation problems," Computational Management Science, Springer, vol. 8(4), pages 355-370, November.
    2. T. L. Magnanti & R. T. Wong, 1981. "Accelerating Benders Decomposition: Algorithmic Enhancement and Model Selection Criteria," Operations Research, INFORMS, vol. 29(3), pages 464-484, June.
    3. Yang Yuan & Suvrajeet Sen, 2009. "Enhanced Cut Generation Methods for Decomposition-Based Branch and Cut for Two-Stage Stochastic Mixed-Integer Programs," INFORMS Journal on Computing, INFORMS, vol. 21(3), pages 480-487, August.
    4. Richard Li-Yang Chen & Neng Fan & Ali Pinar & Jean-Paul Watson, 2017. "Contingency-constrained unit commitment with post-contingency corrective recourse," Annals of Operations Research, Springer, vol. 249(1), pages 381-407, February.
    5. Lewis Ntaimo, 2013. "Fenchel decomposition for stochastic mixed-integer programming," Journal of Global Optimization, Springer, vol. 55(1), pages 141-163, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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. Cheng Lu & Zhibin Deng & Shu-Cherng Fang & Qingwei Jin & Wenxun Xing, 2022. "Fast computation of global solutions to the single-period unit commitment problem," Journal of Combinatorial Optimization, Springer, vol. 44(3), pages 1511-1536, October.

    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. Onur Tavaslıoğlu & Oleg A. Prokopyev & Andrew J. Schaefer, 2019. "Solving Stochastic and Bilevel Mixed-Integer Programs via a Generalized Value Function," Operations Research, INFORMS, vol. 67(6), pages 1659-1677, November.
    2. Nur Banu Demir & Serhat Gul & Melih Çelik, 2021. "A stochastic programming approach for chemotherapy appointment scheduling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 112-133, February.
    3. Aghalari, Amin & Nur, Farjana & Marufuzzaman, Mohammad, 2021. "Solving a stochastic inland waterway port management problem using a parallelized hybrid decomposition algorithm," Omega, Elsevier, vol. 102(C).
    4. Sushil R. Poudel & Md Abdul Quddus & Mohammad Marufuzzaman & Linkan Bian & Reuben F. Burch V, 2019. "Managing congestion in a multi-modal transportation network under biomass supply uncertainty," Annals of Operations Research, Springer, vol. 273(1), pages 739-781, February.
    5. 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.
    6. Poudel, Sushil Raj & Marufuzzaman, Mohammad & Bian, Linkan, 2016. "A hybrid decomposition algorithm for designing a multi-modal transportation network under biomass supply uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 1-25.
    7. Kabli, Mohannad & Quddus, Md Abdul & Nurre, Sarah G. & Marufuzzaman, Mohammad & Usher, John M., 2020. "A stochastic programming approach for electric vehicle charging station expansion plans," International Journal of Production Economics, Elsevier, vol. 220(C).
    8. Valicka, Christopher G. & Garcia, Deanna & Staid, Andrea & Watson, Jean-Paul & Hackebeil, Gabriel & Rathinam, Sivakumar & Ntaimo, Lewis, 2019. "Mixed-integer programming models for optimal constellation scheduling given cloud cover uncertainty," European Journal of Operational Research, Elsevier, vol. 275(2), pages 431-445.
    9. Çelik, Batuhan & Gul, Serhat & Çelik, Melih, 2023. "A stochastic programming approach to surgery scheduling under parallel processing principle," Omega, Elsevier, vol. 115(C).
    10. Binyuan Chen & Simge Küçükyavuz & Suvrajeet Sen, 2011. "Finite Disjunctive Programming Characterizations for General Mixed-Integer Linear Programs," Operations Research, INFORMS, vol. 59(1), pages 202-210, February.
    11. Gutierrez, Genaro J. & Kouvelis, Panagiotis & Kurawarwala, Abbas A., 1996. "A robustness approach to uncapacitated network design problems," European Journal of Operational Research, Elsevier, vol. 94(2), pages 362-376, October.
    12. Lee, Chungmok & Han, Jinil, 2017. "Benders-and-Price approach for electric vehicle charging station location problem under probabilistic travel range," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 130-152.
    13. M. Jenabi & S. M. T. Fatemi Ghomi & S. A. Torabi & Moeen Sammak Jalali, 2022. "An accelerated Benders decomposition algorithm for stochastic power system expansion planning using sample average approximation," OPSEARCH, Springer;Operational Research Society of India, vol. 59(4), pages 1304-1336, December.
    14. Peiling Wu & Joseph C. Hartman & George R. Wilson, 2005. "An Integrated Model and Solution Approach for Fleet Sizing with Heterogeneous Assets," Transportation Science, INFORMS, vol. 39(1), pages 87-103, February.
    15. Lee, Jinkyu & Bae, Sanghyeon & Kim, Woo Chang & Lee, Yongjae, 2023. "Value function gradient learning for large-scale multistage stochastic programming problems," European Journal of Operational Research, Elsevier, vol. 308(1), pages 321-335.
    16. Ogbe, Emmanuel & Li, Xiang, 2017. "A new cross decomposition method for stochastic mixed-integer linear programming," European Journal of Operational Research, Elsevier, vol. 256(2), pages 487-499.
    17. Elisangela Martins de Sá & Ivan Contreras & Jean-François Cordeau & Ricardo Saraiva de Camargo & Gilberto de Miranda, 2015. "The Hub Line Location Problem," Transportation Science, INFORMS, vol. 49(3), pages 500-518, August.
    18. Brech, Claus-Henning & Ernst, Andreas & Kolisch, Rainer, 2019. "Scheduling medical residents’ training at university hospitals," European Journal of Operational Research, Elsevier, vol. 274(1), pages 253-266.
    19. Lim, Gino J. & Bard, Jonathan F., 2016. "Benders decomposition and an IP-based heuristic for selecting IMRT treatment beam anglesAuthor-Name: Lin, Sifeng," European Journal of Operational Research, Elsevier, vol. 251(3), pages 715-726.
    20. Halit Üster & Panitan Kewcharoenwong, 2011. "Strategic Design and Analysis of a Relay Network in Truckload Transportation," Transportation Science, INFORMS, vol. 45(4), pages 505-523, November.

    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:29:y:2017:i:4:p:645-659. 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.