IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v312y2022i2d10.1007_s10479-022-04643-1.html
   My bibliography  Save this article

Derivation and generation of path-based valid inequalities for transmission expansion planning

Author

Listed:
  • J. Kyle Skolfield

    (Arizona State University)

  • Laura M. Escobar

    (São Paulo State University (UNESP))

  • Adolfo R. Escobedo

    (Arizona State University)

Abstract

This paper seeks to solve the long-term transmission expansion planning problem in power systems more effectively by reducing the solution search space and the computational effort. The proposed methodology finds and adds cutting planes based on structural insights about bus angle differences along paths. Two lemmas and a theorem are proposed which formally establish the validity of these cutting planes onto the underlying mathematical formulations. These path-based bus angle difference constraints, which tighten the relaxed feasible region, are used in combination with branch-and-bound to find lower bounds on the optimal investment of the transmission expansion planning problem. This work also creates an algorithm that automates the process of finding and applying the most effective valid inequalities, resulting in significantly reduced testing and computational time. The algorithm is implemented in Python, using Gurobi to add constraints and solve the exact DCOPF-based transmission expansion problem. This paper uses two different-sized systems to illustrate the effectiveness of the proposed framework: the GOC 500-bus system and a modified Polish 2383-bus system.

Suggested Citation

  • J. Kyle Skolfield & Laura M. Escobar & Adolfo R. Escobedo, 2022. "Derivation and generation of path-based valid inequalities for transmission expansion planning," Annals of Operations Research, Springer, vol. 312(2), pages 1031-1049, May.
  • Handle: RePEc:spr:annopr:v:312:y:2022:i:2:d:10.1007_s10479-022-04643-1
    DOI: 10.1007/s10479-022-04643-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-022-04643-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-022-04643-1?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. M. Jenabi & S. Fatemi Ghomi & S. Torabi & S. Hosseinian, 2015. "Acceleration strategies of Benders decomposition for the security constraints power system expansion planning," Annals of Operations Research, Springer, vol. 235(1), pages 337-369, December.
    2. Burak Kocuk & Hyemin Jeon & Santanu S. Dey & Jeff Linderoth & James Luedtke & Xu Andy Sun, 2016. "A Cycle-Based Formulation and Valid Inequalities for DC Power Transmission Problems with Switching," Operations Research, INFORMS, vol. 64(4), pages 922-938, August.
    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. 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.
    2. 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.
    3. Rahmaniani, Ragheb & Crainic, Teodor Gabriel & Gendreau, Michel & Rei, Walter, 2017. "The Benders decomposition algorithm: A literature review," European Journal of Operational Research, Elsevier, vol. 259(3), pages 801-817.
    4. Castro, Jordi & Nasini, Stefano, 2021. "A specialized interior-point algorithm for huge minimum convex cost flows in bipartite networks," European Journal of Operational Research, Elsevier, vol. 290(3), pages 857-869.
    5. N. Beheshti Asl & S. A. MirHassani, 2019. "Accelerating benders decomposition: multiple cuts via multiple solutions," Journal of Combinatorial Optimization, Springer, vol. 37(3), pages 806-826, April.
    6. Emma S. Johnson & Santanu Subhas Dey, 2022. "A Scalable Lower Bound for the Worst-Case Relay Attack Problem on the Transmission Grid," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 2296-2312, July.
    7. López-Ramos, Francisco & Nasini, Stefano & Sayed, Mohamed H., 2020. "An integrated planning model in centralized power systems," European Journal of Operational Research, Elsevier, vol. 287(1), pages 361-377.
    8. Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2020. "Cost minimization of large-scale infrastructure for electricity generation and transmission," Omega, Elsevier, vol. 96(C).
    9. David Bergman & Andre A. Cire, 2018. "Discrete Nonlinear Optimization by State-Space Decompositions," Management Science, INFORMS, vol. 64(10), pages 4700-4720, October.
    10. Pedro Pablo Cardenas Alzate & Laura Monica Escobar Vargas & Antonio Hernando Escobar Zuluaga, 2019. "Planning the Expansion of Long-Term Transmission Networks Using a Cycle-Based Formulation," Modern Applied Science, Canadian Center of Science and Education, vol. 13(1), pages 237-237, January.
    11. Selvaprabu Nadarajah & Andre A. Cire, 2020. "Network-Based Approximate Linear Programming for Discrete Optimization," Operations Research, INFORMS, vol. 68(6), pages 1767-1786, 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:spr:annopr:v:312:y:2022:i:2:d:10.1007_s10479-022-04643-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.