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A Decomposition Algorithm with Fast Identification of Critical Contingencies for Large-Scale Security-Constrained AC-OPF

Author

Listed:
  • Frank E. Curtis

    (Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, Pennsylvania 18015)

  • Daniel K. Molzahn

    (School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30313)

  • Shenyinying Tu

    (Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208)

  • Andreas Wächter

    (Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208)

  • Ermin Wei

    (Department of Electrical and Computer Engineering, Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208)

  • Elizabeth Wong

    (Department of Mathematics, University of California–San Diego, La Jolla, California 92093)

Abstract

A decomposition algorithm for solving large-scale security-constrained AC optimal power flow problems is presented. The formulation considered is the one used in the Advanced Research Projects Agency-Energy Grid Optimization Competition, Challenge 1, held from November 2018 through October 2019. Algorithmic strategies are proposed for contingency selection, fast contingency evaluation, handling complementarity constraints, avoiding issues related to degeneracy, and exploiting parallelism. The results of numerical experiments are provided to demonstrate the effectiveness of the proposed techniques as compared with alternative strategies.

Suggested Citation

  • Frank E. Curtis & Daniel K. Molzahn & Shenyinying Tu & Andreas Wächter & Ermin Wei & Elizabeth Wong, 2023. "A Decomposition Algorithm with Fast Identification of Critical Contingencies for Large-Scale Security-Constrained AC-OPF," Operations Research, INFORMS, vol. 71(6), pages 2031-2044, November.
    • Handle: RePEc:inm:oropre:v:71:y:2023:i:6:p:2031-2044
    DOI: 10.1287/opre.2023.2453
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