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AC Optimal Power Flow: a strengthened SDP relaxation and an iterative MILP scheme for global optimization

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  • Additional Information
    • Contributors:
      Laboratoire d'informatique de l'École polytechnique Palaiseau (LIX); École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS); École des Ponts ParisTech (ENPC)
    • Publication Information:
      HAL CCSD
      Centre Mersenne
    • Publication Date:
      2022
    • Collection:
      École des Ponts ParisTech: HAL
    • Abstract:
      International audience ; We address the issue of computing a global minimizer of the AC Optimal Power Flow problem. We introduce valid inequalities to strengthen the Semidefinite Programming relaxation, yielding a novel Conic Programming relaxation. Leveraging these Conic Programming constraints, we dynamically generate Mixed-Integer Linear Programming (MILP) relaxations, whose solutions asymptotically converge to global minimizers of the AC Optimal Power Flow problem. We apply this iterative MILP scheme on the IEEE PES PGLib benchmark and compare the results with two recent Global Optimization approaches.
    • Relation:
      hal-03595227; https://hal.science/hal-03595227; https://hal.science/hal-03595227v2/document; https://hal.science/hal-03595227v2/file/OJMO_2022__3__A6_0.pdf
    • Accession Number:
      10.5802/ojmo.17
    • Online Access:
      https://doi.org/10.5802/ojmo.17
      https://hal.science/hal-03595227
      https://hal.science/hal-03595227v2/document
      https://hal.science/hal-03595227v2/file/OJMO_2022__3__A6_0.pdf
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • Accession Number:
      edsbas.4D9C75A0