• DocumentCode
    3160231
  • Title

    Branch flow model: Relaxations and convexification

  • Author

    Farivar, Masoud ; Low, S.H.

  • Author_Institution
    Eng. & Appl. Sci, Caltech, Pasadena, CA, USA
  • fYear
    2012
  • fDate
    10-13 Dec. 2012
  • Firstpage
    3672
  • Lastpage
    3679
  • Abstract
    We propose a branch flow model for the analysis and optimization of mesh as well as radial networks. The model leads to a new approach to solving optimal power flow (OPF) problems that consists of two relaxation steps. The first step eliminates the voltage and current angles and the second step approximates the resulting problem by a conic program that can be solved efficiently. For radial networks, we prove that both relaxation steps are always exact, provided there are no upper bounds on loads. For mesh networks, the conic relaxation is always exact and we characterize when the angle relaxation may fail. We propose a simple method to convexify a mesh network using phase shifters so that both relaxation steps are always exact and OPF for the convexified network can always be solved efficiently for a globally optimal solution. We prove that convexification requires phase shifters only outside a spanning tree of the network graph and their placement depends only on network topology, not on power flows, generation, loads, or operating constraints. Since power networks are sparse, the number of required phase shifters may be relatively small.
  • Keywords
    convex programming; load flow control; network topology; phase shifters; power electronics; trees (mathematics); voltage control; OPF problem; angle relaxation; branch flow model; conic program; mesh analysis; mesh network convexification; mesh optimization; network graph; network topology; operating constraint; optimal power flow problem; phase shifter; power network; radial network; relaxation step; spanning tree; Equations; Integrated circuit modeling; Load modeling; Mathematical model; Mesh networks; Optimization; Phase shifters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
  • Conference_Location
    Maui, HI
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-2065-8
  • Electronic_ISBN
    0743-1546
  • Type

    conf

  • DOI
    10.1109/CDC.2012.6425870
  • Filename
    6425870