• DocumentCode
    3296204
  • Title

    Real-time implementation of an intelligent algorithm for electric ship power system reconfiguration

  • Author

    Mitra, Pinaki ; Venayagamoorthy, Ganesh K.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO
  • fYear
    2009
  • fDate
    20-22 April 2009
  • Firstpage
    219
  • Lastpage
    226
  • Abstract
    The naval electric ship is often subject to severe damages under battle conditions. The damages or faults might even affect the generators and as a result, critical loads might suffer from power deficiency which may lead to an eventual collapse of rest of the system. In order to serve the critical loads and maintain a proper power balance without excessive generation, the ship power system requires a fast reconfiguration of the remaining system under fault conditions. A fast intelligent algorithm using the small population based particle swarm optimization (SPPSO) for dynamic reconfiguration of the available generators and loads when a fault in the ship power system is detected is presented in this paper. SPPSO is a variant of PSO which operates with fewer particles and a regeneration concept, where new potential solutions are generated every few iterations. This concept of regeneration makes the algorithm fast and enhances its exploration capability to a large extent. The strength of the proposed reconfiguration strategy is first illustrated with Matlab results and then with a real-time implementation on a real time digital simulator and a digital signal processor.
  • Keywords
    electric generators; electric vehicles; fault diagnosis; particle swarm optimisation; power system faults; ships; Matlab; critical loads; digital signal processor; dynamic reconfiguration; electric ship power system; exploration capability; intelligent algorithm; naval electric ship; power deficiency; real time digital simulator; regeneration concept; small population based particle swarm optimization; Electrical fault detection; Fault detection; Marine vehicles; Particle swarm optimization; Power generation; Power system dynamics; Power system faults; Power systems; Real time systems; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Ship Technologies Symposium, 2009. ESTS 2009. IEEE
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    978-1-4244-3438-1
  • Electronic_ISBN
    978-1-4244-3439-8
  • Type

    conf

  • DOI
    10.1109/ESTS.2009.4906519
  • Filename
    4906519