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Multi-objective based on parallel vector evaluated particle swarm optimization for optimal steady-state performance of power systems

  • Ioannis (John) Vlachogiannis
  • , K Y Lee

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    In this paper the state-of-the-art extended particle swarm optimization (PSO) methods for solving multi-objective optimization problems are represented. We emphasize in those, the co-evolution technique of the parallel vector evaluated PSO (VEPSO), analysed and applied in a multi-objective problem of steady-state of power systems. Specifically, reactive power control is formulated as a multi-objective optimization problem and solved using the parallel VEPSO algorithm. The results on the IEEE 30-bus test system are compared with those given by another multi-objective evolutionary technique demonstrating the advantage of parallel VEPSO. The parallel VEPSO is also tested on a larger power system this with 136 busses. (C) 2009 Elsevier Ltd. All rights reserved.
    Original languageEnglish
    JournalExpert Systems with Applications
    Volume36
    Issue number8
    Pages (from-to)10802-10808
    ISSN0957-4174
    DOIs
    Publication statusPublished - 2009

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