Particle swarm optimization with exponentially varying inertia weight factor for solving multi- area economic dispatch problem

C. Rani, E. Petkov, K. Busawon, M. Farrag

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    This paper aimed at exploring the performance of Particle Swarm Optimisation with Exponentially Varying Inertia Weight Factor (PSO-EVIWF) for solving Multi-Area Economic Dispatch (MAED) problem with tie line constraints considering valve-point loading in each area. The effectiveness of the proposed algorithm has been verified on 4 interconnected areas with 16 generators standard test system. The paper presents the search capability and convergence behavior of the proposed method. Simulation results show that the PSO-EVIWF achieved quality solutions and smooth convergence characteristics and it is an alternative method for solving MAED problem.
    Original languageEnglish
    Title of host publication 3rd International Symposium on Environmental Friendly Energies and Applications (EFEA)
    PublisherIEEE
    Number of pages6
    ISBN (Electronic)9781479975174
    DOIs
    Publication statusPublished - 16 Mar 2015

    Keywords

    • economic dispatch
    • multi- area economic dispatch
    • particle swarm optimisation
    • exponentially varying inertia weight factor

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  • Cite this

    Rani, C., Petkov, E., Busawon, K., & Farrag , M. (2015). Particle swarm optimization with exponentially varying inertia weight factor for solving multi- area economic dispatch problem. In 3rd International Symposium on Environmental Friendly Energies and Applications (EFEA) IEEE. https://doi.org/10.1109/EFEA.2014.7059938