Chaotic adaptive particle swarm optimisation using logistics and gauss map for solving cubic cost economic dispatch problem

C Rani, E Petkov, K Busawon, M Farrag

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

    Abstract

    This paper proposes Chaotic Adaptive Particle Swarm Optimisation (CAPSO) algorithm to solve Cubic Cost Economic Dispatch (CCED) problem. A Chaotic Local Search operator (CLS) is introduced in the proposed algorithm to avoid premature convergence. The basic strategy of the proposed algorithm is combining PSO with Adaptive Inertia Weight Factor (AIWF) and CLS, in which PSO with AIWF is applied to perform global exploration and CLS is used to perform exploitation to find the optimal solution. Logistics and Gauss map technique is used in performing CLS and the results are compared. The applicability and high feasibility of the proposed method is validated on a standard 5-generator test system. The simulation results confirm that this algorithm is capable of giving higher quality solutions with fast convergence characteristics.
    Original languageEnglish
    Title of host publicationIEEE Explore
    PublisherIEEE
    Number of pages5
    ISBN (Electronic)9781479975174
    ISBN (Print)9781479975181
    DOIs
    Publication statusPublished - Mar 2015

    Keywords

    • adaptive particle swarm
    • optimisation
    • economic dispatch

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