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    A statistics-based genetic algorithm for quality improvements of power supplies

    Access Status
    Fulltext not available
    Authors
    Chan, Kit Yan
    Chan, K.
    Pong, G.
    Aydin, M.
    Fogarty, T.
    Ling, S.
    Date
    2009
    Type
    Journal Article
    
    Metadata
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    Citation
    Chan, K.Y. and Chan, K. and Pong, G. and Aydin, M. and Fogarty, T. and Ling, S. 2009. A statistics-based genetic algorithm for quality improvements of power supplies. European Journal of Industrial Engineering. 3 (4): pp. 468-492.
    Source Title
    European Journal of Industrial Engineering
    Additional URLs
    http://www.inderscience.com/search/index.php?action=record&rec_id=27038
    ISSN
    17515262
    School
    Digital Ecosystems and Business Intelligence Institute (DEBII)
    URI
    http://hdl.handle.net/20.500.11937/37477
    Collection
    • Curtin Research Publications
    Abstract

    This paper presents a new statistics-based evolutionary algorithm to improve the qualities of power supplies, in which operational costs and the stability of the power supply are optimised to provide a highly smooth but low-cost power supply service to customers. The proposed method is incorporated with the characteristics of the stochastic method, evolutionary algorithm and a more systematical statistical method, orthogonal design. It intends to compensate for the built-in randomness of the stochastic method and, at the same time, overcome the limitations of local search methods that are not suitable for handling multi-optima problems. Case studies on the WSCC 9-bus and New England 39-bus systems indicate that the proposed approach outperforms the existing method in terms of robustness in solution and convergence speed while the solution quality that can offer a more stable and cheaper power supply to customers is achieved.

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