 A statistics-based genetic algorithm for quality improvements of power suppliesK.Y. Chan, K.W. Chan, Glory T.Y. Pong, M.E. Aydin, T.C. Fogarty and S.H. Ling European Journal of Industrial Engineering, 2009, vol. 3, issue 4, 468-492 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. [Received 03 July 2008; Revised 29 December 2008; Revised 20 January 2009; Accepted 26 January 2009] Keywords: power supply; power systems; evolutionary algorithm; orthogonal arrays; genetic algorithms; GAs; quality improvement; operational costs; stability; optimisation. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:eujine:v:3:y:2009:i:4:p:468-492 Access Statistics for this article More articles in European Journal of Industrial Engineering from Inderscience Enterprises Ltd |
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