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

Authors: K.Y. Chan, K.W. Chan, Glory T.Y. Pong, M.E. Aydin, T.C. Fogarty, S.H. Ling

Addresses: Digital Ecosystems and Business Intelligence Institute, Curtin University of Technology, Perth 6845, Australia. ' Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong. ' Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong. ' Department of Computing and Information Systems, University of Bedfordshire, Luton, Bedfordshire, UK. ' Faculty of Business, Computing and Information Management, London South Bank University, 103 Borough Road, London, SE1 0AA, UK. ' Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW 2007, Australia

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.

DOI: 10.1504/EJIE.2009.027038

European Journal of Industrial Engineering, 2009 Vol.3 No.4, pp.468 - 492

Published online: 13 Jul 2009 *

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