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

Chan, K. Y.; Pong, Glory T.Y.; Aydin, Mehmet Emin; Fogarty, T. C.; Ling, S. H.

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. Copyright © 2009, Inderscience Publishers.

• Journal Article Type: Article
• Publication Date: Jul 29, 2009
• Journal: European Journal of Industrial Engineering
• Print ISSN: 1751-5254
• Electronic ISSN: 1751-5262
• Publisher: Inderscience
• Peer Reviewed: Peer Reviewed
• Volume: 3
• Issue: 4
• Pages: 468-492
• DOI: https://doi.org/10.1504/EJIE.2009.027038
• Keywords: power supply, power systems, evolutionary algorithm, orthogonal arrays, genetic algorithms, GAs, quality improvement, operational costs, stability, optimisation
• Public URL: https://uwe-repository.worktribe.com/output/1001257
• Publisher URL: http://dx.doi.org/10.1504/EJIE.2009.027038