A statistics-based genetic algorithm for quality improvements of power supplies
dc.contributor.author | Chan, Kit Yan | |
dc.contributor.author | Chan, K. | |
dc.contributor.author | Pong, G. | |
dc.contributor.author | Aydin, M. | |
dc.contributor.author | Fogarty, T. | |
dc.contributor.author | Ling, S. | |
dc.date.accessioned | 2017-01-30T14:03:32Z | |
dc.date.available | 2017-01-30T14:03:32Z | |
dc.date.created | 2014-10-08T06:00:33Z | |
dc.date.issued | 2009 | |
dc.identifier.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. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/37477 | |
dc.description.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. | |
dc.publisher | Inderscience Enterprises Ltd | |
dc.relation.uri | http://www.inderscience.com/search/index.php?action=record&rec_id=27038 | |
dc.subject | power systems | |
dc.subject | GAs | |
dc.subject | quality improvement | |
dc.subject | genetic algorithms | |
dc.subject | orthogonal arrays | |
dc.subject | stability | |
dc.subject | evolutionary algorithm | |
dc.subject | operational costs | |
dc.subject | power supply | |
dc.subject | optimisation | |
dc.title | A statistics-based genetic algorithm for quality improvements of power supplies | |
dc.type | Journal Article | |
dcterms.source.volume | 3 | |
dcterms.source.number | 4 | |
dcterms.source.startPage | 468 | |
dcterms.source.endPage | 492 | |
dcterms.source.issn | 17515262 | |
dcterms.source.title | European Journal of Industrial Engineering | |
curtin.department | Digital Ecosystems and Business Intelligence Institute (DEBII) | |
curtin.accessStatus | Fulltext not available |