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dc.contributor.authorDahal, Keshav P.*
dc.contributor.authorSiewierski, T.A.*
dc.contributor.authorGalloway, S.J.*
dc.contributor.authorBurt, G.M.*
dc.contributor.authorMcDonald, J.R.*
dc.date.accessioned2008-12-02T10:35:52Z
dc.date.available2008-12-02T10:35:52Z
dc.date.issued2004en
dc.identifier.citationDahal K.P., Siewierski T.A., Galloway S.J., Burt G.M. and McDonald J.R. (2004). An Evolutionary Generation Scheduling in an Open Electricity Market. Congress on Evolutionary Computation (CEC). Portland, Oregon, USA. 19-23 June 2004. Proceedings of the Congress on Evolutionary Computation. Vol. 1., pp. 1135 - 1142.en
dc.identifier.urihttp://hdl.handle.net/10454/950
dc.descriptionYesen
dc.description.abstractThe classical generation scheduling problem defines on/off decisions (commitment) and dispatch level of all available generators in a power system for each scheduling period. In recent years researchers have focused on developing new approaches to solve nonclassical generation scheduling problems in the newly deregulated and decentralized electricity market place. In this paper a GA-based approach has been developed for a system operator to schedule generation in a market akin to that operating in England and Wales. A generation scheduling problem has been formulated and solved using available trading information at the time of dispatch. The solution is updated after information is obtained in a rolling fashion. The approach is tested for two IEEE network-based problems, and achieves comparable results with a branch and bound technique in reasonable CPU time.en
dc.language.isoenen
dc.rights© 2004 IEEE. Reprinted from Proceedings of the Congress on Evolutionary Computation - CEC 2004. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bradford's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.en
dc.subjectGeneration Schedulingen
dc.subjectElectricity Marketen
dc.titleAn Evolutionary Generation Scheduling in an Open Electricity Marketen
dc.status.refereedYesen
dc.typeConference paperen
dc.identifier.doihttps://doi.org/10.1109/CEC.2004.1330989
refterms.dateFOA2018-07-18T13:22:51Z


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