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A knowledge-based genetic algorithm for unit commitment

dc.contributor.authorAldridge, C.J.*
dc.contributor.authorMcKee, S.*
dc.contributor.authorMcDonald, J.R.*
dc.contributor.authorGalloway, S.J.*
dc.contributor.authorDahal, Keshav P.*
dc.contributor.authorBradley, M.E.*
dc.contributor.authorMacqueen, J.F.*
dc.date.accessioned2009-10-20T06:55:55Z
dc.date.available2009-10-20T06:55:55Z
dc.date.issued2001
dc.identifier.citationAldridge, C., McKee, S., McDonald, J.R. and Dahal, K.P. et al. (2001). A knowledge-based genetic algorithm for unit commitment. IEE Proceedings Generation, Transmission and Distribution. Vol. 148, No. 2, pp. 146-152.en
dc.identifier.urihttp://hdl.handle.net/10454/3689
dc.descriptionNoen
dc.description.abstractA genetic algorithm (GA) augmented with knowledge-based methods has been developed for solving the unit commitment economic dispatch problem. The GA evolves a population of binary strings which represent commitment schedules. The initial population of schedules is chosen using a method based on elicited scheduling knowledge. A fast rule-based dispatch method is then used to evaluate candidate solutions. The knowledge-based genetic algorithm is applied to a test system of ten thermal units over 24-hour time intervals, including minimum on/off times and ramp rates, and achieves lower cost solutions than Lagrangian relaxation in comparable computational time.en
dc.language.isoenen
dc.relation.isreferencedbyhttp://dx.doi.org/10.1049/ip-gtd:20010022en
dc.subjectGenetic algorithmen
dc.subjectKnowledge-based methodsen
dc.subjectEconomic dispatch problemen
dc.subjectKnowledge-based genetic algorithmen
dc.titleA knowledge-based genetic algorithm for unit commitmenten
dc.status.refereedYesen
dc.typeArticleen
dc.type.versionNo full-text available in the repositoryen


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