Economic dispatch by using different crossover operators of genetic algorithm

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dc.contributor.authorDuman, Serhat
dc.contributor.authorÖztürk, Ali
dc.contributor.authorDöşoğlu, M. Kenan
dc.contributor.authorTosun, Salih
dc.date.accessioned2020-04-30T13:32:21Z
dc.date.available2020-04-30T13:32:21Z
dc.date.issued2010
dc.departmentDÜ, Teknik Eğitim Fakültesi, Elektrik Eğitimi Bölümüen_US
dc.description.abstractThe great advances in technology and industry have brought about an increase in the demand for energy in electrical power systems. In order to meet this increased demand, planning the operation of power systems and optimum operation of those systems are required. To obtain it, optimal power flow, reactive power optimization and solutions of the economic dispatch problem are required. The problem of Economical Dispatch (ED) is one of the limited non-linear optimization problems of electrical power systems. Operation of generators with minimum cost by being held in certain limit values is required. Intuitional methods resulting in better conclusions have been used in solving this complicated non-linear problem so far. In this study, the conclusions obtained on conditions with line loss and without line loss of 3 and 6 switchboards with thermal fuel were compared with each other by using different crossover operators of genetic algorithm (GA).en_US
dc.identifier.endpage1183en_US
dc.identifier.issn1303-0914
dc.identifier.issue1en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1173en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12684/247
dc.identifier.volume10en_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.publisherIstanbul Universityen_US
dc.relation.ispartofIstanbul University - Journal of Electrical and Electronics Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCrossover operators; Economic dispatch; Genetic algorithm; Power systemsen_US
dc.titleEconomic dispatch by using different crossover operators of genetic algorithmen_US
dc.typeArticleen_US

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