Simplified Model and Genetic Algorithm Based Simulated Annealing Approach for Excitation Current Estimation of Synchronous Motor

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dc.contributor.authorKaplan, Orhan
dc.contributor.authorÇelik, Emre
dc.date.accessioned2020-04-30T23:31:57Z
dc.date.available2020-04-30T23:31:57Z
dc.date.issued2018
dc.departmentDÜ, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.descriptionKAPLAN, ORHAN/0000-0003-0590-7106en_US
dc.descriptionWOS: 000451843400009en_US
dc.description.abstractReactive power demanded by many loads besides active power is one of the important issue in terms of the efficient use of energy. The optimal solution of reactive power demand can be performed by tuning the excitation current of synchronous motor available in power system. This paper presents an effective application of genetic algorithm-based simulated annealing (GASA) algorithm to solve the problem of excitation current estimation of synchronous motors. Firstly, the multiple linear regression model used in a few studies for estimation of excitation current of synchronous motor, is considered and regression coefficients of this model are optimized by GASA algorithm using training data collected from experimental setup performed. The supremacy of GASA over some recently reported algorithms such as gravitational search algorithm, artificial bee colony and genetic algorithm is widely illustrated by comparing the estimation results. Owing to the observation of weak regression coefficient of load current indicating that it is not much beneficial to excitation current, load current is removed from the regression model. Then, the remaining regression coefficients are tuned to accommodate new modification. It is seen from the findings that both training and testing performance of the simplified model are improved further. The major conclusions drawn from this study are that it introduces a new efficient algorithm for the concerned problem as well as the multiple linear regression model, which has the advantages of simplicity and cost-friendliness.en_US
dc.identifier.doi10.4316/AECE.2018.04009en_US
dc.identifier.endpage84en_US
dc.identifier.issn1582-7445
dc.identifier.issn1844-7600
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage75en_US
dc.identifier.urihttps://doi.org/10.4316/AECE.2018.04009
dc.identifier.urihttps://hdl.handle.net/20.500.12684/4549
dc.identifier.volume18en_US
dc.identifier.wosWOS:000451843400009en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherUniv Suceava, Fac Electrical Engen_US
dc.relation.ispartofAdvances In Electrical And Computer Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectreactive power compensationen_US
dc.subjectpower factoren_US
dc.subjectartificial intelligenceen_US
dc.subjectgenetic algorithmsen_US
dc.subjectsimulated annealingen_US
dc.titleSimplified Model and Genetic Algorithm Based Simulated Annealing Approach for Excitation Current Estimation of Synchronous Motoren_US
dc.typeArticleen_US

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