Neural prediction of power factor in wind turbines

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dc.contributor.authorAta R.
dc.contributor.authorCetin N.S.
dc.date.accessioned2024-07-22T08:22:29Z
dc.date.available2024-07-22T08:22:29Z
dc.date.issued2007
dc.description.abstractThe power generated by wind turbines depends on several factors. One of them is the power factor also known as blade efficiency. In this study, the power factor is predicted using Artificial Neural Networks (ANN) and comparisons made with conventional model approach for the selected turbine profiles mostly used in practice. The study has shown that the prediction of power factors from seven input parameters by ANN yields better results than those of the conventional model.
dc.identifier.issn13030914
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/19083
dc.language.isoEnglish
dc.subjectArtificial intelligence
dc.subjectBackpropagation
dc.subjectElectric generators
dc.subjectElectric power factor
dc.subjectEngines
dc.subjectForecasting
dc.subjectHydraulic machinery
dc.subjectHydraulic motors
dc.subjectParameter estimation
dc.subjectTurbines
dc.subjectWind power
dc.subjectWind turbines
dc.subjectArtificial neural networks (ANN)
dc.subjectConventional modeling
dc.subjectInput parameters
dc.subjectNeural prediction
dc.subjectPower factor (PF)
dc.subjectNeural networks
dc.titleNeural prediction of power factor in wind turbines
dc.typeArticle

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