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Wind power forecasting using advanced neural networks models

Stavrakakis Georgios, Kariniotakis, Georges, N. F .Nogaret

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URIhttp://purl.tuc.gr/dl/dias/2ADC2876-C37A-42E1-B2DA-6F91D189A173-
Identifierhttps://doi.org/10.1109/60.556376-
Languageen-
Extent6 pagesen
TitleWind power forecasting using advanced neural networks modelsen
CreatorStavrakakis Georgiosen
CreatorΣταυρακακης Γεωργιοςel
CreatorKariniotakis, Georgesen
CreatorN. F .Nogareten
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryIn this paper, an advanced model, based on recurrent high order neural networks, is developed for the prediction of the power output profile of a wind park. This model outperforms simple methods like persistence, as well as classical methods in the literature. The architecture of a forecasting model is optimised automatically by a new algorithm, that substitutes the usually applied trial-and-error method. en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-14-
Date of Publication1996-
SubjectWECS (Wind energy conversion systems)en
Subjectwind energy conversion systemsen
Subjectwecs wind energy conversion systemsen
Bibliographic Citation G. N. Kariniotakis , G. S. Stavrakakis, E. F. Nogaret, “Wind power forecasting using advanced neural networks models,” IEEE Trans.on Energy Conv., vol. 11, no. 4, Dec. 1996.doi:10.1109/60.556376en

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