Wind power forecasting using advanced neural networks models

URI	http://purl.tuc.gr/dl/dias/2ADC2876-C37A-42E1-B2DA-6F91D189A173	-
Identifier	https://doi.org/10.1109/60.556376	-
Language	en	-
Extent	6 pages	en
Title	Wind power forecasting using advanced neural networks models	en
Creator	Stavrakakis Georgios	en
Creator	Σταυρακακης Γεωργιος	el
Creator	Kariniotakis, Georges	en
Creator	N. F .Nogaret	en
Publisher	Institute of Electrical and Electronics Engineers	en
Content Summary	In 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 Item	Peer-Reviewed Journal Publication	en
Type of Item	Δημοσίευση σε Περιοδικό με Κριτές	el
License	http://creativecommons.org/licenses/by/4.0/	en
Date of Item	2015-10-14	-
Date of Publication	1996	-
Subject	WECS (Wind energy conversion systems)	en
Subject	wind energy conversion systems	en
Subject	wecs wind energy conversion systems	en
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:10.1109/60.556376	en

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