Institutional Repository
Technical University of Crete
Technical University of Crete
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| 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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