期刊论文详细信息
RENEWABLE ENERGY 卷:36
Short-term wind power forecasting in Portugal by neural networks and wavelet transform
Article
Catalao, J. P. S.1,2  Pousinho, H. M. I.1  Mendes, V. M. F.3 
[1] Univ Beira Interior, Dept Electromech Engn, P-6201001 Covilha, Portugal
[2] Univ Tecn Lisboa, Inst Super Tecn, Ctr Innovat Elect & Energy Engn, P-1049001 Lisbon, Portugal
[3] Inst Super Engn Lisboa, Dept Elect Engn & Automat, P-1950062 Lisbon, Portugal
关键词: Wind power;    Forecasting;    Artificial neural networks;    Wavelet transform;   
DOI  :  10.1016/j.renene.2010.09.016
来源: Elsevier
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【 摘 要 】

This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. Results from a real-world case study are presented. A comparison is carried out, taking into account the results obtained with other approaches. Finally, conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

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