Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.21/2239
Título: Short-term wind power forecasting in Portugal by neural networks and wavelet transform
Autor: Catalão, João Paulo da Silva
Pousinho, Hugo Miguel Inácio
Mendes, Víctor Manuel Fernandes
Palavras-chave: Wind power
Forecasting
Artificial neural networks
Wavelet transform
Feature-extraction
Arima models
Prediction
Speed
Generation
Algorithm
Systems
Data: Abr-2011
Editora: Pergamon-Elsevier Science LTD
Citação: CATALÃO, J. P. S.; POUSINHO, H. M. I.; MENDES, V. M. F. - Short-term wind power forecasting in Portugal by neural networks and wavelet transform. Renewable Energy. ISSN 0960-1481. Vol. 36, n.º 4 (2011) p. 1245-1251.
Resumo: 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.
Peer review: yes
URI: http://hdl.handle.net/10400.21/2239
ISSN: 0960-1481
Aparece nas colecções:ISEL - Eng. Electrotécn. - Artigos

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