Short-term wind power forecasting in Portugal by neural networks and wavelet transform


Autoria(s): Catalão, João Paulo da Silva; Pousinho, Hugo Miguel Inácio; Mendes, Víctor Manuel Fernandes
Data(s)

16/02/2013

16/02/2013

01/04/2011

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.

Identificador

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.

0960-1481

http://hdl.handle.net/10400.21/2239

Idioma(s)

eng

Publicador

Pergamon-Elsevier Science LTD

Direitos

restrictedAccess

Palavras-Chave #Wind power #Forecasting #Artificial neural networks #Wavelet transform #Feature-extraction #Arima models #Prediction #Speed #Generation #Algorithm #Systems
Tipo

article