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A Hybrid Model to Forecast Wind Speed Based on Wavelet and Neural Network

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2 Author(s)
Yao Chuanan ; Coll. of Mech. & Electr. Eng., Henan Agric. Univ., Zhengzhou, China ; Yu Yongchang

To solve the reliability of wind power at the small wind farm and increase forecasting accuracy of wind speed, this paper proposed a hybrid model for forecasting wind speed based on the combination of wavelet transformation and the neural network. The proposed hybrid model to forecast wind speed is a combination of loose and compact wavelet neural networks. By using this model, wind speed signal is decomposed with wavelet transform, and reconstructed to get each scale's sub-series. Then the sub-series are predicted by compact wavelet neural network, respectively. Compared with other models, the proposed method improves wind speed forecasting accuracy.

Published in:

Control, Automation and Systems Engineering (CASE), 2011 International Conference on

Date of Conference:

30-31 July 2011