Wind Energy Resources Prediction Based on EOF Method and RBF Neural Network

Xiao Cao; Zhi Bao Chen; Hai Zhou; Jie Ding

doi:10.4028/www.scientific.net/AMM.281.550

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 281Wind Energy Resources Prediction Based on EOF...

Wind Energy Resources Prediction Based on EOF Method and RBF Neural Network

Abstract:

In this paper, research starts from the data captured from several wind measuring stations. Firstly, the main spatial Patterns are extracted by EOF (empirical orthogonal function) method, and then the time coefficient series corresponding to principal spatial patterns are processed and predicted by RBF (radial basis function) neural network. Furthermore, according to the EOF decomposition method, inversely the new prediction time coefficient series are used to calculate the wind speed values in the future. Finally, the validity and advantages of this prediction approach are tested by the simulation results.

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Periodical:

Applied Mechanics and Materials (Volume 281)

Pages:

550-553

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.281.550

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Online since:

January 2013

Authors:

Xiao Cao, Zhi Bao Chen, Hai Zhou, Jie Ding

Keywords:

EOF Method, RBF Neural Network, Spatial Pattern, Time Coefficient Series, Wind Energy Resources Prediction

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References

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