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

被引：0
|
作者：
Cao Xiao [1 ]
Chen Zhibao [1 ]
Zhou Hai [1 ]
Ding Jie [1 ]
机构：
[1] China Elect Power Res Inst, Beijing, Peoples R China
来源：
MECHANICAL ENGINEERING, MATERIALS AND ENERGY II | 2013年 / 281卷
关键词：
EOF method; spatial patterns; RBF neural network; time coefficient series; wind energy resources prediction;
D O I：
10.4028/www.scientific.net/AMM.281.550
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
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.
引用
收藏
页码：550 / 553
页数：4
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