The wind speed prediction based on AR model and BP neural network

被引：4
|
作者：
Zhang, Conglin [1 ]
机构：
[1] Tianjin Univ, Coll Civil Engn, Tianjin 300072, Peoples R China
来源：
TRENDS IN BUILDING MATERIALS RESEARCH, PTS 1 AND 2 | 2012年 / 450-451卷
关键词：
AR model; BP neural network; wind speed prediction; comparative analysis;
D O I：
10.4028/www.scientific.net/AMR.450-451.1593
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
The output of the wind turbine has high randomness due to natural wind velocity. Whether the output can be predicted accurately or not is directly related to the feasibility of dispatching wind power in the power network. The key of wind farm output prediction is to predict the wind speed of wind farm site. This paper uses AR model and BP neural network to predict 24-hour wind speed, and proves the feasibility of these two predicted methods according to comparison with measured wind speed data. This paper has certain reference significance for improving the precision of wind speed prediction.
引用
收藏
页码：1593 / 1596
页数：4
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