Individual pitch control of wind turbine based on RBF neural network

被引：0
|
作者：
Liu zhongpeng [1 ,2 ]
Huo feng [1 ,2 ]
Xiao shuowen [1 ,2 ]
Zhang xuesong [1 ,2 ]
Zhu shilong [1 ,2 ]
Ji guoruil [1 ,2 ]
Dai haitao [1 ,2 ]
Feng jian [1 ,2 ]
机构：
[1] Guodian United Power Technol Co Itd, Beijing 100039, Peoples R China
[2] State Key Lab Wind Energy Equipment & Control Tec, Beijing 100039, Peoples R China
来源：
PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016 | 2016年
关键词：
Individual pitch control; RBF neural network; Load mitigation;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Load mitigation is one of the most important control objectives in the wind turbine control. Generally, an individual pitch control (IPC) could be used to solve this problem. However, due to an accurate wind turbine model which is essential is hardly obtained, it's hard to design an IPC method in both the classical and the modern control. In this paper, a new IPC algorithm is proposed by using a radial basis function (REF) neutral network with online training. Simulation results from GH-Bladed show that proposed control algorithm can mitigate the loads effectively. The algorithm provide a practical reference for the design of wind turbine controller.
引用
收藏
页码：5769 / 5773
页数：5
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