Wind speed prediction based on machine learning and new energy pumping unit wind power control

被引：0
|
作者：
Zhang C.-Y. [1 ,2 ]
Wang L. [1 ]
Li H. [1 ]
Wu T.-Y. [1 ]
Li Y. [3 ]
机构：
[1] School of Automation Science and Electrical Engineering, Beihang University, Beijing
[2] College of Engineering, Inner Mongolia University for the Nationalities, Tongliao
[3] College of Electronics and Automation, Inner Mongolia Electronic Information Vocational Technical College, Hohhot
来源：
Wang, Liang (wangliang@buaa.edu.cn) | 1997年 / Editorial Board of Jilin University卷 / 51期
关键词：
Feedback linearization; New energy pumping unit; Power tracking; Support vector regression(SVR); Wind energy;
D O I：
10.13229/j.cnki.jdxbgxb20200848
中图分类号：
学科分类号：
摘要：
This paper takes the new energy pumping unit as the research object. In order to improve the ability of new energy pumping unit, first, the maximum wind energy tracking control strategy of the wind turbine is studied, and a wind speed estimation method-support vector regression is presented. Then, the key parameters in the estimation model are optimized by particle swarm optimization. Finally, a feedback linearized sliding mode controller is designed for speed feedback control. By comparing with PID controller, it is verified that the new controller has the characteristics of rapidity and anti-disturbance. Therefore, the maximum wind power tracking control strategy proposed in this paper meets the energy-saving requirements of new energy pumping units. © 2021, Jilin University Press. All right reserved.
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页码：1997 / 2006
页数：9
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