机器学习风速预测及新能源抽油机风功率控制  

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

作　　者：张春友[1,2] 王亮[1] 李宏 武桐言 李岩[3] ZHANG Chun-you;WANG Liang;LI Hong;WU Tong-yan;LI Yan(School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,China;College of Engineering,Inner Mongolia University for the Nationalities,Tongliao 028000,China;College of Electronics and Automation,Inner Mongolia Electronic Information Vocational Technical College,Hohhot 010070,China)

机构地区：[1]北京航空航天大学自动化科学与电气工程学院,北京100191 [2]内蒙古民族大学工学院,内蒙古通辽028000 [3]内蒙古电子信息职业技术学院电子与自动化学院,呼和浩特010070

出　　处：《吉林大学学报（工学版）》2021年第6期1997-2006,共10页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金项目(51865046);内蒙古自治区科技成果转化引导项目(2020CG0085);内蒙古科技英才支持计划项目(NJYT-19-B15)。

摘　　要：为了提高新能源抽油机的节能效果,提出了风力机最大风能跟踪控制策略。通过支持向量回归(SVR)方法估计作用到风轮平面的有效风速,利用粒子群算法对估计模型中的关键参数进行优化,以提高风速估计的精度。在转速反馈控制环节,设计了反馈线性化滑模控制器,通过与PID控制器进行对比研究,验证了所设计新型控制器具有快速性、抗扰动等特点。本文提出的最大风功率跟踪控制策略能够满足新能源抽油机的节能要求。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 energysaving requirements of new energy pumping units.

关 键 词：风能利用 新能源抽油机 支持向量回归 反馈线性化 功率跟踪 

分 类 号：TK89[动力工程及工程热物理—流体机械及工程]