机器学习风速预测及新能源抽油机风功率控制

Chun You Zhang; Liang Wang; Hong Li; Tong Yan Wu; Yan Li

doi:10.13229/j.cnki.jdxbgxb20200848

机器学习风速预测及新能源抽油机风功率控制

Translated title of the contribution: Wind speed prediction based on machine learning and new energy pumping unit wind power control

Chun You Zhang
, Liang Wang^*
, Hong Li
, Tong Yan Wu
, Yan Li

^*Corresponding author for this work

School of Automation Science and Electrical Engineering

Beihang University
Inner Mongolia University for Nationalities
Inner Mongolia Electronic Information Vocational Technical College

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

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.

Translated title of the contribution	Wind speed prediction based on machine learning and new energy pumping unit wind power control
Original language	Chinese (Traditional)
Pages (from-to)	1997-2006
Number of pages	10
Journal	Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition)
Volume	51
Issue number	6
DOIs	https://doi.org/10.13229/j.cnki.jdxbgxb20200848
State	Published - Nov 2021

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Cite this

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title = "机器学习风速预测及新能源抽油机风功率控制",

abstract = "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.",

keywords = "Feedback linearization, New energy pumping unit, Power tracking, Support vector regression(SVR), Wind energy",

author = "Zhang, \{Chun You\} and Liang Wang and Hong Li and Wu, \{Tong Yan\} and Yan Li",

year = "2021",

month = nov,

doi = "10.13229/j.cnki.jdxbgxb20200848",

language = "繁体中文",

volume = "51",

pages = "1997--2006",

journal = "Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition)",

issn = "1671-5497",

publisher = "Editorial Board of Jilin University",

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TY - JOUR

T1 - 机器学习风速预测及新能源抽油机风功率控制

AU - Zhang, Chun You

AU - Wang, Liang

AU - Li, Hong

AU - Wu, Tong Yan

AU - Li, Yan

PY - 2021/11

Y1 - 2021/11

N2 - 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.

AB - 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.

KW - Feedback linearization

KW - New energy pumping unit

KW - Power tracking

KW - Support vector regression(SVR)

KW - Wind energy

UR - https://www.scopus.com/pages/publications/85118928448

U2 - 10.13229/j.cnki.jdxbgxb20200848

DO - 10.13229/j.cnki.jdxbgxb20200848

M3 - 文章

AN - SCOPUS:85118928448

SN - 1671-5497

VL - 51

SP - 1997

EP - 2006

JO - Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition)

JF - Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition)

IS - 6

ER -

机器学习风速预测及新能源抽油机风功率控制

Abstract

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