基于二阶滑模控制的变速双馈风力发电系统最大功率点跟踪

Liu Xiangjie; Wang Chengcheng; Han Yaozhen

doi:10.16383/j.aas.2017.e150252

基于二阶滑模控制的变速双馈风力发电系统最大功率点跟踪

doi: 10.16383/j.aas.2017.e150252

刘向杰^1,,
王诚诚^1,,
韩耀振^1,2, ,

1.
华北电力大学新能源电力系统国家重点实验室北京 102206
2.
山东交通学院信息科学与电气工程学院济南 250357

基金项目:

Natural Science Foundation of Beijing 4122071

the National Natural Science Foundation of China 61273144

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出版历程
- 收稿日期: 2015-10-15
- 录用日期: 2016-02-28
- 刊出日期: 2017-08-20

Second-order Sliding Mode Control of DFIG Based Variable Speed Wind Turbine for Maximum Power Point Tracking

1.
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
2.
School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China

Funds:

Natural Science Foundation of Beijing 4122071

the National Natural Science Foundation of China 61273144

More Information

Author Bio:
Xiangjie LIU received the Ph.D.degree in electrical and electronic engineering from the Research Center of Automation, Northeastern University, Shenyang, China, in 1997.He subsequently held a postdoctoral position with the China Electric Power Research Institute (CEPRI), Beijing, China, until 1999.He has been an Associate Professor in CEPRI since 1999.
He was a Research Associate with the University of Hong Kong, and a Professor with National University of Mexico.He is now a Professor with the Department of Automation, North China Electric Power University, Beijing, China.His research interests include fuzzy control, neural networks, model predictive control with its application in industrial processes.
Prof.Liu is a member of Technical Committee on Control Theory, a member of Technical Committee on Process Control, Chinese Association of Automation, an editor of Chinese Journal of Control Engineering and an editor of Chinese Journal of Electric Power Automation Equipment.He has been in Program for New Century Excellent Talents in University since 2006.E-mail:liuxj@ncepu.edu.cn

Chengcheng Wang is a master student in the Department of Automation, North China Electric Power University (NCEPU).She received the B.S.degree in automation in 2008, from Department of Automation, NCEPU.Her main research interest is sliding mode control of wind turbine systems.E-mail:wangcc@ncepu.edu.cn

Corresponding author: Yanzhen Han received the B.S.degree in automation in 2005 from Qingdao University of Science and Technology, Qingdao, China, and the M.S.degree in automatic control in 2008, from Shandong University, Jinan, China.He is currently working toward the Ph.D.degree in automatic control at North China Electric Power University, Beijing, China.Now he also works as an Associate Professor in Shandong Jiaotong University, Jinan, China.His research interests include modeling, optimization, and sliding mode control of power plants.Corresponding author of this paper.E-mail:hyz125@163.com

摘要

摘要: 本文提出一种超螺旋二阶滑模控制方案同时实现双馈变速风力发电系统最大风能捕获和无功功率调节.通过设计两个二阶滑模控制器，实现控制目标，降低机械磨损，提高控制精度，通过调节发电机转子电压，跟踪风机最优转速和转子电流设定值，实现额定风速以下的最大风能捕获和无功功率调节.采用二次型李雅普诺夫函数确定控制参数范围、确保系统有限时间稳定性.1.5 MW风机系统仿真实验验证所提方案有效性.
- 双馈异步发电机 /
- 最大功率点跟踪 /
- 二阶滑模控制 /
- 变速风电机组
Abstract: This paper proposes a super-twisting second order sliding mode control scheme to maximize the wind energy capture of a doubly fed induction generator based variable speed wind turbine (VSWT) system, and minimize the reactive power simultaneously. Two second order sliding mode controllers are designed to achieve the control objectives, reduce mechanical stress and improve control accuracy. By regulating the generator rotor voltage, one controller makes the wind turbine rotor speed track the optimal speed, which can maximize power generation. The other maintains the rotor current at rated value to minimize the reactive power. A quadratic form Lyapunov function is adopted to determine the range of controller parameters and guarantee the finite time stability. Simulation results on a 1.5MW doubly fed induction generator (DFIG)-based variable speed wind turbine demonstrate the validity of the proposed control strategy.
- Doubly fed induction generator (DFIG) /
- maximum power point tracking (MPPT) /
- second order sliding mode (SOSM) control /
- variable speed wind turbine (VSWT)
Recommended by Associate Editor Qinmin Yang
注释:

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Fig. 1 WT operation regions.

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Fig. 2 Phase diagram of stator flux orientation.

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Fig. 3 $ C_p-\lambda $ characteristic of wind turbine.

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Fig. 4 The schematic diagram of the DFIG-based WT system.

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Fig. 5 Stepwise wind speed profile.

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Fig. 6 Regulation performances of $ \omega _w $ , $ I_{rd} $ and $ C_p . $

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Fig. 7 Comparison of the FOSM and the SOSM controller outputs.

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Fig. 8 Randomly varying wind speed profile.

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Fig. 9 Regulation performances of $ \omega _w $ , $ I_{rd} $ and $ C_p . $

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Fig. 10 SOSM controller outputs.

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$ \omega _w $	wind turbine rotor speed;
$ I_{rd} $	the $d$ -axis component of rotor current;
$ I_{rq} $	the $q$ -axis component of rotor current;
$ U_{rd} $	the $d$ -axis component of the rotor voltage;
$ U_{rq} $	the $q$ -axis component of the rotor voltage;
$ J $	the inertia of the combined rotating parts;
$ K $	turbine total external damping;
$ n_g $	gearbox ratio;
$ \phi _s $	stator flux;
$ L_m $	mutual inductance;
$ L_s $	stator leakage inductance;
$ L_r $	rotor leakage inductance;
$ R_r $	rotor resistance;
$ \omega _1 $	synchronous speed;
$ n_p $	pole pair number.

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Table Ⅰ Characteristic of the Simulated Wind Turbine System

Wind turbine parameters	Value
Number of blades	3
Rotor radius	35 m
Hub height	84.3 m
Rated power	1.5 MW
$ J$	$4.4532\times 10^5 {\rm kg\cdot m^2}$
$K$	$200 {\rm N\cdot m\cdot s/rad}$
$n_g$	$83.531$
$\lambda_{\rm opt} $	8
$n_p$	$2$
$\rho$	$1.2 {\rm g/m^3}$
$U_s$	$690 {\rm V}$
$R_r$	$0.0089 {\rm \Omega}$
$\omega _1$	$1500 {\rm r/\min}$
$L_m $	$0.016 {\rm mH}$
$L_r$	$0.299 {\rm mH}$
$L_s$	$0.407 {\rm mH}$
$ \Delta K$	$40\sin (\pi / {300})t $
$ \Delta R_r$	$0.00178\sin (\pi / {300})t $

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