An SMC-MRAS Speed Estimator for Sensor-Less Control of DFIG Systems in Wind Turbine Applications

Author:

Mbukani Mwana Wa Kalaga1ORCID,Gitau Michael Njoroge1ORCID,Naidoo Raj1ORCID

Affiliation:

1. Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa

Abstract

A sliding mode control-based model reference adaptive system (SMC-MRAS) estimator for sensor-less control of doubly fed induction generator (DFIG) systems in wind turbine applications is proposed in this paper. The proposed SMC-MRAS estimator uses the rotor current as a variable of interest. The proposed SMC-MRAS estimator has the advantage of being immune to machine parameter variations. The SMC parameters are designed using the Lyapunov stability criteria. The performance of the proposed SMC-MRAS estimator is validated using simulations in MATLAB/SIMULINK. A comparative study between the proposed SMC-MRAS estimator and the PI-MRAS estimator is also conducted to demonstrate the superiority of the proposed SMC-MRAS estimator.

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference38 articles.

1. Doubly-fed induction generator using back-to-back PWM converters and its applications to variable-speed wind energy generation;Pena;IEE Proc.-Electr. Power Appl.,1996

2. Doubly-fed induction generators systems for wind turbines;Muller;IEEE Trans. Ind. Appl.,2002

3. Three-phase doubly-fed induction generators: An overview;Tazil;IET Electr. Power Appl.,2010

4. Trends in Wind Turbine Generator Systems;Polinder;IEEE J. Emerg. Sel. Top. Power Electron.,2013

5. Overview of control systems for the operation of DFIGs in wind energy applications;Cardenas;IEEE Trans. Ind. Electron.,2013

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3