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Mathematical Problems in Engineering
Volume 2014, Article ID 750101, 13 pages
http://dx.doi.org/10.1155/2014/750101
Research Article

Robust Fuzzy Control for Doubly Fed Wind Power Systems with Variable Speed Based on Variable Structure Control Technique

1School of Electrical & Information Engineering, Hunan University, Changsha 410082, China
2The CIC of Wind Power Equipment and Energy Conversion, Hunan Institute of Engineering, Xiangtan 411104, China

Received 5 July 2014; Revised 28 October 2014; Accepted 28 October 2014; Published 18 November 2014

Academic Editor: Linni Jian

Copyright © 2014 Xizheng Zhang and Yaonan Wang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The design of a variable structure sliding-mode controller (SMC) for a variable speed wind turbine with double-fed induction-generator, based on the fuzzy logic, is described in this paper. The purpose of this controller is to maximize the energy capture by operating the turbine at the optimal rotational speed as well as fast and stable generator response. The dynamics of both the turbine and the generator are modeled to exhibit their mechanical/electrical characteristics. Two global sliding-mode controllers, which eliminate the reaching phase of SMC and the sliding-mode motion starts from the beginning, are designed to guarantee the robust tracking of both the optimal blade-rotor speed and the reference generator torque/flux in the whole process, despite the parametric uncertainty and external disturbance. To reduce the adverse chattering effect of the conventional SMC, the adaptive fuzzy inference strategy is adopted to deduce the adjustable switch gain, instead of the fixed gains. Simulation results show that the proposed controller achieves global asymptotic tracking, satisfied torque/flux responses, and has better performance and higher utilization ratio of wind energy than the conventional feedback-linearization method.