Power Improvement of Non-Linear Wind Turbines during Partial Load Operation using Fuzzy Inference Control

Journal of Control Engineering and Applied Informatics

Ian Howard¹  Hamed Habibi²  Aghil Yousefi Koma³ 

[1] Associate Professor, Faculty of Science and Engineering, School of Civil and Mechanical Engineering, Curtin University, Perth, Australia;PhD, Faculty of Science and Engineering, School of Civil and Mechanical Engineering, Curtin University, Perth, Australia;Professor, Centre of Advanced Systems and Technologies (CAST), School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran

关键词: wind turbine;    nonlinear model;    partial load operation;    fuzzy inference system;   

DOI  :  

学科分类：农业科学（综合）

来源: Societatea Romana de Automatica si Informatica Tehnica

【 摘 要 】

Power generation in modern and industrial wind turbines can be improved by careful choice and analysis of operational control strategies. This paper considers the design of a new controller employing a fuzzy inference system during partial load operation. Fuzzy logic is used to obtain reference controller gains where the controller scheme uses the generator speed as a feedback signal and the pitch angle is fixed at its optimum value. Fuzzy rules were defined with respect to the response of the wind turbine to reference gains such that the output power tracks the ideal power curve as close as possible without any significant increase of stress on the main shaft and drive train. A variety of membership shape functions were considered to show the resulting effect on the extracted energy and the drive train stress. Simulation results showed an increase of total extracted energy from the wind turbine through the use of the fuzzy inference system controller. The fuzzy controller was evaluated based on a nonlinear model of the wind turbine using real wind speed applied to the model as a disturbance, to consider the practicality of the proposed controller.

【 授权许可】

CC BY