Control of doubly fed induction generator with maximum power point tracking for variable speed wind energy conversion systems

被引：0
作者：
Yaichi I. [1 ]
Semmah A. [1 ]
Wira P. [2 ]
机构：
[1] Department of Electrical Engineering, Faculty of Electrical Engineering, Djillali Liabes University, University Campus, P. O. B. 89, Sidi Bel Abbes
[2] Institut de Recherche en Informatique, Mathématiques, Automatique et Signal (IRIMAS), Université de Haute Alsace, 61 Albert Camus Street, Mulhouse
来源：
Periodica polytechnica Electrical engineering and computer science | 2020年 / 64卷 / 01期
关键词：
Artificial Neural Network; Direct Power Control; Doubly Fed Induction Generator; Maximum Power Point Tracking; Phase Locked Loop; Proportional-Integral;
D O I：
10.3311/PPee.14166
中图分类号：
学科分类号：
摘要：
In this paper, a Direct Power Control (DPC) based on the switching table and Artificial Neural Network-based Maximum Power Point Tracking control for variable speed Wind Energy Conversion Systems (WECS) is proposed. In the context of wind energy exploitation, we are interested in this work to improve the performance of the wind generator by controlling the continuation of the Maximum Power Point Tracking (MPPT) using the Artificial Neural Network (ANN). The results obtained show the interest of such control in this system. The proposed Direct Power Control strategy produces a fast and robust power response, also the grid side is controlled by Direct Power Control based a grid voltage position to ensure a constant DC- link voltage. The THD of the current injected into the electric grid for the Wind Energy Conversion Systems with Direct Power Control is shown in this paper, the THD is lower than the 5 % limit imposed by IEEE STANDARDS ASSOCIATION. This approach Direct Power Control is validated using the Matlab/Simulink software and simulation results can prove the excellent performance of this control as improving power quality and stability of wind turbine. © 2020 Budapest University of Technology and Economics. All rights reserved.
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页码：87 / 96
页数：9
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