Journal of Advanced Research in Science and Technology
Volume 5, Numéro 1, Pages 592-603
2018-06-01

Direct Power Control Based Artificial Neural Networks Of Doubly Fed Induction Generator For Wind Energy Conversion System Application



Authors : Djeriri Youcef .

Abstract

This paper proposes a Direct Power Control (DPC) strategy for a Doubly Fed Induction Generator (DFIG) based wind power generation system, using a Multilayer Perceptron (MLP) controller. This controller replaces the conventional DPC lookup table and allows the converter that is connected to the rotor terminals to operate with constant switching frequency. The digital simulation results of 1.5 MW DFIG are presented to show the validity and efficiency of the proposed control strategy to decouple and control the active and reactive power in different conditions of wind speed

Keywords

Wind energy ; Doubly fed induction generator ; Direct power control ; Artificial neural networks ; Multilayer perceptron.

Les articles similaires

Artificial Neural Network-based Robust Tracking Control For Doubly Fed Induction Generator Used In Wind Energy Conversion Systems

Youcef Djeriri .  Abdelkader Meroufel .  Mohamed Allam . 
pages 173-181.

Control Of A Wind Energy Conversion System Based On Brushless Doubly Fed Induction Generator

Tir Z. .  Abdessemed R. . 
pages 55-69.

Three-level Npc Voltage Source Converter Based Direct Power Control Of The Doubly Fed Induction Generator At Low Constant Switching Frequency

Djeriri Y. .  Meroufel A. .  Belabbes B. .  Massoum A. . 
pages 91-103.

Sliding Mode Control Of Brushless Doubly-fed Machine Used In Wind Energy Conversion System

Serhoud H. .  Benattous D. . 
pages 305-320.

Fault Diagnostic Of Doubly-fed Induction Generator In Stator Inter-turn Short Circuit Based Wind Turbine

Boumalha N. .  Hachelef R. .  Kouchih D. .  Tadjine M. .  Boucherit M. S. . 
pages 63-74.

Formats de citation