ANN-Based Adaptive Rotor Current Control for DFIG Wind Systems: A Comparative Dynamic Analysis

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Year : 2026 | Volume : 16 | 01 | Page :
    By

    Amit Rajendrabhai Pathak,

  • Dr. Rajnikant H. Bhesdadiya,

  1. Research Scholar, Department of Electrical Engineering, Gujarat Technological University, Ahmedabad, Gujarat, India
  2. Assistant Professor, Department of Electrical Engineering, Lukhdhirji Engineering College, Ahmedabad, Gujarat, India

Abstract

The variability of rotor current management in Doubly Fed Induction Generator (DFIG)-based wind energy conversion systems is crucial for maintaining stability in power extraction under fluctuating wind and grid circumstances. Traditional proportional-integral (PI) controllers, despite their ease of use, frequently exhibit diminished performance when faced with parameter uncertainty, nonlinear behaviors, and rapid wind fluctuations.This paper presents an adaptive rotor current control strategy, which is an Artificial Neural Network (ANN)-based approach designed to enhance the performance of both the transient and the steady-state operation of DFIG wind systems. An extensive mathematical model of the DFIG when it runs in the synchronous reference frame is constructed and a standard PI-based rotor current control scheme is applied as a reference point. The suggested ANN controller will autonomously control rotor currents through learning the nonlinear dynamics of the system mechanism to improve resilience to disturbances and parametric variations. ANN training is performed through supervised learning based on the available system operating data in different scenarios involving various wind speeds and grid disturbances. MATLAB/Simulink is used to perform dynamic comparative analyses, which are step wind variations, grid voltage disturbances, and load perturbation. Performance measures, which are rise time, settling time, overshoot, steady-state error and total harmonic distortion (THD) are measured. Simulation data has shown that the ANN-based adaptive controller exhibits a significant improvement in transient response, a decrease in the overshoot and an augmentation of the disturbance rejection of disturbances in contrast to the conventional PI controller. The advanced and smart control scheme proposed is an ideal solution to improve the rotor current control in DFIG wind power systems and increase the reliability and rigor mortis of renewable energy sources.

Keywords: Doubly Fed Induction Generator (DFIG), Rotor Current Control, Artificial Neural Network (ANN), Adaptive Control Strategy, Proportional–Integral (PI) Controller, Dynamic Performance Analysis, Wind Energy Conversion System (WECS), Disturbance Rejection

How to cite this article:
Amit Rajendrabhai Pathak, Dr. Rajnikant H. Bhesdadiya. ANN-Based Adaptive Rotor Current Control for DFIG Wind Systems: A Comparative Dynamic Analysis. Journal of Power Electronics and Power Systems. 2026; 16(01):-.
How to cite this URL:
Amit Rajendrabhai Pathak, Dr. Rajnikant H. Bhesdadiya. ANN-Based Adaptive Rotor Current Control for DFIG Wind Systems: A Comparative Dynamic Analysis. Journal of Power Electronics and Power Systems. 2026; 16(01):-. Available from: https://journals.stmjournals.com/jopeps/article=2026/view=242662


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Ahead of Print Subscription Review Article
Volume 16
01
Received 04/04/2026
Accepted 12/04/2026
Published 02/05/2026
Publication Time 28 Days
71

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