Contribution to the Study and Control Using Advanced Techniques of a DFIG Used in a Wind Farm

Toufik, Mebkhouta (2025) Contribution to the Study and Control Using Advanced Techniques of a DFIG Used in a Wind Farm. Doctoral thesis, Faculté des Sciences et de la technologie.

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Abstract

With the increasing reliance on wind energy for electricity generation, researchers have conducted extensive studies to enhance power quality and maximize energy extraction. Among the various generator technologies, the Doubly-Fed Induction Generator (DFIG) has gained significant attention due to its ability to operate at variable speeds, making it well-suited for a wide range of wind conditions. This thesis provides a comprehensive study of wind energy, beginning with an overview of wind power generation, turbine operation, and the Maximum Power Point Tracking (MPPT) strategy for optimal power extraction. It also explores the process of electromechanical energy conversion through generators and presents an in-depth analysis of advanced control strategies and their classifications. A hybrid control approach integrating Backstepping Control (BSC) with the Linear Quadratic Regulator (LQR) is implemented to enhance system stability and performance. Additionally, the thesis investigates the impact of current sensors on control implementation and system operation. To address sensor failures, the Extended Kalman Filter (EKF) is utilized for current estimation and fault detection, ensuring continuous and reliable system performance. The final part of the study focuses on an advanced control strategy, Finite Set Predictive Current Control (FSPCC), combined with a sensorless approach using the Model Reference Adaptive System (MRAS) observer to eliminate the speed sensor. This approach not only reduces operational costs but also enhances system efficiency, making it a viable solution for real-time wind energy applications. By integrating precise system modeling, advanced control techniques, and sensor fault compensation strategies, this research contributes to the improvement of DFIG-based wind energy systems, enhancing their reliability, efficiency, and cost-effectiveness in practical applications.

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