Publications Scientifiques
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Item Effects of Direct-Quadrature Rotor Current Sensors’ Faults in Wind Energy Conversion System based on Doubly Fed Induction Generator(Istanbul University, 2025) Chouider, Naziha; Beddek, Karim; Haddouche, Rezki; Zerrougui, Mohamed; Ramdani, OmarThis paper investigates the dynamic performance of a grid-connected wind energy conversion system (WECS) based on a doubly fed induction generator (DFIG) in the presence of additive and multiplicative faults in directquadrature rotor current sensors. The system architecture includes direct current-link voltage regulation, via the grid side converter and active/reactive power control, through the rotor side converter. Unlike prior studies that mainly consider symmetrical grid faults, this work systematically introduces various sensor faults specifically in stator current, stator voltage, and rotor current measurements into the rotor current control loop. The impact of these faults is assessed by examining key electrical parameters such as current, voltage, active, and reactive power across the grid, stator, and rotor. Simulation results reveal that rotor current sensor faults significantly degrade system stability and power regulation. These findings highlight the importance of developing robust fault detection and isolation and fault-tolerant control strategies and provide a foundation for enhancing the reliability of DFIG-based WECS under sensor fault conditionsItem Temporal Novel Approach for Bearings Faults Detection and Isolation in Wind Energy Conversion Systems(IndianJournals.com A product of Diva Enterprises Pvt. Ltd., 2020) Beddek, Karim; Tanvir, Aman A.; Beguenane, RachidThis paper presents bearings faults detection and isolation system for a wind energy conversion system (WECS). For this, and contrary to the traditional methods often used and based on the frequency and/or the vibration analysis of generator signals, this novel approach is based on the temporal analysis of electrical signals (current or voltage) of the generator. The method is based on the observer scheme, composed of a time-varying Kalman filter and the strategy of the mean-residual to generate new residual capable to detect and quantify all bearings faults types. The proposed system has been validated on signals of a doubly-fed induction generator and the simulation results approve its efficiency.Item Complex systems modeling and faults detection, using neural networks and genetic algorithms(2015) Beddek, Karim; Kesraoui, MohamedItem Signal-Based sensor fault detection and isolation for PMSG in wind energy conversion systems(IEEE, 2017) Beddek, Karim; Merabet, Adel; Kesraoui, Mohamed; Tanvir, Aman A.; Beguenane, RachidItem Optimization of the artificial neural networks structure for filtering applications in wind energy conversion system(2015) Beddek, Karim; Kesraoui, Mohamed; Merabet, AdelItem Speed control of sensorless induction generator by artificial neural network in wind energy conversion system(Institution of Engineering and Technology (IET), 2017) Merabet, Adel; Tanvir, Aman A.; Beddek, KarimItem Torque and state estimation for real-time implementation of multivariable control in sensorless induction motor drives(Institution of Engineering and Technology, 2017) Merabet, Adel; Tanvir, Aman A.; Beddek, Karim