Yazar "Harrouz, Abdelkader" seçeneğine göre listele

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    Comparative Analysis of Vector Control and Backstepping Control Techniques Applied to Wind Systems with PMSG
    (IEEE, 2024) Tahiri, Fadila; Harrouz, Abdelkader; Hartani, Mohamed Amine; Çolak, İlhami; Badoud, Abdessalam; Dumbrava, Virgil
    This paper compares vector control (VC) and backstepping control (BC) techniques for wind systems with permanent magnet synchronous generators (PMSGs). PMSGs offer high efficiency and compact size but require advanced control strategies for optimal performance. The study evaluates transient response, tracking accuracy, robustness, and disturbance rejection. Simulations of a comprehensive mathematical model demonstrate VC’s improved dynamic response and efficiency through control variable decoupling, while BC excels in tracking performance and robustness using a systematic backstepping approach. The findings aid in selecting suitable control strategies for wind energy systems and contribute to the development of improved algorithms for wind power generation.
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    Evaluating the Performance of MPPT and FPPT Approach in Standalone Solar PV Systems Under Variable Conditions
    (Institute of Electrical and Electronics Engineers Inc., 2024) Amine, Hartani Mohamed; Abdallah, Laidi; Fadila, Tahiri; Aissa, Benhammou; Harrouz, Abdelkader; Çolak, İlhami
    This research paper investigates the performance of standalone solar photovoltaic (PV) systems under varying weather conditions and load fluctuations. It focuses on the implementation and evaluation of Maximum Power Point Tracking (MPPT) and Fixed Power Point Tracking (FPPT) algorithms within a DC/DC converter to optimize the system's performance. Using MATLAB Simulink, the study models and simulates the PV system, analyzing the effects of different control methods and dynamic conditions on power output and stability. The results highlight the importance of precise tracking algorithms for enhancing the efficiency and reliability of PV systems. This work contributes to the development of advanced PV emulators and control strategies, offering new insights for improving solar energy harvesting. © 2024 IEEE.
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    Supervised artificial neural networks by field-oriented control applied to PMSG-based variable-speed wind turbine
    (Institute of electrical and electronics engineers inc., 2024) Aoumri, Mohammed; Harrouz, Abdelkader; Yaichi, Ibrahim; Çolak, İlhami; Kayışlı, Korhan; Dumbrava, Virgil
    Artificial intelligence techniques (AI), especially Artificial Neural Networks (ANN), have a significant impact on the control of electrical machines and power systems. Neural networks have created new and advanced boundaries in controlling power systems and electric generators, and they are already a complex, multidisciplinary technology undergoing dynamic evolution in recent years. This paper presents the application of a control methodology to a permanent magnet synchronous generator (PMSG) in the context of a variable speed wind turbine system. The study particularly focused on exploring the performance and optimization of the wind turbine system through the use of this control approach to extract the maximum amount of variable speed wind energy and address associated errors and problems, the control being studied and applied is Supervised ANN by FOC. The discussion explored the various components and performance of a wind system (WS) through simulations conducted in MATLAB/Simulink.