نبذة مختصرة : Introduction. This paper investigates various methods for controlling the Maximum Power Point Tracking (MPPT) algorithm within the framework of intelligent energy control for grid-connected Hybrid Renewable Energy Systems (HRESs). The purpose of the study is to improve the efficiency and reliability of the power supply in the face of unpredictable weather conditions and diverse energy sources. Intelligent control techniques are used to optimize the extraction of energy from available sources and effectively regulate energy distribution throughout the system. Novelty study is employing intelligent control strategies for both energy optimization and control. This research distinguishes itself from conventional approaches, particularly through the application of Self-Tuning Fuzzy Logic Control (ST-FLC) and fuzzy tracking. Unlike conventional methods that rely on logical switches, this intelligent strategy utilizes fuzzy rules adapted to different operating modes for more sophisticated energy control. The proposed control strategy minimizes static errors and ripples in the direct current bus and challenges in meeting load demands. Methods of this research includes a comprehensive analysis of several optimization techniques under varying weather scenarios. The proposed strategy generates three control signals that correspond to selected energy sources based on solar irradiation, wind velocity and battery charging status. Practical value. ST-FLC technique outperforms both conventional methods and standard Fuzzy Logic Controllers (FLCs). It consistently delivers superior performance during set point and load disturbance phases. The simulation, conducted using MATLAB/Simulink. The results indicate that fuzzy proposed solution enables the system to adapt effectively to various operational scenarios, displaying the practical applicability of the proposed strategies. This study presents a thorough evaluation of intelligent control methods for MPPT in HRESs, emphasizing their potential to optimize energy supply under varying conditions. References 27, tables 6, figures 18.
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