DEVELOPMENT AND PERFORMANCE ANALYSIS OF A HYBRID ANFIS-BASED CONTROL SYSTEM FOR ISLANDED MICROGRIDS
DOI:
https://doi.org/10.55640/Keywords:
Islanded microgrid, ANFIS controller, hybrid control systemAbstract
Reliable and adaptive control strategies are essential for ensuring the stability and efficiency of islanded microgrids operating with high penetration of renewable energy sources. This study presents the development and performance evaluation of a hybrid control system based on an Adaptive Neuro-Fuzzy Inference System (ANFIS) for voltage and frequency regulation in islanded microgrids. The proposed controller integrates rule-based fuzzy logic with the learning capability of neural networks to dynamically respond to load fluctuations and renewable generation variability. A test microgrid model comprising photovoltaic (PV), wind, and battery storage units was simulated in MATLAB/Simulink under various operating scenarios, including sudden load changes and generation intermittency. Performance metrics such as settling time, overshoot, and total harmonic distortion (THD) were analyzed and compared against conventional PID and pure fuzzy controllers. The results demonstrate that the hybrid ANFIS controller significantly enhances dynamic response and maintains grid stability, making it a promising solution for autonomous microgrid management.
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Copyright (c) 2024 Dr. Sarah Connors, Dr. Tarek Al-Shehri (Author)
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