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International Journal of Renewable, Green, and Sustainable Energy

Open Access Peer Review International
Open Access

DEVELOPMENT AND PERFORMANCE ANALYSIS OF A HYBRID ANFIS-BASED CONTROL SYSTEM FOR ISLANDED MICROGRIDS

DOI https://doi.org/10.55640/
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Dr. Sarah Connors 1 , Dr. Tarek Al-Shehri 1 ,
4 Smart Grid and Intelligent Systems Laboratory, University of Manchester, Manchester, United Kingdom
4 Department of Renewable Energy Systems, King Abdulaziz University, Jeddah, Saudi Arabia

Abstract

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.

Keywords

Islanded microgrid, ANFIS controller, hybrid control system

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