ANFIS-Based Synchronizing Control of Wind Turbine Driven DFIG System with PV Battery Support for Transient Reduction

Abstract

This study presents a MATLAB-based simulation of a hybrid renewable energy microgrid comprising a wind turbine-driven Doubly Fed Induction Generator (DFIG), photovoltaic (PV) array, and battery energy storage system (BESS). The primary objective is to minimize transient responses and enhance dynamic stability during synchronization and load variation conditions. To achieve this, an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is designed to regulate the rotor-side voltage source converter (VSC) and optimize system parameters under fluctuating wind and solar conditions. The proposed ANFIS control approach adaptively tunes control signals using fuzzy logic and neural learning to improve voltage stability, frequency regulation, and power quality. Comparative analysis with conventional PI-based control demonstrates that the ANFIS controller significantly reduces overshoot, settling time, and harmonic distortion in system responses. The results confirm the effectiveness of the proposed control technique in achieving smoother synchronization between distributed energy sources, enhanced transient performance, and efficient power management in an isolated or grid-connected environment. This work provides a robust and intelligent control framework for future renewable energy-based microgrids.