AN INTELLIGENT ANFIS CONTROL STRATEGY FOR ELECTRIC VEHICLE-ASSISTED REACTIVE POWER COMPENSATION IN HYBRID AC/DC MICROGRIDS

Abstract

Hybrid AC/DC microgrids have emerged as a promising solution for integrating renewable energy sources, energy storage systems, and electric vehicle (EV) charging infrastructures. However, the increasing penetration of distributed energy resources introduces challenges in reactive power management and power flow coordination between AC and DC subgrids. Conventionally, interlinking converters (ILCs) are solely responsible for maintaining power balance and reactive power compensation, resulting in increased converter ratings and operational stress. This paper proposes an improved control strategy in which electric vehicles actively participate in reactive power support and power balancing operations, thereby reducing the required capacity of interlinking converters. An Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is employed to coordinate EVs, renewable energy sources, and the ILC under varying load and generation conditions. The proposed strategy enhances voltage regulation, improves power quality, minimizes converter losses, and reduces converter sizing requirements. MATLAB/Simulink simulations demonstrate that the proposed ANFISbased control significantly improves dynamic response, reduces reactive power burden on the ILC, and increases overall microgrid efficiency compared to conventional control approaches.