ANFIS-Based Maximum Power Transfer and Stability Enhancement in Grid Connected Solar PV using MATLAB-Simulink

This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based control strategy for maximizing power transfer and enhancing stability in a grid-connected solar photovoltaic (PV) system. The proposed system is designed and implemented using MATLAB-Simulink to ensure efficient real-time simulation. ANFIS is employed to optimize the maximum power point tracking (MPPT) process, enabling the extraction of maximum available solar power under varying irradiation and temperature conditions. Additionally, an independent active and reactive power (P-Q) control strategy is integrated with a voltage source converter (VSC) to ensure stable and efficient power transfer to the grid. The effectiveness of the proposed controller is evaluated through detailed simulations under different environmental conditions, demonstrating its ability to maintain system stability and improve overall power quality. Simulation results validate the superiority of the proposed approach in achieving enhanced performance and reliability in grid-connected PV systems.