C. Radhacharan, Duvvala Bharath Kumar
The increasing penetration of renewable energy resources into modern power systems has intensified the need for intelligent photovoltaic (PV) conversion systems capable of delivering reliable, efficient, and high-quality electrical power under continuously varying environmental conditions. This paper proposes an adaptive dual-port grid-connected photovoltaic inverter incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) for intelligent voltage regulation and enhanced energy management during solar irradiance disparity. The proposed architecture employs two independent photovoltaic sources connected through a dual-port converter that effectively balances power flow under both uniform and non-uniform irradiance conditions. The intelligent ANFIS controller dynamically regulates the converter switching operation to stabilize the DC-link voltage, improve transient response, and minimize harmonic distortion under rapidly changing atmospheric conditions. Four irradiance scenarios are investigated to evaluate the robustness of the proposed system, including complete shading of one photovoltaic module. MATLAB/Simulink simulations demonstrate that the proposed control strategy successfully maintains a constant output voltage despite significant variations in photovoltaic generation. Furthermore, the proposed system achieves superior grid synchronization, lower Total Harmonic Distortion (THD), enhanced voltage stability, improved converter efficiency, and reliable energy transfer compared with conventional control methods. The proposed intelligent dual-port photovoltaic architecture offers a practical solution for future smart-grid applications requiring high reliability, superior power quality, and sustainable renewable energy integration.