Renewable Energy Resources (RES) have become integral components of energy strategies worldwide, witnessing a widespread adoption across various applications. The prevalent utilization of these resources can be attributed to their efficiency, cost-effectiveness and the growing global demand for energy. As daily energy consumption continues to rise, the popularity of renewable energy resources persists, driven by their effectiveness and economic viability across diverse sectors. The proposed system constitutes a Photovoltaic (PV) energy generation system integrated with a high-gain multi-port DC-DC converter, ultimately powering a DC load. The high-gain multi-port DC-DC converter serves as a pivotal component, efficiently managing power flow between the PV source and the DC load. Notably, the DC link voltage, critical for sustained operation, is adeptly regulated by a Modified Adaptive Neuro-Fuzzy Inference System (ANFIS) controller. This controller optimally adjusts the converter's operation, ensuring the stability and reliability of the entire system. The significance lies in the synergy between renewable energy harvesting through PV panels, the versatile multi-port converter and the intelligent control facilitated by the Modified ANFIS, collectively fostering an energy-efficient and robust DC-based power system. The battery system is employed to store surplus energy attained from the PV system, which can be utilized in the lagging period of energy. The overall proposed system is implemented in MATLAB/Simulink. This comprehensive approach not only harnesses solar energy effectively but also showcases the adaptability and precision achieved through advanced control strategies, making it a promising model for sustainable energy applications.
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Ramakrishnan et al. (2024) studied this question.
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