Abstract
Currently, the solar photovoltaic (PV) systems are becoming more and more important in order to meet the world's increasing demand for electricity. In this study, a unique Hybrid Group Search Integrated Rider (HGSR)-MPPT control technique is developed to track the maximum solar energy from the PV panels in order to meet the grid systems' need for electricity. Then, the output voltage of the PV is boosted using the cutting-edge Cuk Step-Up converter, which has a higher voltage gain efficiency and lower stress voltage between the switches. Consequently, the Self-Adaptive Rao Control (SARC) technique is implemented to produce the pulses required to actuate the converter's switching components. More specifically, the improved switched capacitor five-level inverter circuit is modelled in this study to improve the grid unit's power quality with low leakage current, switching stress, and minimal component consumption. In order to improve the performance of the MLI's switching operating modes, the unique Deep Reinforced Q-Learning Control (DRQLC) technique is implemented. The output voltage, current, power, THD, and voltage gain efficiency of the proposed controlling mechanisms' simulation results are evaluated and analyzed.
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