The utilization of photovoltaic (PV) systems for power generation has become widespread in various locations, driven by the depletion of carbon-based fuels and growing ecological concerns. The integration of solar panels for electricity generation, coupled with energy storage batteries to store excess power, is anticipated to play a crucial role in meeting future societal energy demands. In the proposed work, optimization of FOPID controller for the extraction of MPPT in solar PV system undergoes the tuning of controller parameters, such as \({k}_{p},{k}_{i},{k}_{d},\mu \) and \(\lambda \) to attain better efficiency and performance of a model with LED deriver as the load. The MPPT process is implemented on the input side of the converter through controller algorithm. The control method is employed to manage the output voltage of the load and monitor the battery charging status. Similarly, the parameters of the FOPID controller are tuned optimally using the Coati Tuned Dwarf Mongoose algorithm that inherits the characteristics features of both Coati optimization algorithm (COA) and the Dwarf Mongoose optimization algorithm (DMOA). In order to improve the robustness and the convergence speed of the COA, the characteristics of DMOA is introduced into COA. Furthermore, the voltage converter’s design allows for the transfer of electric energy between a solar panel and an LED lamp, as well as between a battery and an LED lamp. A functional battery has been engineered with a two-way power flow, enabling it to supply power to the LED lamp and store excess power from the solar panel. The switches operate alternately, simplifying the mode of operation strategy. The system’s converter stability is analyzed through implementation, ensuring its robust design. The prototype’s experimental results validate the effectiveness of the converter design.
