In the realm of photovoltaic (PV) solar systems, optimizing the extraction of maximum power from solar panels is paramount for enhancing efficiency and overall performance. This paper introduces a novel MPPT algorithm based on the Fuzzy Fishier Mantis Optimizer (FFMO) method tailored specifically for PV solar systems. The new algorithm combines the effective searching and using abilities of the FFMO method with the special features of PV panels to continuously find the maximum power point (MPP) as environmental conditions change. For the solar PV battery system, we provide a fuzzy logic-based maximum power tracking and an optimized proportional integral-based voltage controller using the Fishier-Mantis optimizer. We utilize an algorithm that employs fuzzy logic to maximize PV panel output, irrespective of environmental circumstances. We use the Fishier Mantis optimizer technique to adjust the proportional integral controller's gain, which keeps the voltage steady across the load and helps the fuzzy logic MPPT get the most power from the PV panel. MATLAB Simulink has been used to model and test the whole system. The Fishier Mantis Optimizer is a particle swarm optimization and a genetic algorithm competitor. The whole system has been tested for constant irradiation, variable irradiance, and varied load circumstances. The PV battery system with proportional integral control shows better results in all situations based on the test results of the fuzzy-based MPPT and the Fishier-Mantis optimizer algorithm.
Elwaer et al. (Fri,) studied this question.