A modified shuffled frog algorithm to improve MPPT controller in PV System with storage batteries under variable atmospheric conditions

Owing to the nonlinear behavior of photovoltaic (PV) power plants, it is essential to utilize the maximum power point tracking (MPPT) methods for generating the maximum possible power. The common MPPT approaches cannot operate appropriately in quickly changing environmental circumstances and under partial shading circumstances. In other words, tracking the global maximum power point (GMPP) is not easy in such conditions and multiple peaks are seen in the power-voltage (P-V) curve. The parameters of the proposed FLC is tuned via the modified shuffled frog leaping algorithm (MSFLA) to optimize the fuzzy system of MPPT. The main problems related to the design of FLCs is to tune fuzzy membership functions. To cope with the above-mentioned challenge, this combination covers the weaknesses of each algorithm, optimizing parameters in FLCs, and enhance the speed and accuracy of the system The suggested design is confirmed for MPPT of a PV-BES system using MATLAB/Simulink software. The results indicate a better performance of the offered FLC comparing with the previous works.

Automated summary

This study tunes the parameters of a fuzzy logic controller using a modified shuffled frog leaping algorithm to optimize the maximum power point tracking system. The combination of algorithms improves the performance and accuracy of the system, with results showing better performance compared to previous works.