Research on MPPT Method under Uneven Illumination Intensity Based on BDMOA Algorithm

In photovoltaic power generation systems, uneven light due to external shading reduces efficiency. In the case of uneven illumination, the traditional MPPT algorithm has problems such as slow convergence speed, low accuracy, and large oscillation. In this paper, an improved MPPT algorithm based on dwarf mongoose is proposed. In the initialization process, an improved reverse learning strategy is introduced to expand the population search range, so as to find the global optimal solution. The sine cosine strategy is introduced to accelerate the convergence speed of the algorithm and improve the convergence accuracy, so as to obtain a better solution. The simulation results show that the convergence speed of the algorithm is 0.33 seconds faster, and the oscillation is reduced.