The P-U characteristic curve of a photovoltaic array exhibits multi-peak characteristics in partially shaded environments

leading to the inefficiency of conventional maximum power point tracking(MPPT)algorithm in tracking the maximum power. To address this issue

this paper proposes a two-layer control model for photovoltaic MPPT based on an improved tuned swarm optimization(TSO) algorithm. In the upper layer

the Levy flight strategy and polynomial mutation strategy are embedded into tuna algorithm

creating the Levy-polynomial mutation tuna swam optimization(LPTSO) to search for the global maximum power point. In the lower layer

the perturbation observation method is employed to locally track the global maximum power point

thereby reducing power oscillations in local shading environments. The two-layer control model is applied to the photovoltaic MPPT simulation system

and the simulation experimental results show that

for multi-peak MPPT control

the proposed model achieves significant improvements in convergence speed

tracking efficiency

power oscillations

etc. In conclusion

the proposed two-layer control model for photovoltaic MPPT effectively addresses the issue of maximum power tracking failure in partially shaded environments.