Tracking MPPT under Photovoltaic Shadow Based on FP&O-IMSSA Method

The operation of photovoltaic arrays under shadow conditions can easily result in multiple peaks, which is not conducive to system operation. This paper proposes a fuzzy logic perturbation composite improved sparrow algorithm. This method uses fuzzy logic perturbation to quickly track the maximum power point of the system operation, and then pass the system parameters to the multiple improved sparrow algorithm for simulation. The composite global chaos and reverse elite learning strategy improve the convergence speed, and the adaptive weight coordination avoids the system falling into multiple peaks, making it possible to respond to the changes of I/V in a timely manner during system operation. The improved sparrow algorithm enhances the tracking ability in shadow conditions, where it is prone to local optima. Several simulation models have been constructed to compare and illustrate the improvement of the convergence speed and tracking accuracy of the improved composite algorithm in tracking the maximum power point.