To address the issue of traditional maximum power point tracking (MPPT) control algorithms being prone to local optima and oscillations near the maximum power point in shaded environments, an improved sparrow search algorithm based on chaotic mapping and Levy flight strategy is proposed. When initializing the population, this algorithm uses Circle chaotic mapping to make the population distribution uniform and avoid slow convergence caused by a single population; By incorporating the Levy flight strategy into the alert system, both small step and large step searches can be performed to avoid the algorithm getting stuck in local optima; Finally, by comparing the simulation results of three different lighting schemes, namely traditional perturbation observation algorithm, traditional particle swarm optimization algorithm (PSO), and sparrow search algorithm (SSA), it is verified that ISSA has the characteristics of fast tracking speed, high convergence accuracy, and small overall power oscillation in static and shadow dynamic environments, which can effectively improve the maximum power tracking efficiency and accuracy of photovoltaic arrays in complex shading environments.