Application of Improved Cat Swarm Optimization in MPPT Control of Photovoltaic Arrays

Abstract

In the photovoltaic power generation system, the P-U output curve of the system has a multiple-peak phenomenon due to the influence of complicated factors such as partial shading. The traditional single-peak optimization based on the cat swarm optimization cannot effectively track the MPP point in the case of multiple peaks. This paper proposes a new improved cat swarm optimization, which is applied to the tracking of photovoltaic maximum power point. The method introduces the degree of aggregation, evolutionary speed factor, mutation operator and inertia weight factor. For the traditional cat swarm optimization(CSO), it is easy to fall into a local optimum. When the initial particle distribution is uneven or too concentrated, a narrow search space will be formed. The problem was simulated in the environment of MATLAB/SIMULINK, and the correctness of the method was verified by comparison and analysis with the traditional CSO.