Research on maximum power point tracking algorithm of photovoltaic power generation based on improved atom search optimization algorithm

Abstract

In the face of the change of light conditions of local photovoltaic cells in the photovoltaic array, the P-V curve of photovoltaic cells shows the characteristics of multi-peak. Using Perturb and Observe algorithms (P&O), the traditional MPPT (Maximum Power Point Tracking) Perturb and observe algorithms (P&O) is easy to stay in the local optimal state, which results in the loss of power conversion efficiency of photovoltaic power generation system. In order to improve energy efficiency, the search speed and global optimal accuracy of maximum power point tracking are improved. Aiming at the multi-peak P-V curve caused by local illumination changes, the Improved Atom Search optimization (IASO) MPPT algorithm is proposed. The experimental simulation design of a variety of partial photovoltaic cells under different light intensity and light changes, using the IASO algorithm to compare with ASO, P&O. Simulation results show that the proposed algorithm has lower power fluctuation, higher stability, faster tracking speed and higher efficiency.