Research on Partial Shading MPPT Based on IPSO-PO Algorithm

Under the condition of partial shading, the photovoltaic power generation power has multiple peak points. The traditional maximum power point tracking algorithm is prone to fall into local optimal values and cannot track the maximum power point. Moreover, the traditional algorithm has the disadvantages of slow convergence speed and low tracking accuracy. Therefore, a local shading MPPT based on the improved particle swarm optimization (IPSO) and perturbation observation method (PO) is proposed. Firstly, in the PSO algorithm, the tent chaotic mapping is used to replace the random initialization of the population, and the adaptive factor is adopted to balance the exploration and exploitation of the algorithm, thereby improving the PSO algorithm. The initial power is obtained by initializing the population position. Then, the global search is carried out, and the individual position is continuously updated to approach the maximum power point. Four modes are simulated, and the results show that the IPSO-PO algorithm has a better optimization result. The IPSO-PO algorithm has a faster convergence speed and higher tracking accuracy than the PSO-PO algorithm and the PSO algorithm. The IPSO-PO algorithm solves the problem that the traditional MPPT algorithm is prone to fall into local optimal values, improves the tracking accuracy and convergence speed, and avoids the violent oscillation in the optimization process. It can effectively improve the efficiency of photovoltaic power stations.