关键词: 最大功率点跟踪, 局部阴影, 粒子群优化算法, 自适应权重

Abstract: In a photovoltaic power generation system, photovoltaic arrays tend to be affected by the phenomenon of partial shadow that will cause system instability and reduce its output with the P-U characteristic curve containing more than one peak, which makes the conventional algorithm of MPPT difficult to track the real maximum power point because of its single peak optimization. Particle swarm optimization algorithm is widely used in the maximum power point tracking of partial shadow for its good multimodal global optimization ability. The particle swarm algorithm, however, has shortcomings of low convergence speed and poor searching accuracy. So, the adaptive inertia weigh particle swarm optimization algorithm was proposed to solve these problems, in which the nonlinear dynamic inertia weight factor is introduced into the PSO evolution to reinforce the exploitation of global optimum of the PSO algorithm. To verify the feasibility of the algorithm under constant partial shading and rapidly changing partial shading, a simulation was conducted with Matlab, which shows that the novel algorithm can avoid the premature convergence effectively and the search capability is better.

Key words: maximum power point tracking (MPPT), partial shading, particle swarm optimization algorithm, adaptive inertia weight