采用自适应扰动观察法的光伏并网系统最大功率点跟踪

Maximum Power Point Tracking Using Adaptive Perturbation and Observation Algorithm for Grid-connected Photovoltaic System

提出了一种自适应扰动观察(P&O)算法,用于在不同天气条件下太阳能光伏(PV)并网系统的最大功率点跟踪(MPPT)控制策略;该策略对于从太阳能光伏电池板中,获取最大的功率输出是十分重要的;利用一种依赖于功率变化的可变的扰动步长,提出了改进的自适应扰动观察算法;最后将通过仿真所得到的数据与传统的扰动观察算法进行了比较,结果表明所提出MPPT算法的收敛值和速度得到了改善,稳定时间缩短25%,稳态值提高20%以上,在太阳能光伏并网系统的最大功率点跟踪时是有效而实用的。

This paper proposes an adaptive perturbation and observation(P&O)algorithm for maximum power point tracking(MPPT)control strategy of a grid-connected solar photovoltaic(PV)system under varying atmospheric conditions.This strategy is important in order to extract maximum power output from a solar PV panel.The adaptive P&O algorithm is proposed to utilize a variable perturbation step size which depends on power changes.The obtained simulation results are compared with those using the conventional P&O algorithm,which show the convergence value and speed of the proposed MPPT algorithm are improved.The steady time is shortened by 25%,and the steady-state value is increased by more than 20%.So the proposed algorithm is effective and practical in the MPPT of a grid-connected solar PV system.