采用自适应扰动观察法的光伏并网系统最大功率点跟踪

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。

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

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.