基于光伏MPPT采样电流的自适应变步长INC算法

针对传统电导增量INC（incremental conductance）算法在跟踪最大功率点的过程中无法兼顾跟踪速度与稳态精度的问题，以及传统变步长算法在光照变化时容易发生误判的问题，提出了一种新型的自适应变步长INC算法。光照强度变化较大时，利用负载曲线与I-V特性曲线的工作原理，在暂稳态和非稳态下都可以根据最大功率点跟踪MPPT（maximum power point tracking）采样电流的变化，自适应调节跟踪速度；光照强度变化较小时，能够根据输出电压与功率的变化自适应减小步长，提高稳态精度。追踪速度是传统算法的9.3倍，是现有变步长算法的4.2倍，有效减少了光照强度变化带来的功率损失。

Adaptive Variable-step INC Algorithm Based on PV MPPT Sampling Current

The traditional incremental conductance(INC) algorithm is unable to balance its tracking speed and steady-state accuracy in tracking the maximum power point, and the traditional variable-step algorithm is prone to misjudgment when solar irradiance changes. Aimed at these problems, a novel adaptive variable-step INC algorithm is proposed. When the solar irradiance varies greatly, it can adaptively adjust the tracking speed according to the changes in maximum power point tracking(MPPT) sampling current in transient and unsteady states by using the working principles for load curve and I-V characteristic curve. In the case of small changes in solar irradiance, it can adaptively reduce the step size according to the changes in output voltage and power, thus improving the accuracy in the steady state. The tracking speed of this algorithm is 9.3 times faster than that of the traditional algorithm and 4.2 times faster than that of the existing variable-step algorithm, which effectively reduces the power loss caused by changes in solar irradiance.