基于改进布谷鸟算法结合电导增量法的最大功率点追踪

动态遮阴下,光伏阵列的输出P-U曲线会出现多个功率极值点,传统最大功率点追踪会陷入局部最优。为此,本文提出基于自适应差分进化的改进布谷鸟(ICS)算法与电导增量法(INC)相结合的复合算法(ICS-INC)。该算法提出自适应抛弃概率和自适应步长因子,结合差分变异进行随机偏好游走,使算法的搜索开发能力得到提升,避免陷入局部最优。通过改进Lévy飞行公式减小其随机性,减小算法的迭代次数来缩短跟踪时间,由INC实现局部快速搜索,稳定输出最大功率。仿真结果表明,与其他算法相比,该算法的追踪速度,全局搜索性以及环境变化的适应能力均得到提升。

Maximum power point tracking based on improved Cuckoo algorithm combined with incremental conductance method

Under dynamic shading, the PV array output P-U curve will appear multiple power extreme points, and the traditional maximum power point tracking will fall into local optimal. Therefore, a compound algorithm (ICS-INC) based on the improved Cuckoo (ICS) algorithm and incremental conductance (INC) was proposed. The algorithm proposed adaptive discard probability and adaptive step size factor, combined with differential variation to carry out random preference walk, so as to improve the search and development ability of the algorithm and avoid falling into local optimal. By improving Levy flight formula, randomness was reduced, iteration times of algorithm were reduced, tracking time was shortened, fast search was realized by INC, and maximum power output was stable. The simulation results show that compared with other algorithms, the algorithm"s tracking speed, global search ability and ability to adapt to environmental changes are improved.