摘要
针对光照不均匀时光伏阵列输出呈现非线性、多峰值的问题,提出一种基于自然选择粒子群(SelPSO)算法结合电导增量法(INC)的多峰值最大功率点追踪(MPPT)算法。SelPSO算法通过淘汰和替换迭代过程中适应度低的粒子,更快、更准确地完成对全局最大值点的搜索;使用INC进行局部跟踪,有效减少寻优过程中的功率振荡,达到最大功率点跟踪的目的。利用MATLAB/Simulink进行仿真试验。结果表明:与INC相比,SelPSO算法的功率振荡由12 W降至0.05 W;与PSO算法相比,跟踪时间由0.15 s缩短至0.07 s。该混合算法在复杂环境下具有较优的跟踪速度、收敛精度以及较低的功率波动。
A multi-peak maximum power point tracking(MPPT)algorithm based on the natural selection particle swarm(SelPSO)algorithm combined with the conductivity incremental method(INC)is proposed to address the problem of non-linear,multi-peak photovoltaic arrays with non-uniform illumination.SelPSO algorithm can complete the search of the global maximum point faster and more accurately by eliminating and replacing the particles with low adaptation in the iterative process;Using INC for local tracking can effectively reduce the power oscillations during the search process and achieves the purpose of maximum power point tracking.Simulation experiments are carried out by using MATLAB/Simulink.The results show that compared with INC,the power oscillation of SelPSO algorithm is reduced from 12 W to 0.05 W,and compared with PSO algorithm,the tracking time is shortened from 0.15 s to 0.07 s.This hybrid algorithm has superior tracking speed,convergence accuracy and lower power fluctuation in complex environments.
作者
欧阳名三
陈伟
OUYANG Mingsan;CHEN Wei(School of Electrical and Information Engineering,Anhui University of Science and Technology,Huainan 232001,China)
出处
《北华大学学报（自然科学版）》
CAS
2024年第1期129-135,共7页
Journal of Beihua University（Natural Science）
关键词
最大功率点跟踪
自然选择粒子群
电导增量法
光伏阵列
maximum power point tracking
natural selection particle swarm
conductivity increment method
photovoltaic array
