摘要
传统的光伏系统MPPT算法易陷入局部最优,而基于智能优化算法的MPPT方法追踪速度慢,皆不能同时兼顾准确性和快速性。对此,该文设计一种变步长扰动观察法(IP&O)结合自适应布谷鸟搜索(ICS)算法的复合算法,先利用IP&O迅速到达对应电压最大的功率极大值点,再根据复杂光照环境下光伏阵列的输出特性,利用该点的功率值调整ICS算法的搜索范围,使其快速准确地追踪到最大功率点。通过仿真对比,验证了此算法在追踪速度和精度上的优越性。
The traditional MPPT algorithm of photovoltaic system is easy to fall into the local optimum,and the MPPT method based on the intelligent optimization algorithm has a slow tracking speed,which cannot balance accuracy and speed at the same time.In this regard,this article designs a composite algorithm combining Improved Perturbation and Observation method(IP&O)and improved cuckoo search(ICS)algorithm.It first uses IP&O to quickly track to the power extreme point of the maximum corresponding voltage.Then,according to the output characteristics of the photovoltaic array in the complex lighting environment,the power value of this point is used to dynamically adjust the search range of the ICS algorithm,so that it can track the maximum power point quickly and accurately.Through simulation comparison,the superiority of this algorithm in tracking speed and accuracy is verified.
作者
李昂
刘文锋
李音柯
高春阳
Li Ang;Liu Wenfeng;Li Yinke;Gao Chunyang(College of Electrical Engineering,Shaanxi University of Technology,Hanzhong 723001,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2023年第5期203-209,共7页
Acta Energiae Solaris Sinica
基金
陕西省教育厅专项科研计划(15JK1125)。
关键词
光伏阵列
光照条件
最大功率点跟踪
布谷鸟算法
变步长扰动观察法
photovoltaic arrays
illumination conditions
maximum power point trackers
cuckoo algorithm
improved perturbation and observation method
作者简介
通讯作者:刘文锋(1997-),男,硕士研究生,主要从事光伏发电技术方面的研究。liu956007718@163.com。
