现代电子技术2024，Vol.47Issue(10)：143-150,8.DOI:10.16652/j.issn.1004-373x.2024.10.027
基于改进SCSO算法的光伏MPPT研究
Research on PV MPPT based on improved SCSO algorithm
摘要
Abstract
In allusion to the problem that the power generation efficiency of photovoltaic arrays can decrease under local occlusion,and traditional maximum power point tracking(MPPT)are prone to tracking failure,a MPPT method based on improved sand cat swarm optimization(SCSO)algorithm is proposed.In this algorithm,the elite backward learning and adaptive t-distribution are intorduced on the basis of the standard sand cat swarm algorithm,the local search is optimized,and the Jaya algorithm is intergated.By testing four typical single-peak and multi-peak functions,it is proved that the algorithm has faster convergence speed and is prone to jumping out of local optima.The algorithm is applied into MPPT control,and the simulation results show that under static shading,the proposed method has less time to search for the maximum power point;under dynamic shading conditions,the average response time to rediscover the maximum power point is 0.2 s.The experiments show that the proposed algorithm can adapt to dynamically changing weather,can improve the convergence speed of traditional algorithms,and can prevent getting stuck in local optima.关键词
光伏阵列/最大功率点追踪/沙猫群优化算法/精英反向学习/自适应t分布/Jaya算法Key words
photovoltaic array/maximum power point tracking/sandcat swarm optimization algorithm/elite reverse learning/adaptive t-distribution/Jaya algorithm分类
信息技术与安全科学引用本文复制引用
付光杰,王柏松..基于改进SCSO算法的光伏MPPT研究[J].现代电子技术,2024,47(10):143-150,8.基金项目
海南省重点研发项目(ZDYF2022GXJS003) （ZDYF2022GXJS003）
