局部阴影遮挡下光伏系统最大功率点跟踪算法  

Maximum Power Point Tracking Algorithm for Photovoltaic Systems Under Local Shadow Occlusion

作　　者：程相奥 王霆 王菁菁 苗驰壮 Cheng Xiangao;Wang Ting;Wang Jingjing;Miao Chizhuang(Pinggao Group Co.,Ltd.,Pingdingshan,China)

机构地区：[1]平高集团有限公司,河南平顶山

出　　处：《科学技术创新》2025年第6期173-176,共4页Scientific and Technological Innovation

摘　　要：探究了局部阴影遮挡下光伏系统最大功率点跟踪算法,并对比算法的应用效果。传统的扰动观测法、全局扫描法等存在跟踪精度差、仅适用于无遮挡条件等弊端。粒子群算法可以满足局部阴影遮挡下最大功率点跟踪需求,但是无法兼顾寻优速度和寻优精度,尤其是当粒子数量多且集中分布时收敛速度变的非常慢。改进的量子粒子群算法由于粒子初始位置完全随机且均匀分布,实现了全局寻优,保证寻优结果就是光伏系统的最大功率点,具有跟踪精度更高、寻优速度更快的优点。This paper explores the maximum power point tracking algorithm for photovoltaic systems under local shadow occlusion,and compares the application effects of the algorithm.Traditional perturbation observation methods,global scanning methods,etc.have drawbacks such as poor tracking accuracy and are only suitable for unobstructed conditions.The particle swarm algorithm can meet the requirement of maximum power point tracking under local shadow occlusion,but it cannot balance the optimization speed and accuracy,especially when the number of particles is large and concentrated,the convergence speed becomes very slow.The improved quantum particle swarm algorithm achieves global optimization due to the completely random and uniform distribution of particle initial positions,ensuring that the optimization result is the maximum power point of the photovoltaic system.It has the advantages of higher tracking accuracy and faster optimization speed.

关 键 词：光伏系统 最大功率点跟踪 粒子群算法 量子粒子群算法 

分 类 号：TM615[电气工程—电力系统及自动化]