遮荫条件下光伏发电最大功率的智能跟踪方法综述  

Review of Maximum Power Tracking Methods for Photovoltaic Power Generation Under Shading Conditions

作　　者：叶国敏 肖文波 李军华[1] 金鑫 夏情感 吴华明 姜迪友[2] YE Guo-min;XIAO Wen-bo;LI Jun-hua;JIN Xin;XIA Qing-gan;WU Hua-ming;JIANG Di-you(Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition,Nanchang Hangkong University,Nanchang 330063,China;Key Laboratory of Nondestructive Testing(Ministry of Education),Nanchang Hangkong University,Nanchang 330063,China;Jiangxi Engineering Laboratory for Optoelectronics Testing Technology,Nanchang Hangkong University,Nanchang 330063,China)

机构地区：[1]南昌航空大学江西省图像处理与模式识别重点实验室,南昌330063 [2]南昌航空大学无损检测技术教育部重点实验室,南昌330063 [3]江西省光电检测技术工程实验室,南昌330063

出　　处：《南昌航空大学学报（自然科学版）》2020年第2期36-44,共9页Journal of Nanchang Hangkong University(Natural Sciences)

基　　金：航空科学基金(2017ZC56003);江西省图像处理与模式识别重点实验室开放基金(ET201908119);江西省优势科技创新团队项目(20181BCB24008);无损检测技术教育部重点实验室开放基金(EW201908442,EW201980090);研究生创新基金(YC2019-S348)。

摘　　要：局部遮荫条件下光伏发电将会产生多峰值输出功率,可能导致最大功率点跟踪失效从而造成能量损失。本文对两类最大功率智能跟踪方法进行归纳和评述,第一类方法是传统的控制算法,如粒子群算法等;第二类方法是混合算法,如粒子群和电导增量混合算法等。结果表明:尽管第一类方法能对光伏发电中复杂的非线性、多峰值功率进行寻优,但收敛时间较长和收敛精度不够高;第二类方法可以扬长避短,有效地发挥各算法的优点,提高搜索性能;如粒子群与电导增量混合算法,在0.25 s附近跟踪到最大功率点,其精度达到98.2%;电导增量法在0.29 s附近跟踪到最大功率点,其精度仅为88.5%;而粒子群算法在0.27 s跟踪到最大功率点,其精度仅为95.9%。该综述对未来全局最大功率点跟踪技术的发展提供了指导。Photovoltaic power generation will produce multi-peak output power under partial shading conditions,which may lead to maximum power point tracking failure and power loss.In this paper,two kinds of maximum power intelligent tracking theory are summarized.The first type of method are the traditional general control algorithm,such as particle swarm optimization,and the second are the hybrid methods,such as particle swarm and conductance incremental hybrid algorithm.The results show that,although the first type of theory can optimize the complex nonlinear and multi-peak power in photovoltaic power generation,the convergence time is longer,and the convergence precision is not high enough.The hybrid methods can effectively develop its strengths and avoid its weaknesses,and greatly improve search performance.For example,the hybrid algorithm of particle swarm optimization and conductance increment can track to the maximum power point around 0.25 s with an accuracy of 98.2%,while the incremental conductance method only track to the maximum power point near 0.29 s with an accuracy of 88.5%,and the particle swarm algorithm only track to the maximum power point at 0.27 s with an accuracy of 95.9%.These review provide guidance for the development of global maximum power point tracking technology in the future.

关 键 词：光伏发电 局部遮荫 最大功率 智能跟踪方法 混合算法 

分 类 号：U458[建筑科学—桥梁与隧道工程]