摘要
在局部阴影条件下光伏阵列的功率输出曲线呈现多峰特性,这时常规算法将不能跟踪到阵列的全局最大功率点。因此,本文提出一种基于蚁群算法跟踪全局最大功率点的方法,算法利用蚂蚁爬行十进制数的每位来生成系统的给定电压,根据实测功率值来调整路径的信息素,使蚂蚁逐渐集中在最优的给定电压路径附近,最终实现光伏阵列的全局最大功率点跟踪。通过Simulink搭建光伏阵列仿真模型,结果表明,在环境发生变化时,蚁群算法可以快速准确地跟踪到具有多峰输出特性的光伏阵列的全局最大功率点,提高了光伏阵列在复杂环境下的输出功率。
As photovohaic （PV） array＇ s power output curves show multi-peak characteristic under partially shaded con- ditions, traditional algorithms cannot track the global maximum power point of the array. Therefore, a method based on ant colony optimization （ACO）algorithm is proposed in this paper to track the global maximum power point. The algo- rithm generates the set voltage of PV system by making the ant crawl each decimal digit, and adjusts path pheromones according to measured power to aggregate the ants near the path of optimal set voltage after iteration. Finally, maximum power point tracking （MPPT）is realized. The simulation model of PV array is built in Simulink. The results show that the ACO algorithm can accurately and quickly achieve the global MPPT of PV arrays when the environment changes, which improves the power output efficiency of the PV array.
作者
万晓凤
胡伟
余运俊
胡海林
WAN Xiaofeng HU Wei YU Yunjun HU Hailin(College of Information Engineering, Nanchang University, Nanchang 330031, China)
出处
《电力系统及其自动化学报》
CSCD
北大核心
2016年第12期70-76,共7页
Proceedings of the CSU-EPSA
基金
国家国际科技合作专项资助项目(2014DFG72240)
江西省科技支撑计划资助项目(2013BBE50102)
江西省科技落地计划资助项目(KJLD14006)
关键词
光伏阵列
多峰特性
蚁群优化算法
最大功率点跟踪
photovohaic array
multi-peak characteristic
ant colony optimization algorithm
maximum power point track-ing（MPPT）
