河北建筑工程学院学报2024,Vol.42Issue(1) :171-178.DOI:10.3969/j.issn.1008-4185.2024.01.028

基于改进天鹰算法的光伏MPPT控制研究

Research on MPPT Control Based on Improved Aquila Optimization Algorithm

朱恒 秦景 张语智 陈晓飞 张学泽
河北建筑工程学院学报2024,Vol.42Issue(1) :171-178.DOI:10.3969/j.issn.1008-4185.2024.01.028

基于改进天鹰算法的光伏MPPT控制研究

Research on MPPT Control Based on Improved Aquila Optimization Algorithm

朱恒 1秦景 1张语智 1陈晓飞 1张学泽1
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作者信息

  • 1. 河北建筑工程学院,河北张家口 075000
  • 折叠

摘要

由于光伏阵列的不确定性和间歇性,在局部阴影条件下光伏系统的输出存在多个峰值,传统的最大功率跟踪法(MPPT)不能有效跟踪最大功率点,对于这个问题提出一种基于Intermittency混沌映射的天鹰算法(IAO).通过引入混沌映射改进初始化种群,将占空比作为控制变量,实现MPPT控制.最后仿真模拟结果表明,和原始算法相比改进天鹰算法在MPPT应用的基础上收敛速度、收敛精度都有显著提升,提高了发电效率.

Abstract

Due to the uncertainty and intermittency of photovoltaic arrays,there are multiple peaks in the output of photovoltaic systems under local shadow conditions.The traditional Maximum Pow-er Tracking(MPPT)method cannot effectively track the maximum power point problem.To ad-dress this issue,a Sky Eagle Algorithm(IAO)based on Intermittency Chaos Mapping is proposed.By introducing chaotic mapping to improve the initialization population,the duty cycle is used as the control variable to achieve MPPT control.The final simulation shows that compared with the original algorithm,the improved Tianying algorithm significantly improves the convergence speed and accuracy on the basis of MPPT application,and improves the power generation efficiency.

关键词

光伏系统/MPPT/混沌映射/天鹰算法

Key words

Photovoltaic system/MPPT/chaotic mapping/Aquila Optimization Algorithm

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出版年

2024
河北建筑工程学院学报
河北建筑工程学院

河北建筑工程学院学报

影响因子:0.502
ISSN:1008-4185
参考文献量12
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