基于混沌自适应权重改进蛇优化算法的光伏电池参数提取
Parameter Extraction of Photovoltaic Cells Based on Chaotic Adaptive Weight Improved Snake Optimization Algorithm
朱洪林 1肖文波 2周恒 3李欣蕊1
作者信息
- 1. 南昌航空大学科技学院,江西 共青城 332020
- 2. 南昌航空大学科技学院,江西 共青城 332020;江西省光电检测技术工程实验室,江西 南昌 330063
- 3. 江西省光电检测技术工程实验室,江西 南昌 330063
- 折叠
摘要
针对光伏电池单二极管参数的提取中,蛇优化算法收敛速度慢、收敛精度低、易于陷入局部最优的问题,提出一种混沌自适应权重改进蛇优化算法.混沌的初始化以及自适应权重的设置可动态地改善算法在寻找食物、战斗、交配中的比例.通过对比不同光强和温度下理论与实验伏安数据,验证了改进算法的有效性.结果表明,相比于蛇优化算法,改进算法在收敛速度方面提高约219.7%,精度提高约58.40%,稳定性提高约49.57%.且发现光强对光生电流的影响比温度大,温度对反向饱和电流、串联电阻、并联电阻、理想因子的影响比光强大.
Abstract
A chaotic adaptive weight improved snake optimization algorithm is proposed to solve the issues of slow convergence speed,low convergence accuracy,and susceptibility to local optima in the snake optimization algorithm of single model parameter extraction of photovoltaic cells.The initialization of chaos and the setting of adaptive weights will dynamically better allocate the proportion of search of food,combat,and mating in snake algorithm.By comparing theoretical and experimental voltametric data under different light intensities and temperatures,the improved algorithm is verified.Compared to snake optimization algorithm,the results show that the improved algorithm improves convergence speed by about 219.7%,accuracy by about 58.40%,and stability by about 49.57%.Finally,the influence of light intensity on photogenerated current is found to be greater than that of temperature,and the influence of temperature on reverse saturation current,series resistance,parallel resistance,and ideal factor is greater than that of light intensity.
关键词
光伏电池/单二极管模型/蛇优化算法/混沌自适应权重/参数提取Key words
photovoltaic cells/single diode photovoltaic model/snake optimization algorithm/chaotic adaptive weighting/parameter extraction引用本文复制引用
基金项目
国家自然科学基金(12064027)
江西省教育厅科技项目(GJJ2204302)
江西省高层次高技能领军人才培养工程入选(2022-63号)
九江市市级科技计划项目(S2022KXJJ001)
九江市市级科技计划项目(S2022QNZZ070)
出版年
2024
NETL
NSTL
万方数据