Parameter identification of solar cell model based on RCJAYA algorithm

被引：0

作者：

Ouyang, Chengtian ^{[1
]}

Huang, Zuwei ^{[1
]}

Liu, Yujia ^{[2
]}

Zhang, Lin ^{[3
]}

Zhu, Donglin ^{[4
]}

Zhou, Changjun ^{[4
]}

机构：

[1] School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou

[2] School of Artificial Intelligence, Jiangxi Institute of Applied Science and Technology, Nanchang

[3] School of Software Engineering, Jiangxi University of Science and Technology, Nanchang

[4] School of Computer Science and Technology, Zhejiang Normal University, Jinhua

来源：

Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2024年 / 50卷 / 07期

基金：

中国国家自然科学基金;

关键词：

chaotic perturbation; JAYA algorithm; parameter identification; ranking probability; solar cell;

D O I：

10.13700/j.bh.1001-5965.2022.0576

中图分类号：

学科分类号：

摘要：

A JAYA algorithm based on the ranking probability quantization mechanism and chaotic perturbation (RCJAYA) is proposed as a discrimination approach to increase the precision and accuracy of the intelligent optimization algorithm to detect solar cell parameters.The RCJAYA algorithm selects different ways to update individuals according to the ranking probability to balance the local and global search ability and maintain the population diversity; chaotic perturbation is applied to the optimal individuals to discover a better solution. The replacement strategy is used to update the stagnant individuals and improve the performance of the algorithm. When compared to the five algorithms such as JAYA, the root mean square error of the current of the single and double diodes of solar cells achieved by the RCJAYA algorithm is 9.860 2×10−4 A and 9.825 8×10−4 A, respectively. The results show that the RCJAYA algorithm has more advantages. The simulated current is calculated according to the identification results compared with the measured current, and the average error is 0.000 84 A and 0.000 82 A for single and double diodes, respectively, which indicates that the parameter values identified by RCJAYA are accurate and reliable. © 2024 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.

引用

页码：2133 / 2140

页数：7

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