太赫兹科学与电子信息学报, 2020, 18 (3): 374, 网络出版: 2020-07-16
基于太赫兹技术的太阳能电池寿命预测算法
Solar cell lifetime prediction algorithm based on terahertz technology
太阳能电池 太赫兹光谱 粒子群优化 软退化模式 solar cell terahertz spectroscopy Particle Swarm Optimization soft failure mode
摘要
针对太阳能电池软退化模式下的寿命预测难度大,准确度不高等问题,提出一种先利用太赫兹光谱仪获取太阳能电池板光谱,再用基于布谷鸟算法改进的粒子群-支持向量机回归 (PSO-SVR)算法预测其剩余寿命的新 方法。利用紫外加速试验对预测结果进行验证对比,结果表明,该方法可用于预测不同损耗程度的太阳能电池的剩余寿命,在传统硅太阳能电池板和砷化镓太阳能电池的寿命预测上,相较于其他算法有更好的表现,其准确 度分别高达 98.92%和92.86%。
Abstract
Aiming for the low accuracy and difficulty of predicting solar cell life by using soft failure mode, a new method is proposed to obtain solar panel spectrum by using terahertz spectrometer. Based on the cuckoo algorithm, the study predicts the cell's remaining life by applying Particle Swarm Optimization-Support Vector Regression(PSO-SVR) algorithm and finally employs the ultraviolet acceleration test to verify the prediction results. It turns out that the method is applicable to predict the remaining life of solar cells with different levels of loss. Compared with other algorithms, the technique works better on the life prediction of traditional silicon solar panels and GaAs solar cells, and the accuracies are up to 98.92% and 92.86% respectively.
周兴, 朱希安, 王占刚. 基于太赫兹技术的太阳能电池寿命预测算法[J]. 太赫兹科学与电子信息学报, 2020, 18(3): 374. ZHOU Xing, ZHU Xi ’an, WANG Zhangang. Solar cell lifetime prediction algorithm based on terahertz technology[J]. Journal of terahertz science and electronic information technology, 2020, 18(3): 374.