光伏组件寿命衰退建模与寿命预测高斯随机过程回归方法研究

唐圣学; 宋晓; 李明; 姚帅亮; 陈丽; 孙志国

doi:10.19912/j.0254-0096.tynxb.2021-0687

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太阳能学报 ›› 2022, Vol. 43 ›› Issue (12) : 41-49. DOI: 10.19912/j.0254-0096.tynxb.2021-0687

光伏组件寿命衰退建模与寿命预测高斯随机过程回归方法研究

唐圣学^1,2, 宋晓^1,2, 李明³, 姚帅亮³, 陈丽^1,2, 孙志国^1,2

作者信息 +

RESEARCH ON LIFETIME DEGRADATION MODELING AND GAUSSIAN STOCHASTIC PROCESS REGRESSION METHOD FOR LIFE PREDICTION OF PHOTOVOLTAIC MODULES

Tang Shengxue^1,2, Song Xiao^1,2, Li Ming³, Yao Shuailiang³, Chen Li^1,2, Sun Zhiguo^1,2

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文章历史 +

摘要

服役中光伏组件受到内部老化及外界环境影响,组件寿命衰减过程呈高度的非线性、随机性。针对光伏组件衰退机理及其过程,分析光伏组件衰退过程、衰退因子及其对光伏组串电池组件特性的影响,提出基于指数衰减的太阳电池衰退电路模型,并利用退化模型定量分析衰退因子对寿命预测指标输出功率的影响;进而,选取等效串联电阻和输出功率作为光伏组件寿命预测指标,提出综合输出功率和等效串联电阻的联合高斯随机过程寿命预测方法,并分析核函数和数据特性对寿命预测的影响。仿真与实例验证表明：所提寿命预测模型具有精度高、鲁棒性强的优点。

Abstract

The degradation process of photovoltaic（PV） lifetime with service time is highly nonlinear and random due to internal aging and external environment. Aiming at the degradation mechanism and process of PV modules, this paper analyzes the degradation process of PV modules, the degradation factors and their effects on the characteristics of PV modules, and proposes a degradation circuit model of PV cell based on exponential degradation. The degradation model is used to quantitatively analyze the influence of degradation factors on the output power. Then, the equivalent series resistance and output power are selected as the life prediction indicators, and a joint Gaussian process life prediction method based on output power and equivalent series resistance is proposed, and the influence of kernel function on life prediction is analyzed. Finally, Simulation and verifications show that the proposed life prediction model has the advantages of high accuracy and strong robustness.

导出引用

唐圣学, 宋晓, 李明, 姚帅亮, 陈丽, 孙志国. 光伏组件寿命衰退建模与寿命预测高斯随机过程回归方法研究[J]. 太阳能学报. 2022, 43(12): 41-49 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0687

Tang Shengxue, Song Xiao, Li Ming, Yao Shuailiang, Chen Li, Sun Zhiguo. RESEARCH ON LIFETIME DEGRADATION MODELING AND GAUSSIAN STOCHASTIC PROCESS REGRESSION METHOD FOR LIFE PREDICTION OF PHOTOVOLTAIC MODULES[J]. Acta Energiae Solaris Sinica. 2022, 43(12): 41-49 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0687

中图分类号： TK513.5

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