计及积灰效应下环境应力量化的光伏组件寿命预测

张凌霄; 苏一帆; 胡博; 邵常政; 谢开贵; 吴涛

doi:10.19783/j.cnki.pspc.251390

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计及积灰效应下环境应力量化的光伏组件寿命预测

应用研究 | 更新时间：2026-07-27

- 计及积灰效应下环境应力量化的光伏组件寿命预测
- Lifetime prediction method for photovoltaic modules considering environmental stress quantification under dust accumulation effects
- 电力系统保护与控制 2026年54卷第13期
- 作者机构：
  
  输变电装备技术全国重点实验室 (重庆大学),重庆,400044
- 作者简介：
- 基金信息：
- DOI：10.19783/j.cnki.pspc.251390
  中图分类号：
- 纸质出版：2026
- 稿件说明：
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张凌霄, 苏一帆, 胡博, 等. 计及积灰效应下环境应力量化的光伏组件寿命预测[J]. 电力系统保护与控制, 2026,54(13).

ZHANG Lingxiao, SU Yifan, HU Bo, et al. Lifetime prediction method for photovoltaic modules considering environmental stress quantification under dust accumulation effects[J]. Power System Protection and Control, 2026, 54(13).
张凌霄, 苏一帆, 胡博, 等. 计及积灰效应下环境应力量化的光伏组件寿命预测[J]. 电力系统保护与控制, 2026,54(13). DOI： 10.19783/j.cnki.pspc.251390.

ZHANG Lingxiao, SU Yifan, HU Bo, et al. Lifetime prediction method for photovoltaic modules considering environmental stress quantification under dust accumulation effects[J]. Power System Protection and Control, 2026, 54(13). DOI： 10.19783/j.cnki.pspc.251390.

摘要

针对现有光伏组件寿命预测方法往往忽略积灰动态影响，难以准确评估多尘环境下组件可靠性的问题，提出一种计及积灰效应下环境应力量化的光伏组件寿命预测方法。首先，分析无尘状态下光伏组件热平衡模型，并提出计及积灰效应的光 - 电 - 热耦合模型及环境应力修正方法。其次，利用改进的自适应噪声完备集合经验模态分解法提取光伏退化趋势信号。然后，构建融合温度、湿度、紫外线辐射和热循环效应的改进环境应力累积损伤模型。通过求解参数估计问题，得到计及积灰效应的光伏组件寿命预测模型。最后，基于实际数据集进行验证，所提方法在 50% 训练样本下剩余使用寿命预测误差仅为 0.11 年，与传统方法相比预测精度提升了 9.23%，为干旱多尘地区光伏电站运维和清洗策略制定提供了理论依据和决策指导。

Abstract

Existing lifetime prediction methods for photovoltaic (PV) modules often neglect the dynamic effects of dust accumulation

making it difficult to accurately evaluate module reliability in dusty environments. To address this issue

this paper proposes a lifetime prediction method for PV modules incorporating quantified environmental stress under dust accumulation effects. First

the thermal equilibrium model of PV modules under dust-free conditions is analyzed

and a photo-electro-thermal coupled model and environmental stress correction method accounting for dust accumulation effects

is developed. Second

an improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) method is employed to extract PV degradation trends. Then

an enhanced environmental stress cumulative damage model integrating the effects of temperature

humidity

ultraviolet radiation

and thermal cycling is constructed. By solving the parameter estimation problem

a PV module lifetime prediction model considering dust accumulation effects is obtained. Finally

the proposed method is validated using real-world datasets. Under a 50% training sample ratio

the remaining useful life prediction error is only 0.11 years

representing a 9.23% improvement in prediction accuracy over conventional methods. The results provide a theoretical foundation and practical decision support for operation and maintenance strategies as well as cleaning schedules in PV power plants in arid and dusty regions.

关键词

Keywords

references

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