A DYNAMIC ASSESSMENT METHOD FOR HEALTH STATUS OF PHOTOVOLTAIC MODULES

Chen Hanyu; Li Zhihua; Wang Fei; Yi Yuan; Wu Nan

doi:10.19912/j.0254-0096.tynxb.2024-2237

PDF(2300 KB)

Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (4) : 719-728. DOI: 10.19912/j.0254-0096.tynxb.2024-2237

A DYNAMIC ASSESSMENT METHOD FOR HEALTH STATUS OF PHOTOVOLTAIC MODULES

Chen Hanyu, Li Zhihua, Wang Fei, Yi Yuan, Wu Nan

Author information +

History +

Abstract

To address the need of state estimation for photovoltaic （PV） module health, a method based on dynamic threshold selection and dynamic weight adjustment mechanism for health indicators is proposed. The photogenerated currentI_ph, equivalent series resistanceR_s, and equivalent parallel resistance R_p are taken as health parameters, and they are extracted using the dung beetle algorithm based on the I-V curve of the module. A dynamic health model is developed by integrating factory standards and operational aging effects. A dynamic weight adjustment mechanism is introduced to ensure accurate identification of faults characterized by low-weight parameters. Simulations and experiments confirm that the proposed method improves state estimation reliability compared to static weight approaches, enabling precise identification of misdiagnosed faults.

Key words

photovoltaic modules / parameter extraction / state estimation / performance degradation / dynamic health model / dung beetle identification algorithm

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Chen Hanyu, Li Zhihua, Wang Fei, Yi Yuan, Wu Nan. A DYNAMIC ASSESSMENT METHOD FOR HEALTH STATUS OF PHOTOVOLTAIC MODULES[J]. Acta Energiae Solaris Sinica. 2026, 47(4): 719-728 https://doi.org/10.19912/j.0254-0096.tynxb.2024-2237

References

[1] TIAN J, CULLEY S A, MAIER H R, et al.Is renewable energy sustainable? Potential relationships between renewable energy production and the Sustainable Development Goals[J]. NPJ climate action, 2024, 3: 35.
[2] AGHAEI M, FAIRBROTHER A, GOK A, et al.Review of degradation and failure phenomena in photovoltaic modules[J]. Renewable and sustainable energy reviews, 2022, 159: 112160.
[3] PIERDICCA R, PAOLANTI M, FELICETTI A, et al.Automatic faults detection of photovoltaic farms: solAIr, a deep learning-based system for thermal images[J]. Energies, 2020, 13(24): 6496.
[4] PRATT L, GOVENDER D, KLEIN R.Defect detection and quantification in electroluminescence images of solar PV modules using U-Net semantic segmentation[J]. Renewable energy, 2021, 178: 1211-1222.
[5] 匡兴泽. 基于机器视觉的太阳能电池片缺陷检测算法研究[D]. 武汉: 武汉理工大学, 2016.
KUANG X Z.The algorithm research of defects detection for solar cells base on machine vision[D]. Wuhan: Wuhan University of Technology, 2016.
[6] 张臻, 王磊, 秦志光, 等. 双面光伏组件发电性能影响因素理论与实验研究[J]. 太阳能学报, 2022, 43(3): 171-179.
ZHANG Z, WANG L, QIN Z G, et al.Theoretical and experimental study on influencing factors of bifacial photovoltaic modules field performance[J]. Acta energiae solaris sinica, 2022, 43(3): 171-179.
[7] JORDAN D C, DELINE C, KURTZ S R, et al.Robust PV degradation methodology and application[J]. IEEE journal of photovoltaics, 2018, 8(2): 525-531.
[8] HUANG C, WANG L.Simulation study on the degradation process of photovoltaic modules[J]. Energy conversion and management, 2018, 165: 236-243.
[9] 赵丽琴, 刘昶, 易发胜. 基于动态权重的设备健康状态评估方法[J]. 计算机系统应用, 2020, 29(9): 198-204.
ZHAO L Q, LIU C, YI F S.Assessment method of equipment health state based on dynamic weight[J]. Computer systems & applications, 2020, 29(9): 198-204.
[10] 苏建徽, 余世杰, 赵为, 等. 硅太阳电池工程用数学模型[J]. 太阳能学报, 2001, 22(4): 409-412.
SU J H, YU S J, ZHAO W, et al.Investigation on engineering analytical model of silicon solar cells[J]. Acta energiae solaris sinica, 2001, 22(4): 409-412.
[11] COLVIN D J, IQBAL N, YERGER J H, et al.Degradation of monocrystalline silicon photovoltaic modules from a 10-year-old rooftop system in Florida[J]. IEEE journal of photovoltaics, 2023, 13(2): 275-282.
[12] 李智华, 马浩强, 吴春华, 等. 基于三参数的光伏组件老化程度诊断[J]. 中国电机工程学报, 2022, 42(9): 3327-3338.
LI Z H, MA H Q, WU C H, et al.Diagnosing the aging degree of photovoltaic modules based on three parameters[J]. Proceedings of the CSEE, 2022, 42(9): 3327-3338.
[13] YANG B, WANG J B, ZHANG X S, et al.Comprehensive overview of meta-heuristic algorithm applications on PV cell parameter identification[J]. Energy conversion and management, 2020, 208: 112595.
[14] 韩伟, 王宏华, 陈凌, 等. 光伏组件参数拟合及输出特性研究[J]. 电力自动化设备, 2015, 35(9): 100-107.
HAN W, WANG H H, CHEN L, et al.Research on parameter fitting and output characteristics of PV module[J]. Electric power automation equipment, 2015, 35(9): 100-107.
[15] XUE J K, SHEN B.Dung beetle optimizer: a new meta-heuristic algorithm for global optimization[J]. The journal of supercomputing, 2023, 79(7): 7305-7336.
[16] DE SOTO W, KLEIN S A, BECKMAN W A.Improvement and validation of a model for photovoltaic array performance[J]. Solar energy, 2006, 80(1): 78-88.
[17] 李智华, 张宇浩, 吴春华, 等. 基于动态指标的光伏组件健康程度诊断[J]. 电网技术, 2024, 48(2): 597-606.
LI Z H, ZHANG Y H, WU C H, et al.Health diagnosis of photovoltaic modules based on dynamic health criteria[J]. Power system technology, 2024, 48(2): 597-606.
[18] 中华人民共和国工业和信息化部. 光伏制造行业规范条件(2015年本)[EB/OL]. http://www.miit.gov.cn/zwgk/zcwj/wjfb/gg/art.
MINISTRY OF INDUSTRY AND INFORMATION TECHNOLOGY. Industry specifications of photovoltaic manufacturing(2015)[EB/OL]. http://www.miit.gov.cn/zwgk/zcwj/wjfb/gg/art.
[19] 中华人民共和国工业和信息化部. 光伏制造行业规范条件(2018年本)[EB/OL]. https://wap.miit.gov.cn/zwgk/zcwj/wjfb/gg/art.
MINISTRY OF INDUSTRY AND INFORMATION TECHNOLOGY. Industry specifications of photovoltaic manufacturing(2018)[EB/OL]. https://wap.miit.gov.cn/zwgk/zcwj/wjfb/gg/art.
[20] 中华人民共和国工业和信息化部. 光伏制造行业规范条件(2021年本)[EB/OL]. https://wap.miit.gov.cn/zwgk/zcwj/wjfb/gg/art/2021/art_24b585fce0f64c98be8efe14e0446458.html.
MINISTRY OF INDUSTRY AND INFORMATION TECHNOLOGY. Industry specifications of photovoltaic manufacturing(2021)[EB/OL]. https://wap.miit.gov.cn/zwgk/zcwj/wjfb/gg/art.
[21] 中华人民共和国工业和信息化部. 光伏制造行业规范条件(2024年本)(征求意见稿)[EB/OL]. https://www.miit.gov.cn/jgsj/dzs/gzdt/art.
MINISTRY OF INDUSTRY AND INFORMATION TECHNOLOGY. Industry specifications of photovoltaic manufacturing(2024, Draft for opinions)[EB/OL]. https://www.miit.gov.cn/jgsj/dzs/gzdt/art.
[22] LILLO-SÁNCHEZ L, LÓPEZ-LARA G, VERA-MEDINA J, et al. Degradation analysis of photovoltaic modules after operating for 22 years. A case study with comparisons[J]. Solar energy, 2021, 222: 84-94.
[23] 吴春华, 易苑, 李智华, 等. 考虑参数权重与分层映射的光伏组件健康程度检测[J]. 电工技术学报, 2024, 39(15): 4856-4867.
WU C H, YI Y, LI Z H, et al.Health detection of photovoltaic modules considering parameter weights and hierarchical mapping[J]. Transactions of China Electrotechnical Society, 2024, 39(15): 4856-4867.
[24] 彭炎亮, 李汪根, 刘娇, 等. 基于动态权重和模糊综合评判法的健康评估模型[J]. 计算机系统应用, 2017, 26(1): 37-43.
PENG Y L, LI W G, LIU J, et al.Health assessment model based on dynamic weight and fuzzy comprehensive evaluation method[J]. Computer systems & applications, 2017, 26(1): 37-43.
[25] 丁坤, 刘振飞, 高列, 等. 基于主成分分析和马氏距离的光伏系统健康状态研究[J]. 可再生能源, 2017, 35(1): 1-7.
DING K, LIU Z F, GAO L, et al.Research on photovoltaic system health state based on PCA-MD method[J]. Renewable energy resources, 2017, 35(1): 1-7.
[26] 张治, 王新宇, 王林. 基于麻雀搜索算法的光伏阵列参数辨识[J]. 电气传动, 2022, 52(13): 75-80.
ZHANG Z, WANG X Y, WANG L.Photovoltaic array parameter identification based on sparrow search algorithm[J]. Electric drive, 2022, 52(13): 75-80.
[27] 吴春华, 俞薛颖, 李智华, 等. 基于FCM与高斯隶属度的光伏组件健康状态诊断[J]. 电网技术, 2022, 46(5): 1887-1896.
WU C H, YU X Y, LI Z H, et al.Health state diagnosis of photovoltaic modules based on FCM and Gaussian membership[J]. Power system technology, 2022, 46(5): 1887-1896.