网络首发:2026-05-08,
纸质出版:2026
移动端阅览
陈瀚宇, 李智华, 汪飞, 等. 一种光伏组件健康状况的动态评估方法[J]. 太阳能学报, 2026,47(4):719-728.
陈瀚宇, 李智华, 汪飞, et al. 一种光伏组件健康状况的动态评估方法[J]. 2026, 47(4): 719-728.
陈瀚宇, 李智华, 汪飞, 等. 一种光伏组件健康状况的动态评估方法[J]. 太阳能学报, 2026,47(4):719-728. DOI: doi:10.19912/j.0254-0096.tynxb.2024-2237.
陈瀚宇, 李智华, 汪飞, et al. 一种光伏组件健康状况的动态评估方法[J]. 2026, 47(4): 719-728. DOI: doi:10.19912/j.0254-0096.tynxb.2024-2237.
针对光伏组件健康状态的评估问题
提出一种基于健康指标动态阈值选取和动态权重调整机制的评估方法。将组件光生电流Iph、等效串联电阻Rs和等效并联电阻Rp作为健康参数
基于组件I-V曲线、利用蜣螂算法进行健康参数辨识。结合组件出厂标准和服役年限
建立光伏组件动态健康模型。引入动态权重调整机制
确保准确识别低权重参数表征的故障。仿真和实验结果证明
所提出的方法能够较好地评估光伏组件的健康状况
并对静态权重方法下评估错误的故障信息进行有效诊断。
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 current
equivalent series resistance
and equivalent parallel resistance 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.
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.
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.
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.
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.
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.
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.
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.
HUANG C, WANG L.Simulation study on the degradation process of photovoltaic modules[J]. Energy conversion and management, 2018, 165: 236-243.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
0
浏览量
18
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621