Photovoltaic array multiple fault diagnosis method based on improved deep Q-network

doi:10.3969/j.issn.1000-1565.2026.05.005

Journal of Hebei University(Natural Science Edition) ›› 2026, Vol. 46 ›› Issue (5): 495-505.DOI: 10.3969/j.issn.1000-1565.2026.05.005

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Photovoltaic array multiple fault diagnosis method based on improved deep Q-network

CHEN Jiahui¹,FAN Binbin²,ZHANG Guanghui¹,WANG Shuang¹,ZHANG Limei¹

1. College of Information Science and Technology, Hebei Agricultural University, Baoding 071000, China; 2. International College, Hebei University, Baoding 071002, China

Received:2026-02-07 Online:2026-09-25 Published:2026-09-15

Abstract

CLC Number:

TK513.5

CHEN Jiahui, FAN Binbin, ZHANG Guanghui, WANG Shuang, ZHANG Limei. Photovoltaic array multiple fault diagnosis method based on improved deep Q-network[J]. Journal of Hebei University(Natural Science Edition), 2026, 46(5): 495-505.

References

[1] 王小宇,刘波,孙凯,等.光伏阵列故障诊断技术综述[J].电工技术学报, 2024, 39(20): 6526-6543. DOI:10.19595/j.cnki.1000-6753.tces.231327.
[2] 赵智强,帕孜来·马合木提,刘行行,等.光伏逆变器IGBT器件接线故障诊断方法[J].河北大学学报(自然科学版), 2024, 44(1): 17-26. DOI:10.3969/j.issn.1000-1565.2024.01.003.
[3] 白牧可,钱志研,段祥骏,等.基于进化算法和长短期记忆网络的光伏阵列多类型复合故障诊断方法[J].太阳能学报, 2026, 47(3): 625-634. DOI:10.19912/j.0254-0096.tynxb.2024-1927.
[4] Phan B C, Lai Y C, Lin C E. A deep reinforcement learning-based MPPT control for PV systems under partial shading condition[J]. Sensors, 2020, 20(11): 3039. DOI:10.3390/s20113039.
[5] 彭自然,许怀顺,肖伸平,等.基于HPO-CatBoost的光伏阵列故障诊断模型[J].太阳能学报, 2025, 46(7): 663-673. DOI:10.19912/j.0254-0096.tynxb.2024-0409.
[6] 张思佳,魏业文,白广华,等.基于mRMR特征选择和PO-LightGBM的光伏阵列故障诊断[J/OL].电源学报, 2025-05-14. https://link.cnki.net/urlid/12.1420.tm.20250513.1839.006.
[7] 赵靖英,吴晶晶,张雪辉,等.基于萤火虫扰动麻雀搜索算法-极限学习机的光伏阵列故障诊断方法研究[J].电网技术, 2023, 47(4): 1612-1625. DOI:10.13335/j.1000-3673.pst.2022.1165.
[8] 顾崇寅,徐潇源,王梦圆,等.基于CatBoost算法的光伏阵列故障诊断方法[J].电力系统自动化, 2023, 47(2): 105-114.DOI: 10.7500/AEPS20211123004.
[9] Amiri A F, Oudira H, Chouder A, et al. Faults detection and diagnosis of PV systems based on machine learning approach using random forest classifier[J]. Energy Convers Manag, 2024, 301: 118076. DOI:10.1016/j.enconman.2024.118076.
[10] 昌千琳,罗永捷,王强钢,等.基于I-V曲线全局特征提取的光伏组串Swin-Transformer故障诊断方法[J].电工技术学报, 2025, 40(23): 7664-7676. DOI:10.19595/j.cnki.1000-6753.tces.242073.
[11] 张子洵,魏业文,张轲钦,等.基于ICOA-XGBoost的光伏阵列复合故障诊断研究[J].太阳能学报, 2025, 46(5): 251-259. DOI:10.19912/j.0254-0096.tynxb.2024-0019.
[12] 史洪岩,彭云喆.基于Transformer-BiLSTM并行网络的光伏阵列复合故障诊断[J/OL].电源学报, 2025-06-18. https://link.cnki.net/urlid/12.1420.tm.20250617.1557.011.
[13] Ding Y, Ma L, Ma J, et al. Intelligent fault diagnosis for rotating machinery using deep Q-network based health state classification: a deep reinforcement learning approach[J]. Adv Eng Inform, 2019, 42: 100977. DOI:10.1016/j.aei.2019.100977.
[14] AlMahamid F, Grolinger K. Reinforcement learning algorithms: an overview and classification[C] //2021 IEEE Canadian Conference on Electrical and Computer Engineering(CCECE). September 12-17, 2021. ON, Canada. IEEE, 2021: 1-7. DOI:10.1109/ccece53047.2021.9569056.
[15] Lin E L, Chen Q, Qi X M. Deep reinforcement learning for imbalanced classification[J]. Appl Intell, 2020, 50(8): 2488-2502. DOI:10.1007/s10489-020-01637-z.
[16] 王元章,李智华,吴春华.一种四参数的光伏组件在线故障诊断方法[J].中国电机工程学报, 2014, 34(13): 2078-2087. DOI:10.13334/j.0258-8013.pcsee.2014.13.009.
[17] Mnih V, Kavukcuoglu K, Silver D, et al. Human-level control through deep reinforcement learning[J]. Nature, 2015, 518(7540): 529-533. DOI:10.1038/nature14236.
[18] Barron E N, Ishii H. The Bellman equation for minimizing the maximum cost[J]. Nonlinear Anal Theory Meth Appl, 1989, 13(9): 1067-1090. DOI:10.1016/0362-546X(89)90096-5.
[19] 罗凯元,刘光宇,毛嘉铭.基于改进BiLSTM模型的光伏阵列故障诊断[J].电源学报, 2026, 24(5): 239-247. DOI:10.13234/j.issn.2095-2805.2026.5.239.
[20] 黄雄峰,段熙尧,黄明,等.基于数据驱动的换流阀用IGBT模块芯片焊料层状态评估[J].河北大学学报(自然科学版), 2025, 45(1): 10-19. DOI:10.3969/j.issn.1000-1565.2025.01.002.
[21] Schaul T, Quan J, Antonoglou I, et al. Prioritized experience replay[J]. Computer Science, 2015. DOI:10.48550/arXiv.1511.05952.
[22] Espíndola R P, Ebecken N F F. On extending F-measure and G-mean metrics to multi-class problems[C] //WIT Transactions on Information and Communication Technologies. May 4-6, 2005. Skiathos, Greece. WIT Press, 2005: 25-34. DOI:10.2495/data050031.

Photovoltaic array multiple fault diagnosis method based on improved deep Q-network

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