EARLY INSULATION FAULT IDENTIFICATION AND LOCATION OF DC TRANSMISSION LINES IN PHOTOVOLTAIC POWER STATIONS

Wang Xiaodong, Zhang Hao, Guo Haiyu, Gao Xing

Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (8) : 246-252.

PDF(2524 KB)
Welcome to visit Acta Energiae Solaris Sinica, Today is
PDF(2524 KB)
Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (8) : 246-252. DOI: 10.19912/j.0254-0096.tynxb.2022-0527

EARLY INSULATION FAULT IDENTIFICATION AND LOCATION OF DC TRANSMISSION LINES IN PHOTOVOLTAIC POWER STATIONS

  • Wang Xiaodong, Zhang Hao, Guo Haiyu, Gao Xing
Author information +
History +

Abstract

When an early insulation fault occurs in a DC transmission line, the current fluctuation is small and the fault phenomenon is not obvious, so it is difficult to quickly identify and take protective measures. The topology of the photovoltaic power station line is complex, and it is difficult to accurately locate the fault location. In this paper, a method combining continuous wavelet transform and hybrid neural network model is proposed to identify and locate faults in the shortest possible time. The method first uses continuous wavelet transform to extract two-dimensional time-frequency matrix features from the transient zero-mode current signal, compresses it into a color image, and then sends the image to a neural network model for training. This hybrid neural network model improves recognition accuracy and reduces training time by combining convolutional neural networks and gated recurrent units. Finally, in order to verify the advantages of this method, four HVDC transmission lines are selected in a high noise environment to carry out four time-frequency analysis methods and three neural network model simulation comparisons, and then a separate simulation test is carried out to identify early insulation faults. The results show that this method can effectively identify the early insulation fault and locate the line where it occurs, and has strong anti-noise ability.

Key words

PV power station / insulation / wavelet transform / DC transmission / neural network model / electric fault location

Cite this article

Download Citations
Wang Xiaodong, Zhang Hao, Guo Haiyu, Gao Xing. EARLY INSULATION FAULT IDENTIFICATION AND LOCATION OF DC TRANSMISSION LINES IN PHOTOVOLTAIC POWER STATIONS[J]. Acta Energiae Solaris Sinica. 2023, 44(8): 246-252 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0527

References

[1] 吴春华, 胡雅, 李智华, 等. 基于SSTDR的光伏系统直流母线电弧故障在线检测与定位[J]. 中国电机工程学报, 2020, 40(8): 2725-2735.
WU C H, HU Y, LI Z H, et al.On-line detection and location of DC bus arc faults in PV systems based on SSTDR[J]. Proceedings of the CSEE, 2020, 40(8): 2725-2735.
[2] 权文杰, 童晓阳, 张广骁. 基于S变换行波能谱矩阵相似度的柔性直流单端保护方案[J]. 电力系统自动化, 2022, 46(7): 178-186.
QUAN W J, TONG X Y, ZHANG G X.Single-end flexible DC protection scheme based on similarity of S-transform energy spectrum matrix of traveling wave[J]. Automation of electric power systems, 2022, 46(7): 178-186.
[3] 陈田田, 李银红. 基于电压折射波幅值正负差异的柔性直流电网两段式行波保护[J]. 电力系统自动化, 2022, 46(3): 129-136.
CHEN T T, LI Y H.Two-section traveling wave protection for flexible DC grid based on positive and negative difference of voltage refractive wave amplitude[J]. Automation of electric power systems, 2022, 46(3): 129-136.
[4] 戴志辉, 李毅然, 焦彦军, 等. 耐受高阻和强噪声的柔直配电线路保护原理[J]. 高电压技术, 2022, 48(10): 3966-3974.
DAI Z H, LI Y R, JIAO Y J, et al.Protection scheme for flexible DC distribution lines with high resistance and strong noise endurance ability[J]. High voltage engineering, 2022, 48(10): 3966-3974.
[5] 高淑萍, 段必聪, 宋国兵, 等. 基于暂态电流故障分量的直流配电网单极故障选线方法[J]. 太阳能学报, 2022, 43(3): 141-146.
GAO S P, DUAN B C, SONG G B, et al.Single-pole fault line selection method of DC distribution network based on transient current fault component[J]. Acta energiae solaris sinica, 2022, 43(3): 141-146.
[6] 高飘, 郑晓冬, 晁晨栩, 等. 基于特定频带能量比的高压直流输电线路保护[J]. 电力系统自动化, 2022, 46(15): 136-144.
GAO P, ZHENG X D, CHAO C X, et al.High-voltage DC transmission line protection based on energy ratio of specific frequency band[J]. Automation of electric power systems, 2022, 46(15): 136-144.
[7] 杨赛昭, 向往, 张峻榤, 等. 基于人工神经网络的架空柔性直流电网故障检测方法[J]. 中国电机工程学报, 2019, 39(15): 4416-4430.
YANG S Z, XIANG W, ZHANG J J, et al.The artificial neural network based fault detection method for the overhead MMC based DC grid[J]. Proceedings of the CSEE, 2019, 39(15): 4416-4430.
[8] 王晓卫, 高杰, 吴磊, 等. 柔性直流配电网高阻接地故障检测方法[J]. 电工技术学报, 2019, 34(13): 2806-2819.
WANG X W, GAO J, WU L, et al.A high impedance fault detection method for flexible DC distribution network[J]. Transactions of China Electrotechnical Society, 2019, 34(13): 2806-2819.
[9] 薛蕙, 杨仁刚. 利用Morlet连续小波变换实现非整次谐波的检测[J]. 电网技术, 2002, 26(12): 41-44.
XUE H, YANG R G.Morlet wavelet based detection of noninteger harmonics[J]. Power system technology, 2002, 26(12): 41-44.
[10] CHUNG J Y, GULCEHRE C, CHO K H, et al.Empirical evaluation of gated recurrent neural networks on sequence modeling[J]. arXiv, 2014: 1412.3555.
[11] LIU W X, SONG Y B, CHEN D S, et al.Deformable object tracking with gated fusion[J]. IEEE transactions on image processing, 2019, 28(8): 3766-3777.
[12] 赵兵, 王增平, 纪维佳, 等. 基于注意力机制的CNN-GRU短期电力负荷预测方法[J]. 电网技术, 2019, 43(12): 4370-4376.
ZHAO B, WANG Z P, JI W J, et al.A short-term power load forecasting method based on attention mechanism of CNN-GRU[J]. Power system technology, 2019, 43(12): 4370-4376.
[13] 姚程文, 杨苹, 刘泽健. 基于CNN-GRU混合神经网络的负荷预测方法[J]. 电网技术, 2020, 44(9): 3416-3424.
YAO C W, YANG P, LIU Z J.Load forecasting method based on CNN-GRU hybrid neural network[J]. Power system technology, 2020, 44(9): 3416-3424.
[14] 庄一展, 刘飞, 黄艳辉, 等. 模块化串联光伏直流变换器的环形功率均衡拓扑及效率优化策略[J]. 中国电机工程学报, 2022, 42(5): 1657-1669.
ZHUANG Y Z, LIU F, HUANG Y H, et al.A circular power balancing topology with efficiency optimization strategy for modular cascaded photovoltaic DC/DC converter[J]. Proceedings of the CSEE, 2022, 42(5): 1657-1669.
[15] BAGHERZADEH H, ABEDINI M, DAVARPANAH M, et al.A novel protection scheme to detect, discriminate, and locate electric faults in photovoltaic arrays using a minimal number of measurements[J]. International journal of electrical power & energy systems, 2022, 141: 108172.
[16] YUAN S, YANG B F, ZHANG J Y.Experimental study on short-circuit current characteristics of a photovoltaic system with low voltage ride through capability under a symmetrical fault[J]. Energy reports, 2022, 8: 4502-4511.
PDF(2524 KB)

Accesses

Citation

Detail

Sections
Recommended

/