Abstract
The commonly used fault diagnosis method of the power transmission line (PTL) is the traveling wave method which uses the traditional mode components \(\alpha \), \(\beta \) and o to realize the fault type recognizing and the fault location in distribution network. However, the traditional mode components of the traveling wave method may take the value of zero that cannot provide the effective fault feature for the A-phase ground fault, or the A and B double phases short-circuit fault. Moreover, a single traditional mode component cannot recognize all the types of the faults, and the fault recognition has to use the multiple mode components that increases the complexity. To address the aforementioned issues, this paper proposes an edge computing scheme based on a novel mode component \(\gamma \) for PTL fault diagnosis in distribution network. Firstly, the novel mode component \(\gamma \) is fused according to the traditional mode components \(\alpha \) and \(\beta \), then the propagation property of the traveling wave-\(\gamma \) is derived. Secondly, the edge computing scheme and the PTL fault diagnosis method are designed for distribution network by using the only novel mode component \(\gamma \). Thirdly, the relationship table of the fault type and the boundary conditions as well as the component \(\gamma \) expressions is derived for the fault recognition using the only traveling wave-\(\gamma \). In addition, the fault distance computing is explored by using the traveling wave-\(\gamma \). The computing is composed with the wave-\(\gamma \) head identification using the optimal Wavelet vanishing moment parameter, and the arrival time determination, and the fault location method. To evaluate the efficiency of the proposed edge computing scheme, the simulation experiment and the laboratory tests are conducted. The simulation experiment results show that, the novel mode component \(\gamma \) not only provides the effective fault features for all the ten types of the power transmission line faults, but also increases fault locating accuracy by the average 2.08 % compared with the methods using the traditional mode component \(\alpha \), \(\beta \) and o. Meanwhile, the laboratory tests show that the edge computing method is practical.












Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Abd El-Ghany HA, Azmy AM, Abeid AM (2020) A general travelling-wave-based scheme for locating simultaneous faults in transmission lines. IEEE Trans Power Delivery 35(1):130–139
Argyropoulos PE, Lev-Ari H (2015) Wavelet customization for improved fault-location quality in power networks. IEEE Trans Power Delivery 30(5):2215–2223
Bains TPS, Zadeh MRD (2016) Supplementary impedance-based fault-location algorithm for seriescompensated Lines. IEEE Trans Power Delivery 31(1):334–342
Behnam M, Jianguo Z (2017) Double-ended technique for distinguishing series faults from shunt faults on transmission lines using the sequential components of impedance. IET Gener Transm Dis 11(6):1381–1388
Boler O, Ibrahem A, Ali AA, Granger MG, Abdelgabir H, Sozer Y, De A-G, De Abreu-Garcia JA (2020) A novel high frequency impedance analysis method to protect DC electrical railway systems. IEEE Trans Ind Appl 56(1):66–677
Chen K, Hu J, He JL (2018) Detection and classification of transmission line Faults based on unsupervised feature learning and convolutional sparse autoencoder. IEEE Trans Smart Grid 9(3):1748–1758
Ding JL, Li LX, Zheng YH, Zhao CM, Chen HT, Wang X (2017) Distributed travelling-wave-based fault location without time synchronization and wave velocity error. IET Gener Transm Dis 11(8):2085–2093
Fasihipour H, Seyedtabaii S (2020) Fault detection and faulty phase identification in TCSC compensated transmission lines. IET Gener Transm Dis 14(6):1042–1050
Hamidi RJ, Livani H (2017) Traveling wave based fault location algorithm for hybrid multiterminal circuits. IEEE Trans Power Delivery 32(1):135–144
Hamidi RJ, Livani H, Rezaiesarlak R (2017) Traveling wave detection technique using short-time matrix pencil method. IEEE Trans Power Delivery 32(6):2565–2574
He ZY, Liao K, Li XP, Lin S, Yang JW, Mai RK (2014) Natural frequency-based line fault location in HVDC lines. IEEE Trans Power Delivery 29(2):851–859
Kalpana V, Maheswar R, Nandakumar E (2020) Multiple parametric fault diagnosis using computational intelligence techniques in linear filter circuit. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-020-01908-0
Kang N, Gombos G, Mousavi MJ, Feng XM (2017) A faultlocation algorithm for series-compensated double-circuit transmission lines using the distributed parameter line model. Electr Power Compo Syst 45(6):615–623
Li YJ, Lu HM, Li JR, Xin Li, Li Y, Serikawa S (2016) Underwater image de-scattering and classification by deep neural network. Comput Electr Eng 56:68–77
Lin T-C, Lin P-Y, Liu C-W (2014) An algorithm for locating faults in three-terminal multisection nonhomogeneous transmission lines using synchrophasor measurements. IEEE Trans Smart Grid 5(1):38–50
Liu YD, Sheng GH, Hu Y, Qian Y, Jiang XC, Qiu RC, YL, (2016) Identification of lightning strike on 500-kV transmission line based on the time-domain parameters of traveling wave. IEEE Access 4:7241–7250
Livani H, Evrenosoglu CY (2014) A machine learning and wavelet-based fault location method for hybrid transmission lines. IEEE Trans Smart Grid 5(1):51–59
Lopes FV, Silva KM, Costa FB, Neves WLA, Fernandes D (2015) Real-time traveling wave-vased fault location using two-terminal unsynchronized data. IEEE Trans Power Delivery 30(5):2215–2223
Lu HM, Li YJ, Nakashima S, Serikawa S (2014) Turbidity underwater image restoration using spectral properties and light compensation. IEICE Trans Inf Syst E99D(1):219–p227
Malik H, Sharma R (2017) Transmission line fault classification using modified fuzzy learning. IET Gener Transm Dis 11(16):4041–4050
Milioudis AN, Andreou GT, Labridis DP (2015) Detection and location of high impedance faults in multiconductor overhead distribution lines using power line communication devices. IEEE Trans Smart Grid 6(2):894–902
Minnaar UJ, Nicolls F, Gaunt CT (2016) Automating transmission-line fault root cause analysis. IEEE Trans Power Delivery 31(4):1692–1700
Namdari F, Salehi M (2017) High-speed protection scheme based on initial current traveling wave for transmission lines employing mathematical morphology. IEEE Trans Power Delivery 32(1):246–253
Prasad CD, Nayak PK (2018) Performance assessment of swarm-assisted mean error estimation based fault detection technique for transmission line protection. Comput Electr Eng 71:115–128
Terzija V, Preston G, Stanojević V, Elkalashy NI, Popov M (2015) Synchronized measurements-based algorithm for short transmission line fault analysis. IEEE Trans Smart Grid 6(6):2639–2648
Xi XY, Zhao JF, Liu TZ, Yan LM (2020) Distributedobserver-based fault diagnosis and fault-tolerant control for time-varying discrete interconnected systems. J Ambient Intell Humaniz Comput 11(2):459–482
Xu X, Lu HM, Song JK, Yang Y, Shen HT, Li X (2020) Ternary adversarial networks with self-supervision for zero-shot cross-modal retrieval. IEEE transactions on cybernetics 50(6):2400–2413
Zhan L, Liu Y, Liu Y (2018) A clarke transformation-based DFT phasor and frequency algorithm for wide frequency range. IEEE Trans Smart Grid 9(1):67–77
Zhang S, Gao HL, Song YT (2016) A new fault-location algorithm for extra-high-voltage mixed lines based on phase characteristics of the hyperbolic tangent function. IEEE Trans Power Delivery 31(3):1203–1212
Zhao HS, Li L (2017) Fault diagnosis of wind turbine bearing based on variational mode decomposition and Teager energy operator. IET Renew Power Gener 11(4):453–460
Acknowledgements
This research is sponsored by the Key Natural Science Foundation of China under Grant 61834005, and the Key Scientific and Technological Projects of Shaanxi Province under Grants 2020GY-107 and 2016GY-040.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Wang, M., Chai, W., Xu, C. et al. An edge computing method using a novel mode component for power transmission line fault diagnosis in distribution network. J Ambient Intell Human Comput 13, 5163–5176 (2022). https://doi.org/10.1007/s12652-020-02466-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-020-02466-1