Fault section location in urban distribution network based on fault marking

The goal is to propose an effective method for locating a fault segment in urban power distribution networks. Urban distribution networks have multiple outgoing lines, switches with multiple connections and have variable topology characteristics. It is found that the fault location method based on matrix algorithm has low adaptive capability and fault tolerance when dealing with complex and variable topology. Therefore, this paper proposes an efficient fault segment location method based on special fault indicators, which can significantly improve the accuracy and reliability of fault location. Accordingly, to improve the accuracy and reliability of fault location, a fault segment location method based on fault marking is proposed. The approach proposed in the paper relies on the analysis of the incident matrix, which describes the relationship between nodes and branches, and allows the use of graph theory. The branch state vector is added to obtain the adjacency matrix, which allows to describe the state of change in the dynamics of the distribution network topology. In the next step, a set of nodes and branches, which reflect the incoming and outgoing interconnections of the nodes, is established based on the selected direction of the network binding. According to the direction of the node fault current, the suspicious branches are identified and labeled to indicate the fault. By cumulative calculation and analysis of the labels, the target branches are screened out and the faulty sections of the city power supply network are identified. The results of the case study conducted in the paper show that the proposed method has good adaptability to the variable topology and increases the fault tolerance and accuracy of the developed matrix algorithm. The topological operating state of the network can be changed by controlling the switches to optimize the operation and improve the reliability of the power supply. Thus, the algorithm for fast and accurate fault location is of great importance for improving the safety and quality of urban power supply.

1. Salehi M., Namdari F. Fault location on branched networks using mathematical morphology. IET Generation, Transmission & Distribution. 2018;12(1):207216. https://doi.org/10.1049/iet-gtd.2017.0598.

2. Teng Jen-Hao, Huang Wei-Hao, Luan Shang-Wen. Automatic and fast faulted line-section location method for distribution systems based on fault indicators. IEEE Transactions on Power Systems. 2014;29(4):1653-1662. https://doi.org/10.1109/TPWRS.2013.2294338.

3. Jiang Yazhou, Liu Chen-Ching, Diedesch M., Lee Erik, Srivastava A. K. Outage management of distribution systems incorporating information from smart meters. IEEE Transactions Power System. 2016;31(5):4144-4154. https://doi.org/10.1109/TPWRS.2015.2503341.

4. Gu Jyh-Cherng, Huang Zih-Jhe, Wang Jing-Min, Hsu Lin-Chen, Yang Ming-Ta. High impedance fault detection in overhead distribution feeders using a DSP-based feeder terminal unit. IEEE Transactions on Industry Applications. 2021;57(1):179186. https://doi.org/10.1109/TIA.2020.3029760.

5. Xu Biao, Yin Xianggen, Zhang Zhe, Pang Shuai, Li Xusheng. Fault location for distribution network based on matrix algorithm and optimization algorithm. Automation of Electric Power System. 2019;43(5):152-158. https://doi.org/10.7500/AEPS20180115002.

6. Sun Kongming, Chen Qing, Gao Zhanjun. An automatic faulted line section location method for electric power distribution systems based on multisource information. IEEE Transactions on Power Delivery. 2016;31(4):1542-1551. https://doi.org/10.1109/TPWRD.2015.2473681.

7. Kong Pei, Liu Jianfeng, Zhou Jian, Zhou Yongliang, Song Ziheng. Fault-tolerant algorithm for fault location in distribution network based on integer linear programming. Power System Protection and Control. 2020;48(24):27-35. https://doi.org/10.19783/j.cnki.pspc.200073.

8. Zheng Tao, Ma Wenlong, li Wenbo. Fault section location of active distribution network based on feeder terminal unit information distortion correction. Power System. 2021;45(10):3926-3935. https://doi.org/10.13335/j.10003673.pst.2020.1991.

9. Li Wenbo, Su Jianjun, Wang Xin, Li Jiamei, Ai Qian. Fault location of distribution networks based on multisource information. Global Energy Interconnection. 2020;3(1):77-85. https://doi.org/10.14171/j.20965117.gei.2020.01.009.

10. Sun Kongming, Chen Qing, Zhao Pu. Automatic faulted feeder section location and isolation method for power distribution systems considering the change of topology. Energies. 2017;10(8):1081. https://doi.org/10.3390/en10081081.

11. Zheng Tao, Ma Long, Zhang Bo. Fault tolerant fast fault section location method for active distribution network. Journal of North China Electric Power University. 2022;49(1):12-21.

12. Ding Yi, Zhang Xin, Wang Xudong. A New Method for Fault Section Location of Feeder Based on Peak-Combination. Proceedings of the CSU-EPSA. 2021;33(9):26-31. https://doi.org/10.19635/j.cnki.csuepsa.000789.

13. Jiang Yazhou. Toward detection of distribution system faulted line sections in real time: a mixed integer linear programming approach. IEEE Transactions on Power Delivery. 2019;34(3):1039-1048. https://doi.org/10.1109/TPWRD.2019.2893315.

14. Ji Xingquan, Zhang Shuo, Zhang Yumin, Han Xueshan, Xiao Yundong, Zeng Ruomei. Fault section location for distribution network based on improved electromagnetism-like mechanism algorithm. Automation of Electric Power Systems. 2021;45(22):157-166. https://doi.org/10.7500/AEPS20210121007.

15. Guo Zhuangzhi, Xu Qixing, Hong Junjie, Mao Xiaoming. Integer linear programming based fault section diagnosis method with high fault-tolerance and fast performance for distribution network. Proceedings of the CSEE. 2017;37(3):786-794. https://doi.org/10.13334/j.0258-8013.pcsee.152361.

16. Gong Xuan, Ren Xinxu, Wang Qiujie, Chen Ting, Wang Ling. A section location method with high fault tolerance stability for distribution network with distributed generation. High Voltage Engineering. 2021;47(11):39924006. https://doi.org/10.13336/j.1003-6520.hve.20201665.

17. Liu Pengcheng, Li Xinli. Fault-section location of distribution network containing distributed generation based on the multiple-population genetic algorithm. Power System Protection and Control. 2016;44(2):36-41.

18. Džafić R. A. Jabr S. Henselmeyer, Ðonlagić. T. Fault location in distribution networks through graph marking. IEEE Transactions on Smart Grid. 2018;9(2):1345-1353. https://doi.org/10.1109/TSG.2016.2587583.

19. Guo Mou-Fa, Gao Jian-Hong, Shao Xiang, Chen Duan-Yu. Location of single-line-to-ground fault using 1-d convolutional neural network and waveform concatenation in resonant grounding distribution systems. IEEE Transactions on Instrumentation and Measurement. 2021;70. https://doi.org/10.1109/TIM.2020.3014006.

20. Kiaei I., Lotfifard S. Fault section identification in smart distribution systems using multi-source data based on fuzzy Petri nets. IEEE Transactions on Smart Grid. 2020;11(1):74-83. https://doi.org/10.1109/TSG.2019.2917506.

21. Zhang Guangxiao, Tong Xiaoyang, Hong Qiteng, Lu Xuemin, Booth C. D. A novel fault isolation scheme in power system with dynamic topology using wide-area information. IEEE Transactions on Industrial Informatics. 2022;18(4):2399-2410. https://doi.org/10.1109/TII.2021.3095254.