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Abstract

The structure of the low-voltage distribution network often changes. The change of topology will affect fault detection, fault location, line loss calculation, etc. It leads to fault detection error, inaccurate positioning and abnormal line loss calculation. This paper presents a new method to automatically identify the topology of a low-voltage power grid by using the injection current signal. When the disturbance current signal is injected into the low-voltage line, the current upstream of the injection point will change, and the current downstream of the injection point will not be affected. It is proved theoretically by using the superposition principle. With this method, the disturbance current signal can be injected into the line in turn, and the topology can be identified by observing the change of the current in line. The correctness of the method is proved by Matlab simulation and laboratory verification.
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Bibliography

[1] Short T.A., Electric Power Distribution Handbook, Second Edition, Crc Press (2014).
[2] Bingyin X., Tianyou L. et al., Smart Distribution Grid and Distribution Automation, Automation of Electric Power Systems, vol. 33, no. 17, pp. 38–41 (2009).
[3] Jiang J., Liu L., Resonance mechanisms of a single line-to-ground fault on ungrounded systems, Archives of Electrical Engineering, vol. 69, no. 2, pp. 455–466 (2020).
[4] Grotas S., Yakoby Y., Gera I. et al., Power Systems Topology and State Estimation by Graph Blind Source Separation, IEEE Transactions on Signal Processing, vol. 67, no. (8), pp. 2036–2051 (2019).
[5] Tianyu L., Research on Fault Analysis and Topology Identification Based on Power Line Communication, Master Thesis, Control Engineering, China University of Geosciences (Beijing) (2019).
[6] Xiangyu K., YutingW., Xiaoxiao Y. et al., Optimal configuration of PMU based on customized genetic algorithm and considering observability of multiple topologies of distribution network, Electric Power Automation Equipment, vol. 40, no. 1, pp. 66–72 (2020).
[7] Chao Y., The Development and Manufacture of a Multi-Function Equipment for Low Voltage Area Identifed, Master Thesis, Electrical Engineering, China Dalian University of Technology (2014).
[8] Ya L., Rusen F., Wei J. et al., Research on the intelligent transformer area recognition method based on BP neural network, Electrical Measurement & Instrumentation, vol. 54, no. 3, pp. 25–30 (2017).
[9] Dong-Feng Y., Su-Quan Z. et al., A Novel Method for Power Grid Topology Identification Based on Incidence Matrix Simplification, East China Electric Power, vol. 42, no. 11, pp. 2254–2259 (2014).
[10] Jing M., Yuyu Z. et al., Power Network Topological Analysis Based on Incidence Matrix Notation Method and Loop Matrix, Automation of Electric Power Systems, vol. 38, no. 12, pp. 74–80 (2014).
[11] Zeyang T., Kunpeng Z., Kan C. et al., Substation Area Topology Verification Method Based on Distribution Network Operation Data, High Voltage Engineering, vol. 44, no. 4, pp. 1059–1068 (2018).
[12] Zongzong L., Xuezhong F., Qing W. et al., Station area recognition of distribution network based on electricity information acquisition system, Electrical Measurement and Instrumentation, vol. 56, no. 24, pp. 109–114 (2019).
[13] Jing M., Yuyu Z., Wei M. et al., Power Network Topological Analysis Based on Incidence Matrix Notation Method and Loop Matrix, Automation of Electric Power Systems, vol. 38, no. 12, pp. 74–80 (2014).
[14] Zonghui W., Yu C., Bingyin X. et al., Logical Node Based Topology Identification of Distributed Feeder Automation, Automation of Electric Power Systems, vol. 44, no. 12, pp. 124–130.
[15] Zengping W., Jinfang Z., Yagang Z., A novel substation configuration identification algorithm based on the set of breaker-path functions, Proceedings of the CSEE, vol. 33, no. 1, pp. 137–145 (2013).


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Authors and Affiliations

Haotian Ge
1
Bingyin Xu
1
Wengang Chen
1
Xinhui Zhang
1
Yongjian Bi
1

  1. Shandong University of Technology, China
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Abstract

The topology of low-voltage distribution systems changes with the load or the on/off position of the circuit switch. This will affect power flows, losses, and so on. This paper submits a new method to identify the topology of a low-voltage feeder using the injection high-frequency signal. An inductor can block the high-frequency signal. It can change the propagation direction of the injected high-frequency signal to make it propagate unidirectionally along the low-voltage feeder. By injecting a 5 MHz sinusoidal signal from the upstream direction of the low-voltage feeder, all the line segments and devices on the feeder can be identified. The wavelength of the high-frequency signal is short. The wavelength of the 5 MHz signal is 60 meters. Through the delay of different observation points on the feeder, the length of the line section can be roughly calculated. The highfrequency signal has an obvious reflection on the feeder. Using this feature, we can roughly calculate the length of the line segment. The correctness of the method is demonstrated by MATLAB simulation verification.
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Bibliography

[1] Thomas Allen Short, Electric Power Distribution Handbook, Second Edition, CRC Press (2014).
[2] Kersting W., Distribution System Modeling and Analysis, Fourth Edition, CRC Press (2017).
[3] Grotas S., Yakoby Y., Gera I. et al., Power Systems Topology and State Estimation by Graph Blind Source Separation, IEEE Transactions on Signal Processing, vol. 67, no. 8, pp. 2036–2051 (2019).
[4] Jun Jiang, Ling Liu, Resonance mechanisms of a single line-to-ground fault on ungrounded systems, Archives of Electrical Engineering, vol. 69, no. 2, pp. 455–466 (2020).
[5] Fan Kaijun, Xu Bingyin, Dong Jun et al., Identification method for feeder topology based on successive polling of smart terminal unit, Automation of Electric Power Systems, vol. 39, no. 11, pp. 180–186 (2015).
[6] Zhu Guofang, Shen Peifeng, Wang Yong et al., Dynamic identification method of feeder topology for distributed feeder automation based on topological slices, Power System Protection and Control, vol. 46, no. 14, pp. 152–157 (2018).
[7] Li X., Poor H.V., Scaglione A., Blind topology identification for power systems, 2013 IEEE International Conference on Smart Grid Communications (SmartGridComm), IEEE, pp. 91–96 (2013).
[8] Lazaropoulos A.G., Measurement Differences, Faults and Instabilities in Intelligent Energy Systems– Part 1: Identification of Overhead High-Voltage Broadband over Power Lines Network Topologies by Applying Topology Identification Methodology (TIM), Trends in Renewable Energy, vol. 2, no. 3, pp. 85–112 (2016). [9] Lazaropoulos A.G., Improvement of Power Systems Stability by Applying Topology Identification Methodology (TIM) and Fault and Instability Identification Methodology (FIIM) – Study of the Overhead Medium-Voltage Broadband over Power Lines (OVMVBPL) Networks Case, Trends inRenewable Energy, vol. 3, no. 2, pp. 102–128 (2017).
[10] Passerini F., Tonello A.M., Power line network topology identification using admittance measurements and total least squares estimation, 2017 IEEE International Conference on Communications (ICC), pp. 1–6 (2017).
[11] Soumalas K., Messinis G., Hatziargyriou N., A data driven approach to distribution network topology identification, 2017 IEEE Manchester PowerTech, pp. 1–6 (2017).
[12] Ge Haotian, Xu Binyin, Topology Identification of Low Voltage Distribution Network Based on Current Injection Method, Archives of Electrical Engineering, vol. 70, no. 2, pp. 297–306 (2021).
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Authors and Affiliations

Haotian Ge
1
Bingyin Xu
1
Xinhui Zhang
1
Yongjian Bi
1

  1. Shandong University of Technology, China
Download PDF Download RIS Download Bibtex

Abstract

The topology identification of low-voltage distribution networks is an important foundation for the intelligence of low-voltage distribution networks. Its accuracy fundamentally determines the effectiveness of functions such as power system state estimation, operational control, optimization planning, and intelligent electricity consumption. The low-voltage distribution network is composed of transformers, lines, and end users. The key task of topology identification is to distinguish the connection relationship between distribution transformers, low-voltage lines, and phase sequence with end users, which can be divided into transformer user relationship, line user relationship, and phase user relationship. At present, the main methods of low-voltage network topology identification can be divided into signal injection method and data analysis method. The signal injection method requires a large number of additional terminal devices and is difficult to promote. The data analysis method combines the characteristics of switch state, voltage, current, electrical energy, and other data to perform topology analysis. The commonly used methods include correlation analysis and feature learning. Finally, typical problems that urgently need to be solved in topology recognition and representation were proposed, providing a reference for the research and development of low-voltage distribution network topology automatic recognition technology.
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Authors and Affiliations

Ge Haotian
1
Zhong Jiuming
1

  1. Hainan Normal University, China

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