Low-voltage overhead lines topology identification method based on high-frequency signal injection

• Autorzy: Ge Haotian , Xu Bingyin , Zhang Xinhui , Bi Yongjian

Identyfikatory

DOI

10.24425/aee.2021.138261

• Języki publikacji: EN

Abstrakty

EN

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 high- frequency 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.

Słowa kluczowe

EN

high-frequency signal injection; low voltage overhead lines; topology identification

PL

wtrysk sygnału wysokiej częstotliwości; linie napowietrzne niskiego napięcia; identyfikacja topologii

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2021
• Tom: Vol. 70, nr 4
• Strony: 791--800
• Opis fizyczny: Bibliogr. 12 poz., rys., tab.

Twórcy

autor

Ge Haotian

• Shandong University of Technology, China

autor

Xu Bingyin

• Shandong University of Technology, China

autor

Zhang Xinhui

• Shandong University of Technology, China

autor

Bi Yongjian

• Shandong University of Technology, China

Bibliografia

• [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 Over- head Medium-Voltage Broadband over Power Lines (OV MV BPL) Networks Case, Trends in Renewable 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).

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).