Research on Cross-Circuitry Fault Identification Method for AC/DC Transmission System Based on Blind Signal Separation Algorithm

Yan Tao (), Xiangping Kong, Chenqing Wang, Junchao Zheng, Zijun Bin, Jinjiao Lin and Sudi Xu
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Yan Tao: Electric Power Science Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211103, China
Xiangping Kong: Electric Power Science Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211103, China
Chenqing Wang: Electric Power Science Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211103, China
Junchao Zheng: Electric Power Science Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211103, China
Zijun Bin: Electric Power Science Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211103, China
Jinjiao Lin: Electric Power Science Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211103, China
Sudi Xu: Electric Power Science Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211103, China

Energies, 2025, vol. 18, issue 6, 1-16

Abstract: The AC/DC transmission system is an important component of the power system, and the cross-circuitry Fault diagnosis of the AC/DC transmission system plays an important role in ensuring the normal operation of power equipment and personal safety. The traditional AC/DC transmission detection methods have the characteristics of complex detection processes and low fault line identification rates. Aiming at such problems, this paper proposes a new method of cross-circuitry Fault diagnosis based on the AC/DC transmission system based on a blind signal separation algorithm. Firstly, the method takes the typical cross-circuitry Fault scenario as an example to construct the topology diagram of the AC/DC power transmission system. Then, the electrical signals of the AC system and the DC system of the AC/DC power transmission system are collected, and the collected signals are extracted by the blind signal separation algorithm. Then, aiming at the cross-circuitry Fault problem of the DC system, the electrical quantities of the positive and negative poles on the rectifier side and the inverter side are collected, and the characteristics of the electrical quantities are analyzed by wavelet to determine the fault. At the same time, aiming at the problem of the cross-circuitry Fault of the AC system, three fault types of cross-circuitry Fault, ground fault, and intact fault are set up, and the electrical quantities of A, B, and C are collected on the same side, and the characteristics of three-phase electrical quantities are analyzed by wavelet. Finally, the cross-circuitry Fault judgment interval of the AC/DC system is set as the basis of fault judgment. After experimental verification, the relative error of the model is 1.4683%. The crossline fault identification method of the AC/DC transmission system based on the blind source separation algorithm proposed in this paper can accurately identify the crossline fault location and identify the fault type. It also provides theoretical and experimental support for power system maintenance personnel to maintain equipment.

Keywords: AC/DC transmission system; blind signal separation (BSS); discrete wavelet transform (DWT); cross-circuitry fault (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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