Title: Fault location of high voltage overhead transmission line based on ACO-ENN algorithm

Authors: Guangxin Zhang; Qi Zhang; Jun Ma; Gang Liu; Dong Sun; Zimeng Zhang

Addresses: Changchun Institute of Technology, Changchun, 130012, China ' Changchun Institute of Technology, Changchun, 130012, China ' State Grid Tonghua Electric Power Supply Company, Tonghua, 134000, China ' State Grid Baicheng Electric Power Supply Company, Baicheng, 137000, China ' State Grid Tonghua Electric Power Supply Company, Tonghua, 134000, China ' State Grid Baicheng Electric Power Supply Company, Baicheng, 137000, China

Abstract: Aiming at solving the problems of poor positioning accuracy and long time in traditional methods, a fault location of a high-voltage overhead transmission line based on ACO-ENN algorithm is proposed in this paper. Firstly, self-coding neural network is used to reduce dimension of transmission line signal data. Secondly, the relationship between fault distance and natural frequency is obtained by main frequency extraction method. Finally, ACO-ENN algorithm is used to construct the hidden interlayer weight matrix to obtain the fault location error function of the transmission line, and the fault location result of the high voltage overhead transmission line is obtained under the condition of the minimum error function. The results show that the mean square error of the proposed method is less than 187 m, and when the fault distance of the high voltage overhead transmission line is 300 km, the fault location time of the proposed method is only 0.43 s.

Keywords: ACO-ENN algorithm; high voltage overhead; transmission line; fault location; main frequency extraction; self-coding neural network; error function.

DOI: 10.1504/IJCIS.2023.134619

International Journal of Critical Infrastructures, 2023 Vol.19 No.6, pp.544 - 557

Received: 08 Nov 2021
Accepted: 28 Dec 2021
Published online: 01 Nov 2023 *

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