A method for distribution network line selection and fault location based on a hierarchical fault monitoring and control system. (December 2020)

• Record Type: Journal Article
• Authors: Deng, Feng; Zu, Yarui; Mao, Yu; Zeng, Xiangjun; Li, Zewen; Tang, Xin; Wang, Yang
• Is Part Of: International journal of electrical power & energy systems. Volume 123(2020)
• Publication Date: 2020-12
• Subjects: Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2020.106061
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A cloud-edge-terminal hierarchical fault monitoring and control system is constructed. A novel traveling wave-based line selection and fault location algorithm based on the time difference is presented. A least squares model is introduced to eliminate the calibration error of the initial traveling wave-front arrival time. A low-cost, low-power embedded TWAM and a special traveling wave sensor especially used in distribution networks are development by the author's R&D team. Abstract: The topology structure of a distribution network is complex, and the amount of fault data is considerable, which induces strong fault data processing pressure on traditional cloud service platforms. Edge computing can address the distribution network autonomously and improve the efficiency of distribution network fault data processing. Therefore, in this paper, a novel method is proposed for line selection and fault location in a distribution network based on a cloud-edge-terminal hierarchical fault monitoring and control system. An edge computing gateway is installed at the front end of each main feeder. According to the transmission characteristics of the traveling wave-front, the time characteristic matrices before and after the fault are constructed, and the element variation rules of the matrices under different fault locations are analyzed. Line selection is realized in the cloud service platform; then, the fault location is accurately calculated at the edge computing gateway. To eliminate the calibration error of the initial traveling wave-front arrival time, a least squares model is introduced. The accuracy and reliability of line selection and fault location in the distribution network are improved by fitting the front and end terminal time characteristic matrices before and after the fault. The simulation analysis and field test results show that the proposed method is not affected by the line parameters or the topology structure, and it effectively eliminates the influence of the wave-front calibration error. The proposed method is simple to implement and has high accuracy, reliability and speed.