Traveling Wave Energy Analysis of Faults on Power Distribution Systems

Abstract

This paper explores the most important factors that define the Traveling Wave (TW) propagation on distribution systems. The factors considered in this work are: the distance to the fault location, the fault type, and the crossing of system elements (such as regulators, capacitor banks, laterals, and extra loads within the protection zones). This work uses a realistic, yet simplified, distribution system composed of two protection zones, in which, several combinations of the previously mentioned factors are considered. The simulated fault measurements undergo a signal processing stage in which, first, they are decomposed into independent modes using the Karrenbauer transform. Second, a time–frequency representation is obtained using the Stationary Wavelet Transform (SWT), dividing the signal into several frequency bands. Finally, the Parseval’s Energy (PE) theorem is applied to calculate the signal energy in each frequency band. A qualitative analysis is performed based on the previously calculated energies to outline which are the factors that most affect the TW energy during propagation. The results show that distance, the presence of regulators, either in the propagation path or upstream, and the type of fault are the main factors that affect TW propagation across the system, and therefore they should be considered for TW-based protection schemes for distribution systems.

Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks

“…Simulations were conducted on the PSCAD software package, using frequency-dependent distribution lines and the high-frequency models of capacitor banks and regulators [25]. The IEEE 34 nodes system was selected to develop the proposed scheme.…”

“…There are one voltage regulators in the system (between nodes 814 and 850 and nodes 852 and 832, respectively) that are used as the border of each protection zone. The voltage regulators and the capacitor are modeled for high-frequency transients [25]. For clarification, the nodes located in each of the three PZs are: It is important to note that every node carries a GCN model, and is able to detect and locate faults.…”

“…For this reason, many approaches use a time-frequency decomposition to analyze the TW frequency components. The works in [22,23] used the continuous wavelet transform (CWT) for this purpose, while [24,25] opted for discrete WTs. The reference [26] used the S-transform instead.…”

Signal-based fault location method using time and frequency domain

“…Firstly, the relatively short length of distribution lines complicates the application of existing TW relay signal-processing algorithms designed for transmission networks [3]. Secondly, fault location methods relying on precise TW reflection identification face significant hurdles in distribution systems due to the complex interaction of junctions, laterals, and shunt devices, which generate a dense array of reflections, obscuring fault localization [4].…”

Fault Analysis Method of Active Distribution Network Under Cloud Edge Architecture

“…For example, in case of single-phase grounding fault, the line voltage remains symmetrical, but the phase voltage of non-fault phase will increase by three times. At this time, there is a risk of insulation breakdown of power equipment, which may cause two-point or multi-point grounding short-circuit fault, leading to further development of the fault (Liang, et al, 2020;Hagh, et al, 2019;Miguel, 2022). Therefore, the distribution network fault must be identified in time and handled quickly.…”