Dynamic state estimation‐based fault locating on transmission lines

Abstract

Accurate fault locating minimises labour and outage time. Efforts to increase the accuracy of fault locating methods are ongoing. In this study, a dynamic state estimation-based fault locating (EBFL) method is proposed. Best implementation requires GPS synchronised sample value measurements at both ends of the line. The dynamic state estimator operates on the sampled values using a detailed dynamic model of the line, which includes the fault location as a state. Specifically, the dynamic line model is represented as a multi-section transmission line model, inclusive of phase conductor type and size, shield wire(s) type and size, and tower ground impedances, integrated with the fault model. This study presents extensive numerical experiments demonstrating that the method has higher accuracy than traditional fault locating methods for different fault types, locations and impedances. Additionally, the method works for both two-terminal and three-terminal transmission lines.

A fault locating method for multi-branch hybrid transmission lines in wind farm based on redundancy parameter estimation

“…The fundamental frequency phasor-based methods are named M1 and the traveling wave-based methods are named M2. The method in [12] is named M3, and the proposed method is named M4. The capability of the fault locating methods to deal with the above characteristics of transmission lines is listed in Table 1.…”

“…The above methods are commonly used in end-to-end or simple structured transmission lines. Some new algorithms have been proposed for multi-branch hybrid transmission lines: À improved methods based on traditional methods [9,10];`fault locating methods based on pattern recognition techniques such as Artificial Neural Networks and K-means clustering algorithms [11]; and´a method based on dynamic state estimation is proposed [12,13]. The principle of the first type of methods is first determining the fault branch and then locating the fault point based on the determined fault branch by the traditional method.…”

“…The bad data detecting algorithm is used to ensure the correctness of the original data and locating results. The method for the parameter estimation in this paper is completely different with Reference [12] which uses the SCPQDM dynamic model to simulate the power grid and uses a dynamic state estimation to achieve fault location. Reference [12] is suitable for the power grids of lines of two ends and three ends, the proposed method can be used to locate the faults in the complex grids of multi-branch lines and transmission lines containing overhead and cable segments.…”

A new mixed-integer linear formulation for optimal placement of fault indicators in distribution systems

“…Note that some other methods to locate the fault are presented and used in the literatures. Some of these methods are as follows: installation of smart meters on feeders, installation of phasor measurement units in active distribution systems, impedance‐based fault location for overhead unbalanced distribution systems, application of traveling wave recorders, and dynamic state estimation‐based methods …”

An artificial neural network-based solution to locate the multilocation faults in double circuit series capacitor compensated transmission lines

“…18 Recently, k-nearest neighbor-based fault detection, classification, and location estimation in SCCTL has been reported by authors. 19 Furthermore, dynamic state estimation-based fault location estimation has been proposed in Liu et al 20 Nonetheless, all the aforementioned fault location algorithms are relevant to normal shunt faults occurring at single location and are not applicable for multilocation faults. Multilocation faults may occur in different locations in different phases at same or different time during thunder storms.…”