Hierarchical faulted line section location method for low‐voltage active distribution network considering information distortion

Abstract

Distortion of fault monitoring information is an important factor that affects the accuracy of faulted line section location in low-voltage active distribution networks (ADNs). This paper proposes a faulted line section location method that considers the layered solution for monitoring information distortion, to improve the accuracy and efficiency of fault location in low-voltage ADNs. A multi-target fault section location optimization model that considers information distortion, multipoint faults, and multiple information distortion types is formulated. A combination of information distortion factors is introduced to represent various types of information distortion and to transform the original optimization model into an unconstrained 0-1 programming problem. A hierarchical fault location algorithm for segmenting the distribution network is designed to solve the low accuracy and efficiency of direct solutions for fault location models resulting from a large number of active distribution line sections. Simulation results show that the fault location method considering information distortion effectively guarantees the accuracy and solution efficiency of faulted line section location of low-voltage ADN.

Fault Analysis Method of Active Distribution Network Under Cloud Edge Architecture

“…With the access of distributed power source, the traditional distribution network has changed from the original radial network to the complex active distribution network with interconnected power sources and users (Tajdinian, et al, 2020). At the same time, the applicability and accuracy of traditional distribution network fault location methods are reduced, also bringing difficulties to relay protection (Le, et al, 2020;Chen, et al, 2020).…”

A Comprehensive Method for Fault Location of Active Distribution Network Based on Improved Matrix Algorithm and Optimization Algorithm

“…With the development of distribution automation systems and monitoring devices, DTU and FTU are gradually popularized, which can monitor the electrical status and alarm state during the operation of the distribution network and will timely upload the electrical information to the data center (SCADA) after fault detection. On this basis, some fault location methods are proposed for the active distribution network, such as expert system (ES) [3], artificial neural network (ANN) [4,5], Petri nets [6], the rough set method [7], linked-list method [8,9], matrix algorithm [10][11][12][13][14][15], and optimization algorithm [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30]. Among them, the matrix algorithm and the optimization algorithm, are widely used in the practical distribution network.…”

“…In [18], an analytical model for fault location in the case of alarm information distortion is established, which improves the fault-tolerant capability of the model. In [19], a layered fault location algorithm for the problem of low accuracy and efficiency in the case of multiple faults is designed, which improves the solving efficiency. In addition, genetic algorithm (GA) [20], pseudoelectromagnetism algorithm [21], particle swarm optimization (PSO) [22], imperial competition algorithm (ICA) [23], cuckoo search (CS) [24], harmony search (HS) [25], and many other artificial intelligence algorithms have been introduced into this field in recent years.…”

A detection method of high impedance arcing fault for distribution network with distributed generation based on CEEMDAN and TEO algorithm

“…HIF reduces fault current level which may be below protection thresholds 7,8 . The low fault current might lead traditional protection system failing to detect HIF 9‐11 . Besides, an extremely large fault resistance can make the fault current less than 10% of load current, which usually induces fault characteristics weak and difficult to be accurately extracted.…”