Automatic Faulted Feeder Section Location and Isolation Method for Power Distribution Systems Considering the Change of Topology

Abstract

Abstract:The increasing use of modern measuring devices, such as Feeder Terminal Units (FTUs), on power networks can provide multiple types of information for fault location on distribution systems. Using these devices, in this paper, a novel automatic matrix-based algorithm for the identification and isolation of faulted feeder sections on distribution systems is proposed. The algorithm works in two stages: the first stage automatically identifies the radial feeders that make up the whole system and represents the feeders' topology in matrix form; and the second stage automatically identifies the faulted section of the identified feeder and opens the relevant switches to isolate it. The algorithm can be applied to single and multiple faults, as it operates using measuring device information and detecting the status of switch devices. It does not require any electrical parameters and it is not affected by the fault type or fault resistance. The algorithm was thoroughly tested using a large distribution system and was found to efficiently identify and isolate the faulted feeder section in each case.

Fault Location of Distribution Network Based on the Quantum Ant Colony Algorithm

“…The above distribution network fault location methods can exactly locate the fault point. However, to isolate the fault and reduce energy losses, it is sufficient to just identify the faulted section of the feeder 15 . Besides, the actual site distribution network structure are complicated; thus, the accurate location of the fault point will cause misjudgement due to various uncertain factors.…”

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.…”

Fault Diagnosis and Location Method for Active Distribution Network Based on Artificial Neural Network

“…Faults in ADN are considered as the main contributor to supply interruptions. Therefore, the development of efficient and precise fault diagnosis method has received a lot of research interest in recent years [4], [5].…”