A novel fault diagnosis system for transmission line system based on sequence of events

Liao, Zhiwei; Wang, G.; Ye, Q.H.; Sun, Yabing

doi:10.1049/cp:20030627

Cited by 4 publications

(1 citation statement)

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“…Fault distribution modelling for stochastic prediction of voltage sags in power networks are developed in [12] and [13] with the goal of predicting the performance of the power network under transient conditions. A fault diagnosis model, based on data mining of sequences of events (SOE), for fault diagnosis of high-voltage transmission line systems (HVTLS) is presented in [14]. SOE is a log that records the signals and alarms produced by the protection systems and the proposed model makes use of spatio-temporal characteristics contained in the SOE logs to identify faulty components based on real-time alarm information occurred in accidents.…”

Section: State Of the Artmentioning

confidence: 99%

Analysis of Event Sequences in Power Distribution Systems

Quiroga¹,

Meléndez²,

Herraiz³

et al. 2024

RE&PQJ

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Abstract. In this paper, events registered in power distribution systems are analyzed to recognize sequences of events associated to faults occurred in the network. The events considered in this study are basically voltage sags generated by homopolar faults and registered by power quality monitors installed in the secondary of transformers in distribution substations. The events registered in a measuring point have associated the time of occurrence, and the list of increasingtime ordered events corresponds to a sequence. The aim of this work is to discover the collection of events associated with failures in the network that can be viewed as sequences of events related with the actuation of the protection system. Two algorithms are proposed to recognize these sequences. The methodology is tested with data gathered in different substations which have been manual grouped by the utility 1 .

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Section: State Of the Artmentioning

confidence: 99%