Journal ArticleDOI
High speed transmission system directional protection using an Elman network
Majid Sanaye-Pasand,Om P. Malik +1 more
TLDR
System simulation studies show that the proposed approach is able to detect the direction of a fault on a transmission line rapidly and correctly and is suitable to realize a very fast transmission line directional comparison protection scheme.Abstract:
Detection of the direction of a fault on a transmission line is essential to the proper performance of a power system. It would be desirable to develop a high speed and accurate approach to determine the fault direction for different power system conditions. To classify forward and backward faults on a given line, a neural network's abilities in pattern recognition and classification could be considered as a solution. To demonstrate the applicability of this solution, neural network technique is employed and a novel Elman recurrent network is designed and trained. Details of the design procedure and the results of performance studies with the proposed network are given and analysed in the paper. System simulation studies show that the proposed approach is able to detect the direction of a fault on a transmission line rapidly and correctly. It is suitable to realize a very fast transmission line directional comparison protection scheme.read more
Citations
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Journal ArticleDOI
Study of wavelet-based ultra high speed directional transmission line protection
TL;DR: In this paper, a wavelet-based directional protection scheme was proposed for UHV/EHV transmission line protective relay. But the wavelet singularity detection technique was not used in this paper.
Journal ArticleDOI
A novel fuzzy neural network based distance relaying scheme
TL;DR: This paper presents a new approach to distance relaying using fuzzy neural network (FNM), which provides robust and accurate classification/location of faults for a variety of power system operating conditions even with resistance in the fault path.
Journal ArticleDOI
An overview of transmission line protection by artificial neural network: fault detection, fault classification, fault location, and fault direction discrimination
Anamika Yadav,Yajnaseni Dash +1 more
TL;DR: This paper focuses on the studies of fault detection, fault classification, fault location, fault phase selection, and fault direction discrimination by using artificial neural networks approach.
Transmission Line Fault Detection & Phase Selection using ANN
TL;DR: A novel application of neural network approach to protection of transmission line is demonstrated and results of performance studies show that the proposed neural network- based module can improve the performance of conventional fault selection algorithms.
Journal ArticleDOI
Modular neural network-based directional relay for transmission line protection
TL;DR: The modular neural network concept has been utilized successfully to develop a directional relay algorithm for a transmission system and subsequently implemented on a DSP TMS320F243 EVM-board.
References
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Journal ArticleDOI
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Journal ArticleDOI
Design, implementation and testing of an artificial neural network based fault direction discriminator for protecting transmission lines
TL;DR: A fault direction discriminator that uses an artificial neural network (ANN) for protecting transmission lines and is suitable for realizing an ultrafast directional comparison protection of transmission lines is described.
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