JOURNAL ARTICLE

Fault identification in an AC-DC transmission system using neural networks

Abstract

The possibility of using neural networks to identify faults that may have occurred in an AC-DC power system is explored. Based on the ability of these networks to distinguish reliably between different types of fault, appropriate control measures can be taken to improve the dynamic performance of the AC-DC power system. Three different neural network architectures to distinguish between different types of fault on the AC-DC system are proposed, and a comparison between them is made.< >

Keywords:
Artificial neural network Fault (geology) Computer science Identification (biology) Power (physics) Electric power system Transmission (telecommunications) Power transmission Artificial intelligence Control engineering Engineering Telecommunications Physics

Metrics

8
Cited By
0.94
FWCI (Field Weighted Citation Impact)
11
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

HVDC Systems and Fault Protection
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
High voltage insulation and dielectric phenomena
Physical Sciences →  Materials Science →  Materials Chemistry
High-Voltage Power Transmission Systems
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
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