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Fault Location on Radial Distribution Systems Using Wavelets and Artificial Neural Networks with a New Data Processing FeatureNERI Jr., A. L. , MOREIRA, F. A. , de SOUZA, B. A. |
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Author keywords
distribution power systems, fault location, wavelet transform, data preprocessing, artificial neural networks
References keywords
power(25), fault(22), distribution(21), systems(18), location(18), wavelet(14), neural(10), networks(9), analysis(7), wavelets(6)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2024-05-31
Volume 24, Issue 2, Year 2024, On page(s): 3 - 10
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2024.02001
Web of Science Accession Number: 001242091800001
SCOPUS ID: 85195640726
Abstract
Every power system is vulnerable to fault occurrences. Under permanent fault conditions, maintenance crew has the duty to detect the problem, repair the defect and recover the power supply system. If the fault is previously located, the repair can be performed faster. The common methods to locate the fault in electrical distribution systems use the final user information or some heuristics with fuse coordination and the loss of loads. In this paper, a new algorithm for fault location in distribution power systems is presented. Using computational simulations, travelling waves theory, wavelet transform, a new data preprocessing feature, and artificial neural networks, this new algorithm tries to approximate the fault location using data provided by only one measurement point at the beginning of the feeder. |
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