IEEE Access, Volume (11), No (1), Year (2023-1) , Pages (81852-81881)

Title : ( Comprehensive Study on Transformer Fault Detection via Frequency Response Analysis )

Authors: Seyed Ebrahim Hosseini kakolaki , Vahid Hakimian , Javad Sadeh , Elyas-Rakhshani ,

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Abstract

The sudden outage of a transformer due to a fault can cause irreparable damage to the electricity industry. Hence, by conducting momentarily inspections of the transformers condition, faults can be promptly detected, and the transformer can be disconnected from the power grid to prevent subsequent failures in this equipment. Detecting faults at an early stage can also result in reduced repair costs. One recent promising technique for fault detection is Frequency Response Analysis (FRA), which compares the transformers response in healthy and faulty conditions for understanding the occurrence of transformer faults. This paper presents a comprehensive and accurate modeling approach for the behavior of the transformer at different frequencies, followed by an exposition of the requirements for implementing this method in order to find the fault type, severity, and location. Additionally, various methods for analyzing the results of frequency response are introduced and discussed. In this regard, attempts have been made to introduce advanced complementary methods to address the weaknesses and limitations of the frequency response method. Finally, the concepts are summarized, and suggestions for further research with applications in this field are presented and compared.

Keywords

, Transformer fault detection, Frequency response analysis, Hybrid model, Ladder model, Configuration-transfer function pair, Artificial intelligence, Online frequency response analysis.
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@article{paperid:1095186,
author = {Hosseini Kakolaki, Seyed Ebrahim and Hakimian, Vahid and Sadeh, Javad and Elyas-Rakhshani},
title = {Comprehensive Study on Transformer Fault Detection via Frequency Response Analysis},
journal = {IEEE Access},
year = {2023},
volume = {11},
number = {1},
month = {January},
issn = {2169-3536},
pages = {81852--81881},
numpages = {29},
keywords = {Transformer fault detection; Frequency response analysis; Hybrid model; Ladder model; Configuration-transfer function pair; Artificial intelligence; Online frequency response analysis.},
}

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%0 Journal Article
%T Comprehensive Study on Transformer Fault Detection via Frequency Response Analysis
%A Hosseini Kakolaki, Seyed Ebrahim
%A Hakimian, Vahid
%A Sadeh, Javad
%A Elyas-Rakhshani
%J IEEE Access
%@ 2169-3536
%D 2023

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