LAPSE:2019.0190
Published Article
LAPSE:2019.0190
A Review of Frequency Response Analysis Methods for Power Transformer Diagnostics
Saleh Alsuhaibani, Yasin Khan, Abderrahmane Beroual, Nazar Hussain Malik
January 31, 2019
Power transformers play a critical role in electric power networks. Such transformers can suffer failures due to multiple stresses and aging. Thus, assessment of condition and diagnostic techniques are of great importance for improving power network reliability and service continuity. Several techniques are available to diagnose the faults within the power transformer. Frequency response analysis (FRA) method is a powerful technique for diagnosing transformer winding deformation and several other types of problems that are caused during manufacture, transportation, installation and/or service life. This paper provides a comprehensive review on FRA methods and their applications in diagnostics and fault identification for power transformers. The paper discusses theory and applications of FRA methods as well as various issues and challenges faced in the application of this method.
Keywords
condition assessment, diagnostics, frequency response analysis (FRA), power transformer
Suggested Citation
Alsuhaibani S, Khan Y, Beroual A, Malik NH. A Review of Frequency Response Analysis Methods for Power Transformer Diagnostics. (2019). LAPSE:2019.0190
Author Affiliations
Alsuhaibani S: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
Khan Y: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
Beroual A: Ecole Centrale de Lyon, University of Lyon, AMPERE Lab, CNRS UMR 5005, 36 Avenue Guy de Collongue, Ecully 69134, France [ORCID]
Malik NH: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
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Journal Name
Energies
Volume
9
Issue
11
Article Number
E879
Year
2016
Publication Date
2016-10-27
Published Version
ISSN
1996-1073
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Original Submission
Other Meta
PII: en9110879, Publication Type: Review
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LAPSE:2019.0190
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doi:10.3390/en9110879
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Jan 31, 2019
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Jan 31, 2019
 
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Calvin Tsay
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