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JCR Impact Factor: 0.800
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Issues per year: 4
Current issue: Aug 2023
Next issue: Nov 2023
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  3/2023 - 2

Electrical Evaluation of Oil-Immersed Power Transformers Based on Temporal Variations in Performance Index and Reliability

DIAS, Y. See more information about DIAS, Y. on SCOPUS See more information about DIAS, Y. on IEEExplore See more information about DIAS, Y. on Web of Science, MARQUES, A. See more information about  MARQUES, A. on SCOPUS See more information about  MARQUES, A. on SCOPUS See more information about MARQUES, A. on Web of Science, RIBEIRO, C. See more information about  RIBEIRO, C. on SCOPUS See more information about  RIBEIRO, C. on SCOPUS See more information about RIBEIRO, C. on Web of Science, BRITO, L. See more information about BRITO, L. on SCOPUS See more information about BRITO, L. on SCOPUS See more information about BRITO, L. on Web of Science
 
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Download PDF pdficon (1,408 KB) | Citation | Downloads: 384 | Views: 321

Author keywords
condition monitoring, failure analysis, maintenance engineering, power transformers, reliability engineering

References keywords
power(13), transformers(12), insulation(10), analysis(7), interpretation(5), insulating(5), marques(4), guide(4), dielectric(4), dias(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2023-08-31
Volume 23, Issue 3, Year 2023, On page(s): 13 - 20
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2023.03002
Web of Science Accession Number: 001062641900002
SCOPUS ID: 85172334203

Abstract
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In electrical systems, power transformer failure prediction is a strategic procedure aimed at ensuring the uninterrupted delivery of electricity. In this context, companies of electricity employ predictive maintenance techniques to evaluate the status of this type of equipment. Aiming to contribute by adding monitoring criteria and complementing research in this field, to help maintenance teams project the future status of their power transformers immersed in insulating mineral oil with nominal voltages rated from 34.5 kV to 230 kV and above, with powers from tens to hundreds of MVA, and with and without on-load tap changer, this article presents an innovative method for projection the performance index of these assets on any given date, and to obtain a numerically reliability projection for that date. The originality of this tool stems from its combined use of two easy-to-implement mathematical criteria, considering the historical results of current and previous maintenance dielectric and electrical tests: the Weighted Moving Average and the Consistency of the Historical Neighborhood. Thus, this method is expected to contribute to more accurate to decisions making by maintenance teams.


References | Cited By  «-- Click to see who has cited this paper

[1] N. Chakraborty, S. W. Human, N. Balakrishnan, "A generally weighted moving average chart for time between events," Communications in Statistics - Simulation and Computation, 46:10, 7790-7817, 2017.
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[2] M. B. Perry, "The weighted moving average technique," Wiley Encyclopedia of Operations Research and Management Science, 2010.
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[3] X. Su, X. Yan, and C. Tsai, "Linear regression," Wiley Interdisciplinary Reviews: Computational Statistics 4.3, pp. 275-294, 2012.
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[4] S. Weisberg, "Applied linear regression," John Wiley & Sons, 2013,
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[5] Institute of Electrical and Electronics Engineers, "IEEE Std C57.152-2013 - IEEE guide for diagnostic field testing of fluid-filled power transformers, regulators, and reactors," New York: IEEE, 2013.
[CrossRef]


[6] Institute of Electrical and Electronics Engineers, "IEEE C57.125-2015 - IEEE Guide for Failure Investigation, Documentation, and Analysis for Power Transformers and Shunt Reactors," New York: IEEE, 2015.
[CrossRef]


[7] M. Mandlik, and T. S. Ramu, "Moisture aided degradation of oil impregnated paper insulation in power transformers," IEEE Transactions on Dielectrics and Electrical Insulation, 21.1, pp. 186-193, 2014.
[CrossRef] [Web of Science Times Cited 41] [SCOPUS Times Cited 52]


[8] P. J. Baird, H. Herman, G. C. Steven,s and P. N. Jarman, "Non-destructive measurement of the degradation of transformer insulating paper," IEEE Transactions on Dielectrics and Electrical Insulation, 13(2), pp. 309-318, 2006.
[CrossRef] [Web of Science Times Cited 47] [SCOPUS Times Cited 65]


[9] X. Chendong, "Monitoring paper insulation ageing by measuring furfural contents in oil," in 7th Int. Symp. on High Voltage Eng., pp. 26-30, 1991

[10] L. Cheim, D. Platts, T. Prevost, S. Xu, "Furan analysis for liquid power transformers," Electrical Insulation Magazine, IEEE, vol. 28, pp.8-21, 2012.
[CrossRef]


[11] R. D. Stebbins, D. S. Myers, A. B. Shkolnik, "Furanic compounds in dielectric liquid samples: Review and update of diagnostic interpretation and estimation of insulation ageing," in 7th Int. Conf. on Properties and Appl. of Dielectr. Mater., pp. 921-926, 2003.
[CrossRef]


[12] A. de Pablo, Interpretation of furanic compounds analysis degradation models, CIGRE, 1997

[13] A. de Pablo, "Furfural and ageing: How are they related," In IEEE Colloquium on Insulating Liquids, pp. 5/1-5/4, 1999.
[CrossRef]


[14] A. J. Kachler and I. Hohlein, "Aging of cellulose at transformer service temperatures. Part 1: Influence of type of oil and air on the degree of polymerization of pressboard, dissolved gases and furanic compounds in oil," IEEE Electr. Insul. Mag., vol. 21(2), pp. 15- 21, 2005.
[CrossRef] [Web of Science Times Cited 94] [SCOPUS Times Cited 129]


[15] A. B. Shkolnik, R. T. Rasor and S. D. Myers, "Statistical insights into furan interpretation using a large dielectric fluid testing database," in IEEE PES Transmission and Distribution Conf. and Expo., pp. 1-8, 2012.
[CrossRef] [SCOPUS Times Cited 20]


[16] M. K. Pradhan, T. S. Ramu, "On the estimation of elapsed life of oil-immersed power transformers," IEEE Trans. Power Del., vol. 20(3), pp. 1962-1969, 2005.
[CrossRef] [Web of Science Times Cited 80] [SCOPUS Times Cited 121]


[17] T. K. Saha, "Review of modern diagnostic techniques for assessing insulation condition in aged transformers," IEEE Transaction on Dielectrics and Electrical insulation, vol. 10, No. 5, Oct. 2003.
[CrossRef] [Web of Science Times Cited 481] [SCOPUS Times Cited 710]


[18] F. Ortiz, C. Fernandez-Diego, A. Santisteban, F. Delgado, A. Ortiz, "Estimating the age of power transformers using the concentration of furans in dielectric oil," Renewable Energy and Power Quality Journal, No. 14, May 2016.
[CrossRef] [SCOPUS Times Cited 16]


[19] D. Kanumuri, V. Sharma, and O. P. Rahi, "Analysis using various approaches for residual life estimation of power transformers," International Journal on Electrical Engineering and Informatics - Volume 11, Number 2, Jun. 2019.
[CrossRef] [SCOPUS Times Cited 15]


[20] A. P. Marques, "Optimized diagnosis of power transformers through the integration of predictive techniques," Thesis (PhD in Electrical and Computation Engineering) - School of Electrical, Mechanical and Computer Engineering, Federal University of Goias, Goiania, Brazil 2018

[21] A. Marques, N. K. Moura, Y. A. Dias, C. J. Ribeiro, A. S. Rocha, L. da C. Brito, C. H. B. Azevedo, and J. A. L. Santos, "Method for the evaluation and classification of power transformer insulating oil based on physicochemical analyses," in IEEE Electrical Insulation Magazine, vol. 33, no. 1, pp. 39-49, January-February 2017.
[CrossRef] [SCOPUS Times Cited 10]


[22] A. P. Marques, N. K. Moura, C. J. Ribeiro, Y. A. Dias, A. Rodrigues, A. S. Rocha, C. H. B. Azevedo, J. A. L. Santos, F. de C. Sousa, and L. da C. Brito, "Insulation resistance of power transformers - Method for optimized analysis," in Proc. 19th IEEE International Conference on Dielectric Liquids - ICDL. Manchester, United Kingdom, June 2017.
[CrossRef] [SCOPUS Times Cited 7]


[23] Institute of Electrical and Electronics Engineers, "IEEE Std C57.104-2019," IEEE Guide for the Interpretation of Gases Generated in Oil-immersed Transformers, New York, 2019.
[CrossRef]


[24] International Electrotechnical Commission, IEC 60599:2015, "Mineral oil-impregnated electrical equipament in service - Guide to the interpretation of dissolved and free gases analysis,", 2015

[25] L. C. Brito, A. P. Marques, C. J. Ribeiro, A. S. Rocha, Y. A. Dias, N. K. Moura, P. H. S. Palhares, C. H. B. Azevedo, and J. A. L. Santos, "Combined approach of the IEEE and IEC guides for interpreting dissolved gas analysis in insulating mineral oil," in Proc. VI Brazilian Symposium on Electrical Systems, Natal, May, pp. 1-6, 2016

[26] Y. A. Dias, "Bayesian network for estimating the reliability of power transformers immersed in insulating mineral oil using predictive maintenance techniques," Dissertation. MSc in Electrical and Computation Engineering - Federal University of Goias, Goiania, Brazil, 2019



References Weight

Web of Science® Citations for all references: 856 TCR
SCOPUS® Citations for all references: 2,556 TCR

Web of Science® Average Citations per reference: 32 ACR
SCOPUS® Average Citations per reference: 95 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2023-11-26 05:44 in 115 seconds.




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Stefan cel Mare University of Suceava, Romania


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