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JCR Impact Factor: 0.800
JCR 5-Year IF: 1.000
SCOPUS CiteScore: 2.0
Issues per year: 4
Current issue: Feb 2024
Next issue: May 2024
Avg review time: 56 days
Avg accept to publ: 60 days
APC: 300 EUR


PUBLISHER

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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FEATURED ARTICLE

Analysis of the Hybrid PSO-InC MPPT for Different Partial Shading Conditions, LEOPOLDINO, A. L. M., FREITAS, C. M., MONTEIRO, L. F. C.
Issue 2/2022

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2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

2021-Jun-30
Clarivate Analytics published the InCites Journal Citations Report for 2020. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.221 (1.053 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.961.

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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: 471 | Views: 593

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.


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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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