Abdi, Sifeddine, Harid, Noureddine, Safiddine, Leila, Boubakeur, Ahmed and Haddad, Abderrahmane (Manu) ORCID: https://orcid.org/0000-0003-4153-6146 2021. The correlation of transformer oil electrical properties with water content using a regression approach. Energies 14 (8) , 2089. 10.3390/en14082089 |
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Abstract
An experimental investigation is conducted to measure and correlate the impact of the water content on the electrical characteristics of the mineral oil for transformers, particularly the breakdown voltage, the resistivity, and the dielectric dissipation factor. Regression method is carried out to compare the results obtained through laboratory experiments with those predicted using an analytical model. A treatment to reduce water content in oil involving filtration, degassing and dehydration using a SESCO mobile station was applied to the new, regenerated, and used oil samples in service. The breakdown voltage, the resistivity, and the dielectric dissipation factor of the samples were measured. Regression analysis using an exponential model was applied to examine the samples electrical properties. The results show that, after treatment, the breakdown voltage and resistivity increase as the water content decreases, unlike the dielectric dissipation factor which exhibits a decreasing trend. This trend is found to be similar for the three oil samples: new, regenerated, and used. The results of the regression analysis give close agreement with the experimental results for all the samples and all studied characteristics. The model shows strong correlation with high coefficients (>90%).
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Engineering |
Additional Information: | This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/) |
Publisher: | MDPI |
ISSN: | 1996-1073 |
Date of First Compliant Deposit: | 16 April 2021 |
Date of Acceptance: | 26 March 2021 |
Last Modified: | 03 May 2023 21:09 |
URI: | https://orca.cardiff.ac.uk/id/eprint/140528 |
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