Comprehensive regression modelling for evaluating chemical properties of transformer oil under thermal ageing conditions

Abdi, Sifeddine, Besseri, Boubakar Achraf, Harid, Noureddine, Haddad, Abderrahmane ORCID: https://orcid.org/0000-0003-4153-6146 and Boubakeur, Ahmed 2025. Comprehensive regression modelling for evaluating chemical properties of transformer oil under thermal ageing conditions. Presented at: IEEE International Conference on Dielectric Liquids (ICDL), Lodz, Poland, 18-22 May 2025. 2025 IEEE International Conference on Dielectric Liquids (ICDL). 2025 IEEE International Conference on Dielectric Liquids (ICDL). IEEE, pp. 1-4. 10.1109/icdl63868.2025.11068239

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Abstract

Abstract This study examines thermal ageing effects on transformer oil’s acidity and water content using an innovative exponential regression approach. Mineral oil samples were aged at 80 °C, 100 °C, 120 °C, and 140 °C for 5000 hours, with properties measured at 500-hour intervals. Results reveal temperature-dependent degradation, showing accelerated deterioration above 100 °C. The exponential model achieved strong correlations (R² > 90%) for both acidity and water content, demonstrating its effectiveness in predicting oil ageing. These findings provide valuable insights for transformer condition assessment and maintenance planning, highlighting the model’s potential for practical application in power system reliability management. The research establishes clear relationships between thermal stress, chemical degradation, and measurable oil properties, offering a robust framework for transformer health monitoring.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Schools > Engineering
Publisher:	IEEE
ISBN:	978-1-6654-7758-1
ISSN:	2153-3733
Last Modified:	01 Aug 2025 10:30
URI:	https://orca.cardiff.ac.uk/id/eprint/180195

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