Reliability and condition assessment techniques for oil-immersed power equipment under varying temperatures: A review

Oil-immersed power transformers are important components in modern power grids, relying heavily on the integrity of their insulation systems. It consists of cellulose-based solid insulation and mineral or ester based insulating fluids. The insulation materials degrade over time due to electrical, thermal, mechanical and environmental pressures. Researchers have conducted accelerated aging tests in the lab to replicate real-life conditions to investigate how oil-immersed equipment degrades over time. The valuable techniques to reduce the lifespan of the insulation system enable the study of the material behavior and predict how long the insulation system will withstand. This review examines conventional and advanced transformer insulation assessment techniques, particularly emphasizing efficacy in cold-climate environments. It includes the degree of polymerization (DP), furfural analysis, and dissolved gas analysis (DGA) as well as advanced dielectric response methodologies, including FDS and PDC testing. The review also discusses low-temperature insulating material precision, challenges, and dependability issues. Emerging diagnostic approaches incorporating artificial intelligence, machine learning and optical sensing technologies offer promising improvements in early fault detection and condition monitoring. The acceleration of the deterioration process can lead to premature insulation failure and increased operational risks. Additionally, it discusses the integration of AI and machine learning for enhanced monitoring and the development of cold-resistant materials and fluids for improved transformer reliability in extreme environments.

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Publication Details

Journal
Energy Reports
Published
2025-08-22
DOI
https://doi.org/10.1016/j.egyr.2025.08.016
Citations
2
Primary Topic
Power Transformer Diagnostics and Insulation
Type
article
Field-Weighted Citation Impact
1.46

Funders

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article

Reliability and condition assessment techniques for oil-immersed power equipment under varying temperatures: A review

Xianhao Fan, Ji Liu, Mingze Zhang, Raheel Ahmed
2 citations
Energy Reports
Power Transformer Diagnostics and Insulation
1.46
article

Reliability and condition assessment techniques for oil-immersed power equipment under varying temperatures: A review

Xianhao Fan, Ji Liu, Mingze Zhang, Raheel Ahmed
article en
2 citations

Abstract

Oil-immersed power transformers are important components in modern power grids, relying heavily on the integrity of their insulation systems. It consists of cellulose-based solid insulation and mineral or ester based insulating fluids. The insulation materials degrade over time due to electrical, thermal, mechanical and environmental pressures. Researchers have conducted accelerated aging tests in the lab to replicate real-life conditions to investigate how oil-immersed equipment degrades over time. The valuable techniques to reduce the lifespan of the insulation system enable the study of the material behavior and predict how long the insulation system will withstand. This review examines conventional and advanced transformer insulation assessment techniques, particularly emphasizing efficacy in cold-climate environments. It includes the degree of polymerization (DP), furfural analysis, and dissolved gas analysis (DGA) as well as advanced dielectric response methodologies, including FDS and PDC testing. The review also discusses low-temperature insulating material precision, challenges, and dependability issues. Emerging diagnostic approaches incorporating artificial intelligence, machine learning and optical sensing technologies offer promising improvements in early fault detection and condition monitoring. The acceleration of the deterioration process can lead to premature insulation failure and increased operational risks. Additionally, it discusses the integration of AI and machine learning for enhanced monitoring and the development of cold-resistant materials and fluids for improved transformer reliability in extreme environments.

Energy ReportsVol. 14
Harbin University of Science and Technology (CN), Tsinghua University (CN)
State Grid Corporation of China, Science and Technology Project of State Grid
Affordable and clean energy
Openalex Percentile: Top 15%
Power Transformer Diagnostics and Insulation
1.46
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