Reliability and condition assessment techniques for oil-immersed power equipment under varying temperatures: A review
Raheel Ahmed, Ji Liu, Mingze Zhang, Xianhao Fan
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.