Ensuring timely repair of power transformers based on data of complex diagnostics

• Main Authors: Sultanov Makhsud, Zenina Elena, Shamigulov Peter, Lunenko Valentina, Zhelyaskova Olga
• Format: Article
• Language: English
• Published: EDP Sciences 2021-01-01
• Series: E3S Web of Conferences
• Online Access: https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/64/e3sconf_suse2021_01034.pdf

Timely diagnosis of power transformers is an essential component of ensuring reliable and safe operation of power stations and substations, on which the reliability of the power system depends. Detection of defects in the initial stage allows to maintain reliable operation of transformers, helps to define the "life cycle" and simplify the planning of their replacement. The paper presents an analysis of existing approaches to the creation of power equipment diagnostics systems using the example of power transformers. A neural network model has been developed, demonstrating the possibility of using power transformers to estimate the current residual resource based on the analysis of available diagnostic data.