A Transformer Replacement Decision Method Based on Probability Assessment of Failure Rate

Abstract

Reasonable probability assessment of transformer failure rate (FR) is a critical reference to the transformer replacement work. At present, the lack of support theory for transformer replacement usually causes reliability and economy issues for power companies. For this reason, a transformer replacement decision method based on probability assessment of FR is proposed. Firstly, a first order model of transformer paper degradation is proposed. Then, the Weibull Distribution is used by Monte Carlo Simulation (MCS) to generate the variations of Degree of Polymerization (DP) along with time based on the historical data, and the transformer FR is determined. When the FR is higher than a pre-defined threshold value, the transformer should be replaced for reliability purpose. Finally, the effectiveness of the proposed method for the transformer replacement decision is verified by a typical engineering application.