A Probabilistic Maintenance Scheme Evaluation Method for Transformer Based on Failure Rate

Reasonable maintenance for power transformer is critical to the long-term security operation of transformer. At present, the lack of support theory for transformer maintenance decision usually causes reliability and economy issues for power companies, which may cause "over maintenance" or "owing maintenance" problems. For this reason, a probabilistic maintenance scheme evaluation method for transformer based on failure rate is proposed by simulation of the health states of transformer with unexpected operation stress. Firstly, a first order model of transformer paper degradation is proposed to represent the health state of a transformer. Then, variations of Degree of Polymerization (DP) along with time are randomly generated using Monte Carlo Simulation (MCS) based on the Weibull Distribution under different maintenance schemes. Then the failure rate (FR) curve of transformer is then determined. When the FR is higher than a pre-defined threshold value, the transformer should be replaced for reliability purpose. The effectiveness of the proposed maintenance scheme evaluation method is verified by a typical engineering application. Simulation results show that it can be used to determine an optimum maintenance scheme for transformer to avoid failure risk and reduce the maintenance cost of power companies.