Comparison of Two Popular Methods for Transformer Weibull Lifetime Modelling

The paper is concerned with transformer Weibull lifetime modelling which is recognised as essential for effective asset management within electric utilities. Two popular and widely adopted methods, maximum likelihood estimation and median rank regression, are discussed and compared for their properties in estimating transformer lifetime data. To greatly mimic the field collected transformer lifetime data, Monte-Carlo simulations are conducted to generate multiple sets of transformer lifetime data with the censoring rate being set at 90% and sample size chosen as ranging from 60 to 1000. Weibull parameters are estimated for each sample set with both methods. Performance of each estimation method is then evaluated with respect to their corresponding relative difference between median value and the true value (RD) as well as the relative root mean square error (RRMSE) obtained for each sample size. It is found that the maximum likelihood method is superior to the median rank regression method due to the fact that it always provides smaller RD as well as RRMSE and is hence recommended to be used for transformer Weibull lifetime modelling.