Modeling of replacement alternatives for power transformer populations

The age of the majority of power transformers installed in the western electricity network reaches 30 to 60 years and replacement on short term seems eminent. A technically sound policy concerning the replacement of these assets requires a model that estimates the life expectancies of individual components and from that calculates parameters related to the behavior of a population of assets as a whole. A probabilistic approach is adopted and is applied to thermal degradation of the transformer paper insulation. In this paper, we will focus on the determination of the population reliability from individual reliabilities. These individual reliabilities are based on Arrhenius modeling of paper insulation degradation, including the inherent uncertainty in the parameters involved. A statistical failure model is used to obtain the population reliability figures. The modeling method is demonstrated on two populations of power transformers in The Netherlands to evaluate the different replacement alternatives. Using the model, strategies can be defined to maximize transformer utilization and postpone replacement. The downside is the need to replace the complete fleet in a relatively short time afterwards.