Lifetime Modeling and Management of Transformers

This work have studied and developed lifetime estimation methods for the power transformer and how these could be used for asset management purposes. It is research performed in the intersection of the fields of reliability theory, statistical analysis, and stochastic process theory applied to lifetime estimations and management of transformers. The chosen approaches are the following. The thesis assess the effect of thermal stresses on the lifetime of the transformer. The effect of hotspot temperature is assessed with a loss of life measure. Within this study, improvements to the thermal model have been made. The thesis moves on to an alternative method for lifetime estimation in which diagnostic measurements are forecasted using a stochastic process and iterative realizations of this stochastic process is used to estimate a probability distribution for the transformer. The thesis moves on to study the loss of life measure from a system perspective by calculating the loss of life estimate from the load profiles of cold load pickup, increased electric vehicle penetration, and normal operation. These are applied in such a way that they can be used for asset management purposes. Then, the thesis uses estimates of failure times with the aim to reach a probabilistic, dynamic capacity rating selection method which use a failure rate which is conditioned on the time-dependent load level.