Bayesian estimation of electrical transformer parameters

Electrical transformers are among the oldest and most well studied devices in electrical engineering. Accurate knowledge of the transformers parameters is still required for modeling and simulation of the behavior of the transformer in all scenarios - for the single component as well as for the transformer within a larger system. Measuring the transformer parameters requires several experiments covering both, AC and DC-current measurements. In this work we will present a model based approach to estimate transformer parameters from a reduced set of measurements. This includes the estimation of the DC resistance of the transformer from AC measurements only. The methodology is based on the Bayesian framework, which provides a powerful tool for gaining knowledge about the parameters of interest from indirect measurement data.