A multi-dimensional diagnostic fingerprint for Power Transformers

Power Transformers are the most critical assets in a power system after generators. They are costly, have long lead times for acquisition and their failure compromises the security of the system. As a result of this, a number of testing methods have been developed over time to appraise their condition with a view to extending their lives as well as predicting their end of life as early as possible. Typically these tests are administered at different times depending on the maintenance scheme adopted by the utility and analysed individually. This paper describes the development of a multi-dimensional fingerprint for transformer health estimation. Test results from a number of testing methods are analysed and a binary code system developed to more precisely pinpoint the transformer state.