Advanced monitoring and on-line health diagnosis of single-phase transformers

Abstract

Transformers range in size from a few kVA to several hundred MVA are one of the most critical components of power system with with replacement costs around millions of dollars for power transformers. A sudden in-service failure of a transformer not only results in substantial economic losses but also can result in death of utility personnel apart from the environmental damages caused and grid instability induced. The condition assessment and life estimation of a transformer is an important part of reliable power system operation. The equivalent parameters of a transformer are not affected by external faults and change only in the presence of internal abberations making them suitable for internal condition assessment of transformers. Presently, there is no accurate measurement method for the transformer winding parameters and generally require the transformer to be disconnected from the power system. A new simple algorithm for extracting transformer winding parameters which can be implemented online is presented in this paper. This method doesn't require the transformer to be disconnected from the power grid. The primary and secondary currents and voltages are taken as inputs and winding parameters are obtained by solving the equivalent circuit equations in real time continuously which allows for interpretation and detection of faults in real-time. The proposed method has been tested and validated by simulations. Different cases of parameter variations and their possible interpretations are discussed in order to detect any incipient faults or anomalies in an in-service transformer which serve as advance alarms.