A Two-Level Framework to Fault Diagnosis and Decision Making for Power Transformers

Power transformers are important equipment of a substation from the generation, transmission, and distribution of electricity to end users. The costs associated with purchasing a power transformer in the voltage class of 500 kV (100 MVA) are a few million. The fines imposed by regulatory agencies are significant when there is unavailability of equipment for any defect or failure. Therefore, energy companies have been struggling in preventive and predictive maintenance in order to maintain this equipment in an effective maintenance program, avoiding the occurrence of failures. There are various techniques that are utilized for diagnosis and analysis of transformer failure, but little has been discussed about mechanisms that assist in decision making when it is necessary to overload the transformer, especially in emergency situations. In this paper, we present a framework that unifies the step of fault diagnosis of power transformers with the process of decision making, considering the current operating conditions as well as the life of the equipment. The assistance to the decision-making methodology is based on risk analysis with indicators derived from the failure rate and Arrhenius theory. The validation of the method is performed with a case study using data from a utility.