Risk‐based approach for power transformer replacement considering temperature, apparent age, and expected capacity

Due to the limited availability of end‐of‐life failure data of power transformers by electric utilities, planning the replacement of power transformers is a challenging task for utility engineers. Transformers can be replaced based on their health indices, but they do not allow utility engineers to quantify risks posed by transformer failures. In that context, the study proposes a novel risk‐based approach to plan the replacement of aged power transformers considering their temperature, apparent age, and expected capacity. The approach comprises a methodology that incorporates power transformers' winding hottest‐spot temperature and apparent age into the conventional end‐of‐life failure model, a methodology that calculates the expected capacity of power transformers, a novel transformer ranking index, and a methodology that calculates the optimum year of replacement. Subtransmission and distribution substations were included in the IEEE Reliability Test System to evaluate the performance of the approach. The results show that incorporating the winding hottest‐spot temperature and the apparent age into the end‐of‐life failure model can make a significant improvement on transformer replacement decisions in the event of limited availability of failure data. Results further suggest that end‐of‐life failures of fans and oil pumps can have an impact on the prioritisation of transformer replacement.