Risk assessment algorithm for power transformer fleets based on condition and strategic importance

Abstract

In every electric power system, power transformers (PT) play a critical role. Under ideal circumstances, PT should receive the utmost care to maintain the highest operative condition during their lifetime. Through the years, different approaches have been developed to assess the condition and the inherent risk during the operation of PT. However, most proposed methodologies tend to analyze PT as individuals and not as a fleet. A fleet assessment helps the asset manager make sound decisions regarding the maintenance scheduling for groups of PT with similar conditions. This paper proposes a new methodology to assess the risk of PT fleets, considering the technical condition and the strategic importance of the units. First, the state of the units was evaluated using a health index (HI) with a fuzzy logic algorithm. Then, the strategic importance of each unit was assessed using a weighting technique to obtain the importance index (II). Finally, the analyzed units with similar HI and II were arranged into a set of clusters using the k-means clustering technique. A fleet of 19 PTs was used to validate the proposed method. The obtained results are also provided to demonstrate the viability and feasibility of the assessment model.