Health index for power transformer condition assessment: A comparison of three different techniques

Abstract

In practice, the condition state of Power Transformers (PT) is quantified by using Health Index (HI). This paper analyzes and compares three different state-of-the-art algorithms to compute HI. The first one uses a Weighted Sum Model (WSM), the second is based on a Fuzzy Inference System (FIS), and the third combines both techniques, i.e., WSM and FIS. These three approaches are tested in a PT fleet composed of 30 units. Results show that each approach produces different HI values for the same PTs. Therefore, decision making regarding the PT fleet will depend on the selected approach for HI calculation. This work proposes merging the knowledge involved in each analyzed approach by using a K-means clustering technique to overcome this drawback. This solution could help the asset manager to make adequate decisions regarding the maintenance scheduling of PT when there is uncertainty about the appropriate approach to be selected.