Decision making on the state of transformers based on insulation condition using AHP and TOPSIS methods

Abstract

The evaluation and selection of state of transformers based on their mineral oil data are quite difficult. In this study, analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solutions (TOPSISs) are used as the multi-criteria decision support methodologies to provide a simple approach to rank transformers based on their mineral oil data and to help decision makers to identify the transformer, which is in the most critical state. AHP is exercised for both priority weight calculation and ranking of transformers. The AHP method is used for weight calculation, and then transformers are ranked using TOPSIS. Here, data of 69 in-service and 12 failed transformers in Tamil Nadu state in India is collected for assessment. From the results, transformers with good insulation condition are ranked at top, while the transformers are given lower ranks if they are found to have bad health. It is proved that decisions yielded by both methods are in agreement with reality.