Evaluation of Transformer Bushing Moisture Faults Based on Clustering Algorithms and TOPSIS

Abstract

With the continuous expansion of the scale of power grids, the amount of monitoring data of power equipment is growing and the reliability demand of power equipment is increasing. In order to cope with power transformer accidents caused by damp faults in oil-immersed bushings, this paper applies big data clustering technology to construct a bushing damp fault evaluation index system, and combines the posting progress obtained from TOPSIS method to achieve a quantitative assessment of the damp state of bushings. The effectiveness of this method is also verified with examples.