On Condition Monitoring Aspects of in-Service Power Transformers Using Computational Techniques

Abstract

In this paper, the application of artificial intelligent techniques on condition monitoring and diagnosis of power transformer has been reported. Enormous technological innovations have been reported by researchers to quantify the health assessment methodologies for in-service power transformers such as Artificial Neural Network, Fuzzy logic, Clustering techniques, and Expert systems for precise diagnostics and prognostics tasks. Albeit, numerous reports, and studies, prediction of accurate health status of an in-service power apparatus like transformer is still a challenge. An effort has been made in this paper to compile the outcome of various research tools with practical in-service data to get an overall status of existing technological breakthroughs in the emerging field of condition monitoring of transformer for the benefit of utilities and researchers. The prospective of condition monitoring and diagnosis technologies of a power transformer can be emulated for asset management and prevent catastrophic failures of power transformers.