Review on Evolution of Intelligent Algorithms for Transformer Condition Assessment

Transformers are playing an increasingly significant part in energy conversion, transmission, and distribution, which link various resources, including conventional, renewable, sustainable energy, from generation to consumption. Power transformers their components vulnerable operational factors during entire life cycle, may lead catastrophic failures, irreversible revenue losses, power outages. Hence, it is crucial investigate transformer condition assessment grasp the operating state accurately reduce failures costs enhance reliability performance. In this context, comprehensive data mining analysis based on intelligent algorithms of great significance for promoting comprehensiveness, efficiency, accuracy assessment. article, attempt provide reveal current status evolution a better understanding research perspectives, unified framework survey new findings rapidly-advancing field presented. First, failure statistics outlined, developing mechanism internal latent fault investigated. Then, combination with demands tasks each stage under big data, we analyze source in-depth redefine concept architecture Furthermore, typical methods widely used mainly divided into rule, information fusion, artificial intelligence. The also elaborated, differentiated evaluation, uncertainty methods, analysis. Finally, future directions discussed.