Research and Application of Big Data Analysis of Power Equipment Condition

With the development of smart grid and the rapid expansion of power grid scale, it is very difficult to grasp the operational state of power equipment timely and accurately. In recent years, the informationization of electric power has reached a high level. Data from condition monitoring system, power production management system, operation dispatching system, and environmental meteorology system are gradually integrated and shared. Big data technologies provide new technical methods and tools for power equipment condition assessment and fault diagnosis. We put forward the connotation, purpose, data characteristics, and basic framework for big data analysis of power equipment condition, in consideration of the status quo of big data technology and data mining analysis in power equipment condition assessment. The key techniques of big data integration, conversion, cleaning, distributed storage and processing, data mining with high efficiency, and data-driven analysis model for power equipment condition assessment are comprehensively elaborated. According to the total demand analysis of power equipment condition assessment, the methods and effects of big data techniques in application scenarios such as condition evaluation, anomaly detection, fault prediction and intelligent diagnosis are summarized and discussed. Finally, the major problems in research and application are proposed, and the development trend of the relative technologies is prospected. © 2018, High Voltage Engineering Editorial Department of CEPRI. All right reserved.