Research on fault prediction and diagnosis of power equipment based on big data

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. Combined with the current status of the application of big data technology and data mining analysis methods in equipment statu...

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Bibliographic Details
Published in2022 Power System and Green Energy Conference (PSGEC) pp. 1195 - 1199
Main Authors Liangzhi, Yin, Ying, Li, Zhuo, Zhao, Jiafeng, Wang, Nuodi, Wang, Xuan, Wang, Jinglin, Guan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2022
Subjects
Big Data
Data mining
Electric power big data
fault diagnosis
fault prediction algorithm
Prediction algorithms
Smart grids
Soft sensors
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Summary: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. Combined with the current status of the application of big data technology and data mining analysis methods in equipment status assessment, this paper expounds the connotation and purpose, data sources and characteristics, basic framework and key technical issues involved in big data analysis of power equipment status, and summarizes and discusses big data. Typical application scenarios and application effects of technology in power equipment status assessment, and propose challenges in research and application as well as future development trends.
DOI:10.1109/PSGEC54663.2022.9881104