Intelligent Identification over Power Big Data: Opportunities, Solutions, and Challenges

被引:2
|
作者
Luo, Liang [1 ]
Li, Xingmei [1 ]
Yang, Kaijiang [1 ]
Wei, Mengyang [1 ]
Chen, Jiong [1 ]
Yang, Junqian [1 ]
Yao, Liang [2 ]
机构
[1] Yunnan Power Grid Co Ltd, Dali Power Supply Bur, Dali 671000, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing 210044, Peoples R China
来源
关键词
Data acquisition; data storage; anomaly detection; service fault-tolerant scheduling; FAULT-TOLERANCE; ANOMALY DETECTION; ENERGY MANAGEMENT; SCHEDULING SCHEME; INTERNET; AWARE; EDGE; SYSTEM; ALGORITHM; SERVICES;
D O I
10.32604/cmes.2022.021198
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The emergence of power dispatching automation systems has greatly improved the efficiency of power industry operations and promoted the rapid development of the power industry. However, with the convergence and increase in power data flow, the data dispatching network and the main station dispatching automation system have encountered substantial pressure. Therefore, the method of online data resolution and rapid problem identification of dispatching automation systems has been widely investigated. In this paper, we perform a comprehensive review of automated dispatching of massive dispatching data from the perspective of intelligent identification, discuss unresolved research issues and outline future directions in this area. In particular, we divide intelligent identification over power big data into data acquisition and storage processes, anomaly detection and fault discrimination processes, and fault tracing for dispatching operations during communication. A detailed survey of the solutions to the challenges in intelligent identification over power big data is then presented. Moreover, opportunities and future directions are outlined.
引用
收藏
页码:1565 / 1595
页数:31
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