Big Data Management in Smart Grids: Technologies and Challenges

被引:17
|
作者
Zainab, Ameema [1 ,2 ]
Ghrayeb, Ali [2 ]
Syed, Dabeeruddin [1 ,2 ]
Abu-Rub, Haitham [2 ]
Refaat, Shady S. [2 ]
Bouhali, Othmane [2 ]
机构
[1] Texas A&M Univ, Dept Elect & Comp Engn, College Stn, TX 77843 USA
[2] Texas A&M Univ Qatar, Dept Elect & Comp Engn, Doha, Qatar
关键词
Smart grids; Big Data; Companies; Cloud computing; Data mining; Predictive models; Data models; Apache spark; big data; data mining; Hadoop; indexing; management process; smart grid; stream mining; ANOMALY DETECTION; DATA ANALYTICS; MAP-REDUCE; FRAMEWORK; CONSUMPTION; PLATFORM; STREAM;
D O I
10.1109/ACCESS.2021.3080433
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Smart grids are re-engineering the electricity transmission and distribution system throughout the world. It is an amalgam of increased digital information with the electrical power grids. Managing the data generated from the grid efficiently is the key to successful knowledge extraction from the smart grid big data. Most of the scientific advancements are becoming data-driven and becoming an interesting area of research for data scientists. It is challenging the world computationally enough to develop new storage methods and data processing technologies. Managing big data involves data cleaning, integration of varied data sources, and decision-making applications. This paper focuses on the study of big data management and proposes a management process to help manage the data in the grid. Data management tools and techniques have been leveraged in understanding the sources and data types in the grid. The paper emphasizes the limitations of the existing solutions inclined towards applications of the smart grid big data.
引用
收藏
页码:73046 / 73059
页数:14
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