Real-Time Complex Event Processing and Analytics for Smart Grid

被引:18
|
作者
Liu, Guangyi [1 ]
Zhu, Wendong [1 ]
Saunders, Chris [1 ]
Gao, Feng [1 ]
Yu, Yang [2 ]
机构
[1] SGRI North Amer, Santa Clara, CA 95054 USA
[2] Stanford Univ, Palo Alto, CA 94304 USA
来源
关键词
Smart Grid; Big Data; Lambda Architecture; Complex Event Processing; Real-Time Analytics;
D O I
10.1016/j.procs.2015.09.169
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Electric power networks are among the world's most complex human-made systems. The developing smart grid is an inherently complex system which is rapidly evolving in both definition and implementation. Deployment of advanced technologies within the electric utility sector and usage of state-of-the-art computing systems provides companies with innovative capabilities to forecast electricity demand, influence customer usage patterns, create demand response program, optimize unit commitment, and prevent power outages. At the same time, these advances also lead to the generation of unprecedented data volumes, high data communications requirements, and increased system complexity. Utility companies must be capable of high-volume, high-speed data management and advanced analytics which are designed to transform data into actionable insights, if they strive to successfully implement a modern smart grid. As smart grid operations will leverage Advanced Metering Infrastructure (AMI) to drive more real time decision making and operational activities, complex event processing and stream computing are needed for the modern smart grid. This paper explores the challenges and benefits of transitioning to a smart grid, and explores new architectural approaches built on Lambda Architecture and other emerging software standards which may more effectively leverage established forms of complex event processing. (C) 2015 The Authors. Published by Elsevier B.V.
引用
收藏
页码:113 / 119
页数:7
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