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Issue No.04 - July-Aug. (2013 vol.15)
pp: 38-47
Yogesh Simmhan , University of Southern California
Saima Aman , University of Southern California
Alok Kumbhare , University of Southern California
Rongyang Liu , University of Southern California
Sam Stevens , University of Southern California
Qunzhi Zhou , University of Southern California
Viktor Prasanna , University of Southern California
This article focuses on a scalable software platform for the Smart Grid cyber-physical system using cloud technologies. Dynamic Demand Response (D²R) is a challenge-application to perform intelligent demand-side management and relieve peak load in Smart Power Grids. The platform offers an adaptive information integration pipeline for ingesting dynamic data; a secure repository for researchers to share knowledge; scalable machine-learning models trained over massive datasets for agile demand forecasting; and a portal for visualizing consumption patterns, and validated at the University of Southern California's campus microgrid. The article examines the role of clouds and their tradeoffs for use in the Smart Grid Cyber-Physical System.
Smart grids, Cloud computing, Optimization, Microgrids, Information management, Data handling, Big data, Scientific computing,Dynamic Demand Response, cloud computing, software platform, big data analytics, cyber-physical systems, smart grid, workflows, stream processing, machine learning, scientific computing
Yogesh Simmhan, Saima Aman, Alok Kumbhare, Rongyang Liu, Sam Stevens, Qunzhi Zhou, Viktor Prasanna, "Cloud-Based Software Platform for Big Data Analytics in Smart Grids", Computing in Science & Engineering, vol.15, no. 4, pp. 38-47, July-Aug. 2013, doi:10.1109/MCSE.2013.39
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