Cloud-Based Software Platform for Big Data Analytics in Smart Grids

Author

Simmhan, Yogesh ; Aman, Saima ; Kumbhare, Alok ; Rongyang Liu ; Stevens, Sam ; Qunzhi Zhou ; Prasanna, Viktor

Author_Institution

Univ. of Southern California, Las Angeles, CA, USA

Volume

15

Issue

4

fYear

2013

fDate

July-Aug. 2013

Firstpage

38

Lastpage

47

Abstract

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 Sagileystem.

Keywords

cloud computing; learning (artificial intelligence); power engineering computing; smart power grids; D²R; Smart Grid Cyber-Physical Sagileystem; University of Southern California; agile demand forecasting; big data analytics; campus microgrid; cloud-based software platform; dynamic demand response; information integration pipeline; ingesting dynamic data; intelligent demand-side management; scalable machine-learning models; scalable software platform; smart grid cyber-physical system; smart grids; smart power grids; Big data; Cloud computing; Data handling; Information management; Microgrids; Optimization; Scientific computing; Smart grids; Dynamic Demand Response; big data analytics; cloud computing; cyber-physical systems; machine learning; scientific computing; smart grid; software platform; stream processing; workflows;

fLanguage

English

Journal_Title

Computing in Science & Engineering

Publisher

ieee

ISSN

1521-9615

Type

jour

DOI

10.1109/MCSE.2013.39

Filename

6475927