Proceedings of the 2nd Annual International Conference on Advanced Material Engineering (AME 2016)

Research on Application of Big Data Technique in Smart Distribution Grids

Authors
Da-Jiang Ren
Corresponding Author
Da-Jiang Ren
Available Online June 2016.
DOI
10.2991/ame-16.2016.220How to use a DOI?
Keywords
Smart Distribution Grids, Big Data, Energy Management System.
Abstract

Smart grid is a complete automation system, where large pool of sensors is embedded in the existing power grids system for controlling and monitoring it by utilizing modern information technologies. The data collected from these sensors are huge and have all the characteristics to be called as Big Data. The Smart-grid can be made more intelligent by processing and deriving new information from these data in real time. This paper presents Apache spark as an energy management system which is suitable for storing and performing Big Data analytics on smart grid data for applications like automatic demand response and real time pricing.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd Annual International Conference on Advanced Material Engineering (AME 2016)
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
10.2991/ame-16.2016.220
ISSN
2352-5401
DOI
10.2991/ame-16.2016.220How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Da-Jiang Ren
PY  - 2016/06
DA  - 2016/06
TI  - Research on Application of Big Data Technique in Smart Distribution Grids
BT  - Proceedings of the 2nd Annual International Conference on Advanced Material Engineering (AME 2016)
PB  - Atlantis Press
SP  - 1354
EP  - 1356
SN  - 2352-5401
UR  - https://doi.org/10.2991/ame-16.2016.220
DO  - 10.2991/ame-16.2016.220
ID  - Ren2016/06
ER  -