Wireless Big Data Computing in Smart GridShow others and affiliations
2017 (English)In: IEEE wireless communications, ISSN 1536-1284, E-ISSN 1558-0687, Vol. 24, no 2, p. 58-64Article in journal (Refereed) Published
Abstract [en]
The development of smart grid brings great improvement in the efficiency, reliability, and economics to power grid. However, at the same time, the volume and complexity of data in the grid explode. To address this challenge, big data technology is a strong candidate for the analysis and processing of smart grid data. In this article, we propose a big data computing architecture for smart grid analytics, which involves data resources, transmission, storage, and analysis. In order to enable big data computing in smart grid, a communication architecture is then described consisting of four main domains. Key technologies to enable big-data-aware wireless communication for smart grid are investigated. As a case study of the proposed architecture, we introduce a big-data- enabled storage planning scheme based on wireless big data computing. A hybrid approach is adopted for the optimization including GA for storage planning and a game theoretic inner optimization for daily energy scheduling. Simulation results indicate that the proposed storage planning scheme greatly reduce.
Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Press, 2017. Vol. 24, no 2, p. 58-64
Keywords [en]
Smart grids, Big Data, Wireless communication, Computer architecture, Distributed databases, Energy storage
National Category
Communication Systems Telecommunications
Identifiers
URN: urn:nbn:se:hh:diva-33750DOI: 10.1109/MWC.2017.1600256WCISI: 000400375200010Scopus ID: 2-s2.0-85018275335OAI: oai:DiVA.org:hh-33750DiVA, id: diva2:1090856
Funder
Knowledge Foundation
Note
This work is supported by NSFC (61572262); NSF of Jiangsu Province (BK20141427); NUPT (NY214097); Open research fund of Key Lab of Broadband Wireless Communication and Sensor Network Technology (NUPT), Ministry of Education (NYKL201507); Qinlan Project of Jiangsu Province; The projects 240079/F20 funded by the Research Council of Norway; the project Security in IoT for Smart Grids, with number 248113/070 part of the IKTPLUSS program funded by the Norwegian Research Council, and the Knowledge Foundation (KSS) Sweden.
2017-04-252017-04-252018-03-21Bibliographically approved