Wireless Big Data Computing in Smart Grid

Kun Wang, Yunqi Wang, Xiaoxuan Hu, Yanfei Sun, Der Jiunn Deng, Alexey Vinel, Yan Zhang

Research output: Contribution to journalArticle

77 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number7909159
Pages (from-to)58-64
Number of pages7
JournalIEEE Wireless Communications
Volume24
Issue number2
DOIs
Publication statusPublished - 2017 Apr

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All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Wang, K., Wang, Y., Hu, X., Sun, Y., Deng, D. J., Vinel, A., & Zhang, Y. (2017). Wireless Big Data Computing in Smart Grid. IEEE Wireless Communications, 24(2), 58-64. [7909159]. https://doi.org/10.1109/MWC.2017.1600256WC