A Big Data platform for smart meter data analytics

Tom Wilcox, Nanlin Jin*, Peter Flach, Joshua Thumim

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)

12 Citations (Scopus)

Abstract

Smart grids have started generating an ever increasingly large volume of data. Extensive research has been done in meter data analytics for small data sets of electrical grid and electricity consumption. However limited research has investigated the methods, systems and tools to support data storage and data analytics for big data generated by smart grids. This work has proposed a new core-broker-client system architecture for big data analytics. Its implemented platform is named Smart Meter Analytics Scaled by Hadoop (SMASH). Our work has demonstrated that SMASH is able to perform data storage, query, analysis and visualization tasks on large data sets at 20 TB scale. The performance of SMASH in storing and querying large quantities of data are compared with the published results provided by Google Cloud, IBM, MongoDB, and AMPLab. The experimental results suggest that SMASH provides industry a competitive and easily operable platform to manage big energy data and visualize knowledge, with potential to support data-intensive decision making.

Original languageEnglish
Pages (from-to)250-259
Number of pages10
JournalComputers in Industry
Volume105
Early online date22 Jan 2019
DOIs
Publication statusPublished - Feb 2019

Keywords

  • Big data
  • Meter data analytics
  • Smart grid

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