Adapting big data standards, maturity models to smart grid distributed generation: Critical review

Aditya Sundararajan, Alexander S. Hernandez, Arif I. Sarwat

Research output: Contribution to journalReview articlepeer-review

15 Scopus citations

Abstract

Big data standards and capability maturity models (CMMs) help developers build applications with reduced coupling and increased breadth of deployment. In smart grids, stakeholders currently work with data management techniques that are unique and customised to their own goals, thereby posing challenges for grid-wide integration and deployment. Although big data standards and CMMs exist for other domains, no work in the literature considers adapting them to smart grids, which will benefit from both. Further, existing smart grid standards and CMMs do not fully account for big data challenges. This study bridges the gap by analysing the role of big data in smart grids, and explores if and how big data standards and CMMs can be adapted specifically to ten distributed generation (DG) use-cases that use big data. In doing so, this work provides a useful starting point for researchers and industry members developing standards and CMM assessments for smart grid DG.

Original languageEnglish
Pages (from-to)508-519
Number of pages12
JournalIET Smart Grid
Volume3
Issue number4
DOIs
StatePublished - Aug 1 2020
Externally publishedYes

Funding

This work was supported by the National Science Foundation (NSF) under the CNS division, grant no. 1553494.

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