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

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.

Keywords

• capability maturity model
• distributed power generation
• big data
• smart power grids
• power engineering computing
• data management techniques
• grid-wide integration
• big data standards
• cmms
• smart grid standards
• smart grid dg
• smart grid distributed generation
• capability maturity models