A common data architecture for energy data analytics

The Internet of Things (IoT) is creating a major shift from the traditional approaches to operating and maintaining all energy systems. With the proliferation of cheap sensors, power grids are generating vast amounts of data and there is an increasing interest around data-driven decision making, or...

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Bibliographic Details
Published in2017 IEEE International Conference on Smart Grid Communications (SmartGridComm) pp. 417 - 422
Main Authors Malik, Mayank, Tabone, Michaelangelo, Chassin, David P., Kara, Emre Can, Guha, Ramanathan V., Kiliccote, Sila
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2017
Subjects
Buildings
Computer architecture
Data collection
Generators
Memory
Power systems
Temperature measurement
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Summary:The Internet of Things (IoT) is creating a major shift from the traditional approaches to operating and maintaining all energy systems. With the proliferation of cheap sensors, power grids are generating vast amounts of data and there is an increasing interest around data-driven decision making, or more broadly, energy analytics. Due to the inherent nature of device and data ownership in the power grids, these analytics efforts have been siloed. Energy analytics developers create databases for monolithic applications that lack the infrastructure to quickly transform data between computational resources and persistent data storage, easy dissemination and validation of results, and support integration. We propose a data architecture that supports broader use of data technologies and systems integration guided by publish and subscribe architecture, and polyglot persistence. We provide use cases to discuss our design choices using the electric power grid as the main application domain. However, we believe that the energy industry as a whole can benefit from the proposed architecture.
DOI:10.1109/SmartGridComm.2017.8340736