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Digital Architecture for Monitoring and Operational Analytics of Multi-Vector Microgrids Utilizing Cloud Computing, Advanced Virtualization Techniques, and Data Analytics Methods.
- Source :
-
Energies (19961073) . Aug2023, Vol. 16 Issue 16, p5908. 19p. - Publication Year :
- 2023
-
Abstract
- Microgrids are considered a viable solution for achieving net-zero targets and increasing renewable energy integration. However, there is a lack of conceptual work focusing on practical data analytics deployment schemes and case-specific insights. This paper presents a scalable and flexible physical and digital architecture for extracting data-driven insights from microgrids, with a real-world microgrid utilized as a test-bed. The proposed architecture includes edge monitoring and intelligence, data-processing mechanisms, and edge–cloud communication. Cloud-hosted data analytics have been developed in AWS, considering market arrangements between the microgrid and the utility. The analysis involves time-series data processing, followed by the exploration of statistical relationships utilizing cloud-hosted tools. Insights from one year of operation highlight the potential for significant operational cost reduction through the real-time optimization and control of microgrid assets. By addressing the real-world applicability, end-to-end architectures, and extraction of case-specific insights, this work contributes to advancing microgrid design, operation, and adoption. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19961073
- Volume :
- 16
- Issue :
- 16
- Database :
- Academic Search Index
- Journal :
- Energies (19961073)
- Publication Type :
- Academic Journal
- Accession number :
- 170746427
- Full Text :
- https://doi.org/10.3390/en16165908