Overview of Big Data Analytics Technologies in Smart Grid
Aditya Arya1, Sridhar S2
1Aditya Arya, Department of Electrical and Electronics Engineering, MS Ramaiah Institute of Technology, Bangalore (Karnataka), India.
2Dr. Sridhar S, Department of Electrical and Electronics Engineering, MS Ramaiah Institute of Technology, Bangalore (Karnataka), India.
Manuscript received on 02 December 2022 | Revised Manuscript received on 13 December 2022 | Manuscript Accepted on 15 January 2023 | Manuscript published on 30 January 2023 | PP: 36-45 | Volume-11 Issue-5, January 2023 | Retrieval Number: 100.1/ijrte.E73880111523 | DOI: 10.35940/ijrte.E7388.0111523
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Smart grids have become an essential component of modern society due to their interconnected nature. In the smart grid, unprecedented amounts of data will be created continuously due to the advanced sensor infrastructure. Therefore, analyzing smart grid data is becoming increasingly critical to delivering electricity and managing consumption in the business and physical sectors. Modernizing the grid requires data science, despite the challenges of integrating data analytics into the enterprise. A review of big data management & analysis in the smart grid is presented in this paper. Data analytics and its role in big data management are discussed in this paper along with the challenges of implementing those analytics, and how they can help achieve clean, reliable, and efficient grids. The paper supports Apache Flink due to native streaming for use cases that call for minimal latency, while Apache Spark is better suited for batch data processing.
Keywords: Smart Grid, Big Data, Intelligent Grid, Grid Analytics.
Scope of the Article: Big Data Analytics