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Big Data analytics in Smart Grids for renewable energy networks: Systematic review of information and communication technology tools

Authors :
Ramón Fernando Colmenares-Quintero
Darío Jesús Quiroga-Parra
Natalia Rojas
Kim E. Stansfield
Juan Carlos Colmenares-Quintero
Source :
Cogent Engineering, Vol 8, Iss 1 (2021)
Publication Year :
2021
Publisher :
Taylor & Francis Group, 2021.

Abstract

The industrial and economic development of the industrialized countries, from the nineteenth century, has gone hand in hand with the development of electricity, the internal combustion engine, computers, the Internet, data use, and the intensive use of knowledge focused on science and the technology. Most conventional energy sources have proven to be finite and exhaustible. In turn, the different production activities of goods and services using fossil fuels and conventional energy have significantly increased the pollution of the environment, and with it, contributed to global warming. The objective of this work was to carry out a theoretical approach to data analytics and business intelligence technologies applied to smart electrical-system networks with renewable energies. For this paper, a bibliometric and bibliographic review about Big Data Analytics, ICT tools of industry 4.0 and Business intelligence was carried out in different databases available in the public domain. The results of the analysis indicate the importance of the use of data analytics and business intelligence in the management of energy companies. The paper concludes by pointing out how business intelligence and data analytics are being applied in specific examples of energy companies and their growing importance in strategic and operational decision-making.

Details

Language :
English
ISSN :
23311916
Volume :
8
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Cogent Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.85e3ba933114a55be4821d4e17d29e2
Document Type :
article
Full Text :
https://doi.org/10.1080/23311916.2021.1935410