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A Comprehensive Review of the Current Status of Smart Grid Technologies for Renewable Energies Integration and Future Trends: The Role of Machine Learning and Energy Storage Systems.

Authors :
Kiasari, Mahmoud
Ghaffari, Mahdi
Aly, Hamed H.
Source :
Energies (19961073). Aug2024, Vol. 17 Issue 16, p4128. 38p.
Publication Year :
2024

Abstract

The integration of renewable energy sources (RES) into smart grids has been considered crucial for advancing towards a sustainable and resilient energy infrastructure. Their integration is vital for achieving energy sustainability among all clean energy sources, including wind, solar, and hydropower. This review paper provides a thoughtful analysis of the current status of the smart grid, focusing on integrating various RES, such as wind and solar, into the smart grid. This review highlights the significant role of RES in reducing greenhouse gas emissions and reducing traditional fossil fuel reliability, thereby contributing to environmental sustainability and empowering energy security. Moreover, key advancements in smart grid technologies, such as Advanced Metering Infrastructure (AMI), Distributed Control Systems (DCS), and Supervisory Control and Data Acquisition (SCADA) systems, are explored to clarify the related topics to the smart grid. The usage of various technologies enhances grid reliability, efficiency, and resilience are introduced. This paper also investigates the application of Machine Learning (ML) techniques in energy management optimization within smart grids with the usage of various optimization techniques. The findings emphasize the transformative impact of integrating RES and advanced smart grid technologies alongside the need for continued innovation and supportive policy frameworks to achieve a sustainable energy future. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19961073
Volume :
17
Issue :
16
Database :
Academic Search Index
Journal :
Energies (19961073)
Publication Type :
Academic Journal
Accession number :
179355110
Full Text :
https://doi.org/10.3390/en17164128