Zhu, Y., Li, K. orcid.org/0000-0001-6657-0522 and Zhang, L. orcid.org/0000-0002-4535-3200 (2025) Base station microgrid energy management in 5G networks - a brief review. In: Smart Grid and Cyber Security Technologies. The 2024 Intelligent Computing for Sustainable Energy and Environment (ICSEE2024), 13-15 Sep 2024, Suzhou, China. Communications in Computer and Information Science . Springer , Singapore ISBN 978-981-96-0224-7
Abstract
The number of 5G base stations (BSs) has soared in recent years due to the exponential growth in demand for high data rate mobile communication traffic from various intelligent terminals. The 5G BSs powered by microgrids with energy storage and renewable generation can significantly reduce the carbon emissions and operational costs. The base station microgrid energy management system (BSMGEMS) is crucial to unleash these potentials. This paper presents a brief review of BSMGEMS. The work begins with outlining the main components and energy consumptions of 5G BSs, introducing the configuration and components of base station microgrids (BSMGs), as well as categorizing the energy management systems (EMSs) and communication network topology. Subsequently, the dispatch optimization strategy and energy trading models are reviewed. The paper concludes with a few suggestions for future research.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This version of the proceedings paper has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-981-96-0225-4_1 . |
Keywords: | 5G base stations, energy management systems, energy consumption, scheduling optimization, energy trading |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 03 Jul 2024 09:48 |
Last Modified: | 17 Jan 2025 15:04 |
Published Version: | https://link.springer.com/chapter/10.1007/978-981-... |
Status: | Published |
Publisher: | Springer |
Series Name: | Communications in Computer and Information Science |
Identification Number: | 10.1007/978-981-96-0225-4_1 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:214198 |
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