Benda, D., Chu, X. orcid.org/0000-0003-1863-6149, Sun, S. et al. (2 more authors) (2019) Renewable energy sharing among base stations as a min-cost-max-flow optimization problem. IEEE Transactions on Green Communications and Networking, 3 (1). pp. 67-78. ISSN 2473-2400
Abstract
Limited work has been done to optimize the power sharing among base stations (BSs) while considering the topology of the cellular network and the distance-dependent power loss (DDPL) in the transmission lines. In this paper, we propose two power sharing optimization algorithms for energy-harvesting BSs: the max-flow (MF) algorithm and the min-cost-max-flow (MCMF) algorithm. The two proposed algorithms minimize the power drawn from the main grid by letting BSs with power surpluses transmit harvested power to BSs with deficits. The MCMF algorithm has an additional DDPL cost associated with each transmission line. Hence, the MCMF algorithm shares the harvested power over shorter distances and loses less power during the transmission than the MF algorithm. Our numerical results show that for a fully connected cellular network, i.e., every pair of BSs can share power, with a moderate power loss coefficient per l(R⁺) meters of transmission line, the MCMF algorithm saves up to 10%, 22%, and 30% more main grid power than the MF algorithm for 5, 10, and 15 BSs uniformly distributed in a square area of l² square meters, respectively.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Cellular network; min-cost-max-flow; max-flow; energy harvesting; energy sharing |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - HORIZON 2020 645705 - DECADE |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Dec 2018 16:15 |
Last Modified: | 11 Nov 2021 11:38 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Identification Number: | 10.1109/TGCN.2018.2876005 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:139707 |