Differentially Private Energy Sharing Among Smart Grid-Powered Base Stations

Allowing for energy sharing among base stations (BSs), we investigate a distributed BS system equipped with renewable power units and energy storage batteries. While offering significant benefits, this raises concerns about privacy protection. By leveraging the Laplace mechanism, our differential privacy (DP)-based method safeguards energy consumption data related to processing data tasks from different BSs. To address a long-term average cost minimization problem, we propose a distributed online algorithm for efficient energy sharing. We demonstrate that the boundary constraints of energy storage batteries can still be satisfied by choosing parameters appropriately. We provide a theoretical bound for the optimality gap and validate the effectiveness of our theoretical results. Numerical results indicate our algorithm can potentially reduce the average costs of BSs by up to 34%.

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Publication Details

Published
2024-10-07
DOI
https://doi.org/10.1109/vtc2024-fall63153.2024.10757557
Citations
2
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
Field-Weighted Citation Impact
0.42

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article

Differentially Private Energy Sharing Among Smart Grid-Powered Base Stations

Bochun Wu, Abbas Jamalipour, Kai Li, Fei Wang et al.
2 citations
Energy Harvesting in Wireless Networks
0.42
article

Differentially Private Energy Sharing Among Smart Grid-Powered Base Stations

Bochun Wu, Abbas Jamalipour, Kai Li, Fei Wang, Wei Ni, Liwan Qi
article en
2 citations

Abstract

Allowing for energy sharing among base stations (BSs), we investigate a distributed BS system equipped with renewable power units and energy storage batteries. While offering significant benefits, this raises concerns about privacy protection. By leveraging the Laplace mechanism, our differential privacy (DP)-based method safeguards energy consumption data related to processing data tasks from different BSs. To address a long-term average cost minimization problem, we propose a distributed online algorithm for efficient energy sharing. We demonstrate that the boundary constraints of energy storage batteries can still be satisfied by choosing parameters appropriately. We provide a theoretical bound for the optimality gap and validate the effectiveness of our theoretical results. Numerical results indicate our algorithm can potentially reduce the average costs of BSs by up to 34%.

Commonwealth Scientific and Industrial Research Organisation (AU), The University of Sydney (AU), University of Cambridge (GB), Fudan University (CN), Hexi University (CN)
Natural Science Foundation of Gansu Province
Affordable and clean energy
Openalex Percentile: Top 35%
Energy Harvesting in Wireless Networks
0.42
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