An optimal dispatch strategy for 5G base stations equipped with battery swapping cabinets

Qi Qi, Deying Zhang, Xiang Hu, Xiao Li and Bing Qi

Applied Energy, 2025, vol. 392, issue C, No S0306261925006440

Abstract: The escalating deployment of 5G base stations (BSs) and self-service battery swapping cabinets (BSCs) in urban distribution networks has raised concerns regarding electricity consumption and power efficiency due to their significant energy demands and large numbers. To address this challenge, leveraging the idle energy resources in 5G BS and BSC for distribution network dispatch can alleviate their impact on peak-valley differentials and optimize their benefits. Moreover, as BSCs are predominantly situated at communication tower sites, they not only enhance the backup power capacity for communication loads but also share the power supply capacity with 5G BSs. Consequently, coordinating the dispatch of both 5G BS and BSC can result in enhanced cumulative benefits. Therefore, this paper proposes an optimal dispatch strategy for 5G BSs equipped with BSCs. Firstly, a joint dispatch framework is established, where the idle capacity of batteries in 5G BS and BSC responds to time-of-use tariff and demand response signals. Then, the individual and joint dispatchable capabilities of 5G BS and BSC are formulated, considering their energy storage configuration, operational characteristics and service quality constraints. Following this, an optimal dispatch model of the joint system is developed to maximize the daily operational profit for 5G BS and BSC. The soft actor-critic algorithm is then employed to efficiently generate charging and discharging strategies for all dispatchable units, ensuring communication service quality and meeting battery swapping demands. The solution algorithm is trained and tested in a Python simulation environment, with results validating the effectiveness and efficiency of the proposed strategy in ensuring the timely dispatch of 5G BS and BSC while maximizing their economic advantages.

Keywords: 5G base station; Battery swapping cabinet; Optimal dispatch; Reinforcement learning; Soft actor-critic algorithm (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2025.125914

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