Hybrid quantum-classical stochastic programming
This study proposes a hybrid quantum-classical two-stage stochastic programming approach for the co-planning of BSs and PVs in
This model encompasses numerous energy-consuming 5G base stations (gNBs) and their backup energy storage systems (BESSs) in a virtual power plant to provide power support and obtain economic incentives, and develop virtual power plant management functions within the 5G core network to minimize control costs.
The 5G communication base station can be regarded as a power consumption system that integrates communication, power, and temperature coupling, which is composed of three major pieces of equipment: the communication system, energy storage system, and temperature control system.
Given the significant increase in electricity consumption in 5G networks, which contradicts the concept of communication operators building green communication networks, the current research focus on 5G base stations is mainly on energy-saving measures and their integration with optimized power grid operation.
This paper considers the peak control of base station energy storage under multi-region conditions, with the 5G communication base station serving as the research object. Future work will extend the analysis to consider the uncertainty of different types of renewable energy sources' output.
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