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
With the rapid development of 5G base station construction, significant energy storage is installed to ensure stable communication. However, these storage re...
According to the energy consumption characteristics of the base station, a 5G base station energy consumption prediction model based on the LSTM network is constructed to provide data support for the subsequent BSES aggregation and collaborative scheduling.
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 research on 5G base station load forecasting technology can provide base station operators with a reasonable arrangement of energy supply guidance, and realize the energy saving and emission reduction of 5G base stations.
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