Modeling and aggregated control of large-scale 5G base stations
Collaborating with the power system can provide energy incentives for 5G networks. On the other hand, the existing communication infrastructure in 5G networks allows network
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.
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.
• The 5G base station energy consumption prediction model based on LSTM proposed in this paper takes into account the energy consumption characteristics of 5G base stations. The prediction results have high accuracy and provide data support for the subsequent research on BSES aggregation and optimal scheduling.
The authors declare no conflicts of interest. Abstract 5G base stations (BSs) are potential flexible resources for power systems due to their dynamic adjustable power consumption. However, the ever-increasing energy consumption of 5G BSs place...
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