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This project demonstrates the application of machine learning techniques in predicting energy consumption for 5G base stations. The results obtained from the XGBoost regression model indicate
To address this, we propose a novel deep learning model for 5G base station energy consumption estimation based on a real-world dataset. Unlike existing methods, our approach integrates the Base
Smart energy saving of 5G base stations: Based on AI and other emerging technologies to forecast and optimize the management of 5G wireless network energy consumption
Aimed at 5G base stations with renewable energy sources, the TSRO model proposed in this paper can effectively addresses the uncertainties of renewable energy and communication loads,
This paper proposes an electric load demand model of the 5th generation (5G) base station (BS) in a distribution system based on data flow analysis. First, the electric load model of a 5G BS is
A bi-level optimization framework of capacity planning and operation costs of shared energy storage system and large-scale PV integrated 5G base stations is proposed to realize the
However, due to the utilization of massive antennas and higher frequency bands, the energy consumption of 5G base stations (BSs) is much higher than that of 4G BSs, which incurs huge
The widespread application of 4G and the rapid development of 5G technologies dramatically increase the energy consumption of telecommunication base station (TBS).
To understand this, we need to look closer at the base station power consumption characteristics (Figure 3). The model shows that there is significant energy consumption in the base
phasis must be paid to energy consumption in the communications base station due to this high demand at the BS level. As Roy stated in 2008, a telecom network is like an eco-system in that one cannot just.
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Ye G. Research on reducing energy consumption cost of 5G Base Station based on photovoltaic energy storage system. In: 2021 IEEE International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI), Fuzhou, China, 2021. p. 480-484.
However, due to the utilization of massive antennas and higher frequency bands, the energy consumption of 5G base stations (BSs) is much higher than that of 4G BSs, which incurs huge operation costs and significantly increases carbon emissions under traditional power supply mode .
To improve the energy eficiency of 5G networks, it is imperative to develop sophisticated models that accurately reflect the influence of base station (BS) attributes and operational conditions on energy usage.
3) Average daily electricity trading revenue with large-scale PV integrated 5G BSs In order to guarantee the safe and stable operation of smart distribution network, 5G BSs are only allowed to sell the surplus PV energy to SES operator. Moreover, direct curtailment of surplus PV energy will encounter the PV power curtailment penalty.