How to assess and manage energy performance of
How to assess and manage energy performance of numerous telecommunication base stations: Evidence in China Tian-Jian Yang a, Yue-Jun Zhang b,c,⇑, Su Tang a, Jing Zhang a
Among these, base stations are some of the most energy-intensive, especially in mobile networks. Several factors influence power demand across telecom infrastructure. Network traffic levels vary throughout the day and across locations, requiring dynamic power provisioning.
Firstly, in terms of energy equipment, the electrical component characteristics of the 5 G base station's constituent units are modeled, including air conditioning loads, power supply systems, and energy storage systems.
In Case 2, the total optimal energy storage planning capacity of large-scale 5G BSs in commercial, residential, and working areas is 9039.20 kWh, and the corresponding total rated power is 1807.84 kW. The total energy storage planning capacity of large-scale 5G BSs in Case 3 is 7742 kWh, which is 14.35% lower than that of Case 2.
This section integrates the characteristics of power components and data flow to construct an energy-saving operation model for the 5 G base station. Through optimization, the optimal energy-saving and carbon-reduction strategies for each time period are obtained, thereby promoting energy conservation and emission reduction in 5 G base stations.
How to assess and manage energy performance of numerous telecommunication base stations: Evidence in China Tian-Jian Yang a, Yue-Jun Zhang b,c,⇑, Su Tang a, Jing Zhang a
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