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This restricts the potential use of the power models, as their validity and accuracy remain unclear. Future work includes the further development of the power consumption models to form a unified evaluation framework that enables the quantification and optimization of energy consumption and energy efficiency of 5G networks.
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.
However, the energy consumption of 5G networks is today a concern. In recent years, the design of new methods for decreasing the RAN power consumption has attracted interest from both the research community and standardization bodies, and many energy savings solutions have been proposed.
The simulation results show that 700 MHz and 26 GHz will play an important role in 5G deployment in the UK, which allow base stations to meet short-term and long-term data traffic demands respectively.
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.
From the above comparative analysis results, 5G base station operators invest in photovoltaic storage systems and flexibly dispatching the remaining space of the backup energy storage can bring benefits to both the operators and power grids.
This will enable the efficient utilization of idle resources at 5G base stations in the collaborative interaction of the power system, fostering mutual benefit and win-win between the power grid and the communication operators.
During main power failures, the energy storage device provides emergency power for the communication equipment. A set of 5G base station main communication equipment is generally composed of a baseband BBU unit and multiple RF AAU units. Equation 1 serves as the base station load model:
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