In this paper, a distributed collaborative optimization approach is proposed for power distribution and communication networks with 5G base stations. Firstly, the model of 5G
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With the rapid development of 5G base station construction, significant energy storage is installed to ensure stable communication. However, these storage resources often remain idle, leading to inefficiency.
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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:
Afterward, a collaborative optimal operation model of power distribution and communication networks is designed to fully explore the operation flexibility of 5G base stations, and then an improved distributed algorithm based on the ADMM is developed to achieve the collaborative optimization equilibrium.
In this paper, a distributed collaborative optimization approach is proposed for power distribution and communication networks with 5G base stations. Firstly, the model of 5G base stations considering communication load demand migration and energy storage dynamic backup is established.
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 power supply equipment manages the distribution and conversion of electrical energy among equipment within the 5G base station. During main power failures, the energy storage device provides emergency power for the communication equipment.
At present, the energy storage backup capacity of most 5G BSs in China is generally configured according to the maximum consumption power for 3 h , which is a very conservative parameter setting to ensure the reliable communication services of 5G BSs but causes a wasted dispatchable capacity of energy storage.
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