What is a distributed collaborative optimization approach for 5G base stations?
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.
What is the access mechanism between EMCs and BSS?
To describe the access mechanism between the EMCs and the BSs, we introduce an N b s × N m g connection matrix A, where N m g is the EMCs number and N b s is the number of power towers which is also the number of candidate locations for base stations. It is not necessary for all power towers to be selected as communication power sharing towers.
What are the basic parameters of a base station?
The fundamental parameters of the base stations are listed in Table 1. The energy storage battery for each base station has a rated capacity of 18 kWh, a maximum charge/discharge power of 3 kW, a SOC range from 10% to 90%, and an efficiency of 0.85.
Why are power systems and communication systems increasingly coupled?
Therefore, power systems and communication systems are increasingly coupled. A power system supplies energy, and a communication system meets the demand for information exchange. A BS is the main intermediary between a communication network and a power network.
What is the energy consumption of 5G communication base stations?
Overall, 5G communication base stations’ energy consumption comprises static and dynamic power consumption . Among them, static power consumption pertains to the reduction in energy required in 5G communication base stations that remains constant regardless of service load or output transmission power.
What is a collaborative optimal operation model of 5G base stations?
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.
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