Coordinated scheduling of 5G base station energy storage for voltage
To enhance the utilization of base station energy storage (BSES), this paper proposes a co-regulation method for distribution network (DN) voltage control, enabling BSES
To enhance the utilization of base station energy storage (BSES), this paper proposes a co-regulation method for distribution network (DN) voltage control, enabling BSES
Managing power in 5G networks is complex, requiring high efficiency, low noise, and the ability to handle high-density deployments and diverse operational conditions.
Considering the economic feasibility of power supply solutions throughout the lifecycle, a modeling method is proposed that optimizes the voltage level of converters considering the behavior of...
To enhance the utilization of base station energy storage (BSES), this paper proposes a co-regulation method for distribution network (DN) voltage control, enabling BSES participation in
The optimal voltage level for different supply distances is discussed, and the effectiveness of the model is verified through examples, providing valuable guidance for
As 5G deployments accelerate globally, voltage fluctuations in base stations caused unprecedented 1.7 million network outages last year alone. What if the key to seamless
Firstly, the potential ability of energy storage in base station is analyzed from the structure and energy flow. Then, the framework of 5G base station participating in power system frequency
The 5G base station energy consumption prediction model based on LSTM proposed in this paper takes into account the energy consumption characteristics of 5G base stations.
To enhance the utilization of base station energy storage (BSES), this paper proposes a co-regulation method for distribution network (DN) voltage control, enabling BSES participation in
HVDC systems are mainly used in telecommunication rooms and data centers, not in the Base station. With the increase of power density and voltage drops on the power transmission line in
The optimal voltage level for different supply distances is discussed, and the effectiveness of the model is verified through examples, providing valuable guidance for
To enhance the utilization of base station energy storage (BSES), this paper proposes a co-regulation method for distribution
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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 5G base station energy consumption prediction model based on LSTM proposed in this paper takes into account the energy consumption characteristics of 5G base stations. The prediction results have high accuracy and provide data support for the subsequent research on BSES aggregation and optimal scheduling.
At the same time, the new equipment has altered the power load characteristics of base stations. In the 5G technology framework, the 5G base station comprises macro and micro variants. The micro base station serves indoor blind spots with minimal power consumption. The macro base station exhibits greater potential for demand response.
Furthermore, with the goal of fully utilizing the energy storage resources of 5G base stations, a BSES co-regulation method for voltage regulation in DNs is proposed. The feasibility of the proposed method is verified by case analysis, and the following conclusions can be drawn.