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
The proposed approach enables dynamic load adjustment via 5G computing task migration and coordinated operation between 5G BSs and EVs. Case studies demonstrate
Abstract: The integration of high proportions of distributed energy resources and the soaring development of 5G base stations (BSs) could lead to operational issues such as grid
To achieve "carbon peaking" and "carbon neutralization", access to large-scale 5G communication base stations brings new challenges to the optimal operation of new power
The calculation example analysis results show that communication load transfer can effectively reduce the power consumption of 5G base stations during low load periods and increase the...
A case study is conducted to analyze the impact of the critical factors on the load of 5G BS and the influence of 5G BSs load on the other loads in three typical areas.
In this paper, firstly, an energy consumption prediction model based on long and short-term memory neural network (LSTM) is established to accurately predict the daily load
A 5G BS model considering communication load migration and energy storage dynamic backup is established. A coordinated optimization model of the interacted distribution and 5G
Given the rapid expansion of 5G base stations (BSs), utilizing their energy storage to participate in DN planning and operation optimization provides a promising solution.
The purpose of this paper is to envision the 5G network as flexible DR resources and jointly planning of 5G-DS considering source-network-load-storage coordination.
In this paper, firstly, an energy consumption prediction model based on long and short-term memory neural network (LSTM) is
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