Energy Saving and Digital Management: 5G
To effectively address the high energy consumption challenge of 5G base stations, implementing telecom tower energy management solution is
For 5G base station energy storage participation in distribution network power restoration, this paper intends to compare four aspects. 1) Comparison between the fixed base station backup time and the methods in this paper.
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.
When establishing the objective function, factors such as the loss cost of charging and discharging 5G base station energy storage are ignored, resulting in deficiencies in the energy exchange model for 5G base station energy storage.
• 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.
PDF version includes complete article with source references.
Get technical specifications, application guides, and ROI analysis tools for containerized microgrid solutions, mobile energy storage containers, and portable power systems.
15 Industrialna Street, Włochy District
Warsaw, Poland 02-492
Sales & General: +48 22 824 4067
Technical Support: +48 607 809 270
Monday - Friday: 8:00 AM - 6:00 PM CET
Saturday: 8:00 AM - 2:00 PM CET