Aug 23, 2019 · Energy-Efficient Base Station Deployment in Heterogeneous Communication Network Published in: 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing,
Mar 31, 2024 · With the maturity and large-scale deployment of 5G technology, the proportion of energy consumption of base stations in the smart grid is increasing, and there is an urgent
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Sep 30, 2024 · In the above model, by encouraging 5G communication base stations to engage in Demand Response (DR), the Renewable Energy Sources (RES), and 5G communication base
Sep 2, 2024 · Grounded in the spatiotemporal traits of chemical energy storage and thermal energy storage, a virtual battery model for base stations is established and the scheduling
Aug 20, 2021 · Then, the key technologies for 5G base station to participate in demand response was analyzed. Further, the application scenarios to dispatch 5G base stations as demand-side
The 5G communication base station can be regarded as a power consumption system that integrates communication, power, and temperature coupling, which is composed of three major pieces of equipment: the communication system, energy storage system, and temperature control system.
The objective of this paper is to present a hybrid control strategy for communication base stations that considers both the communication load and time-sharing tariffs.
Meanwhile, communication base stations often configure battery energy storage as a backup power source to maintain the normal operation of communication equipment [3, 4]. Given the rapid proliferation of 5G base stations in recent years, the significance of communication energy storage has grown exponentially [5, 6].
In the above model, by encouraging 5G communication base stations to engage in Demand Response (DR), the Renewable Energy Sources (RES), and 5G communication base stations in ADN are concurrently scheduled, and the uncertainty of RES and communication load is described by using interval optimization method.
A single base station energy storage system is configured with a set of 48 V/400 A-h energy storage batteries. The initial charge state of the batteries is assumed to obey a normal distribution, assuming that the base station has a uniform specification and its parameters are shown in Table 2. Table 2. Parameters of the energy storage system.
Grounded in the spatiotemporal traits of chemical energy storage and thermal energy storage, a virtual battery model for base stations is established and the scheduling potential of battery clusters in multiple scenarios is explored.
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