INTELLIGENT ENGINEERING OF ELECTRIC ENERGY STORAGE SYSTEMS IN THE ...
Huawei Communications Green Base Station Intelligent Energy Storage Cabinet
Underpinned by intra-site, inter-site, and site/network energy storage collaboration, coupled with big data analytics and AI algorithms, the solution supports intelligent voltage boosting, intelligent a. [pdf]
Environmental protection of communication base station energy storage systems
This paper aims to consolidate the work carried out in making base station (BS) green and energy efficient by integrating renewable energy sources (RES). Clean and green technologies are mandatory for reduct. [pdf]FAQS about Environmental protection of communication base station energy storage systems
How to make base station (BS) green and energy efficient?
This paper aims to consolidate the work carried out in making base station (BS) green and energy efficient by integrating renewable energy sources (RES). Clean and green technologies are mandatory for reduction of carbon footprint in future cellular networks.
What are the components of a base station?
A typical base station consists of different sub-systems which can consume energy as shown in Fig. 4. These sub-systems include baseband (BB) processors, transceiver (TRX) (comprising power amplifier (PA), RF transmitter and receiver), feeder cable and antennas, and air conditioner ( Ambrosy et al., 2011 ).
How can radio resources be manipulated to conserve energy?
The radio resources can be manipulated to conserve energy by adapting the capacity and/or converge of the green BS. This is demonstrated in ( Valerdi et al., 2010 ), where both aspects are optimized according to the available renewable energy and battery back-up available.
What is energy storage model?
Energy storage model is defined in terms of battery parameters such as capacity (AH), battery charging losses, charging rate, the system load, etc.
Can BS cooperation save energy?
The authors of ( Li et al., 2011a) estimate that such BS cooperation can save as much as 85% of the total energy consumed during off-peak hours in dense urban areas, which is considered 35% over and above the savings operators would make if they acted on their own.
