Huawei Technologies is targeting to further reduce ICT energy costs by introducing a new tool that uses artificial intelligence to regulate power consumption.
Known as Green 1-2-3, the new solution is designed to strike the right balance between energy efficiency, renewable energy utilization and user experience. It involves three aspects where firstly new materials and processes are being developed to solve condensation, low temperature issues and enable power modules to independently remain in standby, meaning the power consumption during extremely light load can be reduced from 300 W to less than 10 W.
Secondly, multi-dimensional site information such as weather, electricity price, battery status, and service volume are obtained by the software and intelligent scheduling algorithms used to maximize power generation efficiency and load-based power availability, while minimizing overall power cost.
(TOP: Mr. Peng Song, President of ICT Strategy & Marketing at Huawei addresses the Green Energy Summit).
Thirdly, experience-driven approaches are being upgraded to data-driven approaches, allowing energy-saving policies to be generated in minutes and optimization policies to be delivered in milliseconds.
Speaking at the Huawei Green ICT Summit, Peng Song, President of ICT Strategy & Marketing of Huawei, explained that the firm is advocating for expansion of the focus of organizations beyond improving network energy efficiency to reducing absolute energy consumption.
” An artificial intelligence ‘Big Bang’ is underway and is expected to bring new benefits and opportunities to network operators. However, it also requires better ICT infrastructure, due to higher bandwidth and increased computing power leading to a rapid increase in network energy consumption. Indeed, the ICT industry seems to be faced with the tough choice to either go green or develop. However, we believe the industry can choose not to choose, and instead go green and develop simultaneously ” Peng said.
He called for ICT players to consider an upgrade from network-specific policies to site-specific policies in order to improve the accuracy of renewable energy deployment. This will additionally reduce the time required for intelligent scheduling from days to minutes, thus maximizing the economic and environmental benefits of renewable energy.