A review of green AI research under carbon peaking and neutrality goals

Abstract

The large-scale training of artificial intelligence （AI） has led to a significant surge in computational resource demands， energy consumption， and carbon emissions， which not only poses severe challenges to the realization of carbon peaking and neutrality goals by AI technology itself， but also impedes the application of AI in edge devices such as power inspection robots and UAVs. During the digital transformation of power grids under carbon peaking and neutrality goals， study of green AI for energy saving and carbon reduction is of great significance to the construction of new power systems and the advancement of AI. Firstly， the origin and definition of green AI and the key factors affecting the energy consumption of the model are introduced； then the current development status， key issues， improvement methods and effects of green AI model technology are discussed. Afterwards， the energy-saving and carbon reduction measures of high-efficiency physical infrastructures are discussed. Finally， the relevant suggestions and outlooks for the future development of green AI are presented.

Keywords

• green ai
• new-type power systems
• energy conservation
• carbon emission
• model acceleration