Will Grid Construction Keep Up with the Pace of AI Development?
With the rapid development of artificial intelligence technology, its dependence on electricity is also deepening. The development trend of AI shows that the demand for computing power will increase sharply in the future, which will lead to a significant increase in the power consumption of AI systems. At present, the development of global energy construction and transmission and distribution networks faces huge challenges. Especially in the context of renewable energy gradually replacing traditional energy, how to ensure the continuous supply of energy and the stable operation of transmission and distribution networks has become a crucial issue. This paper deeply analyzes the latest trends in the development of AI technology, focusing on the demand and consumption of AI for power resources, and compares it with the current energy generation, revealing the possible imbalance between supply and demand in the future. At the same time, this paper also evaluates the current status of energy construction and transmission and distribution network infrastructure, and explores its development potential and trends. By comparing the changes in energy generation and AI power consumption, the support capacity of the existing power grid for future load growth is analyzed. Results show that although the construction of energy and transmission and distribution networks is advancing rapidly, there may still be a risk of lag in the face of the rapid growth of electricity demand brought about by AI technology. This requires relevant departments to adopt more proactive strategies to accelerate the construction of energy infrastructure and the intelligent upgrade of power grids to ensure that the power grid can keep up with the speed of AI development and achieve stable and reliable energy supply.
Authors
- Yongjun Zhang (ORCID: https://orcid.org/0000-0001-9845-4251)
- Wenxin Huang
Institutions
- Guangdong University of Technology (CN)
- South China University of Technology (CN)
Publication Details
- Published
- 2024-09-20
- DOI
- https://doi.org/10.1109/icpre62586.2024.10768566
- Citations
- 1
- Primary Topic
- Distributed and Parallel Computing Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.35