AI Drives Up Electricity Demand; National Energy Administration Advances Coordinated Computing-Power Development
Coordinated computing-power and electricity planning supports AI development, with the state promoting mutual empowerment between computing power and electricity Optimizing energy allocation and power supply security to seize the initiative in developing a new-type energy system
Wang Hongzhi, head of the National Energy Administration, said on June 26 that with the rapid development of artificial intelligence, demand for related computing power continues to rise, which is also driving a significant increase in electricity consumption. The state will follow the approach of "strengthening computing with power and promoting power through computing," coordinate the allocation of energy resources and the construction of computing infrastructure, and advance the coordinated layout of computing power and electric power.
At a press conference on the "15th FiveYear Plan" development of a new energy system held that day by the State Council Information Office, Wang Hongzhi said that artificial intelligence and energy are forming mutual empowerment. Current applications are mainly concentrated in three areas: improving efficiency, solving operational challenges in power systems, and promoting intelligent operations. For example, AI can be used for intelligent inspections, defect detection, and decision support, and it can also help the grid better cope with fluctuations in wind power and photovoltaics, improving the consumption of new energy.
The National Energy Administration also proposed advancing the synergy between computing and electricity from three dimensions: planning and layout, policy system, and operational regulation. Western regions will strengthen the linkage between national computing power hubs and largescale new energy bases, while eastern regions will promote coordinated planning of distributed computing power with distributed power sources, microgrids, and virtual power plants. At the same time, for different types of computing tasks, load arrangements and power assurance methods will be optimized according to their requirements for latency and power supply stability.