Introduction

The National Development and Reform Commission, the National Energy Administration, the Ministry of Industry and Information Technology, and the National Data Bureau recently issued the “Action Plan for Promoting Bidirectional Empowerment of Artificial Intelligence and Energy”. This plan aims to significantly enhance the clean energy supply capabilities for AI computing facilities and the application level of AI in the energy sector by 2030, creating a new development pattern of deep integration between AI and energy.

Key Focus Areas

The Action Plan centers on two main themes: supporting the development of AI through energy and enabling energy transition with AI. It outlines 29 key tasks that focus on ensuring safe and reliable energy supply for computing facilities, promoting green and low-carbon transformation of these facilities, enhancing the economic synergy between computing power and electricity, opening up high-value application scenarios for AI in the energy sector, exploring the value of energy data, and strengthening innovation in AI models for the energy field.

Ensuring Energy Supply for Computing Facilities

The backbone of computing power is electricity. To ensure the safe and reliable energy supply for computing facilities, the Action Plan proposes a coordinated layout of large-scale renewable energy bases and national computing power hubs. It encourages the orderly aggregation of computing facilities and internet backbone connections in areas rich in renewable energy, promoting local consumption of renewable energy. It also explores direct energy supply from nuclear power and hydrogen energy to computing facilities and encourages the use of grid-connected energy storage to enhance power supply stability.

Green Transformation of Computing Facilities

Green electricity is essential for the green and low-carbon transformation of computing facilities. The Action Plan emphasizes the need to strengthen project layout planning for computing facilities, using the proportion of green electricity as an important reference indicator to enhance the level of green computing power supply. It supports computing facilities in participating in green certificate and green electricity trading to increase the proportion of green electricity consumption. Moreover, it encourages the transformation of backup power sources to green and low-carbon alternatives, promoting the replacement of traditional fuel generators with clean energy sources. Based on the types of computing tasks, the facilities will be managed categorically, promoting direct connections to green electricity for those with flexible adjustment capabilities.

Industry Initiatives

Relevant companies are already taking action. Li Qiang, Vice President of Tencent Group, introduced that Tencent Cloud is developing a model for direct supply of green electricity to computing facilities, allowing clean energy from wind and solar to be delivered directly to data centers without passing through the public grid. This model aims for precise matching of computing power and electricity, with the world’s first 100% green electricity supplied data center established in Chifeng, Inner Mongolia, in collaboration with Envision Group.

The Role of AI in Energy

Tian Qingjun, Senior Vice President of Envision, believes that competition in the AI era is fundamentally a contest of power systems. He notes that stable, low-cost, and sustainable zero-carbon electricity supply has become a key factor limiting project implementation in the AI industry. The collaboration between Tencent and Envision to promote green electricity supply to data centers is rooted in this understanding. With Envision’s comprehensive self-research capabilities spanning from wind turbines to AI scheduling systems, the project can reduce overall energy costs by over 40% and cut carbon emissions by approximately 180,000 tons annually.

Bidirectional Empowerment

A key aspect of bidirectional empowerment between AI and energy is enhancing the collaborative operation of computing power and electricity. The Action Plan proposes establishing an interactive mechanism between computing power and electricity, using electricity market price signals to guide computing facilities in optimizing energy management and facilitating various forms of computing power scheduling across networks and regions to improve economic efficiency. It encourages computing facilities to participate as flexible adjustable resources on the load side of the grid, enhancing the regulation capability of the power system and achieving mutual efficiency gains.

Future Outlook

Tian Qingjun emphasizes that China’s core strength in the global AI arena lies in its complete renewable energy industrial chain. The industry can leverage this advantage to gain a long-term competitive edge in AI. “The end of AI is renewable energy. The first to connect the entire chain from green electricity production to computing power implementation will hold the true initiative in global AI competition.”

High-Value AI Applications in Energy

Notably, the Action Plan clearly states the need to open up high-value application scenarios for AI in the energy sector. It aims to organize pilot projects for the integration of AI applications in energy, continuously selecting benchmark applications that deeply integrate AI with energy industry needs. This will accelerate the deployment of AI across the entire chain of energy planning, exploration, production, operation, equipment maintenance, and safety management. Specific scenarios include reliable and flexible supply of clean energy, safe and stable operation of the power grid, intelligent and efficient coal development, efficient exploration and development of oil and gas, and innovative integration of new energy business models.

Market Opportunities

Regarding the market benefits brought by policies, Tian Qingjun predicts that the large-scale promotion of the green electricity direct connection model will lead to a significant increase in the market for energy storage, particularly for AI data centers and new (semi) off-grid power systems like green hydrogen and ammonia. In the future, energy storage will shift from serving large power grid applications to load-side applications. For instance, AI computing centers require a power supply reliability exceeding 99.99%, making energy storage a necessity under the green electricity direct connection model.