AI Revolutionizes Renewable Energy Operations in China
China is advancing its efforts to modernize and decarbonize its energy infrastructure by integrating artificial intelligence (AI) into daily operations of power generation, distribution, and consumption. Moving beyond high-level policies, AI is now actively managing complex challenges on the ground to improve efficiency and stability.
Case Study: AI-Driven Renewable Factory in Chifeng
In the northern city of Chifeng, a pioneering factory powered exclusively by wind and solar energy demonstrates AI’s practical role. The facility produces hydrogen and ammonia through an isolated system independent of the broader electrical grid. This approach benefits from clean renewable energy but must contend with its inherent variability due to weather fluctuations.
To maintain steady production, the factory employs a sophisticated AI control system developed by Envision. Unlike conventional plants that operate on fixed schedules, this AI continuously adjusts power consumption in response to real-time changes in wind and solar output. Zhang Jian, Envision’s chief engineer for hydrogen energy, likens the AI to a conductor orchestrating the balance between energy supply and industrial demand.
This adaptive system ramps production up as wind speeds rise and scales back during lulls, ensuring optimal use of fluctuating renewable power and maintaining high operational efficiency.
AI’s Strategic Role in China’s Energy Transition
China envisions hydrogen and ammonia as critical low-emission fuels for heavy industry and shipping. The AI-enabled factory exemplifies the broader national strategy of deploying intelligent systems to manage the increasing complexity of a renewable-rich grid.
Experts highlight AI’s potential to support numerous climate-related tasks including emissions monitoring and forecasting electricity supply and demand. Zheng Saina, an associate professor specializing in low-carbon transitions, notes AI’s versatility but also warns about the growing energy demands of AI technologies themselves, particularly from data centers.
National AI+ Energy Strategy and Implementation
China leads global installations of wind and solar capacity, but integrating this intermittent power remains challenging. Beijing formalized its approach in September by launching the “AI+ energy” strategy, promoting close collaboration between AI and energy sectors. The plan includes creating large AI models tailored for grid management, power generation, and industrial applications, with a goal of deploying over 100 AI use cases and dozens of pilot projects by 2027.
Instead of focusing on general-purpose AI models, China emphasizes specialized AI tools for tasks such as wind farm operation, nuclear plant management, and grid balancing. This contrasts with the U.S. focus on large language models, according to Hu Guangzhou, a professor at the China Europe International Business School.
Demand Forecasting and Grid Flexibility
Accurate demand prediction is a key area where AI can deliver immediate benefits. Fang Lurui, assistant professor at Xi’an Jiaotong-Liverpool University, explains that balancing supply and demand in real time is crucial to prevent grid failures. AI-driven forecasts enable operators to optimize battery storage and reduce reliance on coal-fired plants.
Shanghai’s citywide virtual power plant illustrates AI’s potential, integrating diverse energy users like data centers and EV chargers into a single network. A recent trial demonstrated a peak demand reduction exceeding 160 megawatts, equivalent to a small coal plant’s output.
Experts stress that modern power generation’s distributed and intermittent nature requires robust, predictive AI systems capable of rapid adaptation.
AI in Carbon Market and Emissions Control
Beyond power systems, China is applying AI to its national carbon market, affecting more than 3,000 companies in high-emission industries. AI can enhance regulatory oversight by verifying emissions data, refining allowance allocations, and improving corporate cost transparency, according to Chen Zhibin of the think tank adelphi.
Balancing AI’s Energy Demands and Environmental Goals
Despite AI’s benefits, its expanding energy consumption poses risks. Studies forecast that by 2030, Chinese AI data centers may consume energy comparable to Japan’s annual electricity use, with lifecycle emissions peaking after national targets. Researcher Xiong Qiyang warns that continued reliance on coal could undermine climate objectives if AI-driven demand growth is not managed.
In response, new regulations mandate yearly improvements in data center energy efficiency and renewable energy usage. Initiatives encourage locating data centers in resource-rich western regions and experimenting with innovative solutions like an underwater data center near Shanghai, cooled by seawater and powered primarily by offshore wind.
Outlook: AI as Both Challenge and Solution
While AI increases energy consumption, experts like Xiong argue that its strategic application in optimizing industrial processes, power systems, and carbon markets may ultimately support China’s emissions reduction efforts. Policymakers face the task of balancing AI’s growth with sustainable energy transitions.
Foto por Matthew Henry
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