Turning to artificial intelligence (AI), China uses AI as a central tool in its national strategy to drive the shift toward cleaner energy, an action that could reshape not only its domestic energy landscape but also its global efforts to reduce carbon emissions. Underneath a newly established “AI + energy” strategy, Beijing plans to incorporate AI technologies deeply across its power system and energy industries by the year 2027, along with the goal of enhancing efficiency, managing the fluctuation in renewable power, and reinforcing grid stability.
At the heart of this effort is the belief that AI can address one of the most stubborn challenges of renewable energy, its intermittent and unpredictable nature. Solar and wind power, which now account for a rapidly growing share of China’s electricity generation, vary with weather and time of day. AI systems mainly promise to smooth out these fluctuations by analysing vast datasets and forecasting supply and demand patterns, as well as enabling real‑time decision‑making across the grid.
A very significant example of this approach is a renewable hydrogen and ammonia production plant in Chifeng, Inner Mongolia, developed by Envision, which is a leading green Chinese technology company. The facility uses an AI-driven operating system which continually adjusts the production levels to match the availability of solar power as well as wind. When the renewable generation is abundant, the system increases output; as it declines, it scales back, which optimises the use of green electricity and minimises waste. This kind of dynamic management helps maintain productivity while reducing reliance on fossil fuel backups.
Experts have also mentioned that AI-driven systems could play a pivotal role in improving grid flexibility by coordinating electricity supply, energy storage, and diverse end uses across cities and industrial hubs. In Shanghai, the State Grid Corporation has rolled out a citywide, AI-powered virtual power plant that links distributed resources, such as data centres, electric vehicle charging stations, and building energy systems, into a single, flexible power network. Trial operations show the platform has cut peak demand, easing pressure on the grid.
China’s power system faces mounting strain as renewable capacity grows rapidly. Although green electricity accounts for about one-third of consumption, managing variable wind and solar output remains challenging. AI forecasting tools help operators balance supply and demand more efficiently, reducing reliance on fossil-fuel backups. Under its “AI + energy” strategy, China plans large-scale models, pilot projects, and dozens of real-world applications by 2027.
Beyond grid operations and renewable forecasting, AI is also being incorporated into China’s carbon market, which covers thousands of companies across heavy‑emitting industries. By improving the efficiency as well as the accuracy of emissions verification as well as allocation planning, AI could now support more reliable carbon pricing and enforcement, which is a critical component of China’s climate policy toolkit.
However, the growing use of AI in the energy sector introduces its own set of problems and challenges. Data centres powering AI models are projected to consume large amounts of electricity, which could potentially exceed 1,000 terawatt-hours annually by the year 2030, which could also complicate China’s decarbonisation goals if unmanaged. In response, policymakers are promoting stricter energy efficiency standards and a greater reliance on renewable power for AI infrastructure, including concepts such as offshore wind-powered underwater data centres.
The strategy made by China differs from the rest of the other major economies. While Western AI investment often targets consumer applications as well as large language models, Chinese developers are focusing on practical as well as scalable solutions linked to industrial systems as well as grid operations. These aspects reflect Beijing’s broader aims to modernise the energy sector, stop coal dependence and meet the carbon targets through innovation.
As renewable capacity grows and AI coordination deepens, China could set new benchmarks and goals for using digital tools to accelerate decarbonisation, which could potentially shape global energy strategies.
