China to Accelerate New Energy System to Power AI Growth
At the "AI and Energy Dual Empowerment" forum during the 2026 World Artificial Intelligence Conference in Shanghai, a representative from China's National Energy Administration announced plans to accelerate the development of a new energy system. This initiative aims to support the growth of artificial intelligence by providing a sustainable power infrastructure. The administration highlighted that by the "15th Five-Year Plan" period, AI inference workloads are expected to surpass training workloads, becoming the primary consumers of computing power. The unique characteristics of AI workloads, such as latency sensitivity, significant load fluctuations, and concentrated demand, necessitate a shift from simple spatial coordination to a multi-dimensional synergy between computing load and the new power system. This requires integrated planning of core elements like intelligent computing, large models, and data resources. Wang Hongzhi, Party Secretary and Director of the National Energy Administration, stated that nearly 40% of the nation's total electricity consumption currently comes from green energy. He emphasized that abundant and high-quality green power supply is crucial for advancing green computing from a concept to practical application, ensuring efficient energy use and aligning AI development with sustainability goals.
China's strategic focus on integrating its energy system with AI development reflects a global trend driven by the immense power demands of advanced computing. The administration's emphasis on green energy for AI suggests an effort to mitigate the environmental footprint of this rapidly expanding sector. The transition from 'spatial coordination' to 'multi-dimensional synergy' for computing and power systems indicates a forward-looking approach to managing the complex interplay between AI infrastructure and grid stability. This initiative positions China to potentially lead in developing energy-efficient AI solutions, while also highlighting the systemic challenges of balancing exponential technological growth with sustainable resource management over the next decade.
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