AI数据中心集中布局正加剧多地电网压力，需提前规划能源配套。
Concentrated siting of AI data centers drives regional power-system stress under rising global compute demand
- 用大模型分析政策媒体数据，结合电力系统建模预测2025-2030年算力用电
- 6大企业算力用电将从2024年118太瓦时增至2030年239至295太瓦时，占全球1%
- 俄勒冈、弗吉尼亚、爱尔兰等地区电网风险高，德州与日本更具承载能力
生成式人工智能的快速发展正推动全球计算需求前所未有的增长，对电力系统造成持续压力。本研究提出一种AI-能源耦合框架，结合大语言模型（LLMs）对企业和政策、媒体数据的分析，以及定量能源系统建模，预测2025至2030年AI数据中心的电力足迹。结果显示，新增算力基础设施高度集中在北美、西欧和亚太地区，合计占未来算力容量的90%以上。六大领先企业电力消耗预计从2024年的约118太瓦时增长至2030年的239至295太瓦时，相当于全球电力需求的约1%。俄勒冈、弗吉尼亚和爱尔兰等地区可能面临超过0.25的高电力应力指数（PSI），表明局部电网脆弱；而德克萨斯州和日本等多样化系统则能更有效吸纳新增负荷。研究揭示，AI基础设施已从边缘数字服务演变为电力系统动态的结构性组成部分，亟需前瞻性的规划，使计算增长与可再生能源扩张及电网韧性相匹配。
原文摘要 · Abstract (English)
The rapid rise of generative artificial intelligence (AI) is driving unprecedented growth in global computational demand, placing increasing pressure on electricity systems. This study introduces an AI-energy coupling framework that combines large language models (LLMs)-based analysis of corporate, policy, and media data with quantitative energy-system modeling to forecast the electricity footprint of AI-driven data centers from 2025 to 2030. Results show that the new AI infrastructure is highly concentrated in North America, Western Europe, and the Asia-Pacific, which together account for more than 90% of projected compute capacity. Aggregate electricity consumption by the six leading firms is projected to increase from roughly 118 TWh in 2024 to between 239 TWh and 295 TWh by 2030, equivalent to about 1% of global power demand. Regions such as Oregon, Virginia, and Ireland may experience high Power Stress Index (PSI) values exceeding 0.25, indicating local grid vulnerability, whereas diversified systems such as those in Texas and Japan can absorb new loads more effectively. These findings demonstrate that AI infrastructure is evolving from a marginal digital service into a structural component of power-system dynamics, underscoring the need for anticipatory planning that aligns computational growth with renewable expansion and grid resilience.
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