[2604.06198] Concentrated siting of AI data centers drives regional power-system stress under rising global compute demand

[2604.06198] Concentrated siting of AI data centers drives regional power-system stress under rising global compute demand

arXiv - AI 4 min read

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Abstract page for arXiv paper 2604.06198: Concentrated siting of AI data centers drives regional power-system stress under rising global compute demand

Computer Science > Computers and Society arXiv:2604.06198 (cs) [Submitted on 13 Mar 2026] Title:Concentrated siting of AI data centers drives regional power-system stress under rising global compute demand Authors:Danbo Chen, Zijun Zhou, Yongyang Cai, Jiahong Qin, Ani Katchova, Lei Chen View a PDF of the paper titled Concentrated siting of AI data centers drives regional power-system stress under rising global compute demand, by Danbo Chen and 5 other authors View PDF HTML (experimental) Abstract: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, wh...

Originally published on April 09, 2026. Curated by AI News.

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