AIインフラと再生可能エネルギーの共同展開に向けた協調投資フレームワーク：米国電力市場におけるハイパースケール計算需要下の系統安定性ファイナンス

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:AI電力需要と系統・再エネ投資の調整を定量化するCRG指標と投資順序の枠組みは、エネルギー転換研究の新たな分析軸を提供する。

🏢実務担当者:データセンター・再エネ・系統投資の順序と州債活用による資本コスト低減は、大規模電力調達やPPA戦略の立案に実務的示唆を与える。

🏛政策担当者:AI需要を織り込んだ系統拡張の先行投資と資金調達設計は、電力系統計画・許認可・GX投資政策の検討材料になる。

<title>Abstract</title> <p>The rapid growth of artificial intelligence (AI) infrastructure in the United States is creating new challenges for electricity system planning and resource adequacy. Hyperscale data centers require a continuous and highly reliable power supply, increasing pressure on transmission networks, generation resources, and grid infrastructure that were not originally designed to support large concentrations of AI-related electricity demand. This study develops a quantitative planning framework to evaluate the timing, sequencing, and coordination of investments in AI infrastructure, transmission systems, and electricity generation resources across U.S. power markets. Using New York Independent System Operator (NYISO) data and an 8,760-hour generation profile, the study introduces a Capacity Reliability Gap (CRG) metric to measure the difference between projected AI electricity demand and available firm generation capacity. Results show that uncoordinated infrastructure development could lead to a CRG of 23% to 41% by 2030. In contrast, coordinated planning significantly improves resource adequacy and reduces unmet electricity demand. A scalability analysis across PJM, MISO, and CAISO demonstrates that coordinated investment strategies can reduce projected unmet AI-related demand from 62.4 GW to 5.8 GW. The findings also highlight the importance of investment sequencing, showing that transmission expansion should be implemented approximately 14 to 18 months before major generation additions to reduce congestion, renewable energy curtailment, and the risk of stranded assets. Overall, the proposed framework provides practical guidance for system operators, transmission planners, regulators, and policymakers seeking to maintain grid reliability while supporting the rapid growth of AI-driven electricity demand. Highlights: ; Uncoordinated AI and grid investment leaves a 23-41% capacity reliability gap ; Transmission must precede renewable additions by 14-18 months to avoid stranding ; State-anchored bond financing cuts blended capital costs by 15-22% ; Coordinated planning cuts national unmet AI demand from 62.4 GW to 5.8 GW ; Framework holds directionally across NYISO, PJM, MISO, and CAISO Graphical abstract</p>

• Research Square https://doi.org/10.21203/rs.3.rs-11068332/v1first seen 2026-10-02 04:21:21