Exploding AI Power Use: an Opportunity to Rethink Grid Planning and Management
Liuzixuan Lin, Rajini Wijayawardana, Varsha Rao, Hai Nguyen, Wedan, Emmanuel Gnibga, Andrew A. Chien

TL;DR
The paper examines how rapid AI-driven data center growth challenges existing power grid capacities, proposing grid policy adjustments and new planning strategies to ensure reliable AI infrastructure expansion.
Contribution
It identifies specific grid hotspots at risk of inadequate capacity and suggests policy measures to enhance load flexibility and reliability in grid planning.
Findings
EirGrid can support AI growth with relaxed reliability guarantees.
Dominion's capacity increase is insufficient for AI demand.
Other US grids like SPP, CAISO, ERCOT have sufficient capacity.
Abstract
The unprecedented rapid growth of computing demand for AI is projected to increase global annual datacenter (DC) growth from 7.2% to 11.3%. We project the 5-year AI DC demand for several power grids and assess whether they will allow desired AI growth (resource adequacy). If not, several "desperate measures" -- grid policies that enable more load growth and maintain grid reliability by sacrificing new DC reliability are considered. We find that two DC hotspots -- EirGrid (Ireland) and Dominion (US) -- will have difficulty accommodating new DCs needed by the AI growth. In EirGrid, relaxing new DC reliability guarantees increases the power available to 1.6x--4.1x while maintaining 99.6% actual power availability for the new DCs, sufficient for the 5-year AI demand. In Dominion, relaxing reliability guarantees increases available DC capacity similarly (1.5x--4.6x) but not enough for the…
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Taxonomy
TopicsCloud Computing and Resource Management · Distributed and Parallel Computing Systems · Age of Information Optimization
