Exploding AI Power Use: an Opportunity to Rethink Grid Planning and Management

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 5-year AI demand. New DCs only receive 89% power availability. Study of other US power grids -- SPP, CAISO, ERCOT -- shows that sufficient capacity exists for the projected AI load growth. Our results suggest the need to rethink adequacy assessment and also grid planning and management. New research opportunities include coordinated planning, reliability models that incorporate load flexibility, and adaptive load abstractions.