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AI data centres as grid-interactive assets
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AI
DOI：10.1038/s41560-025-01927-1.png)
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Abstract
En 中文
The exponential growth in electricity demand driven by artificial intelligence (AI) is threatening grid reliability, increasing energy costs for communities funding new infrastructure and slowing AI innovation as data centres await interconnection to constrained grids. Here we present a field demonstration of a software-based method that enables AI data centres to operate as flexible grid resources. Tested on a 256-Graphics Processing Unit (GPU) cluster running representative AI workloads in a hyperscale cloud facility in Phoenix, Arizona, the system reduced power usage by 25% for 3 hours during peak demand while maintaining AI quality of service guarantees. By coordinating workloads in response to real-time grid signals, without hardware modifications or energy storage, this approach demonstrates the potential for data centres to contribute to grid stability and affordability while sustaining computational performance within existing power-system constraints. Artificial intelligence is driving rapid growth in electricity demand, straining grid reliability and infrastructure. This study demonstrates a software-based method that allows data centres to adjust workloads in response to real-time grid signals, reducing power use and supporting grid stability without hardware modifications.
Keywords:
AI data centres
grid reliability
power consumption
workload coordination
software-based optimization
Journal
IF:
60.1
Papers:
989
Citations:
5.6W
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