Blowing Off Steam: How Power-Flexible AI Factories Can Stabilize the Global Energy Grid

NVIDIA Corp. — editor’s note: This blog, originally published in March 2026, has been updated. At the half-time whistle of the UEFA EURO 2020 round of 16 football match between England and Germany, millions of viewers stepped away from their screens in the U.K.

to do the same thing at the same time — turn on their kettles. National Grid, which provides electricity for England and Wales, saw a demand spike of about 1 gigawatt — an increase equivalent to the average output of a standard nuclear reactor — in a matter of minutes from this countrywide tea break. Grid operators must carefully manage these demand peaks to keep the system stable, and this could become even more difficult as the grid continues to add large new customers. But what if those new customers could actually be flexible and relieve the grid during periods of peak strain? In a white paper and follow-on arXiv technical paper, Emerald AI — in collaboration with NVIDIA, EPRI, National Grid and Nebius — showed how power-flexible AI factories can autonomously adjust power use during peak demand while preserving priority workloads. For AI factories, proven load flexibility could support faster utility and interconnection conversations by showing that sites can temporarily reduce withdrawals during grid stress, rather than requiring the grid to plan only for worst-case firm demand. For the public, it helps limit grid build-outs by curbing the peak load that the system needs to serve, helping keep electricity rates affordable for everyday bill payers. Boil the Kettle, Balance the Grid  After successful proof-of-concept trials at AI factories in Arizona, Virginia and Illinois, Emerald AI took its flexible grid solution across the pond, last December, bringing the Emerald AI Conductor Platform to Nebius’ new AI factory in London, built on NVIDIA infrastructure — among the first of its kind in the U.K. At the AI factory, the research team ran production-grade AI workloads on a cluster of 96 NVIDIA Blackwell Ultra GPUs connected through the NVIDIA Quantum-X800 InfiniBand platform. The NVIDIA System Management Interface is used to retrieve consistent, seconds-level GPU power telemetry. EPRI and National Grid simulated stress scenarios on the power grid — from lightning strikes to long periods of low wind power supply — and sent signals instructing the AI factory, with the help of the Conductor Platform, to temporarily reduce its power use to relieve grid strain. One of these scenarios was the “TV pickup” phenomenon, where that very same Euro 2020 football match’s energy surge was reenacted. As millions of simulated tea kettles were about to be turned on, the AI cluster ramped down its power use — successfully acting as a shock absorber for the abrupt power surge without disrupting the highest-priority AI workloads running on the cluster. https://blogs.nvidia.com/wp-content/uploads/2026/02/Grid-Responsive-AI-Infrastructure-Chart_v4.mp4 In practice, this means the grid can manage sudden demand swings using existing capacity more efficiently, reducing the need to overbuild permanent infrastructure to meet worst-case peaks and helping keep rates affordable for everyday consumers. “With this technology, AI factories become friendly and helpful grid assets,” said Varun Sivaram, founder and CEO of Emerald AI.