The mechanics of data center flexibility

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Aug 28, 2025

Varun Sivaram, Founder and CEO of Emerald AI, discusses the fascinating world of flexible data centers. He explains how adjusting data center loads can significantly alleviate pressure on power grids, potentially unlocking up to 98 gigawatts of unused capacity. Varun highlights the challenges of maintaining high reliability while enabling flexibility in power usage. He shares insights on innovative strategies like demand response and discusses case studies, including Google's latest agreements, to illustrate how adaptability can transform data centers into valuable grid assets.

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INSIGHT

AI Factories Convert Power More Efficiently

AI data centers convert electricity into compute outputs with much less non-IT loss than before.
Modern AI factories can turn 80–90% of power into computations, increasing grid stress.

INSIGHT

Grids Plan For Worst-Case Nameplate Peaks

Grid planners assume a data center will request its full nameplate capacity at worst possible times.
Interconnection studies plan for peaks across many years, forcing cautious capacity upgrades.

INSIGHT

Training Vs Inference Load Shapes Differ

Training workloads are spiky with ramps and checkpoints, while inference is smoother but still unpredictable.
A single data center's profile can change over time as workloads shift between training and inference.

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Adding flexibility to data center loads could ease strain on the grid and reduce the need for costly new generation. And, according to one study, shaving off just a few megawatts during peak hours could also unlock unused capacity —as many as 98 gigawatts in the U.S — if those facilities reduced load by just 0.5% each year.

The problem: data centers promise near-perfect reliability, often “five nines” (99.999% uptime) in service-level agreements with customers. That leaves little room to adjust something as critical to reliability as power.

But times are changing. The data center market is reckoning with the constraints of the power grid and growing concern about pushing up electricity prices to pay for new generation. In July, the Electric Power Resource Institute’s DCFlex demonstration at an Oracle data center in Phoenix, Arizona, reduced load 25% during peak demand. And this month Google expanded its demand response through two new agreements with Michigan Power and the Tennessee Valley Authority.

So what are the actual mechanics of data center flexibility?

In this episode, Shayle talks to Varun Sivaram, founder and CEO of Emerald AI. The startup’s data center flexibility platform powered EPRI’s DCFlex demonstration. Shayle and Varun cover topics like:

What people often misunderstand about how much of their nameplate capacity data centers actually use
The distinct load profiles of training, inference, and other workloads
How data centers can pause, slow, or shift workloads in time or space to reduce demand
What it will take for flexibility solutions like Emerald AI to earn operator trust
How much flexibility data centers can realistically achieve
Varun’s long-term vision for evolving from occasional demand response to weekly or even daily load shifting

Resources:

Latitude Media: Nvidia and Oracle tapped this startup to flex a Phoenix data center
Latitude Media: Google expands demand response to target machine learning workloads
Catalyst: The potential for flexible data centers

Credits: Hosted by Shayle Kann. Produced and edited by Daniel Woldorff. Original music and engineering by Sean Marquand. Stephen Lacey is our executive editor.

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Catalyst is supported by EnergyHub. EnergyHub helps utilities build next-generation virtual power plants that unlock reliable flexibility at every level of the grid. See how EnergyHub helps unlock the power of flexibility at scale, and deliver more value through cross-DER dispatch with their leading Edge DERMS platform by visiting energyhub.com.

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