Making data centers flexible so they can serve the grid rather than stress it out

Emerging technologies in data centers are being developed to enhance their flexibility and responsiveness to the electrical grid, addressing the increasing demand for power without necessitating extensive grid upgrades. Varun Sivaram, founder of Emerald AI, explains that traditional data centers typically require constant high power, particularly during peak hours, which can strain the grid. However, by implementing software that orchestrates computing loads, data centers can reduce their demand during peak times, potentially allowing for the addition of up to 100 gigawatts of new load without requiring new generating capacity.

Emerald AI's software, known as Conductor, enables data centers to adjust their operations through three types of flexibility: temporal, spatial, and resource. This allows data centers to manage when and where computing tasks occur, as well as to utilize on-site resources like batteries more effectively. Sivaram emphasizes the importance of this flexibility, suggesting that data centers could become controllable energy assets, akin to batteries or generators, which could help integrate more renewable energy into the grid.

The conversation also touches on regulatory challenges and the need for enforceable contracts that ensure data centers fulfill their flexibility commitments. Sivaram argues that making flexibility a legal requirement could enhance grid reliability and support the integration of clean energy sources. He envisions a future where flexible data centers are standard, significantly contributing to the energy landscape by 2030. This shift is seen as essential for accommodating the growing demands of AI and other technologies while promoting a more sustainable energy system.

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.volts.wtf/subscribe

Typically, AI data centers are large, inflexible loads that the grid has to build around, which is one reason utilities take so long to connect them. Emerald AI has designed a “digital brain” that can ramp down, move, or delay computing jobs in a data center on demand, making a data center a flexible asset to the grid. I talk with CEO Varun Sivaram about how the software works, what flexibility costs the compute, why it beats just installing batteries, whether utilities can enforce it, and what it would mean for clean energy. Chapters: 00:00 – Introduction 03:05 – Temporal, spatial, and resource flexibility 06:26 – What Emerald Conductor touches on site 08:35 – Who decides which workloads can flex 10:55 – Who is liable when a job slows down 13:45 – Who actually signs the contract 14:49 – Larger and faster grid connections 18:02 – Enforcing the flexibility promise 19:05 – What broke in the demos, from bad nodes to slow telemetry 26:41 – What flexing costs the compute jobs 29:21 – Why not just use batteries, and the demand merit order 35:44 – Training, inference, and substation-scale data centers 40:23 – PJM, ERCOT, and legal enforceability 44:50 – Renewables, gas, and consumer bills