Work

Sustainable Grid through Distributed Data Centers : Spinning AI Demand for Grid Stabilization and Optimization

Year: 2025

Type: conference-paper

Abstract: We propose a disruptive paradigm to actively place and schedule TWhrs of parallel AI jobs strategically on the grid, at distributed, grid-aware high performance compute data centers (HPC) capable of using their massive power and energy load to stabilize the grid while reducing grid build-out requirements, maximizing use of renewable energy, and reducing Green House Gas (GHG) emissions. Our approach will enable the creation of new, value adding markets for spinning compute demand, providing market based incentives that will drive the joint optimization of energy and learning.

Source: IEEE Conference on Technologies for Sustainability

DOI: 10.1109/sustech63138.2025.11025705

Authors: Scott C Evans, Sachini Piyoni Ekanayake, Alexander Duncan, Blake Rose, Hao Huang, Ibrahima Ndiaye, Nathan Dahlin

Institutions: GE Vernova (United States), University at Albany, State University of New York

Language: English

Topic: Smart Grid Energy Management

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Climate action, Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W4411233561

FWCI:

Cites: 19

Cited by:

Related to: 10