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Title: MSD CoP Webinar: Energy and AI

Abstract

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org).   Abstract: Projections of the need for new data centers to support Artificial Intelligence (AI) are large but highly uncertain. Recent projections indicate up to a 15% annual growth rate in data center electricity demand within the next 5-10 years. Given that most electric utilities are required to have a reserve margin of roughly the same magnitude as the projected growth in demand, these new data center loads could soon threaten resource adequacy and reliability unless data centers build their own generation, interruptible loads are negotiated, commensurate new capacity and/or transmission is built, or some combination of these options. Similarly, depending on the cooling technology and geographic location of new data centers, they could threaten water adequacy in water scarce regions. This webinar will provide an overview of the interactions between energy and AI and highlight two MSD projects exploring the grid and water implications of new data centers to support AI.  Presenters : Dr. Casey Burleyson (Pacific Northwest National Laboratory); Dr. Stephanie Morris (Pacific Northwest National Laboratory); Kendall Mongird (Pacific Northwest National Laboratory) Moderator: Patrick M. Reed (MSD CoP Facilitation Team) This webinar wasmore » held on:  June 16th, 2025 from 1-2 PM EST.« less

Authors:
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  1. Pacific Northwest National Laboratory
Publication Date:
Research Org.:
Pacific Northwest National Lab (United States)
Sponsoring Org.:
USDOE Office of Science (SC); Biological and Environmental Research (BER); Awarding Entity, Inc.
Subject:
Artificial Intelligence; Energy
OSTI Identifier:
2569721
DOI:
https://doi.org/10.57931/2569721

Citation Formats

Burleyson, Casey, Morris, Stephanie T., and Mongird, Kendall. MSD CoP Webinar: Energy and AI. United States: N. p., 2025. Web. doi:10.57931/2569721.
Burleyson, Casey, Morris, Stephanie T., & Mongird, Kendall. MSD CoP Webinar: Energy and AI. United States. doi:https://doi.org/10.57931/2569721
Burleyson, Casey, Morris, Stephanie T., and Mongird, Kendall. 2025. "MSD CoP Webinar: Energy and AI". United States. doi:https://doi.org/10.57931/2569721. https://www.osti.gov/servlets/purl/2569721. Pub date:Wed Jun 18 00:00:00 EDT 2025
@article{osti_2569721,
title = {MSD CoP Webinar: Energy and AI},
author = {Burleyson, Casey and Morris, Stephanie T. and Mongird, Kendall},
abstractNote = {Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org).   Abstract: Projections of the need for new data centers to support Artificial Intelligence (AI) are large but highly uncertain. Recent projections indicate up to a 15% annual growth rate in data center electricity demand within the next 5-10 years. Given that most electric utilities are required to have a reserve margin of roughly the same magnitude as the projected growth in demand, these new data center loads could soon threaten resource adequacy and reliability unless data centers build their own generation, interruptible loads are negotiated, commensurate new capacity and/or transmission is built, or some combination of these options. Similarly, depending on the cooling technology and geographic location of new data centers, they could threaten water adequacy in water scarce regions. This webinar will provide an overview of the interactions between energy and AI and highlight two MSD projects exploring the grid and water implications of new data centers to support AI.  Presenters : Dr. Casey Burleyson (Pacific Northwest National Laboratory); Dr. Stephanie Morris (Pacific Northwest National Laboratory); Kendall Mongird (Pacific Northwest National Laboratory) Moderator: Patrick M. Reed (MSD CoP Facilitation Team) This webinar was held on:  June 16th, 2025 from 1-2 PM EST.},
doi = {10.57931/2569721},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Jun 18 00:00:00 EDT 2025},
month = {Wed Jun 18 00:00:00 EDT 2025}
}