Technical guideFree to read2026

Integrating AI Data Centers with the Power Grid

National Academy of Engineering, The Bridge (LBNL authors) · Jessica Granderson, Ian M. Hoffman et al.

This LBNL article addresses demand flexibility for AI data centers facing grid constraints. It sets out four flexibility mechanisms, utility tariff approaches that encourage flexibility, and operator motivations, stressing that flexibility complements but does not replace new generation.

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Overview

The article was published in The Bridge of the National Academy of Engineering and its authors are from Lawrence Berkeley National Laboratory (they include Jessica Granderson, Ian M. Hoffman and Natalie Mims Frick). It is dated 2026 and carries DOI 10.20357/B7X61S.

According to the abstract, there are four flexibility mechanisms: computational load flexibility, flexible use of core facility infrastructure, energy storage and onsite generation. They represent different ways in which a data center can adjust the power it draws from the grid over time.

On the utility side, the tools include voluntary interruptible service riders, mandated flexibility requirements and faster interconnection for flexible loads. On the operator side, the drivers are faster interconnection, regulatory compliance and reduced community opposition. The article also relays a projection that US data center energy use will reach two to three times its 2023 level by 2028.

The article's central caution is that flexibility complements but does not replace new generation. Flexibility is therefore not the sole answer to the capacity problem, but a tool that can speed up interconnection and ease pressure on the grid.

Key points

  1. Four mechanisms: computational load flexibility, flexible use of core facility infrastructure, energy storage and onsite generation.
  2. Utility tools: voluntary interruptible service riders, mandated flexibility requirements and faster interconnection for flexible loads.
  3. Operator drivers: faster interconnection, regulatory compliance and reduced community opposition.
  4. US data center energy use is projected to reach two to three times its 2023 level by 2028.
  5. Flexibility complements but does not replace new generation.
  6. Published in The Bridge (National Academy of Engineering), LBNL authors, 2026.

Using it in design

  • Expose flexibility capability per design (curtailable MW, BESS duration, on-site generation) as outputs for interconnection applications.
  • Treat a flexible-load commitment as an input to interconnection-timing negotiations.
  • Do not assume flexibility is the only answer to a capacity shortfall; assess the need for new generation separately.

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Who should read it

Electrical designers planning grid interconnection and energy strategy, operators, and policy analysts.

Publication details

Authors
Jessica Granderson; Ian M. Hoffman; Billie Holecek; Eliot Crowe; Sarah Josephine Smith; Natalie Mims Frick
Publisher
National Academy of Engineering, The Bridge (LBNL authors)
Year
2026
Document language
English
Source type
Expert / community
Access
Free to read
Licence
Copyright retained; citation only — the publisher’s terms apply to the original document
Original licence note

LBNL (contractor-operated DOE laboratory) resource; not US-Gov public domain. Cited only.

Citation

Jessica Granderson; Ian M. Hoffman; Billie Holecek; Eliot Crowe; Sarah Josephine Smith; Natalie Mims Frick (2026). Integrating AI Data Centers with the Power Grid. National Academy of Engineering, The Bridge (LBNL authors). https://doi.org/10.20357/B7X61S

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