Technical guideCitation2026

Energy Usage Impact - New Holistic Metrics for AI Data Centers: A Discussion with The Green Grid

The Green Grid · Ricardo Gonzalez Llera, Pritish Parida et al.

This 2026 Green Grid video discussion introduces Energy Usage Impact (EUI) and the DCRE family (WUI, ITWC) as holistic metrics for AI-era data centers, arguing that PUE alone is no longer sufficient.

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Overview

The source is a video discussion listed in The Green Grid library with the date 22 April 2026. The speakers are Ricardo Gonzalez Llera, Pritish Parida (IBM) and Julius Neudorfer (NAAT). The record rests only on the library's public landing page; the video content itself is not summarised here, and access requires a free account sign-in. The discussion covers DCRE and its companion metrics WUI, ITWC and EUI.

These are presented as holistic measures that address dimensions such as energy, water and IT work capacity together. From the source's short description, the metrics appear to be intended as complementary indicators rather than a single reduced efficiency number; the formulas of the metrics are not part of this record. The main message is that traditional metrics such as PUE are insufficient for AI-driven data centers.

PUE measures the efficiency of facility infrastructure but does not measure the work done on the IT side or water use. The heavy energy and water demand of AI loads brings these dimensions to the fore as things to be tracked. As to limits, the official Green Grid definition of EUI should be treated as still developing; the definition to be published must be tracked before formulas are implemented.

The ISO/IEC 30134 series is named as the related standards family. The source is a discussion video and not a binding standard or calculation method. The source matters because it shows the direction of the industry debate on efficiency created by AI loads; however, since no settled calculation standard exists yet, it should be used as a roadmap input in design and reporting and not as a binding yardstick.

Key points

  1. The source is a video dated 22 April 2026.
  2. Speakers: Ricardo Gonzalez Llera, Pritish Parida (IBM), Julius Neudorfer (NAAT).
  3. It covers DCRE and the companion metrics WUI, ITWC and EUI.
  4. Traditional metrics such as PUE are positioned as insufficient for AI-driven data centers.
  5. The metrics aim to address energy, water and IT work capacity together.
  6. Related standards family: ISO/IEC 30134 series.
  7. The record rests only on the public abstract page and contains no formulas.

Using it in design

  • In the metrics roadmap, plan an EUI/DCRE panel combining energy, water and IT work capacity next to PUE.
  • Track the forthcoming Green Grid EUI definition before implementing formulas.
  • In AI-loaded designs, treat water use as a separate monitoring point.
  • Present PUE reports with complementary indicators and do not read them alone.
  • Build a reporting structure compatible with the ISO/IEC 30134 series.

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Who should read it

Designers, operators and ESG leads who set efficiency and sustainability indicators for AI-era data centers.

Related standards

  • ISO/IEC 30134 series

Publication details

Authors
Ricardo Gonzalez Llera; Pritish Parida; Julius Neudorfer
Publisher
The Green Grid
Year
2026
Document language
English
Source type
Industry body
Access
Citation only
Licence
Copyright retained; citation only — the publisher’s terms apply to the original document
Original licence note

Download requires a free TGG account sign-in and is governed by The Green Grid Terms of Use; summary and facts from the public library landing page; full text not redistributed.

Citation

Ricardo Gonzalez Llera; Pritish Parida; Julius Neudorfer (2026). Energy Usage Impact - New Holistic Metrics for AI Data Centers: A Discussion with The Green Grid. The Green Grid. https://www.thegreengrid.org/resources/library-and-tools/energy-usage-impact-new-holistic-metrics-ai-data-centers-discussion

All content and rights belong to the respective authors and publishers. SoSo CAD provides only the citation, its own summary and a link to the source, and is not responsible for the sources' content.