Technical Challenges of AI Data Center Integration into Power Grids—A Survey

The rapid expansion of Artificial Intelligence is fueling the growth of hyperscale data centers, which introduces significant challenges to existing power systems. This paper aims to provide a comprehensive survey of these integration challenges, specifically from the perspective of power grid utility. We find that AI data centers function as a distinct load category, characterized by high power density, rapid and large-scale power transients, and specific power quality profiles. These attributes create difficulties for long-term resource adequacy and transmission planning due to mismatched development timelines. They also strain real-time grid balancing and introduce risks to system stability, such as voltage and frequency deviations and converter-driven instabilities. The analysis further covers the economic and environmental footprints associated with this new type of consumer. The paper concludes that safely integrating these loads requires a coordinated strategy, encompassing data center-side technologies, grid-enhancing solutions, and new policy frameworks.

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Publication Details

Journal
Energies
Published
2025-12-26
DOI
https://doi.org/10.3390/en19010137
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
0.00
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article

Technical Challenges of AI Data Center Integration into Power Grids—A Survey

Pavel Lifshits, Ram Machlev, Juri Belikov, Yoash Levron et al.
Energies
Optimal Power Flow Distribution
article

Technical Challenges of AI Data Center Integration into Power Grids—A Survey

Pavel Lifshits, Ram Machlev, Juri Belikov, Yoash Levron, Elinor Ginzburg-Ganz, Ziv Krieger
article en

Abstract

The rapid expansion of Artificial Intelligence is fueling the growth of hyperscale data centers, which introduces significant challenges to existing power systems. This paper aims to provide a comprehensive survey of these integration challenges, specifically from the perspective of power grid utility. We find that AI data centers function as a distinct load category, characterized by high power density, rapid and large-scale power transients, and specific power quality profiles. These attributes create difficulties for long-term resource adequacy and transmission planning due to mismatched development timelines. They also strain real-time grid balancing and introduce risks to system stability, such as voltage and frequency deviations and converter-driven instabilities. The analysis further covers the economic and environmental footprints associated with this new type of consumer. The paper concludes that safely integrating these loads requires a coordinated strategy, encompassing data center-side technologies, grid-enhancing solutions, and new policy frameworks.

EnergiesVol. 19(1)
Tallinn University of Technology (EE), Technion – Israel Institute of Technology (IL)
Openalex Percentile: Top 41%
Optimal Power Flow Distribution
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Technical Challenges of AI Data Center Integration into Power Grids—A Survey — Pavel Lifshits, Ram Machlev, et al. · Energies (2025) | TGRS Research Map | TGRS