EPRI Study: Data Centers Could Consume up to 9% of U.S. Electricity Generation by 2030

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May 29, 2024, 08:00 ET

PALO ALTO, Calif., May 29, 2024 /PRNewswire/ -- As artificial intelligence (AI) becomes more entrenched in our 24/7 digital economy, the demand for power could surge from the data centers processing AI. According to a new study released today by EPRI, data centers could consume up to 9% of U.S. electricity generation by 2030—more than double the amount currently used. This could create regional supply challenges, among other issues.

AI queries require approximately ten times the electricity of traditional internet searches and the generation of original music, photos, and videos requires much more. With 5.3 billion internet users, rapid adoption of these new tools could increase power demands substantially. At the same time, computing facilities are becoming more concentrated, with single facilities now requesting power consumption that can range from the equivalent of 80,000 to 800,000 homes, exacerbating power delivery challenges.

Drawing on public information about existing data centers, estimates of industry growth, and private electricity demand forecasts by industry experts, EPRI outlined four scenarios of potential annual electricity consumption in U.S. data centers from 2023 to 2030, with annual growth rates ranging from 3.7% to 15%. The lowest scenario assumed limited public uptake of AI tools, coupled with high gains in data center efficiency, and the highest scenario combined rapid expansion of AI applications with fewer efficiency gains. These scenarios placed data center power ranges from 4.6%-9.1%.

"The U.S. electricity sector is working hard to meet the growing demands of data centers, transportation electrification, crypto-mining, and industrial onshoring, while balancing decarbonization efforts," said EPRI Vice President of Electrification and Sustainable Energy Strategy David Porter. "The data center boom requires closer collaboration between large data center owners and developers, utilities, government, and other stakeholders to ensure that we can power the needs of AI while maintaining reliable, affordable power to all customers."

The analysis also looked at regional impacts of increased AI power demand. An estimated 80% of the national data center load in 2023 was concentrated in 15 states, led by Virginia and Texas. Demands for highly reliable power, requests for power from new, non-emitting generation sources, and short lead times for connection—of two years or less—can create local and regional electricity supply challenges.

To overcome these challenges, the analysis suggested three essential strategies:

Improve data center efficiency and flexibility.
Coordinate closely between data center developers and utilities regarding power needs, timing, flexibility, and delivery constraints.
Develop better modeling tools to anticipate and accommodate data center growth without affecting grid reliability.

To address better modeling tools, EPRI recently launched a comprehensive, two-year program to examine and develop new strategies for meeting emerging operational and planning load forecasting challenges. One key focus is on projections of large loads such as data centers. The initiative is exploring better approaches for forecasting load during extreme weather events, estimating customer deployment of distributed energy resources, changing customer behavior, and the impacts of emerging technologies.

A link to EPRI's full analysis is available here: Powering Intelligence: Analyzing Artificial Intelligence and Data Center Energy Consumption (epri.com)

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Rachel Gantz
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Tim Trudell
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About EPRI

Founded in 1972, EPRI is the world's preeminent independent, non-profit energy research and development organization, with offices around the world. EPRI's trusted experts collaborate with more than 450 companies in 45 countries, driving innovation to ensure the public has clean, safe, reliable, affordable, and equitable access to electricity across the globe. Together, we are shaping the future of energy.

SOURCE EPRI