AI data centers are driving rapid demand growth, exposing the limits of traditional electricity forecasting and planning.

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Electricity demand in the United States is rising fast, fueled in large part by the rapid expansion of AI data centers. Grid operators have repeatedly revised their demand forecasts upward as they try to anticipate how much new power these facilities, along with other emerging loads such as advanced manufacturing and crypto mining, will require.

In January, however, something unexpected happened. PJM Interconnection, the nation’s largest grid operator, lowered its demand growth outlook, just weeks after a capacity auction driven by expectations of booming demand produced record high prices.

Estimating how much electricity new data centers and other large loads will actually add to the grid is difficult, and the uncertainty cuts both ways. Overestimating demand can leave consumers paying for grid infrastructure that never gets fully used. Underestimating it can threaten reliability. All of this is playing out as the rapid buildout of data centers is increasingly framed as a question of economic competitiveness and national security.

On the podcast, Shana Ramirez and Arne Olson of Energy and Environmental Economics argue that while improving forecast accuracy remains important, uncertainty itself needs to play a more central role in how the grid is planned and governed. In a recent E3 paper, they lay out why demand forecasts will remain imperfect, and why grid rules and planning processes should be designed to work across a range of possible outcomes rather than relying on a single view of the future.

Ramirez and Olson discuss the reliability and cost challenges this uncertainty creates and describe governance approaches that could help the power system remain reliable and affordable as new loads come online.

Shana Ramirez is director, asset valuation and markets at E3.

Arne Olson is a senior partner at E3.

Related Content:

Boomtowns in the Battery Belt: Risks and Opportunities of Clean Energy Investments in Small Towns of America https://kleinmanenergy.upenn.edu/research/publications/boomtowns-in-the-battery-belt-risks-and-opportunities-of-clean-energy-investments-in-small-towns-of-america/

Energy System Planning: New Models for Accelerating Decarbonization https://kleinmanenergy.upenn.edu/research/publications/energy-system-planning-new-models-for-accelerating-decarbonization/

Energy Policy Now is produced by The Kleinman Center for Energy Policy at the University of Pennsylvania. For all things energy policy, visit kleinmanenergy.upenn.edu.

AI data centers are driving rapid demand growth, exposing the limits of traditional electricity forecasting and planning.
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Electricity demand in the United States is rising fast, fueled in large part by the rapid expansion of AI data centers. Grid operators have repeatedly revised their demand forecasts upward as they try to anticipate how much new power these facilities, along with other emerging loads such as advanced manufacturing and crypto mining, will require.
In January, however, something unexpected happened. PJM Interconnection, the nation&rsquo;s largest grid operator, lowered its demand growth outlook, just weeks after a capacity auction driven by expectations of booming demand produced record high prices.
Estimating how much electricity new data centers and other large loads will actually add to the grid is difficult, and the uncertainty cuts both ways. Overestimating demand can leave consumers paying for grid infrastructure that never gets fully used. Underestimating it can threaten reliability. All of this is playing out as the rapid buildout of data centers is increasingly framed as a question of economic competitiveness and national security.
On the podcast, Shana Ramirez and Arne Olson of Energy and Environmental Economics argue that while improving forecast accuracy remains important, uncertainty itself needs to play a more central role in how the grid is planned and governed. In a recent E3 paper, they lay out why demand forecasts will remain imperfect, and why grid rules and planning processes should be designed to work across a range of possible outcomes rather than relying on a single view of the future.
Ramirez and Olson discuss the reliability and cost challenges this uncertainty creates and describe governance approaches that could help the power system remain reliable and affordable as new loads come online.
Shana Ramirez is director, asset valuation and markets at E3.
Arne Olson is a senior partner at E3.
Related Content:
Boomtowns in the Battery Belt: Risks and Opportunities of Clean Energy Investments in Small Towns of America <a href="https://kleinmanenergy.upenn.edu/research/publications/boomtowns-in-the-battery-belt-risks-and-opportunities-of-clean-energy-investments-in-small-towns-of-america/">https://kleinmanenergy.upenn.edu/research/publications/boomtowns-in-the-battery-belt-risks-and-opportunities-of-clean-energy-investments-in-small-towns-of-america/</a>
Energy System Planning: New Models for Accelerating Decarbonization <a href="https://kleinmanenergy.upenn.edu/research/publications/energy-system-planning-new-models-for-accelerating-decarbonization/">https://kleinmanenergy.upenn.edu/research/publications/energy-system-planning-new-models-for-accelerating-decarbonization/</a>
Energy Policy Now is produced by The Kleinman Center for Energy Policy at the University of Pennsylvania. For all things energy policy, visit kleinmanenergy.upenn.edu.

Energy Policy Now offers clear talk on the policy issues that define our relationship to energy and its impact on society and the environment. The series is produced by the Kleinman Center for Energy Policy at the University of Pennsylvania and hosted by energy journalist Andy Stone. Join Andy in conversation with leaders from industry, government, and academia as they shed light on today's pressing energy policy debates.

Energy Policy Now

Energy Policy Now offers clear talk on the policy issues that define our relationship to energy and its impact on society and the environment. The series is produced by <a href="https://kleinmanenergy.upenn.edu/podcast/">the Kleinman Center for Energy Policy</a> at the University of Pennsylvania and hosted by energy journalist Andy Stone. Join Andy in conversation with leaders from industry, government, and academia as they shed light on today's pressing energy policy debates.

AI data centers are driving rapid demand growth, exposing the limits of traditional electricity forecasting and planning.