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Home / Business and Economy / Grid Strain: AI's Massive Power Demand by 2030

Grid Strain: AI's Massive Power Demand by 2030

29 Jan

•

Summary

  • US data centers' electricity use to surge by 2030.
  • Grid transmission capacity is lagging behind demand.
  • Interconnection delays are a significant barrier for AI.
Grid Strain: AI's Massive Power Demand by 2030

By 2030, U.S. data centers are projected to consume 426 terawatt hours of electricity, a substantial increase that highlights a critical strain on the nation's power grid. This figure represents more than double the 183 terawatt hours consumed in 2024.

The primary challenge is not power generation, but the transmission system's capacity to deliver electricity where and when it is needed. Hyperscale data centers now demand 500 megawatts or more, comparable to a midsized city's consumption, with AI workloads requiring exceptionally stable power.

In 2024, only 888 miles of high-voltage transmission lines were completed, far below the estimated 5,000 miles needed annually. This physical grid capacity constraint leads to multiyear interconnection delays for data center developers, impacting AI investment and deployment.

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Federal policies are shifting to support grid expansion, with over $20 billion allocated for grid funding programs. Regulatory changes, like FERC Order 1920, now mandate transmission planning that includes future AI and electrification loads, indicating a sustained buildout phase for grid modernization.

Disclaimer: This story has been auto-aggregated and auto-summarised by a computer program. This story has not been edited or created by the Feedzop team.
US data centers are projected to consume 426 terawatt hours of electricity by 2030.
The main challenge is the transmission system's capacity to deliver electricity where and when it is needed, rather than power generation capacity.
Federal policies are allocating over $20 billion for grid funding, and regulatory changes mandate transmission planning that includes future AI and electrification loads.

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