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The 470-Gigawatt Queue

Texas is fielding more data-centre power requests than the entire US grid can build this decade. The number tells you where the AI build-out actually breaks.

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· Updated 6 min read
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The most important number in AI infrastructure this year is not a parameter count or a capital-expenditure figure. It is a queue. As of June 2026, the Texas grid operator ERCOT was tracking roughly 470 gigawatts of large-load interconnection requests, about 90% of them tied to data centres, according to figures compiled by grid-modelling firm Energy Exemplar from ERCOT and Utility Dive reporting. Only about 9 GW of that had approval to energise. Real peak load from these projects was about 3.9 GW.

For scale, the entire ERCOT system serves a summer peak of roughly 85 GW. The queue is more than five times the size of the grid it wants to join. Most of it will never be built. But the gap between what is requested, what is approved and what actually draws power is the clearest available picture of where the AI build-out is constrained.

ERCOT large-load requests versus reality, June 2026
Gigawatts
Interconnection requests470 GWApproved to energise9 GWActual peak load3.9 GW
Source: Energy Exemplar, citing ERCOT and Utility Dive, August 2026.

ERCOT large-load requests versus reality, June 2026. GW: Interconnection requests 470 GW, Approved to energise 9 GW, Actual peak load 3.9 GW.

What the federal numbers say

A 2026 Department of Energy study, produced at the direction of Congress and summarised in a Congressional Research Service report, found that US data centres consumed about 192 terawatt-hours in 2024, roughly 4.7% of national electricity. It projected consumption rising to between 521 TWh and 843 TWh by 2030, or 9.5% to 15.3% of the US total. A separate 2026 study by the Electric Power Research Institute put the 2030 range at 9% to 17%.

Those are wide ranges, and the spread is the point. Nobody can forecast AI demand with precision, which is why grid operators are hedging. The North American Electric Reliability Corporation observed that many operators revised their summer 2026 demand projections downward, citing the observed completion rate of large-load interconnections and the slower-than-expected pace at which loads are coming online. Even after the revision, NERC expected peak demand about 11 GW higher in 2026 than in 2025, largely because of data centres.

US data-centre share of national electricity consumption
DOE 2026 study: 2024 actual and 2030 projected range
0%5%10%15%20%20242030 low2030 high
Source: US Department of Energy 2026 study, via Congressional Research Service report R49326.

US data-centre share of national electricity consumption. Share of US consumption: 2024 4.7%, 2030 low 9.5%, 2030 high 15.3%.

Who pays

The politics arrived before the power. On 4 March 2026 the White House announced the Ratepayer Protection Pledge, accepted that day by seven technology companies: Amazon, Google, Meta, Microsoft, OpenAI, Oracle and xAI. Under the proclamation published in the Federal Register, the signatories commit to build, bring or buy the generation their data centres need, to pay for new delivery infrastructure, to negotiate separate rate structures with utilities and states, and to pay for reserved infrastructure whether they use the electricity or not.

The pledge is voluntary. A Brookings analysis notes that it lacks enforcement, and that public opposition is rising regardless: a February 2026 Marquette Law School poll found 70% of Wisconsin voters believed the costs of new data centres outweigh the benefits, up from 55% six months earlier. State legislatures are moving faster than Washington, with several states creating large-customer rate classes that require data centres to fund their own upgrades.

The relief valve

If supply cannot be built fast enough, demand has to bend. On 19 March 2026 Google said it had integrated a total of 1 GW of demand response capacity into its long-term energy contracts with utilities including Indiana Michigan Power, the Tennessee Valley Authority, Entergy Arkansas, Minnesota Power and DTE Energy. Under these agreements, data centres shift or reduce load when the grid is stressed, which lets utilities connect them sooner than a fixed, always-on load would allow.

Demand response does not solve the queue. Training runs and latency-sensitive inference cannot always wait for the grid. But it changes the negotiation between developers and utilities from a fight over capacity to a schedule for flexibility, and that is the shape of the deals that will get built.

Who benefits, who is at risk

Beneficiaries are regions with spare interconnection capacity and clean firm power, equipment makers with long lead-time products, and developers willing to accept flexible or self-supplied power. At risk are developers holding speculative queue positions, utilities that build for demand that never materialises, and, unless pledges become tariffs, the residential ratepayers the pledge was written to protect.

What happens next?

  • ERCOT's batch process for large loads decides which of the 470 GW gets serious; expect most requests to fall away.
  • More states codify large-load tariffs that shift upgrade costs to developers, turning the voluntary pledge into binding rules.
  • Demand-response and behind-the-meter generation become standard terms in data-centre power contracts.
  • Downward forecast revisions continue until interconnection completion rates catch up with announcements.

Sources & references

  1. 01Powering the AI Data Center Buildout Means Rethinking the GridEnergy ExemplarreportERCOT queue figures; cites Utility Dive and ERCOT's Batch Zero process.
  2. 02Data Centers and the Electricity Grid: Frequently Asked Questions (R49326)Congressional Research ServiceprimaryDOE 2026 study, EPRI 2026 study and NERC summer 2026 assessment.
  3. 03Ratepayer Protection Pledge (Proclamation)Federal Registerprimary
  4. 04The pledge to protect ratepayers from AI data center costs needs enforcementBrookings Institutionreport
  5. 05A new milestone for smart, affordable electricity growthGooglecompany
Published 13 September 2026 · Updated 14 September 2026 · Report a correction · How we use AI
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