Where AI data centers are being built, the power they need, and the grid bottlenecks standing in the way.
2026 edition · Built from public EIA, LBNL & ERCOT data.
The 8 findings, the chart that explains the AI power crunch, and a preview of the regional race.
Where the AI buildout meets the grid — in under half a minute. Sound on.
For most of the last decade the binding constraint on large-scale computing was silicon. It isn't any more. What now determines where — and how fast — AI capacity gets built is electricity: how much a region has, how quickly new supply can be connected, and whether the transmission exists to move it.
The forecasts are converging — upward. LBNL's 2025 Update (June 2026) found data centers used 4.7% of U.S. electricity in 2024 and projects about 12% by 2030 (a 9.5–15.3% range), requiring roughly 148 GW of grid connections. EPRI's 2026 analysis lands in the same place: 9–17% by 2030, about 60% above its own 2024 estimate. The leading 2026 studies now span roughly 380–840 TWh a year in 2030, about a twofold spread. We still publish the range rather than pick a winner; every figure here traces to a public primary source and is documented in the methodology.
The U.S. is not short of proposed generation. It is short of connected generation. The median wait to plug a new project into the grid has more than doubled, to about 5 years (61 months for projects built in 2025). And most queued capacity is never built at all: of everything that requested interconnection between 2000 and 2020, just 13% is operating, while about 75% was withdrawn. The queue behaves as an attrition filter, not a build pipeline. Compute scales in months; interconnection scales in years. Read the full breakdown →
Supply is spread across 2,459 utility-scale plants, but demand concentrates. Northern Virginia alone operates about 4,500 MW — more data-center capacity than any market on Earth. In Texas, roughly 474 GW sits in the ERCOT large-load queue, around 90% of it data centers, and under 1% of it is actually drawing power. Those are the grids where the collision happens first. See all 16 regional deep-dives →
Rather than wait out the queue, developers increasingly route around it — behind-the-meter gas, nuclear power purchase agreements and restarts, and small modular reactors. The queue's composition is shifting to match: total volume fell about 10% in 2025 as withdrawals outpaced new requests, even as natural gas requests surged 86% to 253 GW. How the workarounds actually work → And there is a second constraint behind the first — cooling water, much of it demanded in already high-water-stress regions.
New to the terminology? The glossary defines interconnection queue, behind-the-meter, PUE, WUE, curtailment and more — in plain English, with sources.
36 pages of maps, data, and analysis — every figure sourced.
The top 15 metros, mapped and ranked — from Northern Virginia to the inland breakout markets.
Gas, nuclear & SMRs, solar-plus-storage — and the on-site generation boom.
Queue sizes, wait times, and why "queued" is nowhere near "built."
Texas, Virginia, Arizona, Ohio & Georgia — each with a map, stats, and risk rating.
Five scenarios for where the next wave of capital and capacity lands.
Power plants, queues & data-center clusters as CSV / GeoJSON you can use.

Supply is everywhere — 2,459 utility-scale plants — but demand concentrates onto specific, already-stressed grids. The full report breaks down every market, queue, and scenario.
Get the free summary →We publish our analysis in the open, every figure cited. Three deep-dives — a preview of the rigor behind the report.
Interactive: enter a facility size and U.S. market, and see its power draw, homes-equivalent, grid wait and water footprint instantly — computed from public EIA / LBNL figures.
Try the free tool →Why the real limit on AI isn't power plants — it's the interconnection queue, where median waits more than doubled to ~5 years and ~75% of proposed capacity is withdrawn.
Read the analysis →How the buildout routes around the 5-year wait — behind-the-meter gas, nuclear restarts, and SMRs. The deals, megawatts and dates, primary-source cited.
Read the analysis →The constraint with no workaround. Cooling water intensity, hyperscaler use, and why ~2/3 of new U.S. data centers sit in high-water-stress areas.
Read the analysis →Plus 16 regional deep-dives — Northern Virginia, Texas, Phoenix, Memphis, Salt Lake City, Reno and more.
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