US Hyperscalers To Consume 22% More Grid Power By End of 2025 – Slashdot
Summary
A report summarised by The Register and citing 451 Research (S&P Global) warns that U.S. hyperscale datacentres will draw 22% more grid power by the end of 2025 than in 2024, with projections showing demand nearly trebling by 2030. The surge is driven mainly by machine‑learning model development and training on GPU‑heavy servers, plus growth in leased facilities and crypto‑mining. Forecasts put hyperscale grid demand at about 61.8 GW in 2025, rising to 75.8 GW in 2026, 108 GW in 2028 and 134.4 GW by 2030. Virginia and Texas are currently the largest concentrated loads, while operators are also eyeing states such as Idaho, Louisiana and Oklahoma for cheaper or stranded power and alternative generation options.
Key Points
- 451 Research predicts a 22% increase in hyperscale datacentre grid power demand in the US by end‑2025 versus a year earlier.
- Hyperscale grid demand is forecast to nearly treble by 2030, reaching roughly 134.4 GW (excludes enterprise‑owned facilities).
- Estimated figures: 61.8 GW in 2025, 75.8 GW in 2026, 108 GW in 2028, 134.4 GW in 2030.
- Primary driver: development and training of new machine‑learning models on power‑hungry GPU servers, plus cooling and power infrastructure needs.
- Virginia (12.1 GW) and Texas (9.7 GW) are highlighted as the biggest current state loads for datacentres in 2025.
- Datacentre builders favour greenfield builds rather than retrofits because of power and cooling requirements.
- Operators are scouting emerging markets and ‘stranded power’ opportunities in states like Idaho, Louisiana, Oklahoma and West Texas.
- The figures include leased and hyperscale facilities and crypto‑mining sites, but not enterprise datacentres.
Content summary
The article summarises the 451 Research findings: hyperscale facilities in the US will increase their draw on utility grids by 22% by the end of 2025, propelled largely by demand for ML training and GPUs. Building new facilities is often easier than retrofitting old ones due to the scale of electrical and cooling upgrades required. The research gives state‑by‑state detail, flagging Virginia and Texas as current hotspots while noting a search for lower‑cost or stranded power in other states. The projections extend to 2030 and underline the tension between rapid datacentre growth and local grid capacity, generation mix and consumer impacts.
Context and relevance
This is important for anyone tracking energy policy, grid planning, datacentre siting, or the environmental footprint of AI. Rapid increases in concentrated electricity demand affect local grid reliability, capacity planning, transmission upgrades and the economics of power generation — with knock‑on effects on consumer prices and on how quickly renewables and storage need to expand. Policymakers, utilities, regulators and regional planners will use this kind of forecast when allocating transmission upgrades, permitting generation projects, or negotiating power purchase agreements with hyperscalers.
Author style
Punchy: big numbers, big consequences. If you care about the future of AI infrastructure, energy policy or where new datacentres will appear, the details here matter — this isn’t just geekery, it’s infrastructure planning at scale.
Why should I read this?
Short version: hyperscalers are about to ramp up power use in a big way — that affects electricity grids, bills and where tech firms build next. We skimmed the long research so you don’t have to; read the detail if you want the numbers for planning, policy or investment decisions.