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The latest authoritative full-year estimate is about 176 terawatt-hours (TWh) of electricity consumed by U.S. data centers in 2023—roughly 4.4% of total U.S. electricity use. That is an estimate, not a live measurement of 2026 demand, and it excludes cryptocurrency-mining electricity. Lawrence Berkeley National Laboratory’s 2025 forecast puts 2030 consumption at 649 TWh in its reference case, with modeled scenarios ranging from 521 TWh to 843 TWh.
What the headline number means
A terawatt-hour is a unit of energy. The 2023 estimate of 176 TWh equals 176 billion kilowatt-hours over the year. Spread evenly across 8,760 hours, that is an average load of about 20.1 gigawatts (GW)—an arithmetic conversion, not a separate measurement of peak demand. The estimate and its 4.4% share of U.S. electricity consumption are summarized by the Congressional Research Service (CRS).
“Energy” in this article means electricity used by data centers. Facilities may also burn fuel in backup generators or use other behind-the-meter sources, but the headline national estimates focus on electricity. Electricity consumption, peak power demand, carbon emissions, and water use are different measures and should not be treated as interchangeable.
What counts as a data center?
A data center is the physical infrastructure that stores, processes, and moves digital information: servers, storage, networking, power equipment, and cooling systems. The category can encompass hyperscale cloud facilities, colocation buildings rented by multiple customers, enterprise and government computer rooms, research-computing sites, and smaller edge facilities. Servers can also sit inside office or other commercial buildings.
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In other words, “the cloud” is not an abstract place. It runs on buildings and equipment, and the electricity estimate attempts to capture data-center activity broadly. It is not, however, a complete census with a meter reading for every facility. The 176 TWh estimate excludes cryptocurrency mining, so it should not be read as a figure for every electricity-consuming computing operation under every possible definition.
How consumption has changed
U.S. data centers used about 70 TWh in 2014, compared with the estimated 176 TWh in 2023—more than double over that period. The Department of Energy’s Federal Energy Management Program summarizes the historical estimate and an earlier forecast that put annual growth from 2023 to 2028 at 13% to 27%. That growth-rate range belongs to the earlier forecast; it is not a measurement of what happened in each subsequent year. See the DOE/FEMP data-center fact sheet.
The increase is not all attributable to artificial intelligence. Conventional cloud services, business computing, storage, streaming, online services, and networking also use data-center electricity. AI has become a major recent and projected growth driver, but it is one part of a larger digital infrastructure buildout.
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What the 2030 forecast says
LBNL’s 2025 update estimates future U.S. data-center electricity use using scenarios, not a guaranteed outcome. The percentages below refer to modeled total U.S. electricity use; the TWh figures are annual consumption. The LBNL report page describes the scenarios and their assumptions.
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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstall| 2030 scenario | Annual data-center electricity | Approximate share of U.S. electricity | Average continuous load equivalent |
|---|---|---|---|
| Low compounded-uncertainty case | 521 TWh | 9.5% | About 59.5 GW |
| Reference case | 649 TWh | 11.8% | About 74.1 GW |
| High compounded-uncertainty case | 843 TWh | 15.3% | About 96.2 GW |
The average-load equivalents are conversions of annual TWh divided by 8,760 hours; they are not forecasts of each facility’s peak load. The reference case is LBNL’s central estimate under its assumptions. The wider range reflects compounded uncertainty, rather than a promise that consumption will land at either endpoint.
What could move the forecast
- How many data-center IT systems are installed, including specialized graphics processors used for AI.
- How intensively servers and accelerators are used, their idle power, and how long AI chips remain in service.
- Cooling-system performance and the mix of facility types.
- How much new data-center capacity is built, and where it is located.
LBNL’s 2025 update uses a bottom-up model drawing on equipment shipments, device-level electricity assumptions, cooling simulations, facility characteristics, and locations. The scenarios depend on those inputs; they are not direct meter readings of all U.S. facilities.
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Why AI can raise both computing and facility demand
AI training and inference can use large numbers of GPUs or other accelerators. These chips can draw substantially more power than ordinary server processors, and AI workloads can keep them busy at high utilization. Moving data quickly among multiple accelerators also requires networking and supporting equipment. Every watt used by IT equipment becomes heat that must be managed, adding demand for cooling and power delivery.
CRS reports maximum thermal design power ratings of roughly 350 to 700 watts for some advanced data-center GPUs. A chip’s rated maximum is not the same as its actual electricity use, nor does it describe the power draw of a complete server or facility. The whole-facility result also depends on the number of devices, workload, operating time, cooling, and power-conversion equipment.
There is no universal electricity cost for an AI prompt. It varies with the model and hardware, response length, batching, utilization, cooling, location, and whether a calculation counts only the accelerator or the full facility. A separate EPRI estimate cited by CRS puts AI at 10% to 20% of data-center energy in 2024; that is a distinct estimate and should not be combined casually with LBNL’s national totals.
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Where a data center’s electricity goes
The split varies with facility design, climate, equipment, and workload. CRS summarizes evidence indicating that at least roughly half of data-center electricity demand goes directly to IT equipment. It also cites illustrative industry estimates—not a universal allocation—in which servers and systems account for about 40%, networking and storage about 10%, and cooling about 38% to 40%.
| Use | What it includes | How to interpret it |
|---|---|---|
| IT equipment | Servers, processors, memory, storage, and networking | The computing and data-handling load; its share varies by facility. |
| Cooling | Chillers, pumps, fans, cooling towers, air handlers, or liquid-cooling systems | Removes heat from IT equipment. The required amount depends on climate, design, and operating conditions. |
| Power delivery | Transformers, switchgear, uninterruptible power supplies, batteries, and distribution | Supports reliable delivery and conversion of electricity within the facility. |
| Building services | Lighting and other building systems | Part of whole-facility consumption, generally smaller than the main IT and cooling loads. |
| Backup generation | Typically backup generators and associated systems | Important for reliability, emissions, and permitting, but usually not a major source of normal annual electricity use. |
How to read PUE
Power usage effectiveness (PUE) is total facility energy divided by energy used by IT equipment. A PUE of 1.2 means the facility uses 1.2 units of electricity for every 1 unit used by IT; a PUE of 2.0 means another unit goes to cooling, power conversion, and other infrastructure for each IT unit.
PUE measures facility overhead, not useful computing work per watt, electricity carbon intensity, or AI-model efficiency. A low-PUE facility can still use a very large amount of electricity if its IT load is large.
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Why the national average can hide local grid pressure
Data centers are concentrated geographically, so a national share of 4.4% does not mean every region experiences a comparable increase. A large facility can require tens or hundreds of megawatts of capacity. In a particular area, the timing and location of new load can make generation availability, transmission, distribution upgrades, and interconnection queues more consequential than the national annual TWh total.
Effects on electricity markets and household bills depend on the region, utility regulation, rate design, available generation, contracts, and how infrastructure costs are allocated. CRS reported that, as of the end of 2024, there was little evidence of a nationwide effect on electricity rates while some regional effects were visible. That is a time-specific observation, not a guarantee about future bills or local outcomes.
Facility capacity figures also need careful reading. A reported megawatt number may describe IT load, total facility load, utility service, a planned build-out, a single construction phase, or peak or contracted capacity. Those figures are not directly comparable unless their definitions match. For scale, a continuously operating 100-MW load uses about 0.876 TWh per year before accounting for facility overhead.
How data centers fit into rising U.S. electricity demand
Data centers are one contributor to a broader shift in electricity use. EIA’s Annual Energy Outlook 2026 says U.S. electricity consumption grew by an average of 2.1% per year over the preceding five years, after a long period of near-flat demand. Across its modeled cases, EIA projects annual electricity-consumption growth of about 0.9% to 1.6% through 2050 and identifies data-center server energy use as a major factor.
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Those are national electricity-demand projections, not data-center-only forecasts. Manufacturing, building and transportation electrification, heating, cryptocurrency, and general economic growth can also add demand. The data-center share depends on both how quickly facilities use more electricity and how the national total changes.
What the estimates can—and cannot—tell you
- There is no complete, standardized public meter-by-meter dataset. Private operators may not disclose facility-level consumption, and studies can draw the boundary around “data center” differently.
- The 176 TWh figure is a modeled historical estimate for 2023. It is the latest authoritative full-year estimate available as of August 18, 2026, not a measurement of 2026 consumption.
- Cryptocurrency treatment matters. The 176 TWh LBNL-based estimate excludes cryptocurrency-mining electricity use.
- Forecasts rely on assumptions. Shipments and installations, utilization, chip lifetimes, idle power, cooling performance, and construction all affect the modeled 2030 result.
- Electricity source affects grid comparisons. A facility may use grid supply, behind-the-meter generation, or a mix. An electricity-consumption estimate does not by itself establish how much load the grid serves at a particular moment.
Nor does TWh alone determine environmental or household-finance impact. Carbon emissions depend on the electricity source and accounting method; water use depends on cooling technology, climate, design, and local conditions. Ratepayer effects depend on utility rules, contracts, and infrastructure spending. The 176 TWh figure should not be converted into a carbon total or a household-bill effect without those additional inputs.
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