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Data centers draw electricity for two jobs: running information-technology equipment and operating the cooling, power-delivery and building systems that keep that equipment online. A large campus can become one of the biggest customers on a utility system, but its effect on a community is not determined by its annual energy total alone. Peak demand in megawatts, the timing and speed of growth, the facility’s location, and the generation and network capacity available there determine whether upgrades, higher costs or reliability concerns arise.
For the United States as a whole, a 2025 Lawrence Berkeley National Laboratory (LBNL) update estimates that data centers used 192 terawatt-hours (TWh) in 2024, or 4.7% of national electricity consumption. Its 2030 Reference Case projects 649 TWh, equal to 11.8% of forecast U.S. use, but the modeled 2030 range is much wider: 521–843 TWh (9.5%–15.3%). Those national figures describe a sector, not the load or bill impact of a particular town.
What electricity inside a data center actually runs
Servers, storage and networking
The primary load is information technology (IT): servers executing workloads, storage systems retaining data, and network equipment moving traffic. Artificial-intelligence training and inference can use dense server configurations whose power characteristics differ from older general-purpose equipment. LBNL’s 2025 update revised historical estimates and forecasts as new equipment-shipment data and assumptions about AI inference-server power became available. Treat each estimate as versioned, not as a timeless measurement.
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Every watt consumed by IT equipment ultimately becomes heat that must be removed. Chillers, cooling towers, pumps, fans, heat exchangers and controls therefore add a substantial support load. Facilities also consume electricity in uninterruptible power supplies, power distribution equipment, lighting, offices, security systems and other building services. The mix depends on climate, cooling design, utilization and redundancy requirements.
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The U.S. Energy Information Administration (EIA) summarizes the two dominant uses plainly: “These facilities consume large amounts of electricity, both to run their computing equipment and to keep them cool.” That description does not mean cooling is the only non-IT use; it identifies the two principal categories.
What the national estimate includes
LBNL’s 2025 U.S. update accounts for servers, storage, network equipment and supporting infrastructure, and explicitly excludes cryptocurrency mining. Its totals should not be read as a complete measure of every computing facility or as a combined data-center-and-crypto total. When comparing studies, check the publication year, equipment assumptions and scope before treating numbers as directly comparable.
Energy (TWh) and power (MW) answer different questions
Energy is the amount consumed over time. A terawatt-hour measures billions of kilowatt-hours used over a year; gigawatt-hours and megawatt-hours are smaller versions of the same concept. Power is the rate of electricity use at a moment, expressed in megawatts (MW). A facility can have moderate annual energy use but a high short-term peak, or operate at a steadier lower level. Utilities must plan for the highest coincident demand and for how long it lasts, not only for annual TWh.
This distinction explains why a national annual share cannot predict a neighborhood’s peak demand. A continuously operating campus may request firm power around the clock, while a facility that can delay or curtail some workloads presents a different planning problem. In an EIA description of an ERCOT program, a “large flexible load” is associated with expected peak demand capacity of at least 75 MW. That threshold belongs to ERCOT’s process and is not a universal definition for other regions.
How much electricity U.S. data centers use
| Measure | Value | How to interpret it |
|---|---|---|
| 2024 U.S. consumption | 192 TWh (4.7% of total U.S. electricity) | LBNL 2025 update; an estimate of data-center use, excluding cryptocurrency mining. |
| 2030 Reference Case | 649 TWh (11.8% of forecast U.S. electricity) | LBNL projection, not an observed outcome. |
| 2030 combined modeled range | 521–843 TWh (9.5%–15.3%) | LBNL range across modeled scenarios and uncertainties. |
| Share of 2024–2030 U.S. load growth | 33% | Conditional comparison with NERC’s 2025 Long-Term Reliability Assessment; the comparison assumes NERC values include data-center use consistently. |
The Reference Case is a planning scenario, not a promise that 649 TWh will occur. The range reflects uncertainty in deployment, utilization, efficiency and AI-server power. LBNL’s revision of earlier values is a reminder to identify the report year whenever quoting a forecast or historical estimate.
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Why one large facility can matter to a local grid
A concentrated new customer changes the local load shape
A data center connects at a specific point on a distribution or transmission network. If several buildings are built near one another, their demand is geographically concentrated rather than spread across thousands of customers. Growth that arrives faster than a utility’s generation, substation or line additions can create an interconnection queue and require staged construction before the full campus can energize.
Generation, transmission and distribution must all be adequate
Serving the load may require contracts or projects for additional generation, high-voltage transmission, substations, transformers and local feeders. A region can have enough generation in aggregate but still lack a line or transformer capable of delivering it to the site. Conversely, a nearby transmission upgrade may be affordable while regional generation is scarce. The binding constraint is location-specific.
Timing and firm-power requirements affect reliability planning
Many data-center operations are designed for continuous availability, so operators often seek firm service rather than power that is routinely interruptible. A sudden cluster of always-on loads can raise the system peak and reduce the margin available during heat waves, cold snaps or generator outages. Grid operators therefore study coincident peaks, reserve requirements and the schedule for each phase of a project.
Prices and outages are risks, not automatic outcomes
EIA’s March 2026 modeled analysis finds that faster-than-expected demand growth can appear as wholesale price spikes or, in stressed cases, periods of rolling blackouts. Its scenarios also indicate that most regions could accommodate higher-than-expected growth, while near-term load increases produced notable price challenges in modeled ERCOT results. These are modeled possibilities, not evidence that a particular data center caused an outage or raised a household’s bill.
Who pays for the new infrastructure
Rate design and interconnection agreements determine how costs are allocated. DOE’s rate-design work highlights fair assignment of system costs, operational and resource adequacy, and the risk of stranded investment if a utility builds assets for expected load that does not materialize. Contracts may require a customer contribution, minimum payments or other protections, but the terms differ by utility and regulator. National consumption statistics cannot establish whether local retail rates will rise.
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What state-level examples show—and what they do not
EIA reported that Virginia commercial electricity demand increased by 14 billion kilowatt-hours between 2019 and 2023, associating much of the increase with Dominion Energy Virginia and rapid data-center development. The figure is growth in the entire commercial sector, not a direct meter reading of data centers alone. EIA also observed strong commercial-demand increases in Texas and some other states, while commercial use in several large states was flat or below 2019 levels.
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How utilities, grid operators and regulators can respond
Interconnection studies and staged energization
Grid managers evaluate whether existing lines, substations, transformers and generation can serve a proposed load. They can require network upgrades, sequence construction in phases, or set milestones tied to the facility’s demonstrated demand. EIA describes this interconnection oversight as a way to ensure that new large customers can be served by available supply.
Efficiency and better cooling
More efficient servers, higher utilization, liquid cooling, improved airflow management and controls can reduce the electricity needed for a given computing workload. Efficiency lowers both annual energy and the size of supporting electrical and cooling equipment, although efficiency gains may be offset if total computing demand grows faster.
New generation and a broader supply portfolio
DOE identifies solar, land-based wind, batteries and energy efficiency as rapidly scalable options, while noting that clean firm resources such as next-generation geothermal and nuclear may also be important. A portfolio can combine variable renewable generation with storage, firm supply and transmission rather than relying on a single technology. No option automatically removes a local transmission or transformer bottleneck.
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- Various Monitoring Parameters: The power meter plug can monitor the power (W), energy (kWh), volts, amps, hertz, power factor, cost, minimum and maximum power (W), cumulative days and time of your appliances. By switching 7 display modes, you can easily know the various parameters while the appliance is working. The home energy monitor can also calculate and display how much power your appliance uses and how much electricity bill it cost in cumulative time
- Upgraded LCD display: With large screen size 2.36 inch x 1.85 inch, clearer monitor backlit, our electrical usage monitor can display the data clearer and more visible no matter day or night. 180°full wide viewing angles is great for reading and recording the data in any angles. No need to stand on the front of the display and bend over to read the numbers
- Adjustable Backlight Time: Our upgraded watt meter has 5 options of backlight time. The default backlight time duration is 10 minutes(bL-0). If you want to change the backlight time, you can press and hold "UP" and "DOWN" button at the same time to enter backlight time setting, then press "UP" and "DOWN" to select the backlight time (bL-0 =10 minutes, bL-1=1 hour, bL-2=4 hours, bL-3=8 hours, bL-4=always on), finally press the "COST" to save the backlight time settings
- Overload protection: When the power of the appliance exceeds the overload power, the LCD will display “OVERLOAD” to warn the user. All the buttons will quit working and can only be workable when you lower or remove the load power. The default overload power is 3680W and is adjustable from 0 to 3680W. In general, you need to set the overload power to 1800W before using. Just press the "function" button for more than 3 seconds to enter the setting
- Data Memory Function: The wattage meter will record your power consumption data when you remove it from socket, or remove appliances from the electricity monitor. You can directly see the last data when you use it next time. This function can also automatically save the data when there is a sudden power failure
Storage and onsite generation
Batteries can discharge during constrained hours and recharge when the system has headroom. Onsite generation can provide capacity or backup, subject to fuel, emissions, permitting and interconnection rules. DOE also discusses matching consumption with carbon-free output and using onsite capacity to support adequacy. These measures change the facility’s net demand profile; they do not make the underlying grid connection irrelevant.
Demand flexibility and curtailment
Some computing tasks can be scheduled for less-constrained hours, and some customers can agree to reduce load temporarily. In Texas, ERCOT’s large-flexible-load process uses a 75 MW expected peak-demand-capacity threshold. EIA reported that some large loads have voluntary agreements to curtail during particularly high system demand or when generator availability is low. The cited group includes data centers, cryptocurrency mining and certain industrial facilities, so the agreements should not be attributed to every data center.
Transmission and distribution expansion
Where local lines or substations are the limit, utilities may build new circuits, transformers or high-voltage connections. Construction takes time and can create cost-allocation disputes. A project that is canceled or delayed after equipment is ordered can leave underused assets, the stranded-investment risk identified by DOE.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A practical framework for judging a proposed facility
Residents, planners and policymakers can ask for the following information instead of relying on a national percentage:
- Peak demand: the requested and expected maximum MW, including the timing and duration of peaks.
- Annual energy: projected TWh or GWh, kept separate from MW capacity.
- Interconnection status: completed studies, required upgrades, energization milestones and the responsible utility or grid operator.
- Local capacity: available generation, transmission, substations and distribution equipment under normal and contingency conditions.
- Growth profile: how quickly additional buildings or server halls will come online and whether demand could exceed the initial request.
- Flexibility: workloads that can shift, contractual curtailment, batteries or onsite generation, and the conditions under which they would operate.
- Cost allocation: customer contributions, rate treatment, minimum-use commitments and protections against underused infrastructure.
- Estimate scope: the date and methodology of any energy forecast, including whether cryptocurrency mining is included and which facility systems are counted.
Common mistakes when interpreting data-center electricity claims
Treating annual TWh as a local peak forecast
An annual national share says nothing by itself about a specific feeder’s maximum load. Local studies must use MW, timing and network topology.
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Assuming every data center has the same profile
Cooling design, climate, redundancy, server mix, utilization and flexibility vary. A hyperscale campus, a colocation building and an enterprise facility can have very different demand shapes.
Equating renewable procurement with local adequacy
A power-purchase contract or renewable certificate can address energy attributes while the local grid still needs firm capacity, transmission and deliverability during peak hours.
Assuming curtailment is guaranteed
Only loads with an explicit program or contract can be expected to reduce demand under defined conditions. Voluntary participation in one ERCOT process does not establish a rule for another region.
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Using an older state snapshot as a current forecast
Virginia’s 2019–2023 commercial-demand increase is useful context, but a current decision requires the local utility’s latest load forecast, interconnection study and rate order.
What the evidence supports
Data centers are electricity-intensive because computing equipment runs continuously and because cooling and power infrastructure must remove heat and maintain reliable operation. U.S. consumption is already large and could grow substantially by 2030, but the forecast has a broad range. For a community, the decisive questions are where the load connects, how high and inflexible its peak is, whether generation and wires can be expanded in time, and how regulators assign the resulting costs. Those factors—not a national percentage alone—determine whether a particular facility is manageable, expensive to serve or a source of stress during tight system conditions.
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