Data centers are concentrated industrial loads. They consume electricity for computing and for cooling, power conversion, networking, storage, and other support systems. Some cooling designs consume water on site, while the electricity supply can consume additional water at power plants. The local result depends on the facility’s design, operating profile, climate, utility, watershed, and the infrastructure needed to serve it—not on a single national average.
Global demand is substantial: the International Energy Agency (IEA) estimates that data centers used about 415 terawatt-hours (TWh) of electricity in 2024 and projects about 945 TWh in 2030 in its base case. Those figures are a baseline estimate and a scenario projection, not a guarantee for any particular country or community.
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Do data centers use a lot of electricity?
Yes. A data center’s servers are the primary electrical load, but they are not the only one. Electricity also runs cooling equipment, pumps, fans, environmental controls, storage systems, networking equipment, lighting, security systems, uninterruptible power supplies, and other power-conversion equipment. A facility’s total demand therefore includes both information-technology (IT) equipment and the systems that keep it operating.
Where the electricity goes
- Computing: Servers perform the calculations that run cloud applications, websites, databases, artificial-intelligence workloads, and other services.
- Storage and networking: Disks, solid-state storage, switches, routers, and communications equipment move and retain data.
- Cooling and environmental control: Chillers, cooling towers, pumps, fans, air handlers, and controls remove heat and maintain temperature and humidity limits.
- Power infrastructure: Transformers, switchgear, batteries, generators, and uninterruptible power supplies consume energy while delivering stable power to the IT load.
Cooling’s share varies widely. The IEA reports that cooling can account for roughly 7% of electricity use in efficient hyperscale facilities and more than 30% in less-efficient enterprise facilities. These figures illustrate the range between facility types; they are not a universal percentage for an individual site.
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Global estimates and projections
The IEA estimates worldwide data-center electricity consumption at approximately 415 TWh in 2024, about 1.5% of global electricity use. In its base case, demand reaches about 945 TWh in 2030, just under 3% of global electricity use. The IEA identifies uncertainty in equipment shipments, efficiency improvements, and the pace of artificial-intelligence adoption. It also notes that data-center demand is geographically concentrated, which can make local grid integration more difficult than the global percentage suggests.
What the U.S. scenarios show
A U.S. Department of Energy and Lawrence Berkeley National Laboratory (DOE/LBNL) 2025 update, published in 2026, uses a bottom-up model based on equipment shipments, per-device energy use, facility types, locations, and cooling simulations. Its reference case estimates 649 TWh of U.S. data-center electricity use in 2030. When sensitivity and compounded-uncertainty cases are included, the estimate spans 521–843 TWh, equivalent to about 9.5–15.3% of projected U.S. electricity use in 2030.
| Measure | Value | How to interpret it |
|---|---|---|
| Global data-center electricity use, 2024 | About 415 TWh | IEA estimate of current global consumption, not a metered total for every facility. |
| Global base-case demand, 2030 | About 945 TWh | IEA scenario projection; outcomes depend on efficiency, equipment shipments, and AI adoption. |
| U.S. reference case, 2030 | 649 TWh | DOE/LBNL modeled estimate. |
| U.S. compounded-uncertainty range, 2030 | 521–843 TWh | DOE/LBNL scenario range, or approximately 9.5–15.3% of projected U.S. electricity use. |
These national and global numbers should not be treated as a forecast for a particular town. A local project may be much smaller or larger than the average implied by a national total, and its effect depends on the utility’s existing capacity, transmission network, contracts, and regulatory decisions.
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Why do data centers need water?
Servers turn electricity into heat. Cooling systems move that heat out of the building so equipment can operate within its design limits. Some systems reject heat primarily with air; others use water, often through cooling towers or other evaporative equipment. Water may also circulate in a closed loop and be replenished only when treatment, blowdown, leaks, or evaporation require it.
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Direct on-site water
Direct water use occurs at the facility. Evaporative cooling consumes water when a portion of the supply changes to vapor and leaves the site. Cooling towers also require blowdown: a controlled discharge used to prevent minerals and contaminants from concentrating in the circulating water. Other direct uses can include humidification, treatment systems, sanitation, and emergency testing, although cooling is usually the central issue in water discussions.
Withdrawal and consumption are different. Withdrawal is the amount taken from a river, aquifer, utility, or other source. Consumption is the portion not promptly returned to that immediate water cycle, often because it evaporates. The LBNL 2024 report defines consumption as “the amount of withdrawn water that is permanently removed from the immediate water cycle due to evaporation or other irreversible processes.” A project can have high withdrawals but return much of the water, or lower withdrawals with a larger consumed share. Any comparison must state which measure it uses.
Indirect water in electricity generation
Electricity can carry a second water footprint upstream. Thermoelectric power plants commonly use water for cooling, and hydropower reservoirs can lose water through evaporation. The amount varies with the generation technology, cooling system, weather, and location of the plant serving the data center. As a result, a facility’s on-site water figure does not describe all water associated with its electricity use.
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LBNL distinguishes direct, site water consumption from “source” water associated with electricity generation. Adding those values requires compatible boundaries and methods. Publishing only a cooling-tower number can understate the broader water implications; adding an upstream estimate without explaining the grid boundary can overstate or mislead.
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How are electricity and water efficiency measured?
Power Usage Effectiveness (PUE)
PUE is total data-center electricity divided by IT-equipment electricity. A PUE of 1.2, for example, would mean that the facility uses 1.20 units of total electricity for every 1.00 unit used by its IT equipment, but that example is illustrative rather than a value for a particular project. The denominator, measurement period, and operating conditions must be stated before PUE values can be compared.
Water Usage Effectiveness (WUE)
WUE is water consumption per unit of IT-equipment electricity, reported in liters per kilowatt-hour. It is an intensity metric, not a prediction of a community’s total water demand. A low WUE can result from a cooling design that uses little on-site water, but the electricity source may still have a significant upstream water footprint. Conversely, a design with higher direct water use may reduce electricity consumption in a particular climate or operating condition.
Why workload-level water use can differ so much
An LBNL review published in 2025 reports variations exceeding 10,000-fold in water use per workload across different circumstances. The review identifies server efficiency, electricity-grid water factors, server utilization, cooling type, infrastructure efficiency, climate, the share of inactive servers, and the server refresh cycle as important determinants. There is no single cooling recipe that minimizes water in every location.
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Cooling system and climate
Air-cooled, liquid-cooled, hybrid, and evaporative systems have different electricity and water profiles. Hot, dry, humid, or water-stressed climates change the performance of each option. A design that saves water by relying more heavily on mechanical refrigeration may increase electricity use; a design that saves electricity with evaporation may consume more site water. Seasonal peak conditions matter as much as annual averages.
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Server efficiency and utilization
More efficient processors can perform the same task with less electricity, but total demand can still rise if the facility adds servers or runs them more intensively. Inactive or lightly used servers consume resources without delivering the same useful work as fully utilized equipment. Refresh schedules also matter: newer equipment can be more efficient, while manufacturing and replacing equipment have their own resource requirements outside the facility’s operating metrics.
Grid mix and operating schedule
The same building can have different source-water implications depending on which generators supply it. A grid dominated by water-intensive thermoelectric generation has a different upstream profile from one with substantial wind or solar generation, although every grid has a changing mix over time. Operating hours, load ramps, and the ability to shift flexible workloads affect when the facility draws power and whether its load coincides with regional peaks.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How do data centers affect nearby communities?
Concentrated demand and infrastructure
Data centers can add a large, rapidly growing load at one interconnection point. Serving it may require new substations, transmission upgrades, generation, backup arrangements, or construction of utility infrastructure. The IEA identifies geographic concentration as a reason integration can be challenging even when data centers represent a modest share of national electricity use.
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11It is not possible to conclude from national studies alone that a particular project will raise household bills, reduce reliability, or cause outages. Those outcomes depend on utility planning, rate design, contracts, regulation, and the specific grid. A sound local analysis identifies who pays for upgrades, how costs are allocated, what capacity is available, and how the utility manages coincident peaks.
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Water supply and watershed pressure
Community water questions require the facility’s direct withdrawals and consumption, source and quality of water, peak-day demand, seasonal pattern, and discharge conditions. Those figures should be compared with the water provider’s treatment capacity, the watershed’s available supply, drought rules, and other users’ needs. A national water total cannot establish that a named community will face a shortage.
Potential benefits and burdens
Projects can bring construction and operations jobs, tax revenue, and investment in utility infrastructure. They can also impose costs through land conversion, noise, backup-generator emissions, road construction, water-system expansion, or public spending on infrastructure. The balance is location-specific. DOE’s resource hub identifies grid planning, cooling innovation, and water reuse as relevant areas for local decision-making, but examples from one site should not be generalized to every project.
How should communities compare data-center proposals?
Use the same boundaries and time periods for every option. The following framework prevents a low value on one metric from hiding a high value on another.
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|---|---|
| Electricity | What are annual and peak demands? How quickly can load change? Do figures include cooling, storage, networking, and power-conversion systems? |
| Water | What are direct withdrawals and direct consumption? What is the source and quality of water? What are peak-day and seasonal values? Is source water from electricity reported separately? |
| Place | How stressed is the local watershed? What competing demands exist? What generation mix and transmission constraints apply? How does the climate affect cooling? |
| Efficiency and flexibility | Are PUE and WUE definitions, boundaries, and measurement periods disclosed? What are server utilization, cooling design, and documented load-shifting capabilities? |
| Community accountability | Who pays for new infrastructure under the applicable rates and regulations? What jobs and tax effects are expected? Will water, electricity, and performance data be reported publicly? |
What information should residents and planners request?
- Facility load profile: Request connected load, expected annual consumption, peak demand, ramp rates, operating hours, and the share attributable to IT equipment versus support systems.
- Cooling and water balance: Request the cooling technology, water source, treatment chemicals, withdrawal, consumption, discharge, and maximum daily and seasonal demands.
- Common boundary definitions: Confirm whether reported water is withdrawal or consumption and whether electricity figures include all facility systems. Ask for PUE and WUE definitions rather than relying on labels alone.
- Grid-service documents: Review interconnection studies, utility filings, transmission and substation plans, generation assumptions, rate treatment, and cost-allocation agreements.
- Water-system documents: Check permits, water-provider capacity studies, drought plans, watershed assessments, discharge permits, and reuse commitments.
- Monitoring and enforcement: Identify meters, reporting frequency, public data access, permit limits, contingency plans, and consequences if promised efficiency or water targets are missed.
- Local planning record: Read environmental reviews, zoning documents, construction plans, tax agreements, emergency plans, and the community’s own infrastructure assessments.
What can and cannot be inferred from national projections?
National projections are useful for showing scale and direction. They do not reveal a local project’s water source, electricity supplier, cooling design, peak demand, or effect on a particular utility. The DOE/LBNL estimate is produced by a bottom-up model rather than by metering future consumption. Its method is described as follows: “The resulting electricity usage estimates in this Report are derived from a ‘bottom-up’ energy use model, which determines electricity use from real-world data for planned data center IT equipment shipments (purchases), models of per-device annual electricity use and cooling system performance simulations, along with information on data center facility types and locations.”
That approach supports scenario planning, not certainty. Local conclusions require project filings, utility and water-provider documents, permits, environmental reviews, and community planning records. If those documents do not disclose a number, it should be reported as unknown rather than filled with a national average.
What is the practical takeaway?
Data centers use electricity for both computing and the systems that keep computing equipment online. Water can be consumed directly for cooling and indirectly at the power plants that supply the electricity. PUE and WUE help describe intensity, but neither metric alone determines a community impact. The decisive questions are local: how large and flexible the load is, which cooling system and climate apply, where water comes from, what generation serves the site, what infrastructure must be built, and how costs and performance will be monitored.
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