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There is no defensible single power or water figure for a “large” data center. Start with the information-technology (IT) load, not the building’s label: distinguish nameplate capacity from the average load and annual IT energy, declare the facility boundary, then apply power usage effectiveness (PUE) and site water usage effectiveness (WUE) under explicit cooling, climate and operating scenarios.
The core planning equations are facility energy = annual IT energy × PUE and site water (liters) = annual IT energy (kWh) × site WUE (liters/kWh). They produce a transparent estimate only when the numerator and denominator use the same period, meters and boundary. Water associated with electricity generation is a separate, source-water calculation.
Decide what “power” and “water” mean for your project
Separate IT capacity, average demand and annual energy
A data hall advertised as 20 MW may mean 20 MW of installed IT nameplate capacity, a utility service limit, or a contractual capacity. None is automatically the annual average load. Servers, storage and networking equipment operate at different utilizations, workloads fluctuate, and equipment may be installed before it is fully used.
- IT nameplate capacity: the rated capacity of the installed IT equipment or planned build-out, normally expressed in MW.
- Average IT demand: the time-weighted load actually drawn by IT equipment over a stated period.
- Peak IT demand: the highest coincident IT load that the electrical and cooling systems must support.
- Annual IT energy: the integrated IT load over a year, reported in kWh or MWh.
For an annual estimate, use metered annual IT energy or calculate it from a load profile. Multiplying nameplate MW by 8,760 hours assumes 100% utilization all year and is usually a planning upper bound, not a forecast.
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Declare the facility boundary
PUE is total data-center facility energy divided by IT-equipment energy. The facility side can include power transformation and distribution losses, UPS systems, lighting, pumps, fans, cooling equipment and other loads inside the declared boundary. State whether the boundary ends at the data-center building, includes a shared campus, or includes offices and other non-data-center spaces. Do not divide a whole-campus meter by a server-room denominator.
Choose a water boundary
Site WUE is annual site water use in liters divided by IT energy in kWh. It generally captures water used at the facility, chiefly for cooling, but the meter definition must be stated. Clarify whether your report covers withdrawal, discharge, consumption, or a utility-billed volume; those terms are not interchangeable.
If the question is a water footprint, add the water associated with electricity generation. That is called source WUE in Lawrence Berkeley National Laboratory (LBNL) guidance and requires a grid region, an electricity water-intensity factor and its year. There is no universal factor that can be applied to an unnamed site.
Collect the minimum inputs before calculating
A credible estimate should list these inputs beside every result:
- IT nameplate capacity, expected utilization and the hourly or seasonal load shape.
- Annual IT energy, or average load and operating hours used to derive it.
- PUE basis, measurement period and the exact facility boundary.
- Cooling technology and operating mode, including evaporative cooling, cooling-tower cycles and any economizer operation.
- Location, weather data or climate zone and design-day conditions.
- Whether water is site-only or includes source water from electricity generation.
- For a detailed model, UPS efficiency, power-transformation and distribution losses, fan and pump loads, redundancy mode and auxiliary spaces.
Missing inputs should become explicit uncertainty ranges. A precise-looking total with an unstated utilization or boundary is less useful than a range whose assumptions can be challenged.
Estimate electricity step by step
1. Build an IT load profile
Use interval meter data when available. Otherwise divide the planned equipment into classes (for example, general-purpose servers, accelerated-computing servers, storage and network equipment), assign an expected utilization to each class and model daily, weekly and seasonal variation. Integrate the resulting profile to obtain annual IT energy.
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For a simple constant-load illustration, a 20 MW IT installation operating at an assumed 50% average utilization has an average IT demand of 10 MW and annual IT energy of 87,600 MWh (10 MW × 8,760 hours). This is an illustrative calculation, not a benchmark for every 20 MW facility.
2. Select a PUE that matches the boundary and condition
Use annual energy on both sides when reporting PUE: PUE = annual total facility energy ÷ annual IT energy. A momentary power ratio can support a planning snapshot only if both measurements use the same boundary and operating condition. Seasonal cooling, partial occupancy and redundancy can make a snapshot differ materially from annual PUE.
3. Multiply IT energy by PUE
With the illustrative 87,600 MWh of annual IT energy:
| Illustrative planning assumption | Calculation | Facility energy |
|---|---|---|
| PUE 1.20 | 87,600 MWh × 1.20 | 105,120 MWh/year |
| PUE 1.40 | 87,600 MWh × 1.40 | 122,640 MWh/year |
| PUE 1.60 | 87,600 MWh × 1.60 | 140,160 MWh/year |
The PUE values in this table are deliberately labeled assumptions to show the method; they are not universal design targets. Your engineering model or measured operating data should supply the low, base and high values.
4. Estimate peak electrical demand separately
Annual facility energy does not by itself size the service entrance, generators or cooling plant. For a peak snapshot, combine the coincident peak IT load with a PUE-like ratio measured or assumed for that same condition. If a 20 MW IT peak coincides with an assumed snapshot ratio of 1.40, the conditional facility peak is 28 MW. Do not present that figure as an annual PUE result or assume that every subsystem peaks simultaneously without checking the load profile.
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1. Keep the denominator identical to the electricity calculation
Use the same annual IT kWh that underpins PUE. Site WUE is measured in liters per kWh, so the calculation is:
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Annual site water (L) = annual IT energy (kWh) × site WUE (L/kWh)
Convert only after calculating: 1,000 liters equals 1 cubic meter; 3.78541 liters equals one US gallon. Identify the conversion basis and region when reporting gallons.
2. Show a range rather than a universal coefficient
For the illustrative 87.6 million kWh of annual IT energy, the following assumed WUE values produce different site totals:
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| Illustrative WUE assumption | Annual site water | Equivalent volume |
|---|---|---|
| 0.5 L/kWh | 43,800,000 L | 43,800 m³ |
| 1.2 L/kWh | 105,120,000 L | 105,120 m³ |
| 2.0 L/kWh | 175,200,000 L | 175,200 m³ |
These are scenario arithmetic, not expected values for a particular cooling design. A site WUE report should identify the water meter, treatment losses, cooling-tower blowdown and the period covered.
3. Add source water only when the question requires a footprint
Source-water accounting adds the water intensity of the electricity supply to on-site water. Keep the two components in separate columns: on-site withdrawal or consumption, and source water attributable to purchased electricity. A source factor without a stated grid region and year cannot support a comparable result.
Why location and cooling change the answer
Cooling towers and evaporative heat rejection
A cooling tower rejects heat partly by evaporation. Makeup water therefore depends on IT heat, other facility loads, system efficiency, evaporation and blowdown. Water chemistry determines how many cycles of concentration the tower can run before water must be discharged.
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The US Department of Energy Federal Energy Management Program (FEMP) reports that increasing cooling-tower cycles of concentration from three to six reduces makeup-water requirements by 20% and blowdown by 50%. Those figures describe that operational change in a cooling tower, not a guaranteed percentage reduction in total facility water.
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Where outdoor conditions permit, air-side economizers can reduce mechanical-cooling hours. Separating hot and cold aisles and sealing bypass airflow reduce mixing and the cooling burden. Savings depend on climate, humidity limits, filtration, controls and the IT inlet-temperature envelope; they should be modeled rather than applied as fixed percentages.
Direct liquid cooling
Direct liquid cooling carries heat from IT components into a recirculating loop. The loop may reject heat through a cooling tower or another heat-rejection system, so “liquid cooled” does not by itself specify water use or power use. FEMP cites one National Laboratory of the Rockies example with PUE 1.06 and WUE 0.7. That is a result for that center and configuration, not a benchmark that every liquid-cooled facility will achieve.
Water treatment trade-offs
DOE notes that reverse-osmosis treatment can reduce freshwater needs in some settings but increases energy use and operations-and-maintenance requirements. A design that minimizes site water may therefore require more electricity, treatment equipment or maintenance. Include those loads in the same facility boundary used for PUE.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Build low, base and high scenarios
Use a scenario matrix instead of one “large data center” coefficient. Hold the IT workload and reporting period constant, then vary the factors that are genuinely uncertain.
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|---|---|---|---|
| IT utilization and workload | Documented lower-load profile | Best estimate from deployment plan | High-utilization or accelerated-computing profile |
| PUE | Measured or modeled efficient operating mode | Expected annual operating value | Hot-weather, partial-load or degraded-efficiency condition |
| Site WUE | Non-evaporative or highly optimized mode | Expected annual site value | Evaporative cooling, high blowdown or water-stressed operating constraint |
| Peak demand | Coincident load after controls | Design-day coincidence assumption | Redundancy, startup or worst-case operating condition |
Label every scenario with its climate, cooling mode, utilization and boundary. A low-water design can have a higher electricity requirement, while a lower-PUE design can consume more on-site water. Efficiency, reliability, resilience and local water availability must be evaluated together.
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Compare two designs on the same basis
When comparing cooling or electrical designs, keep the IT load, workload output, facility boundary and reporting period identical. Compare:
- Electricity: annual facility kWh and coincident peak demand, including treatment, pumps and fans.
- Water: on-site withdrawal and consumption, with source water shown separately.
- Climate fit: performance across local weather conditions, not only a design-day point.
- Reliability: redundancy, maintenance bypasses, controls and degraded-mode operation.
- Uncertainty: sensitivity to utilization, weather, equipment refresh and operating assumptions.
At workload level, LBNL’s 2025 review identifies server efficiency, grid water-consumption factors, server utilization, cooling type, infrastructure efficiency, climate zone, inactive-server share and server refresh cycle as important determinants. A facility WUE alone cannot describe the water intensity of a particular workload or account for water used to generate its electricity.
What national forecasts can—and cannot—tell you
LBNL’s United States Data Center Energy Usage Report: 2025 Update, published in 2026, estimates national electricity bottom-up from planned IT shipments, per-device annual energy, cooling simulations, facility types and locations. Its 2030 reference case is 649 TWh, with compounded-uncertainty cases of 521 to 843 TWh. The report gives a 2030 range of 9.5% to 15.3% of US electricity use, with an 11.8% reference estimate.
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LBNL’s 2024 methodology modeled 18 facility-space and cooling combinations, drew 50 scenarios per case and ran them against US weather-station data, producing more than one million PUE and site-WUE simulations. That scale illustrates why location, cooling and operating assumptions must remain visible in a project estimate.
Use profiling tools for scoping, then verify with meters
LBNL describes DC Pro and its PUE Estimator as early-stage profiling and scoping tools. The PUE Estimator asks facility questions and can be accessed without a login. It is useful for framing assumptions, but it does not replace subsystem metering, a commissioning process or a site engineering study.
For a real project, request and preserve:
- An interval-metered IT load profile and annual IT-energy total.
- A one-line electrical diagram showing the PUE boundary, shared loads and meter locations.
- Cooling-system sequences, design conditions, economizer limits, tower cycles and treatment equipment.
- Local weather inputs and the design-day assumptions used for peak sizing.
- Water-meter definitions, makeup and blowdown records, discharge handling and any reclaimed-water supply.
- The source-water factor, grid region and year if a footprint calculation is required.
Recalculate PUE and WUE after commissioning and at representative seasons. If a meter cannot isolate a shared load, report the allocation method and its uncertainty instead of implying that the number is directly measured.
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Common estimation mistakes
- Treating nameplate MW as annual demand: apply a documented utilization and load shape.
- Using a PUE from another facility: PUE changes with climate, redundancy, occupancy, boundary and operating mode.
- Mixing instantaneous power and annual energy: use matching time bases; annual PUE requires annual energy.
- Calling site WUE a complete water footprint: add source water only with a region- and year-specific factor.
- Hiding treatment and auxiliary loads: include pumps, fans, UPS, transformation and water treatment inside the stated boundary.
- Reporting one precise answer: publish low, base and high cases and identify the assumption that drives each spread.
- Optimizing water or power in isolation: evaluate the electricity, water, reliability and maintenance consequences together.
The Bottom Line
To estimate a large data center’s needs, obtain annual IT energy and a peak/load profile, declare the facility and water boundaries, and calculate facility energy with PUE and site water with WUE. Publish low, base and high scenarios that expose utilization, cooling, climate and grid assumptions; without those inputs, any single MW or water-volume figure is only a guess.
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