There is no defensible single number for a “large” data center. Estimate its needs by starting with an IT load profile, converting annual IT energy with a declared power usage effectiveness (PUE), and calculating on-site water with site water usage effectiveness (WUE). Keep peak demand separate from annual energy, and state the cooling system, climate, facility boundary, utilization, and whether the water figure includes only the site or also water associated with electricity generation.
Define what you are measuring before doing any arithmetic
People asking “How much power does a large data center use?” may mean several different quantities. A utility must size for maximum coincident demand in megawatts (MW), while an energy budget is usually reported in megawatt-hours (MWh) or gigawatt-hours (GWh) per year. Water planners may need withdrawal, consumption, makeup water, blowdown, or a broader source-water footprint. Those are not interchangeable.
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Nameplate capacity is not average demand
IT nameplate capacity is the maximum rated electrical capacity of servers, storage, and networking equipment. A 100 MW nameplate does not mean the equipment draws 100 MW every hour. Utilization, workload mix, power-management settings, inactive servers, and seasonal variation determine the load profile. Record at least the expected average IT demand, the maximum IT demand, and how many hours each operating state lasts.
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Power, energy, and peak demand use different units
- MW or kW: an instantaneous demand or a design rating.
- MWh or GWh: energy consumed over a stated period.
- Annual IT energy: the denominator used for a defensible annual PUE or site-WUE calculation.
- Peak facility demand: the maximum combined IT and non-IT load that the electrical system must serve, including the operating condition and redundancy assumptions.
For an annual estimate, calculate IT energy from interval data whenever possible. If only an average IT demand is available, multiply it by the hours in the reporting period; use 8,760 hours for a non-leap year and document any excluded downtime or leap-year adjustment.
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Declare the facility boundary
DOE defines PUE as total data-center facility energy divided by the energy used by all IT equipment. State whether the numerator includes cooling plants, air handlers, fans, pumps, UPS losses, power distribution, lighting, controls, offices, workshops, or a whole-campus meter. The denominator and numerator must cover the same facility and period. Quietly pairing a server-room IT meter with a campus-wide utility bill produces a misleading ratio.
Collect the inputs that control the estimate
A planning worksheet should request the following information before a coefficient is chosen.
| Input | What to record | Why it changes the result |
|---|---|---|
| IT capacity and load shape | Nameplate MW, measured intervals, expected utilization, workload mix, and peak-to-average ratio | Determines annual IT kWh and the electrical peak. |
| Reporting period | Month, season, or full year; operating hours and growth date | PUE and WUE are most meaningful when both sides use the same period. |
| Facility boundary | Which meters and buildings are inside the calculation | Prevents non-comparable numerator and denominator values. |
| Cooling design | Chilled water, air-side economizer, cooling tower, dry cooler, direct liquid cooling, or hybrid; operating modes and set points | Changes mechanical energy, evaporation, makeup water, and weather sensitivity. |
| Location and weather | Grid region, climate, design temperatures, humidity, and local weather data | Economizer hours, heat rejection, and source-water intensity vary by location. |
| Water accounting boundary | Site withdrawal, site consumption, discharge, reclaimed water, and source water associated with electricity | “Water use” can describe different physical quantities. |
| Detailed electrical systems | UPS topology and efficiency, transformers, switchgear, distribution losses, fans, and pumps | These non-IT loads can materially affect facility energy. |
For a new build, use design simulations and explicitly label them as forecasts. For an operating site, prefer revenue-grade utility and subsystem meters, with timestamps aligned to the IT energy meter.
Estimate electricity with IT energy and PUE
Step 1: Build the IT energy profile
- Divide the IT estate into meaningful groups, such as general-purpose servers, accelerated-computing racks, storage, and networking.
- For each group, obtain interval demand or a documented average demand and utilization schedule.
- Integrate demand over the reporting period to obtain annual IT energy in kWh or MWh. If using an average, write the assumption beside the result.
- Record peak IT demand separately. Do not substitute peak MW for annual average MW.
Step 2: Apply the PUE equation
Use the DOE definition:
PUE = total data-center facility energy ÷ IT equipment energy
Rearrange it for planning:
facility energy = IT energy × PUE
PUE is dimensionless. If annual IT energy is 525,600 MWh and the declared annual PUE is 1.30, facility energy is 683,280 MWh. The difference, 157,680 MWh, represents the non-IT loads inside the stated boundary. A ratio calculated from instantaneous readings can be useful for a snapshot only when the readings share the same boundary and operating condition; use annual energy on both sides for a reported annual PUE.
Step 3: Keep peak sizing separate
Electrical infrastructure is sized for coincident demand, not simply annual energy divided by 8,760. Include expected IT peaks, cooling response at design weather, UPS operating mode, battery charging, pump starts, and the chosen redundancy arrangement. A PUE applied to a peak snapshot is an approximation unless the PUE components were measured at that same condition. Label it as a design assumption rather than an annual performance result.
Step 4: Test growth and operating modes
Model commissioning, normal production, maintenance, partial occupancy, and future rack additions separately. Specialized graphics processors, server refresh cycles, idle power, and utilization can shift the load profile. A facility that has the same installed MW in two years may consume different annual energy if the workload or utilization changes.
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Estimate on-site water with site WUE
Use the site-WUE definition
DOE and Lawrence Berkeley National Laboratory distinguish site WUE from broader source-water accounting. Site WUE is:
site WUE = annual site water use (liters) ÷ IT equipment energy (kWh)
Therefore:
site water (liters) = IT energy (kWh) × site WUE (liters/kWh)
Use the water meter or cooling-water balance that matches the declared site boundary. State whether the value is withdrawal, consumption, or another accounting convention, and identify reclaimed or rainwater supplies. Convert only after multiplication: 1,000 liters equals 1 cubic meter, and 1 liter equals approximately 0.264172 U.S. gallons.
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At many facilities, site water is chiefly associated with cooling-tower evaporation, drift, and blowdown, but the exact balance depends on the design. Sanitary, irrigation, humidification, treatment, and other loads may be inside or outside the meter. A site-WUE figure does not automatically include water consumed at power plants to generate the facility’s electricity.
Add source water only when the question requires it
If the goal is a water footprint rather than on-site demand, add the water associated with electricity generation. LBNL calls this source WUE and requires a grid region plus a water-intensity factor for a specified year. There is no universal factor for an unnamed site: generation mix, cooling technology at power plants, dispatch, and accounting methods all matter. Report site water and source water as separate lines before presenting a combined total.
Worked example: transparent arithmetic, not a benchmark
The following numbers are illustrative planning assumptions for showing the method; they are not typical values or a performance claim. Assume a facility with 100 MW of IT nameplate capacity, 60% average IT utilization, 8,760 operating hours, annual PUE of 1.30, and site WUE of 0.50 liters per kWh.
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| Calculation | Result |
|---|---|
| Average IT demand | 100 MW × 60% = 60 MW |
| Annual IT energy | 60 MW × 8,760 h = 525,600 MWh (525.6 GWh) |
| Annual facility energy | 525,600 MWh × 1.30 = 683,280 MWh (683.28 GWh) |
| Annual site water | 525,600,000 kWh × 0.50 L/kWh = 262,800,000 L |
| Water conversion | 262,800 m³, or approximately 69.4 million U.S. gallons |
The example’s 100 MW is an IT nameplate, not a claim that the facility draws 100 MW continuously. Its peak facility demand still requires a separate electrical study. Likewise, the water result is site water under the stated WUE boundary; it is not a source-water footprint.
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Scenario ranges expose uncertainty in utilization, cooling, climate, and accounting. The table below keeps the same hypothetical 100 MW IT nameplate and 8,760-hour year while varying only planning assumptions. These are arithmetic cases, not industry benchmarks.
| Case | Average IT utilization | Annual PUE | Site WUE (L/kWh) | IT energy | Facility energy | Site water |
|---|---|---|---|---|---|---|
| Low-demand illustration | 40% | 1.20 | 0.20 | 350.4 GWh | 420.48 GWh | 70.08 million L (70,080 m³) |
| Base illustration | 60% | 1.30 | 0.50 | 525.6 GWh | 683.28 GWh | 262.8 million L (262,800 m³) |
| High-demand illustration | 80% | 1.50 | 1.20 | 700.8 GWh | 1,051.2 GWh | 840.96 million L (840,960 m³) |
For a real project, replace these illustrative inputs with measured or engineered values. Vary one factor at a time to show sensitivity, then run combined cases for hot weather, high utilization, maintenance operation, and water restrictions. Include confidence or uncertainty notes rather than rounding a wide range into a falsely exact total.
Why cooling design changes both electricity and water
Cooling towers and evaporative heat rejection
A cooling tower rejects heat partly through evaporation. Makeup water therefore depends on heat load, other facility loads, system efficiency, evaporation, drift, and blowdown. Increasing cycles of concentration from three to six can reduce cooling-tower makeup-water requirements by 20% and blowdown by 50%, according to DOE FEMP’s 2019 guidance and its cited cooling-tower best-management practices. Those percentages describe the cooling-tower operation in that example, not a guaranteed reduction in total facility water use.
Air-side economizing
When outdoor temperature and humidity are suitable, an air-side economizer can reduce mechanical-cooling hours. The benefit depends on climate, filtration, contamination limits, humidity controls, and the hours the mode is permitted. Model local weather rather than applying a universal savings percentage.
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Separating hot and cold aisles, sealing bypass openings, and controlling fan speed reduce recirculation and fan energy. These measures can improve both PUE and cooling capacity, but the result depends on rack density, containment quality, control tuning, and the operating set points.
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 cooling” does not by itself specify water use. DOE FEMP reports one National Laboratory of the Rockies example with PUE 1.06 and WUE 0.7; that is the result for that center and configuration, not an expected benchmark for every liquid-cooled facility. Pumps, controls, heat exchangers, treatment, and outdoor conditions still determine performance.
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Water treatment trade-offs
Reverse-osmosis treatment can reduce freshwater demand in some settings, while increasing electrical consumption and operations-and-maintenance requirements. Compare the resulting electricity, concentrate disposal, reliability, and treatment costs with the water benefit instead of labeling the option superior on water alone.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Compare design options on the same basis
When comparing cooling or electrical designs, hold the IT workload, output definition, reporting period, and facility boundary constant. Use a table like this for each option.
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|---|---|
| Electricity | What are annual facility MWh, seasonal demand, design peak MW, and UPS or distribution losses? |
| On-site water | What are withdrawal, consumption, blowdown, discharge, and reclaimed-water volumes? |
| Source water | What grid region and year-specific water-intensity factor were used? |
| Cooling and climate fit | How many economizer hours are available, and how does the system perform at design temperature and humidity? |
| Reliability and controls | What redundancy, maintenance mode, control logic, treatment, and failure response are required? |
| Uncertainty | Which inputs are measured, modeled, or assumed, and how wide is the resulting range? |
A design that uses less site water may require more electricity, while a lower PUE can carry higher water consumption. Make the trade-off visible in separate energy and water columns.
Put workload and grid effects in context
LBNL’s 2025 review, by Lei, Lu, Shehabi, and Masanet, reports more than 10,000-fold variation in workload-level water use. The review attributes the spread to server energy efficiency, workload efficiency, utilization, cooling type, infrastructure efficiency, climate zone, inactive-server share, server refresh cycle, and the water intensity of the electric grid. This does not mean one facility will span the entire range. It means a facility WUE alone cannot describe the water intensity of a particular workload. Keep the workload and output definition constant when making workload-level comparisons.
For national context, LBNL’s United States Data Center Energy Usage Report: 2025 Update, published in 2026, estimates 649 TWh of U.S. data-center electricity in 2030 in its reference case. Its compounded-uncertainty range is 521–843 TWh, and the report gives a 9.5%–15.3% share of U.S. electricity use, with an 11.8% reference estimate. These are bottom-up national scenarios based on equipment shipments, per-device annual energy, cooling simulations, facility types, locations, and assumptions about installations, specialized graphics chips, chip lifetimes, idle power, and utilization. They are not a per-facility average and should not be divided by an assumed number of “large” centers.
Use early-stage tools, then validate 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 identifying missing inputs, but it is not a substitute for subsystem measurement, a detailed cooling model, or a site engineering study.
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For an operating facility, request these records:
- Interval IT energy and total-facility energy for the same timestamps.
- A one-line electrical diagram showing utility, UPS, distribution, and meter locations.
- Cooling-plant power, pump and fan meters, tower makeup and blowdown meters, and treatment records.
- Weather data and control-mode logs for the reporting period.
- Definitions for withdrawal, consumption, discharge, reclaimed water, and any off-site source-water factor.
Reconcile meter totals monthly, investigate missing intervals, and document whether maintenance or tenant loads are included. For a proposed facility, preserve the model inputs and rerun the scenarios when rack density, cooling equipment, climate data, or utility assumptions change.
Common estimation mistakes and how to correct them
Calling nameplate MW annual consumption
Problem: multiplying installed IT MW by 8,760 without a utilization profile. Correction: model average and interval demand, then integrate to annual IT kWh.
Mixing boundaries
Problem: using a campus utility bill with a data-hall IT denominator, or adding office water to a cooling-only WUE. Correction: draw the boundary on a diagram and place every meter inside or outside it.
Applying a PUE from another site
Problem: transferring a published ratio to a different climate, cooling design, or operating condition. Correction: use a measured site ratio or a range tied to the proposed equipment and weather.
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Reporting water without its accounting definition
Problem: presenting liters as if withdrawal, consumption, and source water were the same. Correction: report each category separately and identify the conversion and time period.
Ignoring peak conditions
Problem: sizing transformers or cooling equipment from annual average demand. Correction: run a coincident peak study that includes IT bursts, design weather, redundancy, battery charging, and maintenance modes.
Treating a water-saving measure as free
Problem: claiming a total benefit without counting treatment energy, pumps, controls, concentrate, or reliability requirements. Correction: place the measure in the same electricity-and-water comparison table as the alternative.
Quick Recap
A handoff checklist for a defensible estimate
- State the IT nameplate, expected utilization, workload profile, and peak demand.
- Calculate annual IT energy in kWh or MWh for a named reporting period.
- Draw the facility boundary and list every included non-IT load.
- Choose a PUE basis that matches the boundary and operating condition.
- Document cooling technology, controls, climate data, and water-treatment mode.
- Calculate site water with site WUE and show liters before converting to cubic meters or gallons.
- Add source water only with a named grid region, factor, and year.
- Publish low, base, and high cases, identifying measured values versus assumptions.
- Separate annual energy and water from peak electrical and cooling capacity.
- Recheck the estimate when utilization, rack density, equipment generation, weather, or utility conditions change.
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