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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchStart with the IT equipment and its operating profile, then apply a stated PUE for total electricity and a stated site WUE (or a cooling-system model) for on-site water. Keep electricity-related water at power plants separate from water used at the facility, and publish low, central and high cases instead of one universal “watts per GPU” or “water per query” number. Hardware efficiency, utilization, climate, cooling design and the electricity supply can change the result by orders of magnitude.
What the estimate must contain
A defensible plan reports four distinct quantities:
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- IT electricity: energy used by servers, accelerators, memory, storage and networking.
- Total facility electricity: IT electricity plus cooling, power conversion, pumps, fans, lighting and other building loads.
- Direct (site) water: water consumed at the data-center site, chiefly for cooling.
- Indirect (source) water: water consumed while generating the electricity supplied to the facility.
Annual energy is measured in kilowatt-hours (kWh) or megawatt-hours (MWh). Instantaneous or coincident demand is measured in kilowatts (kW) or megawatts (MW). A utility interconnection, transformer and backup-generator plan must be sized for demand; an annual resource plan uses energy. Do not substitute one for the other.
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Step 1: Build an IT load and operating profile
List every major electrical load before applying any facility multiplier. A useful inventory includes:
- Accelerator and server model, quantity and rated power.
- CPU, memory, local storage and external storage systems.
- Network switches, optical equipment and fabric links.
- Expected average utilization, idle draw and power-management limits.
- Hours operating each day, days per year and expected training or inference duty cycle.
- Installation schedule, refresh cycle and equipment lifetime.
Use measured or vendor-qualified average draw for the workload, not only a nameplate maximum. Nameplate capacity is still important for breakers, UPS systems and cooling capacity, but it is not an annual-energy forecast. Calculate average load and peak coincident load separately: ten racks that each can draw 100 kW do not necessarily draw 1 MW at the same instant, while a synchronized training run might approach that value.
Calculate annual IT energy by device class
For each class, use:
annual IT energy (kWh) = average device power (kW) × quantity × operating hours per year
If utilization changes the draw, model active and idle periods explicitly:
annual IT energy = quantity × [active power × active hours + idle power × idle hours]
Apply the same method to storage and networking. A fleet forecast should also include when equipment ships and is commissioned; a rack that arrives halfway through the year cannot contribute a full year of energy. For a multi-year plan, model performance degradation, refresh timing and any change in workload mix.
Record peak and average demand
For each operating state—normal inference, large training jobs, maintenance and startup—record average kW and the highest coincident kW. Add a design margin required by the electrical engineer, but label it as capacity rather than expected consumption. The result should show both the annual kWh/MWh and the maximum MW that the site and utility connection must support.
Step 2: Convert IT energy to total facility electricity with PUE
Power Usage Effectiveness (PUE) is:
PUE = total facility energy ÷ IT equipment energy
Therefore:
annual facility electricity (kWh) = annual IT electricity (kWh) × PUE
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A PUE of 1.0 is the theoretical minimum: every unit of facility energy reaches IT equipment. Real sites are higher because of chillers or dry coolers, pumps, fans, UPS and power-conversion losses, lighting and other services. Use the PUE expected for the actual building, climate and operating load. A national or industry reference value is not a substitute for the design’s own model.
What belongs in the PUE assumption
- Cooling equipment and heat-rejection energy.
- UPS, transformers, switchgear and distribution losses.
- Pumps, fans and controls.
- Lighting and building services included in the facility boundary.
State whether your PUE is a design target, a measured operating value or a conservative planning assumption. PUE can vary with season and utilization, so a single annual figure should be an explicitly documented weighted average or a range.
Step 3: Estimate direct, on-site water
Site Water Usage Effectiveness (site WUE) normalizes water consumed at the facility by IT energy:
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site WUE (L/kWh) = annual site water use (L) ÷ annual IT energy (kWh)
The first-pass estimate is:
annual site water (L) = annual IT energy (kWh) × site WUE (L/kWh)
Site WUE normally captures cooling-tower evaporation, blowdown and other facility water within the stated boundary. Identify whether the metric includes water treatment, humidification, sanitation or only cooling makeup; otherwise two apparently similar WUE values may describe different boundaries.
Replace a generic WUE with a cooling model when possible
Once the cooling design is known, model heat load and heat rejection directly. The model should include:
- IT heat that must be rejected at each operating load.
- Air cooling, direct liquid cooling, chilled-water loops or a hybrid arrangement.
- Chiller, cooling-tower, dry-cooler or adiabatic efficiency.
- Outdoor temperature and humidity by hour or representative weather bin.
- Cooling-tower cycles of concentration, evaporation and blowdown.
- Economizer availability, maintenance modes and water-treatment practice.
DOE FEMP notes that cooling-tower consumption follows the heat load and the efficiency of heat removal. Evaporative systems consume water as it changes phase, while blowdown removes concentrated minerals and creates additional makeup-water demand. Temperature and humidity control, airflow management and economizing affect both energy and water.
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Step 4: Estimate electricity-related (source) water separately
Power plants and grid systems also consume water. Estimate this indirect component as:
source water (L) = electricity purchased or generated (kWh) × location- and technology-specific water-consumption factor (L/kWh)
The factor depends on the generation mix, cooling technology, weather and geography. Use the utility or balancing-area region that will serve the facility, and account for onsite generation or a behind-the-meter supply. Report the result separately from site water:
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- Source water: consumed to produce its electricity.
- Source-inclusive total: the sum, clearly labeled as a broader lifecycle boundary.
The Lawrence Berkeley National Laboratory’s 2024 U.S. analysis distinguishes site WUE from source WUE and uses balancing-authority and power-plant data. Its indirect estimates do not incorporate an individual power-purchase agreement or behind-the-meter generation automatically, so a project model must represent those arrangements explicitly.
How to build low, central and high cases
Publish a range rather than false precision. At minimum, vary the assumptions that commonly dominate the result:
| Variable | Low case | Central case | High case |
|---|---|---|---|
| IT utilization | Lower sustained workload, with idle periods represented | Expected annual workload mix | High sustained training or inference load |
| IT power | Efficient devices and measured average draw | Planning average | Higher draw or conservative power limit |
| PUE | Efficient design at favorable load and weather | Expected annual weighted value | Less favorable load, season or commissioning operation |
| Site WUE | Dry or highly efficient water strategy | Design estimate | Evaporative operation, blowdown or hot-weather stress |
| Source-water factor | Lower-water generation mix | Expected grid factor | Higher-water generation mix or stressed season |
Show which variables drive the spread. LBNL’s June 2026 U.S. report uses sensitivity and compounded-uncertainty scenarios for this reason: shipment timing, per-device annual electricity, cooling performance, facility type and location interact rather than adding one fixed error bar.
Worked example (illustrative arithmetic, not a facility forecast)
Consider a hypothetical first-year deployment with 2,000 accelerators. Assume each averages 0.7 kW while active, operates 6,000 hours per year, and has an additional 0.1 kW of idle-equivalent draw for the remaining 2,760 hours. Assume 100 kW of average storage and networking load for 8,760 hours. These are planning assumptions chosen to demonstrate the method, not measured values for a real site.
- Accelerator energy:
2,000 × [(0.7 × 6,000) + (0.1 × 2,760)] = 8,952,000 kWh. - Storage and network energy:
100 × 8,760 = 876,000 kWh. - Annual IT energy:
8,952,000 + 876,000 = 9,828,000 kWh(9,828 MWh). - Facility electricity: with an explicitly assumed PUE of 1.25,
9,828,000 × 1.25 = 12,285,000 kWh(12,285 MWh). - Direct site water: with an assumed site WUE of 0.20 L/kWh,
9,828,000 × 0.20 = 1,965,600 L. - Indirect source water: if the serving grid’s documented factor were 0.50 L/kWh,
12,285,000 × 0.50 = 6,142,500 L. This is reported separately because it occurs in electricity generation, not at the data center.
If the same IT fleet used a different cooling design or operated in a different climate, the PUE and site-WUE assumptions would change. If the grid factor changed, source water would change even when the building and workload did not.
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How cooling choices change the result
Cooling is a coupled power-and-water decision. LBNL’s 2024 report modeled nine common cooling configurations with thermodynamic simulations across facility types and U.S. weather stations, illustrating why a generic WUE is a weak substitute for a site model.
Air-cooled chillers and dry systems
Air-cooled chillers and dry coolers can reduce routine on-site water demand because they reject heat to air rather than evaporating large quantities of water. Their electricity use, performance in hot weather and available capacity must be modeled; reducing site water can increase power demand under some conditions.
Water-cooled chillers and cooling towers
Water-cooled equipment can serve substantial heat loads efficiently, but cooling-tower evaporation and blowdown create a continuing makeup-water requirement. Cycles of concentration, water chemistry, drought restrictions and tower operating temperature materially affect consumption.
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Liquid loops can move heat efficiently from high-density accelerators and may be paired with dry coolers, chillers or towers. The liquid loop itself is not proof of low site water: the final heat-rejection stage determines much of the facility’s water use. Hybrid designs can switch modes as weather, workload and water availability change.
Economizers and weather
Air- or water-side economizers can use favorable outdoor conditions to reduce mechanical cooling. Their benefit depends on local temperature, humidity, filtration limits and control settings. Use hourly or representative weather data for the proposed location rather than assuming that a cool-climate design performs identically elsewhere.
Inputs and checks before publishing a number
Gather the following and attach a unit, date and boundary to every value:
- Accelerator, server, storage and network inventory.
- Average, idle and peak device power; utilization and operating hours.
- Deployment schedule, refresh plan and expected lifetime.
- Peak coincident IT load and electrical capacity margin.
- Design or measured PUE, including its facility boundary.
- Cooling type, set points, heat-rejection efficiency, evaporation and blowdown assumptions.
- Location, weather data and seasonal operating restrictions.
- Utility or balancing-area region, generation mix, onsite generation and any contracted supply.
- Site-WUE and source-water-factor definitions, units and reporting periods.
Check dimensional consistency: multiplying kW by hours yields kWh; multiplying kWh by L/kWh yields liters. Convert MWh to kWh before applying an L/kWh factor. Keep liters, cubic meters and gallons labeled and do not mix annual totals with hourly rates.
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Common mistakes and how to correct them
Using accelerator nameplate watts as annual consumption
Problem: Nameplate maximum ignores utilization, idle draw and operating hours. Correction: use active and idle states, then model peak separately for infrastructure sizing.
Applying PUE to peak MW instead of annual energy
Problem: PUE is an energy ratio, and a peak-load calculation can misrepresent annual consumption. Correction: multiply annual IT kWh by PUE for annual facility kWh; estimate peak facility kW with a coincident-load model.
Calling all water “WUE”
Problem: site water and electricity-generation water have different locations and drivers. Correction: report site WUE and source water separately, then label any combined figure as source-inclusive.
Using a national average for a site decision
Problem: climate, cooling design, utility region and operating practice can overwhelm a national average. Correction: use local weather, equipment and grid inputs, with low, central and high cases.
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Ignoring commissioning and partial-year operation
Problem: a fleet that ramps over several months cannot consume a full year’s energy in its first year. Correction: model shipment, installation and utilization by month or quarter.
Useful benchmarks, with their limits
LBNL’s 2026 national projection estimates 649 TWh of U.S. data-center electricity in 2030 in its reference case, with a compounded-uncertainty range of 521–843 TWh. The same reference estimate is 11.8% of total U.S. electricity in 2030, with a scenario range of 9.5%–15.3%. These figures cover U.S. data centers nationally, not AI alone and not a particular facility; they provide context, not a substitute for project engineering.
The more-than-10,000-fold workload-level water variation reported by Lei, Lu, Shehabi and Masanet in 2025 likewise should not be turned into a per-query promise. It reflects differences in water consumption per kWh and workload efficiency across the studies reviewed.
Scoping tools and engineering validation
LBNL provides the PUE Estimator for an early PUE estimate and DC Pro for a broader profile and recommendations. Use them to identify major loads and opportunities during concept design, not as a replacement for a detailed electrical study, cooling simulation, utility review or site-specific water model.
As design advances, reconcile the estimate with vendor submittals, rack-level telemetry, utility interval data, cooling-plant measurements and water meters. Recalculate the range when the accelerator mix, utilization target, cooling topology, location or electricity contract changes.
A reporting format readers and decision-makers can audit
Publish a short assumptions register beside every result:
- IT equipment, quantity, average and peak power.
- Utilization, idle periods, operating hours and deployment schedule.
- Annual IT kWh and peak IT kW.
- PUE definition, value and operating condition.
- Annual facility kWh and peak facility MW.
- Cooling design and site-WUE boundary.
- Annual site liters, source-water factor and annual source liters.
- Low, central and high values, with the assumptions that create each case.
- Geography, weather period, grid region and calculation date.
This format lets a reviewer replace one assumption—such as a new accelerator, a different cooling tower or a changed utility mix—without rebuilding the entire estimate or confusing direct water with upstream water.
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