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Estimate a data center campus in phases: convert each phase’s nominal IT capacity into a potential total-facility load using an explicitly stated PUE, then model when capacity becomes operational and how heavily it is used. Report realized peak demand in MW separately from annual electricity use in MWh or TWh. An announced capacity figure alone is not a reliable estimate of either.
Start by identifying which “demand” you need
Data center electricity estimates mix several quantities that answer different questions. Label each figure before calculating or comparing it.
- Nominal IT capacity (MW): the potential power draw of servers and other IT equipment, excluding cooling and other facility infrastructure.
- Facility nameplate capacity (MW): potential total load, including IT equipment and supporting systems such as cooling, power conversion, and lighting. A utility service request may be expressed on this total-facility basis, but confirm the basis with the project and utility.
- Active or operational capacity (MW): the portion of installed potential actually brought into service as buildings, data halls, equipment, and tenants come online.
- Realized peak demand (MW): the actual high power demand after accounting for active capacity and how the site operates.
- Annual electricity use (MWh or TWh): energy consumed over a period. It accumulates across operating hours and is not a power rating.
MW measures power at a moment; MWh measures energy over time. Do not compare one campus’s IT MW with another’s facility MW, or compare MW directly with annual MWh. EPRI distinguishes capacity from annual energy and explains the role of facility overhead and PUE in its data center electricity-demand analysis.
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Build the estimate phase by phase
Use a separate row or calculation for each building or development phase, rather than treating an announced campus total as if every hall were already operating.
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- Set nominal IT capacity. Record the planned IT load in MW for each phase. If an announcement provides only total facility capacity, do not relabel it as IT capacity; seek clarification or keep the basis explicitly unresolved.
- Convert to a potential facility load. Apply a stated PUE assumption to the IT load. PUE is the ratio of total facility load to IT load, so the calculation is potential total-facility load = IT load × PUE. For example, a hypothetical 100 MW IT phase at an assumed PUE of 1.4 implies 140 MW of potential total-facility load. This is an illustration, not a prediction for a particular campus.
- Model schedule and ramp-up. For each forecast year or scenario, estimate what share of each phase is commissioned and active. Account for buildings, data halls, equipment, and tenants coming online at different times; announced capacity may not become operational immediately.
- Apply utilization or a load shape. Estimate how intensively active IT capacity is used and how the facility’s load varies. This is needed to move from potential capacity toward expected operating demand; do not treat nameplate capacity as the expected peak.
- Calculate peak and energy separately. Estimate the realized peak from active capacity and operating behavior. Estimate annual energy from the load over the hours in the year. A simplified constant-load calculation is average MW × hours in the period = MWh, but a varying load requires a load profile or an explicit average-load assumption.
- Aggregate phases. Add phase-level results for the same forecast year and scenario. Keep requested service capacity, potential nameplate, expected realized peak, and annual energy in separate columns.
For a campus with varying loads, annual energy is the area under its load-over-time profile, not simply its maximum MW multiplied by every hour in the year. The simplified calculation is useful only when the average load is represented appropriately.
Choose PUE and operating assumptions for the site
PUE converts IT load to a total-facility basis, but it is not a universal constant. EPRI notes that it can vary with cooling technology, climate, architecture, scale, chip design, and computational use case. State the source and rationale for a project’s PUE assumption; if the design value is unknown, show a range of scenarios instead of presenting one unsupported value.
At minimum, document the following inputs for each phase and forecast year:
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- Nominal IT capacity and whether the figure is planned, installed, or active.
- PUE or another clearly described facility-overhead assumption.
- Construction, commissioning, and tenant ramp-up dates or shares.
- Utilization or load-shape assumptions used to estimate peak and annual energy.
- The forecast horizon and whether values are low, central, or high scenarios.
- Whether each reported figure is a service request, potential nameplate, expected peak, or annual energy.
EPRI’s Powering Intelligence 2026 analysis describes mapping announced nominal IT capacity to annual electricity use and peak demand using PUE, ramp-up, and utilization assumptions, and recommends updating projections as project information changes.
Keep a capacity-to-energy model transparent
A useful planning table makes assumptions visible instead of hiding them in a single campus total. Use one row per phase and forecast year, then include an aggregate row for each scenario.
| Phase and forecast year | Nominal IT capacity (MW) | PUE assumption | Potential facility load (MW) | Active share and utilization basis | Estimated realized peak (MW) | Estimated annual energy (MWh or TWh) |
|---|---|---|---|---|---|---|
| Enter project phase and year | Enter sourced or planned IT capacity | Enter stated value or scenario | IT MW × PUE | Enter ramp-up and operating assumptions | Calculate using the stated load model | Calculate from the annual load profile or stated average load |
The table’s potential facility load is not automatically the expected peak: a phase may be only partly active, and actual load depends on operating behavior. The estimate should identify the assumptions behind those later steps rather than implying that one formula can determine them.
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Validate the estimate with site and utility information
A campus-specific forecast needs project inputs not supplied by a generic capacity announcement: location, IT MW by phase, design PUE, commissioning and tenant schedule, expected utilization or load shape, and the serving utility’s interconnection conditions. Without those, an exact peak, annual MWh, or service requirement cannot be established.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesFor an existing facility, measurements can help validate component and whole-site inputs. The U.S. Department of Energy’s data-center metrics and measurement recommendations define peak total electric demand at the data center boundary, such as the point of electric feed or utility meters for a dedicated facility, and describe metering for IT and supporting equipment. A handheld meter can help gather measurements; it cannot forecast a future campus’s phasing, workload, or utility requirement.
Use national figures only as context
National estimates illustrate why data center growth matters to grid planning, but they are not campus planning factors. The U.S. Department of Energy reports an EPRI estimate that data centers used 4% of U.S. electricity generation in 2023, with a projection of up to 9% by 2030 (DOE report). Separately, DOE’s resource hub summarizes Lawrence Berkeley National Laboratory estimates of about 4.4% of total U.S. electricity in 2023 and approximately 6.7% to 12% in 2028 (DOE resource hub). These estimates have different authors and forecast years, so they should not be merged into a single range.
EPRI describes 100 to 1,000 MW as a range for a typical new data center in its discussion of local impacts; that is contextual, not a recommended estimate for an unspecified campus. Its introduction also notes that data center electricity demand is not publicly reported and that utilities are receiving sharp increases in service-connection requests (EPRI introduction). The figures and project pipeline can change, so forecasts should state their date and be updated as design, schedule, and operating information becomes available.
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