Estimate a data center’s electricity cost by first measuring energy at the right boundary, then applying the facility’s actual utility tariff. For each interval, multiply average demand in kilowatts (kW) by interval length in hours to get kilowatt-hours (kWh); add the intervals for the period. If you know only IT energy, use a matching-period power usage effectiveness (PUE) to estimate whole-facility energy. A kWh-only calculation is a useful starting point, but it may miss demand and other charges on the bill.
Define what you are estimating
Decide whether the answer should represent IT equipment alone or the whole facility, and choose a time period such as a month or year. These are different measurement boundaries: a facility total can include IT equipment, cooling, power conversion and distribution losses, fans, lighting, and other building loads. A meter or bill is useful only if its boundary matches the quantity you want to estimate.
Also distinguish energy from demand. Energy is measured in kWh over time; demand is a power level measured in kW at a point or over a billing interval. A utility may charge for both.
Calculate electricity use from meter or demand data
When interval energy readings are available
Sum the meter’s kWh readings for the period you are estimating. Confirm that the readings cover the full period and that the meter measures the intended boundary.
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When interval-average demand is available
For each interval, calculate energy as average kW × interval hours, then add the interval results. For example, an average demand of 500 kW sustained for a 15-minute interval represents 125 kWh (500 × 0.25). Sum all intervals in the selected period to estimate its energy use.
When only an average demand is known
Multiply representative average kW by the operating hours in the period. Label this as an estimate and state the assumed hours and load. Do not multiply peak or nameplate power by every hour unless the facility actually operates continuously at that level.
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Estimate whole-facility energy from IT energy using PUE
Power usage effectiveness (PUE) is total annual facility energy use divided by annual IT equipment energy use. If you have IT energy but not a whole-facility reading, estimate facility energy as IT energy × PUE. For example, 1,000,000 kWh of IT energy paired with a compatible PUE of 1.5 implies 1,500,000 kWh of facility energy. The PUE must represent a compatible facility boundary and time period; a mismatched figure can mislead.
Do not apply PUE to a meter reading that already covers the whole facility. PUE values are not universal guarantees. A U.S. Department of Energy case study of three federal data centers, based on measured energy-use observations from summer 2012, reported current PUEs of 1.80, 2.07, and 1.78, with modeled potential values of 1.45, 1.55, and 1.38, respectively. Those results illustrate variation across sites and the difference between observed and modeled values; they are not current benchmarks for another facility. DOE federal data center case study.
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Convert energy use into an operating-cost estimate
Use a flat energy rate for a rough estimate
For an energy-only estimate, multiply period kWh by the energy price per kWh. A U.S. Department of Energy example uses 11¢/kWh, the average electricity price at U.S. federal facilities as of July 2024. That is a dated federal-facility example, not a current commercial rate or a rate for every location. DOE federal data center storage purchasing guidance.
Use the tariff for a bill estimate
A more complete estimate should follow the facility’s applicable utility tariff. Depending on the rate design, the bill may include billed peak demand, time-of-use energy prices, fixed monthly charges, and other adjustments in addition to energy charges. Large-load rate structures can differ materially, so a generic cents-per-kWh assumption should be labeled as a rough approximation rather than a predicted bill. DOE technical brief on large-load electricity rate designs.
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For a tariff with time-of-use periods, allocate kWh to the relevant periods and apply each period’s rate. For demand charges, use the billed peak kW and the tariff’s billing rules, rather than multiplying total kWh by an energy rate. Add fixed and other applicable charges to complete the estimate.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Make uncertainty visible
When inputs are incomplete, give a low, base, and high estimate rather than presenting one unsupported precise figure. Vary uncertain inputs such as average load or utilization, operating hours, inferred PUE, and tariff assumptions. Keep measured readings and billed amounts distinct from assumptions and modeled estimates, and state the period and boundary for each figure.
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- Measured: meter or interval readings, with meter boundary and dates.
- Billed: utility charges and the tariff period they cover.
- Assumed: operating hours, average load, or rate used where direct data is missing.
- Modeled: estimates derived from PUE, projections, or scenarios.
Use national statistics as context, not a site estimate
Lawrence Berkeley National Laboratory estimated that U.S. data centers used 176 TWh in 2023, about 4.4% of total U.S. electricity that year. Its 2024 report projected U.S. data-center electricity use of 325–580 TWh in 2028; that is a modeled range, not an observed result. DOE announcement of the 2024 LBNL report.
A 2025 LBNL update reported a 14% increase in U.S. data-center electricity use from 2023 to 2024. Its sensitivity scenarios span -11% to +21% relative to the reference case, while the report describes compounded uncertainty as roughly -20% to +30%. These are national estimates and scenario ranges, not a way to infer an individual facility’s consumption or bill. DOE announcement of the 2025 LBNL update.
Compare estimates on equal terms
Before comparing facilities or competing estimates, align the factors that can change the result:
- Boundary: IT-only or whole facility.
- Time basis: same month or year; do not confuse total energy with peak demand.
- Tariff: energy-only rate or full bill including demand and time-of-use charges.
- Operating conditions: utilization, season, cooling conditions, and hours represented.
- Evidence: meter readings and bills versus nameplate assumptions, extrapolations, or national models.
- PUE fit: compatible period and facility boundary for both PUE and IT energy.
The DOE’s Berkeley Lab Power Chain Tool can help explore potential energy and cost savings from electrical-system efficiency changes using inputs such as UPS, PDU, and transformer information. It is an analysis aid, not a substitute for site meter readings or utility bills. Better Buildings description of the Power Chain Tool.
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