AEO data center server energy use
AEO projects electricity consumed by data-center servers across the commercial building stock, with greater growth in standalone data centers than in data-center rooms combined. Standalone data centers account for the larger increase, but server rooms inside other building types also remain part of the load.
Server electricity is only one end use because space cooling and ventilation support server operation. Chips and related equipment require cooling and ventilation, and those supporting end uses raise commercial electricity intensity along with the direct operational power draw of the installed server stock.
Cooling compounds the curve
Cooling electricity changes with both server activity and the conditions around the building. The EIA models data-center floorspace as substantially more cooling-intensive than ordinary commercial floorspace, while population movement and weather affect the service demand needed to maintain operating conditions.
A campus forecast that copies server power into a flat facilities load will miss this interaction. The AEO assumes a flat server end-use load shape, while space cooling electricity remains sensitive to data-center floorspace, population migration, and weather.
Efficiency cannot carry the whole case
The Counterfactual Baseline assumes additional server efficiency after the later years of the outlook, but continued installations still push total consumption upward. The High Electricity Demand case removes that extra efficiency assumption and gives AI servers a larger share of the installed stock, widening the range of possible electricity use.
Server efficiency assumptions do not stop overall consumption growth when server installations continue to increase. Better server performance can reduce average operational power for a unit of computing, but growth in server stock, higher-intensity equipment, and the cooling needed around that stock can still increase total facility demand.
Two cases frame server consumption
The Counterfactual Baseline and High Electricity Demand cases vary server efficiency, installed stock, and the share of AI servers. The server model covers installed stock and average power draw; the facilities model covers cooling, ventilation, electricity intensity, building type, and the hours in which the site must sustain the combined load.
Utilities need the same separation when they evaluate commercial demand. Standalone data centers in the other-buildings category account for more growth than data-center rooms across other commercial building types.
Translate the cases into building load
The range between the Counterfactual Baseline and High Electricity Demand cases reflects server power draw, installed stock, cooling, and ventilation. A project team can map installed server stock to operational power, then add cooling and ventilation loads that reflect the building type and local conditions described in the AEO model.
Commercial electricity use combines server consumption with supporting space cooling and ventilation. When server installations rise, cooling service demand rises with them; when server efficiency improves, the facilities model should still account for the energy needed to move heat and maintain operating conditions. Reporting those end uses separately keeps server and cooling assumptions visible.
The same structure helps utilities compare projects. Standalone data centers and server rooms in other commercial buildings occupy different building categories but both add server and cooling electricity. Those building categories create different electricity consumption and cooling profiles across the commercial building stock.
AEO cases
The cases differ on server efficiency.
Counterfactual Baseline assumes server efficiency improvement, while High Electricity Demand assumes more AI servers and no additional efficiency improvement. The range does not prove one final level of electricity use. The AEO cutoff excludes later legislation, regulations, executive actions, and court rulings.
The decision value lies in the spread between the cases. Capacity teams can test whether a project remains viable when efficiency improves slowly, server installations grow faster, and cooling electricity rises with more intensive operations instead of treating one baseline as a firm outcome.
Bottom Line
The facilities forecast needs two ledgers.
The AEO cutoff is a limitation because it excludes later legislation, regulations, executive actions, and court rulings. Data center servers require space cooling and ventilation so chips and related IT equipment can operate efficiently. Plans that track only server draw will understate the grid connection, cooling plant, and operating margin needed when the installed stock grows faster than efficiency can reduce total demand.
