Start at the boundary
A GPU power rating is not a facility electricity bill. CPUs, memory, storage, network devices and cooling also consume energy. A planning estimate needs an average operating draw, a period and a boundary for shared equipment. Power usage effectiveness relates facility energy to IT energy over a consistent scope and period.
Do not multiply uncertainty into certainty
Our Capacity & Energy model adds user-entered average GPU power and allocated host power, multiplies by scheduled GPU-hours and then by PUE. The result is a simple facility allocation. It excludes embodied emissions, construction, peak electrical design and off-schedule idle consumption. It does not establish grid access or a connection date.
Industry context is different from project sizing
The IEA’s 2026 report examines fast-growing data-center electricity use and infrastructure constraints. Its estimates are global research context. A specific deployment still needs local utility evidence, capacity reservation, cooling design and a credible delivery sequence. A global demand chart cannot provide those answers.
Use the result to ask a better question
Keep average draw separate from peak provisioning. Request the site’s operating envelope and measurement method, then test an hour, a representative day and a longer period. Avoid counting electricity twice in a cloud quotation that already includes it. Our Deployment Compare tool displays the owned-energy component separately from a supplied cloud rate.