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  "description": "Distinguishes estimated electricity use from conditional demand projections.",
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      "title": "Explore in Atlas",
      "url": "https://semiaifoundry.com/ai-atlas/#energy-forecast-boundaries"
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      "title": "Key Questions on Energy and AI: Executive Summary",
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    {
      "title": "United States Data Center Energy Usage Report: 2025 Update",
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  "content": "Global AI infrastructure · Atlas v1.3.0\n\n# Energy forecasts, geography and measurement boundaries\n\nDistinguishes estimated electricity use from conditional demand projections.\n\n[Explore in Atlas](https://semiaifoundry.com/ai-atlas/#energy-forecast-boundaries)Facility phases to region and world; geography schematic\n\nLearning objectiveRead a dated demand forecast without confusing geography, AI scope or power and energy.\n\n## The mechanism\n\nElectricity demand reports combine observations, estimates and scenarios. A global all-data-center forecast includes many uses beyond AI, while an AI-focused subset requires its own definition. The IEA’s April 2026 update and LBNL’s June 2026 US report differ in geography, publication timing and methodology. Their totals cannot be added or treated as competing measurements of the same scope. Historical forecast revisions are useful evidence about changing assumptions, but an older projection should not silently replace a newer one. Power is an instantaneous rate; annual energy integrates changing load, including non-IT overhead when the report’s boundary includes it.\n\n1.  Identify the report date, geography and whether AI is the whole scope or a subset.\n2.  Separate estimated historical demand from projected future demand.\n3.  Check whether the measure includes cooling and other facility loads.\n4.  Compare revisions only after aligning definitions and explaining changed assumptions.\n5.  Keep local deliverability and useful workload capacity separate from broad annual electricity totals.\n\n## Science and assumptions\n\n### Energy from average power\n\n$$\nE=P_{\\mathrm{avg}}\\Delta t\n$$\n\nEnergy is average power times the duration over which that average applies.\n\nGW times hours gives GWh; divide GWh by 1000 for TWh. Installed peak power is not an interval-average load.\n\nSymbols and units\n\nE\n\nEnergy over the averaging interval\n\nGWh\n\nP\\_avg\n\nAverage real power over that same interval and boundary\n\nGW\n\nΔt\n\nInterval duration\n\nh\n\nPavg in GW and Δt in hours gives GWh; divide by 1,000 for TWh.\n\nAssumptions Average must cover the same interval and boundary; installed or contracted peak power is not Pavg.\n\n## Engineering example\n\nSynthetic constant 1 GW load over 8,760 hours uses 8.76 TWh. A 1 GW nameplate facility does not necessarily use that energy because its average operating load can be lower.\n\n## Distinctions and tradeoffs\n\nA global data-center forecast is not an AI-only measurement, and a 2030 scenario is not observed consumption.\n\nBroader forecasts help planning but hide local grid and workload constraints; granular estimates need more uncertain input data.\n\nAI buildout affects electricity systems, but no annual energy total provides a universal conversion into model throughput or capability.\n\n## Specifications and interfaces\n\nUnits\n\nMW power and MWh/TWh energy\n\n1 TWh equals one million MWh; time is essential.\n\nStatus\n\nEstimated baseline versus forecast scenario\n\nBoth need source date, observation year and scope.\n\n### Interfaces\n\nMetering, shipment and scenario inputs Input\n\nDefined geography, device mix and operating assumptions\n\nDemand estimate or forecast Output\n\nScoped energy with period and uncertainty\n\n## Check your understanding\n\n### Why can a US report not be added to a global total?\n\n1.  US electricity uses different physical units\n2.  Forecasts can never discuss regions\n3.  The global scope already includes the United States\n\nAnswer and reasoning\n\nThe global scope already includes the United States\n\nThe geographies overlap, so adding them double-counts the US contribution.\n\n## Evidence and scope\n\nIEA baseline and projection are separate claim records. LBNL’s laboratory abstract was retrieved; inaccessible full-report methodology is not represented as independently rechecked.\n\nNo current calculator directly models this lesson’s main mechanism. Use the library for related bounds while retaining their stated omissions.\n\n## Sources\n\n-   [Key Questions on Energy and AI: Executive Summary](https://www.iea.org/reports/key-questions-on-energy-and-ai/executive-summary)\n-   [United States Data Center Energy Usage Report: 2025 Update](https://bies.lbl.gov/publications/united-states-data-center-energy-2025)\n\n[Published lesson data](https://semiaifoundry.com/ai-atlas/lesson-data/energy-forecast-boundaries-a7a1ef8a72b5c20c.json) · [Atlas releases and licensing](https://semiaifoundry.com/ai-atlas/licenses.html)\n\n## Continue exploring\n\n### Foundations\n\n-   [Dynamic load, reserve and power control](https://semiaifoundry.com/learn/atlas/rack-dynamic-power/)\n\n### Related lessons\n\n-   [Water withdrawal, consumption and cooling circulation](https://semiaifoundry.com/learn/atlas/water-boundary-accounting/)\n-   [Grid interconnection and deliverable electrical capacity](https://semiaifoundry.com/learn/atlas/grid-interconnection-readiness/)"
}