# Expected Power Capacity Demand Projection

The rapid expansion of data centers across the United States is driving a surge in electricity demand to power advanced computing, including AI, cloud services, and enterprise workloads. To better anticipate this trend, we use an **expected power capacity methodology**.

This methodology goes beyond simply recording announced or active capacities. It provides a **scenario-based perspective** on how much power is likely to come online over time, offering a more realistic view of future demand.

Since not every announced project will proceed as planned, we incorporate **project likelihood ratings**. Facilities are grouped into three levels:

* **"High" likelihood** – Projects are highly likely to progress to buildout and operation due to firm land control with permitting and zoning nearly complete, secured or committed power infrastructure, strong financial backing, experienced developers or anchor tenants.
* **"Medium" likelihood** –Projects have a medium likelihood of progressing to buildout and operation due to lacking land ownership, unconfirmed power infrastructure, early-stage permitting, new or less experienced developers, community concerns, and limited existing data center presence.
* **"Low" likelihood** – Projects have a low likelihood of progressing to buildout and operation due to incomplete or disputed land control, stalled or denied permitting, unavailable or uncertain power infrastructure, little to no published financial backing, strong regulatory or community opposition, and developers with little or no track record.

### The Three Scenarios

1. **Optimistic Case**

* Assumption: Every data center project comes online as planned.
* Purpose: Represents the maximum possible capacity if the industry expands without major obstacles.
* Use Case: Useful for high-growth planning and understanding the upper bound of demand.<br>

2. **Baseline Case**

* Assumption: Each project is weighted by its likelihood of execution. For example, projects considered “high probability” contribute fully to the estimate, while those with “medium” or “low” probability are discounted.
* Purpose: Provides a more realistic picture of expected growth by balancing ambition with execution risk.
* Use Case: Serves as the primary projection for investors, policymakers, and planners.<br>

3. **Conservative Case**

* Assumption: Only projects with a “high” likelihood of execution are included.
* Purpose: Shows the minimum level of new capacity likely to materialize.
* Use Case: Helps organizations plan for worst-case scenarios and ensure resilience.

### Cumulative Growth Over Time

Capacity is not only assessed on a yearly basis but also tracked cumulatively. This means we can see how states, providers or utility companies build up total capacity over multiple years.

<figure><img src="/files/gdvkj3Jw04kLvunWO9zA" alt=""><figcaption><p>Expected Power Capacity Demand (GW) in Virginia</p></figcaption></figure>

### Conclusion

This methodology provides a structured way to project data center power capacity demand by balancing optimism with realism. By offering three scenario paths—optimistic, baseline, and conservative—we help stakeholders prepare for both rapid growth and more cautious expansion, ensuring that infrastructure, investment, and policy keep pace with one of the fastest-growing industries in the energy and technology landscape.

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