What does a data-center buildout ask of the grid?
A transparent planning experiment: demand pathways become capacity decisions, outage tests, and material consequences. The results below are representative-cycle optimization outputs—not an annual forecast or a utility planning commitment.
From demand to consequence
The model follows one auditable chain: public demand evidence becomes an investment decision, an outage test, and a capacity-linked supply-chain estimate.
Three pathways into 2030
Low follows the benchmark trajectory; central adds a staged project ramp; high is a stress case. Cleanview capacity supplies project context, not direct demand.
Capacity follows the peak
Select a pathway to inspect the least-cost capacity bundle under reserve and resilience constraints.
When the import path disappears
Each point is an independent four-hour outage-start test. High growth reaches the model's resource limits and leaves critical load unserved in some starts.
What the bundle costs
The cost breakdown is an optimization accounting view across the representative cycle; it is not an annualized utility revenue or rate forecast.
Infrastructure has a material shadow
These are capacity-linked accounting estimates using analyst intensity ranges, not facility bills of materials. Quantities are tonnes; supply limits are illustrative scenario thresholds, not verified shortages.
Evidence, not false precision
Inputs
- Observed / derived EIA regional load
- NOVEC/PJM forecast benchmark
- Public Cleanview project status
- Published planning context
Boundaries
- Representative 24-hour cycle
- Analyst technology and material ranges
- Independent outage survivability tests
- No facility bill of materials