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How much announced capacity is actually deliverable: on both sides of the meter, the generation that gets built (the PJM completion anchor) and the data-centre load that survives grid operators' screens (PJM + ERCOT). Announced is a scenario, not a baseline.
Interactive front-end over published aggregates · v1 (combines supply and load sides) · canonical concept: DOI 10.5281/zenodo.20559430 · v1 paper: DOI 10.5281/zenodo.21971645 · NM AI Research, ORCID 0009-0003-4213-7769 · CC BY 4.0
Each milestone is conditional on surviving the previous one, so the rates multiply. The steepest drop is at the System Impact Study, where a project learns its share of network-upgrade costs.
| Stage | % of entered | what it is |
|---|
Where the MW die: 61% of announced MW exit before a signed agreement; another 13% exit after one (a signed IA converted to service only ~58% of the time). The gap is viability and build, not paperwork.
Recent cohorts read low only because they have not had time to resolve, so the headline uses the mature, near-fully-resolved windows (bold). Those converge on ~16–25% built, about one announced MW in five.
| Cohort | % built | % withdrawn | maturity |
|---|
On the load side the operators deflate the headline themselves and publish the method. This view does not deflate the load: it places PJM's and ERCOT's own published vetting side by side, and brackets the result. The contribution is the cross-region, reproducible packaging, not the deflation.
PJM accepts a request into its forecast only after a documented haircut (50% default non-firm probability, 70% utilization, 70% capacity-to-demand, minimum 36-month ramp); only the Firm subset (backed by an Electric Service Obligation or Construction Commitment) counts toward capacity. Its worked example survives at ≈48% of requested capacity.
| Stage | 2030 GW | % of submitted | what it is |
|---|
ERCOT had almost no barrier to entry before its PGRR115 rules, so its queue was heavily padded. It publishes a realized de-rate: actual per-site peak consumption is 49.8% of requested MW. Three quantities must be kept apart: request-survival (≈50%), realized utilization (49.8%), and energized-to-date (≈2%, an age figure: the surge is too young to have built out, not a failure rate).
| Stage | GW | % of requested | what it is |
|---|
No matured data-centre load cohort has resolved yet, so the deliverable rate is bracketed, not measured. The band spans the regime change: the lower rail is the lightly-gated queue's historical completion; the upper rail is the operators' newly-vetted acceptance.
| Rail | Survives | basis |
|---|
Cross-region finding: two independent operators, PJM applying a forward de-rate (≈48%) and ERCOT measuring a realized one (49.8%), land near half of requested data-centre demand surviving the first credible screen, and both now gate the forecast on an executed agreement. The two ≈50% figures are constructed differently (PJM's bundles a completion-probability factor; ERCOT's is conditional on the project being built), so the resulting claim is structural, not a numeric identity.
What this is. A realized announced-to-in-service completion rate from PJM's own resolved serial queue (8,253 generation projects, ~837 GW announced). The calculator lets you deflate any announced headline through the three measured attrition stages and watch the deliverable move. Defaults are the PJM mature-cohort base rate; the sliders are for sensitivity, not invention.
The load-bearing assumption. The mature 2010–2017 cohort is generic historical generation (wind/solar/gas) used as a completion base rate, not capacity announced to serve AI. Transferring that rate to the AI-era cohort is the named assumption (cohort comparability); FERC Order 2023 could raise completion, speculation could lower it.
Both sides of the meter (v1). The calculator and PJM evidence deflate the supply side (generation that gets built); de-duplication barely moves it (r1 ≈ 0.81–0.92): the gap is overwhelmingly viability and build, and "Built" counts only In Service (conservative). The Data-centre load view adds the demand side, where the operators do the deflation themselves: this tool packages PJM's and ERCOT's own published vetting and brackets it, rather than deflating the ~950 TWh headline itself. The two ≈50% first-screen figures (PJM applied, ERCOT realized) are constructed differently, so the cross-region claim is structural. Every output is a band with its softest input named: treat any headline as a scenario, not a baseline.
No raw PJM data is bundled here (it carries a redistribution restriction); only the published derived aggregates. The full method reads a locally-obtained PJM export; see the Zenodo record. r2 × r3 = built/entered is an algebraic identity, not an independent check. Anchors (LBNL ~14–20% national; Exelon ~22% of company pipeline) are loosely comparable, not like-for-like.
Disclosure. No third party reviewed, funded, or directed this work. Independent analysis, not investment advice.
Reproducibility. This page embeds the published aggregates (funnel.csv, cohorts.csv, and load-side dc_funnel.csv, ercot_funnel.csv) verbatim, regenerated by build.py; full reproduce.py and write-up live in the Zenodo record.