Methodology

Every site, found and scored in the open.

Refinery Atlas turns public infrastructure data into a ranked pipeline of stranded-power sites. Here is exactly how a footprint becomes a scored, sourced candidate — and how you can audit or re-weight every number behind it.

Principles

01

The fastest MW is already on the grid

Greenfield power waits years for interconnection. A slabbed parking lot or a half-empty mill already holds energized 2–20 MW service the utility hasn't reclaimed. We hunt that.

02

A wide net, then corroboration

Every building footprint becomes a speculative candidate. Layoff notices, closures, and vacancy signals promote it to probable. Researched intelligence lifts it to verified. Confidence is earned, not assumed.

03

Every input is sourced

Each number carries its raw value, its normalization curve, and its provenance. Contacts surface only with a real source URL attached. No black boxes, no fabricated facts.

04

Two surfaces, one model

A searchable index for the analyst and a live map for the scout — both reading the same scored, sourced dataset. Adjust the weights and every site re-ranks.

The discovery funnel

  1. 01
    Ingest

    OSM building footprints + HIFLD/SeerAI grid + ERCOT queue across 40 countries, Texas-first.

  2. 02
    Match

    Each footprint joins its nearest substation (PostGIS KNN); area × archetype W/m² estimates load; generation and oversized polygons are excluded.

  3. 03
    Corroborate

    WARN layoffs, closures, and vacancy signals are name- and proximity-matched to promote candidates from speculative to probable.

  4. 04
    Enrich

    A research pass adds sourced owner / operator / utility / status — verified intelligence, never fabricated.

The candidate scorecard

The headline score every candidate carries is a weighted blend of three signals — the same axes you see on each site’s radar. Each maps its raw value through a piecewise-linear curve to 0–100.

Power60%

Estimated load from footprint × archetype W/m². The thesis weight — energized capacity is the prize.

0 → 100 across 0–20 MW

Grid proximity25%

Straight-line distance to the nearest ≥69 kV substation. Closer is cheaper to interconnect behind the meter.

100 at 0 mi → 10 at 10 mi

Voltage class15%

Voltage of that nearest substation. Higher class means more headroom to add load.

40 at 69 kV → 100 at 345 kV

Confidence tiers

Speculative

Energized footprint, estimated load — no corroborating distress signal yet.

Probable

Corroborated by a WARN layoff, closure, or vacancy signal within range.

Verified

Researched intelligence confirms the opportunity — sourced owner, status, and grid context.

Profiles — the full weighted-sum model

Beyond the headline score, each use-case re-weights eight auditable categories. Every weight is exposed as a slider in the atlas; change them and the whole map re-ranks live.

Profilepowergridlandfiberwaterclimatetaxcommunity
Hyperscale DC3010121587108
Colocation2281025551015
BESS Merchant1840120051510
BESS Offtake2020150052020
Edge DC (2–20 MW)321262236910
Container BESS1830220041313
Stranded Power3810105251218

Power

Available MW, transmission proximity, substation headroom, dual-feed redundancy.

Grid

Locational marginal price, congestion hours, ancillary stack (ECRS, RRS, Reg-Up).

Land

Acres, slope, FEMA flood overlap, NFPA 855 setbacks, zoning compatibility.

Fiber

Distinct providers within 1 mile, distance to nearest IXP, theoretical Dallas latency.

Water

Cooling water availability, distance to >50 cfs waterway, drought severity.

Climate

ASHRAE free-cooling hours, FEMA National Risk Index, severe-weather exposure.

Tax

JETI eligibility, Opportunity Zone, Chapter 312, ITC stack, paired-storage exemption.

Community

Permitting timeline, NIMBY history, construction trades availability and wages.

Why weighted-sum

Of the MCDA families — AHP, TOPSIS, ELECTRE, PROMETHEE — weighted-sum wins here for three reasons: users adjust weights live, it composes cleanly with per-category confidence, and it stays fully auditable in the UI. Composite maps to tiers (S 90+, A 80–89, B 65–79, C 50–64, D <50); confidence below 0.6 flags the weak inputs rather than hiding them.