A large-load facility (hyperscale data center or comparable industrial load) is under consideration for the subject county. This brief establishes the county's measured baseline across the dimensions a large new electrical and housing load actually moves: energy cost-of-living, grid reliability, displacement pressure, and local market structure, so the siting decision is made against evidence rather than assumption.
The honest core of the product: the direction of each impact is documented and defensible; the magnitude is labeled not-yet-calibrated rather than dressed up as false precision (see §8).
Headline baseline read: the subject is a low-energy-stress, elevated-displacement-pressure, structurally-concentrated county on a cooperative utility. It has headroom on energy cost-of-living that a new load consumes, grid fragility demonstrated under extreme weather, and a housing market already stretched on the renter side.
| Dimension | Value | Relevance to a large new load |
|---|---|---|
| Population | 119,398 (flat 5-yr growth) | limited absorptive slack in housing |
| Median household income | $66,254 | mid-income, distributes siting effects differently than an affluent county |
| Poverty / child poverty | 11.7% / 16.8% | the cohort most exposed to rate + rent pressure |
| Renter share | 33.2% | the displacement-exposed tenure |
| Cost-burdened households | 46.1% | already stretched before any new demand |
| Median gross rent | $1,125 | the number a construction-phase influx moves |
| Civic Health Score (v3.2) | 49.8 (state rank mid-pack) | middle of the state |
| Energy Stress | 27.3 — low | the headroom (see §3) |
| Eviction-Risk | 61.7 — elevated | the pre-existing displacement floor (see §5) |
| Monopoly Stack | 4 of 6 — moderate | limited competitive discipline (see §6) |
| Broadband access | 86.6% | adequate for siting |
| Existing federal $ footprint | $474.2M total / $18.3M contracts / $3.4M grants | the county is already a federal-spend node |
Ownership (EIA-861). 5 utilities serve the county: 2 cooperatives, 0 investor-owned, 0 municipal. Dominant ownership is cooperative. The county is not under an investor-owned monopoly. This is a protective factor: cooperative surplus returns to ratepayers rather than shareholders, dampening the rate-extraction channel that hits investor-owned-monopoly counties hardest.
| Class | Sales (MWh) | Customers | Avg price (¢/kWh) |
|---|---|---|---|
| Residential | 16,914 | 1,697 | 12.88 |
| Commercial | 5,274 | 519 | 14.00 |
| Industrial | 63,450 | 221 | 6.16 |
| Total | 85,639 | 2,437 | 7.97 |
The industrial rate (6.16¢) is less than half the residential rate (12.88¢), the standard large-load discount. The siting question this raises is cost-allocation: a hyperscale facility pays the low industrial rate while the capacity it requires is procured against the whole system.
| Year | Customer-hours out | Max customers out | Days with an outage |
|---|---|---|---|
| Year 1 | 1,701,977 | 28,680 | 364 |
| Year 2 | 140,165 | 4,476 | 364 |
| Year 3 | 228,946 | 11,110 | 365 |
| Year 4 | 160,352 | 9,160 | 366 |
| Year 5 | 228,896 | 23,588 | 364 |
The Year 1 spike (1.7M customer-hours, ~10× a normal year) is a major regional winter-storm grid crisis. It is the single most important grid fact for a siting decision here: the local grid has a demonstrated extreme-weather failure mode, and a large new firm load changes both the capacity math and the curtailment priority during the next such event.
Climate demand (NOAA NCEI degree-days). Cooling-dominated: a recent year shows 1,856 heating and 2,780 cooling degree-days. Summer cooling load is the system's peak driver, the same season a data center's own cooling load peaks.
The composite Energy Stress of 27.3 is "low" only in aggregate. The distribution by income (AMI) and tenure shows where the exposure sits, and these are the households a rate change reaches first:
| AMI bracket | Owner burden | Renter burden | Owner HH | Renter HH |
|---|---|---|---|---|
| 0-30% AMI | 19.05% | 13.15% | 2,059 | 3,230 |
| 30-60% AMI | 8.79% | 6.31% | 3,469 | 3,901 |
| 60-80% AMI | 5.77% | 4.47% | 2,725 | 2,590 |
| 80-100% AMI | 4.63% | 3.30% | 2,859 | 1,548 |
| 100%+ AMI | 2.03% | 1.71% | 15,849 | 4,901 |
The poorest owner-occupant households already spend 19% of income on energy, more than 3× the 6% federal energy-poverty threshold; the poorest renters, 13%. There are ~5,300 households in the 0-30% AMI bracket.
| CHS section | Score | Note |
|---|---|---|
| Infrastructure | 60.8 | strongest section |
| Health | 52.8 | |
| Education | 52.5 | |
| Economic | 52.4 | |
| Civic Participation | 41.4 | |
| Transparency / DSQI | 40.1 | weak, public records hard to reach |
| Environment | 32.7 | inverse of Environment Burden Index 67.3 |
| Composite | 49.8 |
The low Transparency / DSQI (40.1) is itself siting-relevant: a county whose records are hard to reach is a county where a large deal is harder for the public to scrutinize.
The eviction composite (61.7, elevated) decomposes as (percentile ranks, higher = more pressure):
| Component | Raw value | Rank score | Weight |
|---|---|---|---|
| Cost burden | 46.1% | 83.3 | 45% |
| Renter share | 33.2% | 80.9 | 20% |
| Energy burden | 5.17% | 19.0 | 20% |
| Utility cost burden | 2.10% | 28.2 | 15% |
Displacement pressure here is housing-cost-driven, not energy-driven: cost burden and renter share are both in the 80th+ percentile nationally, while the energy components are low. A large-load facility's construction phase brings in-migration and a wage-stratified workforce that lands on exactly this constrained rental stock.
| Market | Status | Siting relevance |
|---|---|---|
| Electric | cooperative / competitive | protective |
| Broadband | monopoly | a hyperscale tenant negotiates around it; residents don't |
| Banking | adequate | |
| Legal aid | adequate | thin tenant-side legal capacity if displacement rises |
| Food access | desert | |
| Predatory lending | capture | the cohort under new rate / rent pressure is already lending-captured |
| Hospital | single-system monopoly |
The concentration that matters most for a siting decision is the predatory-lending capture overlapping the cost-burdened renter cohort: the households most exposed to siting-driven cost increases are the ones with the fewest non-predatory financial options.
Magnitude redacted, see §8 caveat.
| Indicator | Baseline | Direction under a large new firm load |
|---|---|---|
| Energy Stress | 27.3 (low) | up — 0-30% AMI households first |
| Grid outage exposure | 1.7M cust-hrs (crisis yr) / ~200k normal | up — peak-event risk; curtailment-priority dependent |
| Eviction-Risk | 61.7 (elevated) | up — construction influx + wage stratification |
| Net Community Protection | +15.2 (thin) | down if rate + rent pressure outpace tax-base gains |
| Federal / tax base | $474M footprint | up — the upside the deal is sold on |
GovParti does not hand a county a false-precision dollar figure. The direction of each impact is established from the measured baseline plus the documented mechanism (rate cost-allocation, grid coincident-peak, construction-phase housing demand). The magnitude is fit from a natural-experiment event study across counties where data centers were already built, using difference-in-differences against synthetic controls. That calibration is in progress, and until it completes, magnitude is reported as a direction plus a modeled range, never a point estimate. The full methodology is documented in GovParti's internal-equations appendix (reproducible for SSRN / openICPSR review).
A mature data-center county elsewhere shows the captured end-state: a county that captured the tax base (CHS 63.8, Infrastructure section 74.9, Net Community Protection +62.8). But that county started affluent (4% poverty, $179k median income, 22% renters). The subject is mid-income with 33% renters and an already-elevated displacement floor. The same siting decision distributes very differently because the starting conditions differ. Surfacing that difference, with the receipts, is exactly what a Tier 3 brief exists to do.
| Domain | Source |
|---|---|
| Demographics, income, poverty, tenure, cost burden | Census ACS 5-year + SAIPE |
| Energy burden by AMI × tenure | DOE LEAD |
| Utility ownership + rates by class | EIA-861 |
| Grid outages | ORNL EAGLE-I |
| Degree-days (climate demand) | NOAA NCEI |
| Health, mortality, health-center access | CDC |
| Traffic safety | NHTSA FARS |
| Environment (EJ, pollution, PFAS, EJI, SVI, AQI, Superfund) | EPA + CDC ATSDR |
| Education, libraries, disasters, legal aid, food | NCES, IMLS, FEMA NRI, LSC, USDA |
| Federal spending footprint | USAspending |
| Transparency / records | GovParti county-records registry |
Every figure is reproducible from cited public sources. Per-index computation (CHS v3.2, Environment Burden Index, Energy Stress v1_partial, Eviction-Risk v1_partial, Monopoly Stack, Market-Protection family) is documented in GovParti's internal-equations appendix.