SunSpot

Inspiration

Solar developers spend weeks and real money evaluating land before knowing if a site is any good. The data that answers "is this a good spot for a 100MW farm" exists, but it's scattered across half a dozen government agencies in half a dozen formats. We wanted to put it in one place and make it interactive.

What it does

SunSpot is an interactive US map for solar farm site selection. Drill from state down to county and get a suitability score built from eight adjustable, weighted factors: solar irradiance, cloud cover, temperature effect, soil, slope, environmental risk, grid access, and financials. Each county shows a 12-month efficiency curve, a cost breakdown, and a payback estimate for a 100MW farm, so developers can compare sites and export the numbers.

How we built it

The map runs on Mapbox GL JS over real Census county boundaries. The scoring engine pulls from NASA (irradiance, cloud/temperature climatology), NREL (PV production modeling), HIFLD (grid infrastructure), USDA (land values), and EIA (electricity prices), normalized into one per-county score. Weights are adjustable in the UI and scores recompute live. Challenges we ran into Reconciling data at very different resolutions — raster climate grids, point infrastructure data, county polygons — into one number per county. Keeping the map responsive while re-scoring 3,000+ counties on every weight change. Making sure the rubric stayed transparent and defensible rather than arbitrary-looking.

Accomplishments that we're proud of

A national, county-level suitability score built entirely on real public data, with fully adjustable weights that recompute live, and a drill-down from map to financial breakdown that feels like one tool, not several stitched together.

What we learned

How differently government agencies structure the same category of data, and how much domain expertise it takes to turn "site selection criteria" into a rubric developers would actually trust. What's next for SunSpot Calibrate the rubric against real built solar farms, add parcel-level data for finer-grained scoring, extend the approach to wind and storage siting, and validate against real permitting outcomes.