High resolution energy demand data for everyone
The energy transition is being planned against a blurry picture of demand. We bring it into focus so that you can make data-driven arguments for electrification, renewables, and distributed energy resources across continents.
- Annual consumption at 1 km², split residential / non-residential / large facilities
- Hourly demand for Great Britain (experimental)
- Seasonal granularity and electrification scenarios
- Hourly demand for more countries and a DER optimization model
Use cases
- Energy System Modeling
Trade-off transmission-level investments with distributed energy resources or add higher-quality spatial detail to your model.
- Community Energy Planning
Easy-to-use baseline energy consumption estimates and electrification scenarios for more accessible and consistent planning.
- CCA & VPP Market Sizing
Quickly screen territories, estimate procurement obligations, or calculate addressable market size.
- Policy Research
Analyze local potential for distributed energy resources, diesel generator replacement with batteries, community generation, and more, across many communities with ease.
- Intervening in Rate Proceedings
Conduct sensitivity analyses in rate cases or distribution plans using an independent baseline and electrification scenarios.
- Grid Planning
Plan, site, and size new infrastructure where metered data doesn't yet exist.
What makes this different from existing products
- Trained on real metered data
Most downscaled products allocate demand proportionally using variables like population density and are never trained on high resolution data. Our algorithms are trained on >100k metered regions.
- Preserves totals
Pixels sum back up to official regional energy statistics, plus the large-site use those statistics leave out.
- Large facilities get special treatment
Smelters, steelworks, refineries and other large sites we identify one by one are points on the map, and their demand lands on their own sites instead of being smeared across a county.
- Sector-differentiated
Separate models for residential vs. non-residential demand, with large facilities estimated site by site.
- Pixel-level metadata and published validation data
We publish the details so that you can trust our model quality and easily understand where values come from.