Energy Flow

An exploratory model of US energy, not a forecast. Pick a region and year to see how energy moves from fuels through generation into end uses. Past the historical boundary the chart switches to projection mode — open Build a scenario below to pull levers (build caps, EV adoption, retirements, carbon price, …) and watch the picture shift.

🔍 See exactly how the model works — every source, assumption & equation behind the numbers
What this is for

The point is what-if, not what-will-be. Move a lever, render the scenario, and the consequences flow through generation, end-use sectors, the emissions panel, and the impact-delta readout side by side. Read the numbers as directional: "this lever, moved this way, shifts the picture this much" — not "2050 will look like this."

Treat it as a sandbox. Build a scenario, ask whether the change you made should have moved the chart that way, then iterate. Saved baskets keep favourite scenarios around to reload and compare.

Build a scenario

Catalog

Editor

Basket

1 Quad equals 293 TWh of electricity — or about four days of everything the US runs on 8.3 billion gallons of gasoline ≈ 470 billion hamburgers — burned for their calories, ~540 kcal each For scale: the whole US runs on about 93 Quads a year — so one Quad is close to four days of total US energy.
Methodology & data sources

Historical artifacts are derived from the EIA SEDS dataset (State Energy Data System) via the project's fetch_eia pipeline. Values use the EIA's captured-energy methodology (October 2023 onward), where noncombustible renewables (solar, wind, hydro, geothermal) count at the heat-rate constant 3,412 Btu/kWh — replacing the previous fossil-fuel-equivalency convention that inflated those sources by a ~3× factor. As a result, renewable shares in this chart will read smaller than older "Estimated" LLNL charts published before the methodology change; they match LLNL's current Actuals series exactly. See EIA SEDS change log for the methodology details.

Projection-mode artifacts (years past the historical boundary) come from the v2model engine — a cost-driven annual loop with Wright's-law learning curves, per-source max-build caps, CES electrification elasticity, and the empirical-correction variables (retirement slippage, capacity-factor degradation, construction-delay drag). Per-state research overrides apply for state regions; the "Build a scenario" panel exposes the full lever surface for what-if exploration.

Lever defaults sit in research/**/*.md with quality tiers L1 (primary EIA / NREL / IRENA) through L4 (transcribed unverified). When a projection consumes any L4 value the meta line surfaces a "⚠ less-verified source" callout. See docs/concepts.md for the v2 engine spec and DECISIONS.md for the full design history.

Explore the model architecture → for a guided tour of the engine's generation sources, submodels, feedback loops, levers, and decision history.