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.
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. Prefer plain language? The assistant turns "make solar cheaper, phase out coal by 2035" into scenario levers for you.
Layout settings (dev)
Build a scenario
Catalog
Editor
Basket
Trajectory to 2050
Solid = your scenario Dashed = default projection · drag the year slider to move the marker. Y-axis is zoomed to the data range, not zero-based.
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. Research findings → for the longer-form things this project noticed along the way (literature gaps, empirical surprises, honest negative results).