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Models / PyPSA-USA ERCOT

Production-cost back-cast of the ERCOT market covering most of Texas: full-year 2025 3-hourly economic dispatch of the real fixed fleet (named EIA-860 units at their true sites), MOSEK-solved, validated per fuel against EIA-930 actuals.

License: MIT
Repository
licenseMITproblemLP

Overview

A production-cost (historical back-cast) model of the ERCOT market covering most of Texas for the full year 2025 at 3-hourly resolution. The fleet is fixed to the historical mix of real, named generating units, and the model dispatches them economically to meet observed demand — answering "given the plants that actually existed, how would the system have been operated, and at what locational prices?"

ERCOT is electrically islanded (its own interconnect), so it is modelled in full rather than carved from a larger grid — the cleanest of the seven.

Spatial resolution: 185 county-level zones. Built on the open-source PyPSA-USA toolchain.

How it's built

  • Fleet — every operable generating unit from the latest EIA record (EIA-860 2024 final plus EIA-860M 2025 monthlies, so 2025 build-out is included), placed at its true coordinates with named identity, scoped to this market's balancing authority.
  • Renewables — wind and solar capacity factors from ERA5 reanalysis (2025 weather), mapped to each bus.
  • Demand — hourly EIA-930 / GridEmissions actuals for the market's balancing authority.
  • Dispatch — an economic-dispatch LP (coal on a must-run floor; no unit commitment yet) over the full year, fixed transmission, load-shedding priced at value-of-lost-load, solved with MOSEK.

Validation

This page checks the model's output against independent observations — see the tables and charts above:

  • Generation by technology — modelled vs EIA-930 / GridEmissions actuals, per fuel, with daily correlation.
  • Generation mix — each technology's share of total generation, model vs observed. This is footprint-invariant, so it stays fair even where the model's carve boundary differs from the EIA-930 balancing-authority footprint.
  • CO₂ emissions — annual generation CO₂ vs an EIA-930-derived estimate; a single headline trust number.

Renewable generation tracks the observed daily shape well (high day-to-day correlation for wind and solar). Wholesale-price validation against ISO day-ahead LMP is deferred to a future calibrated version — the energy-only economic dispatch clears at marginal fuel cost and structurally underprices vs day-ahead LMP (the price metrics are computed and retained in the backend). See Known limitations and the project's validation audit for the full cross-market detail.

Known limitations

This is a research-grade back-cast; treat it as indicative, not a settlement-grade reproduction.

  • Fuel-cost vintage, not fleet. The generator fleet is latest-operable and already includes 2025 build-out (via EIA-860M); what is held at 2024 is unit fuel costs and heat rates (PUDL has no 2025 EIA-923 yet). Any capacity commissioned after the EIA data cutoff is not captured, so the newest late-2025 renewables can read slightly low. Refreshes when EIA-860/923 2025 final lands (~Oct 2026).
  • Coal runs on a must-run floor. Cheap 2025 gas would otherwise let efficient combined-cycle plants out-compete less-efficient coal in the pure linear dispatch, but real coal runs as constrained baseload — so each coal unit carries a minimum-load floor (coal now tracks EIA-930 to within ~20%). Interim; a linearised unit-commitment version is planned.
  • Wholesale prices are not yet validated on the page. The energy-only merit-order LP clears at marginal generation cost (≈ gas cost) and omits scarcity/reserve pricing, time-varying fuel, and fine-grained congestion, so modelled prices sit well below ISO day-ahead LMP. Price validation is deferred to a future calibrated version; the metrics are computed and retained in the backend.

Data & attribution

EIA-860 / EIA-923 / EIA-930 (US Energy Information Administration, public domain), ERA5 reanalysis (Copernicus / ECMWF), renewable profiles via NREL GODEEEP, network and methodology from PyPSA-USA (MIT), solved with MOSEK.

Downloads

  • Solved network (.nc) — the full PyPSA network with dispatch and prices (free, sign-in).
  • Convexity database (.db) — re-solvable model with named units pinned at their sites (licence-gated).