An hourly zonal model of the SPP Integrated Marketplace
The SPP model is an hourly zonal model of the Southwest Power Pool (SPP) Integrated Marketplace. A capacity expansion model builds the forward fleet, a production cost model simulates wholesale market outcomes (prices, dispatch, and flows), and a dispatch model derives battery revenues, spanning SPP’s central United States footprint from the current year through 2050.
SPP operates an energy-only Integrated Marketplace spanning 14 states. The market co-optimizes energy and operating reserves through a Day-Ahead Market and a Real-Time Balancing Market, settling at locational marginal prices (LMPs).
The footprint is represented as 18 settlement zones, each aligned to an SPP member utility’s pricing area.
Footprint and zones
The zonal representation is a deliberate simplification. SPP’s real market clears at thousands of individual pricing nodes; the model groups these into 18 settlement zones and solves one locational price per zone. Congestion between zones is captured through interface limits, but congestion within a zone is not resolved. Hovering a zone on the map shows its full member-utility name.
The zones follow SPP member utilities across the 14-state footprint, grouped geographically:
| Area | Settlement zones (member utility) |
|---|---|
| North | WAUE (WAPA and Basin Electric), NPPD, OPPD, LES |
| Central | WR (Westar, Evergy Kansas Central), SECI (Sunflower), the Kansas City utilities KACY, KCPL and INDN, MPS (Evergy Missouri West), SPRM, EDE (Empire District) |
| South | GRDA, OKGE (East) and OKGE (West) — Oklahoma Gas and Electric’s eastern and western zones, WFEC (Western Farmers), CSWS (AEP West), SPS (Xcel Energy) |
The Oklahoma Gas and Electric territory is split into two zones, OKGE (East) and OKGE (West), at a longitude of 97.7 degrees west. This separates the wind-rich west of Oklahoma from the load-rich east, where Oklahoma City sits, so the price differences and congestion between them are resolved rather than averaged away.
Inputs
| Category | Summary | Key Data Sources | Details |
|---|---|---|---|
| Demand | Forecast peak per zone from SPP planning, scaled by a historical weather-year shape, with large loads layered on | SPP Integrated Transmission Plan, EIA-930, EIA-861, PowerGEM LTRA | Demand |
| Generation | Plant-level inventory mapped to zones, with heat rates, commitment parameters, and weather-year capacity factor profiles | EIA-860M, EIA-923, NREL reV, LBNL, SPP outage feed | Generation |
| Commodity prices | Natural gas from forward curves and long-term outlook with hub delivery premiums, coal anchored to delivered basin prices, plus defaults for minor fuels | CME NG Futures, EIA AEO, EIA-923 | Commodity Prices |
| Transmission | Zonal interface limits and interchange with neighboring systems (SPP West and non-SPP markets) | SPP transmission planning, NREL, EIA-930 | Transmission |
| Capacity expansion | Forward buildout from the CEM, anchored near-term to interconnection-queue projections | NREL ATB, Lazard, Modo Energy BESS CapEx Survey, SPP generator interconnection queue | Capacity Expansion Model |
Modeling
Two-stage unit commitment and dispatch
The model runs in two stages. The unit commitment stage determines which thermal generators are online using binary on/off variables and mixed-integer solving, respecting minimum-load, minimum up and down times, and start costs. The economic dispatch stage fixes those commitment decisions and re-optimizes output as a linear program, yielding locational marginal prices from the shadow price on the power balance constraint at each zone and hour.
Locational and hub prices
The model produces one LMP per zone. From these it reconstructs SPP’s two published trading hubs as weighted averages of their constituent zones, following SPP’s own hub definitions so the modeled hub prices line up with SPP’s:
- SPP North Hub: LES, NPPD, and OPPD (the Nebraska zones).
- SPP South Hub: CSWS, OKGE (East), and WFEC (the Oklahoma zones).
Each zone enters at the weight SPP assigns it in the hub definition. A system price is taken as the simple average of the two hub prices.
Operating reserves
SPP’s real-time market co-optimizes energy with four operating reserve products: regulation-up and regulation-down (procured system-wide) and spinning and supplemental reserves (procured by reserve zone). In the model, reserve prices are not co-optimized inside the production cost solve. Instead they are estimated statistically from historical SPP ancillary-service clearing prices. They are driven by the energy price and adjusted for the growth of the battery fleet competing for a finite reserve requirement, then supplied to the Dispatch Model.
Resource adequacy
SPP has no centralized capacity market. Resource adequacy is governed by a seasonal Planning Reserve Margin (PRM) obligation on load-responsible entities, with separate summer and winter requirements; the winter requirement is materially higher, reflecting SPP’s cold-weather reliability risk. Each technology contributes accredited capacity: thermal by forced-outage-rate class, wind and solar by effective load carrying capability (ELCC) that declines with penetration, and storage by ELCC that varies with duration. This requirement is enforced in the Capacity Expansion Model.
Outputs
Macro databook
Annual system-level metrics compiled from hourly solve outputs:
- Generation by technology: system-wide and zonal splits
- Zonal and hub prices: annual average, TB4 and TB2 spreads
- Peak demand: summer and winter by zone
Site-specific databook
Monthly and annual BESS metrics for individual storage assets:
- Revenue: energy arbitrage and operating reserves
- Cycling: charge/discharge cycles and degradation
Dispatch model revenues
The dispatch model produces site-specific revenue forecasts broken down by stream. See the Dispatch Model for methodology.