How single-asset battery revenues are modeled
The dispatch model produces site-specific revenue forecasts for individual battery energy storage assets, using day-ahead zonal prices from the production cost model. It co-optimizes energy arbitrage against operating reserve revenues from the perspective of a single asset owner. The forecast runs on the day-ahead market only: there is no real-time settlement, so real-time price volatility is not captured.
It is the same single-asset dispatch optimization used across Modo’s market regions, applied to SPP prices. See the core Dispatch Model for the shared methodology.
Revenue streams
| Stream | Method | Source |
|---|---|---|
| Energy arbitrage | Co-optimized | Day-ahead zonal LMPs from the production cost model |
| Operating reserves | Co-optimized | Predicted day-ahead reserve-zone prices |
SPP has no centralized capacity market, so there is no capacity-market revenue stream. A storage asset’s contribution to resource adequacy is reflected through capacity accreditation in the Capacity Expansion Model, not as a market payment.
Energy arbitrage
The battery charges and discharges against its day-ahead zonal LMP, subject to state-of-charge, power, round-trip efficiency, and cycling constraints. The model optimizes over the price horizon with perfect foresight, representing an upper bound on achievable arbitrage; realized capture is lower in practice.
Operating reserves
Four SPP ancillary-service products are modeled. Regulation is procured system-wide, while the contingency reserves are defined across SPP’s reserve zones:
| Product | Procurement level |
|---|---|
| Regulation up | System-wide |
| Regulation down | System-wide |
| Spinning reserve | Reserve zone |
| Supplemental reserve | Reserve zone |
Reserve prices are not co-optimized in the production cost solve. They are predicted statistically (a gradient-boosted model on historical SPP day-ahead ancillary-service clearing prices), driven by the energy price in the relevant reserve zone and adjusted for the growth of the battery fleet: as more storage competes for a finite reserve requirement, per-MW reserve value is depressed. The dispatch model values reserves at these predicted prices for the products an asset is eligible to provide, and trades them off against energy each hour.
SPP also operates ramp-capability and uncertainty products, but these are not valued in the forecast. Only regulation, spinning, and supplemental reserves earn revenue alongside energy.
Calibration
A single calibration factor of 80% is applied to every modeled revenue stream. It scales the optimizer’s perfect-foresight result down to the revenue a real, actively traded asset is expected to capture in practice.
SPP has little realized battery operating history to calibrate against directly, so the factor is carried over from Modo’s benchmarking in more established storage markets, principally Great Britain and Australia’s NEM, where years of modeled and actual asset revenues can be compared. It will be revisited as SPP storage history accumulates.
Outputs
Monthly and annual per-asset metrics:
- Revenue by stream
- Cycling: charge/discharge cycles and degradation
The detailed results also report, for each period, the cleared price of every stream, the day-ahead energy price and each ancillary-service price, alongside the dispatched charge and discharge volumes and state of charge.