SPP LMP Merchant Curve: Southwest Power Pool Price Forecasts

SPP operates a nodal market where individual generator interconnection points settle at their specific locational marginal price. For financial trading and benchmarking purposes, the market coalesces around two reference hubs: the SPP North Hub and the SPP South Hub. The SPP South Hub is the primary load zone reference and the most liquid financial market point, reflecting prices in the Oklahoma and Arkansas load centers and serving as the delivery reference for most long-term PPAs and financial contracts written in the market. The SPP North Hub reflects prices in the generation-heavy northern zones of Kansas and Nebraska, where large concentrations of wind capacity are located. The North Hub typically trades at a discount to the South Hub, with the basis differential widening when north-to-south transmission constraints bind during high-wind periods. Beyond these two primary hubs, SPP’s nodal market produces distinct prices at individual generation nodes, which can diverge materially from hub prices during periods of binding congestion. Wind project economics in particular are sensitive to nodal curtailment and congestion discounts that are not captured by hub-level pricing. Noreva produces both hub-level and zone-level forecasts to address these use cases, with nodal analysis available for specific interconnection points.

Wind curtailment in SPP arises when wind generation output in the northern zones exceeds the capacity of north-to-south transmission paths to deliver that energy to southern load centers. When this occurs, the SPP operator instructs wind generators to reduce output, and in extreme cases, nodal prices at the curtailed generation points can go negative as the system pays generators to reduce injection. The result for a wind project owner is a realized energy revenue that falls below the SPP South Hub reference price by an amount equal to the curtailment-adjusted basis: the combination of price suppression at the generation node and reduced generation volume. This basis risk is not constant. It widens during periods of high wind coincidence across the Oklahoma and Kansas wind fleet, when generation substantially exceeds transmission capacity, and narrows during low-wind periods or high-load summer afternoons when the system is absorbing all available generation. The forward trajectory of curtailment basis depends on the pace of transmission expansion relative to wind capacity additions: SPP has approved several transmission upgrade projects, but the backlog of wind projects in the interconnection queue continues to exceed near-term transmission additions. Noreva’s curtailment basis model incorporates both approved transmission projects and probable future additions to produce a forward curtailment trajectory that is critical for wind project finance. See: Dispatchable Dominance in SPP and MISO.

SPP’s interconnection queue contains over 30 GW of proposed new gas capacity, driven by the need to replace retiring coal generation and provide dispatchable reliability capacity as wind penetration grows. The timing of this thermal buildout is one of the most significant uncertainties in SPP’s long-term LMP forecast. If new gas capacity enters quickly and ahead of demand growth, it will suppress SPP energy prices by adding competing supply to the dispatch stack during low-wind hours when gas sets the marginal price. In this scenario, peaker and combined-cycle asset economics are most challenged, and existing gas generator owners face margin compression. Conversely, if thermal additions are delayed by permitting, financing constraints, or supply chain bottlenecks, the retirement of existing coal capacity tightens the supply stack, supporting elevated on-peak prices and creating investment opportunities for new entrants. The interaction between thermal entry timing and coal retirement schedules is nonlinear: a coal retirement without near-term replacement tightens peak supply more severely than the retirement timing alone would suggest, because the coal unit that retires may have provided firm capacity that the wind-heavy system cannot replace on an equivalent MW basis during low-wind, high-load events. Noreva’s dispatch model captures this dynamic through explicit thermal queue screening and supply-demand balance analysis under a range of entry timing assumptions. Related analysis: Can Gas Save SPP?

SPP shares market boundaries with both MISO on its eastern border and ERCOT on its southern border, with each interface having distinct characteristics that affect SPP price formation. The SPP-MISO eastern interface is an AC-connected border with multiple constrained transmission paths. Economic energy flows across this interface depend on relative supply-demand conditions in each market: when SPP is long on wind generation and MISO is shorter, SPP exports power eastward, which can help absorb surplus wind and reduce SPP curtailment. When SPP is tight and MISO has surplus, flows reverse. The interface capacity is constrained in both directions, creating basis risk for SPP assets near the Arkansas and Missouri borders. The SPP-ERCOT boundary is fundamentally different: ERCOT operates as an electrical island with only limited DC ties to the surrounding AC grid, including SPP. These DC interconnects allow scheduled transfers but do not permit the same level of spontaneous economic energy exchange as AC interfaces. ERCOT price spikes during extreme weather events can therefore not be fully arbitraged away by SPP, limiting the value of geographic diversification across the two markets. For forward curve purposes, the SPP-MISO interface basis is modeled explicitly within Noreva’s dispatch framework, while the SPP-ERCOT DC tie is treated as a constrained scheduled flow with scenario analysis around utilization rates. See: SPP Capacity Market.