In SPP, the difference between running one model and running twenty-two is the difference between seeing a fraction of system constraints and seeing the full picture developers will ultimately be judged against. Other studies that rely on only 1–2 models capture, at best, 12–25% of the binding constraints SPP will identify. That blind spot can mean the difference between a project moving forward or facing millions in unexpected network upgrade costs.

Nira’s prospecting analysis mimics SPP’s interconnection process, applying 22 ERIS and NRIS models across nearly 10,000 Points of Interconnection to surface more than 41,000 unique constraints; the real picture developers must navigate.

Why SPP Uses 22 Models

SPP doesn’t rely on one set of assumptions. Its process is designed to account for the variability of the grid across different conditions:

• ERIS vs. NRIS: SPP requires both Energy Resource (ERIS) and Network Resource (NRIS) models, each of which surfaces different thermal and voltage constraints.

• Seasonal Variation: Power flows and system stress differ dramatically between summer peak, winter peak, and light load. A project that looks clean in one season may trigger dozens of constraints in another.

• Geographic Breadth: With nearly 10,000 POIs in play, constraint patterns shift depending on where generation enters the grid.

• This complexity isn’t optional, it reflects how the grid actually behaves. Skipping models isn’t just incomplete, it’s misleading.

Operating Conditions Add Another Layer of Complexity

It’s not just about the number of models, it’s also about which operating condition you study. SPP runs scenarios under summer peak, winter peak, and light load conditions. Each one surfaces a distinct set of binding constraints.

Summer produces almost three times as many constraints as winter peak, while light load adds a little less than a thousand of additional violations of its own. Because each condition reflects a completely different system state, relying on just one leaves developers blind to the unique risks revealed in the others.

The Risk of Cutting Corners

Developers who only model a couple of cases may think they’ve de-risked a project, but they’re often flying blind:

• Underestimating Costs: Missing constraints leads to underestimating upgrade exposure, sometimes by tens of millions.

• False Positives: Sites that look viable under a single case may be dead on arrival when tested across the full set of models.

• Lost Optionality: Withdrawing too late, or from the wrong position, can close off opportunities that better data would have preserved.

Even with the changes SPP is planning for DISIS 2026, the latest Generator Connection Process (GCP) draft manual shows SPP will still rely on a broad set of models. While the number of directly assigned Network Upgrades may decline due to GRID-C, the trend remains clear: running more models gives a truer, clearer picture of results.

How Nira Helps

Nira eliminates the blind spots of shortcut studies for prospecting by replicating SPP’s interconnection process end-to-end:

• Runs all 22 models across all operating conditions

• Surfaces the full constraint set developers will face

• Flags real upgrade risks early, while filtering out false positives

• Equips teams to make confident siting and withdrawal decisions

The takeaway is simple: in SPP, more models mean more accuracy, more foresight, and more confidence. And Nira is the only software solution that brings that ISO-level methodology into developers’ hands.