As extreme weather events become more frequent and severe, planners need tools to evaluate how the grid performs under credible worst-case scenarios. This report introduces a stress testing framework that complements traditional resource adequacy analysis by simulating high-impact, low-probability (HILP) events—such as prolonged cold snaps, heatwaves, and renewable droughts—while focusing on the role of interregional transmission in mitigating risk.

The method involves four steps: defining extreme event scenarios, identifying key risk drivers, applying stress variables (e.g., thermal outages, renewable variability, load uncertainty, and transmission constraints), and conducting multi-day simulations. By using weather-correlated, synchronized data across neighboring regions, the approach better represents how transmission and external support influence system resilience.

A case study in the Southwest Power Pool (SPP) applies this framework across several types of extreme events and evaluates different assumptions about neighboring systems and import capabilities.

Key findings include:

• Interregional transmission significantly enhances resilience, providing a critical buffer during times of internal system stress. Even when neighboring regions are also under duress, coordinated imports help avoid outages.
• Stress testing enables detailed examination of outlier events that traditional probabilistic methods often mask, while avoiding the need to assign precise probabilities to rare but consequential conditions.
• By resampling historical data to create alternative renewable profiles and thermal outage conditions, stress testing expands the range of credible risk scenarios and benefits from growing access to high-quality weather-correlated datasets.

This approach offers planners a more realistic basis for evaluating extreme system risks and supports more robust, transmission-aware investment decisions.