Current energy system planning tools inadequately capture the impact of extreme weather events, particularly for systems with high renewable share. Energy system modelers increasingly recognize the need to systematically explore extreme events, with some efforts evaluating potential disruptions from cold spells and long-duration outages. Some studies have identified periods of wind and solar droughts, and scenarios from worst-case to multi-year challenges. However, identifying extreme events is highly dependent on the configuration of the energy system in use. Inconsistent testing methodologies may underestimate system vulnerabilities, highlighting the need for standardised stress testing approaches. Additionally, binary results (pass/fail) during extreme events lack comparability across studies and insight into how to improve the system design.

This study introduces a standardised method for stress testing energy system models under extreme weather conditions using the concept of a “survival surface”. Rather than simply determining whether a system can fail, our approach quantifies the margin by which it fails and identifies investments to remedy unserved demand. The survival surface identifies all viable combinations of three key components: (1) external transmission capacity, (2) storage capacity, and (3) back-up power generations. This surface contains configurations where supply meet demands with minimised investment cost. By plotting a given energy system as a point relative to its survival surface, we can quantify the system adequacy with precision. A system with components plotted on the same side as the origin relative to its survival surface is inadequate during the extreme event, and the optimal investment pathway is the perpendicular line to the nearest point on the survival surface. Additionally, comparing survival surfaces across different system designs can show which system is particularly vulnerable to that extreme event.

We integrate the method as a tool in the Calliope modeling framework to facilitate the use of this standardised method for a variety of energy system designs. The process takes a system design and weather time series (wind speed, radiation, temperature) as input and produces a three-dimensional survival surface as output. We showcase this tool with an extreme event in December 2007, a particularly low-wind cold snap, first for Germany, then in interconnected Central Europe, with different renewable scenarios for present-day, 2030, and 2050.

Our method provides a clear framework to evaluate system adequacy in withstanding extreme weather events, quantify the safety margin in three key components, and identify the optimal investment pathway. The integrated tool in the Calliope framework facilitates applications with a wide range of weather data and energy models, providing essential insights for planners and policymakers.