The Challenge

The frequency of costly natural disasters in the U.S. has dramatically increased over the past decade. Extreme weather events are increasing in both frequency and magnitude of impact due to changing climate conditions. In addition, the vulnerability of infrastructure and interdependent systems to these hazards has increased, along with the value of assets which are at risk. Frameworks currently used for energy system planning rely on historical weather information to inform decisions related to investment and retirement decisions, which impact resource adequacy, system reliability, and resilience. This reliance solely on historical data leads to inaccurate representations of electricity demand, availability of renewable generation, frequency and magnitude of extreme weather events. These factors combine place future energy systems at avoidable levels of risk of unserved energy and cascading outages.

Argonne’s Approach

Argonne has developed power system planning capabilities which incorporate data generated by detailed physics-based climate models to capture the impacts of projected future weather conditions more accurately. Leveraging Argonne-generated climate data the team has built models to determine how electricity demand and wind and solar generation profiles may evolve with changing climate conditions. By applying techniques for spatiotemporal alignment, these models, along with the climate and power system data, are incorporated into Argonne’s operations and planning framework, the Argonne Low-carbon Electricity Analysis (A-LEAF)

The methods and tools that Argonne is developing advance the scientific community by providing models and data to represent realistic climate conditions in future power systems and consider these conditions when planning infrastructure investments. The operations and planning tools developed by Argonne enable accurate incorporation of stochastic features into power system models. These enhanced tools can then be applied to provide insight into various  key challenges of grid modernization, such as quantifying the value of long duration energy storage technologies for mitigating extreme weather events in power systems of the future.