Resilience in energy systems is crucial for their ability to prepare, adapt to, and recover from disruptions. However, current planning models for power grid systems often face significant challenges, including limited accuracy and geographic coverage largely due to computational constraints. These limitations hinder the ability to effectively assess and enhance the resilience of the electric grid, making it difficult to withstand and recover from various threats.
To address these challenges, we want to develop capabilities for measuring resilience through advanced modeling and analysis tools. Using methods such as heuristics and machine learning, we aim to increase efficiency in the evaluation of resilience and optimization goals. We also aim to move towards decentralized energy structures through a framework that accounts for multiple objectives and grid dynamics.
Ultimately, our vision is to create flexible, modular, self-healing, and smart systems that can effectively model large-scale failures in interconnected electrical systems and support diverse operational methods.
Project Highlights
Leveraging multi-fidelity power grid models to accelerate optimization methods used for large-scale investment planning applications.
Designing next-generation protection devices that enable deployment of distributed energy resources in low-voltage spot and meshed networks for backup generation during resilience events.
Building on past Sandia work to create microgrids that provide exceptionally robust, threat-agnostic resilience, using any available sources, and using local measurements only, without a need for real-time data sharing.
Partnership Opportunities
We are actively seeking partners to collaborate on our innovative projects aimed at enhancing the resilience and efficiency of energy systems. If you are interested in joining us in this important work, we invite you to explore the available partnership opportunities by getting in touch with us. Together, we can drive advancements in technology and create a more secure energy future.
Defining, Measuring, & Optimizing Grid Resilience