Technical Research Thrusts

The Mission Campaign is organized around three research thrusts answering fundamental questions that are relevant to improving resilience among US energy systems and other critical infrastructures. An integrated portfolio of projects across these three thrusts will ultimately result in a cohesive set of capabilities .

Thrust 1: Science of Vulnerabilities

Question: What are the vulnerabilities and physical failure mechanisms of node electrical hardware and control equipment for intentional and sophisticated kinetic, EMP, GMD, and cyber attacks?

Outcome: New tools to assess vulnerabilities and risk in the energy and critical infrastructure system.

Related Projects

Dynamic Monitoring to Analyze Grid Vulnerability to Fire
ADROC: Emulation Experimentation Platform for Advanced Resilience of Control Systems
The “HARMONIE” Special Protection Scheme
Hallucinating Canaries
Low-Cost HEMP Testing

Thrust 2: Materials, Device, & Cyber Innovation

Question: What novel materials, devices, and cyber advances will most cost effectively increase resilience?

Outcome: New high-energy materials, cost effective physical and cyber solutions.

Related Projects

Nano structural Granular Metals for Improved EMP Protection
Discovery of New High-Frequency Magnetic Materials Enabled by Artificial Intelligence
Signal-Based Fast-Tripping Protection Schemes for Electric Distribution System Resilience
Solid-State Transformer Technology

Thrust 3: System-Level Threat-Informed Computational Science

Question: What are the critical elements of the electrical energy system, mechanisms of cascading failures, and potential approaches for a more resilient/secure architecture?

Outcome: Tools to analyze and asses how to optimize and deploy solutions for maximum benefit (economics, security, and resilience)

Related Projects

Critical Node Identification, Vulnerability Modeling and Topology Optimization for the Electric Grid
Development of Power System Models for Optimal Restoration Subject to Intentional Threats
Dynamics-Informed Optimization for Resilient Energy
REDLY: Resilience Enhancements Through Deep Learning Yields
Power System Vulnerability Identification Through Deep Reinforcement Learning
SHAZAM

Technical Research Thrusts