The Institute Awarded Project to Advance AI-Driven Microgrid Resilience

Marcos Quinones Grueiro has received a new award to design, develop, and demonstrate a Hybrid Surrogate-AI Modeling Framework that will enhance the performance and resilience of microgrids operating in isolated, mission-critical environments. The project aims to create a modular simulation platform that integrates AI- and machine learning–based surrogate models with physics-based simulations to enable rapid, adaptive decision-making under uncertainty.

Through this work, the Institute team will advance microgrid technologies that can maintain power availability and stability in the face of disruptions, resource variability, and component degradation. The effort includes developing a domain-specific modeling language (DSML) for intuitive system design, building hybrid simulation modules for flexible benchmarking, implementing continual learning strategies to ensure model adaptability, and deploying the complete framework as a containerized application for Department of Defense environments.

This innovative project represents a significant step toward AI-enabled energy resilience for critical infrastructure systems.