NSF Convergence Accelerator–Track D: AI-Grid: AI-Enabled, Provably Resilient, Programmable Networked Microgrids

Suny At Stony Brook, Stony Brook NY

Investigators

Abstract

Coordinated networked microgrids (NMs) promise to significantly enhance power grid reliability. Three main challenges prevent their wide adoption: 1) Lack of understanding of NM dynamics; 2) Big data but limited/unscalable analytics; 3) Cyber-infrastructure bottlenecks. This project aims to develop AI-Grid: AI-enabled, provably resilient NMs. Key innovations are a programmable platform integrating reliable modeling under uncertainty, reachability analysis, formal control, high-assurance software architectures, and cybersecurity technologies to enable scalable, autonomic, and ultra-resilient microgrids and NMs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.