Collaborative Research: CyberTraining: Implementation: Small: PowerCyber: Scalable Workforce Development for AI-Enabled Power Grids

The U.S. electric power system is undergoing a rapid transformation driven by inverter-based resources, distributed energy technologies, and emerging artificial intelligence-driven electricity demand. Achieving the scientific and societal benefits of this transformation requires a research workforce that integrates power engineering with advanced cyberinfrastructure, scalable computing, data-driven modeling, and trustworthy artificial intelligence. However, these capabilities remain unevenly distributed across institutions and are not yet systematically embedded in power engineering education. This CyberTraining Implementation project, PowerCyber, addresses this gap by scaling a successful Pilot effort into a national training and community-building program for artificial intelligence-enabled power grid research. The project prepares faculty, postdoctoral researchers, and graduate students to adopt, teach, and extend modern cyberinfrastructure methods through hands-on training, reusable instructional materials, open-source computational environments, and sustained community engagement. By combining a train-the-trainer model with research-ready training pathways, PowerCyber amplifies its impact beyond direct participants and accelerates curriculum adoption across the broader power engineering community. The project strengthens the national cyberinfrastructure workforce, broadens access to advanced computational training, and supports more reproducible, scalable, and trustworthy research for future electric grids. These outcomes will help prepare engineers and researchers to build a cleaner, more reliable, and more resilient energy system. 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.