NSF-funded Machine Learning for Stability Enhancement in Inverter-Dominated Power Systems University of Michigan-Dearborn in United States

NSF-funded research announcement from the University of Michigan-Dearborn in the area of Electrical Engineering and Computer Science.

Assistant Professor Van-Hai Bui announces that his NSF project, “ERI: Scalable Machine Learning Frameworks for Stability Enhancement in Inverter-Dominated Power Systems,” has been awarded for the 2026–2028 period. The project is supported through the NSF Engineering Research Initiation (ERI) program.

The research focuses on modern power systems that increasingly depend on inverter-based resources such as distributed energy generation and battery energy storage systems. These systems are essential for a sustainable energy future, but they also create fast and complex dynamics that make monitoring and control more difficult. The project aims to develop intelligent, data-driven methods that can estimate system behavior in real time and recommend actions to prevent instability.

Research themes include power systems stability, machine learning, inverter-dominated grids, energy storage systems, distributed generation, real-time estimation, and privacy-preserving solutions. The post thanks NSF, collaborators, students, mentors, and the University of Michigan-Dearborn for support.

This is a research funding announcement, not a PhD, postdoc, or master’s application call. No deadline, application portal, or student recruitment details are provided.