Project Grant 2606245

Federal Grant Award Summary

This $392,839 Project Grant, awarded by the National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041) and effective August 1, 2026 through July 31, 2029, supports research at Arizona State University to develop advanced analytical and control methods for large-scale nonlinear power systems. The project applies converse Lyapunov theory to create scalable algorithms that improve power grid stability analysis and control by exploiting network structure to reduce computational complexity. Deliverables include theoretical foundations for partially-quadratic Lyapunov functions applicable to networks with numerous states but limited nonlinearities, data-driven methodologies that leverage real-time trajectory measurements to characterize system dynamics, and performance metrics to assess network response to disturbances. These intellectual outputs directly address the fundamental challenge of analyzing and controlling power grids whose generator dynamics are inherently nonlinear and computationally intractable at scale using conventional convex optimization approaches.

The project generates broader impacts through enhanced capability to predict and mitigate power grid failures, strengthening national industrial and commercial infrastructure resilience. By extending model-based and data-based analytical methods from small-scale to large-scale interconnected systems, the research enables grid operators and utilities to apply more precise stability prediction and control algorithms across real-world power networks. Research is conducted through Arizona State University's Office of Research and Sponsored Projects Administration, which serves as the administrative entity for the institution's federal research portfolio.