Parallel Alternating Current Optimal Power Flow-based Multiscale Frequency Stability-Constrained Unit Commitment with Inverter-based Resources

This NSF project aims to develop new optimization methods for operating the electric power grid reliably and economically with a high penetration of inverter-based resources (IBRs). IBRs are rapidly replacing synchronous-generator-based power plants as energy sources. These IBRs introduce new frequency stability challenges because they lack rotational inertia and respond to disturbances differently from synchronous generators, consequently increasing the risk of widespread outages and blackouts during various events. This project will bring transformative change by enabling power system operators to optimize both electricity production and IBR dynamic parameters to ensure that the frequency of future power systems remain stable with high levels of IBR penetration. This will be achieved by developing computational tools that combine advanced dynamic models of IBRs with large-scale optimization algorithms suitable for real-time grid operation. The intellectual merit of the project includes advancing the fundamental understanding of multiscale frequency stability in low-inertia power systems and establishing new analytical methods that integrate dynamic frequency stability directly into power system optimization. The broader impacts of the project include improving the reliability and resilience of the nation’s electric grid, supporting the secure integration of IBRs, reducing operating costs associated with maintaining grid stability, developing open-source software and educational materials, and preparing a broad workforce through graduate education, industry engagement, and outreach activities. The project addresses three fundamental technical challenges: accurately representing the frequency dynamic behavior of IBRs without excessive computational cost of electromagnetic transient simulations, integrating both small-signal and large-disturbance frequency stability into a unified analytical framework, and efficiently optimizing adjustable inverter control parameters together with generation scheduling. The research will develop measurement-informed reduced-order dynamic models for both grid-following and grid-forming IBRs that preserve the dominant frequency-response characteristics while remaining computationally tractable. These models will be combined with analytical stability criteria derived from control theory to transform complex dynamic stability requirements into optimization-compatible constraints. The resulting multiscale frequency stability constraints will be incorporated into a parallel alternating-current optimal power flow-based unit commitment framework that co-optimizes energy production, operating reserves, and IBR control parameters. The proposed methodology will be validated using detailed dynamic simulations and large-scale synthetic power system models, providing a scalable framework for reliable, resilient, and economically efficient operation of future electric grids with high penetrations of IBRs. 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.