RII Track 4: Probabilistic Dynamic Control Stability Analysis in Power Grids with High Penetration of Renewable Resources

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The legacy power grid is undergoing a radical transformation. Notably, the impact of distributed renewable energy resources is challenging the safe and reliable operation of the power grid and calling for innovative techniques to enhance the reliability and stability in power grids with high penetration of renewable resources. With the support of this NSF EPSCoR RII Tack-4 fellowship, the PI and a Ph.D. student will receive training on new techniques, including novel approaches for modeling the impact of uncertain renewable generation on grid operation and a hardware-in-loop system simulation platform at the National Renewable Energy Laboratory (NREL). The PI and the student will closely collaborate with NREL researchers by focusing on how to better assess grid dynamic stability under uncertain renewable generation. This fellowship will provide an excellent opportunity for a Ph.D. student to gain valuable experience and develop new skillsets. The PI will bring the new techniques back to the home institution, i.e., North Dakota State University (NDSU), and introduce them to other investigators in related fields for the future benefit of NDSU and North Dakota. This fellowship will foster a strong partnership between NDSU and NREL, and help the state of North Dakota better meet its renewable energy goals.The increasing integration of renewable energy resources via power electronic inverters have significantly changed grid dynamics. The dynamic interactions between inverter-based renewable energy resources (IB-RERs) and the power grid have caused the dynamic control stability issue. However, it is challenging to analyze dynamic control stability in power grids with high penetration of IB-RERs, especially considering the impact of variable and uncertain renewable generation. The overarching goal of this fellowship is to support the PI’s training and collaborative research at NREL, focusing on the development and validation of a novel approach for probabilistically assessing dynamic control stability in the power grid with high penetration of IB-RERs. Specific training and research objectives include: 1) modeling the impact of uncertain renewable generation on the dynamic control stability, 2) developing a novel method for probabilistic analysis of dynamic control stability under uncertain renewable generation, and 3) receiving training on advanced hardware-in-loop simulation platforms and performing proof-of-concept validation. This project will expand the PI’s research capacity and transform his career path towards a promising direction in enhancing the dynamic stability of the power grid with large-scale integration of IB-RERs. The results of the research will significantly advance the state-of-the-art of grid stability analysis to better understand the impact of variable and uncertain renewable generation on dynamic control stability, and ultimately support the large-scale renewable integration in power grids, thus providing higher-quality, more reliable, and cleaner electricity to millions of customers across the United States.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.