This Iowa State University Power Group Seminar is an online seminar only
Abstract: In this talk I will discuss cascading failure analysis and mitigation based on the interaction networks constructed using real utility outage data. We addressed several challenges that are unique for real outage data, including more obvious evolution among generations/stages, high heterogeneity among cascades (both very short and very long cascades occur), and data scarcity. For example, a deep convolutional generative adversarial network (DCGAN) based method is developed to learn the implicit features for failure propagation and recover the missing information due to data scarcity. Further, we identified components that are critical for outage propagation based on the interaction networks, with or without considering spatial propagation, and then developed mitigation strategies to reduce the risk of cascading failure.
Bio: Dr. Junjian Qi received his Ph.D. degree in Electrical Engineering from Tsinghua University, Beijing, China in 2013. He is the Hohbach Endowed Assistant Professor with the Department of Electrical Engineering and Computer Science at South Dakota State University, starting 2023 Fall. His research interests include cascading blackouts, microgrid control, cyber-physical system security, and synchrophasors. Dr. Qi is a Senior Member of IEEE and was the recipient of NSF CAREER award in 2020.
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