Physical Anomaly Management in Massively Digitized Power Systems

Dr. Tong Huang


Abstract

The past century has witnessed a digitization trend of electric power grid where increasing digital solutions are being integrated into the grid infrastructure. The digital solutions not only provide opportunities for enhancing monitoring, control and protection of the power grid, but also pose challenges of ensuring both cyber and physical security of the grid. This presentation provides two concrete examples in order to leverage the emerging opportunities and to address pressing challenges in a massively digitized grid. By using rich streaming synchrophasor data in bulk power transmission systems, a purely data-driven algorithm is presented in order to locate sources of forced oscillations. In order to address physical security issues from distributed generation resources and power electronic interfaces in distribution systems, a learning-based framework is designed for assessing physical security of networked microgrids. Furthermore, an advanced energy management system for future digitized power grids is envisioned and thereby future research directions are pointed out.

Speaker Bio

Dr. Tong Huang is a postdoctoral researcher in the Department of Electrical and Computer Engineering at Texas A&M University where he obtained his Ph.D. degree. >From September to December of 2018, he was a visiting Ph.D. student in the Laboratory for Information and Decision Systems (LIDS) at Massachusetts Institute of Technology (MIT). His research interest focuses on designing next-generation energy management systems for power grids with deep renewables by leveraging interpretable AI and power electronics. His industry experience includes an internship at ISO-New England in 2018 and an internship at Mitsubishi Electric Research Laboratories in 2019. He received the Best Paper Award at the 2020 IEEE Power & Energy Society General Meeting, the Best Paper Award at the 54-th Hawaii International Conference on System Sciences, Thomas W. Powell ’62 and Powell Industries Inc. Fellowship, and Texas A&M Graduate Teaching Fellowship.