This Iowa State University Power Group Seminar is an online seminar only
Title: Time-synchronized State and Topology Estimation in Distribution Grids using Machine Learning
Abstract: Due to increasing penetration of behind-the-meter generation in the form of solar photovoltaic, there is a genuine need to track the states (node voltage phasors) of the distribution system at high speeds. Smart meters, although present in bulk, cannot fulfill this need because of high reporting delays. Distribution phasor measurement units have the necessary speed, but it is cost-prohibitive to place them in bulk. Thus, high-speed distribution system state estimation is challenging. This talk will describe how the use of machine learning can help overcome this challenge by performing time-synchronized state and topology estimation while accounting for the different characteristics of modern distribution systems.
Bio: Anamitra Pal received his Bachelor of Engineering degree in electrical and electronics engineering from Birla Institute of Technology, Mesra, Ranchi (India) in 2008 and his M.S. and Ph.D. degrees in electrical engineering from Virginia Tech, Blacksburg, in 2012 and 2014, respectively. He is now an Assistant Professor in the School of Electrical, Computer, and Energy Engineering at Arizona State University. His research interests include data analytics with a special emphasis on time-synchronized measurements, artificial intelligence (AI)-applications in power systems, and critical infrastructure resilience. Dr. Pal has received the 2018 Young CRITIS Award for his valuable contributions to the field of critical infrastructure protection, the 2019 Outstanding IEEE Young Professional Award from the Phoenix Section, and the 2022 NSF CAREER Award.
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