Recent Progress in Privacy Preserving DER Control and Perspectives on Energy Access Challenges

The Distinguished Speaker Webinar Series aims to advance state-of-the-art concepts and methods in artificial intelligence and cyber security. It is jointly hosted by the Center for Cyber Security and AI Research and the School of Electrical Engineering and Computer Science (SEECS) at the University of North Dakota College of Engineering & Mines.

Speaker's Biography: 
Dr. Mingxi Liu is an Associate Professor of Electrical and Computer Engineering at the University of Utah. Before joining University of Utah, he was an NSERC Postdoctoral Fellow with the Energy & Resources Group at UC Berkeley. He received the Ph.D. degree in mechanical engineering from the University of Victoria, Victoria, BC, Canada in 2016. Dr. Liu's broad research interests include control and optimization theories and their applications in power and energy systems, smart grid, and cyber-physical systems.

Dr. Liu is an NSF CAREER awardee, class of 2022. He received the NSERC Postdoctoral Fellowship and NSERC Postgraduate Scholarship-Doctoral from the Natural Sciences and Engineering Research Council of Canada in 2016 and 2014, respectively. He is an Associate Editor of the Advances in Applied Energy, IET Smart Energy Systems and the IEEE Canadian Journal of Electrical and Computer Engineering. He serves on the IEEE CSS Conference Editorial Board.

About the Webinar:
The increasing penetration of renewable energy generation presents significant challenges to power system operation, primarily arising from the uncertainty and intermittency inherent in these energy sources, thereby necessitating enhanced power system flexibility. Distributed energy resources (DERs) have considerable potential to offer this flexibility, but fully realizing their benefits requires addressing three key challenges: scalability, privacy, and cybersecurity. This talk will focus on privacy preservation in distributed DER control, highlighting recent advancements in integrating cryptographic techniques, secret sharing, and state obfuscation into distributed optimization frameworks to safeguard data confidentiality while maintaining algorithm convergence, efficiency, and accuracy. In addition, I will briefly discuss energy access challenges in remote and underserved communities, where limited infrastructure and resource constraints hinder reliable power availability. Insights from our analyses and recent initiatives aimed at addressing these challenges will be presented.