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The ever-increasing penetration of renewable energy sources into power generation portfolio has posed an immense challenge to the existing power grid. Due to inherent intermittency and uncertainty, it is very difficult to effectively accommodate the large amounts of renewable energy being integrated into the system. Failure to survive from such renewable uncertainties may jeopardize system security, and even cause the system to collapse with catastrophic consequences. Hence, it becomes extremely important to develop solutions that are capable of alleviating related uncertainty-induced issues in a reliable and cost-effective manner. Existing efforts, covering many aspects, can be roughly divided into the following three categories: high-accuracy renewable generation forecasting as well as uncertainty modeling from the renewable station side, improvement on the flexibility of system operations and planning, and intelligent management and control strategies using infrastructural supplements, such as demand response resources, energy storage facilities, Flexible AC Transmission Systems (FACTS), etc. In this session, we focus on the advanced modeling, optimization and control technologies for power systems with high shares of renewable sources, which can be served as a fundamental basis for promoting renewable energy integration and deployment, as well as enhancement on system reliability and economy.
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Yu Huang received his B.S. degree from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2015, and the Ph.D. degree from Southeast University, Nanjing, China, in 2020, both in Electrical Engineering. He is currently an associate professor with the Institute of Carbon Neutrality and Advanced Technology, Nanjing University of Posts and Telecommunications, China. He was a Visiting Research Scholar with Department of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA. As the first/corresponding author, He has published more than 20 SCI/EI indexed journal papers. Dr. Huang served as the technical committee member and session chair of several IEEE/international academic conferences. His research interests include power system operation and optimization, uncertainty quantification and risk analysis of renewable integrated systems.
Chao Deng received his Ph. D. degree in Control Science and Engineering from Northeastern University in 2018. From May 2018 to April 2021, he was a Postdoctoral Fellow at Nanyang Technological University, Singapore. Since June 2021, he has been with the Carbon Neutral Advanced Technology Research Institute of Nanjing University of Posts and Telecommunications, China, where he is currently an Assistant Professor, a Master's Instructor, and a candidate of the National Youth Talent Program. He has published more than 20 papers in IEEE Transactions and IFAC journals including IEEE Transactions on Automatic Control and Automatica as the first author and corresponding author. He is currently the Associate Editor of the Journal of Control and Decision. He was the recipient of the Best Paper Award of the International Conference (ICCAR) in 2022. His research interests include distributed fault-tolerant control, security control of cyber-physical systems, and secondary control of smart microgrid systems.