报告主题：Optimal Distributed ADMM-Based control for Frequency Synchronization in Isolated AC Microgrids
报 告 人：Prof. Chia-Chi Chu
会议时间：11月25日(周五) 16:00
会议地点：腾讯会议282-506-651
主办单位：重庆大学、输配电装备及系统安全与新技术国家重点实验室、重庆大学溧阳智慧城市研究院
协办单位：四川大学、电子科技大学、西南交通大学、成都理工大学、成都中医药大学、四川师范大学、西华大学、西南科技大学、西南大学、重庆邮电大学、重庆科技学院
Personal Profile:
Chia-Chi Chu received B.S. and M.S. degrees from National Taiwan University, in 1987 and 1989 respectively, and a Ph.D. from Cornell University, in 1996, all in electrical engineering. From 1995 to 1996, he was a member of the Technical Staff at Avant Corporation. From 1996 to 2006, he was а faculty member of electrical engineering at Chang Gung University. He was a visiting scholar at the University of California at Berkeley, and the University of Sydney, Nanyang Technological University in 1999, 2014, and 2019 respectively. Since 2006, he has been a faculty member of electrical engineering at National Tsing Hua University, and is currently a professor. His current research interests include power system stability and microgrid control.
Dr. Chu was the recipient of the Outstanding Research Award from the Ministry of Science and Technology (MOST), in 2020, Outstanding Professor of Electrical Engineering Award from the Chinese Institute of Electrical Engineering, 2021. He is currently a Senior Member of IEEE, director of IEEE Taipei Section, and an Associate Editor for IEEE Trans. On Power Systems, Int. Trans. Electrical Energy Systems, and Int. J. of Electrical Engineering.
Abstract:
To restrict transient dynamics of each distributed generator (DG) in isolated AC micro-grids (MGs), an optimal distributed alternating direction method of multiplier (ADMM)- based control scheme, will be explored for achieving frequency synchronization within a given finite horizon. By introducing the consensus variable, we re-phrase the frequency synchronization problem as a linear quadratic tracking problem under the framework of multi-agent systems. The objective function of each individual DG is defined as the accumulation of quadratic frequency errors and quadratic inputs. Since the consensus variable is also part of the decision variable, more flexibility can be gained in developing the optimal distributed ADMM-based algorithm within a finite horizon. Since the direct extension of ADMM for static optimization cannot be fully distributed, a fully distributed ADMM-based control is developed by exploring the optimal distributed control theory in each DG. To validate the performance of the proposed method, real-time simulations on OPAL-RT are conducted to validate the effectiveness of the proposed optimal distributed ADMM- based control strategy even under large load variations and plug- and-play operations of DGs.
