报告题目：Several Distributed Optimization Algorithms and Applications

报 告 人：Tingwen Huang教授（Texas A&M University-Qatar）

报告时间：2019年7月26日16:00

报告地点：南一楼中311室

摘要：A class of distributed constrained optimization problems in power systems where the target is to optimize the sum of all agents' local convex objective functions over a general unbalanced directed communication network would be discussed. Also, a game-theory-based distributed charging control method to coordinate large-scale plug-in electric vehicles (PEVs) without compromising the security of the distribution network. Under a noncooperative game framework, a price-driven charging model is designed to minimize the cost of each individual PEV customer while satisfying the network loading constraints. Then, a Newton-type method is developed to find a better Nash equilibrium of the game model at a superlinear convergence rate.

报告人简介:Speaker’s short biography: Tingwen Huang is a professor at Texas A&M University-Qatar. He received his B.S. degree from Southwest Normal University (now Southwest University), China, 1990, his M.S. degree from Sichuan University, China, 1993, and his Ph.D. degree from Texas A&M University, College Station, Texas, 2002. After graduated from Texas A&M University, he worked as a Visiting Assistant Professor there. Then he joined Texas A&M University at Qatar (TAMUQ) as an Assistant Professor in August 2003, then he was promoted to Professor in 2013. His research interests include neural networks based computational intelligence, distributed control and optimization, nonlinear dynamics and applications in smart grids. He has published more than three hundreds peer-review reputable journal papers, including more than one hundred papers in IEEE Transactions. Prof. Tingwen Huang has been elected as IEEE Fellow for contributions to dynamical analysis of neural networks.