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学术报告第201823期

发布时间:2018-05-23 编辑:张惠兰 来源:科研

报告题目:Distributed optimization with application to power systems
报 告 人:Tao Yang

报告时间:2018年5月24日 下午4:00—5:30

报告地点:西十二 S205

报告摘要:

Network system is a fascinating research field that is evolving rapidly across many domains. The goal in networked control of multi-agent systems is to derive desirable collective behavior through distributed control algorithms based on local interaction with neighboring agents.

In this talk, I will share some of my recent work on distributed control and optimization for network systems with applications in power systems. In particular, we consider an optimal coordination problem for distributed energy resources (DERs) including distributed generators and energy storage devices. We first propose an algorithm based on the push-sum and gradient method to optimally coordinate storage devices and distributed generators in a distributed manner. In the proposed algorithm, each DER only maintains a set of variables and updates them through information exchange with a few neighbors over a time-varying directed communication network. We show that the proposed distributed algorithm solves the optimal DER coordination problem if the time-varying directed communication network is uniformly jointly strongly connected, which is a mild condition on the connectivity of communication topologies.

 

报告人简介:

Tao Yang received the B.S. degree in Computer Science from Harbin University of Science and Technology in 2003, the M.S. degree with distinction in control engineering from City University, London in 2004, and the Ph.D. degree in electrical engineering from Washington State University in 2012. Between August 2012 and August 2014, he was an ACCESS Post-Doctoral Researcher with the ACCESS Linnaeus Centre, Royal Institute of Technology, Sweden. He is currently an Assistant Professor at the Department of Electrical Engineering, University of North Texas (UNT). Prior to joining the UNT, he was a Scientist/Engineer II with Energy & Environmental Directorate, Pacific Northwest National Laboratory. His research interests include distributed control and optimization with applications to power systems and transportation systems, Cyber Physical Systems, machine learning, networked control systems, and multi-agent systems.