**报告题目****：**Distributed optimization with application to power systems

**报 告 人：**杨涛 助理教授（北德州大学）

**报告时间****：**2017年7月3日9：00

**报告地点****：**南一楼中311

**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 the first part of this talk, we consider the global optimal consensus problem for discrete-time multi-agent systems with bounded control protocols over fixed undirected communication networks. Each agent is described by a discrete-time single integrator and endowed with a quadratic objective function, which is private to itself. For each agent, we develop two bounded distributed protocols: bounded proportional-integral (PI) protocol and bounded integral (I) protocol, based on the information received from its neighboring agents through the communication network and the gradient of its own objective function. We show that the proposed bounded distributed protocols with properly chosen parameters solve the global optimal consensus problem if the communication network is connected, i.e., the multi-agent system achieves consensus at a state that minimizes the sum of the objective functions of all agents.

In the second part of this talk, we focus on power system application. 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.

**个人简介：**

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 (KTH), 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 the Energy & Environmental Directorate, Pacific Northwest National Laboratory. His research interests include distributed control and optimization in power systems, Cyber Physical Systems, networked control systems, and multi-agent systems.