Prof.Tao Yang
Speech Title:
Distributed Optimization and Its Application in Smart Grids
Abstract:
Distributed optimization algorithms solve large-scale optimization problems by collaborating among multiple agents. Compared with classical centralized optimization algorithms, distributed optimization algorithms are more flexible and efficient. Distributed optimization algorithms have wide applications in transportation systems, power systems, cyber-physical systems and other fields. This report first reviews and summarizes the existing distributed optimization algorithms. Then, for the optimal coordination of distributed energy sources in smart grids, two distributed optimization algorithms are proposed and their convergence are rigorously proved theoretically. Finally，the theoretical results are validated by the IEEE-39 node system.
Bio of lecturer:
Tao Yang is a Professor at the State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University. He was an Assistant Professor at the Department of Electrical Engineering, University of North Texas, Denton, USA, from 2016-2019. He received 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 then joined the Pacific Northwest National Laboratory as a postdoc, and was promoted to Scientist/Engineer II in 2015.
His research interests include industrial artificial intelligence, integrated optimization and control, distributed control and optimization with applications to process industries, cyber physical systems, and networked control systems. He is an Associate Editor for IEEE Transactions on Control Systems Technology and IEEE Transactions on Neural Networks and Learning Systems.
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