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学术报告第201802期

发布时间:2018-01-10 编辑:王腾飞 来源:

报告题目:Demand Response Management in Smart Grid

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

报告时间:2018111日上午1000

报告地点:南一楼中311

 

摘要: Looking at a new energy trading framework based on the repeated game that enables each microgrid to individually and randomly choose a strategy with probability to trade the energy in an independent market so as to maximize his/her average revenue. Also looking at the adaptive learning algorithms to seek the Nash equilibrium (NE) of the constrained energy trading game among individually strategic players with incomplete information. In this game, each player uses the learning automaton scheme to generate the action probability distribution based on his/her private information for maximizing his own averaged utility. It is shown that if one of admissible mixed-strategies converges to the NE with probability one, then the averaged utility and trading quantity almost surely converge to their expected ones, respectively.

 

简介:Dr. Tingwen Huang is Professor of Science at Texas A&M University, USA. He received B.S. degree in mathematics, at Southwest Normal University (now Southwest University) in July 1990, M.S. degree in mathematics, at Sichuan University in July1993, and Ph.D. degree in mathematics, at Texas A&M University, USA in December 2002. He was appointed as Lecturer in 1994 at Jiangsu University, and joined Texas A&M University at Qatar in 2003, and was promoted to a professor.

Professor Tingwen Huang’s research interests include Dynamical Systems, Neural Networks, Complex Networks, Optimization and Control, Traveling Wave Phenomena. He has published more than 200 papers in refereed international journals. Professor Huang serves as President for Asia Pacific Neural Networks Assembly (APNNA) since 2012, a member of program committee for many international conferences, and a very active reviewer for many international journals, and hosts five National Priority Research Project at Qatar. Professor Huang is currently serving as an Associate Editor for IEEE Transactions on Neural Networks and Learning Systems, Cognitive Computation, Journal of Nonlinear Systems and Applications, and so on. He is also the member of American Mathematical Society (AMS), IEEE, and Society for Industrial and Applied Mathematics (SIAM).