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关于举办Tingwen Huang教授学术讲座的通知

发布时间:2021年10月19日

各部门、各单位:

应我校邀请,美国Texas A&M University at Qatar (TAMUQ)大学Tingwen Huang教授将于10月20日(周三)14:45-17:00在腾讯会议线上为我校做学术报告,欢迎广大师生参加!报告的具体安排如下:

报告题目:Efficient Computational Approaches and Applications to Some Optimization Problems in Smart Grid

报 告 人:Tingwen Huang教授,IEEE Fellow,欧洲科学院院士

报告时间:2021年10月20日(周三)14:45—17:00

报告地点:腾讯会议(ID 782141810)

摘    要:In a smart grid context, a demand response strategy of electric vehicle charging is modelled by a stochastic game, where a big data analytic framework is proposed for controlling the electric vehicle charging behaviours. We will look at Plug-In Electric Vehicles (PEVs) Charging: Feeder Overload Control problem. Moreover, a two-stage stochastic game theoretical model is proposed for energy trading problem in a multi-energy microgrid system. In these two work, the risk measurement technique, conditional value at risk (CVaR), is harnessed to estimate the overload risk during the peak hour and the overbidding risk while distributed alternating direction method of multipliers (ADMM) is accelerated by Nesterov gradient method to solve two game models. Concerning the privacy, a research branch of reinforcement learning (RL) that dominates distributed learning for years will be presented by making the first attempt to apply RL-based algorithms in the energy trading game among smart microgrids where no information concerning the distribution of payoffs is a priori available and the strategy chosen by each microgrid is private to opponents, even trading partners. To solve this challenge, 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.

报告人简介:Prof. Tingwen Huang's research focuses on dynamics of nonlinear systems including neural networks, complex networks and multi-agent and their applications to smart grids and cybersecurity. He has published papers in these areas. He has been listed annually as the Highly Cited Researcher by Clarivate Analytics, formerly Thomson Reuters since 2018. His research has been supported by Qatar National Research Fund (QNRF) with more than 7 million US dollars. One of his projects was awarded the Best Research Project Award by QNRF in 2015.

He is very actively involving in professional service. He serves/served as the Past-President (2021), President (2020), President-Elect (2019) for Asia Pacific Neural Network Society, as an action editor or associate editor for 8 prestigious journals, as a guest editor for 10 special issues, as general chair for 6 international conferences, as program chair for 3 international conferences. He is the first recipient of Dean’s Fellow for Recognition of Faculty’s Excellence and Achievements awarded by Texas A&M University at Qatar (TAMUQ) in 2014, was bestowed Faculty Research Excellence Award by TAMUQ in 2015, was elected as IEEE Fellow in 2018, conferred Changjiang Chair Professor in 2019 by Ministry of Education of China, was elected as Fellow of Asia-Pacific Artificial Intelligence Association (AAIA), Academician of the International Academy for Systems and Cybernetic Sciences in 2021, and Member of the European Academy of Sciences and Arts very recently.

特此通知

自动化学院

科研处

国际合作与交流处

2021年10月19日


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