【講座主題】Sustainable Energy Generation, Intelligent Operation and Maintenance
【講座時間】2025-09-22至2025-09-24
【講座地點】北京龍城溫德姆酒店
【主講人1】Juan Jose Rodriguez-Andina
【主講人簡介】Juan Jose Rodriguez-Andina (Fellow, IEEE) received the M.Sc. degree from the Technical University of Madrid, Spain, in 1990, and the Ph.D. degree from University of Vigo, Spain, in 1996, both in electrical engineering. He is a professor with the Department of Electronic Technology, University of Vigo, and also with the Research Institute of Interdisciplinary Intelligent Science, Ningbo University of Technology. In 2010-2011 he was on sabbatical leave as a Visiting Professor at the ADAC Laboratory, North Carolina State University, Raleigh. His current research interests include the implementation of complex control and processing algorithms and intelligent sensors in embedded platforms. Prof. Rodriguez-Andina has authored over 180 journal and conference articles, and holds several Spanish, European, and US patents. He is co-author of the articles that received the 2023 IEEE Transactions on Industrial Electronics Outstanding Paper Award and the 2017 IEEE Industrial Electronics Magazine Best Paper Award. He received the 2020 Anthony Hornfeck Award from the IEEE Industrial Electronics Society (IES). He is the 2024-2025 IES President-Elect. From 2016 to 2021, he was IES Vice President for Conference Activities. He served as Editor-in-Chief of the IEEE Industrial Electronics Magazine (2013-2015) and as Associate Editor of the IEEE Transactions on Industrial Electronics (2008-2018) and IEEE Transactions on Industrial Informatics (2011-2022). He is currently serving as Co-Editor-in-Chief of the IEEE Transactions on Industrial Electronics and as Associate Editor of the IEEE Open Journal of the Industrial Electronics Society.
【講座內容】From a wide historical perspective, Artificial Intelligence (AI) has been applied in Power Electronics (PE) for decades. For many years, though, it has been confined to specific tasks within the life cycle of PE systems, be it for accelerating some design tasks, optimizing control performance, or ensuring safe operation and fault tolerance, among others. In most cases, it was an auxiliary tool to complement expert PE engineers. However, in today’s world, complexity of PE systems is dramatically growing, their requirements are increasingly demanding and often conflicting, reducing time to market is a must for companies to survive, and, last but not least, there is a shortage of talented electrical engineers in general, and PE engineers in particular, as other professional careers are more attractive for younger generations. In this context, AI is emerging as a powerful solution for the whole PE design cycle, from system- to converter- to PCB- and component-level. This is being made efficiently feasible thanks to the recent and continuous advancements in physics-informed and generative AI. After an introduction addressing these issues, this talk will describe practical cases of AI applications in PE, from classical solutions to new paradigms aiming at autonomous and ethical AI-based PE design.
【主講人2】Qing-Long Han
【主講人簡介】Professor Han is Pro Vice-Chancellor (Research Quality) and a Distinguished Professor at Swinburne University of Technology, Melbourne, Australia. He held various academic and management positions at Griffith University and Central Queensland University, Australia. Professor Han was awarded the 2024 IEEE Dr.-Ing. Eugene Mittelmann Achievement Award, the 2024 Chinese Association of Automation (CAA) Science and Technology Achievement Award, the 2021 Norbert Wiener Award, and the 2021 M. A. Sargent Medal. He was the recipient of the IEEE Systems, Man, and Cybernetics Society Andrew P. Sage Best Transactions Paper Award in 2019, 2020, and 2022, respectively, the IEEE/CAA Journal of Automatica Sinica Norbert Wiener Review Award in 2020, and the IEEE Transactions on Industrial Informatics Outstanding Paper Award in 2020. Professor Han is a Member of the Academia Europaea (The Academy of Europe). He is a Fellow of the International Federation of Automatic Control (FIFAC), a Fellow of the Institute of Electrical and Electronics Engineers (FIEEE), an Honorary Fellow of the Institution of Engineers Australia (HonFIEAust), and a Fellow of the Chinese Association of Automation (FCAA). He is a Highly Cited Researcher in both Engineering and Computer Science (Clarivate). He has served as an AdCom Member of IEEE Industrial Electronics Society (IES), a Member of IEEE IES Fellows Committee, a Member of IEEE IES Publications Committee, Chair of IEEE IES Technical Committee on Network-Based Control Systems and Applications, and the Co-Editor-in-Chief of IEEE Transactions on Industrial Informatics. He is currently the President-Elect, an Executive Board Member, and a Steering Committee Member of Asian Control Association (ACA). He is currently the Editor-in-Chief of IEEE/CAA Journal of Automatica Sinica.
【講座內容】With the widespread integration of renewable distributed energy sources such as wind generation, photovoltaic and solar panels, a traditional electrical network has been experiencing a huge revolution towards a smart grid in various terms of generation, transmission, distribution and usage, and so on. Such a revolution poses new theoretical and technical challenges in operation and management of smart grids. To address these challenges, a multi-agent system-based strategy is developed to address control and optimization issues in smart grids, showcasing its strong ability in improving efficiency, reliability and scalability. In this keynote talk, some backgrounds on smart grids from the perspective of multi-agent systems are introduced. Second, a distributed secondary control scheme with an event-triggered communication mechanism is presented to ensure frequency regulation and active power sharing of AC islanded microgrids while significantly reducing the utilization of communication resources. Third, a multi-objective distributed optimization method is provided to address current sharing and voltage regulation in DC microgrids. Finally, some challenging issues are discussed for future investigation.
【主講人3】Yang Shi
【主講人簡介】Yang Shi received his B.Sc. and Ph.D. degrees in mechanical engineering and automatic control from Northwestern Polytechnical University, Xi'an, China, in 1994 and 1998, respectively, and the Ph.D. degree in electrical and computer engineering from the University of Alberta, Edmonton, AB, Canada, in 2005. He is currently a Professor in the Department of Mechanical Engineering, University of Victoria, Victoria, BC, Canada. His research interests include networked and distributed systems, model predictive control (MPC), cyber-physical systems (CPS), robotics and mechatronics, navigation and control of autonomous systems, and energy system applications. Dr. Shi received the University of Saskatchewan Student Union Teaching Excellence Award in 2007, and the Faculty of Engineering Teaching Excellence Award in 2012 at the University of Victoria, and the 2023 REACH Award for Excellence in Graduate Student Supervision and Mentorship. He is the recipient of the JSPS Invitation Fellowship (short-term) in 2013, the UVic Craigdarroch Silver Medal for Excellence in Research in 2015, the 2017 IEEE Transactions on Fuzzy Systems Outstanding Paper Award, the Humboldt Research Fellowship for Experienced Researchers in 2018; CSME Mechatronics Medal (2023); IEEE Dr.-Ing. Eugene Mittelmann Achievement Award (2023). He is IFAC Council Member; VP on Conference Activities of IEEE IES and the Chair of IEEE IES Technical Committee on Industrial Cyber-Physical Systems. Currently, he is Co-Editor-in-Chief of IEEE Transactions on Industrial Electronics, and Editor-in-Chief of IEEE Canadian Journal of Electrical and Computer Engineering; he also serves as Associate Editor for Automatica, IEEE Transactions on Automatic Control, Annual Review in Controls, etc. He is a Distinguished Lecturer of IES.
【講座內容】Cyber-physical systems (CPS) can be described as smart systems that encompass computational (i.e., hardware and software) and physical components, seamlessly integrated and closely interacting to sense and manipulate the changing state of the real world. Modern smart grid, as a typical CPS, allows plug-in hybrid electric vehicles (PHEVs) to be a promising candidate for grid services. Model predictive control (MPC) is a promising paradigm for high-performance and cost-effective control of complex CPS. In this talk, following the CPS design approach, a novel framework for the local aggregator to estimate the charging status and solve for the charging control signals for PHEVs will be presented. The physical battery charging is executed by charging stalls, where charging information is processed in the embedded system and only the generated index information is transmitted to the aggregator via Internet. An aggregation model is developed for the entire cyberspace to inherently guarantee heterogeneous charging requirements. Furthermore, a nonlinear MPC (NMPC) scheme is introduced for achieving the overnight valley-filling service. Finally, some existing challenges and future research directions will be discussed.
【主講人4】Gerard-Andre Capolino
【主講人簡介】Professor Capolino was born in Marseille (France). He received a BSc in electrical engineering from Ecole Centrale de Marseille, Marseille (France) in 1974, an MSc from CentraleSupelec, Paris, France in 1975, a Ph.D. from Aix-Marseille University, Marseille, France in 1978 and a DSc from Institut National Polytechnique de Grenoble, Grenoble, France in 1987. He held positions at the University of Yaoundé I, Cameroon, the University of Dijon, Dijon, France, and the Mediterranean Institute of Technology, Marseille, France. In 1994, he joined the University of Picardie “Jules Verne” in Amiens, France as a Full Professor, Head of the Department of Electrical Engineering (1995-1998), Director of the Energy Conversion & Intelligent Systems Laboratory (1996-2000) and Director of the European Master in Advanced Power Electrical Engineering (MAPEE) recognized by the European Commission (2004-2021). He was elevated to the rank of Chair Professor in 2013. Since September 2021, he has been appointed Emeritus Professor of Electrical Engineering in the same University and the same research lab. He is the founder of the consulting company GAC Conseils. He has been the recipient of the following distinctions: the IEEE-IES Eugene Mittelman Achievement Award in 2008, the ICEM Arthur Ellison Outstanding Achievement Award in 2010, the IEEE-PELS Diagnostics Achievement Award in 2011, the ICEM John Tegopoulous Outstanding Service Award in 2016, the IEEE-PES Cyril Veinott Electromechanical Conversion Award in 2017 and the IEEE France Section Distinguished Service Award in 2018. More than 30 DLs have been given by him till date worldwide.
【講座內容】 The principle of electrical machines has been known for at least 500 years with the first electrostatic machines invented around 1600. The first electromagnetic machines have been imagined later in the 17th century after the discovery of the electromagnetism principle. However, it has been necessary to wait up to the end of the 19th century to have rotating electrical machines structures close to what they are nowadays. Basically, the presentation starts from classical electrical machines which can be manufactured by using steel, copper and sometime aluminum with other insulating materials and parts which are used for the assembly (case, shaft, bearings, fan and more). Then, the presentation moves towards future trends based on high efficiency AC electrical machines, nano-actuators, very high speeds and very low speeds motors/generators and special electrical machines for embedded systems and emergency applications.