Keynote Speaker I
Prof. Leyi Wang
IEEE Fellow
Wayne State University, USA
Le Yi Wang received the Ph.D. degree in electrical engineering from McGill University, Montreal, Canada, in 1990. Since 1990, he has been with Wayne State University, Detroit, Michigan, where he is currently a professor in the Department of Electrical and Computer Engineering. His research interests are in the areas of complexity and information, system identification, robust control, H-infinity optimization, time-varying systems, adaptive systems, hybrid and nonlinear systems, information processing and learning, as well as medical, automotive, communications, power systems, and computer applications of control methodologies. He was a keynote speaker in several international conferences. He serves on the IFAC Technical Committee on Modeling, Identification and Signal Processing. He was an Associate Editor of the IEEE Transactions on Automatic Control and several other journals, and an Associate Editor of Journal of Control Theory and Applications. He was a Visiting Faculty at University of Michigan in 1996, a Visiting Faculty Fellow at University of Western Sydney, Australia, in 2009 and 2013, a Visiting Faculty at Vienna University of Technology, Austria, in 2016, an Organizer and Lecturer of the Advanced Study Institute in INSA Bourges and INRIA Lille, France, in 2022 and 2023. He is an Eminent Engineer in Tau Beta Pi, a member of Academy of Scholars at Wayne State University, and a Fellow of IEEE.
Speech Title: Joint Estimation of Continuous States and Discrete Events in Stochastic Hybrid Systems with Applications to Detection of Power System Contingencies
Traditional types of uncertainties in control and estimation of dynamic systems involve modeling errors and measurement noises. However, cyber-physical contingencies in modern power systems involve sudden and random changes in system structures, topologies, or parameters, exemplified by transmission line faults, generation failures, communication uncertainties, system reorganizations, physical and cyber attacks, etc. The interaction between continuous physical dynamic systems and discrete events of stochastic contingencies can be naturally modeled as stochastic hybrid systems. Randomly switching uncertainties interrupt system observability and controllability, and introduce some fundamental technical challenges. In this presentation, we summarize some recent progress on observability, observer design, and event detection for randomly switched linear systems whose subsystems are unobservable. An operator must combine information from different subsystems and sensors, and integrate observer design with stochastic data of the switching process to achieve simultaneously estimation of the system’s continuous states and detection of contingencies. The coordinated design methods for subsystem observers and their organization for estimating both continuous and discrete states will be discussed. Fundamental conditions and limitations, and convergence properties will be summarized. Applications of the new methodology on state estimation and contingency detection of modern power systems will be presented on some common IEEE bus systems.
Keynote Speaker II
Dr. Pierluigi SIANO
Scientific Director of the Smart Grids and Smart Cities Laboratory with the Department of Management & Innovation Systems
University of Salerno, Canada
Pierluigi Siano (12,700+ citations, 55+ H-Index) has an MS in Electronic Engineering and PhD in Information and Electrical Engineering from the University of Salerno, Italy. He is a Professor and Scientific Director of the Smart Grids and Smart Cities Laboratory with the Department of Management & Innovation Systems, University of Salerno. Since 2021 he has been Distinguished Visiting Professor in the Department of Electrical & Electronic Engineering Science, University of Johannesburg. His research activities are centered on demand response, on energy management, on the integration of distributed energy resources in smart grids, on electricity markets and on planning and management of power systems. In these research fields he has co-authored more than 650 articles including more than 370 international journal papers.
Speech Title: Smart Energy Communities for the Energy Transition
Traditional types of uncertainties in control and estimation of dynamic systems involve modeling errors and measurement noises. However, cyber-physical contingencies in modern power systems involve sudden and random changes in system structures, topologies, or parameters, exemplified by transmission line faults, generation failures, communication uncertainties, system reorganizations, physical and cyber attacks, etc. The interaction between continuous physical dynamic systems and discrete events of stochastic contingencies can be naturally modeled as stochastic hybrid systems. Randomly switching uncertainties interrupt system observability and controllability, and introduce some fundamental technical challenges. In this presentation, we summarize some recent progress on observability, observer design, and event detection for randomly switched linear systems whose subsystems are unobservable. An operator must combine information from different subsystems and sensors, and integrate observer design with stochastic data of the switching process to achieve simultaneously estimation of the system’s continuous states and detection of contingencies. The coordinated design methods for subsystem observers and their organization for estimating both continuous and discrete states will be discussed. Fundamental conditions and limitations, and convergence properties will be summarized. Applications of the new methodology on state estimation and contingency detection of modern power systems will be presented on some common IEEE bus systems.