Keynotes

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Dawn Tilbury

Biography

Dawn M. Tilbury currently serves as Associate Vice President for Research – Convergence Sciences, and directs the Bold Challenges initiative to bring together teams of faculty with social and technical science expertise to address societal challenges. She received the B.S. degree in Electrical Engineering, summa cum laude, from the University of Minnesota in 1989, and the M.S. and Ph.D. degrees in Electrical Engineering and Computer Sciences from the University of California, Berkeley, in 1992 and 1994, respectively.  In 1995, she

joined the Mechanical Engineering Department at the University of Michigan, Ann Arbor, where she is currently Professor, with a joint appointment as Professor of EECS and is a core member of the Robotics Institute. Her research interests lie broadly in the area of control systems, including applications to robotics and manufacturing systems.  From 2017 to 2021, she was the Assistant Director for Engineering at the National Science Foundation, where she oversaw a federal budget of nearly $1 billion annually, while maintaining her position at the University of Michigan. She has published more than 200 articles in refereed journals and conference proceedings.  She is a Fellow of the IEEE, a Fellow of the ASME, and a Life Member of SWE.

Digital Twins for increased productivity in cyber-physical manufacturing systems
 
Digital Twins are a recent technology that encompass multiple aspects of physical counterparts to help make decisions to improve operation outcomes. Massive amounts data collected on the plant floor can be stored, instead of overwritten every sample time.  This data can be used to build models of expected behavior, based on history.  Real-time streaming can be compared to past data on the same process from the same machine, the same process from a different machine in the same plant, or even a similar process at a different plant.  This talk will discuss some examples of Digital Twins that we have developed for anomaly detection, cyber-security, and predictive maintenance in different manufacturing domains.  Future challenges and opportunities in the area will also be discussed, including the automation of the development and maintenance of digital twins.

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Marija Ilic

Biography

Marija Ilić, is a Professor Emerita at Carnegie Mellon University (CMU). She is currently a Senior Research Scientist at the MIT Laboratory for Information and Decision Systems (LIDS)  at the Massachusetts Institute of Technology (MIT). She is an IEEE Life Fellow and an elected member of the US National Academy of Engineering, and the Academia Europaea.  She was the first recipient of the NSF Presidential Young Investigator Award for Power Systems in the US.  She has co-authored several books on the subject of large-scale electric power systems, and has co-organized an annual multidisciplinary Electricity Industry conference series at

Carnegie Mellon (http://www.ece.cmu.edu/~electriconf) with participants from academia, government, and industry.  She was the founder and co-director of the Electric Energy Systems Group  (EESG) at Carnegie Mellon University (http://www.eesg.ece.cmu.edu).  Currently she is building EESG@MIT, in the same spirit as EESG@CMU. Most recently she has offered an open EdX course at MIT entitled ``Principles of Modeling, Simulations and Control in Electric Energy Systems”.

Modeling and control of multi-energy dynamical systems: Hidden paths to decarbonization
Marija Ilic, MIT ilic@mit.edu

In this talk we first illustrate several examples of microgrids, distribution systems and large-scale bulk power systems comprising diverse distributed energy resources (DERs). We describe fundamental problems with today’s operating and planning practice when attempting to integrate   solar, wind intermittent resources and storage. We illustrate examples from Azores Islands and from continental power grids showing typical delivery and power balancing problems with these new resources. We show how frequency stabilization and regulation can be done by using   distributed storage, such as flywheels (for managing large sudden wind gusts); STATCOMS (for managing short sudden wind gusts), and distributed roof-top PVs, HVACs and EVs. We put forward a Dynamic Monitoring and Decision Systems (DyMonDS) architecture in support of overcoming these problems by means of cyber-physical platform.


Next, we propose that the main challenges in implementing interactive distributed integration of new technologies come from: 1) not having provable performance of system modules (components, subsystems), and 2) lack of physics-based protocols for operating the interconnected system by having confidence that operation would be feasible, stable and robust. To overcome these problems, we first revisit modeling and control used in today’s power systems and identify open R&D problems which must be resolved on the way to decarbonization through digitalization and more interactive distributed approaches.  Second, we present our unified energy modeling for control which is multi-layered. The models of components are technology specific, yet they have the structure which utilizes the concept of interaction variables as a means of both characterizing components and supporting protocols for provable performance. Starting from first principles we show existence of such variables and their interpretation in terms of {stored energy; power; rate of change of power}. These aggregate energy models are relevant for assessing and controlling interaction dynamics and can be verified using only interface measurements, and not requiring technology specific internal knowledge of components design and control.  Notably, this approach can be further generalized to characterize interaction variable for their marginal cost and emissions.  This approach sets the basis for multi-energy multi-disciplinary innovations with clear understanding of potential to do useful work (exergy) and fundamentally waster energy (anergy).  We discuss open questions and future work needed to technology-agnostic exploration of candidate architectures and their performance.

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Karl Johansson

Biography

Karl H. Johansson is Professor with the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology in Sweden and Director of Digital Futures. He received MSc and PhD degrees from Lund University. He has held visiting positions at UC Berkeley, Caltech, NTU, HKUST Institute of Advanced Studies, and NTNU. His research interests are in networked control systems and cyber-physical systems with applications in transportation, energy, and automation networks. He is President of the European Control Association and member of the IFAC Council and has served on the IEEE Control Systems Society Board of Governors and the Swedish Scientific Council for Natural Sciences and Engineering Sciences. He has received several best paper awards and other distinctions from IEEE, IFAC, and ACM. He has been awarded Swedish Research Council Distinguished Professor, Wallenberg Scholar with the Knut and Alice Wallenberg Foundation, Future Research Leader Award from the Swedish Foundation for Strategic Research, the triennialIFAC Young Author Prize, and IEEE Control Systems Society Distinguished Lecturer. He is Fellow of the IEEE and the Royal Swedish Academy of Engineering Sciences.

Proposed Title: Traffic Control using Automated Vehicles: New Opportunities for Distributed Sensing, Actuation, and Learning
 
While the long-term benefits of introducing connected and automated vehicles into road traffic are widely understood to be revolutionary, there is much debate about whether its early stages will cause an increase in congestion and issues related to  human-driven vehicles. Notwithstanding, connected vehicles acting as mobile sensors and actuators could enable traffic predictions and control at a scale never before possible, and thereby a much more efficient and sustainable use of the available road infrastructure and energy resources. In this talk, we will present how new freight transport technology based on automated truck platoons can be the backbone for such a system. Novel system architectures, sensing and communication technologies, optimization and learning algorithms together with extensive experimental evaluations will be discussed. How vehicles platoons can influence traffic flows by acting as a moving bottleneck will be shown together with traffic models suitable for designing traffic control systems. It will be argued that these models are possible to learn automatically from data gathered from vehicles acting as traffic flow sensors. Experiments show that relatively few connected vehicles are enough to mitigate stop-and-go waves and improve traffic conditions significantly.  The presentation will be based mainly on joint work with Miguel Aguiar, Matthieu Barreau and Mladen Cicic.

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Stan Atcitty

Biography
Dr. Stan Atcitty is a member of the Navajo Tribe and he received his BS and MS degree in electrical engineering from New Mexico State University in 1993 and 1995, respectively. In 2006, he was the first American Indian male to receive a Ph.D. in electrical and computer engineering from Virginia Tech University. He is presently a Distinguish Member of Technical Staff at Sandia National Laboratories in the Energy Storage Technology and Systems department. He leads the power electronics subprogram as part of the DOE Energy Storage Program and has gained international recognition for its state-of-the-art research and development under his leadership. Five of his projects have won the prestigious R&D 100 award and one Gold Green Energy award from the Research & Development magazine. His interest in research is power electronics necessary for integrating energy storage and distributed generation with the electric utility

grid.  In addition, President Barack Obama presented Stan with the Presidential Early Career Award for Scientist and Engineers on July 31, 2012. This is the highest honor bestowed by the US government for outstanding scientist and engineers who show exceptional leadership at the frontiers of scientific knowledge during the twenty-first century.

Abstract
Energy storage systems play a vital role in electric utility infrastructure and remote power systems by providing multiple technical and economic benefits such as improved asset utilization, consumer flexibility and cost control, and increased value of variable energy sources such as from photovoltaic and wind energy. The DOE Energy Storage Program leads a worldwide effort in addressing energy issues through energy storage R&D for grid-tied and off-grid systems throughout the United States, including on Native American tribal lands. Power conversion systems (PCS) are a key enabling technology for energy storage. In a grid-tied energy storage system, the PCS controls the power supplied to and absorbed from the grid, simultaneously optimizing energy storage device performance and maintaining grid stability. In addition to energy storage and PCS R&D, the Energy Storage Program is also focused on addressing energy access issues in disadvantage tribal communities and promoting tribal sovereignty. This presentation will provide a background on grid-tied energy storage and power electronics R&D and it show examples of energy storage and power electronic benefits to tribal communities.