Prof. Anuradha Annaswamy
Dr. Anuradha Annaswamy is Founder and Director of the Active-Adaptive Control Laboratory in the Department of Mechanical Engineering at MIT. Her research interests span adaptive control theory and its applications to aerospace, automotive, and propulsion systems as well as cyber physical systems such as Smart Grids, Smart Cities, and Smart Infrastructures. Her current research team of 15 students and post-docs is supported at present by the US Air-Force Research Laboratory, US Department of Energy, Boeing, Ford-MIT Alliance, and NSF. She has received best paper awards (Axelby; CSM), Distinguished Member and Distinguished Lecturer awards from the IEEE Control Systems Society (CSS) and a PYI award from NSF. She is the author of a graduate textbook on adaptive control, co-editor of two vision documents on smart grids as well as the two editions of the Impact of Control Technology report, and a member of the National Academy of Sciences Committee Study on modernizing the US Electric System. She is a Fellow of IEEE and IFAC. She is currently serving as the President of CSS.
Talk title: Towards Deep Decarbonization and Autonomous Power Grids
Abstract: Significant changes have occurred all over the world even over the past decade in the energy landscape. Globally, there’s a big push towards a 100% incorporation of wind and solar power for electricity production, with synergistic support from various technologies. For example, in the US, natural gas prices have declined, costs of renewable energy technologies have come down, and large-scale battery energy storage technologies have advanced rapidly. There are however a host of challenges, most of which are due to the intermittency and unpredictability of the renewable energy resources. This talk will focus on some of the solutions for the deep integration of these renewable resources for electricity production that are control centric. A distributed optimization approach that judiciously combines renewable generation with storage and flexible loads has the possibility for ensuring power balances while preserving privacy and ensuring security. A distributed control approach that enables a coordinated network of millions of controllers, all integrated with solar and wind power generation nodes, storage sites, and flexible consumption can lead to effective frequency regulation and voltage control in real‐time. A wholistic and grid-wide integration of devices and systems including IoT devices, microgrids, distribution systems, transmission systems, and markets can lead to a power grid that allows deep decarbonization and ensures reliability and resilience. In this talk, some of these challenges, highlights of the current research in distributed optimization and control, and opportunities for future directions will be discussed. Examples of use cases that illustrate the role of systems and control in renewable‐rich power grids will be presented.
Prof. Anna Stefanopoulou
Prof. Anna Stefanopoulou, is the William Clay Ford Professor of Technology and the Director of the Energy Institute at the University of Michigan. Stefanopoulou joined the Department of Mechanical Engineering in 2000 after working at the University of California, Santa Barbara and in the automotive industry, where she developed algorithms and calibrations for highly efficient and advanced powertrains. Stefanopoulou is currently working with a multidisciplinary group to knit automotive and manufacturing expertise with battery and grid experts with the goal to realize a clean, fully integrated, electrified transportation. She is in the fellow rank of three of the largest engineering societies (IEEE, SAE, ASME). Her innovation in powertrain control technology has been recognized by multiple awards and has been documented in a book, 21 US patents, 340 publications (8 of which have received awards) on estimation and control of internal combustion engines and electrochemical processes such as fuel cells and batteries. Stefanopoulou also has co-authored influential reports on the cost-effectiveness of fuel-efficient technologies for light-duty vehicles, sponsored by the National Academies, to help inform policymakers.
Talk title: FAST with Electric Vehicles
Abstract: The most promising pathway for reaching Flexible, Affordable, and Sustainable Transportation (FAST) is through Electric Vehicles (EVs). By eliminating tailpipe carbon dioxide emissions as well as conventional air pollutants such as nitrogen oxides and particulate matter, EVs take advantage of cleaner electric power generation while minimizing direct, street-level exposures to unhealthy air. No other option has comparable emission reduction potential or as promising a pathway to slow down the damage automobiles and other modes of transportation cause to our planet. This plenary will highlight the critical estimation and optimization technologies needed across the whole spectrum of scale from battery prognostics, to investment analysis, and community-driven policies needed to accelerate the adoption of EVs.
Prof. Giuseppe Notarstefano
Dr. Giuseppe Notarstefano is a Professor in the Department of Electrical, Electronic, and Information Engineering G. Marconi at Alma Mater Studiorum Università di Bologna. He was Associate Professor (June ‘16 – June ‘18) and previously Assistant Professor, Ricercatore, (from Feb ‘07) at the Università del Salento, Lecce, Italy. He received the Laurea degree “summa cum laude” in Electronics Engineering from the Università di Pisa in 2003 and the Ph.D. degree in Automation and Operation Research from the Università di Padova in 2007. He has been visiting scholar at the University of Stuttgart, University of California Santa Barbara and University of Colorado Boulder. His research interests include distributed optimization, cooperative control in complex networks, applied nonlinear optimal control, and trajectory optimization and maneuvering of aerial and car vehicles. He serves as an Associate Editor for IEEE Transactions on Automatic Control, IEEE Transactions on Control Systems Technology and IEEE Control Systems Letters. He has been part of the Conference Editorial Board of IEEE Control Systems Society and EUCA. He is recipient of an ERC Starting Grant 2014.
Talk title: Distributed optimal control in complex multi-robot and energy networks
Abstract: Optimal control theory aims at designing action policies that drive a dynamical system while optimizing a performance index. When dealing with large-scale, complex dynamical systems this task becomes even more challenging and calls for methodological approaches that scale with the number of subsystems. Moreover, the interconnected components of modern complex systems are often spatially-distributed and equipped with embedded computing units. This gives rise to novel computing architectures in which the optimal control problem can be solved in a distributed way to gain in both scalability and privacy. Cooperative robotics and smart energy systems are two domains offering a rich variety of challenging optimal control set-ups that can benefit from scalable, distributed solvers. In this talk I will introduce some interesting classes of optimal control problems arising from controls and robotics as, in particular, in multi-robot and energy networks. I will identify the main challenges that need to be addressed in solving these problems in a distributed context, and present novel distributed methods and numerical tools with their application to the presented domains.