Abstract: Over the past twenty years power systems and economic theory have merged to co-design market architectures that can competitively price and dispatch in real time generators power, so as to follow the random daily electricity demand. In spite of the many technical advances made, today wind and solar power cannot be easily thrown into the mix of generation resources due to their limited dispatchability and intermittent nature when compared to fuel combustion. What is still lacking are technologies and incentives that would make it possible to use opportunistically abundant renewable energy, without compromising reliability. Responsive and controllable consumption could be used to compensate for the volatility introduced by intermittent resources on the generation side. This would require harnessing the flexibility of large population of responsive appliances and electrical vehicles, connected in an Internet of things that is the grid to respond to their real service needs.
This talk will discuss ongoing research on modeling electrical load demand that can both aid the direct management of these loads as well as facilitate the integration of deferrable loads at the planning stage of the optimal power flow dispatch. We specifically focus on Electrical Vehicle charging and indicate how planning and real time decision can use data that come from these dispatchable loads to optimally schedule their charging. We also will indicate paths to extend this to other loads and challenges that lie ahead in the design of scalable and secure architectures for demand side management in the power grid.
Bio: Prof. Anna Scaglione (M.Sc.'95, Ph.D. '99) is currently Professor in Electrical and Computer Engineering at University of California at Davis. She was before a Associate Prof. at Cornell University, Ithaca, NY, where she joined in 2001 as tenure track faculty, after one year in the same role at the University of New Mexico. She is a Fellow of the IEEE since 2011. Dr. Scaglione is the first author of the paper that received the 2000 IEEE Signal Processing Transactions Best Paper Award; she has also received the NSF Career Award in 2002 and she is co-recipient of the Ellersick Best Paper Award (MILCOM 2005) and of the 2013 IEEE Donald G. Fink Prize Paper Award. Her expertise is in the broad area of signal processing for communication systems and networks. Her current research focuses on studying and enabling decentralized signal processing in networks of sensors. She also focuses on sensor systems and networking models for the demand side management and reliable energy delivery.