报告人：Prof. Lang Tong
School of Electrical and Computer Engineering Cornell University, Ithaca, NY 14853 USA
Energy Management Systems for Large Scale Charging of Electric Vehicles
The electrification of the transportation system is one of the key components toward a sustainable society. The technology for Electrical Vehicles1 (EVs) has sufficiently advanced that an accelerated adoption of EVs is increasingly likely. Crucial to the transition toward an EV based transportation is establishing a Large Scale Charging (LSC) infrastructure. By LSC we mean charging systems at public parking facilities, work places, and apartment complexes where a large number of EVs are charged simultaneously.
In this talk, we consider the problem of scheduling for LSC systems. We propose a utility optimization formulation and an on-line deadline scheduling algorithm that exploits the available charging capacity and customers flexible schedule. The proposed scheduling algorithm is compared with the optimal off-line algorithm and other benchmark
Lang Tong is the Irwin and Joan Jacobs Professor in Engineering at Cornell University. He received the B.E. degree from Tsinghua University, Beijing,P.R. China, and PhD degree in EE from the University of Notre Dame, Notre Dame. He was a Postdoctoral Research Affiliate at the Information Systems Laboratory, Stanford University.
Lang Tongs research is in the general area of statistical signal processing, communications, and complex networks. He received the 2004 Best Paper Award from the IEEE Signal Processing Society, the 2004 Leonard G. Abraham Prize Paper Award from the IEEE Communications Society, and the 1993 Outstanding Young Author Award from the IEEE Circuits and Systems Society. He is also a coauthor of seven student paper awards including two IEEE Signal Processing Society Young Author Best Paper Awards.