This talk discusses how to optimally schedule the charging behaviorof plug-in electric taxies (PET) with time varying electricity price in future smart grid. The story goes in twofold. First, from the perspective of a PET driver the goal is to maximize the profit by choosing proper charging slots. This problem is formulated as a Markov decision process and solved by the proposed threshold method. Then, from the perspective of grid operator the goal is to induce the aggregated charging load of PET fleet to track a given profile. This task is accomplished by introducing an automatic pricing mechanism to adjust the electricity price.
Biography: Zaiyue Yang received his B.S. and M.S. degrees from Department of Automation, University of Science and Technology of China, Hefei, China, in 2001 and 2004, respectively, and Ph.D. degree from Department of Mechanical Engineering, University of Hong Kong, in 2008. Then, he worked as postdoctoral fellow and research associate in Department of Applied Mathematics, Hong Kong Polytechnic University before joining Zhejiang University, Hangzhou, China, in 2010. He is currently a professor there. His current research interests include smart grid, signal processing and control theory. He now severs as the guest editor of IEEE Transactions on Industrial Informatics.