学术报告预告
作者：控制学科 发布日期：2015-07-06 浏览次数：

报告一：

主  题：Queueing Network Modeling and Performance Evaluation of Electric Vehicle Battery Swapping Stations

报告人：谭小琪 博士

地  点：教工之家（广C513）

时  间：7月6日上午09:30-10:15

Abstract
Unlike the conventional internal combustion engine vehicles, of which the gasoline tank typically can be refueled within a matter of minutes, electric vehicles (EVs) have to face the obstacle comes from the nature of recharging: significant amount of charging time with a specific yet expensive recharging equipment. In addition, the shorter range of EVs compared to conventional vehicles necessitates more frequent recharges, which exposes EVs to another deadly drawback, i.e., the battery lifetime problem. Compared to the conventional battery charging service, battery swapping concept decouples the ownership of the battery and the EV, which are known to be with different life cycles. Therefore, battery swapping model has a better potential of taking advantage of future improvements in battery technology by regular battery replacement and recycle.  Meanwhile, this ownership decoupling can significantly lower down the upfront cost of buying an EV, thus may help increase the adoption rates. In this talk, we proposed a queueing network model to serve as a performance evaluation framework for EV battery swapping stations. Our target is to 1) understand the performance of an EV battery swapping station based on realistic queueing network modelling technique; 2) understand the optimal infrastructure construction for an battery swapping station in order to guarantee the quality of service;  3) understand how to operate the battery charging process such that the total operational cost (reward) is minimized (maximized). The whole talk will focus on solving a unified mixed queueing network model, with both analytical analysis and numerical experiment.
 
谭小琪博士简历:

Mr. Tan is currently a PhD. student in the Department of Electronic and Computer Engineering at Hong Kong University of Science and Technology (HKUST). He received his B.E. degree from the Department of Information and Telecommunication Engineering (first class honor), Xi'an Jiaotong University, Xi'an, China, 2012. He is interested in developing analytic techniques and efficient algorithms in stochastic modelling, queueing theory, optimization and control, with current research focusing on applying these models and techniques to the fields of smart grids and power systems. Some of his research results have successfully been published as several papers in some main stream international conferences in the smart grid area. In addition, he has several journal papers currently under the second-round review by top-notched journals include IEEE Transactions on Parallel and Distributed Systems and IEEE Transactions on Smart Grid. He was the co-receipt of the student travel grant of IEEE SmartGridComm 2015. He also received the Energy Technology Concentration Award from the School of Engineering at HKUST for supporting his research in the energy area.  During Oct 2015 and May 2016, supported by the Overseas Research Awards of the School of Engineering, HKUST, Mr. Tan will be visiting Harvard University as a Fellow of the School of Applied Engineering and Science.

报告二：

主  题：Optimal scheduling for EV charging with discrete charging levels in distribution grid

报告人：孙博 博士

地 点：教工之家（广C513）

时 间：7月6日上午10:15-11:00

Abstract
To accommodate increasing electric vehicle (EV) penetration in the distribution grid, the concept of coordinated charging has been extensively explored in the literature. However, most of existing works optimistically consider EV charging rate as a continuous variable and implicitly ignore the capacity limitation in the distribution transformers, which both have great impact on the efficiency and stability of practical grid operation. Towards a more realistic setting, a coordinated EV charging model is proposed, in which the charging rate is restricted to be discrete values and loading on distribution transformers are guaranteed not to exceed their capacities. The coordinated EV discrete charging problem is formulated as two successive binary programs: The former one is designed to achieve a desired aggregate load profile (e.g., valley-filling profile) at the distribution grid level while taking into account the capacity constraint of distribution transformers. Leveraging the properties of separable convex function and total unimodularity, the problem is transformed into an equivalent linear program, which can be solved efficiently and optimally. The latter problem aims to minimize the number of on-off switches of all the EVs' charging profiles while preserving optimality of the former problem. Unfortunately, the second binary problem is proved to be NP-hard. Hence, a heuristic algorithm is designed to approximately achieve our target in an iterative manner.
 
孙博博士研究生简历:

Mr. Sun is currently a Ph.D. candidate in the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology (HKUST). He received his B.Eng. degree in Electronic and Information Engineering from the Honors School of Harbin Institute of Technology (HIT). Mr. Sun has published  been serving as a reviewer of the IEEE International Conference on Communication (ICC), the International Teletraffic Congress (ITC) and the IEEE International Conference on Smart Grid Communication (SmartGridComm). His research interests include stochastic modeling and discrete optimization with their applications to smart grids and power systems. His current research focuses on the design of resource allocation and scheduling algorithms for large-scale energy management system.