ENGLISH 中财主站 加入收藏
当前位置: 首 页 > 学术科研 > 讲座报告 > 正文

讲座 | 大数据与管理科学系列讲座(第4期)

发布时间:2020-12-02来源: 浏览次数:

讲座题目:Scaling Up Battery Swapping Services in Cities

主讲人:张玉利博士

http://sme.bit.edu.cn/mediaDir/images/content/2018-04/20180424012920380820_1.jpg

主讲人简介:

张玉利博士,北京理工大学管理与经济学院特别研究员、博士生导师。研究兴趣为不确定性环境下的运筹优化、建模分析与算法设计、大数据驱动的运营管理等。主持国家自然科学基金面上项目、青年基金项目等科研项目。在国内外学术期刊发表学术论文三十余篇,其中部分成果以第一作者发表在Production and Operations Management、INFORMSJournal on Computing和Transportation Research Part B:Methodological等学术期刊。担任北京运筹学会副秘书长、中国运筹学会不确定系统分会常务理事,ManagementScience, Operations Research、Production and OperationsManagement等期刊审稿人。

内容简介:

Battery swappingfor electric vehicle refueling is reviving and thriving. Despite a captivatingsustainable future where swapping batteries will be as convenient as refuelinggas today, tensions are mounting in practice (beyond the traditional \range anxiety"issue): On one hand, it is desirable to maximize battery proximity andavailability to customers. On the other hand, it is undesirable to incur toomany batteries which are environmentally detrimental. Additionally, power gridsfor battery charging are not accessible everywhere. To reconcile thesetensions, some cities are embracing an emerging infrastructure network:Decentralized swapping stations replenish charged batteries from centralizedcharging stations. In this paper, we model this new urban infrastructurenetwork. This task is complicated by non-Poisson swaps (observed from realdata), and by the intertwined stochastic operations of swapping, charging,stocking and circulating batteries among swapping and charging stations. Weshow that these complexities can be captured by analytical models. We nextpropose a new location-inventory model for citywide deployment of hub chargingstations, which jointly determines the location, allocation and reorderquantity decisions with a non-convex non-concave objective function. We solvethis problem exactly and efficiently by exploiting the hidden submodularity andcombining constraint-generation and parameter-search techniques. Even forsolving convexified problems, our algorithm brings a speedup of at least threeorders of magnitude relative to Gurobi solver. The major insight is twofold:Centralizing battery charging may harm cost-efficiency and batteryasset-lightness; however, this finding is reversed if foreseeing thatdecentralized charging will have limited access to grids permitting fastcharging. We also identify planning and operational flexibilities brought bycentralized charging. In a broader sense, this work deepens our understandingabout how mobility and energy are coupled in future smart cities.

主持人:陈俊霖副教授,中央财经大学管理科学与工程学院

时间:2020年12月9日(周三)下午14:00-15:30

地点:腾讯会议ID:197 633 925密码:123456

欢迎广大师生参加!