An Exponential Cone Programming Approach for Managing Electric Vehicle Charging
何龙老师是乔治华盛顿大学(GWU)商学院副教授。之前在新加坡国立大学任副教授。何龙老师在加州大学伯克利分校获得运筹学博士学位，在香港科技大学获得学士学位。何老师的研究兴趣是关于数据驱动的智慧城市管理问题和供应链管理。他的研究获得了MSOM的Best Paper奖以及TSL的Best Paper奖。
We study the problem of an electric vehicle charging service provider, which faces (1) stochastic arrival of customers with distinctive arrival and departure times, and energy requirements as well as (2) a total electricity cost including demand charges, costs related to the highest per-period electricity used in a finite horizon. We formulate its problem of scheduling vehicle charging to minimize the expected total cost as a stochastic program (SP which can be solved by exponential cone program (ECP) approximations. We show that our ECP approach outperforms the sample average approximation (SAA) and a DRO approach using a semi-definite program (SDP) on numerical instances calibrated to real data. We then show that our ECP continues to perform well considering practical implementation issues, including a data-driven setting and an adaptive charging environment. Finally, based on the ECP solutions, we also discuss managerial insights for both charging service providers and policymakers.