电动汽车
电池(电)
匹配(统计)
计算机科学
汽车工程
调度(生产过程)
充电站
功率(物理)
季节性
功率流
工程类
电力系统
数学
运营管理
物理
机器学习
统计
量子力学
作者
Xiaohan Liu,Xiaobo Qu,Xiaolei Ma
标识
DOI:10.1016/j.trd.2021.103057
摘要
• Electric bus charging infrastructure and vehicle flow are jointly optimized. • Power matching and seasonality effects on bus battery are considered. • A surrogate-based optimization approach is proposed to solve the model. • An empirical study with bus operational data in Beijing is analyzed. In this research, a novel optimization model for electric bus charging station location, charger configuration, charging time and vehicle flow is developed considering power matching and seasonality. The seasonality highlights the effect of air temperature on the battery performances of electric buses. Power matching between batteries and chargers jointly determines the maximum battery acceptance rates of electric buses, and this consideration results in nonlinear constraints. A surrogate-based optimization approach is proposed to solve the mixed integer nonlinear program efficiently. The optimization model is demonstrated on a sub-transit network including 17 bus lines in Beijing. The results reveal significant performance differences regarding vehicle scheduling and charging among different bus fleets in the BEB-based transit system. The interesting findings on the distribution of vehicle flows for charging provide strong evidence to consider powering match in the bus charging infrastructure layout.
科研通智能强力驱动
Strongly Powered by AbleSci AI