Stochastic Modeling and Analysis of Public Electric Vehicle Fleet Charging Station Operations

被引：22

作者：

Zhang, Tianyang ^{[1
,2
]}

Chen, Xi ^{[1
]}

Bin Wu ^{[3
]}

Dedeoglu, Mehmet ^{[4
]}

Zhang, Junshan ^{[4
]}

Trajkovic, Ljiljana ^{[5
]}

机构：

[1] GEIRI North Amer, San Jose, CA 95134 USA

[2] Doordash Inc, San Francisco, CA 94103 USA

[3] State Grid Corp China, Beijing 100031, Peoples R China

[4] Arizona State Univ, Sch Elect Comp & Energy Engn, Tempe, AZ 85281 USA

[5] Simon Fraser Univ, Sch Engn Sci, Burnaby, BC V5A 1S6, Canada

来源：

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | 2022年 / 23卷 / 07期

关键词：

Electric vehicle; electric vehicle supply equipment; EV charging networks; public transit; smart grids; LOAD;

D O I：

10.1109/TITS.2021.3099825

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

The electric vehicle (EV) fleet is gradually growing into a major part of public transportation. Proper planning and operation of EV supply equipment (EVSE) is essential to ensure the efficient and economic operations of the EV fleets. Charging stations (CS) have gained market attention due to their lower cost and versatility. Battery swapping stations (BSS) have also received considerable attention because of their promise to provide fast and sustainable battery replacements. However, their commercial viability is unclear due to their requirement for large capital and infrastructure deployment. In this paper, we develop a stochastic model for interactions between CS/BSS and taxi/bus fleets. The model is based on a realistic abstraction of users' behavior defined by various stochastic processes. It also considers the dynamic impacts of the road congestion. Analytical revenue boundaries are derived and verified by simulations. These simulation results may prove valuable for future studies of public transit.

引用

页码：9252 / 9265

页数：14

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