Electric vehicles charging infrastructure framework using internet of things

被引:0
作者
Mejjaouli, Sobhi [1 ]
Alnourani, Sanabel [1 ]
机构
[1] Alfaisal Univ, Coll Engn, Riyadh, Saudi Arabia
关键词
Electric vehicles; Charging stations; EV charging schedule; Internet of things; SMART;
D O I
10.1016/j.jclepro.2024.144056
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Electric vehicles (EVs) sales have grown rapidly recently, and more growth is expected over the coming years. A challenging problem arises when managing different battery requirements of moving EVs through reliable Charging Stations (CSs). Current concerns for EV users are long waiting lines at CSs and dropping below a predefined battery capacity limit. For this reason, this paper proposes an Internet of Things (IoT)-based EV charging scheduling system, which with the use of IoT technologies, decides the optimal assignment between EVs and Charging Points (CPs) located at different CSs at given time t. By using cloud computing and real time data such as number of EVs, number of CSs, number of CPs at different CSs ... etc; the scheduling controller uses a recursive algorithm to generate all possible scenarios, and then shares the optimal assignment (that minimizes the average waiting time and fulfill battery constraints and charging needs) with all EVs. To test the validity of the IOT based scheduling system, sensitivity analysis by running different scenarios (pertaining to different parameters) was conducted. The different scenarios were compared to a base scenario where the system was not used and real-life random assignment is considered. The different run scenarios show superiority over the base scenario in terms of average waiting time (WT) and battery capacity threshold. For example, in the base scenario, violation of battery capacity threshold occurred 9.1% of the time, making random selection an unreliable choice versus no violations when the IOT scheduling system is used. Also, all tested scenarios under the IOT scheduling system show shorter average WT compared to the base scenario. For instance, scenarios 2 and 3 show more than 35% and 55% decrease in WT compared to the base scenario.
引用
收藏
页数:10
相关论文
共 32 条
[1]  
Abd Eldjalil CD, 2017, IEEE ICC
[2]   Optimal location of electric vehicle charging station and its impact on distribution network: A review [J].
Ahmad, Fareed ;
Iqbal, Atif ;
Ashraf, Imtiaz ;
Marzband, Mousa ;
Khan, Irfan .
ENERGY REPORTS, 2022, 8 :2314-2333
[3]   Optimal scheduling of electric vehicle charging operations considering real-time traffic condition and travel distance [J].
An, Yisheng ;
Gao, Yuxin ;
Wu, Naiqi ;
Zhu, Jiawei ;
Li, Hongzhang ;
Yang, Jinhui .
EXPERT SYSTEMS WITH APPLICATIONS, 2023, 213
[4]  
Balamurugan B, 2019, Internet of Things and Big Data Analytics for Smart Generation, P279, DOI [DOI 10.1007/978-3-030-04203, 10.1007/978-3-030-04203-5_13, DOI 10.1007/978-3-030-04203-5_13]
[5]   An optimal charging scheduling model and algorithm for electric buses [J].
Bao, Zhaoyao ;
Li, Jiapei ;
Bai, Xuehan ;
Xie, Chi ;
Chen, Zhibin ;
Xu, Min ;
Shang, Wen-Long ;
Li, Hailong .
APPLIED ENERGY, 2023, 332
[6]   Achieving sustainable transport through resource scheduling: A case study for electric vehicle charging stations [J].
Gong, D. ;
Tang, M. ;
Liu, S. ;
Xue, G. ;
Wang, L. .
ADVANCES IN PRODUCTION ENGINEERING & MANAGEMENT, 2019, 14 (01) :65-79
[7]   Bidding for Preferred Timing: An Auction Design for Electric Vehicle Charging Station Scheduling [J].
Hou, Luyang ;
Wang, Chun ;
Yan, Jun .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 21 (08) :3332-3343
[8]   A robust coordinated charging scheduling approach for hybrid electric bus charging systems [J].
Huang, Di ;
Zhang, Jinyu ;
Liu, Zhiyuan .
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2023, 125
[9]   Optimization of Waiting Time for Electric Vehicles Using a Fuzzy Inference System [J].
Hussain, Shahid ;
Kim, Yun-Su ;
Thakur, Subhasis ;
Breslin, John G. .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (09) :15396-15407
[10]  
Jawale Sayali Ashok, 2021, 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA), P192, DOI 10.1109/ICIRCA51532.2021.9544651