Optimal scheduling of electric vehicle charging operations considering real-time traffic condition and travel distance. (1st March 2023)

• Record Type: Journal Article
• Authors: An, Yisheng; Gao, Yuxin; Wu, Naiqi; Zhu, Jiawei; Li, Hongzhang; Yang, Jinhui
• Is Part Of: Expert systems with applications. Volume 213:Part B(2023)
• Publication Date: 2023-03-01
• Subjects: Electric vehicle charging -- Scheduling -- Particle swarm optimization -- Traffic condition; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2022.118941
• Languages: English
• ISSNs: 0957-4174

Abstract

Abstract: As the number of electric vehicles (EVs) increases rapidly, the problem of electric vehicle charging has widely become a concern. Therefore, considering the fact that charging time for one EV cannot be shortened quickly and the number of charging stations will not expand rapidly, how to schedule charging operations of electric vehicles in urban areas becomes a very important issue, since it can improve charging efficiency and relieve charging anxiety of EV users. Up to now, there is no scheduling software tool for practical use in this field. Based on the analysis of electric vehicle charging behavior characteristics, this paper investigates the EV charging problem at the scheduling level. First, a mathematical model for coordinated charging of EVs is proposed to minimize the total charging time for a given number of vehicles. Second, an earliest finish charging scheduling algorithm is presented to solve the charging problem. Then, by considering the combinatorial nature and practical applications with large number of EVs, two practical swarm-optimization-based EV charging scheduling algorithms are proposed. A real-life case study is presented to illustrate the proposed approaches. Highlights: A traffic network model with average velocity as the weight is established. An electric vehicle charging scheduling model is developed. An particle swarm optimization based algorithm for the charging problem. An enhanced algorithm for the large-scale vehicle charging scheduling.