Regional Electric Bus Scheduling Optimization with Multiple Vehicle Types Considering Opportunity Charging and Travel Time Reliability

被引：0

作者：

Yao, Enjian ^{[1
,2
]}

Wang, Xin ^{[2
]}

Liu, Shasha ^{[1
,2
]}

Yang, Yang ^{[1
,2
]}

Li, Cheng ^{[3
]}

机构：

[1] Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing

[2] School of Traffic and Transportation, Beijing Jiaotong University, Beijing

[3] Key Laboratory of Advanced Public Transportation Science, China Academy of Transportation Sciences, Beijing

来源：

Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2024年 / 24卷 / 04期

基金：

中国国家自然科学基金;

关键词：

adaptive large neighborhood search; electric bus; opportunity charging; regional scheduling; travel time reliability; urban traffic;

D O I：

10.16097/j.cnki.1009-6744.2024.04.015

中图分类号：

学科分类号：

摘要：

In order to improve the operating efficiency and reduce the operating cost of electric bus systems, this paper proposes an electric bus scheduling optimization method that considers opportunity charging and travel time reliability. Firstly, based on the regional scheduling scenario, a strategy of equipping fast-charging piles at the beginning and end stations of the lines and utilizing the succession time for opportunity charging is proposed. Then, considering the stochastic fluctuation of travel time, the reserved travel time characterizing the specific reliability is used as the model input to generate the scheduling scheme, and the departure delay cost is incorporated into the objective function. Considering the overall benefit from the planning to operation stages, a regional multi-model electric bus scheduling optimization model aiming at the minimum total cost was constructed, and an adaptive large-neighborhood search algorithm was designed to solve the model. Finally, four bus lines in the Daxing District of Beijing are taken as examples to verify the effectiveness of the model and the algorithm. The results show that compared with the traditional single-route single-vehicle type scheduling scheme, the optimal scheme based on the proposed method can reduce the daily average cost of bus companies by 37.93%, and the average departure delay time of each vehicle is reduced by 5.63 minutes, which indicates that the proposed method can effectively reduce the cost of enterprises and improve the reliability of public transportation system. Compared with the regional multi-vehicle operation model without considering the opportunity charging strategy and travel time reliability, the optimal scheme in this paper can reduce the total cost by 28.67%. In addition, through the sensitivity analysis, it is suggested that the bus companies should configure the fast-charging resources with 240 kW charging power and prepare the electric bus scheduling scheme with 90% travel time reliability. © 2024 Science Press. All rights reserved.

引用

页码：151 / 165and187

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