基于再生制动能量利用的高速列车时刻表优化

Q4 Engineering
Xin GE, Yuzhao ZHANG, Zhipeng HUANG
{"title":"基于再生制动能量利用的高速列车时刻表优化","authors":"Xin GE, Yuzhao ZHANG, Zhipeng HUANG","doi":"10.3724/sp.j.1249.2023.05539","DOIUrl":null,"url":null,"abstract":"Abstract: Multiple units train generates a large amount of regenerative braking energy during braking, which can be used by traction trains in the same power supply zone. Making full use of this regenerative energy is of great practical significance for green transportation on high-speed rail. In this study, we construct an integer programming model with the goal of maximizing the utilization of the regenerative braking energy in the timetable. We solve the model by using the Gurobi solver under the consideration of the constraints such as the safe running interval of multiple trains and the connection of electric multiple unit trains (EMUs). Finally, we test the validity of the model by an example. The results show that the optimized train schedule has 49. 3% utilization rate of regenerative braking energy, saving 14 967. 622 kW‧h of traction energy consumption, indicating significant energy-saving effects. Through the compara⁃ tive analysis with the simulated annealing algorithm, we conclude that the Gurobi solver is better in terms of accuracy and efficiency. The proposed method can provide a reference for operating departments to formulate the energysaving timetables.","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of high-speed train timetable based on regenerative braking energy utilization\",\"authors\":\"Xin GE, Yuzhao ZHANG, Zhipeng HUANG\",\"doi\":\"10.3724/sp.j.1249.2023.05539\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract: Multiple units train generates a large amount of regenerative braking energy during braking, which can be used by traction trains in the same power supply zone. Making full use of this regenerative energy is of great practical significance for green transportation on high-speed rail. In this study, we construct an integer programming model with the goal of maximizing the utilization of the regenerative braking energy in the timetable. We solve the model by using the Gurobi solver under the consideration of the constraints such as the safe running interval of multiple trains and the connection of electric multiple unit trains (EMUs). Finally, we test the validity of the model by an example. The results show that the optimized train schedule has 49. 3% utilization rate of regenerative braking energy, saving 14 967. 622 kW‧h of traction energy consumption, indicating significant energy-saving effects. Through the compara⁃ tive analysis with the simulated annealing algorithm, we conclude that the Gurobi solver is better in terms of accuracy and efficiency. The proposed method can provide a reference for operating departments to formulate the energysaving timetables.\",\"PeriodicalId\":35396,\"journal\":{\"name\":\"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3724/sp.j.1249.2023.05539\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3724/sp.j.1249.2023.05539","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0

摘要

本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of high-speed train timetable based on regenerative braking energy utilization
Abstract: Multiple units train generates a large amount of regenerative braking energy during braking, which can be used by traction trains in the same power supply zone. Making full use of this regenerative energy is of great practical significance for green transportation on high-speed rail. In this study, we construct an integer programming model with the goal of maximizing the utilization of the regenerative braking energy in the timetable. We solve the model by using the Gurobi solver under the consideration of the constraints such as the safe running interval of multiple trains and the connection of electric multiple unit trains (EMUs). Finally, we test the validity of the model by an example. The results show that the optimized train schedule has 49. 3% utilization rate of regenerative braking energy, saving 14 967. 622 kW‧h of traction energy consumption, indicating significant energy-saving effects. Through the compara⁃ tive analysis with the simulated annealing algorithm, we conclude that the Gurobi solver is better in terms of accuracy and efficiency. The proposed method can provide a reference for operating departments to formulate the energysaving timetables.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
0.90
自引率
0.00%
发文量
14
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信