电工技术学报  2018, Vol. 33 Issue (11): 2479-2485    DOI: 10.19595/j.cnki.1000-6753.tces.170501
电力系统 |
基于多负荷端口戴维南等效的电气化铁路牵引网潮流算法
张俊骐, 吴命利
北京交通大学电气工程学院 北京 100044
Power Flow Algorithm for Electric Railway Traction Network Based on Multiple Load Port Thévenin Equivalence
Zhang Junqi, Wu Mingli
School of Electrical Engineering Beijing Jiaotong University Beijing 100044 China
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摘要 在电气化铁路牵引网的节点电压方程组中,所有的节点电压都是待求的未知量。牵引网中通常有大量的横向并联元件和附加导线,这会使方程组的规模变得非常大,耗费较多的计算时间。该文以交流电气化铁路为例,基于多端口戴维南等效的方法,分别设计了一端口和多端口的潮流算法,降低了迭代方程组的维数,缩短了计算时间,提高了计算效率。通过算例进行了验证,对迭代过程中列车电压的变化和多解现象进行了讨论。
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关键词 电气化铁路牵引网潮流计算多负荷端口戴维南等效潮流多解    
Abstract:All the nodal voltages are the unknowns to be solved in the system of nodal voltage equations of electric railway traction network. There are substantial parallel elements in the network, which makes the dimension of the system of equations high and cost much time to calculate. A power flow Algorithm was designed for one-port and multiple-port AC electric railway network in this paper based on multiple-port Thévenin equivalence. It decreases the dimension of the iterative system of equations, reduces the calculation time, and increases the calculation efficiency. Verification was conducted with an example. It was also discussed in the aspects of the change of the train voltage during the iterations and multiple solutions.
Key wordsElectric railway    traction network    power flow    multiple load port Thévenin equivalence    multiple power flow solutions   
收稿日期: 2017-04-24      出版日期: 2018-06-13
PACS: TM74  
  U223  
基金资助:中央高校基本科研业务费专项资金(2016YJS145)和中国铁路总公司科技研究开发计划重点课题(2016J010-B)资助项目
通讯作者: 吴命利 男,1971年生,教授,博士生导师,研究方向为电气化铁道供电、电能质量和电力系统数字仿真。E-mail:mlwu@bjtu.edu.cn   
作者简介: 张俊骐 男,1991年生,博士研究生,研究方向为电气化铁道供电和电力系统数字仿真。E-mail:14117384@bjtu.edu.cn
引用本文:   
张俊骐, 吴命利. 基于多负荷端口戴维南等效的电气化铁路牵引网潮流算法[J]. 电工技术学报, 2018, 33(11): 2479-2485. Zhang Junqi, Wu Mingli. Power Flow Algorithm for Electric Railway Traction Network Based on Multiple Load Port Thévenin Equivalence. Transactions of China Electrotechnical Society, 2018, 33(11): 2479-2485.
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