Article(id=1149745455933862158, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1149745442428203486, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1672-6073.2024.04.017, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1675872000000, receivedDateStr=2023-02-09, revisedDate=1711468800000, revisedDateStr=2024-03-27, acceptedDate=null, acceptedDateStr=null, onlineDate=1752050277931, onlineDateStr=2025-07-09, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752050277931, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752050277931, creator=13701087609, updateTime=1752050277931, updator=13701087609, issue=Issue{id=1149745442428203486, tenantId=1146029695717560320, journalId=1146123302524792850, year='2024', volume='37', issue='4', pageStart='1', pageEnd='141', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1752050274711, creator=13701087609, updateTime=1753780137206, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1157001011664605316, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1149745442428203486, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1157001011664605317, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1149745442428203486, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=118, endPage=124, ext={EN=ArticleExt(id=1149745456214880531, articleId=1149745455933862158, tenantId=1146029695717560320, journalId=1146123302524792850, language=EN, title=Simulation and Energy Saving Analysis of Various New Urban Rail Traction Power Supply Systems, columnId=1152669334582243706, journalTitle=Urban Rapid Rail Transit, columnName=Electrical and Mechanical Engineering, runingTitle=null, highlight=null, articleAbstract=

To enhance the energy efficiency of urban rail traction powersupply systems, this study investigated various strategies aimed at reducing energy consumption. An equivalent circuit model of an urban rail transit traction power supply system was initially developed based on traditional power flow calculation methods. This model considered the nonlinear characteristics of traction energy for urban rail vehicles and variations in the equivalent circuit within a multivehicle context. Subsequently, a power flow analysis method was devised utilizing the established equivalent circuit model and node voltages. Finally, using data from Hefei rail transit line 1 and results from multitrain operation simulations, the study analyzed power, voltage, and energy consumption across different traction powersupply configurations: existing systems and three new systems integrating inverter feedback, energy storage, and photovoltaic technologies. The findings indicate significant advantages for the new systems: the system with inverter feedback notably reduces traction substation energy consumption, while the energy storage system effectively reduces peak power demands. Additionally, the system incorporating photovoltaic technology achieves a substantial 24.89% reduction in traction substation energy consumption compared to the existing setup. These results serve as a valuable reference for optimizing energy efficiency and emissions reduction efforts in urban rail transit systems, offering insights into practical strategies for enhancing operational sustainability.

, correspAuthors=Mingliang LIU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Mingliang LIU, Zhongbei TIAN, Hongzhi DONG, Junfeng ZHENG, Dongpo ZHU, Lei CHEN), CN=ArticleExt(id=1149745472492974228, articleId=1149745455933862158, tenantId=1146029695717560320, journalId=1146123302524792850, language=CN, title=多种新型城轨牵引供电系统仿真与节能分析, columnId=1152669334955536763, journalTitle=都市快轨交通, columnName=机电工程, runingTitle=null, highlight=null, articleAbstract=

为降低城轨牵引供电系统中的能源消耗,对多种新型城轨供电系统的节能策略开展研究。首先,基于传统潮流计算求解方法,建立城市轨道交通牵引供电系统的等效电路模型,并考虑城轨车辆牵引能量的非线性特性及多车模型中的等效电路变化。然后,利用等效电路模型以及各节点电压,设计系统的潮流解析方法。最后,结合合肥市轨道交通1号线相关数据,利用多列车运行仿真模拟结果,分析现有牵引供电系统与逆变回馈、储能、光伏3种新型牵引供电系统的牵引变电站功率、电压、能耗等指标。研究结果表明:相比于现有牵引供电系统,具有逆变回馈的牵引供电系统可以显著减小牵引变电所能耗,具有储能系统的牵引供电系统能够有效降低牵引变电所峰值功率,具有光伏系统的牵引供电系统可减小 24.89%的牵引变电站能耗。研究结果以期为提高城市轨道交通的节能减排效率提供参考。

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刘明亮,男,本科,高级工程师,主要从事轨道交通电力系统建设与维护工作,

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刘明亮,男,本科,高级工程师,主要从事轨道交通电力系统建设与维护工作,

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IEEE transactions on industrial electronics, 2018, 65(8): 6751-6761., articleTitle=Brake voltage following control of supercapacitor-based energy storage systems in metro considering train operation state, refAbstract=null)], funds=[Fund(id=1154040206232641602, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149745455933862158, awardId=2023A1515012949, language=CN, fundingSource=广东省自然科学基金(2023A1515012949), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1154040195843351356, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149745455933862158, xref=1, ext=[AuthorCompanyExt(id=1154040195855934268, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149745455933862158, companyId=1154040195843351356, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 Hefei Rail Transit Group Co., Ltd. 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caption=传统牵引供电系统仿真上行列车运行情况(发车间隔 $5\mathrm{\;{min}}$ ), figureFileSmall=J5kL0Xt7le2xq8rAyXuoCw==, figureFileBig=6u7E8PpR4qnXh2Ckijy/EA==, tableContent=null), ArticleFig(id=1154040205330866219, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149745455933862158, language=EN, label=Figure 9, caption=The inverter feedback traction power supply system simulates the uplink operation ( 5 minutes between departures), figureFileSmall=+J0MtaDHRn4AcKzzT8ki2Q==, figureFileBig=AY2I8hYm+ttAKN9i0IxXAQ==, tableContent=null), ArticleFig(id=1154040205418946605, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149745455933862158, language=CN, label=图 9, caption=逆变回馈牵引供电系统仿真上行列车运行情况 (发车间隔 5 min), figureFileSmall=+J0MtaDHRn4AcKzzT8ki2Q==, figureFileBig=AY2I8hYm+ttAKN9i0IxXAQ==, tableContent=null), ArticleFig(id=1154040205498638383, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149745455933862158, language=EN, label=Figure 10, 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articleId=1149745455933862158, language=CN, label=图 11, caption=光伏牵引供电系统仿真上行列车运行情况(发车间隔 5 min), figureFileSmall=sD9SpgwcqgTq/aWCD9Sgqw==, figureFileBig=UZzGUKmgVwTM5h48Mn9qEg==, tableContent=null), ArticleFig(id=1154040205771268150, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149745455933862158, language=EN, label=Table 1, caption=Substation distribution, figureFileSmall=null, figureFileBig=null, tableContent=
变电站序号 距离/m 变电站序号 距离/m
1 0 8 19778.91
2 2 114.62 9 22 491.24
3 4 834.39 10 24 281.70
4 8 346.03 11 25 195.49
5 10 752.91 12 26 872.41
6 13 720.36 13 28 681.64
7 16 128.03 - -
), ArticleFig(id=1154040205867737143, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149745455933862158, language=CN, label=表 1, caption=变电站分布, figureFileSmall=null, figureFileBig=null, tableContent=
变电站序号 距离/m 变电站序号 距离/m
1 0 8 19778.91
2 2 114.62 9 22 491.24
3 4 834.39 10 24 281.70
4 8 346.03 11 25 195.49
5 10 752.91 12 26 872.41
6 13 720.36 13 28 681.64
7 16 128.03 - -
), ArticleFig(id=1154040205968400440, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149745455933862158, language=EN, label=Table 2, caption=Comparison of simulation results of each traction power supply system, figureFileSmall=null, figureFileBig=null, tableContent=
系统 发车 间隔/min 变电站总能耗/ (kW·h) 能耗 减小率1%
现有牵引 5 507.38 基准值
供电系统 7 548.35 基准值
逆变回馈牵引 5 471.57 7.05
供电系统 7 474.92 13.39
储能牵引 5 479.74 5.44
供电系统 7 482.87 11.94
光伏牵引 5 390.11 23.11
供电系统 7 411.85 24.89
), ArticleFig(id=1154040206056480828, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149745455933862158, language=CN, label=表 2, caption=各牵引供电系统仿真结果对比, figureFileSmall=null, figureFileBig=null, tableContent=
系统 发车 间隔/min 变电站总能耗/ (kW·h) 能耗 减小率1%
现有牵引 5 507.38 基准值
供电系统 7 548.35 基准值
逆变回馈牵引 5 471.57 7.05
供电系统 7 474.92 13.39
储能牵引 5 479.74 5.44
供电系统 7 482.87 11.94
光伏牵引 5 390.11 23.11
供电系统 7 411.85 24.89
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多种新型城轨牵引供电系统仿真与节能分析
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刘明亮 1 , 田忠北 2 , 董鸿志 3 , 郑俊锋 1 , 朱东坡 1 , 陈磊 4
都市快轨交通 | 机电工程 2024,37(4): 118-124
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都市快轨交通 | 机电工程 2024, 37(4): 118-124
多种新型城轨牵引供电系统仿真与节能分析
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刘明亮1 , 田忠北2, 董鸿志3, 郑俊锋1, 朱东坡1, 陈磊4
作者信息
  • 1 合肥市轨道交通集团有限公司 合肥 230001
  • 2 伯明翰大学 英国伯明翰 B152TT
  • 3 利物浦大学 英国利物浦 L693BX
  • 4 通控研究院(安徽)有限公司 合肥 230001
  • 刘明亮,男,本科,高级工程师,主要从事轨道交通电力系统建设与维护工作,

Simulation and Energy Saving Analysis of Various New Urban Rail Traction Power Supply Systems
Mingliang LIU1 , Zhongbei TIAN2, Hongzhi DONG3, Junfeng ZHENG1, Dongpo ZHU1, Lei CHEN4
Affiliations
  • 1 Hefei Rail Transit Group Co., Ltd. Hefei 230001
  • 2 University of Birmingham Birmingham B152TT UK
  • 3 University of Liverpool Liverpool L693BX UK
  • 4 Tong Kong Research Institute (Anhui) Co., Ltd. Hefei 230001
doi: 10.3969/j.issn.1672-6073.2024.04.017
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为降低城轨牵引供电系统中的能源消耗,对多种新型城轨供电系统的节能策略开展研究。首先,基于传统潮流计算求解方法,建立城市轨道交通牵引供电系统的等效电路模型,并考虑城轨车辆牵引能量的非线性特性及多车模型中的等效电路变化。然后,利用等效电路模型以及各节点电压,设计系统的潮流解析方法。最后,结合合肥市轨道交通1号线相关数据,利用多列车运行仿真模拟结果,分析现有牵引供电系统与逆变回馈、储能、光伏3种新型牵引供电系统的牵引变电站功率、电压、能耗等指标。研究结果表明:相比于现有牵引供电系统,具有逆变回馈的牵引供电系统可以显著减小牵引变电所能耗,具有储能系统的牵引供电系统能够有效降低牵引变电所峰值功率,具有光伏系统的牵引供电系统可减小 24.89%的牵引变电站能耗。研究结果以期为提高城市轨道交通的节能减排效率提供参考。

城市轨道交通  /  牵引供电系统  /  逆变回馈  /  储能系统  /  光伏系统

To enhance the energy efficiency of urban rail traction powersupply systems, this study investigated various strategies aimed at reducing energy consumption. An equivalent circuit model of an urban rail transit traction power supply system was initially developed based on traditional power flow calculation methods. This model considered the nonlinear characteristics of traction energy for urban rail vehicles and variations in the equivalent circuit within a multivehicle context. Subsequently, a power flow analysis method was devised utilizing the established equivalent circuit model and node voltages. Finally, using data from Hefei rail transit line 1 and results from multitrain operation simulations, the study analyzed power, voltage, and energy consumption across different traction powersupply configurations: existing systems and three new systems integrating inverter feedback, energy storage, and photovoltaic technologies. The findings indicate significant advantages for the new systems: the system with inverter feedback notably reduces traction substation energy consumption, while the energy storage system effectively reduces peak power demands. Additionally, the system incorporating photovoltaic technology achieves a substantial 24.89% reduction in traction substation energy consumption compared to the existing setup. These results serve as a valuable reference for optimizing energy efficiency and emissions reduction efforts in urban rail transit systems, offering insights into practical strategies for enhancing operational sustainability.

urban rail transit  /  traction power supply system  /  inverse feedback  /  energy storage system  /  photovoltaic system
刘明亮, 田忠北, 董鸿志, 郑俊锋, 朱东坡, 陈磊. 多种新型城轨牵引供电系统仿真与节能分析. 都市快轨交通, 2024 , 37 (4) : 118 -124 . DOI: 10.3969/j.issn.1672-6073.2024.04.017
Mingliang LIU, Zhongbei TIAN, Hongzhi DONG, Junfeng ZHENG, Dongpo ZHU, Lei CHEN. Simulation and Energy Saving Analysis of Various New Urban Rail Traction Power Supply Systems[J]. Urban Rapid Rail Transit, 2024 , 37 (4) : 118 -124 . DOI: 10.3969/j.issn.1672-6073.2024.04.017
随着城市发展, 城轨列车运营能耗日益增加。根据对国内外城轨运营单位的相关情况调研, 牵引能耗约占城轨运营总能耗的40%~55% [1 。列车制动停车过程中会产生大量的再生制动能量, 这些能量除了按一定比例(通常为 20%至 80%, 由地铁车辆实际运行密度和实际距离所决定) 被其他相邻区间行驶的列车吸收利用外, 剩余的再生能量以热能的形式被车载制动电阻消耗掉,产生巨大的能源浪费 [ 2 ]
国内外研究表明, 在牵引变电站加装逆变回馈系统或储能系统, 能够提升再生制动能量的利用率, 进而降低城轨列车的电能消耗 [ 3 - 7 ] 。然而逆变回馈系统和储能系统在降低变电站能耗及减少碳排放方面效果受限。随着新能源的发展, 在牵引变电站加装光伏等新能源, 可进一步降低牵引变电站的电能消耗, 但新能源常受到天气等因素影响 [ 8 ] 。目前,对具有储能和新能源的牵引供电系统的研究集中在能量管理 [ 9 ] 及其控制方法的优化 [ 10 ] 方面。而对于具有逆变回馈、储能系统和新能源的牵引供电系统的节能特性, 没有进行深入分析及对比。
基于传统潮流计算求解方法, 本文首先建立了城市轨道交通牵引供电系统的等效电路模型, 并考虑城轨车辆牵引能量的非线性特性及多车模型中的等效电路变化, 给出系统潮流解析步骤; 然后, 基于城市轨道交通多种牵引供电系统的模型特征, 设计针对每种系统的潮流解析方法; 最后, 以合肥市轨道交通 1 号线为基础建立等效模型, 对牵引供电系统及多列车运行进行仿真模拟, 并从功率、电压、能耗等方面将本文提出的牵引供电系统与现有多种牵引供电系统进行了对比分析。
直流牵引供电系统直接通过整流器从交流电网上取电。如 图 1 所示, 现代交流变直流牵引供电系统主要包括交流中压网络、变压器、整流器以及起保护作用的交直流断路器, 最终输出稳定直流供给运行的列车。
牵引供电系统可等效为串联内阻和二极管的电流源, 实现传统牵引变电所的单向导通的整流特性分析。 接触网和钢轨(回流轨)等效为有固定电阻率的电阻, 其阻值大小由长度决定, 即由列车运行位置决定。运行列车被等效为理想功率源, 在某一运行时刻列车的功率为恒定值, 由列车运行状态驾驶策略决定。当列车处于牵引工况时, 列车从接触网吸收功率; 当列车处于惰性工况时, 列车不吸收功率; 当列车处于再生制动工况时,列车向接触网发出功率。
随着电力电子技术和新能源的不断发展, 牵引供电系统的供电方式也得到了创新。逆变回馈的牵引供电系统可以将列车产生的再生制动能量通过接触网回馈至变电站。同时, 搭载储能的牵引供电系统可与变电站协同为列车提供动力, 并在列车产生再生制动能量时吸收相应功率。新能源整合的牵引供电系统首先接受新能源供给, 然后再通过牵引整流机组提供电力。传统牵引变电站的等效电路如 图 2 所示。其中, ${U}_{0}$ 为变电站空载电压, ${R}_{\text{sub }}$ 为变电站等效电阻, ${R}_{1}\text{、}{R}_{2}$${R}_{3}$ 为线路等效电阻。
当牵引供电系统接入逆变回馈、储能、光伏后, 其等效电路变化如 图 3 所示。
图 3(a) 所示为含有逆变回馈的牵引变电站等效电路。当牵引变电站处于整流模式时, 整流二极管工作, 逆变装置为开路状态。当牵引变电站处于逆变模式时, 整流二极管为开路状态,逆变装置工作。 图 3(b) 所示为含有储能的牵引变电站等效电路, 储能系统与变电站并联。 图3(c) 所示为含有光伏的牵引变电站等效电路, 光伏系统与变电站并联。其中, ${\mathrm{R}}_{\mathrm{s}1}$ 表示变电站的等效电源内阻。在此模型中,储能及光伏均被等效为功率源。 在仿真计算中, 储能充电功率规定为正值, 放电功率为负值;列车牵引时功率为正值,制动时功率为负值。
(a)逆变回馈等效电路模型(b)储能等效电路模型(c)光伏等效电路模型
对于逆变牵引变电站等效模型, 由于变电站能量呈非线性特性, 如 图 4 所示, 当其工作在整流模式下, 特性曲线为蓝色曲线, ${U}_{\mathrm{{oc}}}$ 为开路电压。当其工作在逆变回馈模式下,其特性曲线为红色曲线, ${U}_{\text{invert }}$ 为逆变工作状态开启电压。
储能等效模型如 图 5 所示,由等效电阻 $R$ 及电容 $C$ 组成,经过 $\mathrm{{DC}}/\mathrm{{DC}}$ 输出功率。其功率输出为
${U}_{\mathrm{C}}= {U}_{\mathrm{C}0}+ \frac{1}{C}\int {I}_{\mathrm{{SC}}}{dt}$
${U}_{\mathrm{{SC}}}= {U}_{\mathrm{C}}+ {I}_{\mathrm{{SC}}}R $
${U}_{\mathrm{{ESS}}}= \frac{{U}_{\mathrm{{SC}}}{I}_{\mathrm{{SC}}}}{{I}_{\mathrm{{ESS}}}}$
式中, ${U}_{\mathrm{C}}$ 为电感电压; ${U}_{\mathrm{C}0}$ 为电感初始电压; $C$ 为电容; $R$ 为电阻; ${U}_{\mathrm{{SC}}}$ 为超级电容侧电压; ${I}_{\mathrm{{SC}}}$ 为超级电容侧电流; ${U}_{\mathrm{{ESS}}}$ 为牵引侧储能电压; ${I}_{\mathrm{{ESS}}}$ 为牵引侧储能电流。
在此模型中, 储能有 3 种工作模式, 充电、放电及备用状态, 如 图 6 所示。工作模式由其电压决定: 当储能电压 ${U}_{\mathrm{{ESS}}}> {U}_{\mathrm{{oc}}}$ 时,储能充电; 当储能电压 ${U}_{\mathrm{{ESS}}}<$ ${U}_{\text{thre }}$ 时,储能放电; 当储能电压 ${U}_{\mathrm{{oc}}}> {U}_{\mathrm{{ESS}}}> {U}_{\text{thre }}$ 时,储能处于备用状态。其中 ${U}_{\text{thre }}$ 为设定的储能放电电压阈值, 可根据系统需要进行调整。此外, 为延长储能系统使用寿命,系统荷电状态 $\mathrm{{SOC}}$ 需满足 ${\mathrm{{SOC}}}_{\min }\leq \mathrm{{SOC}}\leq$ ${\mathrm{{SOC}}}_{\max },{\mathrm{{SOC}}}_{\min }$${\mathrm{{SOC}}}_{\max }$ 为荷电状态最小及最大值。 其中, ${P}_{\mathrm{{ESS}}\_ \text{dis }}$ 为储能装置放电功率, ${P}_{\mathrm{{ESS}}\_ \text{ch }}$ 为储能装置充电功率。
在本文中,将光伏系统等效模型考虑为功率源 [ 8 ] , 为模拟模型输出特性,设定模型每 ${50}\mathrm{\;s}$ 功率变化一次 (模型出力情况由一组随机数进行模拟, 在仿真时段内模型功率满足 $\left\lbrack {0,{2.5}\mathrm{{MW}}}\right\rbrack$ ),每个牵引变电站均安装 ${0.25}\mathrm{{MW}}$ 的光伏发电系统。光伏仅在所在牵引变电站供电时(即变电站电压低于空载电压时), 对牵引系统进行供能。
基于新型多车牵引供电等效模型及传统潮流解析方法, 提出各系统潮流解析步骤。在此方法中, 首先根据运行图数据中某一时刻列车运行位置, 把牵引供电网络支路化, 确定各区间电阻值并建立系统导纳矩阵 $\mathrm{Y}$ 。此导纳矩阵具有实矩阵、对称矩阵和稀疏矩阵的特性。
然后, 依据节点电压法, 通过高斯消去法求解式 (4),得到系统各节点电压和牵引变电站工作负荷等。 由于列车被等效为理想功率源模型, 因而在节点电压方程中的输入电流矩阵中包括牵引变电站输入电流值和列车电流。根据式(5)列车运行功率可以求得列车电压电流的函数关系, 假设列车一个初始电压即可得到列车初始电流值, 代入节点电压方程, 可以得到新的列车电压,经过迭代计算即可得出各节点最终电压值。
$\mathbf{V}= {\mathbf{Y}}^{-1}\mathbf{I}$
${P}_{\mathrm{T}}= {P}_{\mathrm{T}}\left( t\right)= {U}_{\mathrm{T}}\left( t\right){I}_{\mathrm{T}}\left( t\right)$
其中,
$\mathbf{V}= \left\lbrack \begin{array}{l}{V}_{1}\\{V}_{2}\\\cdots \\{V}_{n}\end{array}\right\rbrack $
$\mathbf{I}= \left\lbrack \begin{array}{l}{I}_{1}\\{I}_{2}\\\cdots \\{I}_{n}\end{array}\right\rbrack $
$ Y =\\\left\lbrack \begin{matrix}{Y}_{s1}+ {Y}_{1}& -{Y}_{1}& \ldots & 0 & 0 \\- {Y}_{1}& {Y}_{1}+ {Y}_{s2}+ {Y}_{2}& \ldots &\ldots & 0 \\\ldots &\ldots &\ldots &\ldots &\ldots \\ 0 &\ldots &\ldots &{Y}_{n - 2}+ {Y}_{{sn}- 1}+ {Y}_{n - 1}& -{Y}_{n - 1}\\ 0 & 0 &\ldots &- {Y}_{n - 1}& {Y}_{sn}+ {Y}_{n}\end{matrix}\right\rbrack $
${\mathbf{Y}}_{n}= \left\lbrack \begin{matrix}\frac{1}{{R}_{1}}& 0 & 0 \\ 0 &\frac{1}{{R}_{2}}& 0 \\ 0 & 0 &\frac{1}{{R}_{3}}\end{matrix}\right\rbrack $
式中, $\mathbf{V}$ 为节点电压矩阵; $\mathbf{Y}$ 为牵引供电网络电阻 $R$ 的导纳矩阵; $\mathbf{I}$ 为流入节点的电流矩阵; ${P}_{\mathrm{T}}$ 为牵引功率; $t$ 为系统运行时刻; ${U}_{\mathrm{T}}$ 为牵引电压; ${I}_{\mathrm{T}}$ 为牵引电流; $n$ 为节点序号; ${Y}_{\mathrm{s}n}$ 为节点电压; ${\mathbf{Y}}_{n}$ 为每个节点 $n$ 的导纳矩阵。
当变电站处于逆变回馈状态时, 只需根据特性曲线改变模型内阻参数即可。当储能系统工作时, 充电状态的功率通过充电特性曲线改变内阻, 并由潮流解析获得; 放电状态则将电流与牵引变电站电流相加并输出, 随后基于此数据更新各节点电压。当光伏出力时, 电流与牵引变电站电流相加并输出, 随后基于此数据更新各节点电压。
在包含再生制动的直流牵引供电计算过程中, 列车在再生制动工况时, 会产生电流到接触网, 并导致接触网网压升高。列车实际运行时, 如果列车安全电压高于最大安全网压时, 部分再生制动电能会被制动电阻消耗, 以防止由于网压过高造成的危害, 在仿真过程中也需要设置相应的最高安全网压, 而且安全电压的大小影响再生制动能量的利用效率。由于再生制动电能反馈的原因, 部分牵引变电站输出电流会减少, 但是鉴于牵引变电站是单向整流机组, 不能反向传输电流, 因此对于仿真结果需要进一步判断变电站电压是否高于原有变电站最大电压。若变电站电压高于最高安全网压,变电站会自动关闭,不再输出电流。多车仿真器算法结构流程如 图 7 所示。
现有牵引供电系统仿真基于合肥轨道交通 1 号线 (上行线是九联圩站至天水路站, 下行线是天水路站至九联圩站)。线路总长为 ${28681.64}\mathrm{\;m}$ ,接触网单位阻抗为 ${0.147\Omega }/\mathrm{{km}}$ ,变电站阻抗为 ${0.05125}/{0.041\Omega }$ , 直流额定电压为 ${1500}\mathrm{\;V}$ ,直流空载电压为 ${1664}\mathrm{\;V}$ , 最高直流输出电压为 ${1800}\mathrm{\;V}$ 。变电站分布参数如 表 1 所示。
系统中列车为高功率牵引制动模式(功率约 $3\mathrm{{MW}}$ ), 分别考虑发车间隔为 $5\mathrm{\;{min}}$ 的高峰期和发车间隔为 7 min 的平峰期。
在高功率牵引制动模式下, 对高峰期现有牵引供电进行仿真。传统牵引供电系统仿真上行列车运行情况如 图 8 所示。
在高功率牵引制动模式下, 考虑所有变电站安装逆变回馈系统, 列车所产生的再生制动能量将反馈到接触网, 对高峰期牵引供电进行仿真。上行列车运行情况如 图 9 所示。
储能系统工作模式下,放电时以变电站开路电压为放电模式开启电压。接触网上有多余再生制动能量时储能系统即开启充电模式,以保证有充足荷电状态。 其余时刻储能系统均处于备用状态。储能系统基本参数包括: 额定功率为 ${1.5}\mathrm{{MW}}$ ,额定电压为 ${1500}\mathrm{\;V}$ , 最大荷电状态为 0.9,总容量为 ${8.4}\mathrm{{kW}}\cdot \mathrm{h}$ ,最小荷电状态为 0.2 , 荷电状态初始值为 0.5 。
基于高功率牵引制动模式, 考虑系统内每个变电站均配备储能系统, 高峰期对牵引供电进行仿真(储能系统放电工作电压为 ${1633}\mathrm{\;V}$ )。上行列车运行情况如 图 10 所示。
在高功率牵引制动模式下, 考虑所有变电站均安装光伏发电系统(容量为 ${0.25}\mathrm{{MW}}$ ),对高峰期牵引供电进行仿真。在变电站均考虑光伏发电系统时, 上行列车运行情况如 图 11 所示。
以合肥轨道交通 1 号线工作日一天共有 153 趟车次计算,全天列车仿真能耗为 ${80742}\mathrm{\;{kW}}\cdot \mathrm{h}(3\mathrm{{MW}}$ 牵引制动模式),则一年约为 2 947 万 $\mathrm{{kW}}\cdot \mathrm{h}(3\mathrm{{MW}}$ 牵引制动模式)。
表 2 可知, 逆变回馈及储能系统均能降低牵引供电系统的能耗。其中储能系统由于充电状态的限制, 能耗相比逆变回馈要高, 但其可减小牵引变电站峰值功率(储能与变电站同时提供牵引能,从而减小变电站峰值功率)。安装光伏系统的牵引供电系统在减小牵引变电站能耗方面表现最佳,分别在 $5\mathrm{\;{min}}$$7\mathrm{\;{min}}$ 发车间隔下减少 23.11%和 24.89%的能耗。
$3\mathrm{{MW}}$ 牵引制动模式下,具有逆变回馈系统的列车全天能耗为 ${72405}\mathrm{{kW}}\cdot \mathrm{h}$ ,则一年约为 2643 万 $\mathrm{{kW}}\cdot \mathrm{h}$ 。 具有储能系统的列车全天能耗为 ${73569}\mathrm{\;{kW}}\cdot \mathrm{h}$ ,一年约为 2685 万 $\mathrm{{kW}}\cdot \mathrm{h}$ 。具有光伏发电系统列车全天能耗为 ${61350}\mathrm{{kW}}\cdot \mathrm{h}$ ,一年约为 2239 万 $\mathrm{{kW}}\cdot \mathrm{h}$
各牵引系统的仿真潮流求解时间存在差异, 传统牵引供电系统求解时间为 ${23.5}\mathrm{\;s}$ ,逆变回馈牵引供电系统求解时间为 ${29.3}\mathrm{\;s}$ ,储能牵引供电系统求解时间为 ${30.1}\mathrm{\;s}$ ,光伏牵引供电系统求解时间为 ${24.5}\mathrm{\;s}$ 。仿真速度可满足城轨牵引供电系统的仿真与节能分析。
1) 基于传统潮流计算解析方法, 研究了多种新型城轨供电系统的节能策略, 建立了城市轨道交通牵引供电系统等效电路模型。
2) 对新型城轨牵引供电模型多车运行进行了仿真, 仿真结果表明, 与现有牵引供电系统相比, 具有逆变回馈牵引供电系统能够明显减小变电站能耗, 节能最高可达 13.39%; 具有储能系统牵引供电系统能够明显减小变电站峰值功率,节能最高可达 11.94%;安装光伏发电的系统可显著减少牵引变电站功耗, 节能最高可达 24.89%,同时提升了清洁能源的使用比例。
本文主要探究了单一新型牵引系统的案例分析和节能效果, 下一步将重点研究混合式新型牵引供电系统, 包括合理优化牵引供电系统的储能设备参数、明确光伏发电系统的配比及制定相应的协同控制策略等。
  • 广东省自然科学基金(2023A1515012949)
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2024年第37卷第4期
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doi: 10.3969/j.issn.1672-6073.2024.04.017
  • 接收时间:2023-02-09
  • 首发时间:2025-07-09
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  • 收稿日期:2023-02-09
  • 修回日期:2024-03-27
基金
广东省自然科学基金(2023A1515012949)
作者信息
    1 合肥市轨道交通集团有限公司 合肥 230001
    2 伯明翰大学 英国伯明翰 B152TT
    3 利物浦大学 英国利物浦 L693BX
    4 通控研究院(安徽)有限公司 合肥 230001
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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