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轨道交通能源自洽系统方案设计与配置优化

徐春梅 张逸飞 刘苏瑶 马欣宁 刁利军

徐春梅, 张逸飞, 刘苏瑶, 马欣宁, 刁利军. 轨道交通能源自洽系统方案设计与配置优化[J]. 交通运输工程学报, 2024, 24(4): 43-55. doi: 10.19818/j.cnki.1671-1637.2024.04.004
引用本文: 徐春梅, 张逸飞, 刘苏瑶, 马欣宁, 刁利军. 轨道交通能源自洽系统方案设计与配置优化[J]. 交通运输工程学报, 2024, 24(4): 43-55. doi: 10.19818/j.cnki.1671-1637.2024.04.004
XU Chun-mei, ZHANG Yi-fei, LIU Su-yao, MA Xin-ning, DIAO Li-jun. Scheme design and configuration optimization of self-consistency energy systems for rail transit[J]. Journal of Traffic and Transportation Engineering, 2024, 24(4): 43-55. doi: 10.19818/j.cnki.1671-1637.2024.04.004
Citation: XU Chun-mei, ZHANG Yi-fei, LIU Su-yao, MA Xin-ning, DIAO Li-jun. Scheme design and configuration optimization of self-consistency energy systems for rail transit[J]. Journal of Traffic and Transportation Engineering, 2024, 24(4): 43-55. doi: 10.19818/j.cnki.1671-1637.2024.04.004

轨道交通能源自洽系统方案设计与配置优化

doi: 10.19818/j.cnki.1671-1637.2024.04.004
基金项目: 

国家重点研发计划 2021YFB2601300

详细信息
    作者简介:

    徐春梅(1973-),女,山东潍坊人,北京交通大学副教授,工学博士,从事轨道交通能源融合研究

    通讯作者:

    刁利军(1980-),男,广东河源人,北京交通大学教授,工学博士

  • 中图分类号: U223.2

Scheme design and configuration optimization of self-consistency energy systems for rail transit

Funds: 

National Key Research and Development Program of China 2021YFB2601300

More Information
  • 摘要: 为了提高轨道交通能源自洽系统建设的合理性,以京张铁路动车组列车作为研究对象,结合运行场景和线路条件,确定了以铁路功率调节器为基础的风-光-储微网能源自洽系统的拓扑方案;通过对动车组列车纵向运行的牵引计算,分析了列车运行时的能量流动关系,设计了实时能量管理策略;在满足功率合理分配的前提下,以风-光-储能源自洽系统的经济性和轻量化作为优化目标,研究了能源自洽系统配置方案的多目标优化技术;在既定线路与电源约束等条件下,采用粒子群优化算法对能源自洽系统的光伏电池串并联数量、储能电池串并联数量以及风力发电机规模等控制变量进行寻优计算,实现在既定线路条件与目标下的风-光-储能源自洽系统最佳配置方案;以京张铁路下行线路中16组CR400BF型列车的实际线路条件为例,通过MATLAB/Simulink软件对风-光-储能源自洽系统配置优化方案进行验证,综合系统全生命周期总成本(包括初始购置成本、更换成本和购电成本)和占地总体积这2个优化目标,采用3组不同的权重系数进行方案配置优化。分析结果表明:随着经济性目标权重的提高,对应优化配置方案的全生命周期总成本分别降低19 164.9万元(约49.1%)、18 825.8万元(约48.2%)、17 991.1万元(约46.0%);随着轻量化权重的提高,优化后的能源自洽系统沿线总体积分别减少3 377.2(约50.4%)、3 393.7(约50.6%)、3 446.9 m3(约51.4%)。

     

  • 图  1  轨道交通风-光-储能源自洽系统拓扑

    Figure  1.  Topology of wind-photovoltaic-storage self-consistency energy system for rail transit

    图  2  风机运行区域划分

    Figure  2.  Division of wind turbine operating areas

    图  3  蓄电池等效电路模型

    Figure  3.  Equivalent circuit model of battery

    图  4  轨道交通能源自洽系统典型日环境条件

    Figure  4.  Typical daily environmental conditions of self-consistency energy system in rail transit

    图  5  光伏发电与风力发电输出功率

    Figure  5.  Output powers of photovoltaic and wind powers

    图  6  G7881次列车功率-时间曲线

    Figure  6.  Power-time curve of train G7881

    图  7  能源自洽系统总负载功率需求

    Figure  7.  Total load power demand of self-consistency energy system

    图  8  典型工况能量流动

    Figure  8.  Energy flows under typical working conditions

    图  9  基于规则的实时能量管理控制策略

    Figure  9.  Rule-based real-time energy management control strategy

    图  10  PSO算法流程

    Figure  10.  Flow of PSO algorithm

    图  11  能源自洽系统配置优化流程

    Figure  11.  Configuration optimization flow of self-consistency energy system

    图  12  方案1的能源自洽系统各部分输出功率

    Figure  12.  Output powers of each part of self-consistency energy system in scheme 1

    图  13  方案1的PSO寻优结果

    Figure  13.  PSO optimization results in scheme 1

    图  14  方案2的能源自洽系统各部分输出功率

    Figure  14.  Output powers of each part of self-consistency energy system in scheme 2

    图  15  方案2的PSO寻优结果

    Figure  15.  PSO optimization results in scheme 2

    图  16  方案3的能源自洽系统各部分输出功率

    Figure  16.  Output powers of each part of self-consistency energy system in scheme 3

    图  17  方案3的PSO寻优结果

    Figure  17.  PSO optimization results in scheme 3

    表  1  能源自洽系统初始配置方案

    Table  1.   Initial configuration scheme of self-consistency energy system

    设备 指标 数值
    风力发电机 单体额定功率/kW 1 000
    配置数量/个 10
    配置容量/kW 10 000
    光伏电池 开路电压/V 40.1
    短路电流/A 9.81
    最大功率点电压/V 32.8
    最大功率点电流/A 9.15
    光伏电池串联数/个 20
    光伏电池并联数/个 2 000
    总额定容量/kW 12 000
    储能电池 单体电压/V 2.35
    单体容量/(A·h) 40
    光伏电池串联数/个 250
    光伏电池并联数/个 250
    下载: 导出CSV

    表  2  牵引供电系统相关变量

    Table  2.   Variables related to traction power supply system

    变量 变量说明 备注
    Pa 左供电臂功率 Pa < 0时左供电臂处于制动状态
    Pa>0时左供电臂处于牵引状态
    Pb 右供电臂功率 Pb < 0时右供电臂处于制动状态
    Pb>0时右供电臂处于牵引状态
    PL 负载总需求功率 PL= Pa + Pb
    PL < 0制动,PL>0牵引
    下载: 导出CSV

    表  3  典型工况分析

    Table  3.   Analysis of typical working conditions

    工况 两供电臂运行情况 工况分析
    1 两臂牵引 左、右侧供电臂都处于牵引工况,Pa>0,Pb>0,有功功率由新能源发电系统、储能系统提供
    2 两臂制动 左、右侧供电臂都处于制动工况,Pa < 0,Pb < 0,两侧供电臂产生的再生制动能量由储能装置储存利用,新能源发电也由储能装置储存
    3 一臂牵引,一臂制动(牵引功率大于制动功率) 左、右供电臂一个处于制动工况,一个处于牵引工况,Pa < 0,Pb>0且Pa+Pb>0,此时制动工况侧列车产生的再生制动能量通过交直交变流器流通至牵引工况侧机车直接利用,新能源发电和储能装置也为其提供能量
    4 一臂牵引,一臂制动(牵引功率小于制动功率) 左、右供电臂一个处于制动工况,一个处于牵引工况,Pa < 0,Pb>0且Pa+Pb < 0,此时机车产生的再生制动能量通过交直交变流器流通至牵引工况侧机车利用,多余的能量由储能装置储存利用,新能源发电也由储能装置储存
    下载: 导出CSV

    表  4  瞬时功率分配规则

    Table  4.   Distribution rules of instantaneous power

    控制序号 条件 控制
    1 PL < 0,s < smax PB=max{PB1, PL-Pg} PG=0
    2 PL < 0,s>smax PB=0,PG=0
    3 PL>Pg>0,s < smin PB=max{PB1, -Pg} PG=PL
    4 PL>Pg>0,s>sminPg+PB2=PL PB=PB2PG=0
    5 PL>Pg>0,smin < s < s< smaxPg+PB2 < PL PB=max{PB1, -Pg} PG=PL
    6 PL>Pg>0,s>smaxPg+PB2 < PL PB=0,PG=PL
    7 PL>Pg>0,s>smaxPg+PB2>PL PB=PL-PgPG=0
    8 Pg>PL>0,s < smax PB=max{PB, PL-Pg} PG=0
    9 Pg>PL>0,s>smax PB=0,PG=0
    下载: 导出CSV

    表  5  优化变量的范围

    Table  5.   Scopes of optimized variables  

    变量 取值
    mp 7~24
    np 1~10 000
    mB 86~340
    nB 1~625
    nw 0~20
    下载: 导出CSV

    表  6  能源自洽系统初始配置及优化配置的各目标值

    Table  6.   Target values for initial and optimized configurations of self-consistency energy system

    配置 初始配置 配置方案1 配置方案2 配置方案3
    配置方案 20S2000P
    250S250P
    10
    8S3389P
    154S170P
    0
    13S1950P
    114S238P
    0
    15S1598P
    294S93P
    1
    光伏电池阵列额定容量/kW 12 000.0 8 133.6 7 605.0 7 191.0
    储能电池组额定容量/(kW·h) 5 875.0 2 460.9 2 550.4 2 570.2
    风力机额定容量/kW 10 000 0 0 1 000
    初始购置成本/万元 19 630.0 5 801.8 5 822.8 6 528.6
    更换成本/万元 19 426.0 12 295.0 12 618.0 12 645.0
    购电成本/万元 0.0 1 794.3 1 789.4 1 891.3
    总成本/万元 39 056.0 19 891.1 20 230.2 21 064.9
    系统总体积/m3 6 702.7 3 325.5 3 309.0 3 255.8
    下载: 导出CSV
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出版历程
  • 收稿日期:  2024-01-28
  • 网络出版日期:  2024-09-26
  • 刊出日期:  2024-08-28

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