Scheme design and configuration optimization of self-consistency energy systems for rail transit
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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%)。Abstract: To improve the rationality of the construction of self-consistency energy systems for rail transit, the EMU trains on the Beijing-Zhangjiakou Railway were taken as the research objects. According to operating scenarios and line conditions, the topology scheme of a wind-photovoltaic-storage microgrid self-consistency energy system based on the railway power conditioner was determined. Through traction calculation for the longitudinal operation of the EMU trains, the energy flow relationship during train operation was analyzed, and a real-time energy management strategy was designed. Under the premise of reasonable power distribution, with the economical and lightweight wind-photovoltaic-storage self-consistency energy system as optimization objectives, multi-objective optimization technology for the configuration scheme of the self-consistency energy system was studied. Under the conditions of the established line and power constraints, the particle swarm optimization algorithm was used to optimize and calculate control variables of the self-consistency energy system such as the number of photovoltaic cells in series and parallel, the number of storage batteries in series and parallel, and the scale of wind turbines, so as to achieve the optimal configuration scheme of the wind-photovoltaic-storage self-consistency energy system under the given line conditions and objectives. With the actual line conditions of 16 CR400BF trains on the downline of Beijing-Zhangjiakou Railway as an example, the proposed optimized configuration scheme of the wind-photovoltaic-storage self-consistency energy system was verified through MATLAB/Simulink software. Combining the two optimization objectives of the total lifecycle cost of the system (including initial purchasing cost, replacement cost, and electricity purchasing cost) and the total volume of the occupied area, the configurations were optimized by using three different sets of weight coefficients. Analysis results show that with the increase in the weight of the economic objective, the total lifecycle costs of the corresponding optimized configuration schemes reduce by 191.649 million yuan (about 49.1%), 188.258 million yuan (about 48.2%), and 179.911 million yuan (about 46.0%). As the weight of the lightweight objective increases, the total volumes of the optimized self-consistency energy system along the line reduce by 3 377.2 (about 50.4%), 3 393.7 (about 50.6%), and 3 446.9 m3 (about 51.4%). 6 tabs, 15 figs, 31 refs.
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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 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 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 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 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
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 
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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
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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
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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>smin，Pg+PB2=PL PB=PB2，PG=0 5 PL>Pg>0，smin < s < s< smax，Pg+PB2 < PL PB=max{PB1, -Pg} PG=PL 6 PL>Pg>0，s>smax，Pg+PB2 < PL PB=0，PG=PL 7 PL>Pg>0，s>smax，Pg+PB2>PL PB=PL-Pg，PG=0 8 Pg>PL>0，s < smax PB=max{PB, PL-Pg} PG=0 9 Pg>PL>0，s>smax PB=0，PG=0
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表 5 优化变量的范围
Table 5. Scopes of optimized variables
个 变量 取值 mp 7~24 np 1~10 000 mB 86~340 nB 1~625 nw 0~20
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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
108S3389P
154S170P
013S1950P
114S238P
015S1598P
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
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