Power control strategy of railway hybrid energy storage system based on YNd transformer-multiport converter

doi:10.19799/j.cnki.2095-4239.2024.0551

Abstract

Abstract:

To enhance the utilization of substantial regenerative braking energy generated by electric locomotives and address voltage unbalance issues caused by single-phase traction power supply systems in the grid, this paper proposes a YNd-multiport based railway hybrid energy storage system (YNd-MC-RHESS). The operational principles and modes of the YNd-MC-RHESS are first analyzed. A power optimization control strategy for the multiport converter is then developed with the primary goal of maximizing regenerative braking energy utilization. This strategy integrates nonlinear current control to enhance the converter's response time and improve the energy allocation efficiency within the hybrid storage system. Finally, the proposed control strategy is validated using Hardware-in-the-Loop (HIL) dynamic simulations under typical operational scenarios, demonstrating its capability to dynamically manage power transfers between different ports and ensure equitable energy allocation and release across various storage media. Experimental results reveal that, following the deployment of the hybrid storage system, the utilization rate of regenerative braking energy reaches 93.67%, thereby achieving efficient use of this valuable energy resource.

Key words: traction power supply system, regenerative braking energy, hybrid energy storage, passive control

CLC Number:

U 223

Zhijie LI, Zhongyou LUO, Dongliang NAN, Junyi TANG. Power control strategy of railway hybrid energy storage system based on YNd transformer-multiport converter[J]. Energy Storage Science and Technology, 2024, 13(11): 4030-4039.

Figures/Tables 9

Fig.1

Fig.2

Fig.3

Fig.4

Table 1

Fig.5

Fig.6

Fig.7

Fig.8

References 15

1	陈民武, 陈垠宇, 徐烈, 等. 基于机会约束的贯通式同相牵引供电系统分布式优化运行策略[J/OL]. 中国电机工程学报, 1-11[2024-07-24]. http://kns.cnki.net/kcms/detail/11.2107.TM. 20240402. 1436. 022.html.
	CHEN M W, CHEN Y Y, XU L, et al. Distributed optimal operation of continuous co-phase traction power system via chance-constraint[J/OL]. Proceedings of the CSEE, 1-11[2024-07-24]. http://kns.cnki.net/kcms/detail/11.2107.TM.20240402.1436.022.html.
2	陈垠宇, 陈民武, 李东阳, 等. 计及牵引负荷不确定性的同相供电系统随机优化运行策略[J]. 中国铁道科学, 2023, 44(5): 191-200. DOI: 10.13335/j.1000-3673.pst.2017.0383.
	CHEN Y Y, CHEN M W, LI D Y, et al. Stochastic optimal operation strategy of co-phase power supply system considering uncertainty of traction load[J]. China Railway Science, 2023, 44(5): 191-200. DOI: 10.13335/j.1000-3673.pst.2017.0383.
3	罗忠游, 赵普志, 段玉, 等. 电气化铁路接入风电汇集地区电网的负序优化补偿策略研究[J]. 电力系统保护与控制, 2023, 51(19): 124-134. DOI: 10.19783/j.cnki.pspc.230179.
	LUO Z Y, ZHAO P Z, DUAN Y, et al. A negative sequence optimization compensation strategy for an electrified railway connected to wind power integration areas[J]. Power System Protection and Control, 2023, 51(19): 124-134. DOI: 10.19783/j.cnki.pspc.230179.
4	HE X Q, SHU Z L, PENG X, et al. Advanced cophase traction power supply system based on three-phase to single-phase converter[J]. IEEE Transactions on Power Electronics, 2014, 29(10): 5323-5333. DOI: 10.1109/TPEL.2013.2292612.
5	董志杰, 杨振龙, 马志远, 等. 牵引供电系统贯通供电方案研究[J]. 电气化铁道, 2022, 33(6): 9-14. DOI: 10.19587/j.cnki.1007-936x.2022.06.002.
	DONG Z J, YANG Z L, MA Z Y, et al. Study on through power supply scheme for traction power supply system[J]. Electric Railway, 2022, 33(6): 9-14. DOI: 10.19587/j.cnki.1007-936x. 2022.06.002.
6	LI Z M, LI X Q, WEI Y D, et al. Ground fault analysis and grounding method of static power converters in flexible AC traction power supply systems[J]. IEEE Transactions on Power Electronics, 2022, 37(5): 5535-5546. DOI: 10.1109/TPEL. 2021. 3125739.
7	CHEN M W, CHENG Z, LIU Y L, et al. Multitime-scale optimal dispatch of railway FTPSS based on model predictive control[J]. IEEE Transactions on Transportation Electrification, 2020, 6(2): 808-820. DOI: 10.1109/TTE.2020.2992693.
8	罗忠游, 赵普志, 段玉, 等. 基于超级电容型MMC系统的电铁负序补偿控制策略[J]. 机车电传动, 2023(4): 98-106. DOI: 10.13890/j.issn.1000-128X.2023.04.014.
	LUO Z Y, ZHAO P Z, DUAN Y, et al. Negative sequence compensation control strategy for electrified railways with super-capacitor integrated MMC[J]. Electric Drive for Locomotives, 2023(4): 98-106. DOI: 10.13890/j.issn.1000-128X.2023.04.014.
9	李群湛, 王喜军, 黄小红, 等. 电气化铁路飞轮储能技术研究[J]. 中国电机工程学报, 2019, 39(7): 2025-2033. DOI: 10.13334/j.0258-8013.pcsee.180919.
	LI Q Z, WANG X J, HUANG X H, et al. Research on flywheel energy storage technology for electrified railway[J]. Proceedings of the CSEE, 2019, 39(7): 2025-2033. DOI: 10.13334/j.0258-8013.pcsee.180919.
10	张友鹏, 杨宏伟, 赵珊鹏. 超级电容在高速铁路再生制动能量存储中的应用及控制[J]. 储能科学与技术, 2019, 8(6): 1145-1150. DOI: 10.12028/j.issn.2095-4239.2019.0132.
	ZHANG Y P, YANG H W, ZHAO S P. Application and control of super capacitor in high-speed railway regenerative braking energy storage[J]. Energy Storage Science and Technology, 2019, 8(6): 1145-1150. DOI: 10.12028/j.issn.2095-4239. 2019. 0132.
11	赵宏程, 李再华, 赖俊宏, 等. 基于RPC的混合储能接入双流制牵引供电系统协调运行方法[J]. 储能科学与技术, 2023, 12(9): 2862-2870. DOI: 10.19799/j.cnki.2095-4239.2023.0216.
	ZHAO H C, LI Z H, LAI J H, et al. Coordinated operation method of RPC-based hybrid energy storage access dual-mode traction power supply system[J]. Energy Storage Science and Technology, 2023, 12(9): 2862-2870. DOI: 10.19799/j.cnki.2095-4239.2023.0216.
12	董文哲, 杨斯泐, 梁宗佑, 等. 集成混合储能及RPC的牵引供电系统优化运行[J]. 储能科学与技术, 2023, 12(4): 1185-1193. DOI: 10.19799/j.cnki.2095-4239.2022.0664.
	DONG W Z, YANG S L, LIANG Z Y, et al. Research on optimal operation of traction power supply system with integrated hybrid energy storage and RPC[J]. Energy Storage Science and Technology, 2023, 12(4): 1185-1193. DOI: 10.19799/j.cnki.2095-4239.2022.0664.
13	DE LA TORRE S, SÁNCHEZ-RACERO A J, AGUADO J A, et al. Optimal sizing of energy storage for regenerative braking in electric railway systems[J]. IEEE Transactions on Power Systems, 2015, 30(3): 1492-1500. DOI: 10.1109/TPWRS. 2014. 2340911.
14	郭一帆, 欧阳森, 张晋铭, 等. 含小水电配电网重要负荷评估及其水光储优化配置方法[J]. 广东电力, 2024, 37(5): 32-42. DOI: 10.3969/j.issn.1007-290X.2024.05.004.
	GUO Y F, OUYANG S, ZHANG J M, et al. Assessment of critical load and optimization configuration method for small hydropower distribution network with integrated hydro-PV-energy storage[J]. Guangdong Electric Power, 2024, 37(5): 32-42. DOI: 10.3969/j.issn.1007-290X.2024.05.004.
15	雷鸣宇, 杨子龙, 王一波, 等. 光/储混合系统中的储能控制技术研究[J]. 电工技术学报, 2016, 31(23): 86-92. DOI: 10.19595/j.cnki. 1000-6753.tces.2016.23.012.
	LEI M Y, YANG Z L, WANG Y B, et al. Study on control technology of energy storage station in photovoltaic/storage system[J]. Transactions of China Electrotechnical Society, 2016, 31(23): 86-92. DOI: 10.19595/j.cnki.1000-6753.tces.2016.23.012.

系统	参数	数值
公共电网	电压等级	110 kV
公共电网	短路容量	750 MVA

变压器	高压匹配变压器额定容量	10 MVA
变压器	牵引匹配变压器额定容量	12 MVA

单相AC/DC变换器	网侧变换器额定容量	3 MVA
单相AC/DC变换器	牵引侧变换器额定容量	12 MVA

混合储能装置	额定容量	6 MWh
混合储能装置	额定充放电功率	3 MW

[1]	Zheng LI, Julong CHEN, Wenlin LI, Yu ZHANG, Jierui YANG, Sizhe CHEN. Optimized operation of hybrid energy storage to enhance the performance of AGC with sloped gravity storage [J]. Energy Storage Science and Technology, 2024, 13(8): 2761-2771.
[2]	Dongze GUO, Jihong ZHANG, Qingyu WANG, Shuai ZHANG. Hybrid energy storage power allocation strategy for smoothing wind power output fluctuations [J]. Energy Storage Science and Technology, 2024, 13(5): 1564-1573.
[3]	Ting HE, Junqiang QIAO, Guodong WU. Curtailed power forecasting based on GRU and operation optimization of electric-hydrogen hybrid energy storage system [J]. Energy Storage Science and Technology, 2024, 13(5): 1731-1740.
[4]	Sha HUANG, Yaxin LI. Analysis of fuel cell hybrid energy storage system based on computer software [J]. Energy Storage Science and Technology, 2024, 13(4): 1350-1352.
[5]	Zhaoxiang TANG, Wantao XU, Hao DENG, Wenjie LU. Optimal operation of urban railway traction power supply system with electric vehicles based on chance-constrained programming [J]. Energy Storage Science and Technology, 2024, 13(2): 526-535.
[6]	Yuanming SONG, Yajie LIU, Guang JIN, Xing ZHOU, Xucheng HUANG. Review of energy management methods for lithium-ion battery/supercapacitor hybrid energy storage systems [J]. Energy Storage Science and Technology, 2024, 13(2): 652-668.
[7]	Shanshan SHI, Kai WANG, Yu ZHANG, Kaiyu ZHANG, Kening ZHANG, Yufei WANG, Yani WANG. Collaborative passivity-based control method for hybrid energy storage systems in urban rail transit [J]. Energy Storage Science and Technology, 2024, 13(11): 4040-4052.
[8]	Xinyou WU. Research on optimal configuration of hybrid energy storage capacity of wind power system [J]. Energy Storage Science and Technology, 2024, 13(10): 3593-3595.
[9]	Hongcheng ZHAO, Zaihua LI, Junhong LAI, Yinyu CHEN, Boqi ZHANG, Kanghua GONG, Yi ZENG. Coordinated operation method of RPC-based hybrid energy storage access dual-mode traction power supply system [J]. Energy Storage Science and Technology, 2023, 12(9): 2862-2870.
[10]	Bin LI, Jilei YE, Yu ZHANG, Shanshan SHI, Haojing WANG, Lili LIU, Mingzhe LI. Microgrid-coordinated control strategy with distributed new energy and electro-mechanical hybrid energy storage [J]. Energy Storage Science and Technology, 2023, 12(5): 1510-1515.
[11]	Xin WU, Wenju SHANG, Zhiyong MA, Wei TENG, Shuang ZHANG, Hairong LUO. Coordinated control method for pumped and flywheel hybrid energy storage system [J]. Energy Storage Science and Technology, 2023, 12(2): 468-476.
[12]	Jie SONG, Linxiao GENG, Yongfu SANG, Rongbin WEN, Peng SUN, Linjuan GONG. Study on primary frequency modulation capacity planning of thermal power unit assisted by hybrid energy storage based on EMD decomposition [J]. Energy Storage Science and Technology, 2023, 12(2): 496-503.
[13]	Zhenbo WEI, Yixin YAO, Wenwen ZHANG, Zihang LUO, Yinjiang LI, Yujie REN. Capacity-based optimal configuration of microgrid hybrid energy-storage system with pumped storage based on CEEMDAN [J]. Energy Storage Science and Technology, 2023, 12(11): 3414-3424.
[14]	Jianmin HAN, Feiyu XUE, Shuangyin LIANG, Tianshu QIAO. Hybrid energy storage system assisted frequency modulation simulation of the coal-fired unit under fuzzy control optimization [J]. Energy Storage Science and Technology, 2022, 11(7): 2188-2196.
[15]	Bin GUO, Jie XING, Fei YAO, Xiaomin JING. Optimal configuration of user-side hybrid energy storage based on bi-level programming model [J]. Energy Storage Science and Technology, 2022, 11(2): 615-622.