Simulation model advances in vanadium redox flow battery energy storage and monitoring method for state of charge

doi:10.19799/j.cnki.2095-4239.2021.0207

Abstract

Abstract:

As an electrochemical energy storage technology, the all-vanadium redox flow battery (VRB) is the most promising large-scale energy storage technology with long life and low cost due to its high safety and flexible layout. This article summarizes the simulation model of all-VRB energy storage in two types of models, namely, circuit and electrochemical. Circuit models mainly comprise fixed circuit elements that simulate battery loops in series and parallel, while electrochemical mathematical models describe the internal battery parameters. At the same time, this article summarizes commonly used state of charge (SOC) monitoring methods for all-vanadium redox flow batteries, including the basic principles and usage methods of the open-circuit voltage method, current integration method, and Kalman filter algorithm. The SOC monitoring method supplements simulation models to build a complete all-VRB energy storage system.

Key words: vanadium redox flow battery, simulation model, SOC monitoring

CLC Number:

TM 911

Kehuan XIE, Chuanchang LI, Jian CHEN, Longhai YU, zhun TAN, Weihai QIN. Simulation model advances in vanadium redox flow battery energy storage and monitoring method for state of charge[J]. Energy Storage Science and Technology, 2021, 10(6): 2363-2372.

Figures/Tables 10

References 48

1	SHIGEMATSU T. Redox flow battery for energy storage[J]. SEI Technical Review, 2011, 73(7): 13.
2	刘宗浩, 张华民, 高素军, 等. 风场配套用全球最大全钒液流电池储能系统[J]. 储能科学与技术, 2014, 3(1): 71-77.
	LIU Z H, ZHANG H M, GAO S J, et al. The world's largest all-vanadium redox flow battery energy storage system for a wind farm[J]. Energy Storage Science and Technology, 2014, 3(1): 71-77.
3	SHIGEMATSU T. The development and demonstration status of practical flow battery systems[J]. Current Opinion in Electrochemistry, 2019, 18: 55-60.
4	KEAR G, SHAH A A, WALSH F C. Development of the all-vanadium redox flow battery for energy storage: A review of technological, financial and policy aspects[J]. International Journal of Energy Research, 2012, 36(11): 1105-1120.
5	谢聪鑫, 郑琼, 李先锋, 等. 液流电池技术的最新进展[J]. 储能科学与技术, 2017, 6(5): 1050-1057.
	XIE C X, ZHENG Q, LI X F, et al. Current advances in the flow battery technology[J]. Energy Storage Science and Technology, 2017, 6(5): 1050-1057.
6	沈海峰, 朱新坚, 曹弘飞, 等. 全钒液流电池动态建模[J]. 储能科学与技术, 2018, 7(1): 135-140.
	SHEN H F, ZHU X J, CAO H F, et al. Dynamic modeling of all-vanadium flow battery[J]. Energy Storage Science and Technology, 2018, 7(1): 135-140.
7	邵军康, 李鑫, 莫言青, 等. 全钒液流电池建模与流量特性分析[J]. 储能科学与技术, 2020, 9(2): 645-655.
	SHAO J K, LI X, MO Y Q, et al. Analysis of modeling and flow characteristics of vanadium redox flow battery[J]. Energy Storage Science and Technology, 2020, 9(2): 645-655.
8	常志松, 王志强, 袁铁江, 等. 钒液流电池的综合建模研究[J]. 电工电能新技术, 2019, 38(9): 73-80.
	CHANG Z S, WANG Z Q, YUAN T J, et al. Synthetical modeling and analysis of vanadium redox flow battery[J]. Advanced Technology of Electrical Engineering and Energy, 2019, 38(9): 73-80.
9	CHAHWAN J, ABBEY C, JOOS G. VRB modelling for the study of output terminal voltages, internal losses and performance[C]//2007 IEEE Canada Electrical Power Conference, Montreal, QC, Canada. IEEE, 2007: 387-392.
10	ZHANG Y, ZHAO J Y, WANG P, et al. A comprehensive equivalent circuit model of all-vanadium redox flow battery for power system analysis[J]. Journal of Power Sources, 2015, 290: 14-24.
11	MEREI G, ADLER S, MAGNOR D, et al. Multi-physics model for the aging prediction of a vanadium redox flow battery system[J]. Electrochimica Acta, 2015, 174: 945-954.
12	ZHENG Q, LI X F, CHENG Y H, et al. Development and perspective in vanadium flow battery modeling[J]. Applied Energy, 2014, 132: 254-266.
13	LI M H, FUNAKI T, HIKIHARA T. A study of output terminal voltage modeling for redox flow battery based on charge and discharge experiments[C]//2007 Power Conversion Conference-Nagoya, Nagoya, Japan. IEEE, 2007: 221-225.
14	潘建欣. 全钒液流电池的模型研究[D]. 长沙: 中南大学, 2012.
	PAN J X. Modeling research of all vanadium redox flow battery[D]. Changsha: Central South University, 2012.
15	刘敬. 钒液流电池在微网中的应用研究[D]. 北京: 华北电力大学, 2015.
	LIU J. Research on application of vanadium redox flow battery in microgrid[D]. Beijing: North China Electric Power University, 2015.
16	李国杰, 唐志伟, 聂宏展, 等. 钒液流储能电池建模及其平抑风电波动研究[J]. 电力系统保护与控制, 2010, 38(22): 115-119, 125.
	LI G J, TANG Z W, NIE H Z, et al. Modelling and controlling of vanadium redox flow battery to smooth wind power fluctuations[J]. Power System Protection and Control, 2010, 38(22): 115-119, 125.
17	WEI Z B, BHATTARAI A, ZOU C F, et al. Real-time monitoring of capacity loss for vanadium redox flow battery[J]. Journal of Power Sources, 2018, 390: 261-269.
18	WEI Z B, MENG S J, TSENG K J, et al. An adaptive model for vanadium redox flow battery and its application for online peak power estimation[J]. Journal of Power Sources, 2017, 344: 195-207.
19	李蓓, 郭剑波, 陈继忠, 等. 液流储能电池系统支路电流的建模与仿真分析[J]. 中国电机工程学报, 2011, 31(27): 1-7.
	LI B, GUO J B, CHEN J Z, et al. Modelling and simulating of shunt current in redox flow battery[J]. Proceedings of the CSEE, 2011, 31(27): 1-7.
20	安婷. 钒液流电池储能系统在微电网中的应用[D]. 包头: 内蒙古科技大学, 2014.
	AN T. The application of vanadium redox flow battery energy storage system in microgrid[D]. Baotou: Inner Mongolia University of Science & Technology, 2014.
21	BAROTE L, MARINESCU C, GEORGESCU M. VRB modeling for storage in stand-alone wind energy systems[C]//2009 IEEE Bucharest PowerTech, Bucharest, Romania. IEEE, 2009: 1-6.
22	CHAHWAN J A. Vanadium-redox flow and lithium-ion battery modelling and performance in wind energy applications[D]. Montreal: McGill University, 2007.
23	WANG W L, GE B M, BI D Q, et al. Grid-connected wind farm power control using VRB-based energy storage system[C]//2010 IEEE Energy Conversion Congress and Exposition, Atlanta, GA, USA. IEEE, 2010: 3772-3777.
24	付博. 钒液流电池储能系统及其风电场运行的控制策略研究[D]. 重庆: 重庆大学, 2013.
	FU B. Research on control strategies of vanadium redox flow battery energy storages systemand wind farm operation[D]. Chongqing: Chongqing University, 2013.
25	韩永辉. 钒液流电池在风光互补发电系统中的应用研究[D]. 北京: 华北电力大学, 2014.
	HAN Y H. Research on application of VRB in wind solar hybrid power system[D]. Beijing: North China Electric Power University, 2014.
26	迟晓妮, 朱敏刚, 吴秋轩. 基于等效模型的全钒液流电池运行优化控制研究[J]. 储能科学与技术, 2018, 7(3): 530-538.
	CHI X N, ZHU M G, WU Q X. Research on optimal operation control based on the equivalent model of VRFB system[J]. Energy Storage Science and Technology, 2018, 7(3): 530-538.
27	莫言青. MW·h全钒液流电池建模及控制[D]. 合肥: 合肥工业大学, 2019.
	MO Y Q. Modeling and control of MW·h vanadium redox battery system[D]. Hefei: Hefei University of Technology, 2019.
28	周文源, 袁越, 傅质馨, 等. 全钒液流电池电化学建模与充放电分析[J]. 电源技术, 2013, 37(8): 1349-1353, 1363.
	ZHOU W Y, YUAN Y, FU Z X, et al. Electrochemical model of all vanadium redox flow battery and its charge/discharge analysis[J]. Chinese Journal of Power Sources, 2013, 37(8): 1349-1353, 1363.
29	BLANC C, RUFER A. Multiphysics and energetic modeling of a vanadium redox flow battery[C]//2008 IEEE International Conference on Sustainable Energy Technologies, Singapore. IEEE, 2008: 696-701.
30	GU F C, CHEN H C, LI K Y. Mathematic modeling and performance analysis of vanadium redox flow battery[J]. Energy & Fuels, 2020, 34(8): 10142-10147.
31	ONTIVEROS L J, MERCADO P E. Modeling of a vanadium redox flow battery for power system dynamic studies[J]. International Journal of Hydrogen Energy, 2014, 39(16): 8720-8727.
32	洪为臣, 李冰洋, 王保国. 液流电池理论与技术——荷电状态的表征[J]. 储能科学与技术, 2015, 4(5): 493-497.
	HONG W C, LI B Y, WANG B G. Theoretical and technological aspects of flow batteries: Measurement of state of charge[J]. Energy Storage Science and Technology, 2015, 4(5): 493-497.
33	王文红, 王新东. 全钒液流电池荷电状态的分析与监测[J]. 浙江工业大学学报, 2006, 34(2): 119-122.
	WANG W H, WANG X D. Analysis and measurement of SOC in the vanadium flow battery[J]. Journal of Zhejiang University of Technology, 2006, 34(2): 119-122.
34	MOHAMED M R, AHMAD H, ABU SEMAN M N. Estimating the state-of-charge of all-vanadium redox flow battery using a divided, open-circuit potentiometric cell[J]. Electronics and Electrical Engineering, 2013, 19(3): 37-42.
35	WEI Z B, LIM T M, SKYLLAS-KAZACOS M, et al. Online state of charge and model parameter co-estimation based on a novel multi-timescale estimator for vanadium redox flow battery[J]. Applied Energy, 2016, 172: 169-179.
36	XIONG B Y, ZHAO J Y, WEI Z B, et al. Extended Kalman filter method for state of charge estimation of vanadium redox flow battery using thermal-dependent electrical model[J]. Journal of Power Sources, 2014, 262: 50-61.
37	NG K S, MOO C S, CHEN Y P, et al. Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries[J]. Applied Energy, 2009, 86(9): 1506-1511.
38	TANG X D, MAO X F, LIN J, et al. Li-ion battery parameter estimation for state of charge[C]//Proceedings of the 2011 American Control Conference, San Francisco, CA, USA. IEEE, 2011: 941-946.
39	陈宗海, 钟良, 何耀, 等. 基于充电方式的锂电池SOC校准和估计方法[J]. 控制与决策, 2014, 29(6): 1148-1152.
	CHEN Z H, ZHONG L, HE Y, et al. Method to calibrate and estimate Li-ion battery state of charge based on charging method[J]. Control and Decision, 2014, 29(6): 1148-1152.
40	KALMAN R E. A new approach to linear filtering and prediction problems[J]. Journal of Basic Engineering, 1960, 82(1): 35-45.
41	韩航星, 王金全, 方建华, 等. 全钒液流电池SOC估算方法研究[J]. 电源技术, 2017, 41(4): 661-664.
	HAN H X, WANG J Q, FANG J H, et al. SOC estimation method research of all vanadium redox flow battery[J]. Chinese Journal of Power Sources, 2017, 41(4): 661-664.
42	王笑天, 杨志家, 王英男, 等. 双卡尔曼滤波算法在锂电池SOC估算中的应用[J]. 仪器仪表学报, 2013, 34(8): 1732-1738.
	WANG X T, YANG Z J, WANG Y N, et al. Application of dual extended Kalman filtering algorithm in the state-of-charge estimation of lithium-ion battery[J]. Chinese Journal of Scientific Instrument, 2013, 34(8): 1732-1738.
43	孙成才. 基于.NET的全钒液流电池监控管理系统的设计与实现[D]. 赣州: 江西理工大学, 2018.
	SUN C C. Design and implementation of monitor and management system for vanadium rlow flow battery based on the.NET[D]. Ganzhou: Jiangxi University of Science and Technology, 2018.
44	YANG F F, XING Y J, WANG D, et al. A comparative study of three model-based algorithms for estimating state-of-charge of lithium-ion batteries under a new combined dynamic loading profile[J]. Applied Energy, 2016, 164: 387-399.
45	KANG L W, ZHAO X, MA J. A new neural network model for the state-of-charge estimation in the battery degradation process[J]. Applied Energy, 2014, 121: 20-27.
46	雷肖, 陈清泉, 刘开培, 等. 电动车蓄电池荷电状态估计的神经网络方法[J]. 电工技术学报, 2007, 22(8): 155-160.
	LEI X, CHEN Q Q, LIU K P, et al. Battery state of charge estimation basedon neural-network for electric vehicles[J]. Transactions of China Electrotechnical Society, 2007, 22(8): 155-160.
47	陈星邑. 箱式全钒液流电池组协调控制技术及应用研究[D]. 合肥: 合肥工业大学, 2016.
	CHEN X Y. Research on coordinated control of box-layout vanadium redox flow battery pack[D]. Hefei: Hefei University of Technology, 2016.
48	王熙俊, 张胜寒, 张秀丽, 等. 全钒液流电池SOC监测方法综述[J]. 华北电力技术, 2015(3): 66-70.
	WANG X J, ZHANG S H, ZHANG X L, et al. Review on monitoring methods of SOC in the vanadium redox flow battery[J]. North China Electric Power, 2015(3): 66-70.

[1]	Xuan WANG, Qiang YE. The aggravation of side reactions caused by insufficient localized liquid supply in an all-vanadium redox flow battery stack [J]. Energy Storage Science and Technology, 2022, 11(5): 1455-1467.
[2]	WANG Qiushi, SUN Miaomiao, LIU Qinghua, YANG Hong CHEN Jingyun, LIU Junqing, LIANG Wenbin. Surface modification of carbon fiber paper for vanadium redox flow battery [J]. Energy Storage Science and Technology, 2020, 9(3): 714-719.
[3]	SHAO Junkang, LI Xin, MO Yanqing, QIU Ya, DONG Xueping, ZHU Haoyu. Analysis of modeling and flow characteristics of vanadium redox flow battery [J]. Energy Storage Science and Technology, 2020, 9(2): 645-655.
[4]	CHI Xiaoni, ZHU Mingang, WU Qiuxuan. Research on optimal operation control based on the equivalent model of VRFB system [J]. Energy Storage Science and Technology, 2018, 7(3): 530-538.
[5]	LIU Jinyu,LI Dan, WANG Lihua, HAN Xutong, HUANG Qinglin. SPEEK/ SGO proton exchange membranes with superior proton selectivity for vanadium redox battery [J]. Energy Storage Science and Technology, 2018, 7(1): 66-.
[6]	LI Xiangrong1,2, QIN Ye1, LIU Jianguo1, YAN Chuanwei1. Prediction of viscosity for concentrated aqueous VOSO4 solutions for vanadium flow batteries [J]. Energy Storage Science and Technology, 2017, 6(4): 776-781.
[7]	JIA Xiang, CUI Ning . TICC-500 energy storage phase of modeling and thermal properties [J]. Energy Storage Science and Technology, 2017, 6(1): 135-140.
[8]	CHEN Jizhong, LAI Xiaokang, HUI Dong, LI Bei, WANG Kunyang, LI Youning. Testing and analyzing power-energy response capability of the vanadium redox flow battery [J]. Energy Storage Science and Technology, 2014, 3(5): 486-489.
[9]	LIAO Sida, SONG Shiqiang, ZHANG Jianbo, WANG Baoguo. Simulation of the effects of electrode parameters on all-vanadium redox flow battery performance [J]. Energy Storage Science and Technology, 2014, 3(4): 395-405.
[10]	LI Minghua, FAN Yongsheng, LI Bingyang, WANG Baoguo. Theoretical and technological aspects of flow batteries:Shunt current formation and control [J]. Energy Storage Science and Technology, 2014, 3(2): 164-169.
[11]	LIU Zonghao, ZHANG Huamin, GAO Sujun, MA Xiangkun, LIU Yufeng. The world's largest all-vanadium redox flow battery energy storage system for a wind farm [J]. Energy Storage Science and Technology, 2014, 3(1): 71-77.
[12]	LI Dandan, CHU Youqun, LI Wenwen, MA Chunan. Characteristics of graphite based composite electrodes containing carbon nanotubes for vanadium redox flow batteries [J]. Energy Storage Science and Technology, 2013, 2(3): 227-232.
[13]	NIU Hongjin, TANG Junke, ZHANG Yongming, ZHANG Heng. Review on ion exchange membranes for vanadium redox flow battery applications [J]. Energy Storage Science and Technology, 2013, 2(2): 132-139.
[14]	YANG Linlin, LIAO Wenjun, SU Qing, WANG Zijian. The research &development status of vanadium redox flow battery [J]. Energy Storage Science and Technology, 2013, 2(2): 140-145.