储能科学与技术 ›› 2021, Vol. 10 ›› Issue (6): 2363-2372.doi: 10.19799/j.cnki.2095-4239.2021.0207
谢克桓1(), 李传常1(), 陈荐1, 余龙海2,3, 谭准2, 秦位海2
收稿日期:
2021-05-13
修回日期:
2021-09-04
出版日期:
2021-11-05
发布日期:
2021-11-03
通讯作者:
李传常
E-mail:kehuanxie@126.com;chuanchangli@126.com
作者简介:
谢克桓(1997—),男,硕士研究生,研究方向为全钒液流电池储能系统,E-mail:基金资助:
Kehuan XIE1(), Chuanchang LI1(), Jian CHEN1, Longhai YU2,3, zhun TAN2, Weihai QIN2
Received:
2021-05-13
Revised:
2021-09-04
Online:
2021-11-05
Published:
2021-11-03
Contact:
Chuanchang LI
E-mail:kehuanxie@126.com;chuanchangli@126.com
摘要:
作为电化学储能技术之一的全钒液流电池(VRB),因其具有寿命长、安全性高、布置灵活等特点,是未来最有潜力实现长寿命、低成本的大规模储能技术。本文总结了电路模型和电化学模型两类全钒液流电池储能仿真模型:电路模型多是以固定的电路元件模拟电池回路串并联而成,电化学模型则是描述电池内部参数变化的数学模型。同时,本文总结了全钒液流电池常用的荷电状态(SOC)监测方法:开路电压法、电流积分法与卡尔曼滤波算法的基本原理及使用方法。SOC监测方法是对部分仿真模型的补充,以期构建更为完善的全钒液流电池储能系统。
中图分类号:
谢克桓, 李传常, 陈荐, 余龙海, 谭准, 秦位海. 全钒液流电池储能仿真模型及荷电状态监测方法研究[J]. 储能科学与技术, 2021, 10(6): 2363-2372.
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.
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. |
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