锂电池储能舱运行状态信息采集系统研究

doi:10.19799/j.cnki.2095-4239.2021.0010

摘要/Abstract

摘要：

锂电池储能舱是储能系统的核心部件，内部存放大量电池，一旦发生严重事故极易造成整个锂电池储能舱的烧毁，如无法获取事发时刻系统和电池堆的运行数据，将给事故分析带来困难。本文对锂电池储能舱可能发生的故障及异常情况进行了全面的研究和分析，提出了一种锂电池储能舱运行状态信息采集系统方案，该方案能实时记录运行时的状态信息，并在储能舱发生异常状况时快速启动录波，保存数据为储能系统事故分析提供技术支撑。

关键词: 锂电池储能舱, 运行状态采集, 故障录波, 启动元件, 分析软件

Abstract:

Lithium battery energy storage cabin is the core component of the energy storage system, which stores a large number of batteries. Once a serious accident occurs, it is easy to burn the whole battery cabin. If the operation data of the system and battery stack at the time of the accident cannot be obtained, it will bring difficulties to the accident analysis. In this paper, the possible faults and abnormal conditions of lithium battery energy storage cabin are comprehensively studied and analyzed, and a scheme of lithium battery energy storage cabin operation status information acquisition system is proposed. The scheme can record the operation status information in real time, and quickly start the recording when the abnormal conditions occur in the energy storage cabin, save the data, so as to provide technical support for the accident analysis of energy storage system.

Key words: llithium battery energy storage cabin, operation state acquisition, fault recording, starting element, analysis software

中图分类号:

TM 911

谢建江, 高翔, 夏晨强, 郑益, 王浩. 锂电池储能舱运行状态信息采集系统研究[J]. 储能科学与技术, 2021, 10(3): 1109-1116.

Jianjiang XIE, Xiang GAO, Chengqiang XIA, Yi ZHENG, Hao WANG. Research on information acquisition system of lithium battery energy storage cabin[J]. Energy Storage Science and Technology, 2021, 10(3): 1109-1116.

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参考文献 23

1	国家电网公司"电网新技术前景研究"项目咨询组, 王松岑, 来小康, 等. 大规模储能技术在电力系统中的应用前景分析[J]. 电力系统自动化, 2013, 37(1): 3-8, 30.
	Consulting Group of State Grid Corporation of China to Prospects of New Technologies in Power Systems, Wang Songcen, LAI Xiaokang, et al. An analysis of prospects for application of large-scale energy storage technology in power systems[J]. Automation of Electric Power Systems, 2013, 37(1): 3-8, 30.
2	ABADA S, MARLAIR G, LECOCQ A, et al. Safety focused modeling of lithium-ion batteries: A review[J]. Journal of Power Sources, 2016, 306: 178-192.
3	LIAO Z H, ZHANG S, LI K, et al. A survey of methods for monitoring and detecting thermal runaway of lithium-ion batteries[J]. Journal of Power Sources, 2019, 436: 226879.
4	LIU X, REN D S, HSU H, et al. Thermal runaway of lithium-ion batteries without internal short circuit[J]. Joule, 2018, 2(10): 2047-2064.
5	张华东, 张宏亮. 一起火电厂储能系统火灾事故的调查与认定[J]. 消防科学与技术, 2017, 36(10): 1473-1476.
	ZHANG H D, ZHANG H L. Investigation and determination of an energy storage system fire of a thermal power plant[J]. Fire Science and Technology, 2017, 36(10): 1473-1476.
6	张青松, 姜乃文, 罗星娜, 等. 锂离子电池热失控多米诺效应实证研究[J]. 科学技术与工程, 2016, 16(10): 252-256.
	ZHANG Q S, JIANG N W, LUO X N, et al. Lithium-ion battery thermal runaway domino effect experimental verification research[J]. Science Technology and Engineering, 2016, 16(10): 252-256.
7	侯学勇, 陈军, 陈玉林, 等. 智能变电站故障录波与PMU一体化设计与实现[C]//第十五届保护与控制学术研究讨论文集, 北京: 中国水利水电出版社, 2015: 208-284.
	HOU X Y, CHEN J, CHEN Y L, et al. Design and Implementation for Integrative Equipment of Fault Recorder and PMU in Smart Substation[C]//The 15th Symposium on relay protection and control. Beijing: China Water Power Press, 2015: 208-284.
8	罗毅. 分布式故障录波系统[J]. 电力系统自动化, 2001, 25(20): 59-62.
	LUO Y. Distributed fault recording system[J]. Automation of Electric Power Systems, 2001, 25(20): 59-62.
9	邢浩江, 张东来. 一种实时高精度故障录波系统同步控制方法[J]. 电力系统自动化, 2009, 33(6): 63-66.
	XING H J, ZHANG D L. A high accuracy and real-time synchronous control method for fault recording system[J]. Automation of Electric Power Systems, 2009, 33(6): 63-66.
10	李俊刚, 王皖豫, 崔岱, 等. 故障录波装置中IEC61850标准的研究与应用[J]. 电力系统保护与控制, 2010, 38(8): 97-99,114.
	LI J G, WANG W Y, CUI D, et al. Research and application on IEC61850 in fault recording device[J]. Power System Protection and Control, 2010, 38(8): 97-99,114.
11	BARKHOLTZ H M, PREGER Y, IVANOV S, et al. Multi-scale thermal stability study of commercial lithium-ion batteries as a function of cathode chemistry and state-of-charge[J]. Journal of Power Sources, 2019, 435: doi: 10.1016/j.jpowsour.2019.226777.
12	INOUE T, MUKAI K. Roles of positive or negative electrodes in the thermal runaway of lithium-ion batteries: Accelerating rate calorimetry analyses with an all-inclusive microcell[J]. Electrochemistry Communications, 2017, 77: 28-31.
13	HILDEBRAND S, FRIESEN A, HAETGE J, et al. Delayed thermal runaway investigation on commercial 2.6 A·h NCM-LCO based 18650 lithium ion cells with accelerating rate calorimetry[J]. ECS Transactions, 2016, 74(1): 85-94.
14	JIANG F M, PENG P, SUN Y Q. Thermal analyses of LiFePO₄/graphite battery discharge processes[J]. Journal of Power Sources, 2013, 243: 181-194.
15	苏伟, 钟国彬, 沈佳妮, 等. 锂离子电池故障诊断技术进展[J]. 储能科学与技术, 2019, 8(2): 225-236.
	SU W, ZHONG G B, SHEN J N, et al. The progress in fault diagnosis techniques for lithium-ion batteries[J]. Energy Storage Science and Technology, 2019, 8(2): 225-236.
16	崔涛, 刘孝刚, 姜珊珊, 等. 变电站直流电源系统故障监测装置的研制与应用[J]. 江苏电机工程, 2016, 35(2): 26-30, 38.
	CUI T, LIU X G, JIANG S S, et al. The development and application of fault detection for DC power system[J]. Jiangsu Electrical Engineering, 2016, 35(2): 26-30, 38.
17	王春力, 贡丽妙, 亢平, 等. 锂离子电池储能电站早期预警系统研究[J]. 储能科学与技术, 2018, 7(6): 1152-1158.
	WANG C L, GONG L M, KANG P, et al. Research on early warning system of lithium ion battery energy storage power station[J]. Energy Storage Science and Technology, 2018, 7(6): 1152-1158.
18	FENG X N, PAN Y, HE X M, et al. Detecting the internal short circuit in large-format lithium-ion battery using model-based fault-diagnosis algorithm[J]. Journal of Energy Storage, 2018, 18: 26-39.
19	OUYANG M G, ZHANG M X, FENG X N, et al. Internal short circuit detection for battery pack using equivalent parameter and consistency method[J]. Journal of Power Sources, 2015, 294: 272-283.
20	罗伟林, 张立强, 吕超, 等. 锂离子电池寿命预测国外研究现状综述[J]. 电源学报, 2013, 11(1): 140-144.
	LUO W L, ZHANG L Q, LYU C, et al. Review on foreign status of life prediction of lithium-ion batteries[J]. Journal of Power Supply, 2013, 11(1): 140-144.
21	徐晶. 梯次利用锂离子电池容量和内阻变化特性研究[D]. 北京: 北京交通大学, 2014.
	XU J. Research on the variation characteristics of capacity and internal resistance of lithium-ion batteries echelon use[D]. Beijing: Beijing Jiaotong University, 2014.
22	赵钢, 孙豪赛, 罗淑贞. 基于BP神经网络的动力电池SOC估算[J]. 电源技术, 2016, 40(4): 818-819.
	ZHAO G, SUN H S, LUO S Z. Estimation of power battery SOC based on BP neural network[J]. Chinese Journal of Power Sources, 2016, 40(4): 818-819.
23	蔡信, 李波, 汪宏华, 等. 基于神经网络模型的动力电池SOC估计研究[J]. 机电工程, 2015, 32(1): 128-132.
	CAI X, LI B, WANG H H, et al. Estimation of state-of-charge for electric vehicle power battery with neural network method[J]. Journal of Mechanical & Electrical Engineering, 2015, 32(1): 128-132.

保存间隔	正常运行	出现扰动
模拟量信息	500 mS	10 mS
开关量信息	5 mS	5 mS
电池信息	200 mS	100 mS

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