基于实时二阶电路模型的锂离子电化学储能状态监测方法  

Lithium-ion electrochemical energy storage state monitoring method based on real-time second-order circuit model

作　　者：刘庭响 杨立滨 李正曦 马俊雄 王恺 高金 Liu Tingxiang;Yang Libin;Li Zhengxi;Ma Junxiong;Wang Kai;Gao Jin(Economic and Technological Research Institute,State Grid Qinghai Electric Power Company,Xining 810000,China;Clean Energy Development Research Institute,State Grid Qinghai Electric Power Company,Xining 810000,China)

机构地区：[1]国网青海省电力公司经济技术研究院,青海西宁810000 [2]国网青海省电力公司清洁能源发展研究院,青海西宁810000

出　　处：《能源与环保》2025年第2期221-229,共9页CHINA ENERGY AND ENVIRONMENTAL PROTECTION

基　　金：国家电网公司科技项目(522830230001)。

摘　　要：新能源的加入给电网稳定性带来了挑战,电化学储能电站成为平抑发电波动的关键,其运行状态监测至关重要。对此,提出了一种基于实时二阶电路模型的锂离子电化学储能状态监测方法。该方法由基于扩展卡尔曼滤波(EKF)的在线参数辨识和基于光滑变结构滤波的状态估计2部分组成,将这2种滤波器系统集成的组合称为混合滤波器(hybrid filter,HF),并提出了一种基于粒子群优化(PSO)方法来寻找HF的最优调谐参数。仿真结果表明,相较于传统的双扩展卡尔曼滤波(DEKF),所提的HF和HF+PSO算法能够更有效地选择调谐参数,估计的SOC在1500 s后最大误差约为2%,估计的电池容量在约3000 s时即开始收敛至真实值,而DEKF算法则需长达7000 s。因此,提出的方法对保障电化学储能电站安全可靠运行和提高电力系统稳定性具有重要意义。The integration of new energy sources poses challenges to grid stability,and electrochemical energy storage stations have emerged as a crucial solution to smooth out fluctuations in power generation,monitoring their operating status is crucial.In response,a lithium-ion electrochemical energy storage state monitoring method based on a real-time second-order circuit model was introduced.This method comprises two main parts:online parameter identification using the Extended Kalman Filter(EKF)and state estimation based on Smooth Variable Structure Filter.The combination of integrating these two filter systems is called a hybrid filter(HF).Furthermore,a Particle Swarm Optimization(PSO)approach was proposed to identify the optimal tuning parameters for the HF.Simulation results demonstrate that compared to the traditional Dual Extended Kalman Filter(DEKF),the proposed HF and HF+PSO algorithms can more effectively select tuning parameters,with the estimated State of Charge(SOC)achieving a maximum error of approximately 2%after 1500 seconds,and the estimated battery capacity converging to the true value around 3000 seconds,whereas the DEKF algorithm requires up to 7000 seconds.Therefore,the method presented in this paper holds significant importance in ensuring the safe and reliable operation of electrochemical energy storage stations and enhancing the stability of power systems.

关 键 词：实时二阶电路模型 电化学储能 混合滤波 状态监测 

分 类 号：TM912[电气工程—电力电子与电力传动] TP277[自动化与计算机技术—检测技术与自动化装置]