摘要
针对目前应用于电力系统调峰调频最广泛的磷酸铁锂电池,采用采样点卡尔曼滤波算法对电池荷电状态SOC(StateofCharge)进行估算,再通过Matlab/Simulink平台进行估算模型的搭建,在几种充放电状态下进行了验证,仿真结果表明:利用采样点卡尔曼滤波算法的估算模型,其估算误差在研究的充放电状态下都在1%以内,可为储能电池的安全经济运行管理提供理论估算依据。
For the lithium iron phosphate battery which is widely used in peak and frequency modulation of power system,the sampling point Kalman filter algorithm is used to estimate the state of charge(SOC)of the battery,and then the estimation model is built by Matlab/Simulink platform.Finally,the verification is carried out under several charging and discharging states.The simulation results show that the estimation error of using the sampling point Kalman filter estimation model is less than 1%in the state of charge and discharge studied,which can provide a theoretical estimation basis for the safe and economic operation management of energy storage batteries.
作者
罗日忠
郑国
周波
丁佳欣
楼波
LUO Rizhong;ZHENG Guo;ZHOU Bo;DING Jiaxin;LOU Bo(Zhanjiang Electric Power Co.,Ltd.,Zhanjiang Guangdong 524000,China;South China University of Technology,Guangzhou Guangdong 510640,China)
出处
《湖北电力》
2023年第6期15-20,共6页
Hubei Electric Power
基金
广东省能源集团项目(项目编号:ZJP-PK-23001)。
关键词
电池SOC模型
采样点卡尔曼滤波
电池荷电状态
安时积分法
调频
电力系统
调峰
磷酸铁锂电池
battery SOC model
sampling point Kalman filtering
battery state of charge
ampere-hour integration
frequency modulation
electric power system
peak regulation
lithium iron phosphate battery
