Online collaborative estimation technology for SOC and SOH of frequency regulation of a lead-carbon battery in a power system with a high proportion of renewable energy

作     者：Hongchun Shu Wenlong Li Guangxue Wang Yiming Han Jiannan Li Yutao Tang 

作者机构：不详 Kunming University of Science and TechnologyKunming 650000China Department of Electrical EngineeringKunming University of Science and TechnologyKunmingChina 

出 版 物：《Protection and Control of Modern Power Systems》 (现代电力系统保护与控制（英文）)

年 卷 期：2024年第9卷第1期

页      面：52-64页

核心收录：

学科分类：0820[工学-石油与天然气工程] 0808[工学-电气工程] 08[工学] 0802[工学-机械工程] 0835[工学-软件工程] 080201[工学-机械制造及其自动化] 

基　　金：supported by the National Natural Science Foundation of China(52037003) the Major Special and Technology Project of Yunnan Province(202002AF080001) 

主　　题：battery estimation SOC 

摘      要：In this paper,a collaborative online algo-rithm is proposed to estimate the state of charge(SOC)and state of health(SOH)of leadcarbon batteries that participate in frequency regulation of a power system with a high proportion of renewable *** algo-rithm addresses the inaccurate estimation of energy storage battery states caused by continuous and alter-nating charging and discharging over a short *** of lead-carbon battery chemistry and materials reveals that the resistance of the diaphragm is the most influential factor in battery *** addition,the hyste-resis characteristics of an energy storage battery vary significantly between the charging and discharging stages.A second-order RC equivalent circuit model is proposed that considers the contact and diaphragm resistances,and hysteresis *** on this,models for constant current charging interaction,constant voltage charging interaction,and dynamic discharging interaction are *** adaptive forgetting factor recursive least square(AFF-RLS)method is used to identify the parameters of the interactive *** an interactive multiple model with the embedded unscented Kalman filter(UKF)is used to estimate the SOC of the energy storage *** membrane and contact resistances identified by the interactive multi-model(IMM)are used to estimate the SOH,and online collaborative optimization of the SOC and SOH is *** error of the proposed SOC estimation method is experimentally verified to be within 2%,which is less than 5%of the standard value,and the error of SOH estimation is within 0.5%,demonstrating the high accuracy of the proposed method.