| Energy storage technology is the key technology to achieve the goal of “carbon peaking and carbon neutrality” and large-scale access of renewable energy to the grid.Vanadium redox flow battery(VRB)has many advantages,such as high safety,high overload capacity,long cycle life,independent output power and capacity,etc.,which has wide range of applications.Accurate estimation of key parameters such as state of charge(SOC)and peak power is an important guarantee for safe and stable operation of VRB.Therefore,to improve the accuracy of SOC and peak power estimation,this paper is organized from three aspects of VRB modeling,SOC estimation method and peak power estimation method.Firstly,a comprehensive equivalent model is set up.The traditional model cannot describe the effects of shunt current,flow rate and pump loss on the VRB operation characteristics.In this paper,a comprehensive equivalent model is proposed to describe the coupling relationship between current,flow rate and terminal voltage.This model includes circuit sub-model and hydraulic sub-model.The equivalent circuit sub-model is used to describe the external electrical characteristics of VRB.The equivalent hydraulic sub-model is used to describe the battery pump loss.Genetic algorithm(GA)is used to identify model parameters in this paper.Experimental and simulation data verify the accuracy of the model.This model lays a foundation for accurate estimation of SOC and peak power.Next,the SOC estimation method based on the VRB comprehensive equivalent model is proposed.The traditional SOC estimation method is based on offline equivalent model,and it has poor accuracy.This paper presents SOC estimation method based on unscented Kalman filter(UKF)and on recursive least square with forgetting factor(FRLS).At the same time,a 40A/80 A hybrid current discharge experiment is designed to verify the accuracy of the proposed method,and the root-mean-square error(RMSE)of the estimation SOC is 0.01.Thus,the proposed SOC estimation method has high accuracy and reliability.Finally,the peak power estimation method based on comprehensive equivalent model is proposed.Traditional peak power estimation methods usually apply simplified models and estimation algorithms,which cannot accurately and reliably estimate the peak power.The peak power estimation algorithm based on economic nonlinear model predictive control(ENMPC)is designed in this paper.And an online peak power estimation method based on ENMPC,UKF and FRLS is proposed.Experimental and simulation data verify the accuracy of the peak power estimation method based on ENMPC-UKF-FRLS.In addition,the power safe operating area(SOA)is proposed,the constraint conditions of charge and discharge peak power at different stages are analyzed. |
