Research On Energy Management Technology Of Decommissioned Power Battery Under Energy Storage Replacement Scenario

At present,the scale of retired batteries in our country is accelerating.Through screening and reorganization,the retired batteries are applied in low stress scenarios such as energy storage replacement cabinet,which can not only realize the full utilization of resources but also protect the environment as much as possible,which has great economic and social value.At the same time,the rise of the distribution industry makes the charging demand of the changing cabinet gradually increase.Participating in orderly charging can not only meet the needs of users,but also obtain greater benefits.In this paper,retired lithium batteries are taken as the research object.Based on laboratory test data,core issues such as battery power state estimation and health state estimation,and orderly charging strategy of electrical change cabinet are studied.The main contents of the full text are as follows:Firstly,according to the existing battery characteristic data,the charge-discharge capacity of retired power batteries was used as the indicator to estimate the state of charge and discharge.The improved support vector regression algorithm was used to establish the estimation model of the indicator.The penalty parameters and kernel parameters of the support vector regression were optimized by particle swarm optimization algorithm,and the effectiveness of the whole method was verified by the charge and discharge test of retired power batteries.For battery health state estimation problem put forward a strategy,through the limit of machine learning algorithm to estimate the battery state of health,based on particle swarm algorithm and improved weight value and threshold value of extreme learning machine,after the 38.4 V200 Ah type lithium battery charge and discharge test data to verify the effectiveness of this method.Secondly,the structure of the energy storage changing cabinet system is given and the controlled objects are determined.Considering the factors such as power grid price,peak load and battery capacity,the orderly charging mathematical model with the lowest running charge and the lowest peak and valley load value is established.The particle swarm optimization algorithm based on linear weight decline is used to solve the model,and the solution results are compared with the traditional orderly charging method.The results show that this strategy can realize the power distribution of the energy storage switching cabinet,reduce the operation cost of the switching cabinet and improve the operation efficiency.Finally,Simulink simulation software was used to build a simulation model with a 4:1 ratio with the actual situation,and the above state estimation model and the orderly charging strategy model of the power change cabinet were imported into the Simulink simulation model to verify the accuracy of the proposed calculation and strategy model.Through the upper computer,semi-physical simulation platform and oscilloscope and other instruments to do the semi-physical simulation verification,simulation of the change of the switch in the process of power change.The simulation model is further promoted and integrated into the software,which provides a reference for the more efficient application of decommissioned batteries in the energy storage cabinet in the future.