Research On Typical Mode Analysis And Configuration Method Of Energy Storage Application In Charging Station

The rapid development of electric vehicles has promoted the growth of power load and charging stations.At the same time,it has also brought about a series of problems such as difficulty in expanding the charging station,high operating costs,and affecting the voltage quality of the distribution network.The energy storage configuration can effectively solve the above problems,but the high cost of energy storage restricts its application range.Now,rational allocation of energy storage capacity is a research hotspot.The existing literature mainly allocates capacity for a single type of charging station.When the number of charging stations is large,the workload of each analysis is heavy.This paper studies this as a breakthrough point.Based on the application of energy storage in the charging station,a set of quantitative index system is proposed to realize the rapid identification of the charging station type,and to provide guidance on configuration direction and capacity.An optimal configuration model of the energy storage capacity is established to optimize the allocation capacity and verify the feasibility of the index system by comparison.The main contents are as follows?Firstly,cluster analysis and Bayesian discriminant method are used to classify the load characteristics of multi-group charging stations,which are preliminarily divided into seven categories.In order to further clarify the relationship between charging station types and energy storage allocation,the main influencing factors of load are summarized from the perspective of energy storage allocation as follows:user travel rule and peak-valley price.The relationship between load types and influencing factors is analyzed by correlation analysis.Five kinds of typical charging stations are obtained by simplifying the charging station types,and a load classification index based on energy storage configuration objective is established,which can be used to quickly identify charging station types.Secondly,the application modes of energy storage for charging stations are analyzed,mainly in two directions:improving power and earning price difference.Improving power characteristics can be divided into delaying expansion of charging stations,cutting peak to reduce operating costs and low voltage governance.Earning price difference can be divided into earning peak-valley price difference and earning the difference between photovoltaic grid-connected tariff and local absorption tariff.The cost composition of each mode is analyzed.According to these five application modes,the principles of energy storage preliminary configuration for charging stations include:dividing the direction of energy storage configuration according to the type of charging stations;establishing the indicators of energy storage requirements for charging stations in each mode;putting forward the estimation method of energy storage capacity;simplifying the economic components of energy storage for charging stations,comparing the economy of some scenarios and other modes,and putting quantitative index of whether charging station is worth allocating energy storage.The load characteristics,energy storage allocation direction and allocation value of charging station are preliminarily understood by using the above allocation principles.The results show that energy storage is not suitable for the scenario of earning price difference based on the current price difference.Finally,four energy storage optimal allocation models are established,including delaying the expansion of charging stations,peak shaving to reduce operating costs,low voltage control and photovoltaic energy storage combined configuration.Particle swarm optimization(PSO)is used to optimize the economic cost,considering all constraints.The results show that the reasonable allocation of energy storage in charging station can improve the load characteristics and economy.And the rapid judgment index is simple and universal,although there are small deviations,but it can be used for reference in practical engineering applications.Preliminary judgment of energy storage allocation can effectively reduce the workload of later optimal allocation and improve allocation efficiency.