Development Of Load Scheduling System Of Charging Station Base On Elastic Capacity

In recent years,the number of electric vehicles has grown rapidly and the demand for supporting charging infrastructure has increased significantly.Due to the severe problem of heavy overload in power grids in many developed regions,the access of charging stations is very difficult.To solve this contradiction,this study proposes a scheme to connect charging stations to the distribution grid-to connect charging stations as loads with elastic capacity,i.e.,during the hours when the grid needs to be peaking,charging stations are committed to participate in peaking,thus safeguarding the grid from heavy overloads due to the access of charging stations.Specifically,under the assumption that charging stations are obliged to participate in grid peaking,the characteristics of charging station loads are studied based on actual data,the probability of charging station loads are less than any given loads are defined as their elastic capacities,and optimization methods are introduced to study the optimal allocation of peaking commands to multiple charging stations based on the defined elastic capacities,and a system for scheduling elastic capacity charging station loads is developed on the basis of the above work.The main research work of this study includes the following contents.The requirement analysis and architecture design of the system to be developed were conducted.The functional requirements of the proposed developed elastic capacity-based charging pile load regulation were studied,and a system functional architecture based on four main functional modules,including elastic capacity estimation module,load forecasting module,scheduling optimization module,and comprehensive analysis visualization module,was designed.It proposes a method for estimating the elastic capacity of charging stations based on load history data.The charging station load history data of an actual year in a region was analyzed,according to the probability of charging station loads are less than any given loads are defined as the load elastic capacities,the relationship between load scheduling and load elastic capacity was studied,and the elastic capacities of different charging stations at different times were estimated by arithmetic examples.The study of load scheduling optimization algorithm based on elastic capacity was completed.The SVM method based on the PSO algorithm was applied to forecast the day-ahead load of charging stations,which was used to estimate the range of dispatchable loads of different charging stations.Based on the estimated resilient capacity of different charging stations,the optimization problem is constructed so that the sum of load resilience of all charging stations after participating in peaking is maximized,i.e.,the total impact of the peaking scheduling command on each charging station is minimized from the statistical point of view.The proposed load scheduling optimization algorithm based on the elasticity capacity is verified to be reasonable for the allocation of the peaking commands.A software system for charging station load scheduling was built through the above study.The front-end and back-end development of the system were completed by applying Java Script programming language and Python programming language respectively,and the software development of functions including login,load heavy overload warning,load prediction,charging station scheduling response configuration,etc.was completed,and the software system post-maintenance issues were discussed.