Research On Electric Vehicle Charging Optimization System Based On MQTT

In recent years,with the rapid development of vehicle electrification technology,electric vehicles have gained rapid popularity and the share of new energy vehicles has gradually increased has become a trend.In the future,with the rapid growth of new energy vehicle ownership represented by pure electric vehicles,there will be a large number of charging devices connected to the power grid to provide charging services for electric vehicles,which will bring great challenges to the smooth operation of the power grid.Therefore,it is very important to find the method to arrange the charging of electric vehicles in an orderly manner.In this paper,we will study the optimization of electric vehicle charging,and the main research contents are as follows:The HPSOGA algorithm is used to optimize the charging of electric vehicles,and a charging optimization model is constructed with the objective of minimizing the charging cost for users and the fluctuation rate of grid load.After the simulation analysis,the algorithm can effectively reduce the user charging cost by 41.90% and reduce the fluctuation of grid load by 30.20%,and the performance of the optimization is improved by 3.48% and2.96% compared with the traditional PSO and GA algorithms,respectively.A design scheme for optimizing the charging system of electric vehicles has been proposed to effectively reduce the fluctuation of grid load caused by disorderly charging of electric vehicles.The plan includes a front-end,which is a charging device that provides charging services for electric vehicles;The backend,which is the charging optimization server that sends control information to charging devices,is connected through cloud servers at the front and back ends,enabling reasonable charging arrangements for large-scale electric vehicles.The Io T technology is used to build the charging optimization system,and the HPSOGA algorithm is applied to it.The cloud technology is used to build the MQTT message server to establish the information connection between the charging device and the charging optimization server,and the multi-threading technology is used to realize the concurrent execution of multiple charging optimization tasks in order to meet the user’s charging optimization needs.The multi-threaded technology is used to execute multiple charging optimization tasks concurrently to meet users’ charging optimization needs.Through the data intercommunication between charging devices and the charging optimization service terminal,in order to achieve the purpose of charging optimization.After testing and analysis,in the case of users participating in optimized charging at night after work,the charging expense can be reduced by 64.86% on average,while effectively reducing the fluctuation of grid load.