Research On Related Strategies Optimization Of Electric Vehicle Charging

With the rapid development of modern sciences,technologies such as internet communication and system optimization control have been widely applied in existing power systems.Smart grid is a rising trend of the future power grid.Nowadays,continuous innovation in electric vehicles(EVs)benefits the growth of its market share.Therefore,in the foreseeable future,its power system will have a tremendous impact on the scheduling of the overall electricity grid.One the other hand,in the last decades,demand for electricity has gradually risen while the cost of generating electricity has also risen.In order to improve the stability of the existing power grid,many governments actively has formulated policies to promote the concept of smart grid and constructed relevant facilities.Most of the current optimized scheduling strategies for the smart grid use high electricity prices to divert electricity consumption peak so as to reduce the pressure on power generation.Most of the optimization strategies only consider either the service revenue of the power supply terminal or the peak of the optimized power grid load.Due to the contradiction between them,most of the optimal scheduling strategies cannot effectively satisfy both aspects.The background of this research is involed in the intergration of a variety of electric vehicles into the grid.We studied the current development of the smart grid and electric vehicles all over the world,and established a mathematic model of charging and discharging for all kinds of electric vehicles.Besides,we systematically analyzed present scheduling strategies related to electric vehicles.This article focuses on electric vehicle charging stations as well as charging and swapping station on the basis of primary power system.It is inevitable requirements of smart grid to ensure the load stability for the primary power supply end.In addition,to guarantee the income of primary power supply service with time-of-use price is also vital interests of the suppliers.Therefore,this paper presents a multi-objective optimization solution,which is expected to increase the daily load factor of electric vehicle charging and swapping stations,and at the same time,to ensure the service income of charging electric vehicles within an acceptable range.In this study,aiming at the multi-objective optimization problem mentioned above,a charging scheduling strategy for electric vehicles in smart grid is designed.Assuming that all types of EVs can be integrated into our scheduling architecture,the"internet of th ings(IOT)" concept will also be applied.To figure out the above multi-objective optimization problem,the Pareto optimal solution set was obtained by improving the multi-objective immune optimization algorithm.Finally,the Manhattan minimum distance algorithm was used to solve the consequent multi-criteria decision-making problem.The optimal solution was found in the above Pareto optimal solution set,and the optimal charging scheduling strategy for EV charging stations and swapping stations is obtained.Then the simulation results were analyzed,and the numerical results were used to verify the effectiveness of the proposed method.It was proved that the optimization strategy proposed in this paper could improve the self-loading factor of EV charging station and swapping station,and guarantee daily charging EV service income simultaneously.