Research On Locating And Sizing Determination Method Of Electric Vehicle Charging Station Considering Charging User Behavior

Electric vehicles,which use clean energy to transport vehicles,have played a huge role in dealing with environmental problems and energy shortages.As EV industry is regarded as an important development strategy,this kind of behavior also provides certain growth motivation for upgrading automobile industry.However,when the number of grid-connected EVs charging is large,it is easy to cause certain impacts.On the one hand,the stable operation of the power grid may be harmed by the surge of charging load;on the other hand,the unreasonable location of charging facilities will also have a negative impact on both operators and EV users.Therefore,it is extremely important to build a complete charging infrastructure service system and plan an efficient charging service network.Firstly,this paper presents a time distribution model that takes into account the charging load of EVs.The models of different types of EVs with different charging regularity are studied respectively.Monte Carlo is used to simulate the load distribution in disordered and ordered charging states,and the results verify the accuracy of the model.The results show that when there is a certain scale of EVs connected to the grid,the increase of charging load will have negative feedback to the normal operation of the grid.Orderly charging not only helps users reduce charging costs,but also plays the role of peak cutting and valley filling.Secondly,an improved whale optimization algorithm is proposed to solve the location and capacity model of charging stations.Aiming at the problems of poor convergence ability,low degree of randomness and weak avoidance of local extremum in the late iteration of WOA,Sobol sequence,nonlinear decreasing strategy of convergence factor,"mutualism" search and lens reverse learning method with iterative scaling were used to optimize WOA.IWOA is compared with AO,MPA,PSO,GWO,WOA and other five algorithms based on the solution of twelve test functions,and the results are analyzed.Thirdly,this paper proposes a multi-objective EV charging station location and capacity model based on the calculation of charging user behavior probability,which satisfies the interests of both users and operators,takes the maximum user satisfaction and the minimum total cost of operators as the goal,and the charging demand and charging station capacity as the constraint conditions.Finally,the rationality of IWOA and the multi-objective location model is proved by the example study.IWOA was used to solve the multi-objective model constructed,and the coordinates of each CS and the capacity of each CS were obtained.Compared with other five algorithms,it is found that IWOA has better solving performance.In other words,the proposed location and capacity determination method is an effective way to solve the problems of electric vehicles,and it also has certain guiding significance.