Application Of Location And Capacity Determination Of Electric Vehicle Charging Station Based On Improved Sparrow Search Algorithm In Planning Area

As a large number of electric vehicles are connected to the power grid,unreasonable distribution of charging infrastructure often occurs,which affects users’ charging experience and poses a certain threat to the stable operation of the power grid.As for how to deal with this urgent problem,the core of this paper is the location and volume planning of electric vehicle charging stations,so as to further study and improve this problem.First of all,the location and capacity planning of charging stations should first consider the local electric vehicle(EV)daily charging demand load.Therefore,the first step of this paper focuses on electric vehicle(EV)daily charging load prediction.In view of the fact that the traditional temporal and spatial load forecasting of electric vehicles often adopts disordered random charging behavior,this paper considers the more realistic charging load forecasting strategy based on Lagrange relaxation method.After modification,the impact of charging load on the power grid is analyzed: the peak-to-valley difference rate of load decreases to 39.7%;On this basis,combined with the traffic network and Floyd shortest path algorithm,the travel chain is used to establish the simulation of users’ outbound trajectory,and the spatiotemporal distribution prediction of electric vehicles is carried out,laying a good foundation for the subsequent location and capacity determination.Secondly,in view of the charging station the capacity planning is the selection of variables and constraints,the complicated nonlinear problem,it is difficult to use conventional mathematical methods to solve,this paper proposes a charging station planning method based on improved the sparrow search algorithm,by introducing refraction in the initialization phase reverse strategy,increase the species diversity of its ergodicity;The cauchy variation strategy was introduced into the follower updating formula to make it not easy to fall into local optimum,and the solution was combined with the following site-constant volume model.Finally,the Analytic Hierarchy Process(AHP)and the Entropy Method(EWM)of objective weights are applied to solve the difficulty of multi-objective decision-making of charging stations.The weight of each index of charging station construction and operation cost,user time cost and environmental protection cost is calculated,so as to obtain the final planning model.Combined with 72 nodes of the geometric distribution planning simulation experiment,calculate the optimum configuration scheme,charging stations results show that the construction of charging stations for planning and site selection of the sparrow search algorithm based on improved constant volume scheme can reduce the comprehensive cost2.705 million yuan,reduced the spending have made the economy better,improve the sparrow search algorithm is verified to broaden its application domain,It has certain practical value and solves the planning problem of charging station practically.