Optimization Model Of Electric Vehicle Charging Station Siting In Energy Internet Environment

In the environment of global energy Internet,the electric car as the high-tech product of new energy,new materials,new direction and new technology will lead to revolution in energy,transportation,electricity,communications and other industries,which will become an important driving force of the new energy revolution.To encourage the development of the electric car industry,various countries have issued a large number of preferential policies.The implemention of related incentives and support policy will drive the electric car industry develop rapidly.Therefore,whether the development and planning of charging stations and other infrastructures are scientific and reasonable will become the key factor of balance and rapid development of electric car industry.Current basic facilities of the charging station construction is not unified,has inadequate supporting policies,problems of coordinated advance and unsound standards and regulations seriously restrict the dimensions of the electric car industry development.For scientific and standardized construction of charging station,based on the full consideration of integration of electric vehicles and energy Internet and current problems existing in the charging station planning,this paper will discusse the importance of scientific and optimizing charging station location from theoretical and practical prospects.First,considering with the grid security,economic development,transportation convenience,environment effects,technology development and planning of coordination,this paper analyzes the factors influencing the location of the charging station,builds the evaluation index system of charging station location based on the energy Internet,discusses the logical relationship and the interaction between the planning factors of economic,transportation,environment,technology and grid security,,constructs the charging station siting DPSIR model,divides the index system in five different system of drive system,pressure system,state system,influence system and response system,and describes the relationship between the elements.Secondly,the genetic algorithm is proposed to optimize the BP neural network model and entropy value method of site selection of charging stations is used in calculation of index weight.Thirdly,in order to avoid unmeasured calculation problem of correlation function of the traditional matter-element extension model,the improved matter-element extension model of charging station location planning is adopted in this paper.In addition,RBF neural network based on the genetic variation improved ant clustering algorithm is used in charging station location selection.Usually,there is no scientific method to selecte the initial parameters of RBF neural network,but this problem will be solved by using ant clustering algorithm based on genetic mutation to determine the number of hidden layer RBF neural network.Furthermore,this paper uses corresponding example analysis to prove that this method is scientific and effective.Finally,this paper compares the advantages and disadvantages of each method for charging station location planning problem and provides a new method and train of thought.