Determination Of Location Of Electrical Vehicle Charging Stations Based On The Hybrid Algorithm That Based On Particle Swarm Optimization And Genetic Algorithm And Capacity Optimization

Electric vehicle has become the main development direction for the future automotive technology.As the most important foundation support system to promote the development and popularity of electric vehicles,electric vehicle charging system is also the important link for the process of electric vehicle commercialization and industrialization.Therefor the site selection and capacity optimization of the charging station has become an urgent problem to be solved.At present,the problems of charging station location are still in the initial stage,so in the cost for charging users,there does not take into account the road twists,turns coefficient and reentrant coefficient parameters.And this will cause a large gap between result and the actual situation.In this paper,the parameters of road twists,turns coefficient and reentrant coefficient have been combined,and considered the construction costs,operation and maintenance costs and the cost of being charged,to rise up an annual average cost model of electric vehicle charging station.In the part of algorithm,compared with the characteristics of particle swarm optimization algorithm,like the fast convergence speed,the high precision of the calculation result,but the global search ability is worse than the genetic algorithm.In this paper,a kind of fast speed,high accuracy,and not easy to fall into local optimum of the New Hybrid algorithm has been studied,which named Particle Swarm Genetic Algorithm(PSOGA),to solve the optimization problem of electric vehicle charging station location problem.so as to obtain a more accurate and efficient electric vehicle charging station location method.After the determination of charging station as well as the location of the covering range of vehicle charging quantity,using queuing theory to optimize the capacity of charging station.Establish a detailed construction plans in order to make the cost minimize for the charging station and the user’s time.