Location And Size Planning Of Electric Vehicles Battery Swapping Stations Based On Improved Bats Algorithm

With the increasing amount of electric vehicles year by year,the construction coverage of electric vehicles charging and swapping infrastructures in cities is more and more extensive.The location and size planning of charging and swapping infrastructures has become an indispensable part of urban transportation network planning and construction.This paper studies and discusses the location and size planning of battery swapping stations under the mode of "centralized charging and unified distribution",further studies and improves the method of location and size planning of charging and swapping infrastructures under this mode.Different from the plug-in charging mode,the battery swapping mode is needed to consider the joint influence of central charging station and battery swapping stations,so as to carry out the location and size planning of the battery swapping stations.In order to solve the problem of location and size planning of battery swapping stations,the local daily demand load of electric vehicles must be considered first.Therefore,this paper introduces the charging behavior mode of four kinds of electric vehicles with different uses based on the orderly charging strategy.The Monte Carlo method is used to randomly extract the initial charging time distribution and daily mileage of electric vehicles,calculate the initial state of charge and the time required for full charge of vehicles,and obtain the total daily charging load of four types of electric vehicles respectively.Then the total daily charging load of these four types of electric vehicles is superimposed,and the total daily charging load of electric vehicles is obtained.Aiming at the location and size planning models of battery swapping stations,a multi-objective decision-making model is established with the objectives of annual construction investment costs,annual costs of battery distributions and bettery-swapping distance,and annual battery-swapping time costs.Fuzzy entropy weight method is introduced to avoid the shortage of subjective and objective weights,so as to transform the multi-objective decision-making model into a single objective weight model.As the location and size planning of battery swapping stations is a complex nonlinear problem with multi variables and multi constraints,it is difficult to solve with general mathematical methods.In this paper,a location and capacity planning method based on Voronoi diagram and improved bats algorithm(IBA)is proposed,while retaining the efficient optimization and fast convergence ability of the original algorithm,Logistic chaotic map is introduced to initialize the chaos of bats population,so as to improve the quality of initial population.Inertia weight,acceleration factor,learning factor and individual pole are introduced in order to improve the global search ability and convergence efficiency,the improved strategy based on value and other parameters is combined with Adaptive differential evolution algorithm to increase the diversity of bat population.Taking the minimum value of evaluation function of multi-objective decision as the condition,the Voronoi diagram is used to divide the service area of each battery swapping stations,and the improved bats algorithm is used for global optimization,so as to obtain the optimal solution of the battery swapping stations location and capacity planning scheme.Finally,a demonstration operation planning area of a city in Guangdong Province is taken as an example for analysis and simulation.The simulation results verify the rationality and feasibility of the proposed model and algorithm.