Siting of Electric Vehicle Charging Stations Based on User Behavior

Abstract

Electric vehicles are a promising development opportunity. Electric vehicle charging stations are reasonably planned and can appropriately reduce some unnecessary expenses of operators and users in terms of time and economy. Considering the construction and maintenance cost of EV charging stations and user cost based on user behavior, the location of EV charging stations is determined. A model is built based on an improved genetic algorithm. The global search capability of the genetic algorithm is enhanced by improving the crossover operator. Introducing the particle swarm algorithm to obtain new convergence conditions allows the genetic algorithm to avoid falling into a local optimum. Through the simulation of charging station siting in Shenzhen, the improved algorithm has a faster convergence rate and stronger global search ability, which can provide practical siting strategies for charging station siting in other places.