  As an important supporting facility for electric vehicles, the reasonable
planning and layout of charging stations are of great significance to the
development of electric vehicles. However, the planning and layout of charging
stations is affected by various complex factors such as policy economy,
charging demand, user charging comfort, and road traffic conditions. How to
weigh various factors to construct a reasonable model of charging station
location and capacity has become a major difficulty in the field of electric
vehicle charging facility planning. Firstly, this paper constructs the location
and capacity optimization model of the charging station with the goal of
maximizing the revenue of operators and minimizing the user's charging
additional cost. At the same time, the road time-consuming index is introduced
to quantify the impact of road congestion on the user's charging additional
cost, so as to effectively improve the user's satisfaction during charging.
Then, aiming at the charging station planning model, a non-dominated sorting
genetic algorithm with an elite strategy (NSGA-II) based on chaos
initialization and arithmetic crossover operator is proposed. Finally, taking
the Haidian District of Beijing as the simulation object, the results show that
compared with the situation of urban traffic networks not considered, the model
proposed in this paper significantly reduces the cost of lost time of users by
11.4% and the total additional cost of users' charging by 7.6%. It not only
ensures the economy of the system, but also effectively improves the charging
satisfaction of users, which further verifies the feasibility and effectiveness
of the model, and can provide a reference for the planning and layout of
charging stations in the future.

Systems and Control;Systems and Control