Bi-level programming model approach for electric vehicle charging stations considering user charging costs

Abstract

• A new bi-level planning model is proposed that integrates the interests of both charging station investors and EV users, where the upper model has the global economic return as the optimization objective, and the lower model has the EV user's satisfaction with the charging service (charging cost) as the optimization objective. The global economic cost is optimized while the service satisfaction of the user is improved. • The time cost, economic cost, and mileage anxiety are considered together to characterize the service satisfaction of EV users. Specifically, the charging queuing time, driving distance, desired charging volume, and actual charging volume are used to reflect the charging cost of EV users and to reflect the autonomy of EV users more accurately, and a combination of fast and slow charging posts are used for planning to meet the needs of different users and grid constraints, to improve the operational efficiency of charging stations and reduce the charging queuing time of EV users. • The conventional method and the bi-level planning method are solved separately for a region of Beijing, and the effectiveness of the proposed method is verified by comparing factors such as investors' returns, users' charging costs, and queuing times. The rapid development of electric vehicles (EV) has placed greater demands on the planning and construction of public electric vehicle charging stations (EVCS). As EV users are highly autonomous in their charging behavior, the interests of investors and EV users are mutually affected and challenging to balance. Therefore, this paper proposes a bi-level planning model to balance the interests of investors and EV users and optimize global economic costs while improving the service satisfaction of users. The upper-level model aims to optimize the economic cost. In contrast, the lower-level model aims to optimize the service satisfaction of EV users and characterizes the charging satisfaction of EV users through the costs of charging queuing time, distance traveled, desired to charge volume, and actual charging volume, to more accurately reflect the autonomy of EV users. A combination of fast and slow charging piles is also used for planning to meet the needs of different users and improve charging stations' operational efficiency. Finally, a case study is conducted in an area of Beijing to verify that the optimization model has the advantages of low global economic cost, short charging queuing time for users, and high service satisfaction.