Bilevel design and pricing of EV charging stations with deviation-flow

Electric vehicles (EVs) represent a promising alternative to internal combustion engine vehicles, offering benefits such as lower operating costs, improved driving experience, and reduced environmental impact. However, the continued growth of EV adoption depends heavily on the availability of a well-designed and accessible charging infrastructure. In this study, we propose a novel bilevel programming model for the location and pricing of capacitated EV charging stations in urban areas. The upper level models the decisions of a central planner seeking to maximize the total revenue through optimal station location and design, and dynamic price selection across multiple time periods. The lower level model represents user behavior through a deviation flow capturing approach, where drivers minimize charging costs based on supply prices and station availability, while accounting for preferences related to location attractiveness. Computational tests on a set of randomly generated instances demonstrate the viability of the approach and highlight the impact of temporal demand distribution and charging duration on instance hardness.