LAUSR

Deploying charging stations (CSs) catering to the demand from electric vehicles plays an important role in modernizing energy infrastructures. In this paper, a bi-level optimal allocation model for allocating fast CSs is proposed aiming to maximize the CS investor benefit (upper layer sub-problem) by optimally allocating CSs with the coordinated determination of the expected efficiency of charging service supply (lower layer sub-problem). The efficiency is formulated as a charging performance index in terms of user satisfaction degree, which mathematically couples the upper level and lower level sub-problems. The proposed nonlinear bi-level model is reduced to a single-layer optimization model under the Karush–Kuhn–Tucker optimality conditions. An improved dynamic differential evolution algorithm with an adaptive update strategy is proposed to solve this single-layer optimization model. The proposed method is validated using a realistic case. The test results show that the proposed methodology is able to co-ordinate both objectives of interest, i.e., allocating CSs network with the maximized benefits and optimizing the fast charging service efficiency at the same time.