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The separation of battery charging and swapping processes enables highway operators to more flexibly manage the recharging of depleted batteries at battery swapping stations (BSSs), while also leveraging renewable energy (RE) resources to lower electricity costs. However, previous studies have not addressed the connection between BSS recharging strategies and the demand for fully charged batteries, which is determined by EV swapping schemes. To address this gap, the paper proposes a joint optimization approach for scheduling EVs and managing BSSs, considering RE generation along the highway. Specifically, a spatial-temporal network model is developed to represent the transportation-energy characteristics of EVs, incorporating BSS selection and battery swapping processes. Additionally, a BSS management model is formulated to plan the recharging of depleted batteries and ensure the availability of fully charged batteries to meet the swapping demands of EVs. The Lagrange relaxation algorithm is employed to handle the interaction between EV scheduling and BSS operations. A case study shows that this method effectively coordinates EV swapping schemes with BSS recharging strategies, resulting in a 17.3% improvement in RE generation utilization and a reduction in grid electricity consumption by RMB 1753.8.
Wang et al. (Thu,) studied this question.