Enhancing solar energy generation utilization along highways: optimizing electric vehicle charging-swapping schemes and scheduling mobile energy storage systems

Utilizing solar energy resources to replenish electricity in electric vehicles (EVs) is gaining increasing attention on low-carbon highways. Currently, the primary methods for EV power replenishment are charging and battery swapping. However, the differences between the above two methods and the uneven time-space distribution of solar energy resources pose challenges to optimizing solar energy utilization. Additionally, the use of mobile energy storage systems (MESSs) for EV energy replenishment has become a notable area of research. Therefore, this paper proposes a two-level approach for optimizing EV charging-swapping schemes alongside scheduling MESSs to efficiently allocate solar energy generation along highways. The proposed model employs spatial-temporal network concepts for charging-type EVs, swapping-type EVs, and MESSs to portray the interactions between transportation and energy systems. In the first level, we develop a framework to schedule two types of EVs while managing the recharging process for depleted batteries at battery swapping stations (BSSs). The goal is to maximize the highway manager’s benefits while satisfying fully charged battery demands for swapping-type EVs. In the second level, we focus on optimizing the discharge/charge power and routes of MESSs to effectively redistribute solar energy according to grid-supplied charging demands. Our case study demonstrates that the proposed method significantly enhances solar energy utilization and reduces grid electricity consumption, providing a more sustainable and economical operational solution for green highways. • Design two-level optimization method to enhance solar energy generation utilization. • Optimize charging and swapping schemes for electric vehicles using an integrated model. • Schedule mobile energy storage systems to alleviate energy supply-demand imbalances. • Integrate spatial-temporal networks with highway and energy characteristics.