A State-of-the- Art Holistic Charge Scheduling for Direct Charging and Battery Swapping Station under a Collaborative Environment

This paper proposes a scalable holistic day-ahead scheduling framework for EV charging by considering spatial-temporal properties of EVs for considering the amalgamation of Plug-in charging station (CS) and Battery Swapping Station (BSS). This work explores the factors for increasing the number of EVs charged and the profit of service providers through a novel algorithm including collaboration among aggregators. Using a 25-node transportation network, this framework is tested for realistic traffic scenarios using both non-collaborative and collaborative inter-aggregator schemes. The results under these scenarios prove the efficacy of the proposed framework in maximizing the scheduled vehicles and enhancement of the profit of aggregators against the non-collaborative scheme in each scenario. The proposed framework for day-ahead scheduling is thus capable of charging EVs with various energy demands during a day on its way at an appropriately assigned direct charging station or battery swapping station under a collaborative framework while incorporating realistic energy purchase for different traffic scenarios with cancellation penalties.