Connected electric vehicles (CEVs), as promising core factors in smart cities, take a substantial role in advancing the quality of core transportation services in intelligent transportation systems (ITSs). The application of CEVs triggers the transportability and sustainability of smart cities, especially for ride-sharing and dynamic scheduling operations. Additionally, the combined optimization of the application of these schemes can further contribute to the potential benefits in smart cities. In this article, an online CEV system for joint ride-sharing and dynamic vehicle-to-grid (V2G) scheduling is proposed. Specifically, the joint problem is formulated as a mixed-integer quadratic programming (MIQP) problem. To deal with the forecast uncertainties, an online scheduling problem is thereby formulated, which also accounts for the communication effect to the real-time interactions. In the meantime, a bi-level system algorithm is devised to coordinate the CEV operations through the Benders’ decomposition. The case studies demonstrate that the proposed model can effectively provide high-quality citywise ride-sharing and V2G regulation services through reliable vehicular communications. In addition, the computational time of the proposed online bi-level algorithm can be greatly reduced under different network scales. Furthermore, the sufficient utilization of coordinated CEVs can significantly decrease the system operation cost by approximately 43.71% while alleviating city grid stability issues.


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    Title :

    Online Joint Ride-Sharing and Dynamic Vehicle-to-Grid Coordination for Connected Electric Vehicle System


    Contributors:


    Publication date :

    2024-03-01


    Size :

    882200 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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