As autonomous electric vehicles and car-sharing services are becoming more popular, the contribution of shared autonomous electric vehicles (SAEVs) to the future of urban transportation is getting more achievable. Like conventional electric vehicles, SAEVs can provide power grids with ancillary services. This article proposes a new scheduling scheme for SAEV fleets within a cooperative plan to let power distribution networks benefit from the energy storage of vehicle batteries in recovering critical loads after a predictable extreme event. According to a long-term contract, the detailed request of the distribution system operator (DSO), together with desired constraints and perquisites, is sent to the SAEVs aggregator (SA) prior to the landfall of a predictable extreme event. Afterward, SA runs a targeted algorithm to schedule trip assignments and charging cycles of SAEVs so that the required constraints of DSO are satisfied. The SAEV participants will continue carrying passengers within the scheduled time horizon in addition to delivering energy to the distribution network at the scheduling deadline declared by DSO. This deadline is the time instant when the capacity of the SAEV fleet may be no more applicable to enhance the system preparedness against the approaching event. Numerical results illustrated that the proposed scheme helps improve the power grid resilience by delivering 2396.1 kWh of energy to the distribution network in addition to increasing the total income of each participant SAEV by about 130%. Thus, it is implied that the proposed method offers a win-win situation for both entities.


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    Titel :

    Resilience-Oriented Scheduling of Shared Autonomous Electric Vehicles: A Cooperation Framework for Electrical Distribution Networks and Transportation Sector


    Beteiligte:
    Mohammad Hassan Amirioun (Autor:in) / Saeid Jafarpour (Autor:in) / Ali Abdali (Autor:in) / Josep M. Guerrero (Autor:in) / Baseem Khan (Autor:in)


    Erscheinungsdatum :

    2023




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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