Transportation electrification is crucial for the green transition, as the transport sector contributes 25% of greenhouse gas emissions in Europe. Energy sharing and storage, electrification, and hydrogenation in buildings and transportation, represent key factors for decarbonization. This paper focuses on the sustainable hydrogen-based public transportation in urban areas, evaluating the technical features of a Hydrogen Refueling Station (HRS) for a fleet of hydrogen buses. A methodology based on Genetic Algorithm (GA) is developed to minimize queuing time by optimizing the daily start sequences of the considered buses. Moreover, the study compares the use of refueling dispenser with and without a cooling system (15 and 60 mins for refuelling, respectively). Specifically, no queue is registered in the first case, while GA optimization can reduce the average queue time per bus from 120 to 35 minutes (total stop time decreases from 180 to 95 minutes) in case of non-cooled dispenser. Then, delaying the bus starting threshold to 3 hours, the average queue time per bus is lowered to 12 minutes, with a total stop time at the HRS of 72 minutes. This allows to identify the optimal departure sequences for buses with longer refueling times, reducing both drivers' working hours and costs.


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    Titel :

    Genetic Algorithm Optimization of Fuel Cell Electric Bus Fleet Operation for Carbon-Neutral Districts


    Beteiligte:
    Pelosi, Dario (Autor:in) / Ciotti, Eleonora (Autor:in) / Tritoni, Mattia (Autor:in) / Barelli, Linda (Autor:in)


    Erscheinungsdatum :

    25.07.2024


    Format / Umfang :

    642790 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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