This paper investigates the potential impact of a fleet of electric vehicles charging on the cost of electricity generation, greenhouse gas emissions (GHG) and power system demand through low voltage residential demand-side management (DSM). The proposed optimisation algorithm is used to shift electric vehicles charging loads to minimize the combined impact of three key parameters: financial, environmental, and demand variability. The results show that it is effective to reshape the power demand and reduce electricity cost and GHG emissions without affecting people's driving patterns.


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    Titel :

    EV charging scheduling for cost and greenhouse gases emissions minimization


    Beteiligte:
    Rentao Wu, (Autor:in) / Tsagarakis, G. (Autor:in) / Collin, A. J. (Autor:in) / Kiprakis, A. E. (Autor:in)


    Erscheinungsdatum :

    2017-04-01


    Format / Umfang :

    667561 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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