The displacement of conventional generation by converter connected resources reduces the available rotational inertia in the power system, which leads to faster frequency dynamics and consequently a less stable frequency behavior. Virtual inertia, employing energy storage systems, could be used to limit the rate of change of frequency of power systems, thus, improving frequency dynamics. Electric vehicles (EVs) can represent a reliable solution to enhance frequency stability due to their fast response and capability to provide a large amount of aggregated power. On one hand, EVs are capable of adjusting the battery charging process (i.e., power flow) according to pre-defined algorithms. On the other hand, in case of islanded operation (i.e., low inertia), some of the EV's technical constraints might cause oscillations. This study presents two control algorithms which show that the EVs are capable of providing virtual inertia support. The first controller employs a traditional droop control, while the second one is equipped with an innovative control algorithm to eliminate likely oscillations. It is shown that, the proposed innovative control algorithm compared to the traditional droop control, assures same effects in terms of frequency but reducing significantly the number of variation of the EV's current set-point.


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    Titel :

    Grid Frequency Support by Single-Phase Electric Vehicles Employing an Innovative Virtual Inertia Controller


    Beteiligte:

    Erscheinungsdatum :

    2016-01-01


    Anmerkungen:

    Rezkalla , M M N , Zecchino , A , Pertl , M & Marinelli , M 2016 , Grid Frequency Support by Single-Phase Electric Vehicles Employing an Innovative Virtual Inertia Controller . in Proceedings of the 51st International Universities Power Engineering Conference . IEEE , 51st International Universities Power Engineering Conference , Coimbra , Portugal , 06/09/2016 . https://doi.org/10.1109/UPEC.2016.8113980



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




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