In this article a novel method for the estimation of distance of fault location for single line to ground faults using cross- correlation and Elman Back Propagation Neural Network has been presented. In this proposed work a distinctive analogy has been incorporated between the cross-correlogram obtained from a non- faulty phase and a faulty phase in electric power system and an Electrocardiogram (ECG) of human heart at normal condition. Importance is also involved to the feature extraction & ECG-fault signals analogy, otherwise the majority of the scheme may not be implemented accurately. Furthermore this proposed method alleviates the problems related with fault distances by estimating it & reduces the faulty impacts on transmission line.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Cross-correlation based distance estimation of single line to ground faults using Elman back-propagation neural network


    Beteiligte:


    Erscheinungsdatum :

    01.06.2019


    Format / Umfang :

    3212688 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch