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| Titre: | Artificial Neuron Network Based Faults Detection and Localization in the High Voltage Transmission Lines with Mho Distance Relay |
| Auteur(s): | Boumedine, Mohamed Said
Khodja, Djalal Eddine
Chakroune, Salim |
| Mots-clés: | Fault detection and localization
Diagnosis
High voltage transmission
Mho distance relay
Artificial neural network |
| Date de publication: | 2020 |
| Editeur: | IETA |
| Collection/Numéro: | Journal Européen des Systèmes Automatisés Vol. 53, N°. 1(2020);pp. 137-147 |
| Résumé: | This study offers the opportunity to extend the functioning of the most advanced protection systems. The faults which can arise on the power transmission lines are numerous and varied: Short-circuit; Overvoltage; Overloads, etc. In the context of short circuits, the conventional sensor as the Mho distance relay also known as the admittance relay is generally used. This relay will be discussed later in this study. By taking into account the preventive risks of the Mho relay and discover the new techniques of artificial intelligence, namely the neural network which can contribute to the precise and rapid detection of all types of short-circuit faults. The results of the simulation tests demonstrate the effectiveness of the methods proposed for the automatic diagnosis of faults. |
| URI/URL: | DOI: https://doi.org/10.18280/jesa.530117
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/7129 |
| Collection(s) : | Publications Internationales
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