Title: A Review of Fault Identification and Location Estimation Methods in Distribution Grids
Authors: Biobele Alexander Wokoma, Lesuanu Dumkhana, Otonye Ene Ojuka
Volume: 8
Issue: 10
Pages: 99-102
Publication Date: 2024/10/28
Abstract:
The distribution grid serves the important function of ensuring that power actually gets to consumers at their various feeder points. These can only be effectively achieved if the power system feeders and their associated and interconnected component parts are immune from power systems faults. But in practice this is not always possible hence the distribution grid also experiences some level of power faults or contingencies. To ensure that the distribution grid is effectively restored to normal operation, the faults both pre-fault and post-faults have to be appropriately identified and effectively located. The identification process and location process will typically require the use of appropriate detection and location estimation algorithms well suited to the fault type. In this paper, a broad overview of fault identification and location estimation in the power distribution grids is presented. The paper specifically addresses the various types of fault identification algorithms in use in the modern smart grid era and equally discusses on the aspect of fault location estimation in addition to the fault location estimation algorithms in use. The aspect of machine learning based on Artificial Intelligence (AI), particularly that which relates to the use of artificial neural networks, deep neural networks and hybridizations that exist when employing such techniques.