Fault location is a crucial aspect of electrical power systems. It helps to identify the closest point to the occurrence of a fault, which is advantageous for improving the reliability of the electrical network of utility companies. However, based on the literature review, the problem of locating faults on distribution grids with renewable energy generation still needs improvements. In the literature, several works employ different artificial intelligence models to locate faults and improve the system’s observability in real-time. This work used three intelligent algorithms based on neural networks, KNN, and random forest for fault classification and location. The results showed that the algorithms classified and located all faults with 90% accuracy.
