Fault Detection and Classification in Ring Power System with DG Penetration Using Hybrid CNN-LSTM

• Published in: IEEE access Vol. 12; p. 1
• Main Authors: Alhanaf, Ahmed Sami, Farsadi, Murtaza, Balik, Hasan Huseyin
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Algorithms; Artificial neural networks; Classification; Classification algorithms; CNN; Convolutional neural networks; Deep learning; Distributed generation; Electric power systems; fault classification and location; Fault currents; Fault detection; Fault location; Hybrid CNN-LSTM; Long short term memory; LSTM; Machine learning; Power transmission lines; Protection; Renewable energy sources; Smart grid; Smart grids; Smart sensors; Topology; Transmission line measurements; Transmission lines

A modern electric power system integrated with advanced technologies such as sensors and smart meters is referred to as a "smart grid," aimed at enhancing electrical power delivery efficiency and reliability. However, fault location and prediction can become challenging when dynamic fault...