The artificial neural network is a powerful tool for the detection of the transmission line faults due to its ability to differentiate between various patterns. In this paper, simulation of power system under normal and faulty conditions are carried out using electromagnetic transient program. The voltage and current waveforms at the relay location for normal and fault conditions are extracted. The waveforms obtained are preprocessed in order to improve the performance of the neural network used. Three neural networks are built one for fault detection, one for fault type and a third for fault location. The proposed technique is tested with different types of faults and successive decision was reached.
El Safty, S., El Dessouki, H., & El Sawaf, M. (2021). Artificial Neural Network Fault Detection for Transmission Line Protection.. MEJ- Mansoura Engineering Journal, 29(3), 15-18. doi: 10.21608/bfemu.2021.140365
MLA
S. M. El Safty; H. El Dessouki; M. El Sawaf. "Artificial Neural Network Fault Detection for Transmission Line Protection.". MEJ- Mansoura Engineering Journal, 29, 3, 2021, 15-18. doi: 10.21608/bfemu.2021.140365
HARVARD
El Safty, S., El Dessouki, H., El Sawaf, M. (2021). 'Artificial Neural Network Fault Detection for Transmission Line Protection.', MEJ- Mansoura Engineering Journal, 29(3), pp. 15-18. doi: 10.21608/bfemu.2021.140365
VANCOUVER
El Safty, S., El Dessouki, H., El Sawaf, M. Artificial Neural Network Fault Detection for Transmission Line Protection.. MEJ- Mansoura Engineering Journal, 2021; 29(3): 15-18. doi: 10.21608/bfemu.2021.140365
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