@inproceedings{67f1593be6cd4dde8e904997d602b056,
title = "A wide area synchrophasor based ANN transient stability predictor for the Egyptian power system",
abstract = "This paper proposes an Artificial Neural Networks (ANN) based technique for transient stability prediction. The ANN makes use of the advent of Phasor Measurements Units (PMU) for real-time prediction. Rate of change of bus voltages and angles is used to train a two layers ANN. Potential of the proposed approach is tested using the Egyptian Power System (EPS) as a study system.",
keywords = "Artificial neural networks, Egyptian power system, Phasor measurements units, Synchrophasor, Transient stability prediction, Wide area applications",
author = "Fahd Hashiesh and Mostafa, \{Hossam E.\} and Ibrahim Helal and Mansour, \{Mohamed M.\}",
year = "2010",
doi = "10.1109/ISGTEUROPE.2010.5638923",
language = "English",
isbn = "9781424485109",
series = "IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe",
publisher = "IEEE Computer Society",
booktitle = "IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2010",
address = "United States",
}