Abstract
Real-life applications of intelligent systems that use neural networks require a high degree of success, usability and reliability. Power systems applications can benefit from such intelligent systems; particularly for voltage stabilization. Voltage instability in power distribution systems could lead to voltage collapse and thus power blackouts. This paper presents an intelligent system which detects voltage instability and classifies voltage output of an assumed power distribution system (PDS) as: stable, unstable or overload. The novelty of our work is the use of voltage output images as the input patterns to the neural network for training and generalizing purposes, thus providing a faster instability detection system that simulates a trained operator controlling and monitoring the 3-phase voltage output of the assumed PDS. Experimental results suggest that our method performs well and provides a fast and efficient system for voltage instability detection.
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Khashman, A., Buruncuk, K., Jabr, S. (2007). Intelligent Detection of Voltage Instability in Power Distribution Systems. In: Sandoval, F., Prieto, A., Cabestany, J., Graña, M. (eds) Computational and Ambient Intelligence. IWANN 2007. Lecture Notes in Computer Science, vol 4507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73007-1_105
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DOI: https://doi.org/10.1007/978-3-540-73007-1_105
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73006-4
Online ISBN: 978-3-540-73007-1
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