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Intelligent Detection of Voltage Instability in Power Distribution Systems.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Pandu Rangan, C.
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Sandoval, Francisco
Prieto, Alberto
Cabestany, Joan
Graña, Manuel
Khashman, Adnan
Source :
Computational & Ambient Intelligence; 2007, p870-877, 8p
Publication Year :
2007

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540730064
Database :
Complementary Index
Journal :
Computational & Ambient Intelligence
Publication Type :
Book
Accession number :
33147781
Full Text :
https://doi.org/10.1007/978-3-540-73007-1_105