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Application of Neural-Net Computing to Transient Stability Assessment and Enhancement of Electric Power Systems
Yugoslav journal of operations research, Tome 3 (1993) no. 2, p. 199 Cet article a éte moissonné depuis la source eLibrary of Mathematical Institute of the Serbian Academy of Sciences and Arts

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This paper describes some application of artificial neural networks in electric power systems. The concept of adaptive pattern recognition and neural networks in the process of recognizing and classifying patterns is explained. The Generalized Delta Rule and the Functional Link et architectures of neural nets and the unsupervised/supervised learning concept are discussed. Generalization capabilities of neural nets are illustrated in applications on unstable machine identification, calculation of voltage dips and calculation of generation shedding requirements.
Keywords: short term system dynamics, transient stability, security assessment, neural-nets, adaptive pattern recognition 
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     author = {Miodrag {\DJ}ukanovi\'c and Mirko Mili\'c and Dejan J. \v{S}obaji\'c and Yoh-Han Pao},
     title = {Application of {Neural-Net} {Computing} to {Transient} {Stability} {Assessment} and {Enhancement} of {Electric} {Power} {Systems}},
     journal = {Yugoslav journal of operations research},
     pages = {199 },
     year = {1993},
     volume = {3},
     number = {2},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/YJOR_1993_3_2_a4/}
}
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Miodrag Đukanović; Mirko Milić; Dejan J. Šobajić; Yoh-Han Pao. Application of Neural-Net Computing to Transient Stability Assessment and Enhancement of Electric Power Systems. Yugoslav journal of operations research, Tome 3 (1993) no. 2, p. 199 . http://geodesic.mathdoc.fr/item/YJOR_1993_3_2_a4/