Power system static security assessment using the Kohonen neural network classifier

The authors present the application of an artificial neural network, Kohonen's self-organizing feature map, for the classification of power system states. This classifier maps vectors of an <i>N</i>-dimensional space to a two-dimensional neural net in a nonlinear way, preserving the topological order of the input vectors. Therefore, secure operating points-that is, vectors inside the boundaries of the secure domain-are mapped to a different region of the neural map than insecure operating points. The application of this classifier to power system security assessment is presented, and simulation results are discussed


Published in:
IEEE Transactions on Power Systems, 7, 2, 865 - 72
Year:
1992
ISSN:
0885-8950
Keywords:
Note:
static security assessment;Kohonen neural network classifier;self-organizing feature map;power system;N-dimensional space;two-dimensional neural net;
Laboratories:




 Record created 2007-04-04, last modified 2018-03-18


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