Abstract

This paper presents an automatic security boundary visualization procedure using neural networks. A systematic method for data generation is developed to generate a database for neural network training. Neural networks are used to map the relationship between the precontingency operating parameters and the postcontingency performance measure. Genetic algorithms are used to select best subset of precontingency operating parameters to be used as neural network inputs. A visualization algorithm is developed to draw the boundary. The boundary for a sample system is given.

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