Neural network based calculation of short-circuit currents in three-phase systems

Abstract

In this paper we present a new method for short-circuit studies in three-phase systems based on the use of supervised learning neural net technology and the adaptive pattern recognition concept. Neural nets are used to assess the essential characteristics of short-circuit currents. The main motivation is to exploit generalization capabilities of neural nets to interpolate between training data, and thus to allow fast and direct assessment of short-circuit currents in cases of changing network topology and parameters. We present the results obtained in computer simulations using the example of a power system. © 1992.