Application of neural networks to direct stability analysis of power systems

Abstract

The feasibility of designing neural networks capable of computing the critical clearing times of power system faults is explored. Two distinct approaches are investigated, the patter recognition approach and the optimization approach. The theory of direct stability analysis of power systems is utilized is designing he input features of the pattern recognition approach, and the structure of the Hopfield optimization approach.<>