Generalization of Transient Stability Solution using Neural Network Theory

Abstract

In this paper, we generalize an online transient stability solution technique using the backpropagation method of the neural network theory. The proposed solution technique can be used for general generator models which include controllers such as AVRs and governors, that have been difficult to deal with for the energy function method. The proposed method also can take into account alterations of network configurations and changes of the number of operating generators. Further, the relationship between input data and effects on the results in the neural network is considered.