Transient stability assessment by a new artificial neural network

The problem of transient stability assessment and its difficulties are explained. Then application of a new neural network for evaluation of transient stability is described. This neural network has a new architecture with a novel functional expansion learning algorithm. The proposed neural network is applied for determination of the critical clearing time in a disturbed power system. Obtained results from this neural network for IEEE 30 and 118 bus test systems are mentioned, which confirm the validity of the developed approach. Also, a comparison between the proposed neural network and a multilayer perceptron with standard error backpropagation learning is presented, which indicates the efficiency of the proposed neural network.