A transmission line fault locator based on Elman recurrent networks

In this paper, a transmission line fault location model which is based on an Elman recurrent network (ERN) has been presented for balanced and unbalanced short circuit faults. All fault situations with different inception times are implemented on a 380-kV prototype power system. Wavelet transform (WT) is used for selecting distinctive features about the faulty signals. The system has the advantages of utilizing single-end measurements, using both voltage and current signals. ERN is able to determine the fault location occurred on transmission line rapidly and correctly as an important alternative to standard feedforward back propagation networks (FFNs) and radial basis functions (RBFs) neural networks.

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