文件名称:ERN
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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.
(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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ERN.pdf