Volume 04: Proceedings of 11th International Conference on Applied Energy, Part 3, Sweden, 2019

Fault Diagnosis Of Wavelet Neural Network In Distribution Network Based On D-pmu Measurement Information Yong Xu, Xiangyu Kong, Ligang Zhao, Haiqing Cai


In order to improve the reliability and continuity of smart distribution network, the wavelet neural network (WNN) fault diagnosis method based on distributed phasor measurement units (D-PMU) measurement information has been presented in this paper. Firstly, the D-PMU uploads the collected local data to the main station system, and obtains signals such as voltage and current from the main station, constructed the feature signal after the wavelet packet decomposition and as the input signals of the neural network for algorithm training, and output the training result after satisfying the error requirement, accomplish fault diagnosis. Finally, the effectiveness of the algorithm by simulation analysis using MATLAB software is verified.

Keywords D-PMU, distribution network, neural network, fault diagnosis

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