JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (5): 118-122.doi: 10.6040/j.issn.1672-3961.0.2017.183

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Fault diagnostic method for micro-grid based on wavelet singularity entropy and SOM neural network

QIU Lu1, YE Yinzhong2*, JIANG Chundi3   

  1. 1. Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China;
    2. School of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai 201418, China;
    3. College of Electrical and Information Engineering, Quzhou University, Quzhou 324000, Zhejiang, China
  • Received:2017-02-10 Online:2017-10-20 Published:2017-02-10

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Abstract: According to the diversity of micro grids topology, through analyzing the theories of wavelet transform, singular value decomposition and extended shannon-entropy, the wavelet singular entropy could measure the fault signal. A fault diagnosis method for the micro grid system was proposed by integrating the wavelet singular entropy with the self organizing feature map(SOM)neural network. A micro grid fault simulation system was established by PSCAD4.2. The simulation results proved that the proposed diagnosis method was insensitive to the location and the time fault occurs, which had strong adaptability to the variation in structure topology.

Key words: SOM neural network, fault diagnosis, micro-grid, wavelet singular entropy, topology structure

CLC Number: 

  • TP18
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