• DocumentCode
    3572658
  • Title

    Fault diagnostic method for PV array based on improved wavelet neural network algorithm

  • Author

    Xiao Li ; Pu Yang ; Jiangfan Ni ; Jing Zhao

  • Author_Institution
    Coll. of Autom. Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
  • fYear
    2014
  • Firstpage
    1171
  • Lastpage
    1175
  • Abstract
    As the key equipment in photovoltaic system, the operating reliability of PV array influences on the security and stability of photovoltaic system deeply. To diagnose the fault of PV array effectively, the paper proposes an improved wavelet neural network algorithm for fault diagnosis of PV array, in which uses Gaussian function as activation function and adds additional momentum method and adaptive learning rate method to the training algorithm. The proposed algorithm is applied to fault diagnosis of the actual PV array, the experimental results demonstrate the effectiveness of the algorithm.
  • Keywords
    Gaussian processes; fault diagnosis; photovoltaic cells; photovoltaic power systems; power engineering computing; solar cell arrays; wavelet neural nets; Gaussian function; PV array; adaptive learning rate method; fault diagnostic method; momentum method; photovoltaic system security; photovoltaic system stability; wavelet neural network algorithm; Arrays; Circuit faults; Fault diagnosis; Neural networks; Photovoltaic systems; Training; PV array; fault diagnosis; neural network; wavelet;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2014 11th World Congress on
  • Type

    conf

  • DOI
    10.1109/WCICA.2014.7052884
  • Filename
    7052884