• DocumentCode
    2603721
  • Title

    Line losses calculation in distribution network based on RBF neural network optimized by hierarchical GA

  • Author

    Feng, Ni ; Jianming, Yu

  • Author_Institution
    Xi´´an Univ. of Technol., Xi´´an, China
  • fYear
    2009
  • fDate
    6-7 April 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this paper, we propose a practical method of calculating line losses in distribution network based on RBF neural network (RBFNN) optimized by hierarchical genetic algorithm (HGA). The first step is to determine three parameters of RBFNN, namely the number of hidden layer nodes, the width and the center of the basis function. In the second step, RBFNN is adopted to map the complex nonlinear relation between energy losses and characteristic parameters of distribution net so that the net can learn the trend of energy losses under varying distribution net structure and operation parameters. The simulation results have verified that the method presented is reliable and effective.
  • Keywords
    distribution networks; genetic algorithms; radial basis function networks; distribution network; hidden layer nodes; hierarchical genetic algorithm; line losses; radial basis function neural networks; Artificial neural networks; Computer networks; Energy loss; Feedforward neural networks; Feedforward systems; Mathematical model; Network topology; Neural networks; Optimization methods; Radial basis function networks; Distribution network; HGA; Line losses; RBFNN;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4934-7
  • Type

    conf

  • DOI
    10.1109/SUPERGEN.2009.5348236
  • Filename
    5348236