• DocumentCode
    606585
  • Title

    Parametric identification by minimizing the squared residuals (Application to a photovoltaic cell)

  • Author

    Oukarfi, B. ; Dkhichi, F. ; Fakkar, A.

  • Author_Institution
    Electr. Eng. Dept., EEA & TI Lab., Mohammedia, Morocco
  • fYear
    2013
  • fDate
    7-9 March 2013
  • Firstpage
    40
  • Lastpage
    45
  • Abstract
    In this study we develop an algorithm of nonlinear programming to identify the structural parameters of a photovoltaic cell. This algorithm adjusts at best the parameters of the cell´s electrical model to the experimental measurements. Thus, to achieve this optimization, we minimize a sum of squared residuals by Gauss Newton´s Method which presents an interesting rate of convergence but with sensitivity to the initial conditions. To overcome this issue, we apply, beforehand, the Least Squares Method to the two distinct parts (linear and not linear) of the IPV=f(VPV) characteristic. This first phase allows us to improve the convergence of the algorithm but not its rate. Regarding the last issue we suggest a modified version of Gauss Newton´s algorithm.
  • Keywords
    least squares approximations; nonlinear programming; optimisation; photovoltaic cells; Gauss Newton method; least squares method; nonlinear programming; optimization; parametric identification; photovoltaic cell; squared residuals; Convergence; Current measurement; Manganese; Mathematical model; Noise; Optimized production technology; Temperature measurement; Gauss Newton; Identification; Least squares; photovoltaic Cell;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Renewable and Sustainable Energy Conference (IRSEC), 2013 International
  • Conference_Location
    Ouarzazate
  • Print_ISBN
    978-1-4673-6373-0
  • Type

    conf

  • DOI
    10.1109/IRSEC.2013.6529637
  • Filename
    6529637