• DocumentCode
    2621215
  • Title

    Statistical Analysis and Structure Optimization of Large Photovoltaic Module

  • Author

    Thankalekshmi, Ratheesh R. ; Qiu, Qinru ; Man, K.I.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Binghamton Univ., Binghamton, NY, USA
  • fYear
    2010
  • fDate
    21-23 May 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    There has been an increasing interest in powering electronic systems using solar energy. Designers are seeking for techniques to manufacture solar panels using low cost material in a massive scale. This will likely lead to wide process variation and hence unreliable performance. This paper considers the impact of the process variations on the output power of large Photovoltaic (PV) module by modeling each PV cell as a current source whose short circuit current is a normal random variable. The probability distribution of the overall output power of an NxM PV module is analytically derived. The proposed statistical analysis technique will enable the designer to predict the maximum output power of a PV module for a given confidence level. This analysis also reveals that, when the size and the manufacturing technology are given, the efficiency of a PV module is determined by its topology. The proposed power prediction model can be applied to find the optimal structure of the PV module that maximizes the energy harvesting rate at the given confidence level.
  • Keywords
    optimisation; solar cells; statistical analysis; PV cell; electronic systems; energy harvesting; photovoltaic module; short circuit current; statistical analysis; structure optimization; Costs; Manufacturing; Photovoltaic systems; Power generation; Probability distribution; Random variables; Short circuit currents; Solar energy; Solar power generation; Statistical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Future Information Technology (FutureTech), 2010 5th International Conference on
  • Conference_Location
    Busan
  • Print_ISBN
    978-1-4244-6948-2
  • Type

    conf

  • DOI
    10.1109/FUTURETECH.2010.5482687
  • Filename
    5482687