Estimation of Photovoltaic Cells Model Parameters using Particle Swarm Optimization

  • Vandana Khanna
  • B. K. Das
  • Dinesh Bisht
  • Vandana
  • P. K. Singh
Conference paper
Part of the Environmental Science and Engineering book series (ESE)


Swarm intelligence based technique has been used in this work for the estimation of parameters of photovoltaic cells using the two-diode model of the photovoltaic cell. Particle Swarm Optimization algorithm was used to fit the calculated current–voltage characteristics of the photovoltaic cells to the experimental one. The estimated parameters were the generated photocurrent, saturation currents, series resistance, shunt resistance and ideality factors. The proposed approach was validated using industrial photovoltaic cells.


Photovoltaic cell Particle swarm optimization algorithm Parameter estimation 


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  1. 1.
    K. Bouzidi, M. Chegaar, A. Bouhemadou, “Solar cells parameters evaluation considering the series and shunt resistance”, Solar Energy Materials and Solar Cells, 91(18), 1647–1651 (2007)CrossRefGoogle Scholar
  2. 2.
    M. Chegaar, Z. Ouennoughi, F. Guechi, “Extracting dc parameters of solar cells under illumination”, Vacuum, 75 (4), 367–372 (2004)CrossRefGoogle Scholar
  3. 3.
    M. Haouari-Merbah, M. Belhamel, I. Tobías, J.M. Ruiz, “Extraction and analysis of solar cell parameters from the illuminated current–voltage curve”, Solar Energy Materials and Solar Cells, 87 (1–4), 225-233 (2005), ISSN 0927-0248,  10.1016/j.solmat.2004.07.019.CrossRefGoogle Scholar
  4. 4.
    M. Tivanov, A. Patryn, N. Drozdov, A. Fedotov, A. Mazanik, “Determination of solar cell parameters from its current–voltage and spectral characteristics”, Solar Energy Materials and Solar Cells, 87 (1–4), 457-465 (2005), ISSN 0927-0248, 10.1016/j.solmat.2004.07.033.CrossRefGoogle Scholar
  5. 5.
    A. Ortiz-Conde, F.J. Garcia Sanchez, J. Muci, “New method to extract the model parameters of solar cells from the explicit analytic solutions of their illuminated I–V characteristics”, Solar Energy Materials and Solar Cells, 90 (3), 352–36(2006),1CrossRefGoogle Scholar
  6. 6.
    Joseph A Jervase, HadjBourdoucen and Ali Al-Lawati, “Solar cell parameter extraction using genetic algorithms”, Measurement Science and Technology,12,1922-1925 (2001)Google Scholar
  7. 7.
    M.R. AlRashidi, M.F. AlHajri, K.M. El-Naggar, A.K. Al-Othman, “A new estimation approach for determining the I–V characteristics of solar cells”, Solar Energy, 85 (7), 1543-1550 (2011)CrossRefGoogle Scholar
  8. 8.
    M.F. AlHajri, K.M. El-Naggar, M.R. AlRashidi, A.K. Al-Othman, “Optimal extraction of solar cell parameters using pattern search”, Renewable Energy,44,238-245 (2012)CrossRefGoogle Scholar
  9. 9.
    Hengsi Qin; Kimball, J.W., “Parameter determination of Photovoltaic Cells from field testing data using particle swarm optimization”,Power and Energy Conference at Illinois (PECI), 25-26 Feb. 2011 IEEE, pp.1-4(2011)Google Scholar
  10. 10.
    Bai, Qinghai. “Analysis of particle swarm optimization algorithm”, Computer and Information Science, 3 (1): 180(2010).Google Scholar
  11. 11.
    L. Sandrolini, M. Artioli, U. Reggiani, “Numerical method for the extraction of photovoltaic module double-diode model parameters through cluster analysis”, Applied Energy, 87 (2), 442 451 (2010)CrossRefGoogle Scholar
  12. 12.
    SilkeSteingrube, OtwinBreitenstein, Klaus Ramspeck, StefanGlunz, Andreas Schenk, and Pietro P. Altermatt, “Explanation of commonly observed shunt currents in c-Si solar cells by means of recombination statistics beyond the Shockley-Read-Hall approximation”, Journal of Applied Physics,110(1), 014515 - 014515-10 (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Vandana Khanna
    • 1
  • B. K. Das
    • 2
  • Dinesh Bisht
    • 2
  • Vandana
    • 3
  • P. K. Singh
    • 3
  1. 1.ITM UniversityGurgaonIndia
  2. 2.JIIT UniversityNoidaIndia
  3. 3.National Physical LaboratoryNew DelhiIndia

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