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Parameters identification of solar cell models using generalized oppositional teaching learning based optimization

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  • Chen, Xu
  • Yu, Kunjie
  • Du, Wenli
  • Zhao, Wenxiang
  • Liu, Guohai

Abstract

This paper presents a new optimization method called GOTLBO (generalized oppositional teaching learning based optimization) to identify parameters of solar cell models. GOTLBO employs generalized opposition-based learning to basic teaching learning based optimization through the initialization step and generation jumping so that the convergence speed is enhanced. The performance of GOTLBO is comprehensively evaluated in thirteen benchmark functions and two parameter identification problems of solar cell models, i.e., single diode model and double diode model. Simulation results indicate the excellent performance of GOTLBO compared with four well-known evolutionary algorithms and other parameter extraction techniques proposed in the literature.

Suggested Citation

  • Chen, Xu & Yu, Kunjie & Du, Wenli & Zhao, Wenxiang & Liu, Guohai, 2016. "Parameters identification of solar cell models using generalized oppositional teaching learning based optimization," Energy, Elsevier, vol. 99(C), pages 170-180.
    • Handle: RePEc:eee:energy:v:99:y:2016:i:c:p:170-180
    DOI: 10.1016/j.energy.2016.01.052
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    References listed on IDEAS

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    1. Jiang, Lian Lian & Maskell, Douglas L. & Patra, Jagdish C., 2013. "Parameter estimation of solar cells and modules using an improved adaptive differential evolution algorithm," Applied Energy, Elsevier, vol. 112(C), pages 185-193.
    2. Ishaque, Kashif & Salam, Zainal & Mekhilef, Saad & Shamsudin, Amir, 2012. "Parameter extraction of solar photovoltaic modules using penalty-based differential evolution," Applied Energy, Elsevier, vol. 99(C), pages 297-308.
    3. Askarzadeh, Alireza & Rezazadeh, Alireza, 2013. "Artificial bee swarm optimization algorithm for parameters identification of solar cell models," Applied Energy, Elsevier, vol. 102(C), pages 943-949.
    4. Oliva, Diego & Cuevas, Erik & Pajares, Gonzalo, 2014. "Parameter identification of solar cells using artificial bee colony optimization," Energy, Elsevier, vol. 72(C), pages 93-102.
    5. AlHajri, M.F. & El-Naggar, K.M. & AlRashidi, M.R. & Al-Othman, A.K., 2012. "Optimal extraction of solar cell parameters using pattern search," Renewable Energy, Elsevier, vol. 44(C), pages 238-245.
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