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Extraction of uncertain parameters of a single-diode model for a photovoltaic panel using lightning attachment procedure optimization

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Abstract

The aim of this work is to improve the estimation of parameters of solar photovoltaic models. An approach based on lightning attachment procedure optimization, which takes into account the uncertainties of measurements, is proposed. The approach includes three steps: the extraction of the parameters in a conventional manner, the determination of the partial uncertainties of all the parameters, and finally the determination of the instantaneous parameters based on the results of the first two steps. To validate the proposed theoretical developments, the approach is applied to four different photovoltaic parameter estimation problems. The results obtained are compared with those given by well-established algorithms to confirm the effectiveness of the proposed method, revealing that the proposed method exhibits very effective performance with a root-mean-square error on the order of 1 × 10−17, compared with 1 × 10−4 for existing literature methods.

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References

  1. Chegaar, M., Ouennoughi, Z., Guechi, F.: Extracting dc parameters of solar cells under illumination. Vacuum 75, 367–372 (2004)

    Article  Google Scholar 

  2. Kennerud, K.L.: Analysis of performance degradation in CdS solar cells. IEEE Trans. Aerosp. Electron. Syst. AES–5(6), 912–917 (1969)

    Article  Google Scholar 

  3. Lun, S., et al.: A new explicit I-V model of a solar cell based on Taylor’s series expansion. Sol. Energy 94, 221–232 (2013)

    Article  Google Scholar 

  4. Easwarakhanthan, T., et al.: Nonlinear minimization algorithm for determining the solar cell parameter with microcomputers. Int. J. Sustain. Energy 4(1), 1–12 (1986)

    Google Scholar 

  5. Cabestany, J., Castaiier, L.: Evaluation of solar cell parameters by nonlinear algorithms. J. Phys. D Appl. Phys. 16, 2547–2558 (1983)

    Article  Google Scholar 

  6. Abdul Hamid, N.F. et al. (2013) Solar cell parameters extraction using particle swarm optimization algorithm. In: 2013 IEEE Conference on Clean Energy and Technology (CEAT)

  7. El-Naggar, K.M., et al.: Simulated annealing algorithm for photovoltaic parameters identification. Sol. Energy 86, 266–274 (2012)

    Article  Google Scholar 

  8. Patel, S.J., et al.: Solar cell parameters extraction from a current-voltage characteristic using genetic algorithm. J. Nano Electron. Phys. 5(2), 02008(3pp) (2013)

    Google Scholar 

  9. AlHajri, M.F., et al.: Optimal extraction of solar cell parameters using pattern search. Renew. Energy 44, 238–245 (2012)

    Article  Google Scholar 

  10. Niu, Q., Zhang, L., Li, K.: A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells. Energy Convers. Manag. 86, 1173–1185 (2014)

    Article  Google Scholar 

  11. Oliva, D., Cuevas, E., Pajares, G.: Parameter identification of solar cells using artificial bee colony optimization. Energy 72, 93–102 (2014)

    Article  Google Scholar 

  12. Yuan, X., He, Y., Liu, L.: Parameter extraction of solar cell models using chaotic asexual reproduction optimization. Neural Comput. Appl. 26, 1227–1239 (2015)

    Article  Google Scholar 

  13. Chellaswamy, C., Ramesh, R.: Parameter extraction of solar cell models based on adaptive differential evolution algorithm. Renew. Energy 97, 823–837 (2016)

    Article  Google Scholar 

  14. Xiong, G., et al.: Application of symbiotic organisms search algorithm for parameter extraction of solar cell models. Appl. Sci. 8, 2155 (2018). https://doi.org/10.3390/app8112155

    Article  Google Scholar 

  15. Gao, X., et al.: Parameter extraction of solar cell models using improved shuffled complex evolution algorithm. Energy Convers. Manag. 157, 460–479 (2018)

    Article  Google Scholar 

  16. Beigia, A.M., Maroosi, A.: Parameter identification for solar cells and module using a Hybrid Firefly and Pattern Search Algorithms. Sol. Energy 171, 435–446 (2018)

    Article  Google Scholar 

  17. Yu, K., et al.: Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models. Appl. Energy 226, 408–422 (2018)

    Article  Google Scholar 

  18. Louzazni, M., et al.: Metaheuristic algorithm for photovoltaic parameters: comparative study and prediction with a firefly algorithm. Appl. Sci. 8, 339 (2018). https://doi.org/10.3390/app8030339

    Article  Google Scholar 

  19. Kanimozhi Harish Kumar, G.: Modeling of solar cell under different conditions by Ant Lion Optimizer with LambertW function. Soft Comput. Appl. (2018). https://doi.org/10.1016/j.asoc.2018.06.025

    Article  Google Scholar 

  20. Merchaoui, M., et al.: Particle swarm optimisation with adaptive mutation strategy for photovoltaic solar cell/module parameter extraction. Energy Convers. Manag. 175, 151–163 (2018)

    Article  Google Scholar 

  21. Kang, T.: A novel improved cuckoo search algorithm for parameter estimation of photovoltaic (PV) models. Energies 11, 1060 (2018). https://doi.org/10.3390/en11051060

    Article  Google Scholar 

  22. Gao, X., et al.: Performance comparison of exponential, Lambert W function and Special Trans function based single diode solar cell models. Energy Convers. Manag. 171, 1822–1842 (2018)

    Article  Google Scholar 

  23. Li, Shuijia, et al.: Parameter extraction of photovoltaic models using an improved teachinglearning-based optimization. Energy Convers. Manag. 186, 293–305 (2019)

    Article  Google Scholar 

  24. Muangkote, N., et al.: An advanced onlooker-ranking-based adaptive differential evolution to extract the parameters of solar cell models. Renew. Energy 134, 1129–1147 (2019)

    Article  Google Scholar 

  25. Chena, X., Yu, K.: Hybridizing cuckoo search algorithm with biogeography-based optimization for estimating photovoltaic model parameters. Sol. Energy 180, 192–206 (2019)

    Article  Google Scholar 

  26. Chin, V.J., Salam, Z.: A new three-point-based approach for the parameter extraction of photovoltaic cells. Appl. Energy 237, 519–533 (2019)

    Article  Google Scholar 

  27. Easwarakhanthan, T., et al.: Nonlinear minimization algorithm for determining the solar cell parameters with microcomputers. Int. J. Solar Energy 4, 1–12 (1986)

    Article  Google Scholar 

  28. Tong, N.T., Pora, W.: A parameter extraction technique exploiting intrinsic properties of solar cells. Appl. Energy 176, 104–115 (2016)

    Article  Google Scholar 

  29. Wang, Y., Jiang, X.: An enhanced lightning attachment procedure optimization algorithm. Algorithms 12, 134 (2019). https://doi.org/10.3390/a12070134

    Article  MathSciNet  Google Scholar 

  30. Fouroghi, A.: Lightning Attachment Procedure Optimization (LAPO) source codes demo version 1.0. https://www.mathworks.com/matlabcentral/fileexchange/64459-lapo. Accessed 19 Sep 2017

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Correspondence to Ramzi Ben Messaoud.

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Ben Messaoud, R. Extraction of uncertain parameters of a single-diode model for a photovoltaic panel using lightning attachment procedure optimization. J Comput Electron 19, 1192–1202 (2020). https://doi.org/10.1007/s10825-020-01500-x

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