| Peer-Reviewed

Modeling the Behavior of a Photovoltaic Generator Using a Four-Parameter Electrical Model

Received: 18 May 2022     Accepted: 8 June 2022     Published: 16 June 2022
Views:       Downloads:
Abstract

Photovoltaic solar energy consists of the direct conversion of sunlight into electricity by means of solar cells. These cells, electrically interconnected in series and/or in parallel, form the photovoltaic generator (GPV). The efficiency of the GPV is influenced by the irradiation and the temperature. In the intertropical zone, these two atmospheric factors vary rapidly and considerably influence the efficiency of the photovoltaic generator. This paper highlights the characteristics of the four-parameter cell photovoltaic generator when these two parameters (irradiance and/or temperature) vary rapidly. The simulation results obtained with the MATLAB/SIMULINK software show that with the four-parameter model the response time of the generator is proportional to the variation of the irradiance, i.e. the irradiance perturbation has an almost instantaneous effect on the current delivered by the photovoltaic generator and, when the temperature increases, the maximum power decreases, which confirms the correlation between these parameters. In fact, it can be seen that the developed model gives results close to the values provided by the manufacturers (five parameters) for amorphous, monocrystalline and polycrystalline cells with relative errors varying between 0.015 and 1.26%. The response time of the PV generator obtained with this model is 2 ms. The evaluation of the simulation method was also performed.

Published in Engineering Physics (Volume 6, Issue 1)
DOI 10.11648/j.ep.20220601.12
Page(s) 5-12
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Photovoltaic Generator, Irradiance, Temperature, Parameter

References
[1] W. De Soto. (2004). Improvement and Validation of a Model for Photovoltaic Array Performance. Madison: M. SC. thesis, University of Wisconsin-Madison.
[2] R. Chenni, A detailed modeling method for photovoltaic cells. Energy, 32, 1724–1730.
[3] D. KING (2004). Photovoltaic Array Performance Model. Albuquerque Nouveau-Mexique: Photovoltaic System R&D Department Sandia National Laboratories.
[4] Jimmy Royer (1998). LE POMPAGE PHOTOVOLTÏQUE: Manuel de cours à l’intention des ingénieurs et des techniciens [PHOTOVOLTIC PUMPING: A Course Manual for Engineers and Technicians]. Ottawa: Éditions MultiMondes.
[5] L. M. Ayompe (2010). Validated real-time energy models for small-scale grid-connected PV-systems. Energy (35), 4086-4091.
[6] L. Antonio, S. Hegedus. (2003). Handbook of Photovoltaic Science And Engeneering. John Wiley & Sons Ltd.
[7] S. R. Wenham (2007). Applied Photovoltaic’s Second Edition. TJ International Ltd.
[8] Townsend. A Method for Estimating the Long-Term Performance of Direct-Coupled Photovoltaic Systems. Madison: M. S. thesis, University of Wisconsin-Madison (1989).
[9] C. Hua, C. Shen, “Comparatives study of peak power tracking techniques for solar storage system”, IEEE Applied Power Electronics Conference, APEC’98, Vol. 2, 1998, pp. 679-685.
[10] M. Gradella Villalva, J. Raphael Gazoli, et E. Ruppert Filho, “Comprehensive approach to modeling and simulation of photovoltaic arrays”, IEEE Transactions on Power Electronics, Vol. 24, N°.5, may 2009, pp. 1-10.
[11] Nichiporuk Oleksiy, "Simulation, manufacture, analysis of photovoltaic cells with interdigital rear contacts", Doctoral Thesis, INSA Lyon, 2005, pp. 17-31.
[12] Observ’ER, “Solar photovoltaic barometer”, Solar Systems, April 2004, N°160, pp. 69-83.
[13] Sidibba, A, Ndiaye, D., El Bah, M. and Bouhamady, S. (2018) Analytical Modeling and Determination of the Characteristic Parameters of the Different Commercial Technologies of Photovoltaic Modules. Journal of Power and Energy Engineering, 6, 14-27. doi: 10.4236/jpee.2018.63002.
[14] Razagui, K. Abdeladim, S. Semaoui, A. Hadj Arab, S. Boulahchiche, Modeling the forecasted power of a photovoltaic generator using numerical weather prediction and radiative transfer models coupled with a behavioral electrical model, Energy Reports, Volume 6, Supplement 1,2020, Pages 57-62, ISSN 2352- 847, https://doi.org/10.1016/j.egyr.2019.08.018.
[15] D. M. Djanssou, A. Dadjé, A. Tom, N. Djongyang, "Improvement of the Dynamic Response of Robust Sliding Mode MPPT Controller-Based PSO Algorithm for PV Systems under Fast-Changing Atmospheric Conditions", International Journal of Photoenergy, vol. 2021, Article ID 6671133, 13 pages, 2021. https://doi.org/10.1155/2021/6671133
[16] P. I. S. E, “Studies of UEMOA and Cameroon energy profiles”, J2CM GESTION, France, 2005 pp. 16-23.
[17] World Solar Commission, “World Solar Program Implementation Mechanism”, MAISON DE L’UNESCO SC/EST - 1, rue Miollis 75732 Paris Cedex 15 – France, 1999, pp. 1-29.
[18] H. Yamarhita, K. Tamahashi, M. Michihim., A. Tsuyoshi, K. Amako, and M. Park, «A novel Simulation technique of the PV generation system using real weather conditions», in 2002 Proc. Power Conversion Con!, V01.2, pp. 839 444, April 2002.
[19] G. A. Vokas, A. V. Machias, and J. L. Souflis, “Computer modeling and parameters estimation for solar cells”, h 1991 Proe Medirerranean Electrotechnical Conf, v 0l. l. pp. 206 -209, May 1991.
[20] D. L. King, J. A. Kratochvil, W. E. Boyson, and W. I. Bower, Sandia National Laboratories. ‘Field experience with a new performance characterization procedure for photovoltaic arrays’.
[21] Outdoor testing of photovoltaic arrays in the Saharan region. Mohammed Sadok, Ahmed Mehdaoui. Research Unit of Renewable Energy in Saharan Middle (URER/MS), B. P. 478, drar 01000.
[22] Olivier Gergaud, “Energy modeling and economic optimization of a wind and photovoltaic production system coupled to the grid and associated with an accumulator”, Doctoral thesis from the École Normale Supérieure de Cachan December 9, 2002.
[23] D. M. Djanssou, A. Dadjé and N. Djongyang, Estimation of Photovoltaic Cell Parameters Using the Honey Badger Algorithm; International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249-8958 (Online), Volume-11 Issue-5, June 2022, pp. 105-108. DOI: 10.35940/ijeat.E3552.0611522.
Cite This Article
  • APA Style

    Abdouramani Dadjé, Fabrice Kwefeu Mbakop, Dieudonné Marcel Djanssou, Ruben Zieba Falama. (2022). Modeling the Behavior of a Photovoltaic Generator Using a Four-Parameter Electrical Model. Engineering Physics, 6(1), 5-12. https://doi.org/10.11648/j.ep.20220601.12

    Copy | Download

    ACS Style

    Abdouramani Dadjé; Fabrice Kwefeu Mbakop; Dieudonné Marcel Djanssou; Ruben Zieba Falama. Modeling the Behavior of a Photovoltaic Generator Using a Four-Parameter Electrical Model. Eng. Phys. 2022, 6(1), 5-12. doi: 10.11648/j.ep.20220601.12

    Copy | Download

    AMA Style

    Abdouramani Dadjé, Fabrice Kwefeu Mbakop, Dieudonné Marcel Djanssou, Ruben Zieba Falama. Modeling the Behavior of a Photovoltaic Generator Using a Four-Parameter Electrical Model. Eng Phys. 2022;6(1):5-12. doi: 10.11648/j.ep.20220601.12

    Copy | Download

  • @article{10.11648/j.ep.20220601.12,
      author = {Abdouramani Dadjé and Fabrice Kwefeu Mbakop and Dieudonné Marcel Djanssou and Ruben Zieba Falama},
      title = {Modeling the Behavior of a Photovoltaic Generator Using a Four-Parameter Electrical Model},
      journal = {Engineering Physics},
      volume = {6},
      number = {1},
      pages = {5-12},
      doi = {10.11648/j.ep.20220601.12},
      url = {https://doi.org/10.11648/j.ep.20220601.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ep.20220601.12},
      abstract = {Photovoltaic solar energy consists of the direct conversion of sunlight into electricity by means of solar cells. These cells, electrically interconnected in series and/or in parallel, form the photovoltaic generator (GPV). The efficiency of the GPV is influenced by the irradiation and the temperature. In the intertropical zone, these two atmospheric factors vary rapidly and considerably influence the efficiency of the photovoltaic generator. This paper highlights the characteristics of the four-parameter cell photovoltaic generator when these two parameters (irradiance and/or temperature) vary rapidly. The simulation results obtained with the MATLAB/SIMULINK software show that with the four-parameter model the response time of the generator is proportional to the variation of the irradiance, i.e. the irradiance perturbation has an almost instantaneous effect on the current delivered by the photovoltaic generator and, when the temperature increases, the maximum power decreases, which confirms the correlation between these parameters. In fact, it can be seen that the developed model gives results close to the values provided by the manufacturers (five parameters) for amorphous, monocrystalline and polycrystalline cells with relative errors varying between 0.015 and 1.26%. The response time of the PV generator obtained with this model is 2 ms. The evaluation of the simulation method was also performed.},
     year = {2022}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Modeling the Behavior of a Photovoltaic Generator Using a Four-Parameter Electrical Model
    AU  - Abdouramani Dadjé
    AU  - Fabrice Kwefeu Mbakop
    AU  - Dieudonné Marcel Djanssou
    AU  - Ruben Zieba Falama
    Y1  - 2022/06/16
    PY  - 2022
    N1  - https://doi.org/10.11648/j.ep.20220601.12
    DO  - 10.11648/j.ep.20220601.12
    T2  - Engineering Physics
    JF  - Engineering Physics
    JO  - Engineering Physics
    SP  - 5
    EP  - 12
    PB  - Science Publishing Group
    SN  - 2640-1029
    UR  - https://doi.org/10.11648/j.ep.20220601.12
    AB  - Photovoltaic solar energy consists of the direct conversion of sunlight into electricity by means of solar cells. These cells, electrically interconnected in series and/or in parallel, form the photovoltaic generator (GPV). The efficiency of the GPV is influenced by the irradiation and the temperature. In the intertropical zone, these two atmospheric factors vary rapidly and considerably influence the efficiency of the photovoltaic generator. This paper highlights the characteristics of the four-parameter cell photovoltaic generator when these two parameters (irradiance and/or temperature) vary rapidly. The simulation results obtained with the MATLAB/SIMULINK software show that with the four-parameter model the response time of the generator is proportional to the variation of the irradiance, i.e. the irradiance perturbation has an almost instantaneous effect on the current delivered by the photovoltaic generator and, when the temperature increases, the maximum power decreases, which confirms the correlation between these parameters. In fact, it can be seen that the developed model gives results close to the values provided by the manufacturers (five parameters) for amorphous, monocrystalline and polycrystalline cells with relative errors varying between 0.015 and 1.26%. The response time of the PV generator obtained with this model is 2 ms. The evaluation of the simulation method was also performed.
    VL  - 6
    IS  - 1
    ER  - 

    Copy | Download

Author Information
  • School of Geology and Mining Engineering, University of Ngaoundéré, Ngaoundéré, Cameroon

  • Department of Renewable Energy, National Advanced School of Engineering, University of Maroua (UMa), Maroua, Cameroon

  • Department of Renewable Energy, National Advanced School of Engineering, University of Maroua (UMa), Maroua, Cameroon

  • Faculty of Mines and Petroleum Industries, University of Maroua, Maroua, Cameroon

  • Sections