IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v91y2012i1p395-404.html
   My bibliography  Save this article

A simple behavioural model for solar module electric characteristics based on the first order system step response for MPPT study and comparison

Author

Listed:
  • Amrouche, Badia
  • Guessoum, Abderrezak
  • Belhamel, Maiouf

Abstract

This paper proposes a simple behavioural model for photovoltaic modules. This model can be used to characterise current–voltage and power–voltage outputs of photovoltaic modules as a function of solar module temperature and solar radiation intensity. Such a model cannot only serve as a tool to study the I–V curve and its maximum power point characteristics but also to design photovoltaic power systems and power converters used for PV applications. It can also be used for performance rating. This model has first been developed to study the maximum power point characteristics by exploring the existing similarity between the photovoltaic module I–V characteristic and the step response of a first-order system. It has the advantage to use only parameters that are available on the data sheet. To construct the proposed model, measured I–V curves at different working conditions (solar radiation intensity and ambient temperature) were used, then other I–V characteristics corresponding to different working conditions have been used to validate it. The obtained results show a high degree of correspondence between the real outdoor measured I–V characteristics and those given by the developed model.

Suggested Citation

  • Amrouche, Badia & Guessoum, Abderrezak & Belhamel, Maiouf, 2012. "A simple behavioural model for solar module electric characteristics based on the first order system step response for MPPT study and comparison," Applied Energy, Elsevier, vol. 91(1), pages 395-404.
    • Handle: RePEc:eee:appene:v:91:y:2012:i:1:p:395-404
    DOI: 10.1016/j.apenergy.2011.09.036
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261911006416
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2011.09.036?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Celik, Ali Naci & Acikgoz, NasIr, 2007. "Modelling and experimental verification of the operating current of mono-crystalline photovoltaic modules using four- and five-parameter models," Applied Energy, Elsevier, vol. 84(1), pages 1-15, January.
    2. Sandrolini, L. & Artioli, M. & Reggiani, U., 2010. "Numerical method for the extraction of photovoltaic module double-diode model parameters through cluster analysis," Applied Energy, Elsevier, vol. 87(2), pages 442-451, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chellaswamy, C. & Ramesh, R., 2016. "Parameter extraction of solar cell models based on adaptive differential evolution algorithm," Renewable Energy, Elsevier, vol. 97(C), pages 823-837.
    2. Chi-Jeng Bai & Wei-Cheng Wang & Po-Wei Chen & Wen-Tong Chong, 2014. "System Integration of the Horizontal-Axis Wind Turbine: The Design of Turbine Blades with an Axial-Flux Permanent Magnet Generator," Energies, MDPI, vol. 7(11), pages 1-21, November.
    3. Kara Mostefa Khelil, Chérifa & Amrouche, Badia & Benyoucef, Abou soufiane & Kara, Kamel & Chouder, Aissa, 2020. "New Intelligent Fault Diagnosis (IFD) approach for grid-connected photovoltaic systems," Energy, Elsevier, vol. 211(C).
    4. Gao, Xian-Zhong & Hou, Zhong-Xi & Guo, Zheng & Chen, Xiao-Qian, 2015. "Reviews of methods to extract and store energy for solar-powered aircraft," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 96-108.
    5. Sánchez Reinoso, Carlos R. & Milone, Diego H. & Buitrago, Román H., 2013. "Simulation of photovoltaic centrals with dynamic shading," Applied Energy, Elsevier, vol. 103(C), pages 278-289.
    6. 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.
    7. Fathabadi, Hassan, 2015. "Lambert W function-based technique for tracking the maximum power point of PV modules connected in various configurations," Renewable Energy, Elsevier, vol. 74(C), pages 214-226.
    8. Salam, Zainal & Ahmed, Jubaer & Merugu, Benny S., 2013. "The application of soft computing methods for MPPT of PV system: A technological and status review," Applied Energy, Elsevier, vol. 107(C), pages 135-148.
    9. Fan, Yi & Wang, Pengjun & Heidari, Ali Asghar & Chen, Huiling & HamzaTurabieh, & Mafarja, Majdi, 2022. "Random reselection particle swarm optimization for optimal design of solar photovoltaic modules," Energy, Elsevier, vol. 239(PA).
    10. Evaldo C. Gouvêa & Pedro M. Sobrinho & Teófilo M. Souza, 2017. "Spectral Response of Polycrystalline Silicon Photovoltaic Cells under Real-Use Conditions," Energies, MDPI, vol. 10(8), pages 1-13, August.
    11. Ciprian Cristea & Maria Cristea & Dan Doru Micu & Andrei Ceclan & Radu-Adrian Tîrnovan & Florica Mioara Șerban, 2022. "Tridimensional Sustainability and Feasibility Assessment of Grid-Connected Solar Photovoltaic Systems Applied for the Technical University of Cluj-Napoca," Sustainability, MDPI, vol. 14(17), pages 1-23, August.
    12. Lo Brano, Valerio & Ciulla, Giuseppina, 2013. "An efficient analytical approach for obtaining a five parameters model of photovoltaic modules using only reference data," Applied Energy, Elsevier, vol. 111(C), pages 894-903.
    13. 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.
    14. Amrouche, Badia & Le Pivert, Xavier, 2014. "Artificial neural network based daily local forecasting for global solar radiation," Applied Energy, Elsevier, vol. 130(C), pages 333-341.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Humada, Ali M. & Hojabri, Mojgan & Mekhilef, Saad & Hamada, Hussein M., 2016. "Solar cell parameters extraction based on single and double-diode models: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 494-509.
    2. Piliougine, Michel & Elizondo, David & Mora-López, Llanos & Sidrach-de-Cardona, Mariano, 2013. "Multilayer perceptron applied to the estimation of the influence of the solar spectral distribution on thin-film photovoltaic modules," Applied Energy, Elsevier, vol. 112(C), pages 610-617.
    3. Bonanno, F. & Capizzi, G. & Graditi, G. & Napoli, C. & Tina, G.M., 2012. "A radial basis function neural network based approach for the electrical characteristics estimation of a photovoltaic module," Applied Energy, Elsevier, vol. 97(C), pages 956-961.
    4. Lo Brano, Valerio & Ciulla, Giuseppina, 2013. "An efficient analytical approach for obtaining a five parameters model of photovoltaic modules using only reference data," Applied Energy, Elsevier, vol. 111(C), pages 894-903.
    5. Huang, Chao & Bensoussan, Alain & Edesess, Michael & Tsui, Kwok L., 2016. "Improvement in artificial neural network-based estimation of grid connected photovoltaic power output," Renewable Energy, Elsevier, vol. 97(C), pages 838-848.
    6. Chin, Vun Jack & Salam, Zainal & Ishaque, Kashif, 2015. "Cell modelling and model parameters estimation techniques for photovoltaic simulator application: A review," Applied Energy, Elsevier, vol. 154(C), pages 500-519.
    7. Orioli, Aldo & Di Gangi, Alessandra, 2013. "A procedure to calculate the five-parameter model of crystalline silicon photovoltaic modules on the basis of the tabular performance data," Applied Energy, Elsevier, vol. 102(C), pages 1160-1177.
    8. Samuel R. Fahim & Hany M. Hasanien & Rania A. Turky & Shady H. E. Abdel Aleem & Martin Ćalasan, 2022. "A Comprehensive Review of Photovoltaic Modules Models and Algorithms Used in Parameter Extraction," Energies, MDPI, vol. 15(23), pages 1-56, November.
    9. 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.
    10. Hasan, M.A. & Parida, S.K., 2016. "An overview of solar photovoltaic panel modeling based on analytical and experimental viewpoint," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 75-83.
    11. Shabani, Masoume & Mahmoudimehr, Javad, 2019. "Influence of climatological data records on design of a standalone hybrid PV-hydroelectric power system," Renewable Energy, Elsevier, vol. 141(C), pages 181-194.
    12. Mahmoudimehr, Javad & Shabani, Masoume, 2018. "Optimal design of hybrid photovoltaic-hydroelectric standalone energy system for north and south of Iran," Renewable Energy, Elsevier, vol. 115(C), pages 238-251.
    13. Tuyen Nguyen-Duc & Huy Nguyen-Duc & Thinh Le-Viet & Hirotaka Takano, 2020. "Single-Diode Models of PV Modules: A Comparison of Conventional Approaches and Proposal of a Novel Model," Energies, MDPI, vol. 13(6), pages 1-22, March.
    14. Jordehi, A. Rezaee, 2016. "Parameter estimation of solar photovoltaic (PV) cells: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 354-371.
    15. Abbassi, Rabeh & Abbassi, Abdelkader & Jemli, Mohamed & Chebbi, Souad, 2018. "Identification of unknown parameters of solar cell models: A comprehensive overview of available approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 453-474.
    16. Aurel Gontean & Septimiu Lica & Szilard Bularka & Roland Szabo & Dan Lascu, 2017. "A Novel High Accuracy PV Cell Model Including Self Heating and Parameter Variation," Energies, MDPI, vol. 11(1), pages 1-21, December.
    17. Quesada, B. & Sánchez, C. & Cañada, J. & Royo, R. & Payá, J., 2011. "Experimental results and simulation with TRNSYS of a 7.2Â kWp grid-connected photovoltaic system," Applied Energy, Elsevier, vol. 88(5), pages 1772-1783, May.
    18. Efstratios Batzelis, 2019. "Non-Iterative Methods for the Extraction of the Single-Diode Model Parameters of Photovoltaic Modules: A Review and Comparative Assessment," Energies, MDPI, vol. 12(3), pages 1-26, January.
    19. Mansouri, Majdi & Hajji, Mansour & Trabelsi, Mohamed & Harkat, Mohamed Faouzi & Al-khazraji, Ayman & Livera, Andreas & Nounou, Hazem & Nounou, Mohamed, 2018. "An effective statistical fault detection technique for grid connected photovoltaic systems based on an improved generalized likelihood ratio test," Energy, Elsevier, vol. 159(C), pages 842-856.
    20. Li, W. & Paul, M.C. & Baig, H. & Siviter, J. & Montecucco, A. & Mallick, T.K. & Knox, A.R., 2019. "A three-point-based electrical model and its application in a photovoltaic thermal hybrid roof-top system with crossed compound parabolic concentrator," Renewable Energy, Elsevier, vol. 130(C), pages 400-415.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:91:y:2012:i:1:p:395-404. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.