IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v60y2016icp75-83.html
   My bibliography  Save this article

An overview of solar photovoltaic panel modeling based on analytical and experimental viewpoint

Author

Listed:
  • Hasan, M.A.
  • Parida, S.K.

Abstract

This paper provides a comprehensive review of available models of photovoltaic panel. Modeling and simulation of photovoltaic panel (PV) in virtual environment helps in designing and performance analysis of solar based power system. This paper analyses the currently available models from two different aspects. First aspect is based on electrical characteristics of PV panel using electrical equivalent circuit or through set of mathematical equations. The other aspect is based on the characteristics of PV panel under different environmental conditions. Environmental conditions include varying temperature and non-uniform solar irradiance due to partial shading. Varying environmental conditions causes continuous change in PV panel operating point corresponding to Maximum Power Point (MPP). Therefore an accurate PV panel model built with robust control that includes these environmental conditions will certainly improve the overall performance of the solar power plant. This paper can help researchers in selecting a specific objective based PV panel model out of several models available in literature.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:rensus:v:60:y:2016:i:c:p:75-83
    DOI: 10.1016/j.rser.2016.01.087
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032116001179
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2016.01.087?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. Ciulla, Giuseppina & Lo Brano, Valerio & Di Dio, Vincenzo & Cipriani, Giovanni, 2014. "A comparison of different one-diode models for the representation of I–V characteristic of a PV cell," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 684-696.
    2. Wang, Yaw-Juen & Hsu, Po-Chun, 2011. "An investigation on partial shading of PV modules with different connection configurations of PV cells," Energy, Elsevier, vol. 36(5), pages 3069-3078.
    3. Silvestre, S. & Boronat, A. & Chouder, A., 2009. "Study of bypass diodes configuration on PV modules," Applied Energy, Elsevier, vol. 86(9), pages 1632-1640, September.
    4. 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.
    5. Parida, Bhubaneswari & Iniyan, S. & Goic, Ranko, 2011. "A review of solar photovoltaic technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(3), pages 1625-1636, April.
    6. 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. Haidar Islam & Saad Mekhilef & Noraisyah Binti Mohamed Shah & Tey Kok Soon & Mehdi Seyedmahmousian & Ben Horan & Alex Stojcevski, 2018. "Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems," Energies, MDPI, vol. 11(2), pages 1-24, February.
    2. Sai Krishna, G. & Moger, Tukaram, 2021. "A novel adaptive dynamic photovoltaic reconfiguration system to mitigate mismatch effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    3. Gu, Xufei & Ying, Zhi & Zheng, Xiaoyuan & Dou, Binlin & Cui, Guomin, 2023. "Photovoltaic-based energy system coupled with energy storage for all-day stable PEM electrolytic hydrogen production," Renewable Energy, Elsevier, vol. 209(C), pages 53-62.
    4. Amir, A. & Amir, A. & Selvaraj, J. & Rahim, N.A., 2016. "Study of the MPP tracking algorithms: Focusing the numerical method techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 350-371.
    5. Kumar, Manish & Kumar, Arun, 2017. "Performance assessment and degradation analysis of solar photovoltaic technologies: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 554-587.
    6. Gonçalves, Juliana E. & van Hooff, Twan & Saelens, Dirk, 2021. "Simulating building integrated photovoltaic facades: Comparison to experimental data and evaluation of modelling complexity," Applied Energy, Elsevier, vol. 281(C).
    7. Skoko, Sasa M. & Ciric, Rade M., 2017. "Laboratory exercises of photovoltaic systems–Review of the equpment, methodology, trials and results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 293-303.
    8. Yadav, Anurag Singh & Mukherjee, V., 2021. "Conventional and advanced PV array configurations to extract maximum power under partial shading conditions: A review," Renewable Energy, Elsevier, vol. 178(C), pages 977-1005.

    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. 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.
    2. Ma, Tao & Yang, Hongxing & Lu, Lin, 2014. "Solar photovoltaic system modeling and performance prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 304-315.
    3. Singh, Rashmi & Sharma, Madhu & Rawat, Rahul & Banerjee, Chandan, 2018. "An assessment of series resistance estimation techniques for different silicon based SPV modules," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 199-216.
    4. 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.
    5. Jena, Debashisha & Ramana, Vanjari Venkata, 2015. "Modeling of photovoltaic system for uniform and non-uniform irradiance: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 400-417.
    6. Meng, Zhuo & Zhao, Yiman & Tang, Shiqing & Sun, Yize, 2020. "An efficient datasheet-based parameters extraction method for two-diode photovoltaic cell and cells model," Renewable Energy, Elsevier, vol. 153(C), pages 1174-1182.
    7. 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.
    8. 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.
    9. Kumar, Manish & Kumar, Arun, 2017. "Performance assessment and degradation analysis of solar photovoltaic technologies: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 554-587.
    10. Ghani, F. & Rosengarten, G. & Duke, M. & Carson, J.K., 2014. "The numerical calculation of single-diode solar-cell modelling parameters," Renewable Energy, Elsevier, vol. 72(C), pages 105-112.
    11. Chin, Vun Jack & Salam, Zainal, 2019. "A New Three-point-based Approach for the Parameter Extraction of Photovoltaic Cells," Applied Energy, Elsevier, vol. 237(C), pages 519-533.
    12. Pareek, Smita & Dahiya, Ratna, 2016. "Enhanced power generation of partial shaded photovoltaic fields by forecasting the interconnection of modules," Energy, Elsevier, vol. 95(C), pages 561-572.
    13. Pillai, Dhanup S. & Rajasekar, N., 2018. "Metaheuristic algorithms for PV parameter identification: A comprehensive review with an application to threshold setting for fault detection in PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3503-3525.
    14. 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.
    15. Belhachat, Faiza & Larbes, Cherif, 2017. "Global maximum power point tracking based on ANFIS approach for PV array configurations under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 875-889.
    16. Qamar Navid & Ahmed Hassan & Abbas Ahmad Fardoun & Rashad Ramzan & Abdulrahman Alraeesi, 2021. "Fault Diagnostic Methodologies for Utility-Scale Photovoltaic Power Plants: A State of the Art Review," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    17. Woo Gyun Shin & Suk Whan Ko & Hyung Jun Song & Young Chul Ju & Hye Mi Hwang & Gi Hwan Kang, 2018. "Origin of Bypass Diode Fault in c-Si Photovoltaic Modules: Leakage Current under High Surrounding Temperature," Energies, MDPI, vol. 11(9), pages 1-11, September.
    18. 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.
    19. Muangkote, Nipotepat & Sunat, Khamron & Chiewchanwattana, Sirapat & Kaiwinit, Sirilak, 2019. "An advanced onlooker-ranking-based adaptive differential evolution to extract the parameters of solar cell models," Renewable Energy, Elsevier, vol. 134(C), pages 1129-1147.
    20. Li, Shuijia & Gong, Wenyin & Gu, Qiong, 2021. "A comprehensive survey on meta-heuristic algorithms for parameter extraction of photovoltaic models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).

    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:rensus:v:60:y:2016:i:c:p:75-83. 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/600126/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.