IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v36y2014icp304-315.html
   My bibliography  Save this article

Solar photovoltaic system modeling and performance prediction

Author

Listed:
  • Ma, Tao
  • Yang, Hongxing
  • Lu, Lin

Abstract

A simulation model for modeling photovoltaic (PV) system power generation and performance prediction is described in this paper. First, a comprehensive literature review of simulation models for PV devices and determination methods was conducted. The well-known five-parameter model was selected for the present study, and solved using a novel combination technique which integrated an algebraic simultaneous calculation of the parameters at standard test conditions (STC) with an analytical determination of the parameters under real operating conditions. In addition, the simulation performance of the model was compared with other models, and further validated by outdoor tests, which indicate that the proposed model fits well the entire set of experimental field test I–V curves of the PV module, especially at the characteristic points. After validation, this model was employed to predict the PV system power output under real conditions. The results show that the predictions agree very well with the PV plant field collected data. Thus, the operating performance of a standalone PV system located on a remote island in Hong Kong has been further evaluated with the aid of this model. It is found that the PV array power output is restricted by the status of the battery bank. This research demonstrates that the PV simulation model developed during the study is simple, but very helpful to PV system engineers in understanding the I–V curves and for accurately predicting PV system power production under outdoor conditions.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:rensus:v:36:y:2014:i:c:p:304-315
    DOI: 10.1016/j.rser.2014.04.057
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032114002950
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2014.04.057?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. 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.
    2. Chenni, R. & Makhlouf, M. & Kerbache, T. & Bouzid, A., 2007. "A detailed modeling method for photovoltaic cells," Energy, Elsevier, vol. 32(9), pages 1724-1730.
    3. Ma, Tao & Yang, Hongxing & Lu, Lin & Peng, Jinqing, 2014. "Technical feasibility study on a standalone hybrid solar-wind system with pumped hydro storage for a remote island in Hong Kong," Renewable Energy, Elsevier, vol. 69(C), pages 7-15.
    4. 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.
    5. Almonacid, F. & Rus, C. & Hontoria, L. & Muñoz, F.J., 2010. "Characterisation of PV CIS module by artificial neural networks. A comparative study with other methods," Renewable Energy, Elsevier, vol. 35(5), pages 973-980.
    6. Almonacid, F. & Rus, C. & Hontoria, L. & Fuentes, M. & Nofuentes, G., 2009. "Characterisation of Si-crystalline PV modules by artificial neural networks," Renewable Energy, Elsevier, vol. 34(4), pages 941-949.
    7. 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.
    8. Ahmad, Salsabila & Kadir, Mohd Zainal Abidin Ab & Shafie, Suhaidi, 2011. "Current perspective of the renewable energy development in Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(2), pages 897-904, February.
    9. de Blas, M.A & Torres, J.L & Prieto, E & Garcı́a, A, 2002. "Selecting a suitable model for characterizing photovoltaic devices," Renewable Energy, Elsevier, vol. 25(3), pages 371-380.
    10. Ma, Tao & Yang, Hongxing & Lu, Lin, 2014. "A feasibility study of a stand-alone hybrid solar–wind–battery system for a remote island," Applied Energy, Elsevier, vol. 121(C), pages 149-158.
    11. Ma, Tao & Yang, Hongxing & Lu, Lin, 2013. "Performance evaluation of a stand-alone photovoltaic system on an isolated island in Hong Kong," Applied Energy, Elsevier, vol. 112(C), pages 663-672.
    12. 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.
    13. Carrero, C. & Amador, J. & Arnaltes, S., 2007. "A single procedure for helping PV designers to select silicon PV modules and evaluate the loss resistances," Renewable Energy, Elsevier, vol. 32(15), pages 2579-2589.
    14. Arab, A.Hadj & Chenlo, F. & Mukadam, K. & Balenzategui, J.L., 1999. "Performance of PV water pumping systems," Renewable Energy, Elsevier, vol. 18(2), pages 191-204.
    15. Yordanov, Georgi Hristov & Midtgård, Ole-Morten & Saetre, Tor Oskar, 2012. "Series resistance determination and further characterization of c-Si PV modules," Renewable Energy, Elsevier, vol. 46(C), pages 72-80.
    16. Miguel Pareja Aparicio & Jose Pelegri-Sebastia & Tomas Sogorb & Vicente Llario, 2013. "Modeling of Photovoltaic Cell Using Free Software Application for Training and Design Circuit in Photovoltaic Solar Energy," Chapters, in: Hasan Arman & Ibrahim Yuksel (ed.), New Developments in Renewable Energy, IntechOpen.
    17. Ahmad, G.E. & Hussein, H.M.S. & El-Ghetany, H.H., 2003. "Theoretical analysis and experimental verification of PV modules," Renewable Energy, Elsevier, vol. 28(8), pages 1159-1168.
    18. 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.
    19. Kaldellis, J.K. & Spyropoulos, G.C. & Kavadias, K.A. & Koronaki, I.P., 2009. "Experimental validation of autonomous PV-based water pumping system optimum sizing," Renewable Energy, Elsevier, vol. 34(4), pages 1106-1113.
    20. Sukamongkol, Y. & Chungpaibulpatana, S. & Ongsakul, W., 2002. "A simulation model for predicting the performance of a solar photovoltaic system with alternating current loads," Renewable Energy, Elsevier, vol. 27(2), pages 237-258.
    21. Badescu, Viorel, 2003. "Dynamic model of a complex system including PV cells, electric battery, electrical motor and water pump," Energy, Elsevier, vol. 28(12), pages 1165-1181.
    22. Zhou, Wei & Yang, Hongxing & Fang, Zhaohong, 2008. "Battery behavior prediction and battery working states analysis of a hybrid solar–wind power generation system," Renewable Energy, Elsevier, vol. 33(6), pages 1413-1423.
    23. Ma, Tao & Østergaard, Poul Alberg & Lund, Henrik & Yang, Hongxing & Lu, Lin, 2014. "An energy system model for Hong Kong in 2020," Energy, Elsevier, vol. 68(C), pages 301-310.
    24. Mellit, A. & Benghanem, M. & Kalogirou, S.A., 2007. "Modeling and simulation of a stand-alone photovoltaic system using an adaptive artificial neural network: Proposition for a new sizing procedure," Renewable Energy, Elsevier, vol. 32(2), pages 285-313.
    25. Zhou, Wei & Yang, Hongxing & Fang, Zhaohong, 2007. "A novel model for photovoltaic array performance prediction," Applied Energy, Elsevier, vol. 84(12), pages 1187-1198, December.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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.
    3. Rawat, Rahul & Kaushik, S.C. & Lamba, Ravita, 2016. "A review on modeling, design methodology and size optimization of photovoltaic based water pumping, standalone and grid connected system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1506-1519.
    4. 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.
    5. Gulkowski, Slawomir & Muñoz Diez, José Vicente & Aguilera Tejero, Jorge & Nofuentes, Gustavo, 2019. "Computational modeling and experimental analysis of heterojunction with intrinsic thin-layer photovoltaic module under different environmental conditions," Energy, Elsevier, vol. 172(C), pages 380-390.
    6. 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.
    7. 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.
    8. 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.
    9. Mahesh, Aeidapu & Sandhu, Kanwarjit Singh, 2015. "Hybrid wind/photovoltaic energy system developments: Critical review and findings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1135-1147.
    10. Ma, Tao & Yang, Hongxing & Lu, Lin & Peng, Jinqing, 2015. "Optimal design of an autonomous solar–wind-pumped storage power supply system," Applied Energy, Elsevier, vol. 160(C), pages 728-736.
    11. 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.
    12. Wang, Gang & Zhao, Ke & Shi, Jiangtao & Chen, Wei & Zhang, Haiyang & Yang, Xinsheng & Zhao, Yong, 2017. "An iterative approach for modeling photovoltaic modules without implicit equations," Applied Energy, Elsevier, vol. 202(C), pages 189-198.
    13. Karabacak, Kerim & Cetin, Numan, 2014. "Artificial neural networks for controlling wind–PV power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 804-827.
    14. Goel, Sonali & Sharma, Renu, 2017. "Performance evaluation of stand alone, grid connected and hybrid renewable energy systems for rural application: A comparative review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1378-1389.
    15. Shabani, Masoume & Mahmoudimehr, Javad, 2018. "Techno-economic role of PV tracking technology in a hybrid PV-hydroelectric standalone power system," Applied Energy, Elsevier, vol. 212(C), pages 84-108.
    16. 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.
    17. 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.
    18. 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.
    19. Muhsen, Dhiaa Halboot & Khatib, Tamer & Nagi, Farrukh, 2017. "A review of photovoltaic water pumping system designing methods, control strategies and field performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 70-86.
    20. 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.

    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:36:y:2014:i:c:p:304-315. 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.