IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v70y2014icp49-57.html
   My bibliography  Save this article

New procedure and field-tests to assess photovoltaic module performance

Author

Listed:
  • Paulescu, Marius
  • Badescu, Viorel
  • Dughir, Ciprian

Abstract

The theoretical performance of a photovoltaic (PV) module is typically evaluated by using models based on equivalent circuits whose parameters are derived from data listed in manufacture's datasheet. Few manufactures provide detailed enough datasheets to allow using highly accurate models. In many cases simplified models have to be used due to missing information. This paper proposes a new procedure to evaluate PV modules performance. The procedure is based on the four-parameter model, which can be used with input data provided by most manufactures. Firstly, the parameters extraction in standard test conditions is discussed. Secondly, an algorithm for PV module performance estimation under real weather conditions is proposed. The procedure is validated on a commercial PV module. Estimations and field-test data are found to be in good agreement. The difference between the response time of the pyranometer (tens of seconds) and the response time of the PV module (almost instantaneous) is found to be an important source of errors. This aspect has not been previously discussed in literature with sufficient detail. The proposed procedure represents a feasible tool for calculating the performance of PV modules described by a limited set of data, operating in arbitrary weather conditions.

Suggested Citation

  • Paulescu, Marius & Badescu, Viorel & Dughir, Ciprian, 2014. "New procedure and field-tests to assess photovoltaic module performance," Energy, Elsevier, vol. 70(C), pages 49-57.
    • Handle: RePEc:eee:energy:v:70:y:2014:i:c:p:49-57
    DOI: 10.1016/j.energy.2014.03.085
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544214003491
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2014.03.085?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. Cañete, Cristina & Carretero, Jesús & Sidrach-de-Cardona, Mariano, 2014. "Energy performance of different photovoltaic module technologies under outdoor conditions," Energy, Elsevier, vol. 65(C), pages 295-302.
    2. 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.
    3. Kadri, Riad & Andrei, Horia & Gaubert, Jean-Paul & Ivanovici, Traian & Champenois, Gérard & Andrei, Paul, 2012. "Modeling of the photovoltaic cell circuit parameters for optimum connection model and real-time emulator with partial shadow conditions," Energy, Elsevier, vol. 42(1), pages 57-67.
    4. Chenni, R. & Makhlouf, M. & Kerbache, T. & Bouzid, A., 2007. "A detailed modeling method for photovoltaic cells," Energy, Elsevier, vol. 32(9), pages 1724-1730.
    5. Almonacid, F. & Rus, C. & Pérez-Higueras, P. & Hontoria, L., 2011. "Calculation of the energy provided by a PV generator. Comparative study: Conventional methods vs. artificial neural networks," Energy, Elsevier, vol. 36(1), pages 375-384.
    6. 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.
    7. Ishaque, Kashif & Salam, Zainal & Mekhilef, Saad & Shamsudin, Amir, 2012. "Parameter extraction of solar photovoltaic modules using penalty-based differential evolution," Applied Energy, Elsevier, vol. 99(C), pages 297-308.
    8. Kalogirou, Soteris A. & Agathokleous, Rafaela & Panayiotou, Gregoris, 2013. "On-site PV characterization and the effect of soiling on their performance," Energy, Elsevier, vol. 51(C), pages 439-446.
    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. Senturk, Ali, 2020. "Investigation of datasheet provided temperature coefficients of photovoltaic modules under various sky profiles at the field by applying a new validation procedure," Renewable Energy, Elsevier, vol. 152(C), pages 644-652.
    2. Ozden, Talat & Akinoglu, Bulent G. & Turan, Rasit, 2017. "Long term outdoor performances of three different on-grid PV arrays in central Anatolia – An extended analysis," Renewable Energy, Elsevier, vol. 101(C), pages 182-195.
    3. Paulescu, Marius & Stefu, Nicoleta & Dughir, Ciprian & Sabadus, Andreea & Calinoiu, Delia & Badescu, Viorel, 2022. "A simple but accurate two-state model for nowcasting PV power," Renewable Energy, Elsevier, vol. 195(C), pages 322-330.
    4. Andreea Sabadus & Marius Paulescu, 2021. "On the Nature of the One-Diode Solar Cell Model Parameters," Energies, MDPI, vol. 14(13), pages 1-10, July.
    5. Gaglia, Athina G. & Lykoudis, Spyros & Argiriou, Athanassios A. & Balaras, Constantinos A. & Dialynas, Evangelos, 2017. "Energy efficiency of PV panels under real outdoor conditions–An experimental assessment in Athens, Greece," Renewable Energy, Elsevier, vol. 101(C), pages 236-243.
    6. Su, Shanhe & Chen, Xiaohang & Liao, Tianjun & Chen, Jincan & Shih, Tien-Mo, 2016. "Photon-enhanced electron tunneling solar cells," Energy, Elsevier, vol. 111(C), pages 52-56.
    7. Polo, J. & Fernandez-Neira, W.G. & Alonso-García, M.C., 2017. "On the use of reference modules as irradiance sensor for monitoring and modelling rooftop PV systems," Renewable Energy, Elsevier, vol. 106(C), pages 186-191.
    8. Senturk, A. & Eke, R., 2017. "A new method to simulate photovoltaic performance of crystalline silicon photovoltaic modules based on datasheet values," Renewable Energy, Elsevier, vol. 103(C), pages 58-69.
    9. Park, Nochang & Kim, Ju-Hee & Kim, Hyun-A. & Moon, Jin-Chel, 2017. "Development of an algebraic model that predicts the maximum power output of solar modules including their degradation," Renewable Energy, Elsevier, vol. 113(C), pages 141-147.
    10. Alami, Abdul Hai, 2016. "Synthetic clay as an alternative backing material for passive temperature control of photovoltaic cells," Energy, Elsevier, vol. 108(C), pages 195-200.
    11. Paulescu, Marius & Brabec, Marek & Boata, Remus & Badescu, Viorel, 2017. "Structured, physically inspired (gray box) models versus black box modeling for forecasting the output power of photovoltaic plants," Energy, Elsevier, vol. 121(C), pages 792-802.
    12. Wang, Meng & Peng, Jinqing & Luo, Yimo & Shen, Zhicheng & Yang, Hongxing, 2021. "Comparison of different simplistic prediction models for forecasting PV power output: Assessment with experimental measurements," Energy, Elsevier, vol. 224(C).
    13. Do, Minh-Thang & Soubdhan, Ted & Benoît Robyns,, 2016. "A study on the minimum duration of training data to provide a high accuracy forecast for PV generation between two different climatic zones," Renewable Energy, Elsevier, vol. 85(C), pages 959-964.

    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. 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.
    3. 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.
    4. 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.
    5. 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.
    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. 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.
    8. Rehman, Shafiqur & El-Amin, Ibrahim, 2012. "Performance evaluation of an off-grid photovoltaic system in Saudi Arabia," Energy, Elsevier, vol. 46(1), pages 451-458.
    9. Yu, Kunjie & Liang, J.J. & Qu, B.Y. & Cheng, Zhiping & Wang, Heshan, 2018. "Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models," Applied Energy, Elsevier, vol. 226(C), pages 408-422.
    10. 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.
    11. Madi, Saida & Kheldoun, Aissa, 2017. "Bond graph based modeling for parameter identification of photovoltaic module," Energy, Elsevier, vol. 141(C), pages 1456-1465.
    12. Uche, J. & Círez, F. & Bayod, A.A. & Martínez, A., 2013. "On-grid and off-grid batch-ED (electrodialysis) process: Simulation and experimental tests," Energy, Elsevier, vol. 57(C), pages 44-54.
    13. Chen, Zhicong & Wu, Lijun & Lin, Peijie & Wu, Yue & Cheng, Shuying, 2016. "Parameters identification of photovoltaic models using hybrid adaptive Nelder-Mead simplex algorithm based on eagle strategy," Applied Energy, Elsevier, vol. 182(C), pages 47-57.
    14. 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.
    15. Senturk, Ali, 2020. "Investigation of datasheet provided temperature coefficients of photovoltaic modules under various sky profiles at the field by applying a new validation procedure," Renewable Energy, Elsevier, vol. 152(C), pages 644-652.
    16. 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.
    17. 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.
    18. Bastidas-Rodriguez, J.D. & Petrone, G. & Ramos-Paja, C.A. & Spagnuolo, G., 2017. "A genetic algorithm for identifying the single diode model parameters of a photovoltaic panel," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 38-54.
    19. 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.
    20. Qais, Mohammed H. & Hasanien, Hany M. & Alghuwainem, Saad, 2019. "Identification of electrical parameters for three-diode photovoltaic model using analytical and sunflower optimization algorithm," Applied Energy, Elsevier, vol. 250(C), pages 109-117.

    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:energy:v:70:y:2014:i:c:p:49-57. 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.journals.elsevier.com/energy .

    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.