| Peer-Reviewed

Comparative Analysis of Three NOCT-Based Cell Temperature Models

Received: 25 October 2016    Accepted: 18 November 2016    Published: 21 December 2016
Views:       Downloads:
Abstract

In this paper, comparative analyses of three NOCT-based cell temperature models are presented. The models are the HOMER (Hybrid Optimization of Multiple Energy Resources) software cell temperature, Ross cell temperature model and Davis and Rauschenbach cell temperature model. Noticeably, unlike PVSysts software, the three models do not include the effect of wind speed. Three models are analyzed using the meteorological data of a site in Ibeno, Akwa Ibom state, Nigeria. The results showed that among the three NOCT-based cell temperature models, the Ross model has the highest cell temperature for any given ambient temperature and solar irradiance. The HOMER Davis and Rauschenbach models have almost the same cell temperature values but in all the occasions, the HOMER model gives the lowest cell temperature among the three models. Equally, Ross model has the lowest annual energy yield and the highest thermal loss whereas the HOMER model has the highest annual energy yield and the lowest thermal loss.

Published in International Journal of Systems Science and Applied Mathematics (Volume 1, Issue 4)
DOI 10.11648/j.ijssam.20160104.16
Page(s) 69-75
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), 2024. Published by Science Publishing Group

Keywords

Cell Temperature, Thermal Loss, Energy Yield, Temperature Derating Factor, Photovoltaic, Solar Energy, Renewable Energy

References
[1] Riedel, I., Parisi, J., Dyakonov, V., Lutsen, L., Vanderzande, D., & Hummelen, J. C. (2004). Effect of Temperature and Illumination on the Electrical Characteristics of Polymer–Fullerene Bulk‐Heterojunction Solar Cells. Advanced Functional Materials, 14 (1), 38-44.
[2] Vasisht, M. S., Srinivasan, J., & Ramasesha, S. K. (2016). Performance of solar photovoltaic installations: Effect of seasonal variations. Solar Energy, 131, 39-46.
[3] Armstrong, S., & Hurley, W. G. (2010). A thermal model for photovoltaic panels under varying atmospheric conditions. Applied Thermal Engineering, 30 (11), 1488-1495.
[4] Ali, A., Amjad, M., Mehmood, A., Asim, U., & Abid, A. (2015). Cost effective power generation using renewable energy based hybrid system for Chakwal, Pakistan. Science International, 27 (6), 6017-6022.
[5] Energy, H. O. M. E. R. (2015). Hybrid Optimization of Multiple Energy Resources.
[6] Dolkar, Y., Jamtsho, D., Adhikari, R., Wangdi, T., Dorji, S., Lhendup, T., & Lhamo, P. (2015, February). System Design and Performance Analysis of a Grid-Tied Solar PV Power System in Bhutan. In Computational Intelligence & Communication Technology (CICT), 2015 IEEE International Conference on (pp. 538-542). IEEE.
[7] Guarracino, I., Mellor, A., Ekins-Daukes, N. J., & Markides, C. N. (2016). Dynamic coupled thermal-and-electrical modelling of sheet-and-tube hybrid photovoltaic/thermal (PVT) collectors. Applied Thermal Engineering.
[8] Urrejola, E., Antonanzas, J., Ayala, P., Salgado, M., Ramírez-Sagner, G., Cortés, C.,... & Escobar, R. (2016). Effect of soiling and sunlight exposure on the performance ratio of photovoltaic technologies in Santiago, Chile. Energy Conversion and Management, 114, 338-347.
[9] Skoplaki, E., & Palyvos, J. A. (2009). Operating temperature of photovoltaic modules: A survey of pertinent correlations. Renewable Energy, 34 (1), 23-29. (http://www.sciencedirect.com/science/article/pii/S0960148108001353).
[10] Ya'acob, M. E., Hizam, H., Khatib, T., Radzi, M. A. M., Gomes, C., Marhaban, M. H., & Elmenreich, W. (2014). Modelling of photovoltaic array temperature in a tropical site using generalized extreme value distribution. Journal of Renewable and Sustainable Energy, 6 (3), 033134.
[11] Osterwald, C. R. (2012). Chapter III-2 - standards, calibration, and testing of PV modules and solar cells. Practical handbook of photovoltaics (second edition) (pp. 1045-1069). Boston: Academic Press.
[12] Mattei, M., Notton, G., Cristofari, C., Muselli, M., & Poggi, P. (2006). Calculation of the polycrystalline PV module temperature using a simple method of energy balance. Renewable Energy, 31 (4), 553-567.
[13] Migan, G. A. (2013). Study of the operating temperature of a PV module. Project Report.
[14] Ibrahim, A. (2011). Analysis of Electrical Characteristics of Photovoltaic Single Crystal Silicon Solar Cells at Outdoor Measurements. Smart Grid and Renewable Energy, 2 (2), 169.
[15] Malik, A. Q., & Damit, S. J. B. H. (2003). Outdoor testing of single crystal silicon solar cells. Renewable Energy, 28 (9), 1433-1445.
[16] Olukan, T. A., & Emziane, M. (2014). A comparative analysis of PV module temperature models. Energy Procedia, 62, 694-703.
[17] Jakhrani, A. Q., Othman, A. K., Rigit, A. R. H., & Samo, S. R. (2011). Comparison of solar photovoltaic module temperature models. World Applied Sciences Journal, 14, 1-8.
[18] Krauter, S., & Preiss, A. (2009, June). Comparison of module temperature measurement methods. In Photovoltaic Specialists Conference (PVSC), 2009 34th IEEE (pp. 000333-000338). IEEE.
[19] Carl, C. (2014). Calculating solar photovoltaic potential on residential rooftops in Kailua Kona, Hawaii (Doctoral dissertation, University of Southern California).
[20] Marion, B, M. Andeberg, R. George, P. Gray-Hann, and D. Heimiller. 2001. PVWATTS Version 2- enhanced spatial resolution for calculating grid-connected PV performance. National Renewable Energy Laboratory presented at the NCPV Program Review Meeting Lakewood, Colorado. http://www.nrel.gov/docs/fy02osti/30941.pdf (last accessed 29 December 2013).
[21] Methodology Calculation. In Conférence Internationale des Energies Renouvelables" CIER’13"/International Journal of Scientific Research & Engineering Technology (Vol. 1, No. 02). International Publisher &C. O.
[22] Assoa, Y. B., Zamini, S., Sprenger, W., Misara, S., Pellegrino, M., & Erleaga, A. A. (2012) Numerical Analysis Of The Impact Of Environmental Conditions On Bipv Systems, An Overview Of Bipv Modelling In The Sophia Project. In the 27th European Photovoltaic Solar Energy Conference and Exhibition held in Messe Frankfurt and Congress Center, Frankfurt, Germany... 2012.
[23] Tian, H., Mancilla, F., & Muljadi, E. (2012). A detailed performance model for photovoltaic Systems. National Renewable Energy Laboratory, USA NREL/JA-5500-54601.4] Davis, M. W., Dougherty, B. P., & Fanney, A. H. (2001). Prediction of building integrated photovoltaic cell temperatures. Journal of Solar Energy Engineering, 123, 200–210.
[24] Rauschenbach, H. S., (1980) Solar cell array design handbook. Van Nostrand Reinhold, New York, pp: 390-391.
[25] Sinha, S., & Chandel, S. S. (2014). Review of software tools for hybrid renewable energy systems. Renewable and Sustainable Energy Reviews, 32, 192-205.
[26] Sen, R., & Bhattacharyya, S. C. (2014). Off-grid electricity generation with renewable energy technologies in India: An application of HOMER. Renewable Energy, 62, 388-398.
[27] Brihmat, F., & Mekhtoub, S. (2014). PV Cell Temperature/PV Power Output Relationships Homer Methodology Calculation. In Conférence Internationale des Energies Renouvelables" CIER’13"/International Journal of Scientific Research & Engineering Technology (Vol. 1, No. 02). International Publisher &C. O.
[28] Nordahl, S. H. (2012). Design of Roof PV Installation in Oslo.
[29] Luque, A., & Hegedus, S. (Eds.). (2011). Handbook of photovoltaic science and engineering. John Wiley & Sons.
[30] Perpinan, O., Lorenzo, E., & Castro, M. A. (2007). On the calculation of energy produced by a PV grid‐connected system. Progress in Photovoltaics: research and applications, 15 (3), 265-274.
Cite This Article
  • APA Style

    Anyanime Tim Umoette, Emmanuel A. Ubom, Ibiangake Etie Akpan. (2016). Comparative Analysis of Three NOCT-Based Cell Temperature Models. International Journal of Systems Science and Applied Mathematics, 1(4), 69-75. https://doi.org/10.11648/j.ijssam.20160104.16

    Copy | Download

    ACS Style

    Anyanime Tim Umoette; Emmanuel A. Ubom; Ibiangake Etie Akpan. Comparative Analysis of Three NOCT-Based Cell Temperature Models. Int. J. Syst. Sci. Appl. Math. 2016, 1(4), 69-75. doi: 10.11648/j.ijssam.20160104.16

    Copy | Download

    AMA Style

    Anyanime Tim Umoette, Emmanuel A. Ubom, Ibiangake Etie Akpan. Comparative Analysis of Three NOCT-Based Cell Temperature Models. Int J Syst Sci Appl Math. 2016;1(4):69-75. doi: 10.11648/j.ijssam.20160104.16

    Copy | Download

  • @article{10.11648/j.ijssam.20160104.16,
      author = {Anyanime Tim Umoette and Emmanuel A. Ubom and Ibiangake Etie Akpan},
      title = {Comparative Analysis of Three NOCT-Based Cell Temperature Models},
      journal = {International Journal of Systems Science and Applied Mathematics},
      volume = {1},
      number = {4},
      pages = {69-75},
      doi = {10.11648/j.ijssam.20160104.16},
      url = {https://doi.org/10.11648/j.ijssam.20160104.16},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssam.20160104.16},
      abstract = {In this paper, comparative analyses of three NOCT-based cell temperature models are presented. The models are the HOMER (Hybrid Optimization of Multiple Energy Resources) software cell temperature, Ross cell temperature model and Davis and Rauschenbach cell temperature model. Noticeably, unlike PVSysts software, the three models do not include the effect of wind speed. Three models are analyzed using the meteorological data of a site in Ibeno, Akwa Ibom state, Nigeria. The results showed that among the three NOCT-based cell temperature models, the Ross model has the highest cell temperature for any given ambient temperature and solar irradiance. The HOMER Davis and Rauschenbach models have almost the same cell temperature values but in all the occasions, the HOMER model gives the lowest cell temperature among the three models. Equally, Ross model has the lowest annual energy yield and the highest thermal loss whereas the HOMER model has the highest annual energy yield and the lowest thermal loss.},
     year = {2016}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Comparative Analysis of Three NOCT-Based Cell Temperature Models
    AU  - Anyanime Tim Umoette
    AU  - Emmanuel A. Ubom
    AU  - Ibiangake Etie Akpan
    Y1  - 2016/12/21
    PY  - 2016
    N1  - https://doi.org/10.11648/j.ijssam.20160104.16
    DO  - 10.11648/j.ijssam.20160104.16
    T2  - International Journal of Systems Science and Applied Mathematics
    JF  - International Journal of Systems Science and Applied Mathematics
    JO  - International Journal of Systems Science and Applied Mathematics
    SP  - 69
    EP  - 75
    PB  - Science Publishing Group
    SN  - 2575-5803
    UR  - https://doi.org/10.11648/j.ijssam.20160104.16
    AB  - In this paper, comparative analyses of three NOCT-based cell temperature models are presented. The models are the HOMER (Hybrid Optimization of Multiple Energy Resources) software cell temperature, Ross cell temperature model and Davis and Rauschenbach cell temperature model. Noticeably, unlike PVSysts software, the three models do not include the effect of wind speed. Three models are analyzed using the meteorological data of a site in Ibeno, Akwa Ibom state, Nigeria. The results showed that among the three NOCT-based cell temperature models, the Ross model has the highest cell temperature for any given ambient temperature and solar irradiance. The HOMER Davis and Rauschenbach models have almost the same cell temperature values but in all the occasions, the HOMER model gives the lowest cell temperature among the three models. Equally, Ross model has the lowest annual energy yield and the highest thermal loss whereas the HOMER model has the highest annual energy yield and the lowest thermal loss.
    VL  - 1
    IS  - 4
    ER  - 

    Copy | Download

Author Information
  • Department of Electrical, Electronic Engineering, Akwa Ibom State University, Mkpat Enin, Nigeria

  • Department of Electrical, Electronic Engineering, Akwa Ibom State University, Mkpat Enin, Nigeria

  • Department of Electrical, Electronic Engineering, Akwa Ibom State University, Mkpat Enin, Nigeria

  • Sections