Validation of Thrmal Models for Polycrystalline Photovoltaic Module Under Derna City Climate Conditions

Authors

  • Mahmood Abdel hadi The Libyan Academy – Benghazi – Libya,
  • Yasser Aldali Omar Al Mokhtar University, Faculty of Engineering, Dept. of Mechanical Engineering, Derna – Libya
  • Ali N. Celik Abant Izzet Baysal University, Faculty of Engineering and Architecture, Dept. of Mechanical Engineering, Gölköy Campus 14280 Bolu, Turkey

DOI:

https://doi.org/10.51646/jsesd.v7i2.39

Abstract

The main objective of the present paper is to compare nine diffrent cell temperature models available in the literature with data measured under real Derna city climatic conditions (a semi arid climate) for month of August. Th study focuses on a comparison of nine theoretical models to calculate the cell temperature based on the experimental measurements such as the ambient temperature, irradiance, and wind speed in some of the models. Th presently used models are explicit, depending on the easily measurable parameters and of wide applicability. Six statistical quantitative indicators are used to evaluate the cell temperature models analysed, namely, R2, RMSE, RRMSE, MAE, MBE and MARE. The cell temperature correlations presently studied, fist order linear models depending on the ambient temperature, solar irradiation incident on the panel and voltage output, provide the most accurate cell temperature estimations at Derna city climatic conditions

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References

. Carr, A. J., & Pryor, T. L. (2004). A comparison of the performance of diffrent PV module types in temperate climates. Solar Energy, 76(1-3), 285-294.

. Akhmad, K., Kitamura, A., Yamamoto, F., Okamoto, H., Takakura, H., & Hamakawa, Y. (1997). Outdoor Performance of amorphous silicon and polycrystalline silicon PV modules. Solar Energy Materials and Solar Cells, 46(3), 209-218..

. Rehman, S., & El-Amin, I. (2012). Performance evaluation of an offgrid photovoltaic system in Saudi Arabia. Energy, 46(1), 451-458.

. Ubertini, S., & Desideri, U. (2003). Performance estimation and experimental measurements of a photovoltaic roof. Renewable energy, 28(12), 1833-1850..

. Khatib, T., Mohamed, A., & Sopian, K. (2013). A review of photovoltaic systems size optimization techniques. Renewable and Sustainable Energy Reviews, 22, 454-465.

. Khatib, T., Sopian, K., & Kazem, H. A. (2013). Actual performance and characteristic of a grid connected photovoltaic power system in the tropics: A short term evaluation. Energy Conversion and Management, 71, 115-119..

. Parretta, A., Sarno, A., & Vicari, L. R. (1998). Effcts of solar irradiation conditions on the outdoor performance of

photovoltaic modules. Optics Communications, 153(1-3), 153-163.

. Nishioka, K., Hatayama, T., Uraoka, Y., Fuyuki, T., Hagihara, R., & Watanabe, M. (2003). Field-test analysis of PV

system output characteristics focusing on module temperature. Solar Energy Materials and Solar Cells, 75(3-4), 665-

. Ceylan, İ., Erkaymaz, O., Gedik, E., & Gürel, A. E. (2014). Th prediction of photovoltaic module temperature with

artifiial neural networks. Case Studies in Thrmal Engineering, 3, 11-20.

. Pantic, L. S., Pavlović, T. M., Milosavljević, D. D., Radonjic, I. S., Radovic, M. K., & Sazhko, G. (2016). Th assessment of diffrent models to predict solar module temperature, output power and effiency for Nis, Serbia. Energy, 109, 38-48.

. King, D. L., Boyson, W. E., & Kratochvil, J. A. (2004). Photovoltaic array performance model, Sandia National

Laboratories, paper nr. SAND2004-3844.

. Duffi J. A., & Beckman, W. A. (2013). Solar engineering of thermal processes. John Wiley & Sons.

. Skoplaki, E., Boudouvis, A. G., & Palyvos, J. A. (2008). A simple correlation for the operating temperature of photovoltaic modules of arbitrary mounting. Solar Energy Materials and Solar Cells, 92(11), 1393-1402.

. Koehl, M., Heck, M., Wiesmeier, S., & Wirth, J. (2011). Modeling of the nominal operating cell temperature based on outdoor weathering. Solar Energy Materials and Solar Cells, 95(7), 1638-1646..

. Kurtz, S., Whitfild, K., TamizhMani, G., Koehl, M., Miller, D., Joyce, J., & Zgonena, T. (2011). Evaluation of high‐

temperature exposure of photovoltaic modules. Progress in photovoltaics: Research and applications, 19(8), 954-965.

. 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.

. Barroso, J. S., Barth, N., Correia, J. P. M., Ahzi, S., & Khaleel, M. A. (2016). A computational analysis of coupled

thermal and electrical behavior of PV panels. Solar Energy Materials and Solar Cells, 148, 73-86.

. Faiman, D. (2008). Assessing the outdoor operating temperature of photovoltaic modules. Progress in Photovoltaics: Research and Applications, 16(4), 307-315.

. Kurnik, J., Jankovec, M., & Brecl, K. (2011). Outdoor testing of PV module temperature and performance under diffrent mounting and operational conditions. Solar Energy Materials and Solar Cells, 95(1), 373-376.

. Kaldellis, J. K., Kapsali, M., & Kavadias, K. A. (2014). Temperature and wind speed impact on the effiency of PV

installations. Experience obtained from outdoor measurements in Greece. Renewable Energy, 66, 612-624.

. NASA Surface meteorology and Solar Energy. http://eosweb.larc.nasa.gov/cgi-bin/sse/retscreen.cgi?email=rets@nrcan. gc.ca.

. Muzathik, A. M. (2014). Photovoltaic modules operating temperature estimation using a simple correlation.

International Journal of Energy Engineering, 4(4), 151.

. Kalogirou, S.A., (2009). Solar Energy Engineering: Processes and Systems, USA: Elsevier Inc. Available at: http://dx.doi. org/10.1016/B978-0-12-374501-9.00014-5.

. Charalambous, P. G., Maidment, G. G., Kalogirou, S. A., & Yiakoumetti, K. (2007). Photovoltaic thermal (PV/T)

collectors: A review. Applied Thermal Engineering, 27(2-3), 275-286.

. Skoplaki, E. P. J. A., & Palyvos, J. A. (2009). Operating temperature of photovoltaic modules: A survey of pertinent

correlations. Renewable energy, 34(1), 23-29.

. Willmott, C. J., & Matsuura, K. (2005). Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Climate research, 30(1), 79-82.

. Li, M. F., Tang, X. P., Wu, W., & Liu, H. B. (2013). General models for estimating daily global solar radiation for

diffrent solar radiation zones in mainland China. Energy conversion and management, 70, 139-148.

. Jiang, Y. (2009). Estimation of monthly mean daily diffse radiation in China. Applied Energy, 86 (9), 1458-1464.

. Yadav, A. K., & Chandel, S. S. (2014). Solar radiation prediction using Artifiial Neural Network techniques: A review. Renewable and Sustainable Energy Reviews, 33, 772-781.

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Published

2018-12-31

How to Cite

[1]
M. . Abdel hadi, Y. . Aldali, and A. . Celik, “Validation of Thrmal Models for Polycrystalline Photovoltaic Module Under Derna City Climate Conditions”, jsesd, vol. 7, no. 2, pp. 27–40, Dec. 2018.

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