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Analysis of Solar Radiation Data in Van, Turkey

Year 2018, , 421 - 427, 28.12.2018
https://doi.org/10.18466/cbayarfbe.434552

Abstract

This work has processed, analyzed and regulated the
data comprising surface temperature, sunshine duration and global solar
radiation for the period of 1993 to 2007 in Van (38.28oN, 43.20oE).  Hourly, monthly and annual variations of
solar radiation are calculated. Furthermore, the annual variations of sunshine
duration, surface temperature and clearness index are also analyzed. Annual
average maximum global solar radiation was seen in 2000 with 19.68 MJ/m2day and
the trend of yearly series of global solar radiation increases from 1993 to
2007. The highest hourly and monthly values are 3260 kJ/m2h and 28.72 MJ/m2day,
respectively. Besides, daily monthly and annual of clearness index, hourly
frequency distribution and sunshine duration are discussed and the solar
radiation and the annual clearness index are correlated. Consequently, the Van
region has a high solar energy potential and a high frequency of clear
daylight.

References

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  • 2. Benghanem, M, Daffallah, K.O, Alamri, S.N, Joraid, A.A, Effect of pumping head on solar water pumping system, Energy Conversion and Management, 2014, 77, 334-339.
  • 3. Helwa, N.H, Abdel Rehime, Z.S, Experimental study of the performance of solar dryers with pebble beds, Energy Sources, 2007, 19 (6), 579-591.
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  • 6. Soussib, M, Balghouthia, M, Guizania, A, Energy performance analysis of a solar-cooled building in Tunisia: Passive strategies impact and improvement techniques, Energy and Building 2013, 67, 374-386.
  • 7. Şenkal, O, Şahin, M. Peştemalci, V, The Estimation of solar radiation for different time periods, Energy Sources, Part A: Recovery Utilization and Environmental Effects, 2010, 32(13), 1176-1184.
  • 8. Mohandes, M, Rehman, S, Halawani, T.O, Estimation of global solar radiation using artificial neural networks, Renewable Energy, 1998,14,179-184. 9. Sözen, A, Arcaklioğlu, E, Özalp, M, Estimation of solar potential in Turkey by artificial neural network s using meteorological and geographical data, Energy Conversion and Management, 2004, 45, 3033-3052.
  • 10. Azeez, M.A, Artificial neural network estimation of global solar radiation using meteorological parameters in Gusau, Nigeria, Archives of Applied Science Research, 2011, 3(2), 586-595.
  • 11. Hasni, A, Sehli, A, Draoui, B, Bassou, A, and Amieur, B, Estimating global solar radiation using artificial neural network and climate data in the south-western region of Algeria, Energy Procedia, 2012, 18, 531–537.
  • 12. Hirunlabh, J, Sarachitti, R, Namprakai, P, Estimating solar radiation at the earth’s surface from satellite data, Tammasart International Journal of Science and Technology, 1997, 1,69-79. 13. Janjai, S, Laksanaboonsong, J, Nunez, M, Thongsathitya, A, Development of a method for generating operational solar radiation maps from satellite data for a tropical environment, Solar Energy, 2005, 78,739-751.
  • 14. Vignola, F, Harlan, P, Perez, R, Kmiecik, M, Analysis of satellite derived beam and global solar radiation data, Solar Energy, 2007, 81, 768-772.
  • 15. Bakirci, K, Correlations for estimation of daily global solar radiation with hours of bright sunshine in Turkey, Energy, 2009, 34, 485-501.
  • 16. Toğrul, I.T, Onat, E, A study for estimating solar radiation in Elaziğ using geographical and meteorological data, Energy Conversion and Management, 1999, 40, 1577-1584.
  • 17. Bulut, H, Büyükalaca, O, Simple model for the generation of daily global solar-radiation data in Turkey, Applied Energy, 2007, 84, 477-491.
  • 18. Duffie, J.A, Beckman, W.A, Solar Engineering of Thermal Processes 3rd. ed, John Willey & Sons, New York, 1991. 19. Aksoy, B, Solar radiation over Turkey and its analysis, International Journal of Remote Sensing, 2011, 32, 6261-6272.
  • 20. Esen, H, Experimental energy and energy analysis of a double-flow solar air heater having different obstacles on absorber plates, Building and Environment, 2008, 43, 1046-1054.
Year 2018, , 421 - 427, 28.12.2018
https://doi.org/10.18466/cbayarfbe.434552

Abstract

References

  • 1. Diaz, P, Peña, R. Muñoz, J, Arias, C.A, Sandoval, D, Field analysis of solar PV based collective systems for rural electrification, Energy, 2011, 36, 2509-2516.
  • 2. Benghanem, M, Daffallah, K.O, Alamri, S.N, Joraid, A.A, Effect of pumping head on solar water pumping system, Energy Conversion and Management, 2014, 77, 334-339.
  • 3. Helwa, N.H, Abdel Rehime, Z.S, Experimental study of the performance of solar dryers with pebble beds, Energy Sources, 2007, 19 (6), 579-591.
  • 4. Chaturvedi, S.K, Gagrani, V.D, Abdel Salam, T.M, Solar-assisted heat pump - A sustainable system for low-temperature water heating applications,, Energy Conversion and Management, 2014, 77, 550-557.
  • 5. Ayompe, L.M, Duffy, A, Analysis of the thermal performance of a solar water heating system with flat plate collectors in a temperate climate, Applied Thermal Engineering, 2013, 58:447-454.
  • 6. Soussib, M, Balghouthia, M, Guizania, A, Energy performance analysis of a solar-cooled building in Tunisia: Passive strategies impact and improvement techniques, Energy and Building 2013, 67, 374-386.
  • 7. Şenkal, O, Şahin, M. Peştemalci, V, The Estimation of solar radiation for different time periods, Energy Sources, Part A: Recovery Utilization and Environmental Effects, 2010, 32(13), 1176-1184.
  • 8. Mohandes, M, Rehman, S, Halawani, T.O, Estimation of global solar radiation using artificial neural networks, Renewable Energy, 1998,14,179-184. 9. Sözen, A, Arcaklioğlu, E, Özalp, M, Estimation of solar potential in Turkey by artificial neural network s using meteorological and geographical data, Energy Conversion and Management, 2004, 45, 3033-3052.
  • 10. Azeez, M.A, Artificial neural network estimation of global solar radiation using meteorological parameters in Gusau, Nigeria, Archives of Applied Science Research, 2011, 3(2), 586-595.
  • 11. Hasni, A, Sehli, A, Draoui, B, Bassou, A, and Amieur, B, Estimating global solar radiation using artificial neural network and climate data in the south-western region of Algeria, Energy Procedia, 2012, 18, 531–537.
  • 12. Hirunlabh, J, Sarachitti, R, Namprakai, P, Estimating solar radiation at the earth’s surface from satellite data, Tammasart International Journal of Science and Technology, 1997, 1,69-79. 13. Janjai, S, Laksanaboonsong, J, Nunez, M, Thongsathitya, A, Development of a method for generating operational solar radiation maps from satellite data for a tropical environment, Solar Energy, 2005, 78,739-751.
  • 14. Vignola, F, Harlan, P, Perez, R, Kmiecik, M, Analysis of satellite derived beam and global solar radiation data, Solar Energy, 2007, 81, 768-772.
  • 15. Bakirci, K, Correlations for estimation of daily global solar radiation with hours of bright sunshine in Turkey, Energy, 2009, 34, 485-501.
  • 16. Toğrul, I.T, Onat, E, A study for estimating solar radiation in Elaziğ using geographical and meteorological data, Energy Conversion and Management, 1999, 40, 1577-1584.
  • 17. Bulut, H, Büyükalaca, O, Simple model for the generation of daily global solar-radiation data in Turkey, Applied Energy, 2007, 84, 477-491.
  • 18. Duffie, J.A, Beckman, W.A, Solar Engineering of Thermal Processes 3rd. ed, John Willey & Sons, New York, 1991. 19. Aksoy, B, Solar radiation over Turkey and its analysis, International Journal of Remote Sensing, 2011, 32, 6261-6272.
  • 20. Esen, H, Experimental energy and energy analysis of a double-flow solar air heater having different obstacles on absorber plates, Building and Environment, 2008, 43, 1046-1054.
There are 17 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

İrfan Uçkan

Publication Date December 28, 2018
Published in Issue Year 2018

Cite

APA Uçkan, İ. (2018). Analysis of Solar Radiation Data in Van, Turkey. Celal Bayar Üniversitesi Fen Bilimleri Dergisi, 14(4), 421-427. https://doi.org/10.18466/cbayarfbe.434552
AMA Uçkan İ. Analysis of Solar Radiation Data in Van, Turkey. CBUJOS. December 2018;14(4):421-427. doi:10.18466/cbayarfbe.434552
Chicago Uçkan, İrfan. “Analysis of Solar Radiation Data in Van, Turkey”. Celal Bayar Üniversitesi Fen Bilimleri Dergisi 14, no. 4 (December 2018): 421-27. https://doi.org/10.18466/cbayarfbe.434552.
EndNote Uçkan İ (December 1, 2018) Analysis of Solar Radiation Data in Van, Turkey. Celal Bayar Üniversitesi Fen Bilimleri Dergisi 14 4 421–427.
IEEE İ. Uçkan, “Analysis of Solar Radiation Data in Van, Turkey”, CBUJOS, vol. 14, no. 4, pp. 421–427, 2018, doi: 10.18466/cbayarfbe.434552.
ISNAD Uçkan, İrfan. “Analysis of Solar Radiation Data in Van, Turkey”. Celal Bayar Üniversitesi Fen Bilimleri Dergisi 14/4 (December 2018), 421-427. https://doi.org/10.18466/cbayarfbe.434552.
JAMA Uçkan İ. Analysis of Solar Radiation Data in Van, Turkey. CBUJOS. 2018;14:421–427.
MLA Uçkan, İrfan. “Analysis of Solar Radiation Data in Van, Turkey”. Celal Bayar Üniversitesi Fen Bilimleri Dergisi, vol. 14, no. 4, 2018, pp. 421-7, doi:10.18466/cbayarfbe.434552.
Vancouver Uçkan İ. Analysis of Solar Radiation Data in Van, Turkey. CBUJOS. 2018;14(4):421-7.

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