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A software tool for the creation of a typical meteorological year

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  • Skeiker, Kamal
  • Ghani, Bashar Abdul

Abstract

The generation of a typical meteorological year is of great importance for calculations concerning many applications in the field of thermal engineering. In this context, a method has been proposed by Hall et al. focusing on the generating of typical data, and improving the criterion for final selection of typical meteorological month (TMM). The final selection of the most representative year was done by examining a composite score S, which was calculated as the weighed sum of the scores for the four used meteorological parameters. These parameters were air dry-bulb temperature, relative humidity, wind velocity and global solar radiation intensity.

Suggested Citation

  • Skeiker, Kamal & Ghani, Bashar Abdul, 2009. "A software tool for the creation of a typical meteorological year," Renewable Energy, Elsevier, vol. 34(3), pages 544-554.
    • Handle: RePEc:eee:renene:v:34:y:2009:i:3:p:544-554
    DOI: 10.1016/j.renene.2008.05.046
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    References listed on IDEAS

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    1. Kalogirou, Soteris A., 2003. "Generation of typical meteorological year (TMY-2) for Nicosia, Cyprus," Renewable Energy, Elsevier, vol. 28(15), pages 2317-2334.
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    4. Petrakis, M. & Kambezidis, H.D. & Lykoudis, S. & Adamopoulos, A.D. & Kassomenos, P. & Michaelides, I.M. & Kalogirou, S.A. & Roditis, G. & Chrysis, I. & Hadjigianni, A., 1998. "Generation of a “typical meteorological year” for Nicosia, Cyprus," Renewable Energy, Elsevier, vol. 13(3), pages 381-388.
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    Cited by:

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    4. Pusat, Saban & Ekmekçi, İsmail & Akkoyunlu, Mustafa Tahir, 2015. "Generation of typical meteorological year for different climates of Turkey," Renewable Energy, Elsevier, vol. 75(C), pages 144-151.
    5. Zang, Haixiang & Xu, Qingshan & Bian, Haihong, 2012. "Generation of typical solar radiation data for different climates of China," Energy, Elsevier, vol. 38(1), pages 236-248.
    6. Zhang, Wenhao & Li, Honglian & Wang, Mengli & Lv, Wen & Huang, Jin & Yang, Liu, 2024. "Enhancing typical Meteorological Year generation for diverse energy systems: A hybrid Sandia-machine learning approach," Renewable Energy, Elsevier, vol. 225(C).
    7. Jiang, Yingni, 2010. "Generation of typical meteorological year for different climates of China," Energy, Elsevier, vol. 35(5), pages 1946-1953.
    8. Tejero-González, Ana & Andrés-Chicote, Manuel & García-Ibáñez, Paola & Velasco-Gómez, Eloy & Rey-Martínez, Francisco Javier, 2016. "Assessing the applicability of passive cooling and heating techniques through climate factors: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 727-742.

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