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Comparison of methods for generating typical meteorological year using meteorological data from a tropical environment

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  • Janjai, S.
  • Deeyai, P.

Abstract

This paper presents the comparison of methods for generating typical meteorological year (TMY) data set using a 10-year period of meteorological data from four stations in a tropical environment of Thailand. These methods are the Sadia National Laboratory method, the Danish method and the Festa and Ratto method. In investigating their performance, these methods were employed to generate TMYs for each station. For all parameters of the TMYs and the stations, statistical test indicates that there is no significant difference between the 10-year average values of these parameters and the corresponding average values from TMY generated from each method. The TMY obtained from each method was also used as input data to simulate two solar water heating systems and two photovoltaic systems with different sizes at the four stations by using the TRNSYS simulation program. Solar fractions and electrical output calculated using TMYs are in good agreement with those computed employing the 10-year period hourly meteorological data. It is concluded that the performance of the three methods has no significant difference for all stations under this investigation. Due to its simplicity, the method of Sandia National Laboratories is recommended for the generation of TMY for this tropical environment. The TMYs developed in this work can be used for solar energy and energy conservation applications at the four locations in Thailand.

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  • Janjai, S. & Deeyai, P., 2009. "Comparison of methods for generating typical meteorological year using meteorological data from a tropical environment," Applied Energy, Elsevier, vol. 86(4), pages 528-537, April.
    • Handle: RePEc:eee:appene:v:86:y:2009:i:4:p:528-537
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    Cited by:

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    14. Benghanem, M., 2009. "Measurement of meteorological data based on wireless data acquisition system monitoring," Applied Energy, Elsevier, vol. 86(12), pages 2651-2660, December.
    15. Oluwaseu Kilanko & Sunday O Oyedepo & Joseph O Dirisu & Richard O Leramo & Philip Babalola & Abraham K Aworinde & Mfon Udo & Alexander M Okonkwo & Marvelous I Akomolafe, 2023. "Typical meteorological year data analysis for optimal usage of energy systems at six selected locations in Nigeria," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 18, pages 637-658.
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