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Generation of typical meteorological year for different climates of China

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  • Jiang, Yingni

Abstract

Accurate prediction of building energy performance requires precise information of the local climate. Typical weather year files like typical meteorological year (TMY) are commonly used in building simulation. They are also essential for numerical analysis of sustainable and renewable energy systems. The present paper presents the generation of typical meteorological year (TMY) for eight typical cities representing the major climate zones of China. The data set, which includes global solar radiation data and other meteorological parameters referring to dry bulb temperature, relative humidity, wind speed, has been analyzed. The typical meteorological year is generated from the available meteorological data recorded during the period 1995–2004, using the Finkelstein-Schafer statistical method. The cumulative distribution function (CDF) for each year is compared with the CDF for the long-term composite of all the years in the period. Typical months for each of the 12 calendar months from the period of years are selected by choosing the one with the smallest deviation from the long-term CDF. The 12 typical months selected from the different years are used for the formulation of a TMY.

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  • Jiang, Yingni, 2010. "Generation of typical meteorological year for different climates of China," Energy, Elsevier, vol. 35(5), pages 1946-1953.
    • Handle: RePEc:eee:energy:v:35:y:2010:i:5:p:1946-1953
    DOI: 10.1016/j.energy.2010.01.009
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    1. 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.
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    3. Ohunakin, Olayinka S. & Adaramola, Muyiwa S. & Oyewola, Olanrewaju M. & Fagbenle, Richard O., 2013. "Generation of a typical meteorological year for north–east, Nigeria," Applied Energy, Elsevier, vol. 112(C), pages 152-159.
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    7. 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.
    8. 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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    10. Haixiang Zang & Miaomiao Wang & Jing Huang & Zhinong Wei & Guoqiang Sun, 2016. "A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China," Energies, MDPI, vol. 9(12), pages 1-19, December.
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    12. Carra, Elena & Ballestrín, Jesús & Polo, Jesús & Barbero, Javier & Fernández-Reche, Jesús, 2018. "Atmospheric extinction levels of solar radiation at Plataforma Solar de Almería. Application to solar thermal electric plants," Energy, Elsevier, vol. 145(C), pages 400-407.
    13. Sun, Jingting & Li, Zhengrong & Xiao, Fu & Xiao, Jianzhuang, 2020. "Generation of typical meteorological year for integrated climate based daylight modeling and building energy simulation," Renewable Energy, Elsevier, vol. 160(C), pages 721-729.
    14. Jing Zhao & Yaoqi Duan & Xiaojuan Liu, 2018. "Uncertainty Analysis of Weather Forecast Data for Cooling Load Forecasting Based on the Monte Carlo Method," Energies, MDPI, vol. 11(7), pages 1-18, July.
    15. Fan, Xinying, 2022. "A method for the generation of typical meteorological year data using ensemble empirical mode decomposition for different climates of China and performance comparison analysis," Energy, Elsevier, vol. 240(C).
    16. Kulesza, Kinga, 2017. "Comparison of typical meteorological year and multi-year time series of solar conditions for Belsk, central Poland," Renewable Energy, Elsevier, vol. 113(C), pages 1135-1140.
    17. Li, Honglian & Huang, Jin & Hu, Yao & Wang, Shangyu & Liu, Jing & Yang, Liu, 2021. "A new TMY generation method based on the entropy-based TOPSIS theory for different climatic zones in China," Energy, Elsevier, vol. 231(C).
    18. Li, Chong & Zhou, Dequn & Wang, Hui & Lu, Yuzheng & Li, Dongdong, 2020. "Techno-economic performance study of stand-alone wind/diesel/battery hybrid system with different battery technologies in the cold region of China," Energy, Elsevier, vol. 192(C).
    19. Huang, Kuo-Tsang, 2020. "Identifying a suitable hourly solar diffuse fraction model to generate the typical meteorological year for building energy simulation application," Renewable Energy, Elsevier, vol. 157(C), pages 1102-1115.
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    21. 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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