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Generation of typical solar radiation data for different climates of China

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  • Zang, Haixiang
  • Xu, Qingshan
  • Bian, Haihong

Abstract

In this study, typical solar radiation data are generated from both measured data and synthetic generation for 35 stations in six different climatic zones of China. (1) By applying the measured weather data during at least 10 years from 1994 to 2009, typical meteorological years (TMYs) for 35 cities are generated using the Finkelstein–Schafer statistical method. The cumulative distribution function (CDF) of daily global solar radiation (DGSR) for each year is compared with the CDF of DGSR for the long-term years in six different climatic stations (Sanya, Shanghai, Zhengzhou, Harbin, Mohe and Lhasa). The daily global solar radiation as typical data obtained from the TMYs are presented in the Table. (2) Based on the recorded global radiation data from at least 10 years, a new daily global solar radiation model is developed with a sine and cosine wave (SCW) equation. The results of the proposed model and other empirical regression models are compared with measured data using different statistical indicators. It is found that solar radiation data, calculated by the new model, are superior to these from other empirical models at six typical climatic zones. In addition, the novel SCW model is tested and applied for 35 stations in China.

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  • 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.
    • Handle: RePEc:eee:energy:v:38:y:2012:i:1:p:236-248
    DOI: 10.1016/j.energy.2011.12.008
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    13. Halawa, Edward & GhaffarianHoseini, AmirHosein & Hin Wa Li, Danny, 2014. "Empirical correlations as a means for estimating monthly average daily global radiation: A critical overview," Renewable Energy, Elsevier, vol. 72(C), pages 149-153.
    14. Abreu, Edgar F.M. & Canhoto, Paulo & Prior, Victor & Melicio, R., 2018. "Solar resource assessment through long-term statistical analysis and typical data generation with different time resolutions using GHI measurements," Renewable Energy, Elsevier, vol. 127(C), pages 398-411.
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    16. Kaplani, E. & Kaplanis, S. & Mondal, S., 2018. "A spatiotemporal universal model for the prediction of the global solar radiation based on Fourier series and the site altitude," Renewable Energy, Elsevier, vol. 126(C), pages 933-942.
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    18. Xinying Fan & Bin Chen & Changfeng Fu & Lingyun Li, 2020. "Research on the Influence of Abrupt Climate Changes on the Analysis of Typical Meteorological Year in China," Energies, MDPI, vol. 13(24), pages 1-16, December.

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