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Generalized Models for Estimation of Diffuse Solar Radiation Based on Clearness Index

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Part of the book series: Environmental Science and Engineering ((ENVENG))

Abstract

The acquisition of accurate knowledge of diffuse solar radiation is essential for the conversion and application of solar energy. Nevertheless, most regions around China lack the accurate measured diffuse solar radiation. The main purpose of this study is to establish reliable models for estimating diffuse solar radiation based on the clearness index for both annual and seasonal scenarios. For this purpose, 15 existing diffuse solar radiation models, including nine existing diffuse fraction and six existing diffuse coefficient models, were calibrated for estimation of daily diffuse solar radiation. Long-term, continuously measured global and diffuse solar radiation data were utilized as calibration and validation models. Five statistical parameters such as the mean absolute error (MAE), root mean square error (RMSE), uncertainty indicator at 95% (U95), mean absolute percentage error (MAPE), the correlation coefficient (R), and a global performance indicator (GPI) were used for evaluating the performance and accuracy of the calibrated models. The results showed that the calibrated best-performing models can estimate the daily diffuse solar radiation on a horizontal surface with good accuracy for both annual and seasonal scenarios. Moreover, the calibrated best-performing models can be used for estimating the daily diffuse solar radiation in regions like Wuhan.

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Acknowledgements

The project is supported by National Key R&D Program of China (No. 2018YFD1100700). We sincerely thank the National Meteorological Information Center of China Meteorological Administration for providing the diffuse solar radiation data.

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Correspondence to Zhigang Ren .

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Song, Z., Ren, Z., Deng, Q., Chen, X. (2020). Generalized Models for Estimation of Diffuse Solar Radiation Based on Clearness Index. In: Wang, Z., Zhu, Y., Wang, F., Wang, P., Shen, C., Liu, J. (eds) Proceedings of the 11th International Symposium on Heating, Ventilation and Air Conditioning (ISHVAC 2019). ISHVAC 2019. Environmental Science and Engineering(). Springer, Singapore. https://doi.org/10.1007/978-981-13-9528-4_11

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