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Modeling the hourly solar diffuse fraction in Taiwan

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  • Kuo, Chia-Wei
  • Chang, Wen-Chey
  • Chang, Keh-Chin

Abstract

Using the data for global and diffuse radiation in Tainan, Taiwan, for the years of 2011 and 2012, respectively, four correlation models with five predictors: the hourly clearness index (kt), solar altitude, apparent solar time, daily clearness index and a measure of persistence of global radiation level, are constructed to relate the hourly diffuse fraction on a horizontal surface (d) to the clearness index. Two models use a single logistic equation for all kt values, Eqs. (6) and (7), and the other two models use a set of piece-wise linear equations for four kt intervals, Eqs. (8) and (9). The proposed models are compared respectively with the fourteen models available in the literature, in terms of the four statistical indicators: the mean bias error, the root-mean-square error, the t-statistic and the Bayesian Information Criterion, using the out-of-sample dataset for Tainan, Taiwan. It is concluded from the analysis that the proposed piece-wise linear models perform well in predicting the diffuse fraction, while the performances of the proposed logistic models are more case-dependent. Among those fourteen models considered in this study, the models developed by Erbs et al., Chandrasekaran and Kumar, and Boland et al. have competitive performances as the proposed piece-wise linear models do, when applying to the prediction of diffuse fraction in Tainan, Taiwan.

Suggested Citation

  • Kuo, Chia-Wei & Chang, Wen-Chey & Chang, Keh-Chin, 2014. "Modeling the hourly solar diffuse fraction in Taiwan," Renewable Energy, Elsevier, vol. 66(C), pages 56-61.
  • Handle: RePEc:eee:renene:v:66:y:2014:i:c:p:56-61
    DOI: 10.1016/j.renene.2013.11.072
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    References listed on IDEAS

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    1. Torres, J.L. & De Blas, M. & García, A. & de Francisco, A., 2010. "Comparative study of various models in estimating hourly diffuse solar irradiance," Renewable Energy, Elsevier, vol. 35(6), pages 1325-1332.
    2. Soares, Jacyra & Oliveira, Amauri P. & Boznar, Marija Zlata & Mlakar, Primoz & Escobedo, João F. & Machado, Antonio J., 2004. "Modeling hourly diffuse solar-radiation in the city of São Paulo using a neural-network technique," Applied Energy, Elsevier, vol. 79(2), pages 201-214, October.
    3. Jacovides, C.P. & Tymvios, F.S. & Assimakopoulos, V.D. & Kaltsounides, N.A., 2006. "Comparative study of various correlations in estimating hourly diffuse fraction of global solar radiation," Renewable Energy, Elsevier, vol. 31(15), pages 2492-2504.
    4. Boland, John & Ridley, Barbara & Brown, Bruce, 2008. "Models of diffuse solar radiation," Renewable Energy, Elsevier, vol. 33(4), pages 575-584.
    5. Ridley, Barbara & Boland, John & Lauret, Philippe, 2010. "Modelling of diffuse solar fraction with multiple predictors," Renewable Energy, Elsevier, vol. 35(2), pages 478-483.
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    Cited by:

    1. Li, Fen & Lin, Yilun & Guo, Jianping & Wang, Yue & Mao, Ling & Cui, Yang & Bai, Yongqing, 2020. "Novel models to estimate hourly diffuse radiation fraction for global radiation based on weather type classification," Renewable Energy, Elsevier, vol. 157(C), pages 1222-1232.
    2. Liu, Peirong & Tong, Xiaojuan & Zhang, Jinsong & Meng, Ping & Li, Jun & Zhang, Jingru, 2020. "Estimation of half-hourly diffuse solar radiation over a mixed plantation in north China," Renewable Energy, Elsevier, vol. 149(C), pages 1360-1369.
    3. Lin, Chun-Tin & Chang, Keh-Chin & Chung, Kung-Ming, 2023. "Re-modeling the solar diffuse fraction in Taiwan on basis of a typical-meteorological-year data," Renewable Energy, Elsevier, vol. 204(C), pages 823-835.
    4. 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.
    5. Seyed Abbas Mousavi Maleki & H. Hizam & Chandima Gomes, 2017. "Estimation of Hourly, Daily and Monthly Global Solar Radiation on Inclined Surfaces: Models Re-Visited," Energies, MDPI, vol. 10(1), pages 1-28, January.

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