IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v29y2004i9p1537-1548.html
   My bibliography  Save this article

Estimation of daily diffuse solar radiation in China

Author

Listed:
  • Jin, Zhou
  • Yezheng, Wu
  • Gang, Yan

Abstract

Applying the measured global and diffuse solar radiation data from 78 meteorological stations in China, a countrywide general correlation model for calculating the daily diffuse radiation was derived on the basis of Liu and Jordan method. Two widely used statistics: root mean square error and mean bias error were used to assess the performance of the correlation. And the correlation shows good behavior when applied to most of the stations. Subsequently, with the measured data from the 78 stations, an analysis of geographical distribution of solar energy resource in China was also presented in the form of clearness index (the ratio of global solar radiation to extraterrestrial radiation) percentage frequency, and results show that the solar energy resource in western and northern China is relatively abundant.

Suggested Citation

  • Jin, Zhou & Yezheng, Wu & Gang, Yan, 2004. "Estimation of daily diffuse solar radiation in China," Renewable Energy, Elsevier, vol. 29(9), pages 1537-1548.
    • Handle: RePEc:eee:renene:v:29:y:2004:i:9:p:1537-1548
    DOI: 10.1016/j.renene.2004.01.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148104000448
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2004.01.014?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gopinathan, K.K. & Soler, Alfonso, 1995. "Diffuse radiation models and monthly-average, daily, diffuse data for a wide latitude range," Energy, Elsevier, vol. 20(7), pages 657-667.
    2. Junfeng, Li & Wan, Yih-huei & Ohi, James M., 1997. "Renewable energy development in China: Resource assessment, technology status, and greenhouse gas mitigation potential," Applied Energy, Elsevier, vol. 56(3-4), pages 381-394, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yin, Kaili & Zhang, Xiaojing & Xie, Jingchao & Hao, Ziyang & Xiao, Guofeng & Liu, Jiaping, 2023. "Modeling hourly solar diffuse fraction on a horizontal surface based on sky conditions clustering," Energy, Elsevier, vol. 272(C).
    2. Khorasanizadeh, Hossein & Mohammadi, Kasra, 2016. "Diffuse solar radiation on a horizontal surface: Reviewing and categorizing the empirical models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 338-362.
    3. Zhou, Jin & Wu, Yezheng & Yan, Gang, 2006. "Generation of typical solar radiation year for China," Renewable Energy, Elsevier, vol. 31(12), pages 1972-1985.
    4. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparison of empirical models to estimate monthly mean diffuse solar radiation from measured data: Case study for humid-subtropical climatic region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1326-1342.
    5. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparative analysis of diffuse solar radiation models based on sky-clearness index and sunshine period for humid-subtropical climatic region of India: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 329-355.
    6. Chen, Ji-Long & He, Lei & Chen, Qiao & Lv, Ming-Quan & Zhu, Hong-Lin & Wen, Zhao-Fei & Wu, Sheng-Jun, 2019. "Study of monthly mean daily diffuse and direct beam radiation estimation with MODIS atmospheric product," Renewable Energy, Elsevier, vol. 132(C), pages 221-232.
    7. Pucar, Mila & Despic, Aleksandar, 2005. "The effect of diffuse/indirect light on the energy gain of solar thermal collectors," Renewable Energy, Elsevier, vol. 30(11), pages 1749-1758.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Murshed, Muntasir, 2019. "Trade Liberalization Policies and Renewable Energy Transition in Low and Middle-Income Countries? An Instrumental Variable Approach," MPRA Paper 97075, University Library of Munich, Germany.
    2. Li, Huashan & Bu, Xianbiao & Lian, Yongwang & Zhao, Liang & Ma, Weibin, 2012. "Further investigation of empirically derived models with multiple predictors in estimating monthly average daily diffuse solar radiation over China," Renewable Energy, Elsevier, vol. 44(C), pages 469-473.
    3. Despotovic, Milan & Nedic, Vladimir & Despotovic, Danijela & Cvetanovic, Slobodan, 2016. "Evaluation of empirical models for predicting monthly mean horizontal diffuse solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 246-260.
    4. Liu, Wen & Lund, Henrik & Mathiesen, Brian Vad & Zhang, Xiliang, 2011. "Potential of renewable energy systems in China," Applied Energy, Elsevier, vol. 88(2), pages 518-525, February.
    5. Wan, Kevin K.W. & Tang, H.L. & Yang, Liu & Lam, Joseph C., 2008. "An analysis of thermal and solar zone radiation models using an Angstrom–Prescott equation and artificial neural networks," Energy, Elsevier, vol. 33(7), pages 1115-1127.
    6. Li, Huashan & Bu, Xianbiao & Long, Zhen & Zhao, Liang & Ma, Weibin, 2012. "Calculating the diffuse solar radiation in regions without solar radiation measurements," Energy, Elsevier, vol. 44(1), pages 611-615.
    7. Sabzpooshani, Majid & Mohammadi, Kasra, 2014. "Establishing new empirical models for predicting monthly mean horizontal diffuse solar radiation in city of Isfahan, Iran," Energy, Elsevier, vol. 69(C), pages 571-577.
    8. Xiao, Chaofeng & Luo, Huilong & Tang, Runsheng & Zhong, Hao, 2004. "Solar thermal utilization in China," Renewable Energy, Elsevier, vol. 29(9), pages 1549-1556.
    9. Wei, Xiaolin & Shang, Yunfeng, 2023. "Modernization of governance at Chinese universities: Role of fossil fuels and green energy resource," Resources Policy, Elsevier, vol. 85(PB).
    10. Elminir, Hamdy K. & Azzam, Yosry A. & Younes, Farag I., 2007. "Prediction of hourly and daily diffuse fraction using neural network, as compared to linear regression models," Energy, Elsevier, vol. 32(8), pages 1513-1523.
    11. Hong, Lixuan & Zhou, Nan & Fridley, David & Raczkowski, Chris, 2013. "Assessment of China's renewable energy contribution during the 12th Five Year Plan," Energy Policy, Elsevier, vol. 62(C), pages 1533-1543.
    12. Zhao, Xiaoli & Lyon, Thomas P. & Song, Cui, 2012. "Lurching towards markets for power: China’s electricity policy 1985–2007," Applied Energy, Elsevier, vol. 94(C), pages 148-155.
    13. Notton, Gilles & Paoli, Christophe & Vasileva, Siyana & Nivet, Marie Laure & Canaletti, Jean-Louis & Cristofari, Christian, 2012. "Estimation of hourly global solar irradiation on tilted planes from horizontal one using artificial neural networks," Energy, Elsevier, vol. 39(1), pages 166-179.
    14. Yang, Jun & Wang, Xiaobing & Ma, Hengyun & Bai, Junfei & Jiang, Ye & Yu, Hai, 2014. "Potential usage, vertical value chain and challenge of biomass resource: Evidence from China’s crop residues," Applied Energy, Elsevier, vol. 114(C), pages 717-723.
    15. Zhou, Jin & Wu, Yezheng & Yan, Gang, 2006. "Generation of typical solar radiation year for China," Renewable Energy, Elsevier, vol. 31(12), pages 1972-1985.
    16. Wu, C.Z. & Yin, X.L. & Yuan, Z.H. & Zhou, Z.Q. & Zhuang, X.S., 2010. "The development of bioenergy technology in China," Energy, Elsevier, vol. 35(11), pages 4445-4450.
    17. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparison of empirical models to estimate monthly mean diffuse solar radiation from measured data: Case study for humid-subtropical climatic region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1326-1342.
    18. Lam, Joseph C. & Wan, Kevin K.W. & Lau, Chris C.S. & Yang, Liu, 2008. "Climatic influences on solar modelling in China," Renewable Energy, Elsevier, vol. 33(7), pages 1591-1604.
    19. Chen, Ji-Long & He, Lei & Chen, Qiao & Lv, Ming-Quan & Zhu, Hong-Lin & Wen, Zhao-Fei & Wu, Sheng-Jun, 2019. "Study of monthly mean daily diffuse and direct beam radiation estimation with MODIS atmospheric product," Renewable Energy, Elsevier, vol. 132(C), pages 221-232.
    20. Lam, J.C.K. & Woo, C.K. & Kahrl, F. & Yu, W.K., 2013. "What moves wind energy development in China? Show me the money!," Applied Energy, Elsevier, vol. 105(C), pages 423-429.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:29:y:2004:i:9:p:1537-1548. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.