IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v126y2018icp226-241.html
   My bibliography  Save this article

Estimation of daily and monthly diffuse radiation from measurements of global solar radiation a case study across China

Author

Listed:
  • Wang, Hong
  • Sun, Fubao
  • Wang, Tingting
  • Liu, Wenbin

Abstract

With increasing demand for energy, broaden renewable energy of income and reduce expenditure is becoming more and more important. Diffuse radiation (Rd) is an important consideration in building energy saving. Hundreds of methods were developed to calculate Rd because it is seldom available in many countries and its spatial-pattern is strongly station-dependent. There are only 13 stations that monitor both global solar radiation (Rs) and Rd after 1993 across China. Based on 812640 measurements of daily Rs and Rd collected from 80 stations across China during 1957–2014, we wished to calibrate and validate a simple approach, which can be easily used to predict Rd over both daily and monthly periods for all locations in China and gave the accurate values of parameters. The approach, of the case study method, is based on Rs and extra-terrestrial solar radiance (Ra). Results showed that the daily method can be employed well, while the monthly approach was applied well in the Southern Region (SR) only. The monthly approach of the Northern Region (NR) was improved using its regional characteristics. The methods achieved can effectively estimate Rd and strongly apply in engineering for only two parameters, which accurate values for all stations has been offered.

Suggested Citation

  • Wang, Hong & Sun, Fubao & Wang, Tingting & Liu, Wenbin, 2018. "Estimation of daily and monthly diffuse radiation from measurements of global solar radiation a case study across China," Renewable Energy, Elsevier, vol. 126(C), pages 226-241.
    • Handle: RePEc:eee:renene:v:126:y:2018:i:c:p:226-241
    DOI: 10.1016/j.renene.2018.03.029
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148118303355
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2018.03.029?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. Cheng, C.L. & Chan, C.Y. & Chen, C.L., 2006. "An empirical approach to estimating monthly radiation on south-facing tilted planes for building application," Energy, Elsevier, vol. 31(14), pages 2940-2957.
    2. Taşdemiroğlu, E & Sever, R, 1991. "Estimation of monthly average, daily, horizontal diffuse radiation in Turkey," Energy, Elsevier, vol. 16(4), pages 787-790.
    3. Jiang, Yingni, 2009. "Estimation of monthly mean daily diffuse radiation in China," Applied Energy, Elsevier, vol. 86(9), pages 1458-1464, September.
    4. Jamil, Basharat & Akhtar, Naiem, 2017. "Estimation of diffuse solar radiation in humid-subtropical climatic region of India: Comparison of diffuse fraction and diffusion coefficient models," Energy, Elsevier, vol. 131(C), pages 149-164.
    5. Matthijs Tollenaar & Jon Fridgen & Priyanka Tyagi & Paul W. Stackhouse Jr & Saratha Kumudini, 2017. "The contribution of solar brightening to the US maize yield trend," Nature Climate Change, Nature, vol. 7(4), pages 275-278, April.
    6. Lou, Siwei & Li, Danny H.W. & Lam, Joseph C. & Chan, Wilco W.H., 2016. "Prediction of diffuse solar irradiance using machine learning and multivariable regression," Applied Energy, Elsevier, vol. 181(C), pages 367-374.
    7. 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.
    8. El-Sebaii, A.A. & Al-Hazmi, F.S. & Al-Ghamdi, A.A. & Yaghmour, S.J., 2010. "Global, direct and diffuse solar radiation on horizontal and tilted surfaces in Jeddah, Saudi Arabia," Applied Energy, Elsevier, vol. 87(2), pages 568-576, February.
    9. 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.
    10. El Mghouchi, Y. & El Bouardi, A. & Choulli, Z. & Ajzoul, T., 2016. "Models for obtaining the daily direct, diffuse and global solar radiations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 87-99.
    11. Kambezidis, H.D. & Psiloglou, B.E. & Karagiannis, D. & Dumka, U.C. & Kaskaoutis, D.G., 2017. "Meteorological Radiation Model (MRM v6.1): Improvements in diffuse radiation estimates and a new approach for implementation of cloud products," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 616-637.
    12. Noorian, Ali Mohammad & Moradi, Isaac & Kamali, Gholam Ali, 2008. "Evaluation of 12 models to estimate hourly diffuse irradiation on inclined surfaces," Renewable Energy, Elsevier, vol. 33(6), pages 1406-1412.
    13. Younes, S. & Claywell, R. & Muneer, T., 2005. "Quality control of solar radiation data: Present status and proposed new approaches," Energy, Elsevier, vol. 30(9), pages 1533-1549.
    14. Zhang, Mingshun & Wang, Mujie & Jin, Wei & Xia-Bauer, Chun, 2018. "Managing energy efficiency of buildings in China: A survey of energy performance contracting (EPC) in building sector," Energy Policy, Elsevier, vol. 114(C), pages 13-21.
    15. Lemos, Leonardo F.L. & Starke, Allan R. & Boland, John & Cardemil, José M. & Machado, Rubinei D. & Colle, Sergio, 2017. "Assessment of solar radiation components in Brazil using the BRL model," Renewable Energy, Elsevier, vol. 108(C), pages 569-580.
    16. Boland, John & Ridley, Barbara & Brown, Bruce, 2008. "Models of diffuse solar radiation," Renewable Energy, Elsevier, vol. 33(4), pages 575-584.
    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. Mohammad Ehteram & Ali Najah Ahmed & Chow Ming Fai & Haitham Abdulmohsin Afan & Ahmed El-Shafie, 2019. "Accuracy Enhancement for Zone Mapping of a Solar Radiation Forecasting Based Multi-Objective Model for Better Management of the Generation of Renewable Energy," Energies, MDPI, vol. 12(14), pages 1-26, July.
    2. Wang, Hong & Sun, Fubao & Liu, Fa & Wang, Tingting & Liu, Wenbin & Feng, Yao, 2023. "Reconstruction of the pan evaporation based on meteorological factors with machine learning method over China," Agricultural Water Management, Elsevier, vol. 287(C).

    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. 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.
    2. 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.
    3. Wang, Lunche & Lu, Yunbo & Zou, Ling & Feng, Lan & Wei, Jing & Qin, Wenmin & Niu, Zigeng, 2019. "Prediction of diffuse solar radiation based on multiple variables in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 151-216.
    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. Feng, Lan & Lin, Aiwen & Wang, Lunche & Qin, Wenmin & Gong, Wei, 2018. "Evaluation of sunshine-based models for predicting diffuse solar radiation in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 168-182.
    6. Yang, Liu & Cao, Qimeng & Yu, Ying & Liu, Yan, 2020. "Comparison of daily diffuse radiation models in regions of China without solar radiation measurement," Energy, Elsevier, vol. 191(C).
    7. Jamil, Basharat & Akhtar, Naiem, 2017. "Estimation of diffuse solar radiation in humid-subtropical climatic region of India: Comparison of diffuse fraction and diffusion coefficient models," Energy, Elsevier, vol. 131(C), pages 149-164.
    8. 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.
    9. Jawed Mustafa & Shahid Husain & Saeed Alqaed & Uzair Ali Khan & Basharat Jamil, 2022. "Performance of Two Variable Machine Learning Models to Forecast Monthly Mean Diffuse Solar Radiation across India under Various Climate Zones," Energies, MDPI, vol. 15(21), pages 1-32, October.
    10. Karakoti, Indira & Pande, Bimal & Pandey, Kavita, 2011. "Evaluation of different diffuse radiation models for Indian stations and predicting the best fit model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(5), pages 2378-2384, June.
    11. Every, Jeremy P. & Li, Li & Dorrell, David G., 2020. "Köppen-Geiger climate classification adjustment of the BRL diffuse irradiation model for Australian locations," Renewable Energy, Elsevier, vol. 147(P1), pages 2453-2469.
    12. Karakoti, Indira & Das, Prasun Kumar & Singh, S.K., 2012. "Predicting monthly mean daily diffuse radiation for India," Applied Energy, Elsevier, vol. 91(1), pages 412-425.
    13. Liu, Yanfeng & Zhou, Yong & Chen, Yaowen & Wang, Dengjia & Wang, Yingying & Zhu, Ying, 2020. "Comparison of support vector machine and copula-based nonlinear quantile regression for estimating the daily diffuse solar radiation: A case study in China," Renewable Energy, Elsevier, vol. 146(C), pages 1101-1112.
    14. Furlan, Claudia & de Oliveira, Amauri Pereira & Soares, Jacyra & Codato, Georgia & Escobedo, João Francisco, 2012. "The role of clouds in improving the regression model for hourly values of diffuse solar radiation," Applied Energy, Elsevier, vol. 92(C), pages 240-254.
    15. Fan, Junliang & Wu, Lifeng & Zhang, Fucang & Cai, Huanjie & Ma, Xin & Bai, Hua, 2019. "Evaluation and development of empirical models for estimating daily and monthly mean daily diffuse horizontal solar radiation for different climatic regions of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 168-186.
    16. Li, Huashan & Ma, Weibin & Wang, Xianlong & Lian, Yongwang, 2011. "Estimating monthly average daily diffuse solar radiation with multiple predictors: A case study," Renewable Energy, Elsevier, vol. 36(7), pages 1944-1948.
    17. 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.
    18. Nunez Munoz, Maria & Ballantyne, Erica E.F. & Stone, David A., 2022. "Development and evaluation of empirical models for the estimation of hourly horizontal diffuse solar irradiance in the United Kingdom," Energy, Elsevier, vol. 241(C).
    19. Zhiyong Tian & Bengt Perers & Simon Furbo & Jianhua Fan & Jie Deng & Janne Dragsted, 2018. "A Comprehensive Approach for Modelling Horizontal Diffuse Radiation, Direct Normal Irradiance and Total Tilted Solar Radiation Based on Global Radiation under Danish Climate Conditions," Energies, MDPI, vol. 11(5), pages 1-19, May.
    20. Abreu, Edgar F.M. & Canhoto, Paulo & Costa, Maria João, 2019. "Prediction of diffuse horizontal irradiance using a new climate zone model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 28-42.

    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:126:y:2018:i:c:p:226-241. 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.