IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v168y2022ics136403212200750x.html
   My bibliography  Save this article

Empirical sunshine-based models vs online estimators for solar resources

Author

Listed:
  • Paulescu, Marius
  • Badescu, Viorel
  • Budea, Sanda
  • Dumitrescu, Alexandru

Abstract

Monthly averaged daily global solar irradiation data collected from four online platforms (NASA POWER, MERRA2, ERA5 and CAMS) are compared with ground measured data retrieved from World Radiation Data Center and Baseline Surface Radiation Network. Similarly, monthly averaged daily global solar irradiation estimated by five different Ångström-Prescott-type equations have been compared with the same ground measured data. The accuracy of the online platforms and Ångström – Prescott equations, respectively, is largely comparable, although some differences are noticed. Both the platforms and the Ångström-Prescott equations are sensitive to climates. A tendency of the Ångström-Prescott equations to exceed the platforms performance in the tropical and continental climates was noticed. Without exception the platforms and models perform better in summer than in winter. No Ångström – Prescott equation outperforms the platforms during all seasons, and, mutually, no platform outperforms the Ångström – Prescott equations during all seasons.

Suggested Citation

  • Paulescu, Marius & Badescu, Viorel & Budea, Sanda & Dumitrescu, Alexandru, 2022. "Empirical sunshine-based models vs online estimators for solar resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  • Handle: RePEc:eee:rensus:v:168:y:2022:i:c:s136403212200750x
    DOI: 10.1016/j.rser.2022.112868
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S136403212200750X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rser.2022.112868?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. Jánosi, Imre M. & Medjdoub, Karim & Vincze, Miklós, 2021. "Combined wind-solar electricity production potential over north-western Africa," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    2. Bakirci, Kadir, 2009. "Correlations for estimation of daily global solar radiation with hours of bright sunshine in Turkey," Energy, Elsevier, vol. 34(4), pages 485-501.
    3. Despotovic, Milan & Nedic, Vladimir & Despotovic, Danijela & Cvetanovic, Slobodan, 2015. "Review and statistical analysis of different global solar radiation sunshine models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1869-1880.
    4. Sun, Xixi & Bright, Jamie M. & Gueymard, Christian A. & Acord, Brendan & Wang, Peng & Engerer, Nicholas A., 2019. "Worldwide performance assessment of 75 global clear-sky irradiance models using Principal Component Analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 550-570.
    5. Aliana, Arnau & Chang, Miguel & Østergaard, Poul Alberg & Victoria, Marta & Andersen, Anders N., 2022. "Performance assessment of using various solar radiation data in modelling large-scale solar thermal systems integrated in district heating networks," Renewable Energy, Elsevier, vol. 190(C), pages 699-712.
    6. Psiloglou, B.E. & Kambezidis, H.D. & Kaskaoutis, D.G. & Karagiannis, D. & Polo, J.M., 2020. "Comparison between MRM simulations, CAMS and PVGIS databases with measured solar radiation components at the Methoni station, Greece," Renewable Energy, Elsevier, vol. 146(C), pages 1372-1391.
    7. Boilley, Alexandre & Wald, Lucien, 2015. "Comparison between meteorological re-analyses from ERA-Interim and MERRA and measurements of daily solar irradiation at surface," Renewable Energy, Elsevier, vol. 75(C), pages 135-143.
    8. Paulescu, M. & Stefu, N. & Calinoiu, D. & Paulescu, E. & Pop, N. & Boata, R. & Mares, O., 2016. "Ångström–Prescott equation: Physical basis, empirical models and sensitivity analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 495-506.
    9. Almorox, Javier & Voyant, Cyril & Bailek, Nadjem & Kuriqi, Alban & Arnaldo, J.A., 2021. "Total solar irradiance's effect on the performance of empirical models for estimating global solar radiation: An empirical-based review," Energy, Elsevier, vol. 236(C).
    10. Antonanzas-Torres, F. & Cañizares, F. & Perpiñán, O., 2013. "Comparative assessment of global irradiation from a satellite estimate model (CM SAF) and on-ground measurements (SIAR): A Spanish case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 248-261.
    11. Prieto, Jesús-Ignacio & García, David, 2022. "Global solar radiation models: A critical review from the point of view of homogeneity and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    12. Cao, Qimeng & Liu, Yan & Sun, Xue & Yang, Liu, 2022. "Country-level evaluation of solar radiation data sets using ground measurements in China," Energy, Elsevier, vol. 241(C).
    13. Ramirez Camargo, Luis & Dorner, Wolfgang, 2016. "Comparison of satellite imagery based data, reanalysis data and statistical methods for mapping global solar radiation in the Lerma Valley (Salta, Argentina)," Renewable Energy, Elsevier, vol. 99(C), pages 57-68.
    14. Salazar, Germán & Gueymard, Christian & Galdino, Janis Bezerra & de Castro Vilela, Olga & Fraidenraich, Naum, 2020. "Solar irradiance time series derived from high-quality measurements, satellite-based models, and reanalyses at a near-equatorial site in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    Full references (including those not matched with items on IDEAS)

    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. Makade, Rahul G. & Chakrabarti, Siddharth & Jamil, Basharat & Sakhale, C.N., 2020. "Estimation of global solar radiation for the tropical wet climatic region of India: A theory of experimentation approach," Renewable Energy, Elsevier, vol. 146(C), pages 2044-2059.
    2. Ramirez Camargo, Luis & Gruber, Katharina & Nitsch, Felix, 2019. "Assessing variables of regional reanalysis data sets relevant for modelling small-scale renewable energy systems," Renewable Energy, Elsevier, vol. 133(C), pages 1468-1478.
    3. Qiu, Rangjian & Li, Longan & Wu, Lifeng & Agathokleous, Evgenios & Liu, Chunwei & Zhang, Baozhong & Luo, Yufeng & Sun, Shanlei, 2022. "Modeling daily global solar radiation using only temperature data: Past, development, and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    4. Yang, Dazhi, 2022. "Estimating 1-min beam and diffuse irradiance from the global irradiance: A review and an extensive worldwide comparison of latest separation models at 126 stations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    5. Wang, Lunche & Kisi, Ozgur & Zounemat-Kermani, Mohammad & Salazar, Germán Ariel & Zhu, Zhongmin & Gong, Wei, 2016. "Solar radiation prediction using different techniques: model evaluation and comparison," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 384-397.
    6. Paulescu, M. & Stefu, N. & Calinoiu, D. & Paulescu, E. & Pop, N. & Boata, R. & Mares, O., 2016. "Ångström–Prescott equation: Physical basis, empirical models and sensitivity analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 495-506.
    7. 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.
    8. Fan, Junliang & Wu, Lifeng & Zhang, Fucang & Cai, Huanjie & Zeng, Wenzhi & Wang, Xiukang & Zou, Haiyang, 2019. "Empirical and machine learning models for predicting daily global solar radiation from sunshine duration: A review and case study in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 186-212.
    9. Chen, Ji-Long & He, Lei & Yang, Hong & Ma, Maohua & Chen, Qiao & Wu, Sheng-Jun & Xiao, Zuo-lin, 2019. "Empirical models for estimating monthly global solar radiation: A most comprehensive review and comparative case study in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 91-111.
    10. Qin, Shujing & Liu, Zhihe & Qiu, Rangjian & Luo, Yufeng & Wu, Jingwei & Zhang, Baozhong & Wu, Lifeng & Agathokleous, Evgenios, 2023. "Short–term global solar radiation forecasting based on an improved method for sunshine duration prediction and public weather forecasts," Applied Energy, Elsevier, vol. 343(C).
    11. Zhang, Jianyuan & Zhao, Li & Deng, Shuai & Xu, Weicong & Zhang, Ying, 2017. "A critical review of the models used to estimate solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 314-329.
    12. Urraca, R. & Martinez-de-Pison, E. & Sanz-Garcia, A. & Antonanzas, J. & Antonanzas-Torres, F., 2017. "Estimation methods for global solar radiation: Case study evaluation of five different approaches in central Spain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1098-1113.
    13. Mecibah, Mohamed Salah & Boukelia, Taqiy Eddine & Tahtah, Reda & Gairaa, Kacem, 2014. "Introducing the best model for estimation the monthly mean daily global solar radiation on a horizontal surface (Case study: Algeria)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 194-202.
    14. Kokou Amega & Yendoubé Laré & Ramchandra Bhandari & Yacouba Moumouni & Aklesso Y. G. Egbendewe & Windmanagda Sawadogo & Saidou Madougou, 2022. "Solar Energy Powered Decentralized Smart-Grid for Sustainable Energy Supply in Low-Income Countries: Analysis Considering Climate Change Influences in Togo," Energies, MDPI, vol. 15(24), pages 1-24, December.
    15. Hernández-Escobedo, Q. & Fernández-García, A. & Manzano-Agugliaro, F., 2017. "Solar resource assessment for rural electrification and industrial development in the Yucatan Peninsula (Mexico)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1550-1561.
    16. Chen, Shanlin & Li, Mengying, 2022. "Improved turbidity estimation from local meteorological data for solar resourcing and forecasting applications," Renewable Energy, Elsevier, vol. 189(C), pages 259-272.
    17. Enrique A. Enríquez-Velásquez & Victor H. Benitez & Sergey G. Obukhov & Luis C. Félix-Herrán & Jorge de-J. Lozoya-Santos, 2020. "Estimation of Solar Resource Based on Meteorological and Geographical Data: Sonora State in Northwestern Territory of Mexico as Case Study," Energies, MDPI, vol. 13(24), pages 1-41, December.
    18. Bright, Jamie M. & Sun, Xixi & Gueymard, Christian A. & Acord, Brendan & Wang, Peng & Engerer, Nicholas A., 2020. "Bright-Sun: A globally applicable 1-min irradiance clear-sky detection model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
    19. Sun, Xixi & Bright, Jamie M. & Gueymard, Christian A. & Bai, Xinyu & Acord, Brendan & Wang, Peng, 2021. "Worldwide performance assessment of 95 direct and diffuse clear-sky irradiance models using principal component analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    20. Dos Santos, Cícero Manoel & De Souza, José Leonaldo & Ferreira Junior, Ricardo Araujo & Tiba, Chigueru & de Melo, Rinaldo Oliveira & Lyra, Gustavo Bastos & Teodoro, Iêdo & Lyra, Guilherme Bastos & Lem, 2014. "On modeling global solar irradiation using air temperature for Alagoas State, Northeastern Brazil," Energy, Elsevier, vol. 71(C), pages 388-398.

    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:rensus:v:168:y:2022:i:c:s136403212200750x. 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.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.