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Recent improvements of the Meteorological Radiation Model for solar irradiance estimates under all-sky conditions

Author

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  • Kambezidis, H.D.
  • Psiloglou, B.E.
  • Karagiannis, D.
  • Dumka, U.C.
  • Kaskaoutis, D.G.

Abstract

This study presents the recent improvements of the Meteorological Radiation Model (MRM v6) against previous model versions for more accurate estimates of the solar radiation components, i.e. global, diffuse and direct. The MRM v6 follows a different approach for the simulation of the atmospheric conditions by selecting the most appropriate aerosol model (desert, urban, maritime or continental), and usage of look-up tables for the spectral variation of the aerosol optical depth (AOD) and single scattering albedo (SSA). Furthermore, the MRM v6 uses hourly data of sunshine duration in order to achieve better simulations under cloudy skies. The results show that the MRM v6 improves the estimates of the measured global, diffuse and direct solar irradiances at Athens, Greece since the Root Mean Square Error (RMSE) becomes 13.7%, 40.8% and 24.2%, respectively, against 18.0%, 44.5% and 34.1% for the MRM v5. A decrease is also found in Mean Bias Error (MBE), especially for the diffuse (from 26.2% to 19.5%) and direct (from −9.0% to −2.4%) irradiances, indicating that the inclusion of the aerosol properties in MRM v6 significantly improves the estimations. The MRM simulations are very satisfactory on monthly basis indicating that the model is suitable for solar energy applications.

Suggested Citation

  • Kambezidis, H.D. & Psiloglou, B.E. & Karagiannis, D. & Dumka, U.C. & Kaskaoutis, D.G., 2016. "Recent improvements of the Meteorological Radiation Model for solar irradiance estimates under all-sky conditions," Renewable Energy, Elsevier, vol. 93(C), pages 142-158.
  • Handle: RePEc:eee:renene:v:93:y:2016:i:c:p:142-158
    DOI: 10.1016/j.renene.2016.02.060
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    Cited by:

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    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. Moldovan, Camelia Liliana & Păltănea, Radu & Visa, Ion, 2020. "Improvement of clear sky models for direct solar irradiance considering turbidity factor variable during the day," Renewable Energy, Elsevier, vol. 161(C), pages 559-569.
    8. Ruiz-Arias, José A., 2021. "Aerosol transmittance for clear-sky solar irradiance models: Review and validation of an accurate universal parameterization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
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    11. Tingting Zhu & Yiren Guo & Cong Wang & Chao Ni, 2020. "Inter-Hour Forecast of Solar Radiation Based on the Structural Equation Model and Ensemble Model," Energies, MDPI, vol. 13(17), pages 1-15, September.
    12. 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.
    13. Torres, José Luis & García, Ignacio, 2021. "Analytical expressions for estimating sky diffuse irradiance and illuminance on tilted planes for the CIE Standard General Skies," Renewable Energy, Elsevier, vol. 174(C), pages 320-335.
    14. Su, Gang & Zhang, Shuangyang & Hu, Mengru & Yao, Wanxiang & Li, Ziwei & Xi, Yue, 2022. "The modified layer-by-layer weakening solar radiation models based on relative humidity and air quality index," Energy, Elsevier, vol. 239(PE).
    15. Qin, Wenmin & Wang, Lunche & Lin, Aiwen & Zhang, Ming & Xia, Xiangao & Hu, Bo & Niu, Zigeng, 2018. "Comparison of deterministic and data-driven models for solar radiation estimation in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 579-594.
    16. Zhou, Zhigao & Wang, Lunche & Lin, Aiwen & Zhang, Ming & Niu, Zigeng, 2018. "Innovative trend analysis of solar radiation in China during 1962–2015," Renewable Energy, Elsevier, vol. 119(C), pages 675-689.
    17. 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.
    18. Ruiz-Arias, José A., 2022. "Spectral integration of clear-sky atmospheric transmittance: Review and worldwide performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    19. Paulescu, Eugenia & Paulescu, Marius, 2021. "A new clear sky solar irradiance model," Renewable Energy, Elsevier, vol. 179(C), pages 2094-2103.
    20. Paredes, Paula & Trigo, Isabel & de Bruin, Henk & Simões, Nuno & Pereira, Luis S., 2021. "Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products," Agricultural Water Management, Elsevier, vol. 248(C).
    21. Cao, Fei & Li, Huashan & Yang, Tian & Li, Yan & Zhu, Tianyu & Zhao, Liang, 2017. "Evaluation of diffuse solar radiation models in Northern China: New model establishment and radiation sources comparison," Renewable Energy, Elsevier, vol. 103(C), pages 708-720.

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