IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v146y2020icp1372-1391.html
   My bibliography  Save this article

Comparison between MRM simulations, CAMS and PVGIS databases with measured solar radiation components at the Methoni station, Greece

Author

Listed:
  • Psiloglou, B.E.
  • Kambezidis, H.D.
  • Kaskaoutis, D.G.
  • Karagiannis, D.
  • Polo, J.M.

Abstract

This study examines the performance of the estimated solar radiation components obtained via the Meteorological Radiation Model, satellite-based data sets (CAMS, PVGIS-CMSAF-SARAH) and reanalysis (PVGIS-ERA5) against ground measurements taken with the Sunshine-Pyranometer at Methoni station, Greece. MRM shows satisfactory simulations for the global solar irradiation (R2 = 0.97, RMSE = 11.5%, MBE = −2.5%) at 15-min time-intervals, while for the diffuse larger biases are found (R2 = 0.57, RMSE = 45%). Solar irradiation estimates via CAMS at 15-min intervals reveal RMSE values of 19.5%, 38% and 28% for the global, diffuse and direct radiations, respectively. Biases are progressively reduced for hourly, daily and monthly data sets. PVGIS databases simulate the global irradiance reasonably well (R2 = 0.82–0.92), exhibiting high uncertainties for the diffuse (R2 = 0.39–0.49) and direct (R2 = 0.75–0.87), regarding instantaneous measurements. Simulations under clear-sky conditions of all components are found to be significantly improved, from both MRM, satellite-based retrievals and reanalysis. Overcast and partially cloudy skies result in large uncertainties, especially for the diffuse and direct irradiations, since the satellite sensors may detect clouds at time intervals of unobstructed Sun disk by clouds. In addition, broken bright clouds near to the Sun's disk may increase significantly the measured diffuse irradiance, leading to large biases in the simulations from both MRM and satellite databases.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:146:y:2020:i:c:p:1372-1391
    DOI: 10.1016/j.renene.2019.07.064
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148119310845
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2019.07.064?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. Khatib, Tamer & Mohamed, Azah & Sopian, K., 2012. "A review of solar energy modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2864-2869.
    2. Gherboudj, Imen & Ghedira, Hosni, 2016. "Assessment of solar energy potential over the United Arab Emirates using remote sensing and weather forecast data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 1210-1224.
    3. 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.
    4. Linares-Rodriguez, Alvaro & Ruiz-Arias, José Antonio & Pozo-Vazquez, David & Tovar-Pescador, Joaquin, 2013. "An artificial neural network ensemble model for estimating global solar radiation from Meteosat satellite images," Energy, Elsevier, vol. 61(C), pages 636-645.
    5. Otsuki, Takashi, 2017. "Costs and benefits of large-scale deployment of wind turbines and solar PV in Mongolia for international power exports," Renewable Energy, Elsevier, vol. 108(C), pages 321-335.
    6. Yadav, Amit Kumar & Malik, Hasmat & Chandel, S.S., 2015. "Application of rapid miner in ANN based prediction of solar radiation for assessment of solar energy resource potential of 76 sites in Northwestern India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1093-1106.
    7. Olatomiwa, Lanre & Mekhilef, Saad & Shamshirband, Shahaboddin & Petković, Dalibor, 2015. "Adaptive neuro-fuzzy approach for solar radiation prediction in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1784-1791.
    8. Ana Maria Gracia Amillo & Thomas Huld & Paraskevi Vourlioti & Richard Müller & Matthew Norton, 2015. "Application of Satellite-Based Spectrally-Resolved Solar Radiation Data to PV Performance Studies," Energies, MDPI, vol. 8(5), pages 1-34, April.
    9. Vernay, Christophe & Blanc, Philippe & Pitaval, Sébastien, 2013. "Characterizing measurements campaigns for an innovative calibration approach of the global horizontal irradiation estimated by HelioClim-3," Renewable Energy, Elsevier, vol. 57(C), pages 339-347.
    10. Jacovides, C.P. & Kaskaoutis, D.G. & Tymvios, F.S. & Asimakopoulos, D.N., 2004. "Application of SPCTRAL2 parametric model in estimating spectral solar irradiances over polluted Athens atmosphere," Renewable Energy, Elsevier, vol. 29(7), pages 1109-1119.
    11. Xu, Xiaojun & Du, Huaqiang & Zhou, Guomo & Mao, Fangjie & Li, Pingheng & Fan, Weiliang & Zhu, Dien, 2016. "A method for daily global solar radiation estimation from two instantaneous values using MODIS atmospheric products," Energy, Elsevier, vol. 111(C), pages 117-125.
    12. 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.
    13. Kaskaoutis, D.G. & Kambezidis, H.D., 2008. "The role of aerosol models of the SMARTS code in predicting the spectral direct-beam irradiance in an urban area," Renewable Energy, Elsevier, vol. 33(7), pages 1532-1543.
    14. Park, Sang Yong & Yun, Bo-Yeong & Yun, Chang Yeol & Lee, Duk Hee & Choi, Dong Gu, 2016. "An analysis of the optimum renewable energy portfolio using the bottom–up model: Focusing on the electricity generation sector in South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 319-329.
    15. 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.
    16. Polo, J. & Antonanzas-Torres, F. & Vindel, J.M. & Ramirez, L., 2014. "Sensitivity of satellite-based methods for deriving solar radiation to different choice of aerosol input and models," Renewable Energy, Elsevier, vol. 68(C), pages 785-792.
    17. Polo, J. & Martín, L. & Vindel, J.M., 2015. "Correcting satellite derived DNI with systematic and seasonal deviations: Application to India," Renewable Energy, Elsevier, vol. 80(C), pages 238-243.
    18. 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.
    19. 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.
    20. Kanters, Jouri & Wall, Maria, 2016. "A planning process map for solar buildings in urban environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 173-185.
    21. Gueymard, Christian A., 2005. "Interdisciplinary applications of a versatile spectral solar irradiance model: A review," Energy, Elsevier, vol. 30(9), pages 1551-1576.
    22. Akarslan, Emre & Hocaoglu, Fatih Onur, 2016. "A novel adaptive approach for hourly solar radiation forecasting," Renewable Energy, Elsevier, vol. 87(P1), pages 628-633.
    23. Paliatsos, A.G. & Kambezidis, H.D. & Antoniou, A., 2003. "Diffuse solar irradiation at a location in the Balkan Peninsula," Renewable Energy, Elsevier, vol. 28(13), pages 2147-2156.
    24. Lombardi, P. & Sokolnikova, T. & Suslov, K. & Voropai, N. & Styczynski, Z.A., 2016. "Isolated power system in Russia: A chance for renewable energies?," Renewable Energy, Elsevier, vol. 90(C), pages 532-541.
    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. Tan, Yunhui & Wang, Quan & Zhang, Zhaoyang, 2023. "Near-real-time estimation of global horizontal irradiance from Himawari-8 satellite data," Renewable Energy, Elsevier, vol. 215(C).
    2. Özdemir, Samed & Yavuzdoğan, Ahmet & Bilgilioğlu, Burhan Baha & Akbulut, Zeynep, 2023. "SPAN: An open-source plugin for photovoltaic potential estimation of individual roof segments using point cloud data," Renewable Energy, Elsevier, vol. 216(C).
    3. Tefera Mekonnen & Ramchandra Bhandari & Venkata Ramayya, 2021. "Modeling, Analysis and Optimization of Grid-Integrated and Islanded Solar PV Systems for the Ethiopian Residential Sector: Considering an Emerging Utility Tariff Plan for 2021 and Beyond," Energies, MDPI, vol. 14(11), pages 1-24, June.
    4. Federico Minelli & Diana D’Agostino & Maria Migliozzi & Francesco Minichiello & Pierpaolo D’Agostino, 2023. "PhloVer: A Modular and Integrated Tracking Photovoltaic Shading Device for Sustainable Large Urban Spaces—Preliminary Study and Prototyping," Energies, MDPI, vol. 16(15), pages 1-35, August.
    5. Memme, Samuele & Fossa, Marco, 2022. "Maximum energy yield of PV surfaces in France and Italy from climate based equations for optimum tilt at different azimuth angles," Renewable Energy, Elsevier, vol. 200(C), pages 845-866.
    6. Ameur, Arechkik & Berrada, Asmae & Bouaichi, Abdellatif & Loudiyi, Khalid, 2022. "Long-term performance and degradation analysis of different PV modules under temperate climate," Renewable Energy, Elsevier, vol. 188(C), pages 37-51.
    7. 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).
    8. Buscemi, A. & Guarino, S. & Ciulla, G. & Lo Brano, V., 2021. "A methodology for optimisation of solar dish-Stirling systems size, based on the local frequency distribution of direct normal irradiance," Applied Energy, Elsevier, vol. 303(C).
    9. Maria. C. Bueso & José Miguel Paredes-Parra & Antonio Mateo-Aroca & Angel Molina-García, 2020. "A Characterization of Metrics for Comparing Satellite-Based and Ground-Measured Global Horizontal Irradiance Data: A Principal Component Analysis Application," Sustainability, MDPI, vol. 12(6), pages 1-18, March.
    10. Jianhui Bai & Xuemei Zong & Yaoming Ma & Binbin Wang & Chuanfeng Zhao & Yikung Yang & Jie Guang & Zhiyuan Cong & Kaili Li & Tao Song, 2022. "Long-Term Variations in Global Solar Radiation and Its Interaction with Atmospheric Substances at Qomolangma," IJERPH, MDPI, vol. 19(15), pages 1-24, July.
    11. Sánchez-Aparicio, M. & Martín-Jiménez, J. & Del Pozo, S. & González-González, E. & Lagüela, S., 2021. "Ener3DMap-SolarWeb roofs: A geospatial web-based platform to compute photovoltaic potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    12. António Couto & Ana Estanqueiro, 2020. "Exploring Wind and Solar PV Generation Complementarity to Meet Electricity Demand," Energies, MDPI, vol. 13(16), pages 1-21, August.
    13. Jianhui Bai & Xuemei Zong & Christian Lanconelli & Angelo Lupi & Amelie Driemel & Vito Vitale & Kaili Li & Tao Song, 2022. "Long-Term Variations of Global Solar Radiation and Its Potential Effects at Dome C (Antarctica)," IJERPH, MDPI, vol. 19(5), pages 1-30, March.

    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. 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.
    2. Rohani, Abbas & Taki, Morteza & Abdollahpour, Masoumeh, 2018. "A novel soft computing model (Gaussian process regression with K-fold cross validation) for daily and monthly solar radiation forecasting (Part: I)," Renewable Energy, Elsevier, vol. 115(C), pages 411-422.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Polo, J. & Téllez, F.M. & Tapia, C., 2016. "Comparative analysis of long-term solar resource and CSP production for bankability," Renewable Energy, Elsevier, vol. 90(C), pages 38-45.
    10. Feiyan Chen & Zhigao Zhou & Aiwen Lin & Jiqiang Niu & Wenmin Qin & Zhong Yang, 2019. "Evaluation of Direct Horizontal Irradiance in China Using a Physically-Based Model and Machine Learning Methods," Energies, MDPI, vol. 12(1), pages 1-19, January.
    11. 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).
    12. 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.
    13. 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.
    14. Gueymard, Christian A. & Bright, Jamie M. & Lingfors, David & Habte, Aron & Sengupta, Manajit, 2019. "A posteriori clear-sky identification methods in solar irradiance time series: Review and preliminary validation using sky imagers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 412-427.
    15. Lu, Yunbo & Wang, Lunche & Zhu, Canming & Zou, Ling & Zhang, Ming & Feng, Lan & Cao, Qian, 2023. "Predicting surface solar radiation using a hybrid radiative Transfer–Machine learning model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    16. Keshtegar, Behrooz & Mert, Cihan & Kisi, Ozgur, 2018. "Comparison of four heuristic regression techniques in solar radiation modeling: Kriging method vs RSM, MARS and M5 model tree," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 330-341.
    17. 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).
    18. Rodrigues, Eugénio & Gomes, Álvaro & Gaspar, Adélio Rodrigues & Henggeler Antunes, Carlos, 2018. "Estimation of renewable energy and built environment-related variables using neural networks – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 959-988.
    19. Zou, Ling & Wang, Lunche & Xia, Li & Lin, Aiwen & Hu, Bo & Zhu, Hongji, 2017. "Prediction and comparison of solar radiation using improved empirical models and Adaptive Neuro-Fuzzy Inference Systems," Renewable Energy, Elsevier, vol. 106(C), pages 343-353.
    20. 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.

    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:146:y:2020:i:c:p:1372-1391. 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.