Skip to main content
SpringerLink
Log in

Several models to estimate daily global solar irradiation: adjustment and evaluation

  • Review Paper
  • Published:
Arabian Journal of Geosciences Aims and scope Submit manuscript

Abstract

Global solar irradiation (Hg) is a variable of great importance for different applications. Despite the great advance in the latter, Hg measurements are not readily available in many places. So, several models with different input variables have been developed and used to estimate Hg worldwide. Estimating Hg from models that use air temperature offers an interesting alternative in the absence of measurements. Four groups of models were used in this study: empirical models group (M) with ten models, linear regression models group (RM) with six models, artificial neural network (ANN) models, and support vector machine (SVM) models groups with six models for each one. All the methods take into account different air temperature combinations as input variables (Tmax, Tmin, ΔT, and Tmed). These models were applied to Campo Grande, Brazil, with 10 years data (2005–2017) in order to adjust and evaluate the Hg. The models were evaluated based on four statistical indexes: RMBE, RRMSE, MAPE, and WAI. The models were adjusted and validated using statistical techniques. The results show that the air temperature is an important entry point. Estimates with empirical models perform well (RMBE between 2.84 and 8.68%; RRMSE between 17.78 and 22.93%; MAPE between 17.23 and 23.31%; WAI between 0.85 and 0.90), with errors less than or equal to ANN models (RMBE between 13.94 and 22.67%; RRMSE between 25.37 and 34.95%; MAPE between 29.26 and 49.51%; WAI between 0.51 and 0.81) and SVM (RMBE between 5.80 and 10.15%; RRMSE between 18.87 and 30.34%; MAPE between 19.49 and 42.14%; WAI between 0.55 and 0.884). The regression models had errors with variations similar to the empirical and SVM models. The results show the need to adjust the local coefficients and further studies to further consolidate the models.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Data availability

The solar irradiation database is in the public domain and is available at https://www.inmet.ms.gov.br/.

References

  • Abraha MG, Savage MJ (2008) Comparison of estimates of daily solar radiation from air temperature range for application in crop simulations. Agric For Meteorol 148:401–416

    Article  Google Scholar 

  • Aladenola OO, Madramootoo CA (2014) Evaluation of solar radiation estimation methods for reference evapotranspiration estimation in Canada. Theor Appl Climatol 118:377–385

    Article  Google Scholar 

  • Almorox J, Hontoria C, Benito M (2011) Models for obtaining daily global solar radiation with measured air temperature data in Madrid (Spain). Appl Energy 88:1703–1709

    Article  Google Scholar 

  • Almorox J, Bocco M, Willington E (2013) Estimation of daily global solar radiation from measured temperatures at Cañada de Luque, Córdoba, Argentina. Renew Energy 60(382-387):2013

    Google Scholar 

  • Alsamamra H (2019) Estimation of Global solar radiation from temperature extremes: a case study of Hebron City, Palestine. J Energy Nat Resour 8:1–5

    Article  Google Scholar 

  • Al-Shamisi MH, Assi AH, Hejase HAN (2013) Artificial neural networks for predicting global solar radiation in al ain city – UAE. Int J Green Energy 10:443–456

    Article  Google Scholar 

  • Anis MS, Jamil B, Ansari MA, Bellos E (2019) Generalized models for estimation of global solar radiation based on sunshine duration and detailed comparison with the existing: A case study for India. Sustain Energy Technol Assess 31:179–198

    Google Scholar 

  • Annandale JG, Jovanic NZ, Benade N, Allen RG (2002) Software for missing data error analysis of Penman-Monteith reference evapotranspiration. Irrig Sci 21:57–67

    Article  Google Scholar 

  • Antonopoulos VZ, Papamichail DM, Aschonitis VG, Antonopoulos AV (2019) Solar radiation estimation methods using ANN and empirical models. Comput Electron Agric 160:160–167

    Article  Google Scholar 

  • Ayodele TR, Ogunjuyigbe ASO, Monyei OG (2016) On the global solar radiation prediction methods. J Renew Sustain Energy 8:023702

    Article  Google Scholar 

  • Bailek N, Bouchouicha K, Abdel-Hadi YA, El-Shimy M, Slimani A, Jamil B, Djaafari A (2020) Developing a new model for predicting global solar radiation on a horizontal surface located in Southwest Region of Algeria. J Astron Geophys 9:341–349

    Google Scholar 

  • Bakhashwain JM (2016) Prediction of global solar radiation using support vector machines. Int J Green Energy 13:1467–1472

    Article  Google Scholar 

  • Bakirci K, Kirtiloglu Y (2018) Prediction of diffuse solar radiation using satellite data. Int J Green Energy 15:76–79

    Article  Google Scholar 

  • Biazar SM, Rahmani V, Isazadeh M, Kisi O, Dinpashoh Y (2020) New input selection procedure for machine learning methods in estimating daily global solar radiation. Arab J Geosci 13:431

    Article  Google Scholar 

  • Bouchouicha KA, Muhammed H, Nadjem B, Nouar A (2019) Estimating the global solar irradiation and optimizing the error estimates under Algerian desert climate. Renew Energy 139:844–858

    Article  Google Scholar 

  • Bristow KL, Campbell GS (1984) On the relationship between incoming solar radiation and daily maximum and minimum temperature. Agric For Meteorol 31:159–166

    Article  Google Scholar 

  • Cao F, Li H, Zhao L (2017) Comparison of the daily global solar radiation from different data sources in Northwest China climate. Int J Green Energy 14:548–554

  • Chen J-L, Liu H-B, Wu W, Xi D-T (2011) Estimation of monthly solar radiation from measured temperatures using support vector machines - a case study. Renew Energy 36:413–420

    Article  Google Scholar 

  • Chen R, Ersi K, Yang J, Lu S, Zhao W (2004) Validation of five global radiation models with measured daily data in China. Energy Convers Manag 45:1759–1769

    Article  Google Scholar 

  • Chen J-L, He L, Yang H, Ma M, Chen Q, Wu S-J, Xia Z-L (2019) Empirical models for estimating monthly global solar radiation: a most comprehensive review and comparative case study in China. Renew Sust Energ Rev 108:91–111

    Article  Google Scholar 

  • Chukwujindu NS (2017) A comprehensive review of empirical models for estimating global solar radiation in Africa. Renew Sust Energ Rev 78:955–995

    Article  Google Scholar 

  • Despotovic M, Nedica V, Despotovic D, Cvetanovicc S (2015) Review and statistical analysis of different global solar radiation sunshine models. Renew Sust Energ Rev 52:1869–1880

    Article  Google Scholar 

  • Doorga JRS, Rughooputh DDDV, Boojhawon R (2019) Modelling the global solar radiation climate of Mauritius using regression techniques. Renew Energy 131:861–878

    Article  Google Scholar 

  • Duffie JA, Beckman WA (2013) Solar engineering of thermal processes, 4rd. John Wiley& Sons, Inc., New Jersey, NJ

    Book  Google Scholar 

  • Evrendilek F, Ertekin C (2008) Assessing solar radiation models using multiple variables over Turkey. Clim Dyn 31:131–149

    Article  Google Scholar 

  • Fadare DA (2009) Modeling of solar energy potential in Nigeria using an artificial neural network model. Appl Energy 86:1410–1422

    Article  Google Scholar 

  • Fan J, Chen B, Wu L, Zhang F, Lu X, Xiang Y (2018) Evaluation and development of temperature-based empirical models for estimating daily global solar radiation in humid regions. Energy 144:903–914

    Article  Google Scholar 

  • Fan J, Wang X, Zhang F, Ma X, Wu L (2019) Predicting daily diffuse horizontal solar radiation in various climatic regions of China using support vector machine and tree-based soft computing models with local and extrinsic climatic data. J Clean Prod 12:119264

    Google Scholar 

  • Fathizad H, Mobin MH, Gholamnia A, Sodaiezadeh H (2017) Modeling and mapping of solar radiation using geostatistical analysis methods in Iran. Arab J Geosci 10:391

    Article  Google Scholar 

  • Frank E, Hall MA, Witten IH (2016) The WEKA Workbench. Online Appendix for “Data Mining: Practical Machine Learning Tools and Techniques”. Morgan Kaufmann, Fourth Edition

    Google Scholar 

  • Gueymard CA, Ruiz-Arias JA (2015) Validation of direct normal irradiance predictions under arid conditions: a review of radiative models and their turbidity-dependent performance. Renew Sust Energ Rev 45:379–396

    Article  Google Scholar 

  • Hargreaves GH, Samani ZA (1982) Estimating potential evapotranspiration. J Irrig Drain Eng 108:225–230

    Article  Google Scholar 

  • Hargreaves GL, Hargreaves GH, Riley JP (1985) Irrigation water requirement for Senegal River Basin. J Irrig Drain Eng 111:265–275

    Article  Google Scholar 

  • Hassan GE, Youssef ME, Mohamed ZE, Ali MA, Hanafy AA (2016) New temperature-based models for predicting global solar radiation. Appl Energy 179:437–450

    Article  Google Scholar 

  • Hassan MA, Khalil A, Kaseb S, Kassem MA (2017) Independent models for estimation of daily global solar radiation: a review and a case study. Renew Sust Energ Rev 82:1565–1575

    Article  Google Scholar 

  • Haykin S (2009) In: Pearson Education, Inc. (ed) Neural networks and learning machines, 3rd edn, New Jersey

  • Hunt LA, Kucharb L, Swanton CL (1998) Estimation of solar radiation for use in crop modeling. Agric For Meteorol 91:293–300

    Article  Google Scholar 

  • Ihaddadene R, Ihaddadene N, Bemba M, De Souza A (2019) Daily global solar radiation estimation based on air temperature: case of study south of Algeria. International Conference on Renewable Energy and Environment Engineering, E3S Web of Conferences 80, 01002. https://doi.org/10.1051/e3sconf/20198001002

  • Jamil B, Akhtar N (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. Renew Sust Energ Rev 78:329–355

    Article  Google Scholar 

  • Kashyap Y, Bansal A, Sao AK (2015) Solar radiation forecasting with multiple parameters neural networks. Renew Sust Energ Rev 49:825–835

    Article  Google Scholar 

  • Khatib T, Mohamed A, Sopian K, Mahmoud M (2012) Solar energy prediction for malaysia using artificial neural networks. Int J Photoenergy 1–16. https://doi.org/10.1155/2012/419504

  • Li M, Liu H, Guo P, Wu W (2010) Estimation of daily solar radiation from routinely observed meteorological data in Chongqing, China. Energy Convers Manag 51:2575–2579

    Article  Google Scholar 

  • Liu X, Mei X, Li Y, Wang Q, Jensen RJ, Zhang Y, Porter JR (2009) Evaluation of temperature-based global solar radiation models in China. Agric For Meteorol 149:1433–1446

    Article  Google Scholar 

  • Loghmari I, Timoumi Y, Messadi A (2018) Performance comparison of two global solar radiation models for Spatial interpolation purposes. Renew Sust Energ Rev 82:837–844

    Article  Google Scholar 

  • Maluta ENS, Mulaudzi T, Sankaran V (2014) Estimation of the global solar radiation on the horizontal surface from temperature data for the Vhembe District in the Limpopo Province of South Africa. Int J Green Energy 11:454–464

    Article  Google Scholar 

  • Meenal R, Selvakumar AI (2018) Assessment of SVM, empirical and ANN based solar radiation prediction models with most influencing input parameters. Renew Energy 121:324–343

    Article  Google Scholar 

  • Meza F, Varas E (2000) Estimation of mean monthly solar global radiation as a function of temperature. Agric For Meteorol 100:231–241

    Article  Google Scholar 

  • Mohammadi B, Aghashariatmadari Z (2020) Estimation of solar radiation using neighboring stations through hybrid support vector regression boosted by Krill Herd algorithm. Arab J Geosci 13:363

    Article  Google Scholar 

  • Mohammadi K, Shamshirband S, Tong CW, Arif M, Petkovic D, Che S (2015) A new hybrid support vector machine–wavelet transform approach for estimation of horizontal global solar radiation. Energy Convers Manag 92:162–171

    Article  Google Scholar 

  • Naderi M, Sabzpooshani M (2019) On the importance of relative humidity for prediction of diffuse solar radiation in warm and humid climate of Iran. Int J Green Energy:1230–1241. https://doi.org/10.1080/15435075.2019.1671398

  • Nazari-Sharabian M, Karakouzian M (2020) Relationship between sunspot numbers and mean annual precipitation: application of cross-wavelet transform—a case study. J Multidiscip Sci J 3:67–78

    Google Scholar 

  • Nourani V, Elkiran G, Abdullahi J, Tahsin A (2019) Multi-region modeling of daily global solar radiation with artificial intelligence ensemble. Nat Resour Res 28:1217–1238

    Article  Google Scholar 

  • Nwokolo SC, Ogbulezie JC (2018) A quantitative review and classification of empirical models for predicting global solar radiation in West Africa. Beni-Suef Univ J Basic Appl Sci 7:367–396

    Google Scholar 

  • Piri J, Shamshirband S, Petkovic D, Tong CW, Rehman MH (2015) Prediction of the solar radiation on the Earth using support vector regression technique. Infrared Phys Technol 68:179–185

    Article  Google Scholar 

  • Quej VH, Almorox J, Ibrakhimov L, Saito L (2016) Empirical models for estimating daily global solar radiation in Yucatán Peninsula, Mexico. Energy Convers Manag 110:448–456

    Article  Google Scholar 

  • Raghavendra S, Deka PC (2014) Support vector machine applications in the field of hydrology: a review. Appl Soft Comput 19:372–386

    Article  Google Scholar 

  • Ramli MA-M, Twaha S, Al-Turki YA (2015) Investigating the performance of support vector machine and artificial neural networks in predicting solar radiation on a tilted sufarce: Saudi Arabia case Study. Energy Convers Manag 105:442–452

    Article  Google Scholar 

  • Rehman S, Mohandes M (2008) Artificial neural network estimation of global solar radiation using air temperature and relative humidity. Energy Policy 36:571–576

    Article  Google Scholar 

  • Santos CM, Souza JL, Ferreira Junior RA et al (2014) On modeling global solar irradiation using air temperature for Alagoas State, Northeastern Brazil. Energy 71:388–398

    Article  Google Scholar 

  • Santos CM, Escobedo JF, Teramoto ET, Silva SHMG (2016) Assessment of ANN and SVM models for estimating normal direct irradiation (Hb). Energy Convers Manag 126:826–836

    Article  Google Scholar 

  • Siva Krishna Rao K, D. V, Premalatha M, Naveen C (2018) Models for forecasting monthly mean daily global solar radiation from in-situ measurements: application in Tropical Climate, India. Urban Clim 24:921–939

    Article  Google Scholar 

  • Smola AJ, Schölkopf B (2004) A tutorial on support vector regression. Stat Comput 14:199–222

    Article  Google Scholar 

  • Solmaz O, Ozgoren M (2012) Prediction of hourly solar radiation in six provinces in turkey by artificial neural networks. J Energy Eng 138:194–204

    Article  Google Scholar 

  • Tabari H, Ozgur K, Ezani A, Talaee PH (2012) SVM, ANFIS, regression and climate based models for reference evapotranspiration modeling using limited climatic data in a semi-arid highland environment. J Hydrol 444–445:78–89

    Article  Google Scholar 

  • Uckan I, Khudhur KM (2018) Estimation and comparison of various global solar radiation models on horizontal surface in a hot and dry region. Int J Green Energy 15:358–370

    Article  Google Scholar 

  • Vapnik NV (2000) The nature of statistical learning theory, 2nd edn. Springer-Verlag New York, pp 324. https://doi.org/10.1007/978-1-4757-3264-1

  • Weiss A, Hays CJ, Hu Q, Easterling WE (2001) Incorporating bias error in calculating solar irradiance: implications for crop yield simulations. Agron J 93:1321–1326

    Article  Google Scholar 

  • Willmott CJ, Robeson SM, Matsuura K (2012) A refined index of model performance. Int J Climatol 32:2088–2094

    Article  Google Scholar 

  • Yacef R, Mellit A, Belaid S, Şen Z (2014) New combined models for estimating daily global solar radiation from measured air temperature in semi-arid climates: application in Ghardaïa, Algeria. Energy Convers Manag 79:606–615

    Article  Google Scholar 

  • Yadav AK, Malik H, Chandel SS (2014) Selection of most relevant input parameters using WEKA for artificial neural network based solar radiation prediction models. Renew Sust Energ Rev 31:509–519

    Article  Google Scholar 

  • Yao W, Zhang X, Hao H, Wang X, Li X (2018) A support vector machine approach to estimate global solar radiation with the influence of fog and haze. Renew Energy 128:155–162

    Article  Google Scholar 

  • Yıldırım HB, Çelik O, Teke A, Barutçu B (2018) Estimating daily global solar radiation with graphical user interface in Eastern Mediterranean region of Turkey. Renew Sust Energ Rev 82:1528–1537

    Article  Google Scholar 

  • Zhang J, Zhao L, Deng S, Xu W, Zhang Y (2017) A critical review of the models used to estimate solar radiation. Renew Sust Energ Rev 70:314–329

    Article  Google Scholar 

  • Zhang WG, Zhang XL, Xiao WL (2009) Portfolio selection under possibilístico mean-variance utility and a SMO algorithm. Eur J Oper Res 197:693–700

Download references

Acknowledgements

The authors would like to thank their Universities for their support.

Author information

Authors and Affiliations

  1. Faculty of Agronomic Engineering – UFPA, Federal University of Para, Rua Coronel José Porfírio, n° 2515. Bairro: São Sebastião. CEP, Altamira, PA, 68372-040, Brazil

    Cícero Manoel dos Santos

  2. Campus Experimental de Registro, São Paulo State University, Registro, SP, Brazil

    Érico Tadao Teramoto

  3. Federal University of Mato Grosso do Sul, C.P. 549, 79070- 900, Campo Grande, MS, Brazil

    Amaury de Souza & Flavio Aristone

  4. Department of Mechanical Engineering, University of M’Sila, 28000, M’Sila, Algeria

    Razika Ihaddadene

Authors
  1. Cícero Manoel dos Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Érico Tadao Teramoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Amaury de Souza
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Flavio Aristone
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Razika Ihaddadene
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cícero Manoel dos Santos.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Responsible Editor: Zhihua Zhang

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

dos Santos, C.M., Teramoto, É.T., de Souza, A. et al. Several models to estimate daily global solar irradiation: adjustment and evaluation. Arab J Geosci 14, 286 (2021). https://doi.org/10.1007/s12517-021-06603-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12517-021-06603-8

Keywords

Search

Navigation