skip to main content

A Comparative Study of Regression Models and Meteorological Parameters to Estimate the Global Solar Radiation on a Horizontal Surface for Baghdad City, Iraq

1Energy and Renewable Energies Technology Center, University of Technology, Baghdad, Iraq

2Ministry of Higher Education and Scientific Research, Baghdad, Iraq

3Mechanical Eng. Dept., University of Technology, Baghdad, Iraq

Received: 21 May 2021; Revised: 6 Aug 2021; Accepted: 1 Sep 2021; Available online: 20 Sep 2021; Published: 1 Feb 2022.
Editor(s): H. Hadiyanto
Open Access Copyright (c) 2022 The Authors. Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Abstract

In this study, data of the monthly average of daily global solar radiation falling on a horizontal surface, relative humidity, maximum temperature, and duration of sunshine for the city of Baghdad were collected through two sources. First, from the Iraqi Meteorological Authority (IMA) for a period extending from 1961 to 2016. The second is from NASA, for the period from 1984 to 2004. Then, four linear regression models, two single and two polynomials were formulated to calculate the values of the monthly average of daily global horizontal solar radiation (GHSR) incidents. The models calculated the monthly average of daily extraterrestrial radiation and day length, using some data provided by NASA and the IMA. To ensure the validity of the used models, a statistical test was performed for the performance of the proposed models, using the indicators mean bias Error (MBE), root mean square error (RMSE) as well as mean percentage error (MPE). The validation shows the relationship between the measured and computed values (through the analysis of the results), where a great convergence was found between the measured and calculated values. This means that the proposed models can be adapted to predict global solar radiation. The highest values of measured solar radiation were during the month of June, which were 28.555 and 27.280 MJ/m2/day from the IMA and NASA, respectively. The same applies to the radiation calculated using the four empirical models. The month of June was the highest in terms of solar radiation values. The radiation values were 28.947, 26.315, 29.699, and 26.716 MJ/m2/day for the first, second, third, and fourth models, respectively. The lowest values of measured and calculated radiation were during the month of December. Always, radiation measured by the IMA was greater than those of NASA, as well as the values of radiation calculated in the two IMA-based models were greater than the other two NSA-based models. In the absence of a method for measuring the diffuse and direct (beam) solar radiations, as well as the lack of such values by meteorological authorities, and its paramount importance, they were reported to mathematically calculate them in this study. The values of statistical indicators RMSE; MJ/m2/day, MBE; MJ/m2/day and MPE% were (0.4769, 0.0164, 0.2207), (0.8641, 0.1773, -0.9680), (0.6420, 0.3996, -1.1487), (0.9604, 0.218, -1.0225) for the first, second, third and fourth models, respectively. According to the results of the statistical test, it can be indicated that the single linear regression model, based on the IMA’s data (model No.1), is the most accurate to calculate global solar radiation for Baghdad City.

Fulltext View|Download
Keywords: Global solar radiation, Iraqi meteorological authority; linear regression model; meteorological Data; NASA; sunshine duration;

Article Metrics:

  1. Abdelhafidi, N., Bachari, N.E.I. & Abdelhafidi, Z. (2021). Estimation of solar radiation using stepwise multiple linear regression with principal component analysis in Algeria. Meteorol Atmos Phys, 133, 205–216; doi: 10.1007/s00703-020-00739-0
  2. Ali Etem Gürel, Ümit Agbulut & Yunus Biçen (2020). Assessment of machine learning, time series, response surface methodology and empirical models in prediction of global solar radiation. Journal of Cleaner Production, 277, 122353; doi: 10.1016/j.jclepro.2020.122353
  3. Angstrom, A. (1924). Solar and terrestrial radiation. Report to the international commission for solar research on actinometric investigations of solar and atmospheric radiation. Q. J. Roy. Meteorol. Soc. 50 (210),121–126; doi: 10.1002/qj.49705021008
  4. Bailek, N., Bouchouicha, K., Abdel-Hadi, Y.A., 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. NRIAG Journal of Astronomy and Geophysics, 9(1), 341-349; doi: 10.1080/20909977.2020.1746892
  5. Bakirci, K. (2009). Correlations for estimation of daily global solar radiation with hours of bright sunshine in Turkey. Energy, 34(4), 485–501; doi: 10.1016/j.energy.2009.02.005
  6. Bamehr, S. & Sabetghadam, S. (2021). Estimation of global solar radiation data based on satellite-derived atmospheric parameters over the urban area of Mashhad, Iran. Environmental Science and Pollution Research, 28(6), 7167-7179; doi: 10.1007/s11356-020-11003-8
  7. Benghanem, M. & Joraid, A. (2007). A multiple correlation between different solar parameters in Medina, Saudi Arabia. Renew Energy, 32(14), 2424–2435; doi: 10.1016/j.renene.2006.12.017
  8. Besharat F, Dehghan AA, Faghih AR. ( 2013). Empirical models for estimating global solar radiation: a review and case study. Renew Sustainable Energy Rev, 21,798–821; doi: 10.1016/j.rser.2012.12.043
  9. Blal, M., Khelifi, S., Dabou, R., Sahouane, N., Slimani, A., Rouabhia, A., Ziane, A., Necaibia, A., Bouraiou, A. and Tidjar, B. (2020). A prediction models for estimating global solar radiation and evaluation meteorological effect on solar radiation potential under several weather conditions at the surface of Adrar environment. Measurement, 152, 107348; doi: 10.1016/j.measurement.2019.107348
  10. Chaichan, M.T., Kazem, H.A. and Abed, T.A. (2018). Traffic and outdoor air pollution levels near highways in Baghdad, Iraq. Environment Development and Sustainability, 20(2), 589-603; doi: 10.1007/s10668-016-9900-x
  11. Chaichan, M.T., Kazem, H. A. (2018) Generating Electricity Using Photovoltaic Solar Plants in Iraq, Springer, ISBN: 978-3-319-75030-9; doi: 10.1007/978-3-319-75031-6
  12. Duffie, J.A., Beckman, W.A. (1991) Solar engineering of thermal process. 2nd edn. John Wiley & Sons, New York, NY, USA
  13. El-Sebaii, A. A. and Trabea, A. A. (2005). Estimation of Global Solar Radiation on Horizontal Surfaces Over Egypt, Egypt. J. Solids, 28(1), 163-175
  14. Ertekin, C., Yaldiz, O. (2000). Comparison of some existing models for estimating global solar radiation for Antalya (Turkey). Energy Conversion and Management, 41(4), 311–330; doi: 10.1016/S0196-8904(99)00127-2
  15. Garba Musa Argungu, Yusuf Abubakar Sanusi, Kabir Ahmed Dabai, Muazu Abubakar, Abubakar Roko.( 2020). Comparative Analysis of the Performance of Six Models for the Estimation of Global Solar Radiation for Katsina, Nigeria. American Journal of Energy Engineering. 8(2), 18-25; doi: 10.11648/j.ajee.20200802.11
  16. Gopinathan, K.K.( 1988). A new model for estimating total solar radiation in Doha. Energy Conversion and Managemen, 28, 63–72
  17. Iqbal, M. ( 1983) An Introduction to Solar Radiation, Academic Press, Toronto, Canada
  18. Kacem Gairaa , Yahia Bakelli. (2013). A Comparative Study of Some Regression Models to Estimate the Global Solar Radiation on a Horizontal Surface from Sunshine Duration and Meteorological Parameters for Gharda / a Site, Algeria. Hindawi Publishing Corporation ISRN Renewable Energy; doi: 10.1155/2013/754956
  19. Kazem, H.A., Yousif, J.H., Chaichan, M.T.(2016). Modeling of Daily Solar Energy System Prediction using Support Vector Machine for Oman. International Journal of Applied Engineering Research, 11(20), 10166-10172
  20. Koussa, M., Malek, A., Haddadi, M. (2009). Statistical comparison of monthly mean hourly and daily diffuse and global solar irradiation models and a Simulink program development for various Algerian climates. Energy Conversion and Management,50(5),1227–1235; doi: 10.1016/j.enconman.2009.01.035
  21. Liu, D.L. (1996). Incorporating Diurnal Light Variation and Canopy Light Attenuation into Analytical Equations for Calculating Daily Gross Photosynthesis. Ecological Modeling, 93(1-3), 175–189; doi: 10.1016/0304-3800(95)00223-5
  22. Liu, P., Tong, X., Zhang, J., Meng, P., Li, J. and Zhang, J. (2020). Estimation of half-hourly diffuse solar radiation over a mixed plantation in north China. Renewable Energy, 149(2), 1360-1369; doi: 10.1016/j.renene.2019.10.136
  23. Moafaq, K.S.Al-Ghezi. (2019). Study the Maximum Solar Radiation by Determining the Best Direction of the Solar Collectors. International Research Journal of Advanced Engineering and Science, 4(3), 42-44
  24. Moafaq, K.S.Al-Ghezi. (2017). Calculate the Reflected Hourly Solar Radiation by Mirror Surfaces of Solar Concentrators Parabolic Trough. International Journal of Computation and Applied Sciences IJOCAAS, 3(3), 256-260
  25. Moafaq, K.S.Al-Ghezi. (2017). The Global and Scattered Radiation Evaluation for a Horizontal Surface in Baghdad City. International Journal Of Computation and Applied Sciences IJOCAAS, 3(1), 153-158
  26. Moafaq, K.S.Al-Ghezi., Khaleel, I.Abass., Ahmed, Q. Salam.,Raid, S. Jawad & Hussein, A. Kazem. (2021). The possibilities of using nano-CuO as coolants for PVT system: An experimental study. Journal of Physics: Conference Series, 1973(1), 012123; doi: 10.1088/1742-6596/1973/1/012123
  27. Mohamed Salah Mecibah, Taqiy Eddine Boukelia, Reda Tahtah, Kacem Gairaa. 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, 36, 194–202; doi: 10.1016/j.rser.2014.04.054
  28. Mujabar, S. & Venkateswara, R.C. (2021). Empirical models for estimating the global solar radiation of Jubail Industrial City, the Kingdom of Saudi Arabia. SN Applied Sciences, 3(1), 1-11; doi: 10.1007/s42452-020-04043-9
  29. NASA. https://eosweb.larc.nasa.gov/cgi-bin/sse/daily.cgi
  30. Page, J.K.(1961). The estimation of monthly mean values of daily total short wave radiation on vertical and inclined surface from sunshine records for latitudes 40oN-40oS. UN Conference on New Sources of Energy, 4, 378-390
  31. Rabaia, M.K.H., Abdelkareem, M.A., Sayed, E.T., Elsaid, K., Chae, K.J., Wilberforce, T. & Olabi, A.G. (2021). Environmental impacts of solar energy systems: A review. Science of The Total Environment, 754, p.141989; doi: 10.1016/j.scitotenv.2020.141989
  32. Sabbagh, J., Sayigh, A.A.M, El-Salam, E.M.A. (1977). Estimation of the total solar radiation from meteorological data. Sol Energy, 19(3), 307–311; doi: 10.1016/0038-092X(77)90075-5
  33. Sen, Z. (2007). Simple nonlinear solar irradiation estimation model. Renew Energy, 32(2), 342–350; doi: 10.1016/j.renene.2006.02.015
  34. Sridharan, M. (2021). Generalized Regression Neural Network Model Based Estimation of Global Solar Energy Using Meteorological Parameters. Annals of Data Science, 1-19; doi: 10.1007/s40745-020-00319-4
  35. Trenberth, K.E., Fasullo, J.T. & Kiehl, J. (2009). Earth's global energy budget. Bulletin of the American Meteorological Society, 90(3), 311–324; doi: 10.1175/2008BAMS2634.1
  36. Yousif, J.H., Al-Balushi, H.A., Kazem, H.A. & Chaichan, M,T. (2019). Analysis and forecasting of weather conditions in Oman for renewable energy applications. Case Studies in Thermal Engineering, 13, 100355; doi: 10.1016/j.csite.2018.11.006
  37. Yu, L., Zhang, M., Wang, L., Lu, Y. & Li, J. ( 2021). Effects of aerosols and water vapor on spatial-temporal variations of the clear-sky surface solar radiation in China. Atmospheric Research, 248, 105162; doi: 10.1016/j.atmosres.2020.105162

Last update:

  1. The Influence of Temperature and Irradiance on Performance of the photovoltaic panel in the Middle of Iraq

    Moafaq Kaseim Al-Ghezi, Roshen Tariq Ahmed, Miqdam Tariq Chaichan. International Journal of Renewable Energy Development, 11 (2), 2022. doi: 10.14710/ijred.2022.43713
  2. Daily Solar Radiation Forecasting based on a Hybrid NARX-GRU Network in Dumaguete, Philippines

    Al Diego Pega Fuselero, Hannah Mae San Agustin Portus, Bonifacio Tobias Doma Jr. International Journal of Renewable Energy Development, 11 (3), 2022. doi: 10.14710/ijred.2022.44755
  3. Advanced techniques for enhancing solar distiller productivity: a review

    Miqdam T. Chaichan, Hussein A. Kazem, Ali H. A. Al-Waeli, Wissam H. Elawee, Mohammed A. Fayad, Kamaruzzaman Sopian. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 46 (1), 2024. doi: 10.1080/15567036.2023.2289559
  4. Emissions Characteristics and Engine Performance from the Interaction Effect of EGR and Diesel-Ethanol Blends in Diesel Engine

    Mohammed Ali Fayad, Moafaq Kaseim Al-Ghezi, Sanaa A Hafad, Slafa I Ibrahim, Marwa K Abood, Hind A Al-Salihi, Louay A Mahdi, Miqdam Tariq Chaichan, Hayder Abed Dhahad. International Journal of Renewable Energy Development, 11 (4), 2022. doi: 10.14710/ijred.2022.45051
  5. Daily global solar radiation time series prediction using variational mode decomposition combined with multi-functional recurrent fuzzy neural network and quantile regression forests algorithm

    Mohammed Abdallah, Babak Mohammadi, Hamid Nasiri, Okan Mert Katipoğlu, Modawy Adam Ali Abdalla, Mohammad Mehdi Ebadzadeh. Energy Reports, 10 , 2023. doi: 10.1016/j.egyr.2023.10.070
  6. Status of Solar-Energy Adoption in GCC, Yemen, Iraq, and Jordan: Challenges and Carbon-Footprint Analysis

    Ashraf Farahat, Abdulhaleem H. Labban, Abdul-Wahab S. Mashat, Hosny M. Hasanean, Harry D. Kambezidis. Clean Technologies, 6 (2), 2024. doi: 10.3390/cleantechnol6020036
  7. Modified Nano-Fe2O3-Paraffin Wax for Efficient Photovoltaic/Thermal System in Severe Weather Conditions

    Miqdam T. Chaichan, Maytham T. Mahdi, Hussein A. Kazem, Ali H. A. Al-Waeli, Mohammed A. Fayad, Ahmed A. Al-Amiery, Wan Nor Roslam Wan Isahak, Abdul Amir H. Kadhum, Mohd S. Takriff. Sustainability, 14 (19), 2022. doi: 10.3390/su141912015
  8. Modeling of Temperature and Irradiance Effect on Solar Cells Parameters By MATLAB/Simulink and Verification Using Experimental Data

    Mohammad Tamjid Hossain Partho, Mohammad Shafiul Alam, Muhammed Mahbubur Rashid. 2023 9th International Conference on Computer and Communication Engineering (ICCCE), 2023. doi: 10.1109/ICCCE58854.2023.10246110
  9. Performance enhancement of solar distillation system works in harsh weather conditions: An experimental study

    Miqdam Tariq Chaichan, Hussein A. Kazem, Ali H.A. Al-Waeli, Suha A. Mohammed, Zakaria M. Omara, K. Sopian. Thermal Science and Engineering Progress, 43 , 2023. doi: 10.1016/j.tsep.2023.101981
  10. Estimation of global solar radiation using sunshine-based models in Ethiopia

    Natei Ermias Benti, Abreham Berta Aneseyee, Ashenafi Abebe Asfaw, Chernet Amente Geffe, Girum Ayalneh Tiruye, Yedilfana Setarge Mekonnen. Cogent Engineering, 9 (1), 2022. doi: 10.1080/23311916.2022.2114200
  11. Influence of Renewable Fuels and Nanoparticles Additives on Engine Performance and Soot Nanoparticles Characteristics

    Mohammed A. Fayad, Azher M Abed, Salman H Omran, Alaa Abdulhady Jaber, Amerah A Radhi, Hayder A Dhahad, Miqdam T Chaichan, Talal Yusaf. International Journal of Renewable Energy Development, 11 (4), 2022. doi: 10.14710/ijred.2022.45294
  12. Nano-Iron Oxide-Ethylene Glycol-Water Nanofluid Based Photovoltaic Thermal (PV/T) System with Spiral Flow Absorber: An Energy and Exergy Analysis

    Amged Al Ezzi, Miqdam T. Chaichan, Hasan S. Majdi, Ali H. A. Al-Waeli, Hussein A. Kazem, Kamaruzzaman Sopian, Mohammed A. Fayad, Hayder A. Dhahad, Talal Yusaf. Energies, 15 (11), 2022. doi: 10.3390/en15113870

Last update: 2024-11-23 01:38:36

No citation recorded.