International Journal of Physics
ISSN (Print): 2333-4568 ISSN (Online): 2333-4576 Website: https://www.sciepub.com/journal/ijp Editor-in-chief: B.D. Indu
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International Journal of Physics. 2024, 12(2), 83-88
DOI: 10.12691/ijp-12-2-4
Open AccessArticle

Choice of the Best Regression Model for Estimating the Global Solar Radiation Component in the City of Ouagadougou in Burkina-Faso

Toussaint Tilado Guingane1, 2, , Mouhamadou Falilou Ndiaye3, Sosthène Tassembedo2, Éric Korsaga2, Dominique Bonkoungou1, 2, Zacharie Koalaga2 and François Zougmore2

1Laboratoire des Matériaux et Environnement (LA.M.E.), Unité de Formation et de Recherche en Sciences Exactes et Appliquée

2(UFR/SEA), Université Pr KI-ZERBO, Ouagadougou, Burkina Faso

3Laboratoire de Sciences et Technologies (LaST), Unité de Formation et de Recherche en Sciences et Techniques (UFR/ST), Université Thomas SANKARA, Ouagadougou, Burkina Faso

Pub. Date: April 25, 2024

Cite this paper:
Toussaint Tilado Guingane, Mouhamadou Falilou Ndiaye, Sosthène Tassembedo, Éric Korsaga, Dominique Bonkoungou, Zacharie Koalaga and François Zougmore. Choice of the Best Regression Model for Estimating the Global Solar Radiation Component in the City of Ouagadougou in Burkina-Faso. International Journal of Physics. 2024; 12(2):83-88. doi: 10.12691/ijp-12-2-4

Abstract

The aim of the study was to identify the best-performing regression model for estimating the solar radiation component in Ouagadougou, Burkina Faso, a region characterised by high levels of sunshine. Of the four models evaluated, the Bristow Campbell model emerged as the optimal choice, outperforming the others in terms of accuracy. The importance of this research lies in the need to select a regression model adapted to the specific climatic conditions of the region, thus contributing to more accurate energy planning and sustainable use of solar energy. The evaluation of the models was based on metrics such as RMSE, MBE, t-statistic, R2, and the d metric, reinforced by detailed graphical visualisations and correlations between the models and real data. The results clearly demonstrated the performance of the Bristow Campbell model, underlining its reliability and efficiency in estimating global solar radiation. This conclusion is supported by an in-depth analysis of the metrics and graphs, providing valuable insights for researchers, energy planners and policy makers.

Keywords:
solar radiation regression model metrics performance Bristow Campbell model

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  T.T Guingane, “Contribution a l’etude de l’influence d’un systeme pv connecte sur le reseau electrique”, Doctorat Université Ouaga I Professeur Joseph Ki-Zerbo Burkina Faso, Sciences Appliquées, Spécialité : Sciences Physique-semi-conducteurs, 11/05/2018.
 
[2]  P. GROS, «Utilisation du modèle linéaire. Rappels de base – Méthodes de validation», Laboratoires Côtiers de l’Ifremer, (Novembre 2000).
 
[3]  M.S. Okundamiya et al., “Empirical Model for Estimating Global Solar Radiation on Horizontal Surfaces for Selected Cities in the Six Geopolitical Zones in Nigeria”, Research Journal of Applied Sciences, Engineering and Technology 2(8): 805-812, (2010).
 
[4]  Menges H. O., Ertekin C., Sonmete M. H. “Evaluation of global solar radiation models for Konya, Turkey”, Energy Conversion and Management 47: 3149–3173, 2006. Moussa Diop, “Energy Systems: Vulnerability – Adaptation – Resilience (VAR)”, Regional focus: sub-Saharan Africa, Senegal, (2009).
 
[5]  E. Mboumboue, D. Njomo, M. L. Ndiaye, P. A. N'diaye, M. F. Ndiaye, and A. K. Tossa, “ On the applicability of several conventional regression models for the estimation of solar global radiation component in Cameroon and Senegal sub-Saharan tropical regions ”, Journal of Renewable and Sustainable Energy 8, 025906 (2016).
 
[6]  Daniel K. Fisher, H. C. Pringle III, “ Evaluation of alternative methods for estimating reference evapotranspiration”, Agricultural Sciences, Vol.4, No.8A, 51-60 (2013).
 
[7]  Y.M.Irwan, I.Daut, I.Safwati , M.Irwanto , N.Gomesh , M.Fitra, “ An Estimation of Solar Characteristic in Kelantan using Hargreaves Model”, TerraGreen 13 International Conference 2013 - Advancements in Renewable Energy and Clean Environment, Energy Procedia 36 ( 2013 ) 473 – 478.
 
[8]  F. M. Abed Al-Dulaimy, and G. Y. M. Al-Shahery,” Estimation of Global Solar Radiation on Horizontal Surfaces over Haditha, Samara, and Beji, Iraq.”, The Pacific Journal of Science and Technology, Volume 11. Number 1. May 2010 (Spring).
 
[9]  J. A. Duffie, W .A. Beckman, “Solar Engineering of Thermal Processes”, Fourth Edition, Published by John Wiley & Sons, Inc., Hoboken, New Jersey,2013.
 
[10]  J. Annandale, N.Z.Jovanovic, N.Benade, R.G.Allen, “Software for missing data error analysis of Penman-Monteith reference evapotranspiration”, Springer-Verlag, 2001.
 
[11]  M. H. Soulouknga, R. Z.Falama, O. O. Ajayi, S. Y. Doka, T. C. Kofane, “ Determination of a Suitable Solar Radiation Model for the Sites of Chad”, Energy and Power Engineering, 2017, 9, 703-722, http://www.scirp.org/journal/epe, ISSN Online: 1947-3818.
 
[12]  D. G. Goodin, J. M. S. Hutchinson, R. L. Vanderlip, and M. C. Knapp, “ Estimating Solar Irradiance for Crop Modeling Using Daily Air Temperature Data”, Agronomy Journal, Vol. 91, September–October 1999, 845-851.
 
[13]  R. Rakotomalala,” Analyse de corrélation Étude des dépendances - Variables quantitatives”, Version 1.1, March 2015, Université Lumière Lyon 2.
 
[14]  P. Dagnelie, “Statistique théorique et appliquée Tome 1 ”, De Boeck Supérieur s.a., 2013, 3e édition, Rue des Minimes 39, B-1000 Bruxelles.
 
[15]  C. J. Willmott, “On the validation of models,” Phys. Geogr. 2, 184–194 (1981).
 
[16]  C. J. Willmott et al., “A refined index of model performance,” Int. J. Climatol. 32, 2088–2094 (2011).
 
[17]  C. P. Jacovides and H. Kontoyiannis, “Statistical procedures for the evaluation of evapotranspiration computing models,” Agric. Water Manage. 27, 365–371 (1995).
 
[18]  R. J. Stone, “Improved statistical procedure for the evaluation of solar radiation estimation models,” Sol. Energy 51(4), 289–291 (1993).
 
[19]  I. S. Nouhoun, “Modélisation du rayonnement solaire pour la simulation des performances thermiques des Eco-bâtiments en Afrique Subsaharienne ”, Master en génie électrique et énergétique, spécialité : énergie renouvelables, 23 Septembre 2020, Institut International d’Ingénierie Rue de la Science Burkina Faso.
 
[20]  J. Liu, T. Pan , D. Chen , X. Zhou , Q. Yu , G. N. Flerchinger , D.L. Liu , X. Zou, H. W. Linderholm , J.Du , D.Wu and Y.Shen,” An Improved Ångström-Type Model for Estimating Solar Radiation over the Tibetan Plateau ”, Energies 2017, 10, 892.