ESECI: A Tool for Estimating Solar Radiation in Côte d’Ivoire

Maurice Aka Djoman^1, , Wanignon Ferdinand Fassinou¹, Stéphane Aka Koffi² and Augustin Memeledje¹

¹Laboratoire des Sciences de la Matière, de l’Environnement et de l’Energie Solaire (LASMES), UFR SSMT, Université Félix Houphouët-Boigny, Abidjan, Côte d’Ivoire

²Laboratoire de Technologie (LabTech) UFR SSMT, Université Félix Houphouët-Boigny, Abidjan, Côte d’Ivoire

Cite this paper:
Maurice Aka Djoman, Wanignon Ferdinand Fassinou, Stéphane Aka Koffi and Augustin Memeledje. ESECI: A Tool for Estimating Solar Radiation in Côte d’Ivoire. International Journal of Physics. 2022; 10(1):79-87. doi: 10.12691/ijp-10-1-7

Abstract

In this work, we present a tool dedicated to the estimation of solar radiation in Côte d'Ivoire named ESECI. In fact, the unavailability of sufficient quality and quantity of solar data is a limiting factor in any project involving solar energy systems (thermal conversion and photovoltaic conversion). Côte d’Ivoire does not possess a solar irradiance measurement network. Only fourteen (14) weather stations exist to measure sunshine hours from which solar radiation is derived. Moreover, these measures are sometimes incomplete due to lack of monitoring. We have implemented a computer program to calculate solar radiation for any sky. The estimation of solar irradiance takes into account its different components (direct, diffuse and global) on any surface. A comparative analysis between the simulation results and the measurements shows that the model correctly predicts solar irradiance in clear sky and in uniformly overcast sky. For days with frequent cloudy periods, the tool simply calculates the average values of the solar irradiance during the fluctuation times. The results obtained indicate that the tool implemented is an alternative to the lack of data on the solar deposit in Côte d’Ivoire.

Keywords:
solar energy systems sunshine hours solar irradiation solar deposit

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References:

[1]	Z. Qu, La nouvelle méthode Heliostat-4 pour l’évaluation du rayonnement solaire au sol. Thèse de Doctorat Paris Tech, 2013, p. 195.
[2]	A. Tom, Contribution au séchage solaire des produits carnés : modélisation et réalisation d’un séchoir adapté au pays tropicaux. Thèse de Doctorat Paris Tech, Ecole Nationale Supérieure d’Arts et Métiers, 2015
[3]	Thomas Huld, PVMAPS: Software tools and data for the estimation of solar radiation and photovoltaic module performance over large geographical areas. Solar Energy 142 (2017) 171-181.
[4]	An, Jingjing & Yan, Da & Guo, Siyue& Gao, Yan & Peng, Jinqing& Hong, Tianzhen. (2020). An improved method for direct incident solar radiation calculation from hourly solar insolation data in building energy simulation. Energy and Buildings. 227. 110425.
[5]	T. Hove, E. Manyumbu, G. Rukweza,Developing an improved global solar radiation map for Zimbabwe through correlating long-term ground- and satellite-based monthly clearness index values,Renewable Energy,Volume 63,2014,Pages 687-697,ISSN 0960-1481.
[6]	J. Tovar-Pescador, D. Pozo-Vazquez, J. A. Ruiz-Arias, J. Batlles, G. Lopez & J. L. Bosch. On the use of the digital elevation model toestimate the solar radiation in areas of complextopography. Meteorol. Appl. 13, 279-287 (2006).
[7]	Cédric Bertrand, Gilles Vanderveken, Michel Journée. Evaluation of decomposition models of various complexity to estimate the direct solar irradiance over Belgium. Renewable Energy 74 (2015) 618-626.
[8]	Z. ER, A Study of Evaluation of Solar Energy Simulation and Modeling Systems. Acta Physica Polonia Vol. 130 (2016). Special issue of the 2nd International Conference on Computational and Experimental Science and Engineering (ICCESEN).
[9]	Bed Raj KC, Shekhar Gurung, Estimation of Daily Global Radiation using RadEst 3.00 Sftware at Nepalgunj, Nepal. Journal of the Institute of Engineering, 2016, 12(1) 199-209.
[10]	H. Ambarita, Development of software for estimating clear sky solar radiation in Indonesia. Conf. Series: Journal of Physics: Conf. Series 801 (2017) 012093.
[11]	Y. Kherbiche, N. Ihaddadene, R. Ihaddadene and M. Mostefaoui. Programming interface in Matlab to estimate solar radiation in Algeria: Application to M’sila. Interntional Journal of Scientific Research & Engineering Technology (IJSET) Vol._ pp. 32-37.
[12]	Siaka Touré, Dobet D. N’Dri, Hassan Salami, Modibo Sidibé&Diakaridja Traoré, Experimental study of an optimized solar still type with to condensing compartments suitable for alcoholic distillation. African Journal of Science, Technology, Innovation and Development, 7:6, 495-499.
[13]	A. Dajuma, S. Yahaya, S. Touré, A. Diedhiou, R. Adamou, A. Konaré, M. Sido, M. Golba, Sensitivity of Solar Photovoltaic Panel Efficiencyto Weather and Dust over West Africa: Comparative Experimental Study between Niamey (Niger) and Abidjan (Côte d’Ivoire). Computational Water, Energy, and Environmental Engineering, 2016, 5, 123-147.
[14]	Wanignon Ferdinand Fassinou, Higher heating value (HHV) of vegetable oils, fats and biodiesels evaluation based on their pure fatty acids’ HHV. Energy 45 (2012) 798-805.
[15]	Plan d’Actions National des Energies Renouvelables (PANER) de la Côte d’Ivoire, Période [2016-2020/2030]. Ministère du Pétrole et de l’Energie, 2016.
[16]	M. Capderou, Atlas solaire de l’Algérie. Tome 1, Vol.1 et 2. Modèles théorique et expérimentaux, Office des publications universitaires, Algérie, 1987.
[17]	Angstrom, A., 1924. Solar terrestrial radiation. Q.J.R. Meterol. Soc., 50: 121-125.
[18]	Prescott, J.A., 1940. Evaporation from a water surface in relation to solar radiation. Trans. R. Sco. Aust., 64: 9114-125.
[19]	Djoman, M. A., Ferdinand Fassinou, W., &Memeledje, A. (2021). Calibration of Ångström-Prescott Coefficients to Estimate Global Solar Radiation in Côte d’Ivoire. European Scientific Journal, ESJ, 17(37), 24.
[20]	Maurice Aka Djoman, Ferdinand WanignonFassinou, Augustin Memelèdje. General Formulation of Ångström-Prescott Coefficients: A New Approach for Côte d’Ivoire. International Journal of Physics. 2021; 9(5):245-250.
[21]	M. Collares-Pereira and A. Rabl. The average distribution of solar radiation – Correlation between diffuse and hemispherical and between daily and hourly insolation values. Solar Energy Vol. 22, pp. 155-164, 1974.
[22]	D.G. Erbs, S.A. Klein and J.A. Duffie, Estimation of the diffuse radiation fraction for hourly, daily, and monthly-average global radiation. Solar Energy 28(4), 293-302 (1982).
[23]	J.E. Hay, Calculation of monthly mean solar radiation for horizontal and inclined surfaces. Solar Energy, Vol. 23, pp. 301-307, 1979.
[24]	J.E. Hay and J.A. Davies, Calculation of the solar radiation incident on inclined surfaces. In proceedings of the first Canadian Solar Radiation Data Workshop, Ministry of Supply and Services, Toronto, Canada p.59 (1980).
[25]	D. T. Reindl, W. A. Beckman and J. A. Duffie, Diffuse fraction correlations. Solar Energy, 45, 1 (1990 a).
[26]	T. M. Klucher, Evaluation of models to predict insolation on tilted surfaces. Solar Energy 23 (2), 111-114 (1979).
[27]	Liu, B. Y. H. and R. C. Jordan. The long-term average performance of flat-plate solar energy collectors. Solar Energy, 7, 53 (1963).
[28]	B. Y. H. Liu and R. C. Jordan, The interrelationship and characteristic distribution of direct, diffuse and total solar radiation. Sol. Energy 4(3), 1-19 (1960).