The comparative study of the solar powers between two main cities of Chad is performed in the present work, the city of Mongo in the Centre and that of Pala in the South, with an aim of knowing which one of the two cities is more adequate for an installation of the solar power station, taking into account the regional climatic and environmental conditions of both cities. To do this, the graphical statistical analysis of long-term solar irradiance data and temperature is performed. The data used is that of the decade (2010-2020), based on solar radiation data handed by the National Aeronautics and Space Administration (NASA) and Photovoltaic Geographical Information System (PGIS) for Mongo in the centre and Pala in the south of Chad. The shape of the mean monthly irradiation has been plotted and has been approximated using the sinusoidal function through the mean square analysis. The temperature data has been also obtained by the same process and plotted versus irradiance in order to find the adequate mathematical relationship between them. For the statistical analysis, the maximum entropy principle has been used. As results, it is found that the maximum irradiance is obtained in March, which are 226.26kWh/m2 for Pala and 219.355kWh/m2 for Mongo, while the minimum irradiances are obtained in August, which are 151.67kWh/m2 for Pala and 158.9kWh/m2 for Mongo. The temperature data is also obtained and the mean monthly data plotted, showing that apart for the months of March and April, the the shapes of irradiation and temperatures are similar for both sites. Then it is found that the frequency and probability density distributions reach their maximum at the same dates.
| Published in | Journal of Energy, Environmental & Chemical Engineering (Volume 9, Issue 1) |
| DOI | 10.11648/j.jeece.20240901.14 |
| Page(s) | 33-45 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Irradiation Solar Data, Temperature Data, Maximum Entropy Principle, Mean Square Analysis, Statistical Analysis
| [1] | Abakar Mahamat Tahir, Mahamat Adoum Abdraman, Ruben Mouangue, Alexis Kuitche, Estimate of the Wind Resource of Two Cities in the Sahara and Sahel in Chad, International Journal of Energy and Power Engineering 2020; 9(6): 86-94. https://doi.org/10.11648/j.ijepe.20200906.11 |
| [2] | Abdelhamid Issa Hassane, Abdel-Hamid Mahamat Ali, Abakar Mahamat Tahir, Jean-Marie Hauglustaine, International journal of renewable energy research Vol. 9, No. 3, September, 2019. https://doi.org/10.20508/ijrer.v9i3 |
| [3] | Dr Fatih Birol, Executive Director, International Energy Agency, Africa Energy Outlook 2022. |
| [4] | Gour Chand Mazumder, Abu Shahadat Md. Ibrahim, Md. Habibur Rahman, Saiful Huque, Solar PV and Wind Powered Green Hydrogen Production Cost for Selected Locations, International journal of renewable energy research, vol. 11, no. 4, December, 2021. https://doi.org/10.20508/ijrer.v11i4.12516.g8327 |
| [5] | N. M. Nahar and Jagdish P. Gupta, Energy-conservation potential for solar cookers in arid zones of India, Energy Vol. 16, No. 6, pp. 965-969, 1991. https://doi.org/10.1016/0360-5442(91)90048-Q |
| [6] | Pegah Mirzania, Joel A. Gordon, Nazmiye Balta-Ozkan, Ramazan Caner Sayan, Lochner Marais, Barriers to powering past coal: Implications for a just energy transition in South Africa, Energy Research & Social Science, Volume 101, July 2023, 103122. https://doi.org/10.1016/j.erss.2023.103122 |
| [7] | Evelyne Taryam, “Accès Énergie Tchad: Un Frein au Développement,” Thinking Africa, January 2021, https://www.thinkingafrica.org/V2/lacces-a-lenergie-au-tchad-un-frein-au-developpement/ |
| [8] | Ali Ramadan Ali, Mahamat Kher Neduinga, Marinette Jeutho Gouajio, André Abanda, Hervé Simo, Adoum Danao Adile, Fabien Kenmogne, Effects of adding the antiparallel diodes in a model of solar photovoltaic cell: Theory and Pspice simulations, Journal of Modern Green Energy, (2024), accepted for publication. |
| [9] | Bali Tamegue Bernard, Donatien Njomo, Venant Sorel Chara-Dackou, Mahamat Hassane Babikir, Mahamat Ker Nediguina, Daniel Roméo Kamta Legue, Techno-Economic Analysis of Wind Power Generation in Mongo and Abeche, Chad, International Journal of Sustainable Development and Planning, Vol. 19, No. 1, January, 2024, pp. 55-67. https://doi.org/10.18280/ijsdp.190105 |
| [10] | A. K. Azad, M. G. Rasul, T. Yusaf, (2014). Statistical Diagnosis of the Best Weibull Methods for Wind Power Assessment for Agricultural Applications. Energies, 2014, 7, 3056-3085; https://doi.org/10.3390/en7053056 |
| [11] | F. Youcef Ettoumi, A. Mefti, A. Adane, M. Y. Bouroubi, Statistical analysis of solar measurements in Algeria using beta distributions, Renewable Energy 26 (2002) 47–67. https://doi.org/10.1016/S0960-1481(01)00100-8 |
| [12] | Marinette G. Jeutho, Fabien Kenmogne and David Yemélé, Statistical estimation of mean wind energy available in western Region, of Cameroon: case of the Bafoussam's city, Journal Of Harmonized Research in Engineering 5(1), 2017, 15-27. |
| [13] | Marinette G. Jeutho, Kenmogne Fabien, Yemele David, How to Use the Temperature Data to Find the Appropriate Site for Best Wind Speed Generation? Applications on Data Obtained from Three Different Cities of Cameroon, International Journal of Scientific Engineering and Science, Volume 2, Issue 4, pp. 53-62, 2018. |
| [14] | Adoum Kriga, Allassem Désiré, André Abanda, Adoum Danao Adile, Yaya Dagal Dari 6 and Fabien Kenmogne, Forecast of the electrical energy demand of N’Djamena, Chad, based on the statistical method, World Journal of Advanced Research and Reviews, 2023, 17(01), 762–768. https://doi.org/10.30574/wjarr.2023.17.1.0073 |
| [15] | Lund, H. (2007). Renewable energy strategies for sustainable development. Energy 32(6). https://doi.org/10.1016/j.energy.2006.10.017 |
| [16] | Sarkar, Md. N. I. (2016) Estimation of Solar Radiation from Cloud Cover Data of Bangladesh. Renewables: Wind, Water, and Solar, 3, 11, pages 912-919. https://doi.org/10.1186/s40807-016-0031-7 |
| [17] | Ayodele, T. R. and Ogunjuyigbe, A. S. O. (2015) Prediction of Monthly Average Global Solar Radiation Based on Statistical Distribution of Clearness Index. Energy, 90, 1733-1742. https://doi.org/10.1016/j.energy.2015.06.137 |
| [18] | Liu, Y. H. and Jordan, R. C. (1960) The Inter Relationship and Characteristic Distribution of Direct, Diffuse and Total Solar Radiation from Meterological Data. Solar Energy, 4, 1-19. https://doi.org/10.1016/0038-092X(60)90062-1 |
| [19] | Jain, A., Mehta, R. and Mittal, S. K. (2011) Modeling Impact of Solar Radiation Onsite selection for Solar PV Power Plants in India. International Journal of Green Energy, 8, 486-498. https://doi.org/10.1080/15435075.2011.576293 |
| [20] | Kumar, R. and Umanand, L. (2005) Estimation of Global Radiation Using Clearness index Model for Sizing Photovoltaic System. Renew Energy, 30, 2221-2233. https://doi.org/10.1016/j.renene.2005.02.009 |
| [21] | Khorasanizadeh, H. and Mohammadi, K. (2013) Prediction of Daily Global Solar Radiation by Day of the Year in Four Cities Located in the Sunny Regions of Iran. Energy Conversion and Management, 76, 385-392. https://doi.org/10.1016/j.enconman.2013.07.073 |
| [22] | Karakoti, I., Das, P. K. and Singh, S. K. (2012) Predicting Monthly Mean Daily Diffuse Radiation for India. Applied Energy, 91, 412-425. https://doi.org/10.1016/j.apenergy.2011.10.012 |
| [23] | Hassan, G. E., Youssef, M. E., Zahraa, E., Mohamed, A. A. and Hanafy, A. A. (2016) New Temperature-Based Models for Predicting Global Solar Radiation. Applied Energy, 179, 437-450. https://doi.org/10.1016/j.apenergy.2016.07.006 |
APA Style
Ali, A. R., Nediguina, M. K., Kriga, A., Gouajio, M. J., Adile, A. D., et al. (2024). Mathematical Prediction of Electrical Solar Energy Based on Solar Data for Two Main Cities of Chad: Mongo in the Centre and Pala in the South of Chad. Journal of Energy, Environmental & Chemical Engineering, 9(1), 33-45. https://doi.org/10.11648/j.jeece.20240901.14
ACS Style
Ali, A. R.; Nediguina, M. K.; Kriga, A.; Gouajio, M. J.; Adile, A. D., et al. Mathematical Prediction of Electrical Solar Energy Based on Solar Data for Two Main Cities of Chad: Mongo in the Centre and Pala in the South of Chad. J. Energy Environ. Chem. Eng. 2024, 9(1), 33-45. doi: 10.11648/j.jeece.20240901.14
AMA Style
Ali AR, Nediguina MK, Kriga A, Gouajio MJ, Adile AD, et al. Mathematical Prediction of Electrical Solar Energy Based on Solar Data for Two Main Cities of Chad: Mongo in the Centre and Pala in the South of Chad. J Energy Environ Chem Eng. 2024;9(1):33-45. doi: 10.11648/j.jeece.20240901.14
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Download@article{10.11648/j.jeece.20240901.14,
author = {Ali Ramadan Ali and Mahamat Kher Nediguina and Adoum Kriga and Marinette Jeutho Gouajio and Adoum Danao Adile and Fabien Kenmogne and Abakar Mahamat Tahir},
title = {Mathematical Prediction of Electrical Solar Energy Based on Solar Data for Two Main Cities of Chad: Mongo in the Centre and Pala in the South of Chad},
journal = {Journal of Energy, Environmental & Chemical Engineering},
volume = {9},
number = {1},
pages = {33-45},
doi = {10.11648/j.jeece.20240901.14},
url = {https://doi.org/10.11648/j.jeece.20240901.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeece.20240901.14},
abstract = {The comparative study of the solar powers between two main cities of Chad is performed in the present work, the city of Mongo in the Centre and that of Pala in the South, with an aim of knowing which one of the two cities is more adequate for an installation of the solar power station, taking into account the regional climatic and environmental conditions of both cities. To do this, the graphical statistical analysis of long-term solar irradiance data and temperature is performed. The data used is that of the decade (2010-2020), based on solar radiation data handed by the National Aeronautics and Space Administration (NASA) and Photovoltaic Geographical Information System (PGIS) for Mongo in the centre and Pala in the south of Chad. The shape of the mean monthly irradiation has been plotted and has been approximated using the sinusoidal function through the mean square analysis. The temperature data has been also obtained by the same process and plotted versus irradiance in order to find the adequate mathematical relationship between them. For the statistical analysis, the maximum entropy principle has been used. As results, it is found that the maximum irradiance is obtained in March, which are 226.26kWh/m2 for Pala and 219.355kWh/m2 for Mongo, while the minimum irradiances are obtained in August, which are 151.67kWh/m2 for Pala and 158.9kWh/m2 for Mongo. The temperature data is also obtained and the mean monthly data plotted, showing that apart for the months of March and April, the the shapes of irradiation and temperatures are similar for both sites. Then it is found that the frequency and probability density distributions reach their maximum at the same dates.
},
year = {2024}
}
TY - JOUR T1 - Mathematical Prediction of Electrical Solar Energy Based on Solar Data for Two Main Cities of Chad: Mongo in the Centre and Pala in the South of Chad AU - Ali Ramadan Ali AU - Mahamat Kher Nediguina AU - Adoum Kriga AU - Marinette Jeutho Gouajio AU - Adoum Danao Adile AU - Fabien Kenmogne AU - Abakar Mahamat Tahir Y1 - 2024/03/13 PY - 2024 N1 - https://doi.org/10.11648/j.jeece.20240901.14 DO - 10.11648/j.jeece.20240901.14 T2 - Journal of Energy, Environmental & Chemical Engineering JF - Journal of Energy, Environmental & Chemical Engineering JO - Journal of Energy, Environmental & Chemical Engineering SP - 33 EP - 45 PB - Science Publishing Group SN - 2637-434X UR - https://doi.org/10.11648/j.jeece.20240901.14 AB - The comparative study of the solar powers between two main cities of Chad is performed in the present work, the city of Mongo in the Centre and that of Pala in the South, with an aim of knowing which one of the two cities is more adequate for an installation of the solar power station, taking into account the regional climatic and environmental conditions of both cities. To do this, the graphical statistical analysis of long-term solar irradiance data and temperature is performed. The data used is that of the decade (2010-2020), based on solar radiation data handed by the National Aeronautics and Space Administration (NASA) and Photovoltaic Geographical Information System (PGIS) for Mongo in the centre and Pala in the south of Chad. The shape of the mean monthly irradiation has been plotted and has been approximated using the sinusoidal function through the mean square analysis. The temperature data has been also obtained by the same process and plotted versus irradiance in order to find the adequate mathematical relationship between them. For the statistical analysis, the maximum entropy principle has been used. As results, it is found that the maximum irradiance is obtained in March, which are 226.26kWh/m2 for Pala and 219.355kWh/m2 for Mongo, while the minimum irradiances are obtained in August, which are 151.67kWh/m2 for Pala and 158.9kWh/m2 for Mongo. The temperature data is also obtained and the mean monthly data plotted, showing that apart for the months of March and April, the the shapes of irradiation and temperatures are similar for both sites. Then it is found that the frequency and probability density distributions reach their maximum at the same dates. VL - 9 IS - 1 ER -
Department of Civil Engineering, Advanced Teacher Training College of the Technical Education, University of Douala, Douala, Cameroon
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