In Chad, the lack of drinking water is a real problem in the desert area. This paper focuses on the statistical assessment of water production using a wind source in North-Eastern Chad to serve the population. The statistical analysis method used for estimating wind power density is the Weibull distribution. Two sites were chosen for the study, namely Fada and Amdjarass. The data used is collected over eight years and two statistical tests were used to assess the convergence of the different distributions. Average wind speeds were calculated to assess the energy potential of the sites. At 10m from the ground, the average wind speeds obtained over eight (08) years are 6.11 m/s at Amdjarass with predominant winds from the North East and 5.43 m/s at Fada with predominant winds from the East. This makes the two localities with high wind potential in Chad. An electric water pumping technique was used for water quantity estimation by testing four (04) wind turbines. The GEVMP aerogenerator meets the needs of both sites. Installed on a 55m high mast, this two-blade aerogenerator can provide on average between 3778.3 m3 of water/day to 1511.3 m3 of water/day for a system ranging from 60m to 150m in head at Fada. This corresponds on average to 139.36l/d/pers (60m HMT) to 55.74l/d/pers (150m HMT). As in Amdjarass, the GEVMP aerogenerator can provide between 3986.3 m3 of water/day to 1594.5 m3 of water/day for a system ranging from 60m to 150m in head. This corresponds on average to 129.57l/d/pers (60m HMT) to 51.82l/d/pers (150m HMT).
| Published in | World Journal of Applied Physics (Volume 7, Issue 2) |
| DOI | 10.11648/j.wjap.20220702.12 |
| Page(s) | 21-31 |
| 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), 2022. Published by Science Publishing Group |
Wind, Energy, Pumping, Water
| [1] | Institut National de la Statistique, des Etudes Economiques et Démographiques. (2022). ‘Population du Tchad en 2022’ [Population of Chad in 2022]. Retrieved 24 April 2022, from https://www.inseed.td/index.php/blog-with-right-sidebar/tchadbref/91-chomage |
| [2] | Projet Régional d’Appui au Pastoralisme au Sahel. (2015). ‘Recensement Général de la Population’ [General Livestock Census in Chad]. Retrieved 25 April 2022, from www.praps-tchad.net |
| [3] | Tchad - Programme d'approvisionnement en eau potable et d'assainissement en milieux semi urbain et rural de onze régions - Phase 1. (2018). rapport détaillé [Detailed Report of the Drinking Water Supply and Sanitation Program in Semi-Urban and Rural Areas of Eleven Regions - Phase 1]. Retrieved 5 April 2022, from https://www.pseau.org/outils/ouvrages/dgre_bf_pnaepa_document_de_programme.pdf |
| [4] | Abakar Ramadane. (2017). ‘Problematique de l’Eau et de l’Assainissement au Tchad’ [Problems of Water and Sanitation in Chad]. Retrieved 22 April 2022, from https://www.unece.org/fileadmin/DAM/env/documents/2017/WAT/03Mar_29_30_National_Workshop_Chad/2_Ramadane_Problematique_du_secteur_Eau_et_assainissement.pdf |
| [5] | OCHA. (2022). Apercu des Besoins Humanitaires au Tchad’ [Overview of Humanitarian Needs in Chad]. Retrieved 26 April 2022, from https://reliefweb.int/report/chad/tchad-aper-u-des-besoins-humanitaires-2022-mars-2022#:~:text=La%20vision%202030%20(le%20Tchad,(PND%202017%2D2021 |
| [6] | Ministère de l’Environnement, de l’Eau et de la Pêche. (2027). ‘Programme de coopération Tchad-UNICEF 2017-2021 dans le secteur de l’Eau, Hygiène et Assainissement’ [Chad-UNICEF cooperation program 2017-2021 in the water, hygiene and sanitation sector]. Retrieved 25 April 2022 from https://reliefweb.int/report/chad/r-sultats-2017-le-programme-de-coop-ration-tchad-unicef-2017-2021-dans-le-secteur-de-l |
| [7] | Shaohui Zhou, Yuanjian Yang, Zhiqiu Gao, Xingya Xi, Zexia Duan, and Yubin Li, ‘Estimating vertical wind power density using tower observation and empirical models over varied desert steppe terrain in northern China’, Atmos. Meas. Tech., 15, 757–773, 2022. https://doi.org/10.5194/amt-15-757-2022 |
| [8] | Kidmo, D. K., Bogno, B., Deli, K. and Goron, D. (2020) Seasonal Wind Characteristics and Prospects of Wind Energy Conversion Systems for Water Production in the Far North Region of Cameroon. Smart Grid and Renewable Energy, 11, 127-164. https://doi.org/10.4236/sgre.2020.119009 |
| [9] | Marcel Hamda Soulouknga, Sunday Olayinka Oyedepo, Serge Yamigno Doka, Timoleon Crépin Kofane, 'Evaluation of the cost of producing wind-generated electricity in Chad', International Journal of Energy and Environmental Engineering', January 2020. https://doi.org/10.1007/s40095-019-00335-y |
| [10] | Elie Bertrand KS, Abraham K and Lucien M (2020) Sustainable Energy ‘Through Wind Speed and Power Density Analysis in Ambam, South Region of Cameroon’. Front. Energy Res. 8: 176. |
| [11] | Seydo Ouedraogo, Komlan Lolo, Kodjo Attipou, Ayite Senah Akoda Ajavon, Sonnou Tiem, ‘Assessment of wind Potential in the perspective of Water Pumping in Sahelian Area of Burkina Faso’, International Journal of Engineering Research & Technology (IJERT), vol. 9 Issue 03, March-2020. |
| [12] | Youssef Kassem, Hüseyin Çamur, Sama A. M. Abughinda and Ali Şefik, ‘Wind Energy Potential Assessment in Selected Regions in Northern Cyprus Based on Weibull Distribution Function’, Journal of Engineering and Applied Sciences 15 (1): 128-140, 2020. |
| [13] | Dieudonné Kidmo Kaoga, Noël Djongyang, Serges Yamigno Doka, Danwe Raidandi, 'Statistical Analysis of Wind Speed Distribution Based on six Weibell Methods for Wind Power Evaluation in Garoua, Cameroon', Revue des Energies Renouvelables, Vol. 18, N°1, pp. 105 - 125, 2015. |
| [14] | Al-Mhairat, B.; Al-Quraan, A. Assessment of Wind Energy Resources in Jordan Using Different Optimization Techniques. Processes 2022, 10, 105. https://doi.org/10.3390/pr10010105. |
| [15] | Krishneel Singh, Leonie Bule, MGM Khan and M Rafiuddin Ahmed, ‘Wind energy resource assessment for Vanuatu with accurate estimation of Weibull parameters’, Energy Exploration & Exploitation 2019, Vol. 37 (6) 1804–1833 https://doi.og/10.1177/0144598719866897journals.sagepub.com/home/eea |
| [16] | Al-Motasem I. Aldaoudeyeh and Khaled Alzaareer, ‘Evaluating the Accuracy of Wind Turbine Power-Speed Characteristics Fits for the Generator Control Region’. INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH, Vol. 10, No. 2, June, 2020. |
| [17] | Dongbum Kang, Kyungnam Ko, and Jongchul Huh, ‘Comparative Study of Different Methods for Estimating Weibull Parameters: A Case Study on Jeju Island, South Korea’, Energies 2018, 11, 356; https://doi.org/10.3390/en11020356 |
| [18] | Ahmet Emre Onay, Emrah Dokur, Mehmet Kurban,’ Performance comparison of new generation parameter estimation methods for Weibull distribution to compute Wind Energy Density’, ELEKTRONIKA IR ELEKTROTECHNIKA, ISSN 1392-1215, VOL. 27, NO. 5, 2021. https://doi.org/10.5755/j02.eie.28919 |
| [19] | Z. R. Shu and Mike Jesson, ‘Estimation of Weibull parameters for wind energy analysis across the UK’, J. Renewable Sustainable Energy 13, 023303 (2021). https://doi.org/10.1063/5.0038001 |
| [20] | Younes El Khchine, Mohammed Sriti, Nacer Eddine El Kadri Elyamani, 'Evaluation of wind energy potential and treds in morocco', Heliyon 5 (2019) e01830. |
| [21] | Ijjou Tizgui, Hassane Bouzahir, Fatima El Guezar and Brahim Benaid, ‘Estimation of Electricity Production for a Moroccan Wind Farm’, ResearchGate. https://www.researchgate.net/publication/312571205 |
| [22] | G. Al Zohbi, P. Hendrick et P. Bouillard, ‘Evaluation du potentiel d’énergie éolienne au Liban’ [Assessment of wind potential in Lebanon], Revue des Energies Renouvelables Vol. 17 N°1 (2014) 83 – 96. |
| [23] | Mehr Gul, Nengling Tai, Wentao Huang, Muhammad Haroon Nadeem and Moduo Yu, ‘Evaluation of Wind Energy Potential Using an Optimum Approach based on Maximum Distance Metric’, Sustainability 2020, 12, 1999; https://doi.org/10.3390/su12051999 |
| [24] | A Shobana Devi, Dr. G Maragatham, M R Prabu, K Boopathi, ‘Short-Term Wind Power Forecasting Using RLSTM’, INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH, Vol. 11, No. 1, March, 2021. |
| [25] | Boro, D., Donnou, H. E. V., Kossi, I., Bado, N., Kieno, F. P. and Bathiebo, J. (2019) Vertical Profile of Wind Speed in the Atmospheric Boundary Layer and Assessment of Wind Resource on the Bobo Dioulasso Site in Burkina Faso. Smart Grid and Renewable Energy, 10, 257-278. https://doi.org/10.4236/sgre.2019.1011016 |
| [26] | Marcel Hamda Soulouknga, Dumitru-Dorin Lucache, Serge Yamigno Doka, Timoleon Crepin Kofane, ‘Techno-economic assessment of wind energy conversion systems for power generation for the city of N'Djamena in Chad’, Journal of Renewable Energies 23 (2020) 318– 330. |
| [27] | Sadam Alphonsea, Bikai Jacquesa, Tetang Fokone Abrahamb, Kapseu Cesarc, ‘Potentiel énergétique éolien et profil de consommation d’énergie dans le village Wouro Kessoum Ngaoundéré Cameroun’ [Wind potential and energy consumption profile in the village Wouro Kessoum Ngaoundéré Cameroon], Journal of Renewable Energies 23 (2020) 72 – 85. |
| [28] | N. A. Satwika, R. Hantoro, E. Septyaningrum and A. W. Mahmashani 'Analysis of wind energy potential and wind development to evaluate performance of wind installation in Bali, Indonesia', Journal of Mecanical Enineering and Sciences, Volume 13, issue 1, pp. 4461-4476, March 2019. https://doi.org/10.15282/jmes.13.1.2019.09.0379 |
| [29] | Galarza, J., Condezo, D., Camayo, B. and Mucha, E. (2020) Assessment of Wind Power Density Basedon Weibull Distribution in Region of Junin, Peru. Energy and Power Engineering, 12, 16-27. https://doi.org/10.4236/epe.2020.121002 |
| [30] | J. L. Nsouandélé, D. K. Kidmo, S. M. Djetouda and N. Djongyang, ‘Estimation statistique des données du vent à partir de la distribution de Weibull en vue d’une prédiction de la production de l’énergie électrique d’origine éolienne sur le Mont Tinguelin à Garoua dans le Nord Cameroun’ [Statistical estimation of wind data from the Weibull distribution with a view to predicting the production of electrical energy of wind origin on Mount Tinguelin in Garoua in northern Cameroon], Revue des Energies Renouvelables Vol. 19, N°2 (2016) 291 – 301. |
| [31] | M. Benabdelkader, A. Malek et B. Draoui, ‘Perspective du pompage éolien appliqué à l’irrigation du palmier dattier dans la région de Béchar’ [Perspective of wind pumping applied to date palm irrigation in the Béchar region], Revue des Energies Renouvelables Vol. 14 N°3 (2011) 381 – 395. |
| [32] | 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. Vol. 9, No. 6, 2020, pp. 86-94. doi: 10.11648/j.ijepe.20200906.11 |
APA Style
Mahamat Kher Nediguina, Mahamat Adoum Abdraman, Mahamat Barka, Abakar Mahamat Tahir. (2022). Electric Water Pumping Powered by a Wind Turbine in North East Chad. World Journal of Applied Physics, 7(2), 21-31. https://doi.org/10.11648/j.wjap.20220702.12
ACS Style
Mahamat Kher Nediguina; Mahamat Adoum Abdraman; Mahamat Barka; Abakar Mahamat Tahir. Electric Water Pumping Powered by a Wind Turbine in North East Chad. World J. Appl. Phys. 2022, 7(2), 21-31. doi: 10.11648/j.wjap.20220702.12
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.wjap.20220702.12,
author = {Mahamat Kher Nediguina and Mahamat Adoum Abdraman and Mahamat Barka and Abakar Mahamat Tahir},
title = {Electric Water Pumping Powered by a Wind Turbine in North East Chad},
journal = {World Journal of Applied Physics},
volume = {7},
number = {2},
pages = {21-31},
doi = {10.11648/j.wjap.20220702.12},
url = {https://doi.org/10.11648/j.wjap.20220702.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wjap.20220702.12},
abstract = {In Chad, the lack of drinking water is a real problem in the desert area. This paper focuses on the statistical assessment of water production using a wind source in North-Eastern Chad to serve the population. The statistical analysis method used for estimating wind power density is the Weibull distribution. Two sites were chosen for the study, namely Fada and Amdjarass. The data used is collected over eight years and two statistical tests were used to assess the convergence of the different distributions. Average wind speeds were calculated to assess the energy potential of the sites. At 10m from the ground, the average wind speeds obtained over eight (08) years are 6.11 m/s at Amdjarass with predominant winds from the North East and 5.43 m/s at Fada with predominant winds from the East. This makes the two localities with high wind potential in Chad. An electric water pumping technique was used for water quantity estimation by testing four (04) wind turbines. The GEVMP aerogenerator meets the needs of both sites. Installed on a 55m high mast, this two-blade aerogenerator can provide on average between 3778.3 m3 of water/day to 1511.3 m3 of water/day for a system ranging from 60m to 150m in head at Fada. This corresponds on average to 139.36l/d/pers (60m HMT) to 55.74l/d/pers (150m HMT). As in Amdjarass, the GEVMP aerogenerator can provide between 3986.3 m3 of water/day to 1594.5 m3 of water/day for a system ranging from 60m to 150m in head. This corresponds on average to 129.57l/d/pers (60m HMT) to 51.82l/d/pers (150m HMT).},
year = {2022}
}
TY - JOUR T1 - Electric Water Pumping Powered by a Wind Turbine in North East Chad AU - Mahamat Kher Nediguina AU - Mahamat Adoum Abdraman AU - Mahamat Barka AU - Abakar Mahamat Tahir Y1 - 2022/07/22 PY - 2022 N1 - https://doi.org/10.11648/j.wjap.20220702.12 DO - 10.11648/j.wjap.20220702.12 T2 - World Journal of Applied Physics JF - World Journal of Applied Physics JO - World Journal of Applied Physics SP - 21 EP - 31 PB - Science Publishing Group SN - 2637-6008 UR - https://doi.org/10.11648/j.wjap.20220702.12 AB - In Chad, the lack of drinking water is a real problem in the desert area. This paper focuses on the statistical assessment of water production using a wind source in North-Eastern Chad to serve the population. The statistical analysis method used for estimating wind power density is the Weibull distribution. Two sites were chosen for the study, namely Fada and Amdjarass. The data used is collected over eight years and two statistical tests were used to assess the convergence of the different distributions. Average wind speeds were calculated to assess the energy potential of the sites. At 10m from the ground, the average wind speeds obtained over eight (08) years are 6.11 m/s at Amdjarass with predominant winds from the North East and 5.43 m/s at Fada with predominant winds from the East. This makes the two localities with high wind potential in Chad. An electric water pumping technique was used for water quantity estimation by testing four (04) wind turbines. The GEVMP aerogenerator meets the needs of both sites. Installed on a 55m high mast, this two-blade aerogenerator can provide on average between 3778.3 m3 of water/day to 1511.3 m3 of water/day for a system ranging from 60m to 150m in head at Fada. This corresponds on average to 139.36l/d/pers (60m HMT) to 55.74l/d/pers (150m HMT). As in Amdjarass, the GEVMP aerogenerator can provide between 3986.3 m3 of water/day to 1594.5 m3 of water/day for a system ranging from 60m to 150m in head. This corresponds on average to 129.57l/d/pers (60m HMT) to 51.82l/d/pers (150m HMT). VL - 7 IS - 2 ER -
Email: