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eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

Forecast of the electrical energy demand of N’Djamena, Chad, based on the statistical method

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  • Forecast of the electrical energy demand of N’Djamena, Chad, based on the statistical method

Adoum  Kriga 1,  Allassem Désiré 2,  André Abanda 3, 4, Adoum Danao Adile 5, Yaya Dagal Dari 6 and Fabien Kenmogne 4, *

1 Department of technology, Faculty of exact and applied science, University of N'djamena, Chad.
2 National Institute of Sciences and Techniques of Abeche (INSTA), Chad.
3 Department of Civil Engineering, National Advanced Polytechnical School of Douala, University of Douala, Cameroon.
4 Department of Civil Engineering, Advanced Teacher Training College of the Technical Education, University of Douala, Cameroon.
5 Department of Industrial Engineering and Maintenance, Polytechnic University of Mongo, Chad.  
 6 Department of Mechanical Engineering, National Institute of Science and Technology of Abeché, Chad.
 
Research Article
World Journal of Advanced Research and Reviews, 2023, 17(01), 762-768
Article DOI: 10.30574/wjarr.2023.17.1.0073
DOI url: https://doi.org/10.30574/wjarr.2023.17.1.0073
 
Received on 04 December 2022; revised on 19 January 2023; accepted on 21 January 2023
 
We study the forecast of the electrical energy demand of the N'Djamena city, Chad, by 2032 using the statistical model based on the linear regression technic. A series of data of the maximum power demand (PMA) for the past years from 2005 to 2017 are obtained from the dispatching center of the company national electricity board of N'Djamena, which allow us to make energy projection from 2018 to 2032. Then these data are analyzed by the statistical method of linear regression forecast. The results obtained by the linear regression are closed to that provided by the Excel trend curve and they have a strong linear correlation coefficient of 0.963 between the maximum powers estimated and the given years. In addition, the predicted power peak needed by electricity consumers by 2032 is 175 MW compared to 90 MW in 2017, meaning that in 15 years, the consumption of electrical energy will pass from simple to double.
 
Electrical energy; Forecast; Statistical method; Generation fleet; Peak power
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2023-0073.pdf

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Adoum Kriga, Allassem Désiré, André Abanda, Adoum Danao Adile, Yaya Dagal Dari 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(1), 762-768. Article DOI: https://doi.org/10.30574/wjarr.2023.17.1.0073

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