PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Assessment of the Geographic and Technical Potential for Large-Scale Wind Energy Production Using a GIS-Based MCDM-AHP Multi-criteria Analysis Method and Sensitivity Analysis: Case of Cameroon
Version 1
: Received: 31 January 2024 / Approved: 2 February 2024 / Online: 2 February 2024 (07:46:43 CET)
How to cite:
Fotsing Metegam, I.F.; Bomeni, I.Y.; Chara-Dackou, V.S.; Njomo, D.; Tchinda, R. Assessment of the Geographic and Technical Potential for Large-Scale Wind Energy Production Using a GIS-Based MCDM-AHP Multi-criteria Analysis Method and Sensitivity Analysis: Case of Cameroon. Preprints2024, 2024020122. https://doi.org/10.20944/preprints202402.0122.v1
Fotsing Metegam, I.F.; Bomeni, I.Y.; Chara-Dackou, V.S.; Njomo, D.; Tchinda, R. Assessment of the Geographic and Technical Potential for Large-Scale Wind Energy Production Using a GIS-Based MCDM-AHP Multi-criteria Analysis Method and Sensitivity Analysis: Case of Cameroon. Preprints 2024, 2024020122. https://doi.org/10.20944/preprints202402.0122.v1
Fotsing Metegam, I.F.; Bomeni, I.Y.; Chara-Dackou, V.S.; Njomo, D.; Tchinda, R. Assessment of the Geographic and Technical Potential for Large-Scale Wind Energy Production Using a GIS-Based MCDM-AHP Multi-criteria Analysis Method and Sensitivity Analysis: Case of Cameroon. Preprints2024, 2024020122. https://doi.org/10.20944/preprints202402.0122.v1
APA Style
Fotsing Metegam, I.F., Bomeni, I.Y., Chara-Dackou, V.S., Njomo, D., & Tchinda, R. (2024). Assessment of the Geographic and Technical Potential for Large-Scale Wind Energy Production Using a GIS-Based MCDM-AHP Multi-criteria Analysis Method and Sensitivity Analysis: Case of Cameroon. Preprints. https://doi.org/10.20944/preprints202402.0122.v1
Chicago/Turabian Style
Fotsing Metegam, I.F., Donatien Njomo and René Tchinda. 2024 "Assessment of the Geographic and Technical Potential for Large-Scale Wind Energy Production Using a GIS-Based MCDM-AHP Multi-criteria Analysis Method and Sensitivity Analysis: Case of Cameroon" Preprints. https://doi.org/10.20944/preprints202402.0122.v1
Abstract
This article presents the suitability analysis of onshore wind farm sites using an AHP (Hierarchical Analysis Process) multi-criteria decision-making (MCDM) approach based on geographic information system modeling (GIS). This analysis is based on different technical aspects (wind speed, elevation, slope), economic (proximity to the electricity network, proximity to roads) and social (proximity to residential areas, population density). The introduction of the factor “population density” and the constraint “required area” rarely used in previous studies makes it possible to refine the results. The data is classified into several categories in a gradual manner, namely unsuitable (0); less suitable (1); suitable (2); highly suitable (3) and most suitable (4). The results of the study show us that the largest percentage relating to spatial coverage is observed in the “suitable” range with 50.89% and the corresponding TWPP (theoretical wind power potential) is 1377.926 GW; it is followed by “highly suitable” 5.67% and a TWPP of 153.652 GW; then “less suitable” with 1.04% and a TWPP of 28.163GW. No areas were identified in “most suitable” and finally the “unsuitable” range with 42.4%. The results show that the most favorable areas are located in the part of the far north of the country corresponding to the strong wind zone. The sensitivity analysis was carried out based on scenario tests (technical, economic and equal-weight) in order to give greater visibility of choice to the different stakeholders who would like to invest in onshore wind energy in Cameroon. This study is useful in more than one way because the results obtained can help investors, the government and other stakeholders to identify potential areas for the deployment of wind energy systems in Cameroon. Furthermore, a study of hybrid solar-wind systems could improve the efficiency of electricity parks in Cameroon.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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