BAREKENG: Jurnal Ilmu Matematika dan Terapan
Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application

WIND ENERGY GENERATION POTENTIAL FOR SELECTED AFRICAN STATIONS BASED ON THE PERFORMANCE OF FIVE WEIBULL DISTRIBUTION PARAMETERS

Francis Olatunbosun Aweda (Physics Programme, College of Agriculture, Engineering and Science, Bowen University, Nigeria)
Solomon Oluwadara Adeola (Bangor University International College, United Kingdom)
Olusanya Odunayo Jegede (Physics Programme, College of Agriculture, Engineering and Science, Bowen University, Nigeria)
Isaac Adewale Ojedokun (Electrical Electronics Programme, College of Agriculture, Engineering and Science, Bowen University, Nigeria)
Saeed Abioye Bello (Physics Department, University of Ilorin, Nigeria)
Oluwatoyin Olasunkami Olasanmi (Physics Department, University of Ilorin, Nigeria)
Kayode Oyeniyi Oyedoja (Technology Education Department, Emmanuel Alayande University of Education, Oyo, Nigeria)
Bukunmi Sunday Olatinwo (College of Mechanics and Engineering Sciences, Hohai University, China)



Article Info

Publish Date
24 Aug 2026

Abstract

The assessment of wind energy potential is essential for sustainable energy planning, particularly in Africa, where renewable energy sources are increasingly considered for power generation. This study evaluates the wind energy potential of eight selected African stations Nairobi (Kenya), Addis Ababa (Ethiopia), Cairo (Egypt), Tunis (Tunisia), Abuja (Nigeria), Accra (Ghana), Pretoria (South Africa), and Luanda (Angola) using wind speed data from 2000 to 2023 obtained from NASA’s power data access viewer. The Weibull probability distribution function (PDF) and cumulative distribution function (CDF) were applied to characterize wind speed variations, employing five different parameter estimation methods. The results indicate significant spatial variability in wind characteristics across the stations. The mean wind speed ranged from 2.31 m/s in Accra, Ghana, to 6.82 m/s in Nairobi, Kenya, highlighting substantial differences in wind energy potential. The shape parameter (k) varied between 1.79 in Luanda and 2.31 in Addis Ababa, while the scale parameter (c) ranged from 2.91 m/s in Accra to 7.48 m/s in Nairobi. Wind power density estimates revealed that Nairobi exhibited the highest power density of 248.7 W/m², followed by Addis Ababa (198.3 W/m²), indicating strong wind energy potential. In contrast, Accra had the lowest power density (34.6 W/m²), suggesting limited viability for wind power generation. Seasonal variations showed that wind speeds peaked in the dry season and declined during wet periods across most locations. These findings provide valuable insights into wind energy feasibility in Africa, aiding policy makers in site selection for wind power development and contributing to the continent’s transition toward renewable energy sources.

Copyrights © 2026






Journal Info

Abbrev

barekeng

Publisher

Subject

Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

Description

BAREKENG: Jurnal ilmu Matematika dan Terapan is one of the scientific publication media, which publish the article related to the result of research or study in the field of Pure Mathematics and Applied Mathematics. Focus and scope of BAREKENG: Jurnal ilmu Matematika dan Terapan, as follows: - Pure ...