Modelling approach and predictive assessment of wind energy potential in the Nouakchott region, Mauritania

El Moustapha Bououbeid, Ahmed Mohamed Yahya*, Mamadou Lamine Samb, Shafiqur Rehman, Abdel Kader Mahmoud, Christophe Menezo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Mauritanian government has opted the utilization of renewables sources for power generation to reduce the carbon emissions foot print of the country. Accordingly, wind and wind power characteristics are being investigated in the present work in the northern and southern areas of Nouakchott, Mauritania. The study utilizes the wind speed data measured at 20, 40, and 60 m above the ground level (AGL) over a period of 12 months. The data is collected every 5 s- and 10-minutes averaged values are stored. The Weibull probability density function is used to study the wind characteristics and its potential for the two selected sites. The results show that the mean annual wind speed and wind power density at the Nouakchott South site are, respectively (6.42 m/s and 185.25 W/m2), (7.06 m/s and 230. 48 W/m2) and (7.72 m/s and 287.8 W/m2) at 20, 40 and 60 m. However, these values are (5.49 m/s and 116.79 W/m2), (6.51 m/s and 174.08 W/m2) and (7.33 m/s and 246.07 W/m2) at respective heights mentioned above at Northern site. Two statistical indicators are used to investigate the efficiency of used method. These indicators are the coefficient of determination (R2) and root mean square error (RMSE) between the measured and estimated wind speed values are found in the range of 0.962–0.981 and 0.014–0.02 respectively. This shows the reliability of the fitted distribution function and the accuracy of the estimation method used. Three wind turbines with rated power 2000 kW are selected to estimate the available wind power at the two sites. The results indicate a good and harness able wind power potential in the Nouakchott Mauritania region.

Original languageEnglish
Pages (from-to)969-981
Number of pages13
JournalModeling Earth Systems and Environment
Issue number1
StatePublished - Feb 2024

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.


  • Density function
  • Mauritania
  • Monitoring
  • Statistical analysis
  • Weibull parameters
  • Weibull probability
  • Wind energy potential

ASJC Scopus subject areas

  • General Environmental Science
  • General Agricultural and Biological Sciences
  • Computers in Earth Sciences
  • Statistics, Probability and Uncertainty


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