Suitability and evaluating wind speed probability distribution models in a hot climate: Djibouti case study

Abdoulkader Ibrahim Idriss*, Ramadan Ali Ahmed, Rima Kassim Said, Abdou Idriss Omar, Burak Barutçu, Abdoulhamid Awalo Mohamed, Tahir Cetin Akinci

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


The paper investigates the most reliable numerical method for estimating the Weibull parameters to calculate the wind power density in urban and rural hot regions of the Republic of Djibouti. It is important to mention that no similar studies have been carried out and therefore this is the first study to evaluate and diagnosis the best Weibull distribution method for wind analysis and wind energy potential in the country. Five investigated numerical methods such as Graphical Method (GM), Empirical Method of Justus (EMJ), Energy Pattern Factor Method (EPFM), Standard Deviation Method (SDM) and Moment Method (MM) were adopted to estimate Weibull c and k parameters. Four statistical indicators including root mean square error, index of agreement, coefficient of determination and relative percentage error were used to precisely rank the methods. The study aims to identify the most accurate method to determine the wind power density in four stations which are University of Djibouti, International Airport of Djibouti, Ghoubet and Bara Wein. Then, to provide a complete analysis, the study is performed on monthly, yearly and seasonal scales. The results reveal that GM and EPFM are the most accurate methods for estimating the c and k parameters and are recommended in estimating the wind power density in Djibouti.

Original languageEnglish
Pages (from-to)1586-1596
Number of pages11
JournalInternational Journal of Renewable Energy Research
Issue number3
Publication statusPublished - 2019

Bibliographical note

Publisher Copyright:
© 2019 International Journal of Renewable Energy Research.


  • Estimation methods
  • Rural
  • Urban
  • Wind power density
  • Wind speed


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