Wind Speed Analysis for Coastal Regions of Pakistan using Extended Generalized Lindley Distribution


Usman R. M. , BURSA N., Ahsan-Ul-Haq M.

GAZI UNIVERSITY JOURNAL OF SCIENCE, vol.35, no.2, pp.765-774, 2022 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 35 Issue: 2
  • Publication Date: 2022
  • Doi Number: 10.35378/gujs.753789
  • Journal Name: GAZI UNIVERSITY JOURNAL OF SCIENCE
  • Journal Indexes: Emerging Sources Citation Index, Scopus, Academic Search Premier, Aerospace Database, Aquatic Science & Fisheries Abstracts (ASFA), Communication Abstracts, Compendex, Metadex, Civil Engineering Abstracts, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.765-774
  • Keywords: Wind speed analysis, Weibull distribution, Lindley distribution, Generalized Lindley distribution, Power density error, DETERMINING WEIBULL PARAMETERS, NUMERICAL-METHODS, PROBABILITY-DISTRIBUTIONS, NORTHEAST REGION, PERFORMANCE

Abstract

The wind energy potential of a specified area can be estimated using wind speed distribution. In this study, the selection of probability density functions is used to model wind speed data recorded at two stations in Pakistan. The suitability of fitted distributions is evaluated using the goodness of fit criterion, power density error, log-likelihood, root mean square error, coefficient of determination, AIC, and BIC. The wind speed data are obtained from two coastal regions of Pakistan at 10m/s average rate for session 2017-2018. Findings indicated that the extended generalized Lindley distribution provide generally the best fit to the wind speed data for both stations. However, it is also observed that power Lindley and extended generalized Lindley distributions have better performance based on power density error criteria in Gwadar and Haripur, respectively.