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Wind energy estimation at Quetta

Author

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  • Nasir, S.M.
  • Raza, S.M.
  • Jafri, Yasmin Zahra

Abstract

Hourly wind data at Quetta airport (Samungli) for the years 1984–1985, were obtained using a standard anemometer height of 10 m, with a view to work out the feasibility of wind energy utilization. Quetta (lat. 30°11 'N long. 66°57'E) is elevated at 1799 m above sea level. In this paper, we analyse the wind energy data by using the Weibull distribution. Scaling and shaping parameters are determined by using least-squares approximation to a straight line. Actual wind data, weighted Weibull density function and weighted Rayleigh probability density function for regular and continuous periods of 4 weeks up to a year (wind characteristics are being recorded and summarized as diurnal and monthly wind velocity distributions and wind power density roses) are plotted which shows that the Weibull distribution is generally of the right shape to fit low-averaged wind speed frequency curves. However, density function of a normal distribution is also determined. Deviations in wind speed distributions at very low-averaged wind speeds and at comparatively large-averaged wind speeds are found.

Suggested Citation

  • Nasir, S.M. & Raza, S.M. & Jafri, Yasmin Zahra, 1991. "Wind energy estimation at Quetta," Renewable Energy, Elsevier, vol. 1(2), pages 263-267.
    • Handle: RePEc:eee:renene:v:1:y:1991:i:2:p:263-267
    DOI: 10.1016/0960-1481(91)90085-4
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    Cited by:

    1. Ilyas, Syed Zafar & Anwar, Muhammad & Nasir, S.M, 2000. "Cumulative frequency distribution of solar insolation at Quetta, Pakistan," Renewable Energy, Elsevier, vol. 20(1), pages 83-86.
    2. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
    3. Calif, Rudy & Emilion, Richard & Soubdhan, Ted, 2011. "Classification of wind speed distributions using a mixture of Dirichlet distributions," Renewable Energy, Elsevier, vol. 36(11), pages 3091-3097.

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