Research Article Open Access

Statistical Modelling of Botswana’s Monthly Maximum Wind Speed using a Four-Parameter Kappa Distribution

Oliver Moses1 and Bhagabat Prasad Parida2
  • 1 Okavango Research Institute, University of Botswana, Maun, Botswana
  • 2 Department of Civil Engineering, University of Botswana, Gaborone, Botswana

Abstract

Wind speed modelling has been key to many environmental and engineering applications, particularly in environmentally friendly wind power generation to meet energy demands. Efficient assessment of wind speed at different recurrence intervals requires the choice of a suitable statistical distribution and an unbiased method of parameter estimation. This study suggests the use of a four parameter Kappa distribution, with its parameters estimated using the method of L-moments, to model Botswana’s monthly maximum wind speed data at six meteorological weather stations. These synoptic weather stations are Gaborone, Sir Seretse Khama Airport, Tsabong, Tshane, Gantsi and Maun which are broadly spread across the country’s economic activity centres. Reliable wind speed quantiles have been obtained for the selected stations and have been found to fall within the interval 13.80 to 21.69 m s-1. Mean maximum wind speeds have been found to range between 12.65 and 14.97 m s-1, with standard deviations ranging between 1.58 and 2.44 m s-1. These results can reliably be used by environmentalists and technologists working in the energy sector in Botswana.

American Journal of Applied Sciences
Volume 13 No. 6, 2016, 773-778

DOI: https://doi.org/10.3844/ajassp.2016.773.778

Submitted On: 22 April 2016 Published On: 22 June 2016

How to Cite: Moses, O. & Parida, B. P. (2016). Statistical Modelling of Botswana’s Monthly Maximum Wind Speed using a Four-Parameter Kappa Distribution. American Journal of Applied Sciences, 13(6), 773-778. https://doi.org/10.3844/ajassp.2016.773.778

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Keywords

  • Botswana
  • Four Parameter Kappa Distribution
  • L-Moments
  • Wind Power Production
  • Wind Speed Quantiles