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http://hdl.handle.net/10311/2488
Title: | Statistical modelling of Botswana's monthly maximum wind speed using a four-parameter kappa distribution |
Authors: | Moses, Oliver Parida, Bhagabat Prasad |
Keywords: | Botswana Four parameter kappa distribution L-moments Wind power production Wind speed quantiles |
Issue Date: | 21-Jun-2016 |
Publisher: | American Journal of Applied Sciences, https://thescipub.com |
Citation: | 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, Vol. 13, No. 6, pp. 773-778. |
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. |
Description: | Main Article |
URI: | http://hdl.handle.net/10311/2488 |
ISSN: | 1546-9239 (Print) 1554-3641 (Online) |
Appears in Collections: | Research articles (ORI) |
Files in This Item:
File | Description | Size | Format | |
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Oliver_AJA_2016.pdf | Main article | 202.63 kB | Adobe PDF | ![]() View/Open |
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