2021
DOI: 10.11648/j.ijsd.20210701.11
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Fitting Wind Speed to a 3-Parameter Distribution Using Maximum Likelihood Technique

Abstract: Kenya is one of the countries in the world with a good quantity of wind. This makes the country to work on technologies that can help in harnessing the wind with a vision of achieving a total capacity of 2GW of wind energy by 2030. The objective of this research is to find the best three-parameter wind speed distribution for examining wind speed using the maximum likelihood fitting technique. To achieve the objective, the study used hourly wind speed data collected for a period of three years (2016 -2018) from… Show more

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Cited by 2 publications
(1 citation statement)
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“…The results showed that Marsabit had mean wind power density of 2202 W/m 2 with a prevalent wind speed of 11 m/s while, Garisa registered a mean wind power density of 190 W/m 2 with a prevalent wind speed of 3.90 m/s [16]. There other couple of studies that have assessed wind energy in other places and are well documented in [17], [18]; [19]. The wind regime characteristics of Narok county are still scanty owing to few studies that have been done on the same area even though wind energy mapping shows that Narok is lying in windy region.…”
Section: Introductionmentioning
confidence: 99%
“…The results showed that Marsabit had mean wind power density of 2202 W/m 2 with a prevalent wind speed of 11 m/s while, Garisa registered a mean wind power density of 190 W/m 2 with a prevalent wind speed of 3.90 m/s [16]. There other couple of studies that have assessed wind energy in other places and are well documented in [17], [18]; [19]. The wind regime characteristics of Narok county are still scanty owing to few studies that have been done on the same area even though wind energy mapping shows that Narok is lying in windy region.…”
Section: Introductionmentioning
confidence: 99%