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Rayleigh Distribution-Based Model for Prediction of Wind Energy Potential of Cameroon

Afungchui David

Afungchui David 1

  1. University of Bamenda, Faculty of Sciences; Department of Physics, Bambili, NWR, Cameroon 1

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on PubMed

Pages: 26-43

DOI: 10.18488/journal.81/2014.1.1/81.1.26.43

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Abstract:

Modelling and prediction of wind characteristics are essential design inputs in the development of wind energy systems. This paper exploits the characteristics of the Rayleigh probability density function to analyse the wind potential of all the regions of the republic of Cameroon. In the procedure, the probability density (PD) curves of some representative towns of the ten regions of Cameroon are presented. These curves highlight the fraction of time for which some wind velocity V prevails at the sites and the most frequent wind speed expected at these sites which coincide with the peak of the PD curves. We then proceed to calculate the power density of the sites, as well as the energy available for wind turbine extraction. We recommend the Savonius rotor for the regions of low wind speed based on its low cut-in speed of 1m/s.
Contribution/ Originality
This study is one of very few studies which have investigated the wind energy potential of Cameroon in an exhaustive manner covering all the regions. It also proposes the prospect of harnessing the energy of the wind and recommends the Savonius rotor as the wind turbine generator of choice in Cameroon.

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Reference:

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  2. IEA Country Energy Balance, Available: http://www.laurea.fi/en/connect/results/Documents/Cameroon%20Country%20Report.pdf, 2009.
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