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

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  • Afungchui David

    (University of Bamenda, Faculty of Sciences; Department of Physics , PO Box 39, Bambili, NWR, Cameroon)

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.

Suggested Citation

  • Afungchui David, 2014. "Rayleigh Distribution-Based Model for Prediction of Wind Energy Potential of Cameroon," Energy Review, Conscientia Beam, vol. 1(1), pages 26-43.
  • Handle: RePEc:pkp:enerev:2014:p:26-43
    DOI: 10.18488/journal.81/2014.1.1/81.1.26.43
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    Cited by:

    1. Abdullahi Abubakar Mas’ud & Asan Vernyuy Wirba & Jorge Alfredo Ardila-Rey & Ricardo Albarracín & Firdaus Muhammad-Sukki & Álvaro Jaramillo Duque & Nurul Aini Bani & Abu Bakar Munir, 2017. "Wind Power Potentials in Cameroon and Nigeria: Lessons from South Africa," Energies, MDPI, Open Access Journal, vol. 10(4), pages 1-19, March.

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