Abstract

<p>Three-hourly wind speed data measured using the Beaufort scale at a height of 10m, from 6am to 6pm local time (5 periods per day), was obtained from the Bafoussam Airport. It was analyzed using the Weibull and Rayleigh probability density models and wind rose plots. It was determined that the lowest wind speeds (most calms) were observed during the first period (6am) and the highest at 3pm (fourth period). The very low morning wind speed adversely affected the daily mean wind speed. Better, but still poor, power density results were obtained at this fourth (3pm) period. The monthly and yearly mean speeds varied between 1.9 and 3.1m/s and with very low standard deviations. The wind rose plots also showed that all the significant winds fell in the first quadrant (NE) and predominantly on angle 10<sup>o</sup> with some discernibly on 20<sup>o</sup> and 30<sup>o</sup>, only. Three goodness-of-fit tests: the chi square, coefficient of determination or R<sup>2</sup> and root mean square error, showed the Weibull to be a better fit to the wind regime than the Rayleigh model. The shape parameters were always greater than the scale parameters. Results show that, using the Weibull parameters, the power density of Bafoussam falls in the category 1 of the wind energy resource group and hence is not a very good wind energy exploitable candidate.</p>

Highlights

  • Mankind’s crave for energy is insatiable due to ever increasing population and industries

  • Results show that, using the Weibull parameters, the power density of Bafoussam falls in the category 1 of the wind energy resource group and is not a very good wind energy exploitable candidate

  • We studied the Wind characteristics of Bafoussam airport, Cameroon, based on three-hourly wind speeds, measured five times a day starting at 6am local time and at a height of 10m

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Summary

Introduction

Mankind’s crave for energy is insatiable due to ever increasing population and industries. With a huge hydroelectric potential of (294 TWh), and occupying a prestigious position as the second largest in Africa, after the DR Congo (1000 TWh), Cameroon still suffers from severe energy crisis: very frequent power outages and rampant low tension; during the evenings. This is witnessed during the dry season: January to April. In this work we study the wind characteristics of Bafoussam, in the southern part of Cameroon and about 80km from Bamenda It is a regional headquarter (of the West Region), heavily populated and with many agro-industrial activities and medium sized industries and structures and, inherently exposed to the same energy demise. Wind directions are important in determining the directions in which the blades of a vertical axis turbine should be facing so as to minimize the wear and tear when turning to face its direction or during furling

Site Description and Data
Estimation of Wind Potential
Modeling and Evaluation Techniques of Wind Speed
Determination of the Weibull Parameters
Weibull Power density Model
Rayleigh Model
Rayleigh Power Density Model
The Minimum Chi Square Method
Results and Discussions
Conclusion
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