1. Mapping wind power density for Zimbabwe: a suitable Weibull-parameter calculation method
- Author
-
Downmore Musademba, Luxmore Madiye, and Tawanda Hove
- Subjects
lcsh:GE1-350 ,Wind power ,General Computer Science ,Mean squared error ,Meteorology ,business.industry ,Rayleigh distribution ,graphical method ,Probability density function ,power density ,Weibull distribution parameters ,Wind speed ,Standard deviation ,General Energy ,Wind profile power law ,lcsh:Energy conservation ,Physics::Space Physics ,lcsh:TJ163.26-163.5 ,business ,Physics::Atmospheric and Oceanic Physics ,lcsh:Environmental sciences ,Weibull distribution ,Mathematics - Abstract
The two-parameter Weibull probability distribution function is versatile for modelling wind speed frequency distribution and for estimating the energy delivery potential of wind energy systems if its shape and scale parameters, k and c, are correctly determined from wind records. In this study, different methods for determining Weibull k and c from wind speed measurements are reviewed and applied at four sample meteorological stations in Zimbabwe. The appropriateness of each method in modelling the wind data is appraised by its accuracy in predicting the power density using relative deviation and normalised root mean square error. From the methods considered, the graphical method proved to imitate the wind data most closely followed by the standard deviation method. The Rayleigh distribution (k=2 is also generated and compared with the wind speed data. The Weibull parameters were calculated by the graphical method for fourteen stations at which hourly wind speed data was available. These values were then used, with the assistance of appropriate boundary layer models, in the mapping of a wind power density map at 50m hub height for Zimbabwe. Keywords: Weibull distribution parameters, graphical method, power density.
- Published
- 2017