Statistical Analysis of Wind Speed for Energy Potential Estimation in Bahir Dar, Ethiopia using Weibull Distribution Function

Abstract

In this study, statistical analysis method has been used to assess the wind energy potential in Bahir Dar, Ethiopia. The analysis has been conducted based on the wind speed data collected by National Meteorological Agency (NMA) for the time span of 2006 to 2015. Weibull distribution function has been used as a statistical analysis model to fit the actual data via probability density function and cumulative density function. While estimating the Weibull parameters (shape and scale) in this wind energy potential assessment, three statistical methods, namely, the Graphical method (GM), method of moments (MOM) and standard deviation method (STDM) were used. Comparison of these statistical methods for the good fit was done by the analysis of the relative percentage error (RPE), root mean square deviation (RMSD), mean percentage error (MPE) and coefficient of variance (R²) procedures. The regression coefficient (R²) between the actual wind speeds and the Weibull predicted values ranged between 0.614-0.872. From this result, the method of moment (MOM) is the best efficient method for determining the value of shape and scale to fit the Weibull distribution curves. The annual mean wind speed in Bahir Dar is 6.86m/s, while the mean wind speed and the power density predicted by the Weibull probability density function are 5.97m/s and 11.37kwatt/m² respectively. The Weibull distribution function can be used with acceptable accuracy for prediction of wind energy output required for preliminary design and assessment of wind power plants.

Keywords: Weibull distribution function, Probability density function, Cumulative density function, Graphical method (GM), Method of moments (MOM), Standard deviation method (STDM), Regression coefficient

DOI: 10.7176/APTA/86-02

Publication date:October 31^st 2022