COMPARISON OF FIVE NUMERICAL METHODS FOR ESTIMATING WEIBULL PARAMETERS FOR WIND ENERGY APPLICATIONS IN THE DISTRICT OF KOUSSERI, CAMEROON

There is a crucial need in the Northern regions of Cameroon to enhance the development of wind technology and engineering, which can be considered to design and characterize Wind Energy Conversion Systems (WECS). The Weibull Probability Density Function (PDF) with two parameters is widely accepted and commonly utilized for modeling, characterizing and predicting wind resource and wind power, as well as assessing optimum performance of WECS. Therefore, it’s crucial to precisely estimate the scale and shape parameters for any candidate site. The statistical data of 28 years (1985-2013) wind speed measurements in the district of Kousseri were analyzed and the Weibull parameters determined. The performance of the proposed five methods was carried out based on the correlation coefficient R? and root mean square error (RMSE). The results established that the proposed five methods are effective in evaluating the parameters of the Weibull distribution for the available data. However, the most accurate models are the energy pattern factor method followed by the maximum likelihood method and the graphical method. The least precise models are the modified maximum likelihood method and the empirical method.