Statistical Evaluation of Wind Speed Distribution in Derna, Libya, Using Two Weibull Methods for Wind Energy Assessment

Abstract

Following the Hurricane Daniel disaster that struck the city of Derna, interest in reconstruction in the city increased, including renewable energy as a key supporter. This research paper examines wind data in Derna from a meteorological station that has monitored wind data over several years. Windographer software was used to analyze and visualize real wind resource data. Also, this paper It was derived the dimensionless parameters, which are the shape parameter k and the scale parameter C of the Weibull method to provide accurate and efficient estimation of energy output. Two numerical methods, the Maximum Likelihood Method (MLM) and the Least Squares Method (LSM), are examined to estimate the Weibull parameters. To analyze the efficiency of the methods and to ascertain how closely the measured data follow the Weibull methods, goodness of fit tests was performed using the chi-square test (χ2), correlation coefficient (R2), root mean square error (RMSE), and Relative percentage of error (RPE). The results revealed that the MLM was the most accurate and efficient method for determining the value of Weibull. In addition, the potential for wind energy development in Derna is fitted for generating electricity.