Statistical study and evaluation of six numerical methodes to predict wind speed parameters of the Weibull function in Al- Aziziyah, Libya

Abstract

Wind turbines depend on several factors to produce energy, and the most important of these factors is wind speed. As wind speed data is a major factor in the study of wind power, it should be accurately modeled. This work provides a comparative evaluation of six methods for computing the Weibull parameters for Al-Aziziyah city- Libya located 32.18 latitude (No) 13.03 longitude (Eo). Ten minutes average wind speed has been collected within the period of twenty five months for three different height 10m, 20m and 40m using data logger EKO 21B. Graphical method (GM), Empirical method of Justus (EMJ), Energy Pattern Factor (EPF) method, Empirical method of Lysen (EML), Maximum Likelihood Method (MLM) and the Modified Maximum Likelihood Method (MMLM) are the methods used. Those methods are assessed using statically indicators Mean Absolute Error (MAE), Root Mean Square Error (RMES), Coefficient of determination (R2) and Chi-Square Test (χ2). The analysis shows that The MMLM and MLM are the most accurate methods respectively for evaluating Weibull distribution parameters for the study region while (GM) and (EML) gives lower results.