A novel energy pattern factor method for wind speed distribution parameter estimation

Abstract

Power output of wind turbine depends on many factors. Among them, the most crucial one is wind speed. Since wind speed data is a significant factor for wind energy analyses, it should be modeled accurately. Weibull distribution has been used extensively to model variation of wind speed. Therefore, the most appropriate distribution parameter estimation method selection is critical in order to minimize data set modeling errors. In this context, a novel, robust, efficient and better method than standard methods to estimate Weibull parameters is presented for the first time in this paper. The accuracy of the proposed method is verified using different data sets. Also, developed method is compared with Graphic Method (GM), Maximum Likelihood Method (MLM), Alternative Maximum Likelihood Method (AMLH), Modified Maximum Likelihood Method (MMLH), Moment Method (MM), Justus Moment Method (JMM), WAsP Method (WM) and Power Density Method (PD). The results indicate that the proposed novel method is adequate to determine Weibull distribution parameters.