An optimal approach of wind power assessment using Chebyshev metric for determining the Weibull distribution parameters

Abstract Statistical distribution methods have been used to estimate the wind power potential (WPP) at several locations globally. Although two-parameter Weibull distribution (WD) is considered to be the most appropriate method for wind data representation, the accuracy of the numerical methods used for Weibull parameter estimation (WPE) is still inconsistent. In this context, artificial intelligence (AI) optimization techniques can be a useful tool for achieving high accuracy; however, the conventional approaches do not guarantee convergence in the case of Weibull parameters. In this work, an AI optimization approach is proposed based on the Chebyshev metric. It has been mathematically proved that the proposed method guarantees convergence in all cases of WPE. Weibull Fitness tests are computed using real-time wind data obtained from a site located near the coastal region of Pakistan. Results show that the proposed approach offers more accuracy than the numerical methods used for WPE. Furthermore, a brief cost analysis illustrates that the considered site is appropriate for wind power production.