Enhancing Wind Energy Potential Assessment with Three-Parameter Weibull Distribution: A Comparative Analysis using MATLAB

¹ Department of Mechanical Engineering, Shree Venkateshwara Hi-Tech Engineering College, Gobichettipalayam 638 455, Tamilnadu, India
² Department of Mechanical Engineering, Nandha Engineering College, Perundurai 638 052, Tamilnadu, India
³ Department of Electrical and Electronics Engineering, Karpagam Academy of Higher Education, Coimbatore 641 021, Tamilnadu, India
⁴ Department of Mechatronics Engineering, Velammal Institute of Technology, Panjetty 601 204, Tamilnadu, India
⁵ Department of Robotics and Automation, Rajalakshmi Engineering College, Chennai 602 105, Tamilnadu, India
⁶ Department of Automobile Engineering, Rajalakshmi Engineering College, Chennai 602 105, Tamilnadu, India
⁷ Department of Mechanical Engineering, Nandha College of Technology, Perundurai 638 052, Tamilnadu, India

^* Corresponding author: dr.r.girimurugan@gmail.com

Abstract

To determine the wind energy potential, the probability density function is typically used. For data distribution with modest wind speeds, this paper developed a three-parameter Weibull model. The distribution factors were determined using the maximal likelihood technique. The world renowned, user-friendly programming language Matrix Laboratory (MATLAB) processes all data that needs analysis. A comparison was made between the 3-factor Weibull, the 2-factor Weibull, and Rayleigh through R2 and root mean square error (RMSE). The ECMWF Reanalysis v5 (ERA 5) reanalysis's hourly wind speeds are statistically represented by these three distributions. Due to its placement between the optimal R2 and RMSE, the three-parameter Weibull model achieves good results. Weibull with three parameters has a R2 of 0.9898, Weibull with two parameters has a R2 of 0.9886, and Rayleigh has a R2 of 0.5162. The root-mean-squared errors (RMSEs) for Rayleigh, 2-factor and 3-factor Weibull, are 0.0082 and 0.0070, respectively.