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

• Published in: E3S web of conferences Vol. 529; p. 2009
• Main Authors: K, Kannakumar, M K, Murthi, G, Ravivarman, Babu D, Magesh, Babu Loganathan, Ganesh, R, Karthikeyan, R, Girimurugan
• Format: Journal Article
• Language: English
• Published: EDP Sciences 2024
• Subjects: era 5; rayleigh; rmse; weibull distribution; wind energy
• ISSN: 2267-1242; 2267-1242
• DOI: 10.1051/e3sconf/202452902009

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.