Method of Four Moments Mixture-A new approach for parametric estimation of Weibull Probability Distribution for wind potential estimation applications

Cutting down the reliance on fossil fuels and utilization of wind energy as green energy source requires detailed resource exploration using some probability distribution. In contrast to literature methods which are based on first and second moment of Weibull Probability Distribution (WPD) for its parametric estimation, the new method proposed in this study (called Method of Four Moments Mixture, MFMM) combines the effect of first four moments of WPD. This model is based on the squared deviation (deviation of sample from population) of first four moments; minimization of which using Nelder-Mead algorithm estimates parameters of WPD. In order to assess its comprehensive effectiveness, this method has been validated using large dataset i.e. five years wind data measured at 50 m height for thirty-six stations (in Pakistan) for parametric estimation and it has been compared with six past methods using MAPE, RMSE and R-2. To rank all seven methods, Global Performance Indicator (GPI) was evaluated and it was found that MFMM is the best method for all stations. Therefore, it can be effectively used in wind resource assessment of various geographical regions in the world. (C) 2022 Elsevier Ltd. All rights reserved.

Automated summary

A new method for wind resource assessment based on the squared deviation of the first four moments of the Weibull Probability Distribution (WPD) is proposed in this study. The method is validated using a large dataset and found to be the best among all stations, making it suitable for wind resource assessment in different geographical regions worldwide.