Accuracy Testing of Different Methods for Estimating Weibull Parameters of Wind Energy at Various Heights above Sea Level

Sajid Ali, Hongbae Park, Adnan Aslam Noon, Aamer Sharif and Daeyong Lee ()
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Sajid Ali: Energy Innovation Research Center for Wind Turbine Support Structures, Kunsan National University, 558 Daehak-ro, Gunsan-si 54150, Jeollabuk-do, Republic of Korea
Hongbae Park: Department of Wind Energy, The Graduate School of Kunsan National University, 558 Daehak-ro, Gunsan-si 54150, Jeollabuk-do, Republic of Korea
Adnan Aslam Noon: Department of Mechanical Engineering, FET, International Islamic University, Islamabad 44000, Pakistan
Aamer Sharif: School of Engineering, Edith Cowan University, Joondalup, Perth 6027, Australia
Daeyong Lee: Department of Wind Energy, The Graduate School of Kunsan National University, 558 Daehak-ro, Gunsan-si 54150, Jeollabuk-do, Republic of Korea

Energies, 2024, vol. 17, issue 9, 1-19

Abstract: The Weibull algorithm is one of the most accurate tools for forecasting and estimating wind energy potential. Two main parameters of the Weibull algorithm are the ‘Weibull shape’ and ‘Weibull scale’ factors. There are six different numerical methods to estimate the two Weibull parameters. These six methods are the empirical method of Justus (method 1), the empirical method of Lysen (method 2), the maximum likelihood method (method 3), the modified maximum likelihood method (method 4), the energy pattern factor method (method 5) and the graphical method (method 6). Many commercial wind energy software programs use the Weibull algorithm, and these six methods are used to calculate the potential wind energy at a given site. However, their accuracy is rarely discussed, particularly regarding wind data height. For this purpose, wind data measured for a long period (six years) at real sites are introduced. The wind data sites are categorized into three levels, i.e., low, medium, and high, based on wind data measurement height. The analysis shows that methods 1 and 2 are the most accurate methods among all six methods at low and medium heights. The number of errors increases with the height of these two methods. Methods 3 and 4 are the most suitable options for larger heights, as these scenarios have minimal error. The present study’s findings can be used in various fields, e.g., wind energy forecasting and wind farm planning.

Keywords: wind data height; forecasting; error and accuracy; Weibull methods; measured data (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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