Brazilian wind energy generation potential using mixtures of Weibull distributions

dos Santos, Fábio Sandro; do Nascimento, Kerolly Kedma Felix; da Silva Jale, Jader; Xavier, Sílvio Fernando Alves; Ferreira, Tiago A.E.

doi:10.1016/j.rser.2023.113990

Cited by 12 publications

(1 citation statement)

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“…In order to address this challenge, wind potential forecasting and estimation algorithms are used frequently. So far, the most accurate and robust technique used to analyze the wind energy potential of a site is the Weibull model of wind energy [5].…”

Section: Introductionmentioning

confidence: 99%

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

Ali,

Park,

Noon

et al. 2024

Energies

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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.

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Section: Introductionmentioning

confidence: 99%