Comparison of Weibull Estimation Methods for Diverse Winds

Abstract

<jats:p>Wind farm siting relies on in situ measurements and statistical analysis of the wind distribution. The current statistical methods include distribution functions. The one that is known to provide the best fit to the nature of the wind is the Weibull distribution function. It is relatively straightforward to parameterize wind resources with the Weibull function if the distribution fits what the function represents but the estimation process gets complicated if the distribution of the wind is diverse in terms of speed and direction. In this study, data from a 101 m meteorological mast were used to test several estimation methods. The available data display seasonal variations, with low wind speeds in different seasons and effects of a moderately complex surrounding. The results show that the maximum likelihood method is much more successful than industry standard WAsP method when the diverse winds with high percentile of low wind speed occur.</jats:p>

Rüzgar hız dağılımı modelinin Yusufcuk algoritması ile parametre tahminlemesi

“…12 ile ve standart sapma Eş. 13 ile hesaplanmaktadır [22]. Weibull dağılım parametreleri iteratif tekniklerle ortalama hız ve standart sapma kullanılarak elde edilmektedir.…”

Assessment of wind energy potential and characteristics in Qatar for clean electricity generation

“…To determine these parameters, diverse methods could be implemented, such as wind variability, standard deviation, power density, Moroccan method, Weibull probability density function, and so on (El Khchine et al, 2019). In the present study, these parameters are calculated by implementing the WAsP method; this technique employs an iterative approach to calculate k via equation (1) followed by the use of such result in equation ( 2) to obtain A (Bingo¨l, 2020). ln…”

Coastal Wind Power in Southern Santa Catarina, Brazil

“…The Maximum Likelihood Method (MLM) [36,37] was employed to estimate the k and c Weibull parameters for all the BOOA observations. The MLM has proven to achieve a very good performance compared with other methods employed for the two-parameter estimation [38][39][40].…”

“…The results of U, D p , c, and k from Dalmaz (2007) [15] are reproduced in Table 5 and Figures 8 and 9. Dalmaz (2007) employed the two-parameter Weibull distribution and estimated c and k by means of the so-called power density or energy pattern factor method [39,40,65,66]. Table 5 also shows the percentages and periods of data coverage.…”