Critical evaluation of wind speed frequency distribution functions

2010 ◽  
Vol 2 (1) ◽  
pp. 013102 ◽  
Author(s):  
A. N. Celik ◽  
A. Makkawi ◽  
T. Muneer
Keyword(s):  
Wind Speed ◽  
Frequency Distribution ◽  
Critical Evaluation ◽  
Distribution Functions

scholarly journals Mixture probability distribution functions using novel metaheuristic method in wind speed modeling

2021 ◽  
Author(s):  
Amr Khaled Khamees ◽  
Almoataz Y. Abdelaziz ◽  
Ziad M. Ali ◽  
Mosleh M. Alharthi ◽  
Sherif S.M. Ghoneim ◽  
...  
Keyword(s):  
Wind Speed ◽  
Probability Distribution ◽  
Distribution Functions ◽  
Probability Distribution Functions

scholarly journals Frequency Distribution Model of Wind Speed Based on the Exponential Polynomial for Wind Farms

2019 ◽  
Vol 11 (3) ◽  
pp. 665 ◽  
Author(s):  
Lingzhi Wang ◽  
Jun Liu ◽  
Fucai Qian
Keyword(s):  
Wind Speed ◽  
Frequency Distribution ◽  
Least Squares Method ◽  
Wind Farms ◽  
Rayleigh Distribution ◽  
Distribution Model ◽  
Exponential Polynomial ◽  
Distribution Models ◽  
Wind Speed Data ◽  
Wind Speeds

This study introduces and analyses existing models of wind speed frequency distribution in wind farms, such as the Weibull distribution model, the Rayleigh distribution model, and the lognormal distribution model. Inspired by the shortcomings of these models, we propose a distribution model based on an exponential polynomial, which can describe the actual wind speed frequency distribution. The fitting error of other common distribution models is too large at zero or low wind speeds. The proposed model can solve this problem. The exponential polynomial distribution model can fit multimodal distribution wind speed data as well as unimodal distribution wind speed data. We used the linear-least-squares method to acquire the parameters for the distribution model. Finally, we carried out contrast simulation experiments to validate the effectiveness and advantages of the proposed distribution model.

The Development of Estimators for the Peaks-Over-Threshold Method

2002 ◽  
Author(s):  
A. Naess ◽  
P. H. Clausen
Keyword(s):  
Wind Speed ◽  
Synthetic Data ◽  
Distribution Functions ◽  
Statistical Distribution ◽  
Peaks Over Threshold ◽  
Threshold Method

The paper discusses the accuracy and efficiency of some of the standard estimators used in conjunction with the Peaks-Over-Threshold (POT) method. A comparison is made between some commonly adopted estimators and two types of estimators proposed by the authors. The comparison is based on an extensive set of synthetic data simulated from a range of different statistical distribution functions that have been assumed to describe wind speed processes.

Reliability analysis of a telecommunication tower

1999 ◽  
Vol 26 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Kamal El-Fashny ◽  
Luc E Chouinard ◽  
Ghyslaine McClure
Keyword(s):  
Wind Speed ◽  
Probability Distribution ◽  
Reliability Analysis ◽  
Structural Reliability ◽  
Joint Probability ◽  
Distribution Functions ◽  
Sensitivity Analyses ◽  
Ice Thickness ◽  
Joint Probability Distribution ◽  
Type I

This study presents a structural reliability analysis of a microwave tower subject to wind and freezing-rain hazards. The tower (name code CEBJ, owned by Hydro-Québec) is a 66 m tall, three-legged, steel lattice structure located in the James Bay area. The reliability analysis is performed conditionally with respect to wind speed and ice thickness accretion, and the results are integrated over the domain of wind and ice values using their joint probability distribution. This approach makes it possible to perform sensitivity analyses with respect to various assumptions on the joint probability distribution function of the climatological variable, without having to repeat the detailed coupled reliability - structural analysis of the tower. The probability distribution functions assumed for the wind speed and the ice thickness accretion on the tower members are both extreme-value type I (Gumbel) distributions. Adopting a weakest link model, the failure of the tower is assumed to occur when any of the members fails either in tension, compression, or global buckling. Without loss of generality, the proposed procedure can be applied with more refined probability distribution functions.Key words: reliability, telecommunication towers, wind, ice.

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