Comparative study of wind gusts: detection techniques and terrain specific features

Abstract

In this research work, the phenomenon of extreme wind events or gusts has been studied in detail and different aspects related to the nature of gusts are explored.
In order to detect wind gusts from a stochastic time series different gust detection techniques collected from previous research works and literature studies were compiled, refined, verified and compared against each other. In addition some important insight is also given regarding the setting up of appropriate values for various gust defining parameters.
The gust detection techniques are developed into computational codes and applied over different data sets. A comparison between these techniques highlights the pros and cons of each one of them. The peak to peak method and the velocity increment method provides accurate information about the maximum wind speed acceleration within a small time interval. Other methods like peak over threshold and the acceleration over threshold methods are useful to detect specific type of wind gusts above a certain threshold.
Wind data sets sampled at high frequency resolution and from different geographical locations were obtained and analyzed through these gust detections algorithms. Among these locations are the offshore wind farm at Egmond aan Zee (OWEZ), IJmuiden and the Cabauw Experimental Site for Atmospheric Research (CESAR) which are a representative of a near offshore, far offshore and an onshore location respectively. By using a uniform gust threshold criteria for peak over threshold and acceleration over threshold methods, a comparison between different locations reveal that the maximum gusts were detected for IJmuiden which generally has higher wind speeds throughout the year.
For each location, the total number of gusts detected have been combined to obtain a mean gust shape. Furthermore, the maximum wind gusts are selected from each month and compared with the standard IEC gust shapes.
The available high resolution wind data is for a duration of 1 year only which is not sufficient for the prediction of a maximum 50 year gust. However two different approaches are discussed to demonstrate the procedure. A statistical approach involving the extrapolation of data to predict the amplitude of maximum 50 year gust highlights the need for the availability of long term wind data. The analytical approach involving the calculation of the return period of different gusts is also explained and the results presented within this report are promising to continue further research within this domain.
The techniques, findings and conclusions obtained through this research work can be further tested and eventually utilized to compliment or improve upon the existing extreme load cases of the wind turbine design standards.