Using Fractal Dimension to Evaluate Wind Gusts Long-Term Persistence

The wind data persistence provides useful information about the climatological characteristics of a given location. Particularly, the wind gusts persistence should be taken into account in many studies such as site selection for wind turbines and synthetic generation of the wind gusts data. In this paper we examine the long-term persistence of daily wind gusts data with many years of record using the fractal dimension. The persistence measures the correlation between adjacent values within the time series. Values of a time series can affect other values in the time series that are not only nearby in time but also far away in time. For this purpose, an elaborated method to measure the fractal dimension of temporal discrete signals is presented. The fractal dimension is then used as criterion in the proposed approach to detect the long term correlation in wind gusts series. The results show that daily wind gusts are anti-persistent.