Height-dependence of the temporal variability of wind speed : a multiscale approach

Abstract

Climate change and diminishing fossil fuel reserves have contributed to the increasing need for alternative renewable energy resources. Wind power is particularly attractive as it is both renewable and abundant. However, the spatial and temporal variability of wind makes power production intermittent, which affects the feasibility of large-scale implementation. Using statistical moments and multiscale analysis, this project intends to characterize wind speed variability as a function of height and to deepen wind variability understanding. Detrended Fluctuation Analysis (DFA) is a multiscale analysis method which is capable of assessing time series variability based on the scaling relationship between time scale and the average size of the fluctuations in the time series, thereby taking into consideration the temporal succession of time series values. By applying the coefficient of variation and DFA through three consecutive years and at 6 successive heights, a relationship can be identified between wind speed variability and height. This study found that wind speed variability consistently decreases with height up to a certain height. Beyond this height, wind speed variability was found to decrease at a more gradual rate or not at all. This was confirmed both through statistical moments and multiscale analysis. The outcomes of this project have implications for the methodology used to assess potential locations of wind turbines, as well as for studies regarding turbine design.