Abstract
Wind is an abundant, yet intermittent, source of renewable energy, with speeds changing both spatially and temporally over a wide range of time scales. While wind variability is well documented on large meteorological time scales and the behavior of turbulent flow at high frequencies is well understood, there remain questions in the literature regarding the intermediate region of these domains. Understanding wind variability at the microscale, here considering a frequency range of 10−2 Hz < f < 1 Hz, is key for wind turbine control and modeling. In this paper, we quantify the variability of wind conditions for the meteorological tower at the Eolos wind research station in Minnesota using power spectral density analysis. Spectral analysis of wind samples with similar mean wind speeds was conducted to test the hypothesis that the wind spectrum’s shape is independent of the mean wind speed. Historical wind speed data were compared and evaluated to identify diurnal, seasonal, and interannual trends in the spectrum of wind at frequencies above 10−3 Hz. We conclude that the shape of the wind spectrum is independent of the mean wind speed following the Kolmogorov −5/3 law for turbulent flows for incoming wind, with some variations in slope and spectrum magnitude. While no conclusive diurnal, seasonal, or interannual trends were observed, it is shown that some variations in both slope and spectrum magnitude can occur on these time scales.