Evidence of crossover phenomena in wind speed data
Rajesh G. Kavasseri, Radhakrishnan Nagarajan
Abstract
In this report, a systematic analysis of hourly wind speed data obtained from three potential wind generation sites (in North Dakota) is analyzed. The power spectra of the data exhibited a power-law decay characteristic of 1/fα processes with possible long-range correlations. Conventional analysis using Hurst exponent estimators proved to be inconclusive. Subsequent analysis using detrended fluctuation analysis (DFA) revealed a crossover in the scaling exponent (α). At short time scales, a scaling exponent of α 1.4 indicated that the data resembled Brownian noise, whereas for larger time scales the data exhibited long range correlations (α 0.7). The scaling exponents obtained were similar across the three locations. Our findings suggest the possibility of multiple scaling exponents characteristic of multifractal signals.
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