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Evidence of crossover phenomena in wind-speed data

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2 Author(s)
Kavasseri, R.G. ; Dept. of Electr. & Comput. Eng., North Dakota State Univ., Fargo, ND, USA ; Nagarajan, R.

In this paper, 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 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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Circuits and Systems I: Regular Papers, IEEE Transactions on  (Volume:51 ,  Issue: 11 )