风电场风速时间序列的多重分形去趋势波动分析

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Abstract In order to detect the scale qualities of wind speed time series, the wind speed time series are analyzed by multi-fractal detrended fluctuation analysis(MF-DFA) method. Detailed quantitative the volatility singularity of partial and different levels of the wind speed time series are calculated by the generalized Hurst index, scaling function and multi-fractal spectrum, and the effects of multi-fractal parameters on wind speed prediction are considered. The analysis results show that fluctuation of wind speed time series have log-range correlation and significant multi-fractal characteristics. The multi-fractal parameters associated with the change of wind speed, to some degree, can be predicted by multi-fractal spectrums, and the prediction becomes more accurate with the more fluctuation of the wind speed.

Key words： Wind farm wind speed detrended fluctuation analysis multi-fractal

Received: 16 August 2012 Published: 05 November 2014

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TM614

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	Sun Bin
	Yao Haitao

Cite this article:

Sun Bin,Yao Haitao. Multi-fractal Detrended Fluctuation Analysis of Wind Speed Time Series in Wind Farm[J]. Transactions of China Electrotechnical Society, 2014, 29(6): 204-210.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2014/V29/I6/204

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