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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摘要为探索风电场风速时间序列的标度不变性,采用多重分形去趋势波动分析方法（MF-DFA）对风速时间序列进行分析。通过计算广义Hurst指数、尺度函数、多重分形谱,细致量化了风速序列的局部和不同层次的波动奇异性,并考察了多重分形参数对风速预测的影响。研究结果表明：风速时间序列的波动具有长程相关性,且呈现显著多重分形特征;多重分形参数与风速变化存在一定的关联性,采用多重分形谱可在一定程度上对风速的变化趋势进行预测,且风速波动量越大,预测的结果越准确。

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	孙斌
	姚海涛

关键词 ：风电场, 风速, 去趋势波动分析, 多重分形

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

收稿日期: 2012-08-16 出版日期: 2014-11-05

PACS:

TM614

基金资助:中国电机工程学会电力青年科技创新项目(201002)资助

作者简介: 孙斌男,1972年生,博士,教授,研究方向为时间序列预测控制。姚海涛男,1988年生,硕士研究生,研究方向为风电场风速预测算法。

引用本文:

孙斌, 姚海涛. 风电场风速时间序列的多重分形去趋势波动分析[J]. 电工技术学报, 2014, 29(6): 204-210. Sun Bin , Yao Haitao. Multi-fractal Detrended Fluctuation Analysis of Wind Speed Time Series in Wind Farm. Transactions of China Electrotechnical Society, 2014, 29(6): 204-210.

链接本文:

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

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