Influence of Sub-Daily Variation on Multi-Fractal Detrended Fluctuation Analysis of Wind Speed Time Series

Xianxun Wang; Yadong Mei; Weinan Li; Yanjun Kong; Xiangyu Cong

doi:10.1371/journal.pone.0146284

Influence of Sub-Daily Variation on Multi-Fractal Detrended Fluctuation Analysis of Wind Speed Time Series

PLoS One. 2016 Jan 7;11(1):e0146284. doi: 10.1371/journal.pone.0146284. eCollection 2016.

Authors

Xianxun Wang^{1

2}, Yadong Mei^{1

2}, Weinan Li^{1

2}, Yanjun Kong^{1

2}, Xiangyu Cong³

Affiliations

¹ State Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan, Hubei, China.
² Hubei Collaborative Innovation Center for Water Resources Security, Wuhan, Hubei, China.
³ POWERCHINA Kunming Engineering Corporation Limited, Kunming, Yunnan, China.

Abstract

Using multi-fractal detrended fluctuation analysis (MF-DFA), the scaling features of wind speed time series (WSTS) could be explored. In this paper, we discuss the influence of sub-daily variation, which is a natural feature of wind, in MF-DFA of WSTS. First, the choice of the lower bound of the segment length, a significant parameter of MF-DFA, was studied. The results of expanding the lower bound into sub-daily scope shows that an abrupt declination and discrepancy of scaling exponents is caused by the inability to keep the whole diel process of wind in one single segment. Additionally, the specific value, which is effected by the sub-daily feature of local meteo-climatic, might be different. Second, the intra-day temporal order of wind was shuffled to determine the impact of diel variation on scaling exponents of MF-DFA. The results illustrate that disregarding diel variation leads to errors in scaling. We propose that during the MF-DFA of WSTS, the segment length should be longer than 1 day and the diel variation of wind should be maintained to avoid abnormal phenomena and discrepancy in scaling exponents.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Electric Power Supplies
Fractals
Humans
Models, Statistical*
Power Plants
Renewable Energy*
Wind*

Grants and funding

This study was supported by the Major Program of National Natural Science Foundation of China, grant number: 51239004, (URLs: http://npd.nsfc.gov.cn/fundingProjectSearchAction.action), Recipient: Yadong Mei; and the Program of National Natural Science Foundation of China, grant number: 51479140 (URLs: http://npd.nsfc.gov.cn/fundingProjectSearchAction.action), Recipient: Yadong Mei. The funder provided support in experiment field and tools. The POWERCHINA Kunming Engineering Corporation Limited provided support in data collection. The funder and the commercial company did not have any additional role in the study design, data analysis, decision to publish, or preparation of the manuscript. The specific roles of the authors are articulated in the ‘author contributions’ section.