title: Influence of Sub-Daily Variation on Multi-Fractal Detrended Fluctuation Analysis of Wind Speed Time Series.
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.
authors.affiliation: State Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan, Hubei, China.|Hubei Collaborative Innovation Center for Water Resources Security, Wuhan, Hubei, China.
authors.forename: Xianxun
authors.initials: X
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan, Hubei, China.|Hubei Collaborative Innovation Center for Water Resources Security, Wuhan, Hubei, China.
authors.forename: Yadong
authors.initials: Y
authors.lastname: Mei
authors.affiliation: State Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan, Hubei, China.|Hubei Collaborative Innovation Center for Water Resources Security, Wuhan, Hubei, China.
authors.forename: Weinan
authors.initials: W
authors.lastname: Li
authors.affiliation: State Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan, Hubei, China.|Hubei Collaborative Innovation Center for Water Resources Security, Wuhan, Hubei, China.
authors.forename: Yanjun
authors.initials: Y
authors.lastname: Kong
authors.affiliation: POWERCHINA Kunming Engineering Corporation Limited, Kunming, Yunnan, China.
authors.forename: Xiangyu
authors.initials: X
authors.lastname: Cong
mesh_terms: D011211:Electric Power Supplies; D017709:Fractals; D006801:Humans; D015233:Models, Statistical; D011210:Power Plants; D059205:Renewable Energy; D014919:Wind