期刊
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
卷 392, 期 18, 页码 4106-4120出版社
ELSEVIER
DOI: 10.1016/j.physa.2013.04.038
关键词
Wind farm; Intermittency; Multifractal analysis; Empirical mode decomposition; Hilbert spectral analysis; Multifractal random walk
资金
- Regional Council of Guadeloupe, European funding [1/1.41-31614]
- National Natural Science Foundation of China [11072139]
- Regional Council of Guadeloupe, European funding [1/1.41-31614]
- National Natural Science Foundation of China [11072139]
The objectives are to study and model the aggregate wind power fluctuations dynamics in the multifractal framework. We present here the analysis of aggregate power output sampled at 1 Hz during three years. We decompose the data into several Intrinsic Mode Functions (IMFs) using Empirical Mode Decomposition (EMD). We use a new approach, arbitrary order Hilbert spectral analysis, a combination of the EMD approach with Hilbert spectral analysis (or Hilbert Huang Transform) and the classical structure-function analysis to extract the scaling exponents or multifractal spectrum zeta(q): this function provides a full characterization of a process at all intensities and all scales. The application of both methods, i.e. structure-function and arbitrary-order Hilbert spectral analyses, gives similar results indicating that the aggregate power output from a wind farm, possesses intermittent and multifractal properties. In order to check this result, we generate stochastic simulations of a Multifractal Random Walk (MRW) using a log-normal stochastic equation. We show that the simulation results are fully compatible with the experimental results. (C) 2013 Elsevier B.V. All rights reserved.
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