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Taylor Law in Wind Energy Data

Author

Listed:
  • Rudy Calif

    (EA 4935, LARGE Laboratoire en Géosciences et Énergies, Université des Antilles, 97159 Pointe-à-Pitre, Guadeloupe, France)

  • François G. Schmitt

    (CNRS, UMR 8187 LOG Laboratoire d’Océanologie et de Géosciences, Université de Lille 1, 28 avenue Foch, Wimeureux 62930, France)

Abstract

The Taylor power law (or temporal fluctuation scaling), is a scaling relationship of the form σ ~ (P) λ where !! is the standard deviation and hPi the mean value of a sample of a time series has been observed for power output data sampled at 5 min and 1 s and from five wind farms and a single wind turbine, located at different places. Furthermore, an analogy with the turbulence field is performed, consequently allowing the establishment of a scaling relationship between the turbulent production IP and the mean value (P).

Suggested Citation

  • Rudy Calif & François G. Schmitt, 2015. "Taylor Law in Wind Energy Data," Resources, MDPI, vol. 4(4), pages 1-9, October.
    • Handle: RePEc:gam:jresou:v:4:y:2015:i:4:p:787-795:d:57875
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    References listed on IDEAS

    as
    1. Youngki Lee & Luis A. N. Amaral & David Canning & Martin Meyer & H. Eugene Stanley, 1998. "Universal features in the growth dynamics of complex organizations," Papers cond-mat/9804100, arXiv.org.
    2. Šuvakov, Milovan & Tadić, Bosiljka, 2006. "Transport processes on homogeneous planar graphs with scale-free loops," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 372(2), pages 354-361.
    3. Calif, Rudy & Schmitt, François G. & Huang, Yongxiang, 2013. "Multifractal description of wind power fluctuations using arbitrary order Hilbert spectral analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4106-4120.
    4. Timothy H. Keitt & H. Eugene Stanley, 1998. "Dynamics of North American breeding bird populations," Nature, Nature, vol. 393(6682), pages 257-260, May.
    5. Zoltan Eisler & Janos Kertesz, 2005. "Scaling theory of temporal correlations and size dependent fluctuations in the traded value of stocks," Papers physics/0510058, arXiv.org, revised May 2006.
    6. Calif, Rudy & Emilion, Richard & Soubdhan, Ted, 2011. "Classification of wind speed distributions using a mixture of Dirichlet distributions," Renewable Energy, Elsevier, vol. 36(11), pages 3091-3097.
    7. Zhi-Qiang Jiang & Liang Guo & Wei-Xing Zhou, 2007. "Endogenous and exogenous dynamics in the fluctuations of capital fluxes: An empirical analysis of the Chinese stock market," Papers physics/0702035, arXiv.org.
    8. Dahlstedt, Kajsa & Jensen, Henrik Jeldtoft, 2005. "Fluctuation spectrum and size scaling of river flow and level," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 596-610.
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