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Multiparametric statistical and dynamical analysis of angular high-frequency wind speed time series

Author

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  • Stosic, Tatijana
  • Telesca, Luciano
  • Stosic, Borko

Abstract

High frequency data from the city of Petrolina, Northeast Brazil, are used to find the wind speed projection series at different angles, which are then analyzed by using several statistical tools: detrended fluctuation analysis (DFA), multifractal detrended fluctuation analysis (MFDFA) and Fisher–Shannon analysis (FSA). It is found that α, the DFA scaling exponent, varies between 0.6 (indicating weak persistence) and unity (strong persistence), at different time frames and at different projection angles. At lower projection angles wind speed is characterized by higher heterogeneity, lower disorder, higher organization and relative dominance of small fluctuations. The statistical analysis of wind speed with varying the direction could contribute to enrich the knowledge of the dynamics of wind speed.

Suggested Citation

  • Stosic, Tatijana & Telesca, Luciano & Stosic, Borko, 2021. "Multiparametric statistical and dynamical analysis of angular high-frequency wind speed time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    • Handle: RePEc:eee:phsmap:v:566:y:2021:i:c:s0378437120309250
    DOI: 10.1016/j.physa.2020.125627
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    References listed on IDEAS

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    1. Ray Huffaker & Marco Bittelli, 2015. "A Nonlinear Dynamics Approach for Incorporating Wind-Speed Patterns into Wind-Power Project Evaluation," PLOS ONE, Public Library of Science, vol. 10(1), pages 1-17, January.
    2. de Oliveira Santos, Maíra & Stosic, Tatijana & Stosic, Borko D., 2012. "Long-term correlations in hourly wind speed records in Pernambuco, Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1546-1552.
    3. Fengzhong Wang & Shwu-Jane Shieh & Shlomo Havlin & H. Eugene Stanley, 2009. "Statistical analysis of the overnight and daytime return," Papers 0903.0993, arXiv.org.
    4. Stanley, H.E. & Amaral, L.A.N. & Goldberger, A.L. & Havlin, S. & Ivanov, P.Ch. & Peng, C.-K., 1999. "Statistical physics and physiology: Monofractal and multifractal approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 270(1), pages 309-324.
    5. Kavasseri, Rajesh G. & Nagarajan, Radhakrishnan, 2005. "A multifractal description of wind speed records," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 165-173.
    6. Pierini, Jorge O. & Lovallo, Michele & Telesca, Luciano, 2012. "Visibility graph analysis of wind speed records measured in central Argentina," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 5041-5048.
    7. Telesca, Luciano & Lovallo, Michele, 2017. "On the performance of Fisher Information Measure and Shannon entropy estimators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 569-576.
    8. Laib, Mohamed & Golay, Jean & Telesca, Luciano & Kanevski, Mikhail, 2018. "Multifractal analysis of the time series of daily means of wind speed in complex regions," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 118-127.
    9. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    10. Telesca, Luciano & Lovallo, Michele & Hsu, Han-Lun & Chen, Chien-Chih, 2011. "Analysis of dynamics in magnetotelluric data by using the Fisher–Shannon method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1350-1355.
    11. Fernando Porté-Agel & Yu-Ting Wu & Chang-Hung Chen, 2013. "A Numerical Study of the Effects of Wind Direction on Turbine Wakes and Power Losses in a Large Wind Farm," Energies, MDPI, vol. 6(10), pages 1-17, October.
    12. Jung, Christopher & Schindler, Dirk, 2019. "Wind speed distribution selection – A review of recent development and progress," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    13. Drisya, G.V. & Asokan, K. & Kumar, K. Satheesh, 2018. "Diverse dynamical characteristics across the frequency spectrum of wind speed fluctuations," Renewable Energy, Elsevier, vol. 119(C), pages 540-550.
    14. Chang, Tian-Pau & Ko, Hong-Hsi & Liu, Feng-Jiao & Chen, Pai-Hsun & Chang, Ying-Pin & Liang, Ying-Hsin & Jang, Horng-Yuan & Lin, Tsung-Chi & Chen, Yi-Hwa, 2012. "Fractal dimension of wind speed time series," Applied Energy, Elsevier, vol. 93(C), pages 742-749.
    15. Li, Xudong & Telesca, Luciano & Lovallo, Michele & Xu, Xuan & Zhang, Jun & Song, Weiguo, 2020. "Spectral and informational analysis of pedestrian contact force in simulated overcrowding conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    16. Guignard, Fabian & Lovallo, Michele & Laib, Mohamed & Golay, Jean & Kanevski, Mikhail & Helbig, Nora & Telesca, Luciano, 2019. "Investigating the time dynamics of wind speed in complex terrains by using the Fisher–Shannon method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 611-621.
    17. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2019. "Multifractal behavior of price and volume changes in the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 54-61.
    18. Santos, J.V.C. & Moreira, D.M. & Moret, M.A. & Nascimento, E.G.S., 2019. "Analysis of long-range correlations of wind speed in different regions of Bahia and the Abrolhos Archipelago, Brazil," Energy, Elsevier, vol. 167(C), pages 680-687.
    19. Zunino, L. & Tabak, B.M. & Figliola, A. & Pérez, D.G. & Garavaglia, M. & Rosso, O.A., 2008. "A multifractal approach for stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6558-6566.
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    Cited by:

    1. Perini de Souza, Noéle Bissoli & Cardoso dos Santos, José Vicente & Sperandio Nascimento, Erick Giovani & Bandeira Santos, Alex Alisson & Moreira, Davidson Martins, 2022. "Long-range correlations of the wind speed in a northeast region of Brazil," Energy, Elsevier, vol. 243(C).
    2. Santos, E.C.O. & Guedes, E.F. & Zebende, G.F. & da Silva Filho, A.M., 2022. "Autocorrelation of wind speed: A sliding window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).

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