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Power spectrum and multifractal detrended fluctuation analysis of high-frequency wind measurements in mountainous regions

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  • Telesca, Luciano
  • Lovallo, Michele
  • Kanevski, Mikhail

Abstract

The main objective of the study was to investigate the temporal features of the wind speed in complex mountainous terrains that are important for the assessment and development of wind energy. Six high-frequency records of 10-min averages of wind speed measured in Switzerland are investigated in order to better characterize their inner time dynamics. All the wind speed time series are modulated by components periods of 1day and 12h, linked with the temperature and pressure daily variation due to the sunset and sunrise. Furthermore the time dynamics of the wind speed is characterized by the presence of two different timescale ranges, separated by a crossover at about 7days: persistent and multifractal at larger timescales and antipersistent and monofractal (or weakly multifractal) at smaller ones. The found features do not seem to depend on the altitude, because all the wind speed series share the same dynamical characteristics. The results of this comprehensive study can be utilized to better understand the mechanisms governing the time dynamics of wind speed and to perform a better wind energy assessment and management.

Suggested Citation

  • Telesca, Luciano & Lovallo, Michele & Kanevski, Mikhail, 2016. "Power spectrum and multifractal detrended fluctuation analysis of high-frequency wind measurements in mountainous regions," Applied Energy, Elsevier, vol. 162(C), pages 1052-1061.
    • Handle: RePEc:eee:appene:v:162:y:2016:i:c:p:1052-1061
    DOI: 10.1016/j.apenergy.2015.10.187
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    1. 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.
    2. Astolfi, Davide & Castellani, Francesco & Garinei, Alberto & Terzi, Ludovico, 2015. "Data mining techniques for performance analysis of onshore wind farms," Applied Energy, Elsevier, vol. 148(C), pages 220-233.
    3. Shipkovs, Peteris & Bezrukov, Valery & Pugachev, Vladislav & Bezrukovs, Vladislavs & Silutins, Vladimirs, 2013. "Research of the wind energy resource distribution in the Baltic region," Renewable Energy, Elsevier, vol. 49(C), pages 119-123.
    4. Kavasseri, Rajesh G. & Nagarajan, Radhakrishnan, 2005. "A multifractal description of wind speed records," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 165-173.
    5. Chang, Tian Pau, 2011. "Performance comparison of six numerical methods in estimating Weibull parameters for wind energy application," Applied Energy, Elsevier, vol. 88(1), pages 272-282, January.
    6. Li, Gong & Shi, Jing, 2010. "On comparing three artificial neural networks for wind speed forecasting," Applied Energy, Elsevier, vol. 87(7), pages 2313-2320, July.
    7. 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.
    8. Juan Luis Lopez & Jesus Guillermo Contreras, 2013. "Performance of multifractal detrended fluctuation analysis on short time series," Papers 1311.2278, arXiv.org.
    9. Stanley, H.E. & Afanasyev, V. & Amaral, L.A.N. & Buldyrev, S.V. & Goldberger, A.L. & Havlin, S. & Leschhorn, H. & Maass, P. & Mantegna, R.N. & Peng, C.-K. & Prince, P.A. & Salinger, M.A. & Stanley, M., 1996. "Anomalous fluctuations in the dynamics of complex systems: from DNA and physiology to econophysics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 224(1), pages 302-321.
    10. Shu, Z.R. & Li, Q.S. & Chan, P.W., 2015. "Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function," Applied Energy, Elsevier, vol. 156(C), pages 362-373.
    11. 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.
    12. De Giorgi, Maria Grazia & Ficarella, Antonio & Tarantino, Marco, 2011. "Error analysis of short term wind power prediction models," Applied Energy, Elsevier, vol. 88(4), pages 1298-1311, April.
    13. Douak, Fouzi & Melgani, Farid & Benoudjit, Nabil, 2013. "Kernel ridge regression with active learning for wind speed prediction," Applied Energy, Elsevier, vol. 103(C), pages 328-340.
    14. Plamen Ch. Ivanov & Luís A. Nunes Amaral & Ary L. Goldberger & Shlomo Havlin & Michael G. Rosenblum & Zbigniew R. Struzik & H. Eugene Stanley, 1999. "Multifractality in human heartbeat dynamics," Nature, Nature, vol. 399(6735), pages 461-465, June.
    Full references (including those not matched with items on IDEAS)

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