Wind speed time series characterization by Hilbert transform

S. Alpay, L. Bilir, S. Ozdemir, B. Ozerdem

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


Predictions of wind energy potential in a given region are based on on-location observations. The time series of these observations would later be analysed and modelled either by a probability density function (pdf) such as a Weibull curve to represent the data or recently by soft computing techniques, such as neural networks (NNs). In this paper, discrete Hilbert transform has been applied to characterize the wind sample data measured on İzmir Institute of Technology campus area which is located in Urla, İzmir, Turkey, in March 2001 and 2002. By applying discrete Hilbert transform filter, the instantaneous amplitude, phase and frequency are found, and characterization of wind speed is accomplished. Authors have also tried to estimate the hourly wind data using daily sequence by Hilbert transform technique. Results are varying.
Original languageEnglish
Pages (from-to)359-364
Number of pages6
JournalInternational Journal of Energy Research
Issue number5
Early online date15 Nov 2005
Publication statusPublished - 1 Apr 2006


  • discrete Hilbert transform
  • wind speed estimation
  • wind speed characterization
  • wind speed time series


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