Abstract
Understanding the inherent features of wind speed (variability on different time scales) has become critical for assured wind power availability, grid stability, and effective power management. The study utilizes the wavelet, autocorrelation, and FFT (fast Fourier transform) techniques to analyze and assimilate the fluctuating nature of wind speed data collected over a period of 29–42 years at different locations in the Kingdom of Saudi Arabia. The analyses extracted the intrinsic features of wind speed, including the long-term mean wind speed and fluctuations at different time scales (periods), which is critical for meteorological purposes including wind power resource assessment and weather forecasting. The long-term mean wind speed varied between 1.45 m/s at Mecca station and 3.73 m/s at Taif. The annual variation is the largest (±0.97 m/s) at Taif and the smallest (±0.25 m/s) at Mecca. Similarly, the wind speed fluctuation with different periods was also discussed in detail. The spectral characteristics obtained using FFT reveal that Al-Baha, Najran, Taif and Wadi-Al-Dawasser having a sharp peak at a frequency f = 0.00269 (1/day) retain a more regular annual repetition of wind speed than Bisha, Khamis-Mushait, Madinah, Mecca, and Sharourah. Based on the autocorrelation analysis and FFT results, the stations are divided into three groups: (i) having strong annual modulations (Al-Baha, Najran, Taif and Wadi-Al-Dawasser), (ii) having comparable annual and half-yearly modulations (Bisha, Khamis-Mushait, and Mecca) and (iii) having annual modulation moderately prominent (Madinah and Sharourah).
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Acknowledgements
The authors would like to acknowledge the support provided by the Deanship of Scientific Research (DSR) at King Fahd University of Petroleum & Minerals (KFUPM) for funding this work through Grant number IN151026.
The third author wishes to acknowledge the support given to him from the Research Grant Council of Shenzhen Government through Grant KQCX2014052114423867. The fourth author extends his appreciation to the Deanship of Scientific Research at King Saud University (Saudi Arabia) for funding part of the work through the international research group project no. IRG14–36.
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Appendix
Appendix
While the wavelet decomposition results of wind speed data for Al-Baha, Wadi-Al-Dawasser, Khamis-Mushait, Shrourah are illustrated before, those for Bishas, Madinah, Mecca, Najran, and Taif are presented in figures A1–A5.
Decomposition of wind speed time series data for Bisha using db8.
Decomposition of wind speed time series data for Madinah using db8.
Decomposition of wind speed time series data for Mecca using db8.
Decomposition of wind speed time series data for Najran using db8.
Decomposition of wind speed time series data for Taif using db8.
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Zheng, Q., Rehman, S., Alam, M.M. et al. Decomposition of wind speed fluctuations at different time scales. J Earth Syst Sci 126, 36 (2017). https://doi.org/10.1007/s12040-017-0816-0
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DOI: https://doi.org/10.1007/s12040-017-0816-0