FREQUENCY DOMAIN ANALYSIS FOR STATISTICAL ASSESSMENT OF WIND RESOURCES

被引:0
作者
Little, M. L. [1 ]
Pope, K. [2 ]
机构
[1] Mem Univ Newfoundland, Dept Elect Engn, 240 Prince Phillip Dr, St John, NF, Canada
[2] Mem Univ Newfoundland, Dept Mech Engn, 240 Prince Phillip Dr, St John, NF, Canada
来源
2016 IEEE CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (CCECE) | 2016年
关键词
Wind Velocity Analysis; Wind Turbines; Wind Turbine Performance Modeling; Frequency Domain Analysis; POWER; SYSTEM;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper, frequency domain analysis with a discrete-time Fourier transform is applied to wind velocity data to study the frequency distribution of wind-regime variability. Seasonal and diurnal trends are identified with a logarithmic-window recursive filtering algorithm and probability density residual analysis. The remaining spectrum is shown to approximate a piecewise linear summation of pink, white and Kolmogorov band-limited noise signals. The largest variance contribution is Kolmogorov turbulence. The spectrum elements are reconstructed into a time-domain signal and analyzed for probability density modeling and envelope detection through Hilbert transform. The magnitude and distribution of wind velocity variance is strongly correlated with the frequency spectrum, indicating frequency domain analysis as a promising method for wind turbine performance modeling and design of hybrid wind power systems.
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页数:5
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