A Comparison of Alternative Approaches for the Synthetic Generation of a Wind Speed Time Series

[+] Author and Article Information
F. C. Kaminsky, R. H. Kirchhoff, C. Y. Syu, J. F. Manwell

College of Engineering, University of Massachusetts, Amherst, MA 01003

J. Sol. Energy Eng 113(4), 280-289 (Nov 01, 1991) (10 pages) doi:10.1115/1.2929974 History: Received March 01, 1990; Revised May 20, 1991; Online June 06, 2008


In this paper, alternative approaches for synthetically generating a wind speed time series are discussed. These approaches include: (1) the use of independent values from a specific probability distribution; (2) the use of an algorithm based on the statistical behavior of a one-step Markov chain; (3) the use of an algorithm based on the behavior of a transition probability matrix that describes the next wind speed value statistically as a function of the current wind speed value and the previous wind speed value; (4) the use of Box-Jenkins models; (5) the use of the Shinozuka algorithm; and (6) the use of an embedded Markov chain. The ability of each approach to capture the statistical properties of the desired wind speed time series is discussed. In this context the statistical properties of interest are the probability distribution of the wind speed values, the autocorrelation function of the wind speed values, and the spectral density of the wind speed values.

Copyright © 1991 by The American Society of Mechanical Engineers
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