Design Wind Speeds Using Fast Fourier Transform: A Case Study

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Author(s): Z.. Ismail (Universiti Malaya, Malaysia), N. H. Ramli (Universiti Malaya, Malaysia), Z.. Ibrahim (Universiti Malaya, Malaysia), T. A. Majid (Universiti Sains Malaysia, Malaysia), G. Sundaraj (Universiti Sains Malaysia, Malaysia)and W. H.W. Badaruzzaman (Universiti Kebangsaan Malaysia, Malaysia)
Copyright: 2008
Pages: 16
Source title: Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Vijayan Sugumaran (Oakland University, Rochester, USA)
DOI: 10.4018/978-1-59904-941-0.ch089

Keywords: Artificial Intelligence / Computer Science & IT / Information Science Reference

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Abstract

In this chapter, a study on the effects of transforming wind speed data, from a time series domain into a frequency domain via Fast Fourier Transform (FFT), is presented. The wind data is first transformed into a stationary pattern from a non-stationary pattern of time series data using statistical software. This set of time series is then transformed using FFT for the main purpose of the chapter. The analysis is done through MATLAB software, which provides a very useful function in FFT algorithm. Parameters of engineering significance such as hidden periodicities, frequency components, absolute magnitude and phase of the transformed data, power spectral density and cross spectral density can be obtained. Results obtained using data from case studies involving thirty-one weather stations in Malaysia show great potential for application in verifying the current criteria used for design practices.

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