Stochastic generation of hourly mean wind speed data

Hafzullah Aksoy, Z Fuat Toprak, Ali Aytek and N Erdem Ünal

Renewable Energy, 2004, vol. 29, issue 14, 2111-2131

Abstract: Use of wind speed data is of great importance in civil engineering, especially in structural and coastal engineering applications. Synthetic data generation techniques are used in practice for cases where long wind speed data are required. In this study, a new wind speed data generation scheme based upon wavelet transformation is introduced and compared to the existing wind speed generation methods namely normal and Weibull distributed independent random numbers, the first- and second-order autoregressive models, and the first-order Markov chain. Results propose the wavelet-based approach as a wind speed data generation scheme to alternate the existing methods.

Keywords: Normal distribution; Weibull distribution; Autoregressive models; Markov chain; Wavelet; Hourly mean wind speed (search for similar items in EconPapers)
Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148104001272
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:29:y:2004:i:14:p:2111-2131

DOI: 10.1016/j.renene.2004.03.011

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().