Continuous wind speed models based on stochastic differential equations

Rafael Zárate-Miñano, Marian Anghel and Federico Milano

Applied Energy, 2013, vol. 104, issue C, 42-49

Abstract: This paper proposes two general procedures to develop wind speed models based on stochastic differential equations. Models are intended to generate wind speed trajectories with statistical properties similar to those observed in the wind speed historical data available for a particular location. The developed models are parsimonious in the sense that they only use the information about the marginal distribution and the autocorrelation observed in the wind speed data. Since these models are continuous, they can be used to simulate wind speed trajectories at different time scales. However, their ability to reproduce the statistical properties of the wind speed is limited to a time frame of hours since diurnal and seasonal effects are not considered. The developed models can be embedded into dynamic wind turbine models to perform dynamic studies. Statistical properties of wind speed data from two real-world locations with significantly different characteristics are used to test the developed models.

Keywords: Stochastic differential equations; Dynamic analysis; Wind speed; Weibull distribution; Ornstein–Uhlenbeck process; Memoryless transformation (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (28)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261912007969
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:appene:v:104:y:2013:i:c:p:42-49

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2012.10.064

Access Statistics for this article

Applied Energy is currently edited by J. Yan

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