DocumentCode
991659
Title
Correlation of wind speed between neighboring measuring stations
Author
Bechrakis, Dimitrios A. ; Sparis, Panagiotis D.
Author_Institution
Dept. of Electr. & Comput. Eng., Democritus Univ. of Thrace, Xanthi, Greece
Volume
19
Issue
2
fYear
2004
fDate
6/1/2004 12:00:00 AM
Firstpage
400
Lastpage
406
Abstract
A method for establishing wind speed correlation between neighboring measuring stations is presented in this paper. The aim of this study is to develop a model, in which given the wind speed at a particular site to simulate the wind speed at another, nearby site, in order to estimate the wind power of an area. This method takes into account the evolution of the sample cross correlation function (SCCF) of wind speed in time domain and uses an artificial neural network to perform the wind speed simulation. Four separate pairs of wind data measuring stations at two different regions were examined. Tests showed that the higher the SCCF value between two sites, the better simulation achieved. Also, in a pair of stations under investigation the reference station must be the one that contains more information in its wind speed signal, in order to obtain the optimum simulation performance.
Keywords
correlation methods; neural nets; power system simulation; wind power; wind power plants; artificial neural network; neighboring measuring stations; sample cross correlation function; wind data measuring station; wind power; wind speed correlation; Area measurement; Artificial neural networks; Discrete event simulation; Neural networks; Testing; Time measurement; Velocity measurement; Wind energy; Wind forecasting; Wind speed; Correlation; neural network applications; simulation; wind energy;
fLanguage
English
Journal_Title
Energy Conversion, IEEE Transactions on
Publisher
ieee
ISSN
0885-8969
Type
jour
DOI
10.1109/TEC.2004.827040
Filename
1300707
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