Open AccessModel of a synthetic wind speed time series generator
Author(s) -
Negra Nicola Barberis,
Holmstrøm Ole,
BakJensen Birgitte,
Sørensen Poul
Publication year - 2007
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.244
Subject(s) - wind speed , autocorrelation , wind power , monte carlo method , range (aeronautics) , generator (circuit theory) , computer science , time series , series (stratigraphy) , power (physics) , engineering , meteorology , mathematics , statistics , aerospace engineering , electrical engineering , paleontology , physics , quantum mechanics , machine learning , biology
Wind energy has assumed a great relevance in the operation and planning of today's power systems due to the exponential increase of installations in the last 10 years. For this reason, many performed studies have looked at suitable representations of wind generation for power system analysis. One of the main elements to consider for this purpose is the model of the wind speed that is usually required as input. Wind speed measurements may represent a solution for this problem, but, for techniques such as sequential Monte Carlo simulation, they have to be long enough in order to describe a wide range of possible wind conditions. If these information are not available, synthetic wind speed time series may be a useful tool as well, but their generator must preserve statistical and stochastic features of the phenomenon. This paper deals with this issue: a generator for synthetic wind speed time series is described and some statistical issues (seasonal characteristics, autocorrelation functions, average values and distribution functions) are used for verification. The output of the model has been designed as input for sequential Monte Carlo simulation; however, it is expected that it can be used for other similar studies on wind generation. Copyright © 2007 John Wiley & Sons, Ltd.