Journal
WIND ENERGY
Volume 11, Issue 2, Pages 193-209Publisher
WILEY
DOI: 10.1002/we.244
Keywords
wind speed time series; Markov chain; Monte Carlo simulation; synthetic wind speed generator
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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 lost 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 (C) 2007 John Wiley & Sons, Ltd.
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