2015/11/07 by Rafael Zárate Miñano, Miñano, Rafael Zárate, Federico Milano +1
Mathematics · Physics and Astronomy · #60 #Applications (stat.AP) #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #J.2 #Statistics and Probability (physics.data-an) #acm:60 #msc:60 #physics.data-an #stat.AP
paper · pdf · doi:10.48550/arxiv.1511.02345
17 pages, 25 references
arxiv created 2015/11/07 · arxiv updated 2015/11/10
This paper provides a systematic method to build wind speed models based on stochastic differential equations (SDEs). The resulting models produce stochastic processes with a given probability distribution and exponential decaying autocorrelation function. The only information needed to build the models is the probability density function of the wind speed and its autocorrelation coefficient. Unlike other methods previously proposed in the literature, the proposed method leads to models able to reproduce an exact exponential autocorrelation even if the probability distribution is not Gaussian. A sufficient condition for the property above is provided. The paper includes the explicit formulation of SDE-based wind speed models obtained from several probability distributions used in the literature to describe different wind speed behaviors.