Cluster-based probabilistic structure dynamical model of wind turbine wake. Issue 8 (3rd August 2021)

• Record Type: Journal Article
• Authors: Ali, Naseem; Calaf, Marc; Cal, Raúl Bayoán
• Is Part Of: Journal of turbulence. Volume 22:Issue 8(2021)
• Page Start: 497
• Page End: 516
• Publication Date: 2021-08-03
• Subjects: Wind energy -- wakes -- clustering -- k-means -- POD -- Markov chain; Turbulence -- Periodicals; Turbulence -- Périodiques; 532.0527
• DOI: 10.1080/14685248.2021.1925125
• Languages: English
• ISSNs: 1468-5248

Abstract

Abstract : For complex flow systems like the one of the wind turbine wakes, which include a range of interacting turbulent scales, there is the potential to reduce the high dimensionality of the problem to low-rank approximations. Unsupervised cluster analysis based on the proper orthogonal decomposition is used here to identify the coherent structure and transition dynamics of wind turbine wake. Through the clustering approach, the nonlinear dynamics of the turbine wake is presented in a linear framework. The features of the fluctuating velocity are grouped based on similarity and presented as the centroids of the defining clusters. Determined from probability distribution of the transition, the dynamical system identifies the features of the wakes and the inherent dynamics of the flow.