ON ESTIMATION OF EMPIRICAL ORTHOGONAL MODES IN INFLOW TURBULENCE FOR WIND TURBINES

An understanding of the inflow turbulence spatial structure is important in decisions related to siting of wind turbines. This study proposes the use of Proper Orthogonal Decomposition (POD) of the most energetic modes that characterize the spatial inflow random field describing the turbulence experienced by a wind turbine. The appeal for the use of POD techniques is that preferred spatial “modes” or patterns of wind excitation can be empirically developed using data from spatial arrays of sensed input/excitation. These loading modes explain in part the behavior of dynamic systems in an analogous way to how natural modes of vibration associated with response and developed using structure mass, stiffness, and damping properties can explain the same though again only in part. Proper orthogonal decomposition has generated much interest in wind engineering applications in recent years, albeit mainly for buildings, not for wind turbines. This study seeks to extend thinking related to this heuristically appealing approach to describing inflow by first examining the orthogonal subprocesses derived from a POD analysis defined by theoretical power spectra and coherence models commonly used for wind turbines. Then, based on field data from a wind turbine, estimates of cross-power spectral density functions are used to estimate empirical POD modes that are compared with those based on theoretical considerations. Accuracy in predicting power and coherence spectra from a limited number of POD modes is discussed.