Towards a Simplified Dynamic Wake Model using POD Analysis

We apply the proper orthogonal decomposition (POD) to large eddy simulation data of a wind turbine wake in a turbulent atmospheric boundary layer. The turbine is modeled as an actuator disk. Our analyis mainly focuses on the question whether POD could be a useful tool to develop a simplified dynamic wake model. The extracted POD modes are used to obtain approximate descriptions of the velocity field. To assess the quality of these POD reconstructions, we define simple measures which are believed to be relevant for a sequential turbine in the wake such as the energy flux through a disk in the wake. It is shown that only a few modes are necessary to capture basic dynamical aspects of these measures even though only a small part of the turbulent kinetic energy is restored. Furthermore, we show that the importance of the individual modes depends on the measure chosen. Therefore, the optimal choice of modes for a possible model could in principle depend on the application of interest. We additionally present a possible interpretation of the POD modes relating them to specific properties of the wake. For example the first mode is related to the horizontal large scale movement. Besides yielding a deeper understanding, this also enables us to view our results in comparison to existing dynamic wake models

Stochastic Wake Modelling Based on POD Analysis

In this work, large eddy simulation data is analysed to investigate a new stochastic modeling approach for the wake of a wind turbine. The data is generated by the large eddy simulation (LES) model PALM combined with an actuator disk with rotation representing the turbine. After applying a proper orthogonal decomposition (POD), three different stochastic models for the weighting coefficients of the POD modes are deduced resulting in three different wake models. Their performance is investigated mainly on the basis of aeroelastic simulations of a wind turbine in the wake. Three different load cases and their statistical characteristics are compared for the original LES, truncated PODs and the stochastic wake models including different numbers of POD modes. It is shown that approximately six POD modes are enough to capture the load dynamics on large temporal scales. Modeling the weighting coefficients as independent stochastic processes leads to similar load characteristics as in the case of the truncated POD. To complete this simplified wake description, we show evidence that the small-scale dynamics can be captured by adding to our model a homogeneous turbulent field. In this way, we present a procedure to derive stochastic wake models from costly computational fluid dynamics (CFD) calculations or elaborated experimental investigations. These numerically efficient models provide the added value of possible long-term studies. Depending on the aspects of interest, different minimalized models may be obtained

Extreme winds in the new European Wind Atlas

As a part of the New European Wind Atlas project, we investigate the estimation of extreme winds from mesoscale simulations. In order to take the smoothing effect of the simulations into account, a spectral correction method is applied to the data. We show that the corrected extreme wind estimates are close to the values obtained from offshore met masts. Hence, after further investigations we plan to use the examined approach as a basis for the calculation of extreme winds on the complete New European Wind Atlas, which will be publicly available at the end of the project

Wind Turbine Wakes in Directionally Varying Wind Shears

In the atmospheric boundary layer, the Coriolis force associated with the Earth’s rotation induces a spanwise wind shear in addition to the wall-normal one leading to a continuous change in wind direction with height. The spanwise wind shear in directionally sheared inflow has a significant impact on the formation and development of wind-turbine wakes. The present work aims to provide an analytical framework for predicting wind turbine wakes in directionally varying wind shears