Abstract

The analysis of wind turbine wakes’ structure and interaction with other machines installed in the same array or park has become a key element in the current wind energy research due to the notable impact that wakes can have on the actual energy production of the turbines themselves. The present frontier of the research in this field is leading to the massive use of large-eddy simulations to completely solve the flow field surrounding the rotors. By doing so, however, enormous calculation resources are needed, which are often not available in an industrial context and also generally not compatible with extended optimization analyses (e.g. for a park layout definition). In this latter case, several cases need to be solved in a reasonable amount of time and therefore more computationally efficient methods are still needed. Within this context, the present study reports a comparative analysis between three different techniques to analyse the wind turbine wakes’ structure and their mutual interaction. In particular, a state-of-the-art 3D RANS calculation of the famous NREL Phase VI rotor was used as a benchmark for comparison with two other methods. The first one is based on the Virtual Blade Model (VBM) of the commercial solver ANSYS® FLUENT®, in which a 3D RANS calculation of the flow field is carried out for the outer domain, while the effect of the rotating blades on the fluid is simulated through a body force, which acts inside a disk of fluid with an area equal to the swept area of the turbine. The value of the body force is time-averaged over a cycle from the forces calculated by a simplified Blade Element Method. In the present study, a stall delay model was also implemented within the VBM module. The second one is instead based on the even more simple approach with an Actuator Disk Model (ADM), in which the turbine presence is actually modelled as a sink of momentum in the main flow. Cross-comparisons between the techniques are shown, both in terms of single wake description and of wake-turbine interaction, leading to the conclusion that the VBM model may represent a valuable and computationally affordable tool in many wind energy applications.

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