Abstract

Wind turbine interaction in wind farms can lead to energy loss and increased wind turbine loads, with the magnitude of these effects strongly depending on atmospheric conditions. One-dimensional Reynolds-averaged Navier-Stokes (RANS) models are able to represent the atmospheric boundary layer (ABL) over a range of model fidelity, and can be used for steady-state inflow profiles in three-dimensional RANS simulations of wind farms. In the present work, an overview of existing and recently developed atmospheric inflow models is presented. The inflow models are applied to separately demonstrate impacts on the velocity deficit of a row of ten wind turbines, due to: turbulence intensity and atmospheric stability in the atmospheric surface layer; ABL depth; and Coriolis-induced veer.

Highlights

  • Modeling wind turbine interaction in wind farms is important to obtain a better understanding of wake-induced energy losses and blade fatigue loads

  • Wind turbine interaction in wind farms can lead to energy loss and increased wind turbine loads, with the magnitude of these effects strongly depending on atmospheric conditions

  • This large amount of wind veer should be considered as an extreme case that can occur for very stable conditions

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Summary

Introduction

Modeling wind turbine interaction in wind farms is important to obtain a better understanding of wake-induced energy losses and blade fatigue loads. Wind turbine interaction can lead to energy redistribution between wind turbines due to upstream effects known as global blockage. The magnitude of the wake and blockage effects in wind farms are strongly dependent on the atmospheric conditions as turbulence intensity and atmospheric stability. Large-eddy simulation (LES) is a transient CFD method that resolves the large scale turbulence and models the small scales. RANS models all turbulence scales and may not provide accurate results in all cases compared to turbulence resolving method as LES; it is a useful method to isolate relative effects, which can leverage the understanding of wind farm flows

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