On- and offshore wind farms are getting larger, with trends toward larger turbines and more turbines per unit area now the norm. To enable the efficient use of turbines within a wind farm, it is important that the reduced efficiency of turbines located in the wake of neighbouring turbines is well understood and quantified. Unfortunately, these wake losses are complicated, with strong dependencies on atmospheric stability, surrounding terrain and topography, flow turbulence, and for offshore wind turbines, wave conditions. With the expectation of increased penetration of offshore wind energy into national electricity grids, the ability to effectively predict power from these wind farms is becoming increasingly important.
This project seeks to explore two main research challenges. Firstly, we seek to better understand the complex relationship between offshore wind turbine wakes, wave conditions and atmospheric stability. This is a particularly difficult modelling challenge as the processes that influence these wake dynamics span a wide range of spatial and temporal scales that are difficult to capture in a single simulation model. This has been deemed a “Grand Challenge” in wind energy research and will be explored here parametrically through both experimental and numerical methods. The second challenge relates to the methods used to study this process. Here we will use numerical simulations (Large Eddy Simulations or Hybrid Turbulence Models) to model the flow behind an offshore wind turbine under different atmospheric stability conditions and with different underlying wave conditions (IIT). We will then attempt to replicate a selection of these flow conditions in the wind-wave tunnel at UQ. We will then do the same in the UQ wind tunnel but make the simplification that the waves can be represented and replaced by a textured undulating surface. In all cases the flow characteristics of the turbine wake will be measured and compared.
•Improved understanding of how well wind tunnels can replicate offshore wind turbine wakes using artificial flow control and simulated ocean waves.
•Improved understanding of the wind science associated with interactions between wakes, waves and atmospheric stability conditions.
•Insight into wake dynamics that will lead to better wind farm design and improved power output.
•Publication of high-quality research papers in leading wind energy journals.
A strong interest in numerical or experimental fluid mechanics, atmospheric or wind science, experience developing and/or running mathematical codes or laboratory experimentation, interest in renewable energy
Experience with meso- or micro-scale meteorological models, experience with computational fluid dynamics models, experience with wind tunnel testing
Bachelors (with honours) or Masters degree in engineering, atmospheric science or a related (e.g. energy, mathematics, physics) field.