Multiscale modelling for wind farm design, performance assessment and loading

The wind industry is developing wind turbines and airborne wind energy devices which span altitudes well above the well-studied surface layer. A full understanding of the unsteady inflow conditions which drive loads and performance at these altitudes is lacking. MERIDIONAL will provide a comprehensively validated tool chain based on an open-source platform which will draw on an integrated knowledge and data hub to allow the efficient and accurate assessment of the performance and loads experienced by onshore, offshore, and airborne wind energy systems. This tool chain can be used for component, device and plant level planning and operation. It will consist of models which can capture the unsteady time-resolved inflow structures which drive performance and loads within the wind plant, incorporating inter and intra farm turbine interactions. Inflow conditions will be analysed and modelled beyond the surface layer to capture the conditions within and above the atmospheric boundary layer. This is critical to a full understanding of the loads and performance of wind farms and airborne wind energy devices. Model validation will be underpinned by a range of high quality and unique datasets drawing on high-fidelity simulations, and kite-borne, lidar, drone and mast measurements from field test campaigns in complex terrain, offshore and airborne. The strength of the tool chain results from developing different models for different situations, using higher order approaches (e.g., meso and microscale LES) when required and lower order models (physics or data-driven) where these are sufficient to accurately predict loads and performance. The knowledge and data hub will allow users of the tool chain to draw on a wide range of existing and project-generated measurement and simulation data to allow site specific analysis to be carried out at any location. MERIDIONAL allows stakeholders to increase wind plant efficiency and reduce material costs through less conservative design.

This project has received funding from the European Union under grant agreement No 101084216.