Coughlan, Katherine | Search NASA

DOE OSTI2024

Assessing the impacts of wakes on floating wind farms with shared anchors

This paper examines wake effects for floating wind farms with shared anchors. Three 20-turbine farms are examined: a grid-formation baseline with no shared anchors, a farm based on 3-line anchors, and a farm based on 6-line anchors, governed by a wind turbine spacing of 8 rotor diameters. The IEA 15 MW reference turbine on the UMaine semisubmersible platform was used with a taut mooring system in deep- water depths representative of U.S. west coast lease areas. A steady-state wake model showed that, when evaluating a sweep of wind headings, the baseline design had the lowest wake losses, with a value of 11.7 %, followed by the 6-line at 12.9% and the 3-line at 13.8%. Dynamic simulations were run in FAST.Farm to analyse the effects of wakes on mean anchor loads for wind headings that showed significant wake losses. The baseline farm showed the largest anchor load reductions due to wake effects (up to 16%), followed by the 3-line farm (up to 8%), and the 6-line farm, which showed relatively consistent load magnitudes on the 6-line anchors across all headings.

17 WIND ENERGY↗

DOE OSTI2024

Floating Wind Farm Layout Optimization Considering Moorings and Seabed Variations

This paper presents a method for optimizing the layout of floating wind farms that accounts for realistic seabed variations and the consequent adjustments to the mooring systems required for different turbine positions. The mooring lines of floating wind farms create large spatial constraints that are depth-dependent, since mooring designs must adapt to variations in seabed conditions over the array area. We develop a layout optimization methodology that addresses this, adjusting mooring system designs based on the local seabed characteristics as the layout changes and using steady-state models for the wake effects and mooring lines. The approach includes design algorithms that adjust the anchor positions and line length to achieve the desired mooring line profile for different water depths, and a layout optimization framework that implements spatial constraints between the turbines, mooring lines, and lease area boundaries. Demonstrating the method on several cases shows the effect of the seabed and spatial-constraint factors, as well as their interactions, on the optimal array layout. This demonstration paves the way for scaling up the method, using more powerful optimization algorithms to handle larger farm sizes and situations with more intensely varied seabed conditions.

17 WIND ENERGY↗