Author(s): Connor Jordan; Davor Dundovic; Anastasia Fragkou; Georgios Deskos; Daniel Coles; Matthew Piggott; Athanasios Angeloudis

Linked Author(s): Anastasia Fragkou, Athanasios Angeloudis

Keywords: Tidal energy; Array optimisation; Shallow water equations; Wake superposition

Abstract: Tidal array optimisation is a multifaceted problem that aims at the improvement of an array design’s performance, including its overall power yield. Benefits include reductions in investment uncertainty, thus supporting the tidal stream energy industry to reach its potential. Considering the complex, high-energy tidal hydrodynamics at proposed sites, defining an optimal array layout is challenging and remains an active research area. Existing optimisation methodologies can be either computationally untenable or restrictively simplified for practical cases. We present an optimisation approach that combines an analytical-based wake model, FLORIS, with a coastal ocean hydrodynamics model, Thetis. The approach is first demonstrated through idealised steady and transient flow cases to highlight hydrodynamics structures that are overlooked, including spatial complexity, tidal asymmetry, and the practical exploitation of blockage effects.. We thus explore the use of analytical wake superposition in combination with the use of simple heuristic techniques to achieve turbine array optimisation at a fraction of the computational cost of alternative methods. Towards this objective, we designed a custom condition-based placement algorithm. The algorithm is applied to the Pentland Firth, including a case of 24 turbines that follow a power curve constrained by a rated speed of ~3.0 m/s. This case study serves to demonstrate device-specific implications whilst also considering the temporal variability of the tide. Overall, this turbine layout optimisation process is able to deliver an array design that is 12% more productive on average than a staggered layout. Performance was quantified through assessment of the optimised layout using a shallow water equation model which more correctly represents turbines through discrete momentum sink terms.

DOI: https://doi.org/10.3850/IAHR-39WC2521711920221177

Year: 2022