Abstract
The representation of flow across influential spatiotemporal scales introduces a challenge when micro-siting tidal stream turbine arrays. Robust representative approximations could accelerate design optimisation, yet there is no consensus on what defines the most appropriate flow conditions. We summarise existing approaches to representative flow field selection for array optimisation and propose an objective-driven process. The method curates a subset of flow fields that best captures relevant dynamics, enabling the streamlined representation of tidal cycles. To demonstrate the method, we consider flow modelling data in the Inner Sound of the Pentland Firth, Scotland, UK. We examine the impact of flow field inputs to array design through comparative analyses using a heuristic array optimisation process. Results indicate notable sensitivity of the turbine layout to the flow conditions selected. For the case study presented, our method led to 4%–5% energy yield prediction improvements relative to use of simple time-interval based approaches and up to 2% improvement against using peak flow fields; these can be pivotal margins to secure feasibility by developers. We also find that using the data associated with a single monitored point across the array for flow field selection can lead to sub-optimal results, emphasising the need for accurate spatiotemporal representation.