Abstract
Wave-induced loading and performance variability significantly impacts the design and operational efficiency of tidal turbines. Limited understanding of the extent and impact of these interactions often results in conservatism and overdesign, resulting in increased costs and material inefficiencies. Developing robust and reliable numerical models for tidal turbines operating in complex flow conditions is crucial for optimizing their design. However, as numerical models advance, comprehensive experimental datasets capturing turbine loading and performance under diverse flow conditions are essential for validating these models and quantifying uncertainties.
This paper will present results from a large-scale laboratory experiment conducted on a highly instrumented, three-bladed, fixed-pitch horizontal-axis tidal turbine previously developed for a benchmarking study, funded by the UK's EPSRC and the Supergen ORE Hub. The 1.6m diameter turbine achieves a peak power coefficient of 0.485 at a tip-speed ratio of 5.78 and operates in a post-critical blade Reynolds number regime (Re≈3×105), allowing for meaningful performance comparisons to full-scale devices. Experiments were performed at Qinetiq’s Haslar facility, in the 12.2m wide, 5.4m deep towing tank under controlled wave conditions, with a blockage ratio of 3.0%. The experiments covered a parameter space over a range of wave amplitudes following Froude scaling, together with a range of wave frequencies following reduced frequency scaling relative to full-scale conditions.
Equipped with advanced instrumentation, the turbine recorded integrated power and thrust through a torque-thrust transducer, as well as spanwise distributions of flapwise and edgewise bending moments via strain gauges placed at the blade root and within the blade along its span. High-fidelity measurements captured both time-averaged performance and unsteady loading across a range of tip-speed ratios. Additionally ultrasonic wave probes were used to measure free surface elevation before and aft the turbine. The experimental data enables, for instance, the identification of unsteady loading paths with respect to blade azimuth position and wave phase.
The resulting dataset offers high-resolution data for validating numerical models and quantifying uncertainties associated with turbine design and analysis. This work aims to reduce conservatism in engineering models, enhance confidence in turbine design processes, and support the development of reliable, cost-effective tidal energy systems.