• Energy Research

In order to design and evaluate the behaviour of a numerically optimised wave energy converter (WEC), a recommended procedure is to initially study small scale models in controlled laboratory conditions and then progress further up until the full-scale is reached. At any point, an important step is the correct selection of the wave theory to model the dynamical behaviour of the WEC. Most authors recommend the selection of a wave theory based on dimensional parameters, which usually does not consider the model scale. In this work, the scale effects for a point absorber are studied based on numerical simulations for three different regular waves conditions. Furthermore, three different wave theories are used to simulate two scales 1:1 and 1:50. The WEC-wave interaction is modelled by using a numerical wave tank implemented in ANSYS-Fluent with a floating object representing the WEC. Results show that the normalised difference between 1:1 and 1:50 models, keeping the same wave theory fluctuate between 30% and 58% of the WEC heave motion and that a wrong selection of the wave theory can lead to differences up to 138% for the same variable. It is also found that the limits for the use of wave theories depends on the particular model and that the range of applicability of different theories can be extended.

Wave tank tests often involve simulating extreme wave conditions as they enable the maximum expected loads to be inferred: a vital parameter for structural design. The definition, and simulation of, extreme conditions are often fairly simplistic, which can result in conditions and associated loads that are not representative of those that would be observed at the deployment location. Here we present a method of defining, simulating at scale, and validating realistic site-specific extreme wave conditions for survival testing of wave energy converters. Bivariate inverse-first order reliability method (I-FORM) environmental contours define extreme pairs of significant wave height and energy period ( H m 0 – T E ), while observed extreme conditions are used to define realistic frequency and directional distributions. These sea states are scaled, simulated and validated at the FloWave Ocean Energy Research Facility to demonstrate that the site-specific extreme wave conditions can be re-created with accuracy. The presented approach enables greater realism to be incorporated into tank testing with survival sea states. The techniques outlined and explored here can provide further and more realistic insight into the response of offshore structures and devices, and can help make important design decisions prior to full-scale deployment.

Abstract Tidal stream turbines are subject to large hydrodynamic loads, including those induced by extreme waves. Scale model testing in the laboratory plays an important role in ensuring that full scale tidal turbines are designed and operated in a manner that is appropriate for harsh ocean environments where waves and tidal currents coexist. For the first time, a fully-instrumented scaled tidal turbine is tested in short-duration focused wave groups representative of extreme environmental load cases expected at energetic tidal sites. In this paper, the subsequent variations in rotor-based loads, power and blade root bending moments are reported. These measurements are found to strongly follow the spectral and temporal form of the focused wave conditions, and peak loads and power output are found to exceed current-only values by 85% and 200% respectively. These rotor-averaged values display a high level of repeatability, demonstrating the suitability of focused waves for testing seabed-mounted tidal turbines. Extreme blade loads, which are dependent on angular position relative to wave phase, are captured through rapidly obtained repeat tests. New insight is subsequently gained into loading and response of tidal turbines in extreme sea conditions.

Acoustic Doppler Profilers (ADPs) are routinely used to measure flow velocity in the ocean, enabling multi-points measurement along a profile while Acoustic Doppler Velocimeters (ADVs) are laboratory instruments that provide very precise point velocity measurement. The experimental set-up allows laboratory comparison of measurement from these two instruments. Simultaneous multi-point measurements of velocity along the horizontal tank profile from Single-Beam Acoustic Doppler Profiler (SB-ADP) were compared against multiple co-located point measurements from an ADV. Measurements were performed in the FloWave Ocean Energy Research Facility at the University of Edinburgh at flow velocities between 0.6 ms − 1 and 1.2 ms − 1 . This paper describes the data; the analysis of the inter-instrument comparison is presented in an associated Sensors paper by the same authors. This data-set contains (a) time series of raw SB-ADP uni-directional velocity measurements along a 10 m tank profile binned into 54 measurements cells and (b) ADV point measurements of three-directional velocity time series recorded in beam coordinates at selected locations along the profile. Associated with the data are instrument generated quality data, metadata and user-derived quality flags. An analysis of the quality of SB-ADP data along the profile is presented. This data-set provides multiple contemporaneous velocity measurements along the tank profile, relevant for correlation statistics, length-scale calculations and validation of numerical models simulating flow hydrodynamics in circular test facilities.

Wave energy has the potential to provide a sustainable solution for global energy demands, particularly in coastal regions. This study explores the use of reinforcement learning (RL), specifically the Q-learning algorithm, to optimise the energy extraction capabilities of a wave energy converter (WEC) using a single-body point absorber with resistive control. Experimental validation demonstrated that Q-learning effectively optimises the power take-off (PTO) damping coefficient, leading to an energy output that closely aligns with theoretical predictions. The stability observed after approximately 40 episodes highlights the capability of Q-learning for real-time optimisation, even under irregular wave conditions. The results also showed an improvement in efficiency of 12% for the theoretical case and 11.3% for the experimental case from the initial to the optimised state, underscoring the effectiveness of the RL strategy. The simplicity of the resistive control strategy makes it a viable solution for practical engineering applications, reducing the complexity and cost of deployment. This study provides a significant step towards bridging the gap between the theoretical modelling and experimental implementation of RL-based WEC systems, contributing to the advancement of sustainable ocean energy technologies.

The EU H2020 MaRINET2 project has a goal to improve the quality, robustness and accuracy of physical modelling and associated testing practices for the offshore renewable energy sector. To support this aim, a round robin scale physical modelling test programme was conducted to deploy a common wave energy converter at four wave basins operated by MaRINET2 partners. Test campaigns were conducted at each facility to a common specification and test matrix, providing the unique opportunity for intercomparison between facilities and working practices. A nonproprietary hinged raft, with a nominal scale of 1:25, was tested under a set of 12 irregular sea states. This allowed for an assessment of power output, hinge angles, mooring loads, and six-degree-of-freedom motions. The key outcome to be concluded from the results is that the facilities performed consistently, with the majority of variation linked to differences in sea state calibration. A variation of 5–10% in mean power was typical and was consistent with the variability observed in the measured significant wave heights. The tank depth (which varied from 2–5 m) showed remarkably little influence on the results, although it is noted that these tests used an aerial mooring system with the geometry unaffected by the tank depth. Similar good agreement was seen in the heave, surge, pitch and hinge angle responses. In order to maintain and improve the consistency across laboratories, we make recommendations on characterising and calibrating the tank environment and stress the importance of the device–facility physical interface (the aerial mooring in this case).