The potential for tidal energy to be a part of future renewable energy systems is expanding. Tidal turbines deployed in open waters or channels are effective methods to harness energy from tidal currents. Sharing similar functionality with wind turbines, horizontally mounted tidal turbines require a minimum tidal current velocity to operate effectively. The Deep Green (DG) power plant which is based on a tethered kite model aims, however, to operate efficiently in tidal current velocities as low as 1.2 m/s. The kite wing is steered in a lemniscate trajectory almost perpendicular to the tidal current. In the trajectory, the relative flow velocity through the turbine attached to the wing reaches several times the tidal current velocity, enabling efficient operation of the turbine in relatively low-velocity tidal currents. This could reduce geographical limitations in installing large-scale tidal power arrays.
In a previous project, numerical modelling of the DG was carried out in a tidal flow using Large Eddy Simulations (LES) and Actuator Line Modelling (ALM) implemented in OpenFOAM solver. ALM using momentum sources has been used in modelling wind turbines and has been validated against experimental data and observations. The ALM has been further developed in order to be able to model wings (here the kite) that move in arbitrary paths compared to horizontally mounted turbines with rotational paths. This numerical model for the DG kite in a tidal flow has, however, up to now not been validated against observations, which is beneficial before further analyses are made, e.g., optimization studies.
In this study, Acoustic Doppler Current Profiler (ADCP) observations taken in the wake of a DG are compared to the results from the numerical model under similar conditions. Comparing the numerical results directly with the observations leads to discrepancies, hence the model data is resampled in a similar way that the ADCP would measure and process data using a virtual ADCP for the model. Flow properties such as the instantaneous and time-averaged stream velocities are in turn compared for both the tidal flow without the DG and with a DG. The effect of the DG on the tidal flow is analysed using the model and the observations. After resampling the model data, the model and observations show good agreement. This suggests 1) that the DG model using ALM can be used for further analysis and 2) that whilst comparing model data with ADCP observations for studying the small-scale effects of tidal turbine wakes, care should be taken to sample the model data consistently with observations.