Abstract
The ocean energy exploitation is arousing growing interest in the renewable energy sector. In the short term, horizontal axis tidal turbines are the most promising technology due to the accumulated know-how in the field of wind energy. In order to maximize the performance of the devices in a cluster, it is essential to optimize the layout. The marine environment offers different conditions than atmospheric situations, in terms of confinement and turbulence intensity. Moreover, tidal currents exhibit a highly predictable pattern in speed intensity and direction unlike the wind resource, which has a more random behaviour. Nonetheless, most of tidal sites are characterized by the inversion of flow where the two prevailing directions are not perfectly aligned and opposite, hence the angle between those directions should be a design variable. In this work we will consider as a case study the site proposed in [1], where this angle is ±20°. For those sites with a flow inversion of almost 180°, the staggered configuration is preferable to avoid wakes interference as mentioned in [2]. Furthermore, many studies [3] had analysed positive interaction between neighbouring devices in a cluster, hence it is important to establish the optimal relative position accounting for fluid dynamic positive effects, and not only negative aspects such as wake interactions. For this reason, in this work we present a novel approach to determine the best configuration of a cluster of few turbines, a ”module”, which will be the optimized ”building block” for the whole farm. The procedure to be followed consist of two phases in which both the characteristics of the site and those of the turbine are taken into consideration. To place the devices in an optimal configuration, we first consider the change of flow direction during the tidal cycle for the site of interest, allowing only those configurations which avoid wake interference for both prevailing flow directions; then, we assess the best layout by exploiting positive interactions between devices in the cluster. The mutual fluid dynamic influence is analysed by means of a 3D Blade Element Momentum model of the turbine [4] implemented in the Open Source SHYFEM code. A series of simulations is performed to outline the power production trend of the module, and consequently find the optimal distancing between the machines. CFD simulations are also used to extract the module wake characteristics.