The use of vertical-axis turbines is raising interest in the field of hydropower production from rivers or water channels, where suitable mass flows are available, without the need of high water jumps or large construction sites. Like their wind-based counterparts, these machines have many advantages in terms of installation and maintenance, but suffer from an inherently complex rotor hydrodynamics, characterized by a continuous variation of the blade angle of attack beyond the static stall limit and the corresponding onset of dynamic instabilities. In virtue of their typically lower rotational speed nonetheless, hydrokinetic machines can benefit from the possibility of active blade pitch control, which is barely feasible in case of wind turbines due to their high characteristic operation frequencies. Moving from this background, a novel control strategy, based on a double-cam desmodromic pitching system, has been developed in the present study by means of a combination of medium- and high-fidelity numerical approaches. In order to tailor the corresponding pitching law, here implemented in a parametric form, to this class of machines, a dedicated automatic optimization framework has been developed in the ANSYS® WORKBENCH® 20.2 suite. The latter combines a Multi-Objective Genetic Algorithm (MOGA) optimizer with an advanced two-dimensional Actuator Line Model (ALM) model of the turbine, developed by the authors. This optimization approach has then been applied to a test rotor with the objective of maximising the turbine power coefficient while containing the rotor stream- and cross-wise force oscillations. The resulting optimal configurations have been eventually verified via high-fidelity, fully-resolved CFD simulations. Results show that variable pitch can represent a promising solution for increasing the performance of vertical-axis hydrokinetic turbines, leading to a +35% efficiency enhancement as well as to a reduction of the machine unsteady loads.
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