Maximization of Wave Energy Conversion Into Electricity Using Oscillating Water Columns and Nonlinear Model Predictive Control

The oscillating water column (OWC) wave energy converter (WEC) together with a self-rectifying air turbine and generator which convert alternating airflow induced by the water motion into kinetic energy and then into electric energy is a promising device for the advancement of marine renewable energy. As researchers overcome the modeling challenges of OWCs, such as the nonlinearities due to air compressibility and power take-off (PTO) dynamics, we can integrate control algorithms to improve the efficiency of the OWC. Herein, we present a nonlinear model predictive controller (NMPC) that maximizes the generated electro-mechanical power while maintaining the efficiency of a self-rectifying turbine attached to an OWC WEC. To achieve this goal, a good trade-off between maximizing generated power and turbine efficiency is found by adjusting the importance of both objectives in the computation of the control signal. Furthermore, we apply the proposed NMPC to an array of three WECs that takes into account the hydrodynamic interactions between the devices in the computation of optimal generator torque control signal.