Data-based modelling and optimal control for wave energy conversion systems

Wave energy holds great potential as a renewable energy source. To make use of this potential, wave energy converters (WECs) are utilized to capture the perpetual motion of the ocean as an energy source. However, the industry for WECs has not reached maturity, marked by significant variability and a lack of standards. Furthermore, improving the efficiency of the wave energy converters is still a key challenge. In order to make it applicable against operational costs, which is a crucial factor for the economical viability of the device, the control technique used for the WEC has an impactful role and needs to be explored. However, the control of the WECs is different than the standard control problem, which generally employs set-point tracking and is about energy maximization. In this work, a generalized framework has been developed to identify and optimize WEC systems. The framework integrates various tools for the simulation of the dynamics using the hydrodynamic coefficients and for the optimization of power take-off (PTO) trajectories. From system identification to optimization, each stage is included and tailored for compatibility with the pseudo-spectral method, which is used for the discretization of the optimization problem. A set of simulations was carried out to validate the results of the framework in numerous sea states to maximize energy extraction while constraining the PTO motion and force. Two different WEC models were tested, allowing for a comparative analysis of parameter impacts within the framework. The results validate the framework’s effectiveness and lay the groundwork for further studies toward developing more practical and cost-effective WEC devices.