Data-based Modelling of Nonlinear Hydrodynamics for Wave Energy Conversion Systems

This thesis investigates the creation of a model for wave energy converters (WECs) that focuses on controlling the nonlinear hydrodynamics, particularly the Froude-Krylov (FK) effects, in wave energy conversion systems. This research aims to use a two-degree-of-freedom model and data-based modeling approaches to accurately represent the dynamic interactions between wave forces and wave energy converters (WECs). The goal is to maintain computational efficiency while dealing with the complexity and computational extent of existing models. A complete dataset on FK forces is produced by utilizing the computational solution NLFK4ALL to simulate real ocean wave circumstances with different wave spectra. System identification approaches are utilized to obtain a concise yet precise model of the WEC, specifically emphasizing its vertical and rotational movements. This research contributes to the ongoing efforts to improve the efficiency and reliability of wave energy conversion technologies by studying the nonlinear FK effects and their significant effect on WEC performance. The findings of this research can help promote the wider use of renewable energy sources. The results highlight the effectiveness of data-driven and control-focused modeling methods in addressing important obstacles in the wave energy conversion area. These obstacles include the requirement for models that strike a balance between precise physical representation and manageable computational complexity.