Optimizing wave energy harvesting through oscillating water columns in semi-submersible energy harvesting platforms: A comprehensive study on enhancing efficiency and competitiveness

In coastal regions with substantial wave energy potential, significant efforts have been dedicated to advancing both the Technology Readiness Level (TRL) and Technology Performance Level (TPL) of Wave Energy Converters (WECs). Despite their promising energy generation capabilities, the widespread adoption of WEC devices faces a notable challenge in the form of their relatively high Levelized Cost of Energy (LCOE). This economic hurdle hampers their competitiveness when compared to conventional fossil fuels and other renewable energy sources. Oscillating Water Columns (OWCs) stand out due to their noteworthy potential, primarily attributed to their low Operations and Maintenance (O&M) costs. To enhance the energy performance of OWC arrays and pave the way for hybrid offshore energy solutions, the integration of a semi-submersible Energy Harvesting Platform (EHP) is proposed. This integration involves configuring the array with specific OWC End-Stop limitations and geometry to establish resonant conditions during the predominant wave, thereby optimizing constructive interactions and desirable OWC motion with the EHP's heave, pitch, and roll. A Genetic Algorithm (GA) is employed for this optimization process. Additionally, a novel parameter, the In Situ Interaction Factor (ISIF) is introduced, to evaluate the EHP's power capture performance. This metric compares the actual energy harvested from the array of WECs on the platform to the cumulative energy harvested by each device in isolation. Notably, ISIF achieved a remarkable value of 1.99, highlighting the highly efficient constructive interaction achieved through the precise positioning of OWCs. This resulted in nearly doubling the power capture compared to 23 OWCs operating in isolation, underscoring the potential of the EHP in harnessing wave energy. Validation of the analytical analysis was conducted using the open-source Boundary Element Method (BEM) tool NEMOH, alongside reference to the experimental studies.