Multi-Objective Evolutionary Framework for Layout and Operational Optimization of a Multi-Body Wave Energy Converter

As global energy demand continues to rise, the focus has increasingly shifted toward renewable energy sources. In this context, multi-body Wave Energy Converters (WECs) stand out due to their superior power capture efficiency and enhanced survivability, facilitated by their operational flexibility. Nevertheless, the complexity associated with deploying multi-body WECs in arrays has constrained extensive research in this domain. This study introduces an optimization strategy for the layout design and control of multi-body WECs aimed at efficiently harnessing wave energy. Utilizing Evolutionary Multi-Objective Optimization (EMO) algorithms, this framework optimizes the arrangement and operational parameters of WEC arrays, specifically tailored for the marine conditions off the coast of Oman. The research encompasses two primary optimization phases: layout optimization, which seeks an optimal balance between power production and the separation distance between WEC devices, and operational control optimization, which adjusts WEC configurations according to varying wave conditions. This approach aims to maximize energy capture and ensure sustainable array performance while addressing technical challenges. Simulation results indicate that the optimized configurations not only enhance energy extraction but also significantly reduce hydrodynamic loads, promising improved longevity and efficiency for multi-body WEC systems in extreme marine environments.