Mooring-based frequency-domain and AI-based time-domain optimization for improved power capture performance of the TALOS wave energy converter

Mooring-based frequency-domain analysis combined with AI-based time-domain optimization offers a systematic approach to improving power capture performance in multi-degree-of-freedom wave energy converters. While most existing studies focus on single-degree-of-freedom systems, enhanced energy absorption can be achieved by exploiting the dynamic potential of multi-DoF configurations. This study investigates the TALOS wave energy converter, a six-degree-of-freedom system, with the objective of improving its power capture capability through coordinated mooring and power take-off (PTO) optimization. The optimization framework begins with a frequency-domain analysis to assess the influence of mooring parameters on the system response. Based on this analysis, two refined configurations, denoted as TALOS-L and TALOS-H, are developed using optimized mooring stiffness characteristics. Subsequently, time-domain simulations are conducted using a genetic algorithm to determine optimal PTO damping settings under site-specific sea conditions. The results show that adaptive tuning of both mooring and PTO parameters significantly improves power capture across different sea states. In particular, the TALOS-H configuration, featuring tuned surge mooring stiffness and genetically optimized PTO damping, consistently outperforms the baseline configuration. These findings highlight the importance of site-specific tuning and demonstrate the effectiveness of AI-based optimization for enhancing the adaptability and efficiency of multi-degree-of-freedom wave energy converters.