This study proposes a health and performance optimization framework based on Particle Swarm Optimization (PSO) to improve the structural performance and energy utilization efficiency of coastal wind–wave energy harvesting systems. A semi-submersible floating wind turbine–wave energy integrated system is selected as the case study. The control variable method and numerical simulations are employed to determine the optimal structural parameters. Furthermore, a multi-scenario coordinated optimization model for wind, wave, energy storage, and load is established using the Velocity Pause Particle Swarm Optimization (VPPSO) algorithm. The optimal structural parameters are identified as an outer diameter of 16 m, an inner diameter of 8 m, a height of 8 m, and a draft of 3.5 m. The results show that VPPSO achieves faster convergence and better optimization performance compared to conventional algorithms. In the optimal scenario with wind–wave curtailment and energy storage participation, the minimum economic cost of 1780 CNY is achieved after 200 iterations. The proposed method provides theoretical guidance for the optimal design and efficient operation of coastal wind–wave energy harvesting systems.
Zhang et al. (Thu,) studied this question.