A bibliometric review of hybrid offshore renewable energy and the optimization methods

This study presents a comprehensive bibliometric review of hybrid offshore renewable energy sources (HORES) and their optimization methods over the past 24 years. The analysis highlights a significant increase in global publications on HORES, reflecting increasing demand on the resource utilization and environmental sustainability. Specifically, the number of publications on HORES has increased by approximately 70% from 2000 to 2023, indicating rising interest and research activity in this area. The findings show that classical optimization methods are reliable for optimization. However, the methods face limitations due to restricted parameters. In comparison, artificial intelligence (AI) algorithms provide optimal solutions with rapid convergence but require substantial computational resources. Hybrid optimization methods combine the strengths of both classical and AI methods. This methods are evolving as a promising solution to these challenges. Potential research directions include the enhancement of hybrid optimization methods, integrated engineering collaboration, mixing of emerging technologies, and conducting long-term impact studies are proposed. These efforts are crucial for advancing the field of ORES and achieving sustainable power production.