Abstract
Harnessing energy from ocean waves presents a promising solution to combating global climate change in the marine environment, significantly contributing to mitigation efforts, climate enrichment, and decarbonization. This study offers a comprehensive overview of wave energy conversion technologies, focusing on point absorber wave energy converters (PA-WECs) through scientometric and systematic analysis from 2015 to 2024. Data were collected from the Web of Science and Scopus databases, analyzing 1519 research articles and 1518 patents. The study identifies six major knowledge domains based on co-occurring keywords, keyword clusters, and knowledge bursts: wave characteristics, buoy shape optimization, power take-off system design, experimental optimization, WEC arrays, and control strategies. Key findings reveal that oscillating water column technology leads the field with 788 publications and 1027 patents. In contrast, PA-WECs show considerable innovation potential, with 611 publications and 320 patents, particularly in buoy optimization and control strategies. The study includes a gap analysis, identifying critical areas for further research, such as integrating artificial intelligence (AI) and machine learning for improved control and monitoring of PA-WEC systems. Challenges like the need for accurate wave climate data, optimized floater geometry, and robust control strategies in extreme weather conditions are addressed. The findings suggest that integrating AI, remote sensing, and machine learning can enhance PA-WEC efficiency, supporting the development of sustainable energy solutions. This study advances the UN SDGs by fostering clean energy innovation (SDG-7), climate resilience (SDG-13), and sustainable use of the oceans (SDG-14).