Version 1
: Received: 10 September 2024 / Approved: 11 September 2024 / Online: 11 September 2024 (16:17:03 CEST)
How to cite:
Pazhouhan, M.; Karimi Mazraeshahi, A.; Jahanbakht, M.; Rezanejad, K.; Rohban, M. H. Wave and Tidal Energy: A Patent Landscape Study. Preprints2024, 2024090921. https://doi.org/10.20944/preprints202409.0921.v1
Pazhouhan, M.; Karimi Mazraeshahi, A.; Jahanbakht, M.; Rezanejad, K.; Rohban, M. H. Wave and Tidal Energy: A Patent Landscape Study. Preprints 2024, 2024090921. https://doi.org/10.20944/preprints202409.0921.v1
Pazhouhan, M.; Karimi Mazraeshahi, A.; Jahanbakht, M.; Rezanejad, K.; Rohban, M. H. Wave and Tidal Energy: A Patent Landscape Study. Preprints2024, 2024090921. https://doi.org/10.20944/preprints202409.0921.v1
APA Style
Pazhouhan, M., Karimi Mazraeshahi, A., Jahanbakht, M., Rezanejad, K., & Rohban, M. H. (2024). Wave and Tidal Energy: A Patent Landscape Study. Preprints. https://doi.org/10.20944/preprints202409.0921.v1
Chicago/Turabian Style
Pazhouhan, M., Kourosh Rezanejad and Mohammad H. Rohban. 2024 "Wave and Tidal Energy: A Patent Landscape Study" Preprints. https://doi.org/10.20944/preprints202409.0921.v1
Abstract
Wave and tidal energy, recognized as vital renewable resources, harness the ocean's kinetic and potential power. This study aims to provide an in-depth patent analysis of the technological landscape within these sectors. We applied a dual approach: first, a descriptive analysis was conducted to explore patent publication trends, technology lifecycle stages, patent activity by country, top assignees, and IPC classifications. Our analysis provided a detailed overview of the sector's growth and the key players involved. Second, we utilized topic modeling, specifically BERTopic enhanced with large language models (LLMs), to identify and fine-tune key technolog-ical themes within the patent data. In this study, we identified seven distinct clusters each for wave and tidal energy using this approach. This method led to a novel categorization of the pa-tents, revealing latent themes within the patent data. Although our categorization differs from traditional methods, it provides deeper insights into the thematic focus of the patents, highlight-ing emerging trends and areas of innovation within wave and tidal energy technologies to better exploit and optimize ocean energy conversion infrastructure.
Keywords
Wave Energy; Tidal Energy; Patent Analysis; Topic Modeling; Large Language Models; BERTopic
Subject
Engineering, Marine Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.