Marine renewable energy: Progress, challenges, and pathways to scalable sustainability

Enwei Tang, Junyao Gao, Weiqing Huang and Yu Qian

Energy, 2025, vol. 335, issue C

Abstract: The escalating demand for electricity and increasingly adverse impacts of climate change necessitate urgent advancement in the development and utilization of Marine Renewable Energy (MRE). From 2011 to 2024, significant technological progress has been achieved in MRE exploitation. This study analyzes relevant studies during this 14-year period, providing a comprehensive review encompassing current developments, existing challenges, and optimization strategies, with particular emphasis on artificial intelligence (AI) applications and potential within this field. Among various MRE types, offshore wind energy demonstrates the most mature development level, while other energy forms exhibit relatively lower conversion efficiency and economic viability. The inherent power generation fluctuations and surplus electricity production in renewable energy systems can be effectively addressed through Hybrid Renewable Energy system (HRES) and novel energy storage technologies (hydrogen, ammonia, methanol). The high costs associated with MRE development have consistently been a primary constraint limiting progress in this field, while artificial intelligence (AI) demonstrates significant potential for reducing costs and enhancing power generation efficiency. However, in application scenarios lacking sufficient, high-quality data, it is necessary to combine methods such as first-principles modeling. Additionally, the integration of circular economy theory with life cycle assessment (LCA) applied to large-scale MRE power generation platforms or farms is another key optimization strategy. As future MRE power facilities inevitably trend toward higher efficiency and larger scales, investigating the environmental impacts of this progression on marine ecosystems constitutes essential work that cannot be overlooked in future research.

Keywords: Marine renewable energy; Hybrid power generation systems; AI; Hybrid methodology; Renewable energy integration (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:335:y:2025:i:c:s0360544225037259

DOI: 10.1016/j.energy.2025.138083

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