AI and Intelligent Systems for Marine Energy

Marine energy, encompassing wave, tidal, ocean current, ocean thermal, and salinity gradient systems, holds immense potential to diversify the global clean energy mix and drive decarbonization. However, deploying these technologies at scale presents unique operational, ecological, and environmental challenges. Marine energy devices must operate reliably within stochastic, harsh, and rapidly changing hydrodynamic conditions while coexisting harmoniously with sensitive marine ecosystems and other ocean uses. In this context, artificial intelligence and intelligent systems emerge as transformative enablers. Beyond basic data processing, machine learning, physics-informed neural networks, reinforcement learning, and high-fidelity digital twins offer unprecedented capabilities. They allow for real-time adaptive control, autonomous health monitoring, and intelligent multi-hazard risk assessment. Furthermore, AI tools provide the predictive power needed to understand how marine energy installations interact with surrounding ocean dynamics, facilitating optimal marine spatial planning, minimizing ecological footprints, and ensuring system-level resilience under intensifying climate variability and extreme environmental forcing.While existing literature often treats device efficiency and structural design in isolation, realizing the full potential of ocean energy requires a holistic systems approach. This Research Topic aims to bridge engineering innovation and marine system sustainability by positioning AI and intelligent systems as pivotal enablers of adaptive, sustainable, and scalable marine energy solutions. We seek to assemble cutting-edge research that moves beyond narrow techno-economic metrics to address system-level sustainability outcomes. This includes deploying data-driven methodologies to model complex environmental interactions, anticipate cumulative hydrodynamic and ecological effects, optimize the multi-use of marine space (such as hybrid offshore energy, aquaculture, and coastal protection platforms), and ensure structural survivability during compound extreme events. By uniting interdisciplinary perspectives across computational intelligence, ocean engineering, and coastal sustainability, this collection aims to provide practical, scalable frameworks that accelerate sustainable marine energy transition.This Research Topic welcomes original research, reviews, mini-reviews, perspectives, and technology/code papers focusing on the novel application of AI, intelligent systems, and data-driven methods to ocean renewable energy. Topics of interest include, but are not limited to:- AI-driven resource characterization & environmental forecasting: Machine learning for high-resolution metocean forecasting, wave/tidal resource assessment, and climate-induced variability modeling.- Adaptive control & autonomous optimization: Reinforcement learning and real-time control algorithms to maximize energy capture, manage dynamic loads, and ensure device survivability in extreme sea states.- Intelligent digital twins & predictive asset management: Physics-informed digital twins, anomaly detection, condition monitoring, and predictive maintenance to enhance offshore reliability and reduce operational intervention.- Environmental interactions & ecological impact modeling: Data-driven assessment of marine energy systems on hydrodynamic circulation, sediment transport, benthic habitats, underwater acoustics, and marine fauna behavior.- Sustainable marine space utilization & hybrid systems: AI-enabled multi-use marine spatial planning, grid integration, and intelligent power management for coupled offshore platforms (e.g., co-located wind–wave–solar or aquaculture installations).- System-level resilience & life-cycle sustainability: Life-cycle assessment (LCA), circular economy modeling, and risk frameworks evaluating long-term environmental sustainability and climate adaptation of marine energy infrastructure.All submissions will undergo a rigorous peer-review process in accordance with the standards of Frontiers in Marine Science. We look forward to receiving your valuable contributions to this evolving field. Topic editors: Wenchi Ni, Yong Ma, Mingxin Li Source: https://www.frontiersin.org/research-topics/85783/ai-and-intelligent-systems-for-marine-energy