Application and Prospects of Digital Technologies in Operation and Maintenance of Deep-Sea Offshore Wind Turbines
Deep-sea offshore wind energy is a strategic frontier for renewable energy, but operation and maintenance (O&M) costs exceed 20% of the total life-cycle cost, driven by harsh marine environments and remote locations. This review analyzes the development trends of offshore wind turbines: large capacity and commercialization, deep-sea and floating configurations, and intelligent automation. It synthesizes data acquisition methods and advanced analytics for offshore wind turbine monitoring, and summarizes the application status of digital technologies—artificial intelligence, big data, and digital twins—in O&M of critical components. The review highlights that floating offshore wind turbines, predominantly semi-submersible, are essential for deep-sea exploitation, yet their O&M remains labor-intensive and hazardous. Digital technologies enable predictive maintenance, fault diagnosis, and real-time monitoring, with demonstrated improvements in efficiency and cost reduction. Key challenges include data scarcity, model interpretability, and integration with existing infrastructure. Future research should focus on autonomous inspection, multi-source data fusion, and digital twin frameworks for floating wind turbines. The findings provide a theoretical and practical basis for reducing O&M costs and enhancing the competitiveness of deep-sea offshore wind power.