Speaker
Description
Digital twin (DT) technology could significantly improve operation and maintenance of offshore wind turbine (OWT). Data integration, scalability, computational power demands, system integration, and real-time responsiveness to environmental dynamics are some of the major challenges to wider deployment. This paper presents a comprehensive evaluation of current DT applications in the OWT, along with an identification of the key operational and technological challenges. Addressing these challenges, a conceptual framework is proposed to guide future research and development efforts. The framework incorporates developments in big data analytics, multi-physics modeling, and machine learning, emphasizing multidisciplinary approaches. In order to ensure sustainable growth in offshore wind energy systems, this study offers a path for the methodical development and implementation of reliable DT solutions.
