Offshore wind power digital twin modeling system for intelligent operation and maintenance applications

Abstract

Offshore wind power operates in a complex and harsh environment, while turbines continue to develop in the direction of large capacity and scale. Therefore, offshore wind power increasingly needs to reduce the overall operation and maintenance costs and improve the operation and control level of individual turbines and wind farms. Digital twin technology is intelligent, efficient and visual, and can provide intelligent services such as data analysis, fault diagnosis, performance evaluation and optimization suggestions for offshore wind power operation and maintenance. Relying on the digital twin five-dimensional model and its based prognostics health management method, a set of offshore wind power digital twin modeling system is deployed through the construction of data governance and maintenance fault recognition process. The system realizes the operation analysis and optimization of wind turbines, as well as the diagnosis and early warning of key equipment and field groups of wind turbines, which improves the management and control level of offshore wind power, improves the quality of operation and maintenance, optimizes the arrangement of offshore tasks, and reduces the cost of operation and maintenance. In the future, the system has great application prospects in predictive maintenance, quality improvement, efficient operation and maintenance of offshore wind power, providing support for the development of intelligent operation and maintenance of offshore wind power.