TwinsTower

The next-generation modular energy island (MODENERLAND) offers a promising solution to unlock the plentiful Aeolian source at deep-waters. Meanwhile, high-speed wind and strong corrosivity in the harsh marine environment, along with increasing dynamics, escalate corrosion-fatigue (C-F) deterioration of wind turbine structures on MODENERLAND notably. Real-time monitoring of external loads and structural response of wind turbine structures becomes gradually possible with advancing SHM tools such as LiDAR, computational vision, etc. This offers a promising possibility for digital twin (DT) of ageing wind turbine structures. Accordingly, an effective and dynamic prognosis approach is deemed essential to achieve a better understanding of the up-to-date and future deterioration state, by integrating the site-specific data in a DT-based manner. Facing the above concerns, the TwinsTower action is initiated to develop new and practical contributions towards a better understanding of the corrosion fatigue of wind towers in modular energy islands, with both the physical model, inspection result and monitoring data integrated. The project devotes to: (i) establish an integrated corrosion fatigue prediction model for wind towers in the modular energy island; (ii) construct a digital twins-based prognosis approach for wind towers in modular energy islands, with the monitoring and inspection result integrated. The work aims at novel insights into the deterioration of wind turbine structures, by integrating measured data and theoretical models via a digital twin-based approach. Not only does this presentation highlight the escalating deterioration issue in wind turbine structures, but it also offers a novel basis for crucial insights into the digital twin-based operation and maintenance (O&M) by integrating models and data from various sources.