Digital Twin‐Based Deterioration Prognosis of Steel Wind Turbine Towers in Modular Energy Islands

The Modular Energy Island (MEI) 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 the corrosion‐fatigue (C‐F) deterioration issue of steel wind turbine towers on MEIs notably. Thus, a better understanding of the C‐F states is of particular concern to maximize the lifetime power generation and minimize operational costs. This study aims to provide novel insights into the C‐F deterioration states of wind turbine towers by integrating the material test data, site measurement, and multi‐physics simulation based on the concept of digital twins. The DTU 10MW reference turbine has been selected as an engineering prototype. Based on the in‐situ wind‐wave data, the structural response of the steel turbine tower at critical details is predicted via multi‐physics simulations and accordingly, stress spectra are constructed. Besides, the corrosion rate is estimated from material test data and the site‐specific climate conditions. Then, a probabilistic C‐F model is established for the deterioration state of critical components in the tower by incorporating the derived stress spectra and corrosion rate. Not only does this study highlight the escalating C‐F deterioration issue in steel wind turbine towers, but it also offers a novel basis for crucial insights into the digital twin‐based operation and maintenance (O&M) of the next‐generation MEIs by integrating models and data from various sources.