A digital twinning framework for intelligent operation and maintenance of floating offshore wind turbines under corrosion-fatigue

Abstract

Floating offshore wind turbines (FOWTs) present a significant opportunity for harnessing deep-water wind resources, yet their operational longevity is challenged by the harsh marine environment, particularly through corrosion fatigue (C-F) in critical structural connections like ring-flanges. This paper introduces an intelligent Digital Twin (DT) framework designed to mitigate C-F and enhance the operation and maintenance (O&M) of FOWT structures by enabling adaptive control strategies. The framework integrates data from Supervisory Control and Data Acquisition (SCADA) and Structural Health Monitoring (SHM) systems with multi-physics simulations and a time-variant probability-stress-life (t-PSN) C-F model. A case study on the IEA 15MW reference FOWT, under site-specific environmental conditions, was carried out to demonstrate the DT's application. Three distinct adaptive control strategies (CS1-Baseline, CS2-Rated speed 7 m/s, and CS3-Rated speed 9 m/s) were evaluated for their impact on the C-F reliability of ring-flange connections. Results indicate that adaptive control strategies CS2 and CS3 significantly extend the reliable operational lifespan beyond 20 years, compared to approximately 15 years under the baseline CS1, before reaching critical reliability thresholds. For instance, at 20 years, ring-flange reliability indices under CS2 remained robust (approximate to 3.5-3.7). Also, the change in control strategies also results in different level of compromise in power generation. The study underscores the DT's capability to predict C-F progression, inform the selection of damage-mitigating control strategies, and provide a foundation for proactive, condition-based maintenance, thereby contributing to enhanced resilient and cost-effective FOWT operations.