Sustainable Marine Structures for Offshore Wind Energy: Failure Modes and Risk Assessment of Turbine Blade Failures-A Case Study of the Dogger Bank Wind Farm


Abstract

Offshore wind energy plays a critical role in global decarbonization efforts, with large-scale projects being increasingly installed in deep-water and high-wind environments. However, the commissioning phase of offshore wind turbines presents unique operational vulnerabilities that remain relatively underexplored in existing risk assessment studies. This research applies Failure Mode and Effects Analysis (FMEA) to investigate the August 2024 failure of an offshore wind farm (North Sea, UK, at the Dogger Bank), one of the first documented commissioning-phase structural failures in a commercial-scale offshore wind project. Six failure modes were identified, evaluated, and ranked using Risk Priority Numbers (RPN) derived from Severity (S), Occurrence (O), and Detection (D) ratings on a 1–10 scale, as defined by established offshore FMEA practice. Blade structural fracture at the root section received the highest RPN of 378 (S = 9, O = 6, D = 7), reflecting catastrophic consequences, and the absence of real-time load monitoring during non-operational phases. Pitch system locking ranked second (RPN = 320, S = 8, O = 5, D = 8). Root cause analysis identifies the convergence of three primary factors: operational analysis protocols, active load regulation checks, control system limitations during commissioning, and the absence of real-time structural monitoring. A three-layer mitigation framework is proposed: (1) immediate weather-adaptive commissioning controls with threshold limits; (2) redundant pitch control with independent emergency power; and (3) AI-enhanced structural health monitoring during all transitional phases. The findings highlight the importance of phase-specific risk assessment for commissioning, maintenance, and decommissioning stages to reduce operational risk. The proposed FMEA-based approach provides a transferable methodology for risk identification and mitigation in large-scale offshore wind turbine systems.

References

Online ISSN: 2661-3158, Published by Nan Yang Academy of Sciences Pte. Ltd.