AI for Resilient Offshore Wind: Lessons from Project WILLOW
Rising curtailment—temporary reductions in turbine output to balance the grid—can accelerate structural fatigue and shorten offshore turbine lifespans. Project WILLOW offers a practical response: a data-driven, AI-managed strategy that adapts production based on each turbine’s health state rather than applying uniform limits across a farm.
Health-Aware Curtailment: Optimizing Turbine Life
WILLOW pioneers “health-aware curtailment,” where machine-learning models consume real-time structural health data to modulate loading on the most vulnerable units. The strategy prioritizes prevention of fatigue accumulation by selectively reducing generation on turbines showing increased stress or early signs of wear. That targeted approach lowers the risk of premature failures and can extend service life for individual assets, translating into lower lifecycle costs for operators.
Smart Technology Drives Predictive Maintenance
The system fuses SCADA streams with structural health monitoring sensors such as accelerometers and corrosion monitors, and applies supervised and physics-informed ML models to estimate remaining useful life. WILLOW converts noisy telemetry into probabilistic lifetime forecasts and actionable maintenance triggers. The result is a shift from calendar-based servicing to condition-driven interventions that reduce unplanned downtime and direct maintenance spend where it matters most.
Improving Grid Stability and Policy Foresight
Extending turbine lifetimes and making output more predictable strengthens grid reliability. Fewer forced outages and smoother generation profiles ease balancing needs and improve the economics of co-located storage by reducing extreme ramp events. For policymakers, WILLOW highlights pathways to update curtailment rules, reimbursements, and asset valuation frameworks so that health-aware controls and AI analytics are rewarded. Incorporating AI-based asset management into regulatory standards would encourage sustainable utilization of built infrastructure and more resilient energy systems.
Project WILLOW demonstrates how AI and integrated sensing can shift operational practice from uniform limits to measured, health-driven decisions, setting a technical and policy benchmark for the next generation of offshore wind asset management.
