Presentations

Abstract

Grid-imposed curtailment, i.e. adjusting turbine output according to grid requirements, can lead to higher fatigue damage due to increased cyclic loads. Such curtailment reduces aerodynamic damping as well as introduces transient loading cycles from frequent power adjustments. As a result, structural vibrations are amplified and fatigue load accumulation accelerates. Balancing turbine lifespan with performance output and enabling operation beyond the design lifetime require innovative approaches in both structural health monitoring and operational strategy development. On one hand using SHM to track fatigue consumption over turbine operation can inform maintenance needs and supports end of life decisions. On the other hand, adaptive location specific control strategies, including derating and power boosting, can reduce stress on key components and optimize their lifespan throughout turbine life.  FlexiWind is a joint research project of Ramboll, the Fraunhofer Institute for Wind Energy Systems, and the University of Stuttgart as well as the associated partners GE Renewable Energy, Iberdrola Renewables and Beckhoff Automation, funded by the German Federal Ministry for Economic Affairs and Climate Action.   The FlexiWind project aims to explore the potential of flexible control strategies for Wind Turbine Generators (WTG) and wind farms, optimizing operations through advanced control methods. By integrating market data on electricity prices and targeted operational strategies, this approach ensures the efficient operation of individual turbines as well as the wind farm. A key focus is the individual control of each WTG to enhance grid regulation and manage fatigue loads.  FlexiWind aims to develop strategies that reduce operational costs, extend turbine lifespans, and improve the overall competitiveness of wind energy. Operational strategies like derating and power boosting are employed to actively manage turbine loads and optimize performance under varying conditions in real-time. As a result, the lifespan of turbines can be precisely influenced, even for continued operation beyond the design lifetime.  Two different approaches are selected to provide accurate assessments of fatigue damage in critical components, considering the effects of varying environmental and operational conditions to inform controller decisions, thus enabling optimized operation by balancing fatigue loads and power production. The physics-based approach employs finite element models to simulate wind turbine substructure behaviour under various load conditions. The AI-based approach utilizes real monitoring data from multiple turbines, including SCADA, acceleration, and strain gauge, with LSTM model trained on these datasets to predict fatigue damage. Both approaches result in a comprehensive lookup table detailing fatigue damage for different load case combinations, derating, and power boost. The research shows that current regulations focusing primarily on maximizing yield fall short on addressing optimized collective farm operation. Future approaches should prioritize flexible regulation to optimize operation, support grid stabilization, and extend the lifespan of turbine components while meeting grid requirements.