Abstract
Rotor blade icing negatively affects the operation of wind turbines and its electricity generation. The ice layer increases the blade masses, influences aerodynamics, and can fall off anytime during rotation with unpredictable trajectory and impact on ground. Due to this potential risk to human life, operation needs to be interrupted. Turbines equipped with blade heating face a downtime of some minutes to hours until removal of ice and restart of operation. Older turbines without heating system might stand still for a longer duration, resulting in significant loss of generated electricity. Modern Supervisory Control And Data Acquisition (SCADA) systems either detect icing by sophisticated measurement systems in the rotor blades, for example fiber Bragg grating devices, or predict the presence of ice by a combination of measured moisture, temperature and wind speed. Wireless acceleration sensors on the turbine tower may detect icing, monitor ice growth and even predict time of alert. The present work discusses the surveillance of an existing power plant by both wireless and wired acceleration sensors in parallel to the ice alerts of the turbine’s SCADA system and change of key parameters for indication of icing status.
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Acknowledgments
The authors want to thank the German Federal Ministry for Economic Affairs and Energy for funding the MISTRALWind project under grant number 0325795 (for details see https://www.zfp.tum.de/index.php?id=80) and the IM WIND project (for details see https://www.zfp.tum.de/forschungsprojekte/im-wind/). The authors also want to thank all project partners, particularly MAX BÖGL for their support during the measurement campaigns.
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B. Wondra performed the experiments of the wireless acceleration sensor system and wrote the main part of the manuscript. J. Rupfle processed and prepared the wire-based sensor data for subsequent FEM analysis. A. Emiroglu performed the FEM-model based simulations of the ice related impacts onto the wind turbine tower and wrote the referring simulation section. C. Grosse contributed by advises on evaluation methods.
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Wondra, B., Rupfle, J., Emiroglu, A., Grosse, C.U. (2023). Analysis of Icing on Wind Turbines by Combined Wireless and Wired Acceleration Sensor Monitoring. In: Rizzo, P., Milazzo, A. (eds) European Workshop on Structural Health Monitoring. EWSHM 2022. Lecture Notes in Civil Engineering, vol 253. Springer, Cham. https://doi.org/10.1007/978-3-031-07254-3_15
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DOI: https://doi.org/10.1007/978-3-031-07254-3_15
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