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Wind turbine loads induced by terrain and wakes: An experimental study through vibration analysis and Computational Fluid Dynamics

Articolo
Data di Pubblicazione:
2017
Citazione:
Wind turbine loads induced by terrain and wakes: An experimental study through vibration analysis and Computational Fluid Dynamics / Castellani, F., Buzzoni, M., Astolfi, D., D’Elia, G., Dalpiaz, G., Terzi, L.. - In: ENERGIES. - ISSN 1996-1073. - 10:11(2017), pp. 1839-1-1839-19. [10.3390/en10111839]
Abstract:
A wind turbine is a very well-known archetype of energy conversion system working at non-stationary regimes. Despite this, a deep mechanical comprehension of wind turbines operating in complicated conditions is still challenging, especially as regards the analysis of experimental data. In particular, wind turbines in complex terrain represent a very valuable testing ground because of the possible combination of wake effects among nearby turbines and flow accelerations caused by the terrain morphology. For these reasons, in this work, a cluster of four full-scale wind turbines from a very complex site is studied. The object of investigation is vibrations, at the level of the structure (tower) and drive-train. Data collected by the on-board condition monitoring system are analyzed and interpreted in light of the knowledge of wind conditions and operating parameters collected by the Supervisory Control And Data Acquisition (SCADA). A free flow Computational Fluid Dynamics (CFD) simulation is also performed, and it allows one to better interpret the vibration analysis. The main outcome is the interpretation of how wakes and flow turbulences appear in the vibration signals, both at the structural level and at the drive-train level. Therefore, this wind to gear approach builds a connection between flow phenomena and mechanical phenomena in the form of vibrations, representing a precious tool for assessing loads in different working conditions.
Tipologia CRIS:
Articolo su rivista
Keywords:
wind energy; wind turbine; wakes; vibration analysis; supervisory control and data acquisition; condition monitoring
Elenco autori:
Castellani, Francesco; Buzzoni, Marco; Astolfi, Davide; D’Elia, Gianluca; Dalpiaz, Giorgio; Terzi, Ludovico
Autori di Ateneo:
D'ELIA GIANLUCA
Link alla scheda completa:
https://iris.unimore.it/handle/11380/1295063
Link al Full Text:
https://iris.unimore.it//retrieve/handle/11380/1295063/466929/energies-10-01839-v2.pdf
Pubblicato in:
ENERGIES
Journal
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URL

https://www.mdpi.com/1996-1073/10/11/1839
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