Robust estimation and diagnosis of wind turbine pitch misalignments at a wind farm level
Ver/ Abrir
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7034
comunitat-uji-handle3:10234/8619
comunitat-uji-handle4:
INVESTIGACIONMetadatos
Título
Robust estimation and diagnosis of wind turbine pitch misalignments at a wind farm levelFecha de publicación
2020-02-28Editor
ElsevierISSN
0960-1481; 1879-0682Cita bibliográfica
SALES-SETIÉN, Ester; PEÑARROCHA-ALÓS, Ignacio. Robust estimation and diagnosis of wind turbine pitch misalignments at a wind farm level. Renewable Energy, 2020, vol. 146, p. 1746-1765Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.sciencedirect.com/science/article/abs/pii/S096014811931153XVersión
info:eu-repo/semantics/acceptedVersionPalabras clave / Materias
Resumen
Wind turbine pitch misalignments provoke aerodynamic asymmetries which cause severe damage to the turbine. Hence,
it is of interest to develop fault tolerant strategies to cope with pitch misalignments. Fault tolerant ... [+]
Wind turbine pitch misalignments provoke aerodynamic asymmetries which cause severe damage to the turbine. Hence,
it is of interest to develop fault tolerant strategies to cope with pitch misalignments. Fault tolerant strategies require the information regarding the diagnosis and the estimation of the faults. However, most existing works focus only on open-loop
misalignment diagnosis and do not provide robust fault estimates. In this work, we present a novel strategy to both estimate
and diagnose pitch misalignments. The proposed strategy is developed at a wind farm level and it exploits altogether the
information provided by the temporal and spatial relations of the turbines in the farm. Fault estimation is first addressed with
a closed-loop switched observer. This observer is robust against disturbances and it adapts to the varying conditions along the wind turbine operation range. Fault diagnosis is then achieved via statistical-based decision mechanisms with adaptive
thresholds. Both the observer and the decision mechanisms are designed to guarantee the desired performance. Introducing
some restrictions over the number of simultaneous faulty turbines in the farm, the proposed approach is ameliorated via a
bank of the aforementioned observers and decision mechanisms. Finally, the strategies are tested using a well-known wind
farm benchmark. [-]
Publicado en
Renewable Energy, 2020, vol. 146, p. 1746-1765Proyecto de investigación
This work has been supported by the Spanish Ministry of Edu-cation, Culture and Sports (Grant FPU14/01592), the Spanish Min-istry of Economy, Industry and Competitiveness (Project TEC2015-69155-R) and the Universitat Jaume I of Castell o (ProjectP11B2015-42)Derechos de acceso
info:eu-repo/semantics/openAccess
Aparece en las colecciones
- ESID_Articles [472]
El ítem tiene asociados los siguientes ficheros de licencia: