The wind preview provided by a nacelle-based lidar system allows the wind turbine controller to react to the wind disturbance prior to its impact on the turbine. This technology, commonly referred to as lidar-assisted wind turbine control, has been shown to be beneficial in reducing wind turbine structural loads. The wind preview quality defines how the lidar estimated disturbance is correlated with the actual one. In practice, the preview quality can vary following the change in atmospheric conditions and lidar operating states.When assessing the benefits of lidar-assisted control, previous studies mainly focused on the freestream turbulence where the turbine wake has not been included. In reality, wind turbines sometimes operate within the wake caused by upstream situated turbines, which happens more often in a narrowly spaced wind farm. Based on existing literature, the wake turbulence has three main phenomena compared with the freestream turbulence, i.e. (1) the reduced wind speed region (wake deficit), (2) the meandering (wake deficit moves in the lateral and vertical directions), and (3) the smaller-scale added turbulence caused by the interaction between rotor and the flow. The extent to which these phenomena affect the quality of lidar wind preview still needs to be investigated.In this paper, we use the dynamic wake meandering model, which covers the three wake characteristics mentioned above, and analyze its impact on lidar wind preview qualities. The most representative turbine layout where two turbines lie in a row will be considered. Frequency-domain analysis will be carried out to assess the measurement coherence of the lidar and the results will be compared to the freestream case.

Investigation on the wind preview quality for lidar-assisted wind turbine control under wake conditions

Schlipf D.;Zhang Z.;Cheng P. W.
2022-01-01

Abstract

The wind preview provided by a nacelle-based lidar system allows the wind turbine controller to react to the wind disturbance prior to its impact on the turbine. This technology, commonly referred to as lidar-assisted wind turbine control, has been shown to be beneficial in reducing wind turbine structural loads. The wind preview quality defines how the lidar estimated disturbance is correlated with the actual one. In practice, the preview quality can vary following the change in atmospheric conditions and lidar operating states.When assessing the benefits of lidar-assisted control, previous studies mainly focused on the freestream turbulence where the turbine wake has not been included. In reality, wind turbines sometimes operate within the wake caused by upstream situated turbines, which happens more often in a narrowly spaced wind farm. Based on existing literature, the wake turbulence has three main phenomena compared with the freestream turbulence, i.e. (1) the reduced wind speed region (wake deficit), (2) the meandering (wake deficit moves in the lateral and vertical directions), and (3) the smaller-scale added turbulence caused by the interaction between rotor and the flow. The extent to which these phenomena affect the quality of lidar wind preview still needs to be investigated.In this paper, we use the dynamic wake meandering model, which covers the three wake characteristics mentioned above, and analyze its impact on lidar wind preview qualities. The most representative turbine layout where two turbines lie in a row will be considered. Frequency-domain analysis will be carried out to assess the measurement coherence of the lidar and the results will be compared to the freestream case.
2022
Proceedings of the American Control Conference
978-1-6654-5196-3
File in questo prodotto:
File Dimensione Formato  
Investigation_on_the_wind_preview_quality_for_lidar-assisted_wind_turbine_control_under_wake_conditions.pdf

Accesso riservato

Descrizione: paper
: Publisher’s version
Dimensione 2.26 MB
Formato Adobe PDF
2.26 MB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1233674
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact