Articles | Volume 2, issue 1
https://doi.org/10.5194/wes-2-269-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/wes-2-269-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
24 May 2017
Research article |
| 24 May 2017
Wind field reconstruction from nacelle-mounted lidar short-range measurements
DTU Wind Energy, Roskilde, Denmark
David Schlipf
Stuttgart Wind Energy, University of Stuttgart, Stuttgart, Germany
Florian Haizmann
Stuttgart Wind Energy, University of Stuttgart, Stuttgart, Germany
Rozenn Wagner
DTU Wind Energy, Roskilde, Denmark
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Cited
37 citations as recorded by crossref.
- Characterization of wind turbine flow through nacelle-mounted lidars: a review S. Letizia et al. 10.3389/fmech.2023.1261017
- Turbulence statistics from three different nacelle lidars W. Fu et al. 10.5194/wes-7-831-2022
- Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals D. Conti et al. 10.5194/wes-6-841-2021
- Wind turbine power curve modelling under wake conditions using measurements from a spinner-mounted lidar A. Sebastiani et al. 10.1016/j.apenergy.2024.122985
- Novel rotor effective wind speed estimation method for light detection and ranging application B. Zhang et al. 10.1680/jener.21.00086
- Wind field reconstruction for the dispersion modeling of accidental chemical spills on complex geometry B. Wang et al. 10.1016/j.cjche.2019.02.029
- Updates on the OpenFAST Lidar Simulator F. Guo et al. 10.1088/1742-6596/2265/4/042030
- Data Reliability Enhancement for Wind-Turbine-Mounted Lidars N. Angelou & M. Sjöholm 10.3390/rs14133225
- Revealing inflow and wake conditions of a 6 MW floating turbine N. Angelou et al. 10.5194/wes-8-1511-2023
- Investigation of wind veer characteristics on complex terrain using ground-based lidar U. Tumenbayar & K. Ko 10.14710/ijred.2023.56352
- An Optimized Sensing Arrangement in Wind Field Reconstruction Using CFD and POD S. Sun et al. 10.1109/TSTE.2019.2961381
- Quantification and correction of motion influence for nacelle-based lidar systems on floating wind turbines M. Gräfe et al. 10.5194/wes-8-925-2023
- Prediction of wind fields in mountains at multiple elevations using deep learning models H. Gao et al. 10.1016/j.apenergy.2023.122099
- Wind field reconstruction from lidar measurements at high-frequency using machine learning C. Stock-Williams et al. 10.1088/1742-6596/1102/1/012003
- Experimental investigation on power performance testing using nacelle lidar measurements over excavated terrain U. Tumenbayar et al. 10.1016/j.jweia.2021.104671
- Wake detection in the turbine inflow using nacelle lidars D. Held et al. 10.1088/1742-6596/1102/1/012005
- Research on the Characteristics of Urban Building Cluster Wind Field Based on UAV Wind Measurement O. Pu et al. 10.3390/buildings13123109
- Wind field reconstruction using nacelle based lidar measurements for floating wind turbines M. Gräfe et al. 10.1088/1742-6596/2265/4/042022
- Wind speed measurement for absolute power curve determination from induction zone lidar measurements C. Slinger et al. 10.1088/1742-6596/1618/3/032027
- Research challenges and needs for the deployment of wind energy in hilly and mountainous regions A. Clifton et al. 10.5194/wes-7-2231-2022
- Evaluation of the “fan scan” based on three combined nacelle lidars for advanced wind field characterisation P. Meyer & J. Gottschall 10.1088/1742-6596/2265/2/022107
- Power-generation enhancements and upstream flow properties of turbines in unsteady inflow conditions N. Wei & J. Dabiri 10.1017/jfm.2023.454
- Reconstruction of Three-Dimensional Dynamic Wind-Turbine Wake Wind Fields with Volumetric Long-Range Wind Doppler LiDAR Measurements . Beck & . Kühn 10.3390/rs11222665
- Reconstruction of turbulent flow fields from lidar measurements using large-eddy simulation P. Bauweraerts & J. Meyers 10.1017/jfm.2020.805
- Real-time three dimensional wind field reconstruction from nacelle LiDAR measurements F. Guillemin et al. 10.1088/1742-6596/1037/3/032037
- From wind to loads: wind turbine site-specific load estimation with surrogate models trained on high-fidelity load databases N. Dimitrov et al. 10.5194/wes-3-767-2018
- IEA Wind Task 32: Best Practices for the Certification of Lidar-Assisted Control Applications D. Schlipf et al. 10.1088/1742-6596/1102/1/012010
- Modeling Uncertainties of Wind Field Reconstruction Using Lidar D. Schlipf et al. 10.1088/1742-6596/1452/1/012088
- A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines E. Mahmoodi et al. 10.3390/en16155710
- Reconstruction of Unsteady Wind Field Based on CFD and Reduced-Order Model G. Zhang & S. Liu 10.3390/math11102223
- The induction zone/factor and sheared inflow: A linear connection? A. Meyer Forsting et al. 10.1088/1742-6596/1037/7/072031
- Lower Order Description and Reconstruction of Sparse Scanning Lidar Measurements of Wind Turbine Inflow Using Proper Orthogonal Decomposition A. Kidambi Sekar et al. 10.3390/rs14112681
- Residual-connected physics-informed neural network for anti-noise wind field reconstruction R. Tian et al. 10.1016/j.apenergy.2023.122439
- IEA Wind Task 32: Wind Lidar Identifying and Mitigating Barriers to the Adoption of Wind Lidar A. Clifton et al. 10.3390/rs10030406
- Wind turbine load validation using lidar‐based wind retrievals N. Dimitrov et al. 10.1002/we.2385
- Aeroelastic load validation in wake conditions using nacelle-mounted lidar measurements D. Conti et al. 10.5194/wes-5-1129-2020
- Comparison of different measurement methods for a nacelle-based lidar power curve M. Hofsäß et al. 10.1088/1742-6596/1037/5/052034
37 citations as recorded by crossref.
- Characterization of wind turbine flow through nacelle-mounted lidars: a review S. Letizia et al. 10.3389/fmech.2023.1261017
- Turbulence statistics from three different nacelle lidars W. Fu et al. 10.5194/wes-7-831-2022
- Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals D. Conti et al. 10.5194/wes-6-841-2021
- Wind turbine power curve modelling under wake conditions using measurements from a spinner-mounted lidar A. Sebastiani et al. 10.1016/j.apenergy.2024.122985
- Novel rotor effective wind speed estimation method for light detection and ranging application B. Zhang et al. 10.1680/jener.21.00086
- Wind field reconstruction for the dispersion modeling of accidental chemical spills on complex geometry B. Wang et al. 10.1016/j.cjche.2019.02.029
- Updates on the OpenFAST Lidar Simulator F. Guo et al. 10.1088/1742-6596/2265/4/042030
- Data Reliability Enhancement for Wind-Turbine-Mounted Lidars N. Angelou & M. Sjöholm 10.3390/rs14133225
- Revealing inflow and wake conditions of a 6 MW floating turbine N. Angelou et al. 10.5194/wes-8-1511-2023
- Investigation of wind veer characteristics on complex terrain using ground-based lidar U. Tumenbayar & K. Ko 10.14710/ijred.2023.56352
- An Optimized Sensing Arrangement in Wind Field Reconstruction Using CFD and POD S. Sun et al. 10.1109/TSTE.2019.2961381
- Quantification and correction of motion influence for nacelle-based lidar systems on floating wind turbines M. Gräfe et al. 10.5194/wes-8-925-2023
- Prediction of wind fields in mountains at multiple elevations using deep learning models H. Gao et al. 10.1016/j.apenergy.2023.122099
- Wind field reconstruction from lidar measurements at high-frequency using machine learning C. Stock-Williams et al. 10.1088/1742-6596/1102/1/012003
- Experimental investigation on power performance testing using nacelle lidar measurements over excavated terrain U. Tumenbayar et al. 10.1016/j.jweia.2021.104671
- Wake detection in the turbine inflow using nacelle lidars D. Held et al. 10.1088/1742-6596/1102/1/012005
- Research on the Characteristics of Urban Building Cluster Wind Field Based on UAV Wind Measurement O. Pu et al. 10.3390/buildings13123109
- Wind field reconstruction using nacelle based lidar measurements for floating wind turbines M. Gräfe et al. 10.1088/1742-6596/2265/4/042022
- Wind speed measurement for absolute power curve determination from induction zone lidar measurements C. Slinger et al. 10.1088/1742-6596/1618/3/032027
- Research challenges and needs for the deployment of wind energy in hilly and mountainous regions A. Clifton et al. 10.5194/wes-7-2231-2022
- Evaluation of the “fan scan” based on three combined nacelle lidars for advanced wind field characterisation P. Meyer & J. Gottschall 10.1088/1742-6596/2265/2/022107
- Power-generation enhancements and upstream flow properties of turbines in unsteady inflow conditions N. Wei & J. Dabiri 10.1017/jfm.2023.454
- Reconstruction of Three-Dimensional Dynamic Wind-Turbine Wake Wind Fields with Volumetric Long-Range Wind Doppler LiDAR Measurements . Beck & . Kühn 10.3390/rs11222665
- Reconstruction of turbulent flow fields from lidar measurements using large-eddy simulation P. Bauweraerts & J. Meyers 10.1017/jfm.2020.805
- Real-time three dimensional wind field reconstruction from nacelle LiDAR measurements F. Guillemin et al. 10.1088/1742-6596/1037/3/032037
- From wind to loads: wind turbine site-specific load estimation with surrogate models trained on high-fidelity load databases N. Dimitrov et al. 10.5194/wes-3-767-2018
- IEA Wind Task 32: Best Practices for the Certification of Lidar-Assisted Control Applications D. Schlipf et al. 10.1088/1742-6596/1102/1/012010
- Modeling Uncertainties of Wind Field Reconstruction Using Lidar D. Schlipf et al. 10.1088/1742-6596/1452/1/012088
- A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines E. Mahmoodi et al. 10.3390/en16155710
- Reconstruction of Unsteady Wind Field Based on CFD and Reduced-Order Model G. Zhang & S. Liu 10.3390/math11102223
- The induction zone/factor and sheared inflow: A linear connection? A. Meyer Forsting et al. 10.1088/1742-6596/1037/7/072031
- Lower Order Description and Reconstruction of Sparse Scanning Lidar Measurements of Wind Turbine Inflow Using Proper Orthogonal Decomposition A. Kidambi Sekar et al. 10.3390/rs14112681
- Residual-connected physics-informed neural network for anti-noise wind field reconstruction R. Tian et al. 10.1016/j.apenergy.2023.122439
- IEA Wind Task 32: Wind Lidar Identifying and Mitigating Barriers to the Adoption of Wind Lidar A. Clifton et al. 10.3390/rs10030406
- Wind turbine load validation using lidar‐based wind retrievals N. Dimitrov et al. 10.1002/we.2385
- Aeroelastic load validation in wake conditions using nacelle-mounted lidar measurements D. Conti et al. 10.5194/wes-5-1129-2020
- Comparison of different measurement methods for a nacelle-based lidar power curve M. Hofsäß et al. 10.1088/1742-6596/1037/5/052034
Latest update: 18 Apr 2024
Short summary
The paper describes an innovative methodology to extract useful wind field estimates from remote sensing instruments – called lidars – mounted on the nacelle of a wind turbine. We used lidar measurements at multiple distances upstream and close to the wind turbine rotor in order to retrieve free-stream wind characteristics. The methodology and the obtained results open new paths to assess the power performance of wind turbines, which is essential to ensure financially viable wind farm projects.
The paper describes an innovative methodology to extract useful wind field estimates from remote...
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