Evaluation of lidar-assisted wind turbine control under various turbulence characteristics
<p>Lidar systems installed on the nacelle of wind turbines can provide a preview of incoming turbulent wind. Lidar-assisted control (LAC) allows the turbine controller to react to changes in the wind before they affect the wind turbine. Currently, the most proven LAC technique is the collectiv...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-02-01
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| Series: | Wind Energy Science |
| Online Access: | https://wes.copernicus.org/articles/8/149/2023/wes-8-149-2023.pdf |
| _version_ | 1811168142837153792 |
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| author | F. Guo D. Schlipf P. W. Cheng |
| author_facet | F. Guo D. Schlipf P. W. Cheng |
| author_sort | F. Guo |
| collection | DOAJ |
| description | <p>Lidar systems installed on the nacelle of wind turbines can provide a preview of incoming turbulent wind. Lidar-assisted control (LAC) allows the turbine controller to react to changes in the wind before they affect the wind turbine. Currently, the most proven LAC technique is the collective pitch feedforward control, which has been found to be beneficial for load reduction. In literature, the benefits were mainly investigated using standard turbulence parameters suggested by the IEC 61400-1 standard and assuming Taylor's frozen hypothesis (the turbulence measured by the lidar propagates unchanged to the rotor). In reality, the turbulence spectrum and the spatial coherence change by the atmospheric stability conditions. Also, Taylor's frozen hypothesis does not take into account the coherence decay of turbulence in the longitudinal direction. In this work, we consider three atmospheric stability classes, unstable, neutral, and stable, and generate four-dimensional stochastic turbulence fields based on two models: the Mann model and the Kaimal model. The generated four-dimensional stochastic turbulence fields include realistic longitudinal coherence, thus avoiding assuming Taylor's frozen hypothesis. The Reference Open-Source Controller (ROSCO) by NREL is used as the baseline feedback-only controller. A reference lidar-assisted controller is developed and used to evaluate the benefit of LAC. Considering the NREL 5.0 <span class="inline-formula">MW</span> reference wind turbine and a typical four-beam pulsed lidar system, it is found that the filter design of the LAC is not sensitive to the turbulence characteristics representative of the investigated atmospheric stability classes. The benefits of LAC are analyzed using the aeroelastic tool OpenFAST. According to the simulations, LAC's benefits are mainly the reductions in rotor speed variation (up to 40 %), tower fore–aft bending moment (up to 16.7 %), and power variation (up to 20 %). This work reveals that the benefits of LAC can depend on the turbulence models, the turbulence parameters, and the mean wind speed.</p> |
| first_indexed | 2024-04-10T16:21:08Z |
| format | Article |
| id | doaj.art-3a5eec0b8bcc4994a4c6b2a2da60d519 |
| institution | Directory Open Access Journal |
| issn | 2366-7443 2366-7451 |
| language | English |
| last_indexed | 2024-04-10T16:21:08Z |
| publishDate | 2023-02-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Wind Energy Science |
| spelling | doaj.art-3a5eec0b8bcc4994a4c6b2a2da60d5192023-02-09T12:57:13ZengCopernicus PublicationsWind Energy Science2366-74432366-74512023-02-01814917110.5194/wes-8-149-2023Evaluation of lidar-assisted wind turbine control under various turbulence characteristicsF. Guo0D. Schlipf1P. W. Cheng2Wind Energy Technology Institute, Flensburg University of Applied Sciences, Kanzleistraße 91–93, 24943 Flensburg, GermanyWind Energy Technology Institute, Flensburg University of Applied Sciences, Kanzleistraße 91–93, 24943 Flensburg, GermanyStuttgart Wind Energy (SWE), Institute of Aircraft Design, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany<p>Lidar systems installed on the nacelle of wind turbines can provide a preview of incoming turbulent wind. Lidar-assisted control (LAC) allows the turbine controller to react to changes in the wind before they affect the wind turbine. Currently, the most proven LAC technique is the collective pitch feedforward control, which has been found to be beneficial for load reduction. In literature, the benefits were mainly investigated using standard turbulence parameters suggested by the IEC 61400-1 standard and assuming Taylor's frozen hypothesis (the turbulence measured by the lidar propagates unchanged to the rotor). In reality, the turbulence spectrum and the spatial coherence change by the atmospheric stability conditions. Also, Taylor's frozen hypothesis does not take into account the coherence decay of turbulence in the longitudinal direction. In this work, we consider three atmospheric stability classes, unstable, neutral, and stable, and generate four-dimensional stochastic turbulence fields based on two models: the Mann model and the Kaimal model. The generated four-dimensional stochastic turbulence fields include realistic longitudinal coherence, thus avoiding assuming Taylor's frozen hypothesis. The Reference Open-Source Controller (ROSCO) by NREL is used as the baseline feedback-only controller. A reference lidar-assisted controller is developed and used to evaluate the benefit of LAC. Considering the NREL 5.0 <span class="inline-formula">MW</span> reference wind turbine and a typical four-beam pulsed lidar system, it is found that the filter design of the LAC is not sensitive to the turbulence characteristics representative of the investigated atmospheric stability classes. The benefits of LAC are analyzed using the aeroelastic tool OpenFAST. According to the simulations, LAC's benefits are mainly the reductions in rotor speed variation (up to 40 %), tower fore–aft bending moment (up to 16.7 %), and power variation (up to 20 %). This work reveals that the benefits of LAC can depend on the turbulence models, the turbulence parameters, and the mean wind speed.</p>https://wes.copernicus.org/articles/8/149/2023/wes-8-149-2023.pdf |
| spellingShingle | F. Guo D. Schlipf P. W. Cheng Evaluation of lidar-assisted wind turbine control under various turbulence characteristics Wind Energy Science |
| title | Evaluation of lidar-assisted wind turbine control under various turbulence characteristics |
| title_full | Evaluation of lidar-assisted wind turbine control under various turbulence characteristics |
| title_fullStr | Evaluation of lidar-assisted wind turbine control under various turbulence characteristics |
| title_full_unstemmed | Evaluation of lidar-assisted wind turbine control under various turbulence characteristics |
| title_short | Evaluation of lidar-assisted wind turbine control under various turbulence characteristics |
| title_sort | evaluation of lidar assisted wind turbine control under various turbulence characteristics |
| url | https://wes.copernicus.org/articles/8/149/2023/wes-8-149-2023.pdf |
| work_keys_str_mv | AT fguo evaluationoflidarassistedwindturbinecontrolundervariousturbulencecharacteristics AT dschlipf evaluationoflidarassistedwindturbinecontrolundervariousturbulencecharacteristics AT pwcheng evaluationoflidarassistedwindturbinecontrolundervariousturbulencecharacteristics |