Articles | Volume 8, issue 12
https://doi.org/10.5194/wes-8-1893-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-8-1893-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Feedforward pitch control for a 15 MW wind turbine using a spinner-mounted single-beam lidar
Department of Wind and Energy Systems, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
Wind Energy Technology Institute, Flensburg University of Applied Sciences, Kanzleistraße 91–93, 24943 Flensburg, Germany
David Schlipf
Wind Energy Technology Institute, Flensburg University of Applied Sciences, Kanzleistraße 91–93, 24943 Flensburg, Germany
Alfredo Peña
Department of Wind and Energy Systems, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
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Nacelle lidars with different beam scanning locations and two types of systems are considered for inflow turbulence estimations using both numerical simulations and field measurements. The turbulence estimates from a sonic anemometer at the hub height of a Vestas V52 turbine are used as references. The turbulence parameters are retrieved using the radial variances and a least-squares procedure. The findings from numerical simulations have been verified by the analysis of the field measurements.
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Measuring the variability of the wind is essential to operate the wind turbines safely. Lidars of different configurations have been placed on the turbines’ nacelle to measure the inflow remotely. This work found that the multiple-beam lidar is the only one out of the three employed nacelle lidars that can give detailed information about the inflow variability. The other two commercial lidars, which have two and four beams, respectively, measure only the fluctuation in the along-wind direction.
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We carry out a probabilistic calibration of the Dynamic Wake Meandering (DWM) model using high-spatial- and high-temporal-resolution nacelle-based lidar measurements of the wake flow field. The experimental data were collected from the Scaled Wind Farm Technology (SWiFT) facility in Texas. The analysis includes the velocity deficit, wake-added turbulence, and wake meandering features under various inflow wind and atmospheric-stability conditions.
Davide Conti, Vasilis Pettas, Nikolay Dimitrov, and Alfredo Peña
Wind Energ. Sci., 6, 841–866, https://doi.org/10.5194/wes-6-841-2021, https://doi.org/10.5194/wes-6-841-2021, 2021
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We define two lidar-based procedures for improving the accuracy of wind turbine load assessment under wake conditions. The first approach incorporates lidar observations directly into turbulence fields serving as inputs for aeroelastic simulations; the second approach imposes lidar-fitted wake deficit time series on the turbulence fields. The uncertainty in the lidar-based power and load predictions is quantified for a variety of scanning configurations and atmosphere turbulence conditions.
Alfredo Peña, Branko Kosović, and Jeffrey D. Mirocha
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Yiyin Chen, David Schlipf, and Po Wen Cheng
Wind Energ. Sci., 6, 61–91, https://doi.org/10.5194/wes-6-61-2021, https://doi.org/10.5194/wes-6-61-2021, 2021
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Wind evolution is currently of high interest, mainly due to the development of lidar-assisted wind turbine control (LAC). Moreover, 4D stochastic wind field simulations can be made possible by integrating wind evolution into 3D simulations to provide a more realistic simulation environment for LAC. Motivated by these factors, we investigate the potential of Gaussian process regression in the parameterization of a two-parameter wind evolution model using data of two nacelle-mounted lidars.
Pedro Santos, Alfredo Peña, and Jakob Mann
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Preprint withdrawn
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We show that the vector of vertical flux of horizontal momentum and the vector of the mean vertical gradient of horizontal velocity are not aligned, based on Doppler wind lidar observations up to 500 m, both offshore and onshore. We illustrate that a mesoscale model output matches the observed mean wind speed and momentum fluxes well, but that this model output as well as idealized large-eddy simulations have deviations with the observations when looking at the turning of the wind.
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Short summary
A high-quality preview of the rotor-effective wind speed is a key element of the benefits of feedforward pitch control. We model a one-beam lidar in the spinner of a 15 MW wind turbine. The lidar rotates with the wind turbine and scans the inflow in a circular pattern, mimicking a multiple-beam lidar at a lower cost. We found that a spinner-based one-beam lidar provides many more control benefits than the one on the nacelle, which is similar to a four-beam nacelle lidar for feedforward control.
A high-quality preview of the rotor-effective wind speed is a key element of the benefits of...
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