Abstract
Nacelle lidars are an attractive alternative to meteorological masts for power performance testing in complex terrain, because of the ease of deployment. This report presents the comparison of wind speed and power curve measurements using a nacelle-mounted 4-beam Wind Iris lidar to the standard mast-mounted cup anemometer measurements, in a complex site. The model-fitting wind field reconstruction technique using measurements between 0.5D and 1D upstream, which has previously been demonstrated in flat terrain (Nørrekær Enge campaign), is here tested in complex terrain.
The nacelle lidar has been deployed on a Vestas V112 turbine at the Ogorje wind farm in Croatia between June and August 2017. The data analysis has been performed with three different wind speed estimates applied to the exact same dataset:
1) the cup anemometer wind speed measurements at 2.5D (285m) upstream.
2) the nacelle lidar wind speed estimate using the wind model fitting to the measurement at 302 m upstream
3) the nacelle lidar wind speed estimate using the wind-induction model fitting to the measurement between 0.5D and 1D upstream. With the wind model, the wind speed estimate is 1.7% lower than the cup anemometer wind speed, corresponding to an overestimate of 2.2 in AEP.
With the wind-induction model, the wind speed estimate is 2.5% lower than the cup anemometer wind speed corresponding to an overestimate 3.6% in AEP. In the latter case, the reference wind speed is the cup anemometer measurements corrected using the site calibration.
The difference between the two approaches though does not seem to be due to the model and approach themselves, but rather indicate the difficulty to assess a new method by comparison to a reference with relatively high uncertainty due to the site calibration. Comparison without site calibration correction showed better agreement between the lidar wind-induction approach and the cup anemometer measurement (1.4% underestimation).
In this study, measurements from nacelle lidars close to the turbine rotor were used to estimate the free stream wind speed. Using this technique, we demonstrated that it is possible to measure a turbine’s power curve at a (moderately) complex site without the need for a site calibration.
The nacelle lidar has been deployed on a Vestas V112 turbine at the Ogorje wind farm in Croatia between June and August 2017. The data analysis has been performed with three different wind speed estimates applied to the exact same dataset:
1) the cup anemometer wind speed measurements at 2.5D (285m) upstream.
2) the nacelle lidar wind speed estimate using the wind model fitting to the measurement at 302 m upstream
3) the nacelle lidar wind speed estimate using the wind-induction model fitting to the measurement between 0.5D and 1D upstream. With the wind model, the wind speed estimate is 1.7% lower than the cup anemometer wind speed, corresponding to an overestimate of 2.2 in AEP.
With the wind-induction model, the wind speed estimate is 2.5% lower than the cup anemometer wind speed corresponding to an overestimate 3.6% in AEP. In the latter case, the reference wind speed is the cup anemometer measurements corrected using the site calibration.
The difference between the two approaches though does not seem to be due to the model and approach themselves, but rather indicate the difficulty to assess a new method by comparison to a reference with relatively high uncertainty due to the site calibration. Comparison without site calibration correction showed better agreement between the lidar wind-induction approach and the cup anemometer measurement (1.4% underestimation).
In this study, measurements from nacelle lidars close to the turbine rotor were used to estimate the free stream wind speed. Using this technique, we demonstrated that it is possible to measure a turbine’s power curve at a (moderately) complex site without the need for a site calibration.
| Original language | English |
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| Publisher | DTU Wind Energy |
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| Volume | 0157 |
| Number of pages | 64 |
| ISBN (Print) | 978-87-93549-25-8 |
| Publication status | Published - 2017 |
| Series | DTU Wind Energy E |
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| Volume | 0157 |