09:30 - 11:00 LiDARs replacing meteorological masts
Over the last five years the on and offshore wind industries have seen an increase in both acceptance of LiDAR measurements and commercial applications for LiDAR. It is through sharing the results of validation studies that uncertainties can be reduced and the full commercial value of this technology and its wide number of applications can be realized.
- Delegates will be able to describe the value of validation of floating against fixed LiDARs and defend why this practice is a suitable alternative to validation against meteorological masts
- Delegates will be able to explain why LiDAR measurements are at least as good as meteorological mast measurements
- Delegates will be able to identify two different approaches to using commercial LiDARs to measure turbulence intensity
- Delegates will be able to explain why different measurement devices have different uncertainties levels
Lead Session Chair:
Breanne Gellatly, Axys, Italy
Jonathan Chauvin (1) F Guillaume Sabiron (1) Fabrice Guillemin (1) Matthieu Boquet (2) Raghavendra Krishna Murthy (2)
(1) IFP Energies nouvelles, Rueil Malmaison, France (2) LEOSPHERE SAS , Orsay, France
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Presenter's biographyBiographies are supplied directly by presenters at EWEA 2015 and are published here unedited
Fabrice Guillemin has been working IFP Energies nouvelles during 9 years, as a research engineer in control and signal processing for transport and wind energy applications.
He is now wind turbine control project manager. He, at IFPEn, is involved in “ANR SmartEole” project realization, a collaborative experimental project including, between others, Leosphere, Maia Eolis, and Prisme laboratory. SmartEole project addresses lidar based windturbine and windfarm efficiency improvements.
He works also on ground based lidar applications, including measurements filtering and reconstruction strategies for turbulence intensity estimation.
Performance study of Lidar measurements filtering for turbulence estimation
Atmospheric turbulence impacts the wind energy industry in several ways, specifically through power performance effects, impacts on turbine loads, fatigue, and wake losses effects. Turbulence is evaluated by the turbulence intensity, calculated by dividing the standard deviation of 10 minute wind speed series by its mean wind speed. Lidar instruments are more and more present and used at wind farm project sites and its capacity to retrieve turbulence is raising more and more interest.
Ground based Lidar provide several measurements at some chosen altitude depending on the number of line of sight (LOS). On each LOS, the measurement is the wind speed projection on its LOS. Therefore, the wind speed estimation at the zenith is a combination of these measurements leading to a mean speed estimation and a challenging estimation of the turbulence intensity. The proposed approach is to study the performances of turbulence intensity estimation based on a ground-based WINDCUBE V2 Lidar. For that, wind field reconstruction and additional filtering techniques are tested to estimate the turbulence intensity estimation.
Main body of abstract
The proposed approach provides an estimation of the radial wind speed measurement for each LOS. Several parameters in the filtering process needs to be evaluated. The wind power density spectrum is used to define the various filter dynamics. Moreover, the filter is adaptive as it adapts itself to the operating conditions (wind speed, wind direction, …). Finally, a dedicated reconstruction is provided to take into account the Lidar LOS configuration and range weighting function.
Results of the proposed filtering techniques are reported on several (long term) experimental campaigns and compared to reference measuring masts. Sensitivity of the methods to measurement heights, turbulence conditions, atmospheric stability and terrain complexity (from flat sites to steeper slopes and roughness) is also studied.
A radial wind speed measurement filter approach is proposed and compared with several experimental campaigns. This is a first step in evaluating the current challenges associated with measuring the turbulence intensity from a ground-based Lidar. Further work will focus on the improvement of this technique and on the study of its sensitivity for better turbulence intensity estimation.
There are two main learning objectives. The first one is to propose a new filtering technique that is applied there on a ground-based Lidar. The second one is to show concrete results of the proposed approach, to see its sensitivity and start a reflection on the impact on the turbulence retrieval.