Delegates are invited to meet and discuss with the poster presenters during the poster presentation sessions between 10:30-11:30 and 16:00-17:00 on Thursday, 19 November 2015.
Lead Session Chair:
Stephan Barth, ForWind - Center for Wind Energy Research, Germany
Jonathan Chauvin (1) F Guillaume Sabiron (1) Guillemin Fabrice (1)
(1) IFP Energies nouvelles, Rueil Malmaison, France
Printer friendly version: Print
Presenter's biographyBiographies are supplied directly by presenters at EWEA 2015 and are published here unedited
Guillaume Sabiron received an M.Sc. degree in control theory, electronics, and computer science from Grenoble Institute of Technology, France. He obtained his Ph.D. degree from ISAE Supaero in Toulouse, France. Since 2014, he has been working as a research scientist at IFP Energies Nouvelles. His research interests are focused on Lidar based wind turbine control, wave energy converters, and eco-driving for heavy duty vehicles.
PosterDownload poster (8.37 MB)
Real time estimation of rotor-effective wind speed from turbine-mounted Lidar
One of the major issues of development of wind energy is to reduce the cost of produced energy. Advanced control system implementation is one of the levers to optimize the performance of wind turbines. Wind turbine control can be improved through the use of a turbine-mounted Lidar, which measures the wind speed at some chosen distance ahead of a wind turbine, giving advance notice of the approaching wind disturbance. Therefore, many recent control strategies use the knowledge of the incoming wind and impact of these blade pitch control laws can be measured in terms of mechanical loads on the structure.
A turbine-mounted Lidar has several line of sights (LOS) providing multiple measurements at some distance (typically 100m) of the rotor. A major difficulty for real time control is then to use these measurements for blade pitch control. Classical estimation strategies consist to delay the Lidar output by a time depending on the LOS and the mean wind speed classically justified by the Taylor frozen hypothesis. Then to recover the longitudinal speed, a simple scaling is applied to remove the influence of the projection of the wind vector over the Lidar axis. Our approach is to design real time filter that also takes the Lidar dynamics and the wind field into account.
Main body of abstract
This classical reconstruction has several drawbacks, inherent to Lidars (both continuous and pulsed). First of all, as any sensor, the measurement are noisy (typically 1 m/s). Filtering is then needed especially for the control not to be inconsistent. Moreover, rather than detecting the wind speed at only a focal distance away from the Lidar, wind speed values along the entire laser beam are averaged according to what is called the range weighting function. Therefore, when one gets a measurement at 100m for example, the Lidar gives a convolution of the wind speed values from a distance of 85m to a distance of 115m. This has a major filtering impact on the measurement and has to be taken into account to reconstruct the rotor-effective wind speed.
The proposed approach consists in an adaptive optimal filter design to estimate the rotor-effective wind speed from turbine-mounted Lidar measurement. As a Lidar provides several measurements due to several LOS, we are able to estimate the rotor-effective wind speed on several point of the plan and thus to give relevant information to the pitch controllers such as the mean wind speed but also the vertical and horizontal shear. This real time filter is a Wiener filter that “invert” the whole dynamics between the Lidar measurement and the rotor. More precisely, the delays and the range weighting function of the Lidar are taken into account while power density spectrum models and Taylor frozen hypothesis are also used to estimate the wind speed propagation and operating conditions. Simulation results are provided in several wind operating conditions (wind speed, turbulence, …) and both Lidar type (continuous-wave and pulsed) showing the relevance of dedicated filters.
Optimal filters were designed to take the measurement noise, the weighting function, and the wind field operating conditions into account. Simulations results and comparison to classical reconstructions are provided to show the interest to design dedicated filters. Further work will consist in experimental implementation and validation of such strategies.
There are two main learning objectives. The first one is to propose a new filtering technique for real time rotor-effective wind speed. The second one is to show results of the proposed approach, to see its sensitivity and start a reflection on the impact on theses technique on pitch control strategies.