11th EAWE PhD Seminar on Wind Energy in Europe 23-25 September 2015 Stuttgart, Germany Session XXXX Paper XXXXXXX
Evolution of wind towards wind turbine
A. Giyanani
#1, W.A.A. M. Bierbooms
#2, G.J.W. van Bussel
#3#
Delft University of Technology, Wind Energy Research Group,
Faculty of Aerospace Engineering, Kluyverweg 1, 2629HS Delft, The Netherlands
1
a.h.giyanani@tudelft.nl
Keywords – wind evolution, remote sensing, lidar data, wind field modelling
I. ABSTRACT
Remote sensing of the atmospheric variables with the use of LiDAR is a relatively new technology field for wind resource assessment in wind energy. The validation of LiDAR measurements and comparisons is of high importance for further applications of the data.
Within the framework of Top consortium for Knowledge and Innovation Offshore Wind (TKI-WoZ), ECN initiated the LAWINE (Lidar Applications for Wind farm Efficiency) project in cooperation with XEMC Darwind, AventLidar Technology and TU Delft. Two measurement campaigns were carried out to evaluate the applications of LiDAR in wind energy. The project lays emphasis on testing and developing the LiDAR technology, wind resource and power performance assessment, optimisation of wind turbine control, load reduction and optimisation of wind farm operation.
G. I. Taylor suggested for certain cases, the turbulence might be considered to be frozen as it advects past a sensor [1]. This is particularly applicable in cases where the turbulent eddies evolve at a timescale longer than the time of eddies advection past the sensor. With Lidars, this case is invalid and the evolution of wind from far wind to the wind turbine could be studied. Bossanyi proposed a method recently to unfreeze the turbulence and performed some simulations to reduce the fatigue load reductions [2]. The model from Bossanyi is already incorporated in the recent versions of Bladed and requires further testing and improvements based on atmospheric and site conditions. Simley and Pao concluded that the error induced due to induction zone is negligible and suggested more studies replicating realistic conditions to be necessary [3]. Most of the current models lack in some or the other aspect and the trick lies in developing a model which bridges the gap between measurements and the controls of the wind turbine.
In this paper, the parameters important for unfreezing of turbulence are studied and compared using a nacelle mounted pulsed Lidar at the ECN test site as shown in Fig. 1. Wind field simulations using the different existing models and coherence functions are compared. The blockage effects along with the coherence model representing time and phase delay of the evolution wind field are modelled with the simulated wind fields. The eddy size and the life of eddies are of high importance in these studies and this is also linked to the concept of wavelet analysis [4]. Schlipf et al. found that the eddy size uptil 𝑘 = 0.128 𝑟𝑟𝑟/𝑠 satisfy the assumption of
Taylor’s frozen turbulence [5]. The parameters introduced here would be accounted for in the wind evolution model to provide deeper insight into the dynamics of the wind upwind of the turbine using the Lidar measurements.
Fig. 1 Parameters important for the wind evolution model, characteristic of Taylor’s frozen turbulence wind fields and influence of blockage effects and site dependency
The model thus developed would be tested with valid Lidar measurements and using a transfer function with range weighting included into the wind turbine control simulation. The validation of the model would be done with the help of Computational Fluid dynamics, CFD.
ACKNOWLEDGEMENTS
This work was carried out in the framework of the LAWINE project with the subsidy of the Dutch funding scheme TKI “Wind op Zee”. The following project partners are acknowledged for their contributions: ECN, the Netherlands, XEMC Darwind BV, the Netherlands and Avent Lidar Technology, France.
REFERENCES
[1] G. Taylor, “The spectrum of turbulence,” Proceedings of the Royal Society of London, Series A, Mathematical and Physical Sciences, vol. 164, no. Feb, 18, 1938, pp. 476-490, 1938
[2] E. Bossanyi, “Un-freezing the turbulence: improved wind field modelling for investigating Lidar-assisted wind turbine control,” in Proceedings of EWEA 2012, Copenhagen, Denmark, 2012
[3] E. Simley, L. Y. Pao, P. Gebraad and M. Churchfield, “Investigation of the Impact of the Upstream Induction Zone on LIDAR Measurement Accuracy for Wind Turbine Control Applications using Large-Eddy Simulation,” Journal of Physics: Conference Series, vol. 524, no. The Science of making torque from Wind, 2014, 2014.
[4] C. Torrence and G. P. Compo, “A Practical Guide to Wavelet Analysis,” Bulletin of the American Meteorological Society, vol. 79, no. 1, pp. 61-78, 1998.
[5] D. Schlipf, D. Trabucchi, O. Bischoff, M. Hofsäß et al. “Testing of frozen turbulence hypothesis for wind turbine applications with a scanning lidar system,” in 15th International Symposium for the Advancement of Boundary Layer Remote Sensing (ISARS), Paris, France, 2010.
