Leo E. Jensen
DONG Energy
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Leo E. Jensen.
IEEE Transactions on Power Systems | 2007
Poul Ejnar Sørensen; Nicolaos Antonio Cutululis; A. Vigueras-Rodriguez; Leo E. Jensen; Jesper Hjerrild; Martin Heyman Donovan; Henrik Madsen
This paper deals with power fluctuations from wind farms. The time range in focus is between one minute and up to a couple of hours. In this time range, substantial power fluctuations have been observed during unstable weather conditions. A wind power fluctuation model is described, and measured time series from the first large offshore wind farm, Horns Rev in Denmark, are compared to simulated time series. The comparison between measured and simulated time series focuses on the ramping characteristics of the wind farm at different power levels and on the need for system generation reserves due to the fluctuations. The comparison shows a reasonable agreement between simulations and measurements, although there is still room for improvement of the simulation model.
Journal of Atmospheric and Oceanic Technology | 2010
R. J. Barthelmie; S. C. Pryor; Sten Tronæs Frandsen; Kurt Schaldemose Hansen; J.G. Schepers; K. Rados; W. Schlez; A. Neubert; Leo E. Jensen; S. Neckelmann
Abstract There is an urgent need to develop and optimize tools for designing large wind farm arrays for deployment offshore. This research is focused on improving the understanding of, and modeling of, wind turbine wakes in order to make more accurate power output predictions for large offshore wind farms. Detailed data ensembles of power losses due to wakes at the large wind farms at Nysted and Horns Rev are presented and analyzed. Differences in turbine spacing (10.5 versus 7 rotor diameters) are not differentiable in wake-related power losses from the two wind farms. This is partly due to the high variability in the data despite careful data screening. A number of ensemble averages are simulated with a range of wind farm and computational fluid dynamics models and compared to observed wake losses. All models were able to capture wake width to some degree, and some models also captured the decrease of power output moving through the wind farm. Root-mean-square errors indicate a generally better model pe...
Wind Engineering | 2009
Rajai Aghabi Rivas; Jens Clausen; Kurt Schaldemose Hansen; Leo E. Jensen
The current paper is concerned with determining the optimal layout of the turbines inside large offshore wind farms by means of an optimization algorithm. We call this the Turbine Positioning Problem. To achieve this goal a simulated annealing algorithm has been devised, where three types of local search operations are performed recursively until the system converges. The effectiveness of the proposed algorithm is demonstrated on a suite of real life test cases, including Horns Rev offshore wind farm. The results are verified using a commercial wind resource software indicating that this method represents an effective strategy for the wind turbine positioning problem. The findings enable the comparison of the optimized and the grid layouts and the study of the wake differences between these configurations. It is seen that for very large offshore wind farms the difference in wake losses is negligible while, as the wind farms size reduces, the differences start becoming significant. A sensitivity analysis is also performed showing that greater density of turbines in the perimeter of the optimized wind farm reduces the wake losses even if the wind climate changes.
48th AIAA Aerospace Sciences Meeting Including The New Horizons Forum and Aerospace Exposition | 2010
Helge Aagaard Madsen; Christian Bak; Uwe Schmidt Paulsen; Mac Gaunaa; Niels N. Sørensen; Peter Fuglsang; Jonas Romblad; A Niels; Olsen; Peder Bay Enevoldsen; Jesper Laursen; Leo E. Jensen
The paper describes the DAN-AERO MW experiments carried out within a collaborative, three years research project between Riso DTU and the industrial partners LM Glasfiber, Siemens Wind Power, Vestas Wind Systems and finally the utility company DONG Energy. The main objective of the project is to establish an experimental data base which can provide new insight into a number of fundamental aerodynamic and aeroacoustic issues, important for the design and operation of MW size turbines. The most important issue is the difference between airfoil characteristics measured under 2D, steady conditions in a wind tunnel and the unsteady 3D flow conditions on a rotor. The different transition characteristics might explain some of the difference between the 2D and 3D airfoil data and the experiments have been set up to provide data on this subject. The overall experimental approach has been to carry out a number of coordinated, innovative measurements on full scale MW size rotors as well as on airfoils for MW size turbines in wind tunnels. Shear and turbulence inflow characteristics were measured on a Siemens 3.6 MW turbine with a five hole pitot tube. Pressure and turbulent inflow characteristics were measured on a 2MW NM80 turbine with an 80 m rotor. One of the LM38.8 m blades on the rotor was replaced with a new LM38.8 m blade where instruments for surface pressure measurements at four radial sections were build into the blade during the blade production process. Additionally, the outmost section on the blade was further instrumented with around 60 microphones for high frequency surface pressure measurements. The surface
Wind Energy | 2012
Kurt Schaldemose Hansen; R. J. Barthelmie; Leo E. Jensen; Anders Sommer
Wind Energy | 2010
R. J. Barthelmie; Leo E. Jensen
Wind Energy | 2008
Poul Ejnar Sørensen; Nicolaos Antonio Cutululis; A. Vigueras-Rodriguez; Henrik Madsen; Pierre Pinson; Leo E. Jensen; Jesper Hjerrild; Martin Heyman Donovan
Journal of Wind Engineering and Industrial Aerodynamics | 2008
Pierre Pinson; Lasse K. Christensen; Henrik Madsen; Poul Ejnar Sørensen; Martin Heyman Donovan; Leo E. Jensen
Wind Energy | 2009
Sten Tronæs Frandsen; Hans Ejsing Jørgensen; R. J. Barthelmie; Ole Rathmann; Jake Badger; Kurt Schaldemose Hansen; Søren Ott; Pierre-Elouan Réthoré; Søren Ejling Larsen; Leo E. Jensen
Wind Energy | 2009
Jochen Cleve; Martin Greiner; Peder Bay Enevoldsen; Bo Birkemose; Leo E. Jensen